From d27d1e26273ddeaa1a8e34efe2f6e00b5351717a Mon Sep 17 00:00:00 2001
From: Andrews Sobral <andrewssobral@gmail.com>
Date: Sat, 18 Mar 2017 18:40:18 +0100
Subject: [PATCH] BGSLibrary 2.0.0
---
.gitignore | 6 +-
CMakeLists.txt | 103 +-
Demo.cpp | 158 +-
Demo.py | 84 +
Demo2.cpp | 139 +-
FrameProcessor.cpp | 452 ++---
FrameProcessor.h | 207 +--
Main.cpp | 2 +-
PreProcessor.cpp | 2 +-
PreProcessor.h | 1 -
README.md | 9 +-
VideoAnalysis.cpp | 76 +-
VideoCapture.cpp | 58 +-
VideoCapture.h | 5 +-
config/FrameProcessor.xml | 39 +-
dataset/demo.avi | Bin 0 -> 355840 bytes
{frames => dataset/frames}/1.png | Bin
{frames => dataset/frames}/10.png | Bin
{frames => dataset/frames}/11.png | Bin
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{frames => dataset/frames}/6.png | Bin
{frames => dataset/frames}/7.png | Bin
{frames => dataset/frames}/8.png | Bin
{frames => dataset/frames}/9.png | Bin
demos/DemoFrameDifferenceBGS.cpp | 49 -
demos/DemoMultiLayerBGS.cpp | 49 -
demos/linux_ubuntu/.gitignore | 8 +
.../linux_ubuntu}/CMakeLists.txt | 7 +-
.../linux_ubuntu}/FrameDifferenceTest.cpp | 6 +-
.../linux_ubuntu}/README.txt | 0
demos/linux_ubuntu/config/.gitignore | 4 +
demos/macosx/.gitignore | 8 +
.../macosx}/CMakeLists.txt | 7 +-
.../macosx}/FrameDifferenceTest.cpp | 6 +-
{example_macosx => demos/macosx}/README.txt | 0
demos/macosx/config/.gitignore | 4 +
.../README_CMAKE_USERS_OPENCV2.txt | 39 +-
docs/README_CMAKE_USERS_OPENCV3.txt | 77 +
.../README_LINUX_USERS.txt | 5 +-
.../README_VS2010_OPENCV2.txt | 13 +-
example_linux/config/KEEP_THIS_FOLDER | 1 -
example_macosx/config/KEEP_THIS_FOLDER | 1 -
{java_gui => gui_java}/README.txt | 0
.../_COPY_bgslibrary.exe_HERE_ | 0
{java_gui => gui_java}/bgslibrary_gui.jar | Bin
.../bgslibrary_gui.properties | 0
{java_gui => gui_java}/build.xml | 0
{java_gui => gui_java}/config/.gitignore | 0
.../config/FrameProcessor.xml | 0
.../config/PreProcessor.xml | 0
.../config/VideoCapture.xml | 0
.../images/bgslibrary_gui_screen01.png | Bin
.../images/bgslibrary_gui_screen02.png | Bin
.../images/bgslibrary_gui_screen03.png | Bin
.../images/bgslibrary_gui_screen04.png | Bin
{java_gui => gui_java}/images/logo.jpg | Bin
.../lib/commons-configuration-1.8.jar | Bin
{java_gui => gui_java}/lib/commons-io-2.3.jar | Bin
.../lib/commons-lang-2.6.jar | Bin
.../lib/commons-logging-1.1.1.jar | Bin
.../lib/swingx-all-1.6.3.jar | Bin
.../lib/swingx-beaninfo-1.6.3.jar | Bin
{java_gui => gui_java}/manifest.mf | 0
.../nbproject/build-impl.xml | 0
.../nbproject/genfiles.properties | 0
.../nbproject/private/config.properties | 0
.../nbproject/private/private.properties | 0
.../nbproject/private/private.xml | 0
.../nbproject/project.properties | 0
{java_gui => gui_java}/nbproject/project.xml | 0
{java_gui => gui_java}/run_camera.bat | 0
{java_gui => gui_java}/run_java_gui.bat | 0
.../run_java_gui_with_console.bat | 0
{java_gui => gui_java}/run_video.bat | 0
.../src/br/com/bgslibrary/Main.java | 0
.../src/br/com/bgslibrary/entity/Command.java | 0
.../com/bgslibrary/entity/Configuration.java | 0
.../br/com/bgslibrary/gui/AboutDialog.form | 0
.../br/com/bgslibrary/gui/AboutDialog.java | 0
.../src/br/com/bgslibrary/gui/MainFrame.form | 0
.../src/br/com/bgslibrary/gui/MainFrame.java | 0
.../src/br/com/bgslibrary/resources/logo.jpg | Bin
{vs2010mfc => gui_mfc}/.gitignore | 0
{vs2013mfc => gui_mfc}/ReadMe.txt | 0
.../config/AdaptiveBackgroundLearning.xml | 0
.../AdaptiveSelectiveBackgroundLearning.xml | 0
.../config/DPAdaptiveMedianBGS.xml | 0
.../config/DPEigenbackgroundBGS.xml | 0
.../config/DPGrimsonGMMBGS.xml | 0
{vs2010mfc => gui_mfc}/config/DPMeanBGS.xml | 0
.../config/DPPratiMediodBGS.xml | 0
.../config/DPTextureBGS.xml | 0
{vs2010mfc => gui_mfc}/config/DPWrenGABGS.xml | 0
.../config/DPZivkovicAGMMBGS.xml | 0
.../config/FrameDifferenceBGS.xml | 0
.../config/FuzzyChoquetIntegral.xml | 0
.../config/FuzzySugenoIntegral.xml | 0
{vs2010mfc => gui_mfc}/config/GMG.xml | 0
.../config/IndependentMultimodalBGS.xml | 0
{vs2010mfc => gui_mfc}/config/KDE.xml | 0
.../config/LBAdaptiveSOM.xml | 0
.../config/LBFuzzyAdaptiveSOM.xml | 0
.../config/LBFuzzyGaussian.xml | 0
.../config/LBMixtureOfGaussians.xml | 0
.../config/LBSimpleGaussian.xml | 0
{vs2010mfc => gui_mfc}/config/LOBSTERBGS.xml | 0
.../config/MixtureOfGaussianV1BGS.xml | 0
.../config/MixtureOfGaussianV2BGS.xml | 0
{vs2010mfc => gui_mfc}/config/MultiCueBGS.xml | 0
.../config/MultiLayerBGS.xml | 0
.../config/SigmaDeltaBGS.xml | 0
.../config/StaticFrameDifferenceBGS.xml | 0
{vs2010mfc => gui_mfc}/config/SuBSENSEBGS.xml | 0
{vs2010mfc => gui_mfc}/config/T2FGMM_UM.xml | 0
{vs2010mfc => gui_mfc}/config/T2FGMM_UV.xml | 0
{vs2010mfc => gui_mfc}/config/T2FMRF_UM.xml | 0
{vs2010mfc => gui_mfc}/config/T2FMRF_UV.xml | 0
{vs2010mfc => gui_mfc}/config/VuMeter.xml | 0
.../config/WeightedMovingMeanBGS.xml | 0
.../config/WeightedMovingVarianceBGS.xml | 0
{vs2010mfc => gui_mfc}/dataset/video.avi | Bin
.../outputs/background/.gitignore | 0
.../outputs/foreground/.gitignore | 0
.../outputs/input/.gitignore | 0
{vs2010mfc => gui_mfc}/src/.gitignore | 0
{vs2010mfc => gui_mfc}/src/App.cpp | 0
{vs2010mfc => gui_mfc}/src/App.h | 0
{vs2010mfc => gui_mfc}/src/Dlg.cpp | 0
{vs2010mfc => gui_mfc}/src/Dlg.h | 0
{vs2013mfc => gui_mfc}/src/ReadMe.txt | 0
.../src/bgslibrary_vs2013_mfc.rc | Bin
.../src/bgslibrary_vs2013_mfc.sln | 0
.../src/bgslibrary_vs2013_mfc.vcxproj | 0
.../src/bgslibrary_vs2013_mfc.vcxproj.filters | 0
.../src/bgslibrary_vs2013_mfc.vcxproj.user | 0
.../src/res/bgslibrary_vs2013_mfc.ico | Bin
.../src/res/bgslibrary_vs2013_mfc.rc2 | Bin
{vs2010mfc => gui_mfc}/src/resource.h | Bin
{vs2010mfc => gui_mfc}/src/stdafx.cpp | 0
{vs2010mfc => gui_mfc}/src/stdafx.h | 0
{vs2010mfc => gui_mfc}/src/targetver.h | 0
gui_qt/.gitignore | 9 +
gui_qt/CMakeLists.txt | 52 +
gui_qt/README.txt | 17 +
gui_qt/application.qrc | 10 +
gui_qt/bgslibrary_gui.cpp | 38 +
gui_qt/bgslibrary_gui.pro | 248 +++
gui_qt/build/.gitignore | 4 +
gui_qt/figs/copy.png | Bin 0 -> 1338 bytes
gui_qt/figs/cut.png | Bin 0 -> 1323 bytes
gui_qt/figs/new.png | Bin 0 -> 852 bytes
gui_qt/figs/open.png | Bin 0 -> 2073 bytes
gui_qt/figs/paste.png | Bin 0 -> 1645 bytes
gui_qt/figs/save.png | Bin 0 -> 1187 bytes
gui_qt/mainwindow.cpp | 571 ++++++
gui_qt/mainwindow.h | 110 ++
gui_qt/mainwindow.ui | 631 +++++++
gui_qt/qt_utils.cpp | 74 +
gui_qt/qt_utils.h | 99 ++
gui_qt/texteditor.cpp | 320 ++++
gui_qt/texteditor.h | 64 +
gui_qt/ui_mainwindow.h | 306 ++++
output/bg/.gitignore | 4 +
output/fg/.gitignore | 4 +
output/in/.gitignore | 4 +
.../PerformanceUtils.cpp | 259 +--
.../PerformanceUtils.h | 16 +-
package_analysis/PixelUtils.cpp | 351 ++++
.../tb => package_analysis}/PixelUtils.h | 18 +-
package_bgs/AdaptiveBackgroundLearning.cpp | 72 +-
package_bgs/AdaptiveBackgroundLearning.h | 55 +-
.../AdaptiveSelectiveBackgroundLearning.cpp | 53 +-
.../AdaptiveSelectiveBackgroundLearning.h | 54 +-
package_bgs/DPAdaptiveMedian.cpp | 110 ++
package_bgs/DPAdaptiveMedian.h | 53 +
...ackgroundBGS.cpp => DPEigenbackground.cpp} | 67 +-
package_bgs/DPEigenbackground.h | 55 +
.../DPGrimsonGMMBGS.cpp => DPGrimsonGMM.cpp} | 69 +-
.../DPEigenbackgroundBGS.h => DPGrimsonGMM.h} | 67 +-
package_bgs/{dp/DPMeanBGS.cpp => DPMean.cpp} | 67 +-
.../{dp/DPZivkovicAGMMBGS.h => DPMean.h} | 67 +-
...DPPratiMediodBGS.cpp => DPPratiMediod.cpp} | 75 +-
.../{dp/DPMeanBGS.h => DPPratiMediod.h} | 68 +-
.../{dp/DPTextureBGS.cpp => DPTexture.cpp} | 91 +-
package_bgs/DPTexture.h | 59 +
.../{dp/DPWrenGABGS.cpp => DPWrenGA.cpp} | 70 +-
package_bgs/{dp/DPWrenGABGS.h => DPWrenGA.h} | 67 +-
...ZivkovicAGMMBGS.cpp => DPZivkovicAGMM.cpp} | 69 +-
.../DPGrimsonGMMBGS.h => DPZivkovicAGMM.h} | 67 +-
package_bgs/FrameDifference.cpp | 84 +
...FrameDifferenceBGS.h => FrameDifference.h} | 45 +-
package_bgs/FrameDifferenceBGS.cpp | 83 -
package_bgs/{tb => }/FuzzyChoquetIntegral.cpp | 127 +-
package_bgs/FuzzyChoquetIntegral.h | 53 +
package_bgs/{tb => }/FuzzySugenoIntegral.cpp | 133 +-
package_bgs/FuzzySugenoIntegral.h | 53 +
package_bgs/GMG.cpp | 49 +-
package_bgs/GMG.h | 50 +-
package_bgs/IBGS.h | 63 +-
package_bgs/{db/imbs.cpp => IMBS/IMBS.cpp} | 254 +--
package_bgs/{db/imbs.hpp => IMBS/IMBS.hpp} | 62 +-
package_bgs/IndependentMultimodal.cpp | 74 +
...ifferenceBGS.h => IndependentMultimodal.h} | 46 +-
package_bgs/{ae => }/KDE.cpp | 83 +-
package_bgs/KDE.h | 57 +
package_bgs/{ae => KDE}/KernelTable.cpp | 48 +-
package_bgs/{ae => KDE}/KernelTable.h | 22 +-
package_bgs/KDE/NPBGSubtractor.cpp | 1160 ++++++++++++
package_bgs/{ae => KDE}/NPBGSubtractor.h | 26 +-
package_bgs/{ae => KDE}/NPBGmodel.cpp | 42 +-
package_bgs/{ae => KDE}/NPBGmodel.h | 28 +-
package_bgs/KNN.cpp | 111 ++
package_bgs/KNN.h | 57 +
package_bgs/{lb => }/LBAdaptiveSOM.cpp | 67 +-
package_bgs/{lb => }/LBAdaptiveSOM.h | 60 +-
package_bgs/{lb => }/LBFuzzyAdaptiveSOM.cpp | 69 +-
package_bgs/{lb => }/LBFuzzyAdaptiveSOM.h | 60 +-
package_bgs/{lb => }/LBFuzzyGaussian.cpp | 66 +-
package_bgs/{lb => }/LBFuzzyGaussian.h | 58 +-
package_bgs/{lb => }/LBMixtureOfGaussians.cpp | 68 +-
package_bgs/{lb => }/LBMixtureOfGaussians.h | 59 +-
package_bgs/{ck/LbpMrf.cpp => LBP_MRF.cpp} | 55 +-
.../{WeightedMovingMeanBGS.h => LBP_MRF.h} | 48 +-
package_bgs/LBP_MRF/MEDefs.cpp | 57 +
package_bgs/{ck => LBP_MRF}/MEDefs.hpp | 29 +-
package_bgs/{ck => LBP_MRF}/MEHistogram.cpp | 305 ++--
package_bgs/{ck => LBP_MRF}/MEHistogram.hpp | 30 +-
package_bgs/{ck => LBP_MRF}/MEImage.cpp | 963 +++++-----
package_bgs/{ck => LBP_MRF}/MEImage.hpp | 38 +-
.../{ck => LBP_MRF}/MotionDetection.cpp | 126 +-
.../{ck => LBP_MRF}/MotionDetection.hpp | 32 +-
package_bgs/{ck => LBP_MRF}/block.h | 268 +--
package_bgs/{ck => LBP_MRF}/graph.cpp | 18 +-
package_bgs/{ck => LBP_MRF}/graph.h | 105 +-
package_bgs/{ck => LBP_MRF}/maxflow.cpp | 260 +--
package_bgs/LBSP/BackgroundSubtractorLBSP.cpp | 85 +
package_bgs/LBSP/BackgroundSubtractorLBSP.h | 101 ++
.../LBSP/BackgroundSubtractorLBSP_.cpp | 79 +
package_bgs/LBSP/BackgroundSubtractorLBSP_.h | 107 ++
.../LBSP/BackgroundSubtractorLOBSTER.cpp | 342 ++++
.../LBSP/BackgroundSubtractorLOBSTER.h | 83 +
.../LBSP/BackgroundSubtractorPAWCS.cpp | 1349 ++++++++++++++
package_bgs/LBSP/BackgroundSubtractorPAWCS.h | 169 ++
.../LBSP/BackgroundSubtractorSuBSENSE.cpp | 753 ++++++++
.../LBSP/BackgroundSubtractorSuBSENSE.h | 129 ++
package_bgs/LBSP/DistanceUtils.h | 332 ++++
package_bgs/LBSP/LBSP.cpp | 334 ++++
package_bgs/LBSP/LBSP.h | 134 ++
package_bgs/LBSP/LBSP_.cpp | 334 ++++
package_bgs/LBSP/LBSP_.h | 134 ++
.../{pl => LBSP}/LBSP_16bits_dbcross_1ch.i | 0
.../{pl => LBSP}/LBSP_16bits_dbcross_3ch1t.i | 0
.../{pl => LBSP}/LBSP_16bits_dbcross_3ch3t.i | 0
.../{pl => LBSP}/LBSP_16bits_dbcross_s3ch.i | 0
package_bgs/LBSP/RandUtils.h | 112 ++
package_bgs/{lb => }/LBSimpleGaussian.cpp | 62 +-
package_bgs/{lb => }/LBSimpleGaussian.h | 56 +-
package_bgs/LOBSTER.cpp | 98 ++
package_bgs/LOBSTER.h | 49 +
...ssianV1BGS.cpp => MixtureOfGaussianV1.cpp} | 69 +-
...fGaussianV1BGS.h => MixtureOfGaussianV1.h} | 50 +-
...ssianV2BGS.cpp => MixtureOfGaussianV2.cpp} | 73 +-
...fGaussianV2BGS.h => MixtureOfGaussianV2.h} | 49 +-
.../{sjn/SJN_MultiCueBGS.cpp => MultiCue.cpp} | 587 ++++---
package_bgs/MultiCue.h | 254 +++
.../{jmo/MultiLayerBGS.cpp => MultiLayer.cpp} | 133 +-
package_bgs/MultiLayer.h | 99 ++
package_bgs/{jmo => MultiLayer}/BGS.h | 8 +-
.../BackgroundSubtractionAPI.h | 39 +-
.../{jmo => MultiLayer}/BlobExtraction.cpp | 194 +-
.../{jmo => MultiLayer}/BlobExtraction.h | 8 +-
.../BlobLibraryConfiguration.h | 5 +-
package_bgs/MultiLayer/BlobResult.cpp | 847 +++++++++
package_bgs/{jmo => MultiLayer}/BlobResult.h | 60 +-
.../{jmo => MultiLayer}/CMultiLayerBGS.cpp | 28 +-
.../{jmo => MultiLayer}/CMultiLayerBGS.h | 27 +-
.../LocalBinaryPattern.cpp | 16 +-
.../{jmo => MultiLayer}/LocalBinaryPattern.h | 9 +-
.../OpenCvDataConversion.h | 9 +-
package_bgs/MultiLayer/OpenCvLegacyIncludes.h | 50 +
package_bgs/MultiLayer/blob.cpp | 1148 ++++++++++++
package_bgs/{jmo => MultiLayer}/blob.h | 120 +-
package_bgs/PAWCS.cpp | 93 +
package_bgs/PAWCS.h | 48 +
package_bgs/PBAS/PBAS.cpp | 585 +++++++
package_bgs/PBAS/PBAS.h | 207 +++
package_bgs/PixelBasedAdaptiveSegmenter.cpp | 126 ++
package_bgs/PixelBasedAdaptiveSegmenter.h | 58 +
package_bgs/SigmaDelta.cpp | 101 ++
package_bgs/SigmaDelta.h | 49 +
package_bgs/{bl => SigmaDelta}/sdLaMa091.cpp | 84 +-
package_bgs/{bl => SigmaDelta}/sdLaMa091.h | 6 +-
...renceBGS.cpp => StaticFrameDifference.cpp} | 52 +-
package_bgs/StaticFrameDifference.h | 42 +
package_bgs/SuBSENSE.cpp | 96 +
package_bgs/SuBSENSE.h | 49 +
package_bgs/T2F/FuzzyUtils.cpp | 512 ++++++
package_bgs/{tb => T2F}/FuzzyUtils.h | 15 +-
package_bgs/{tb => T2F}/MRF.cpp | 156 +-
package_bgs/{tb => T2F}/MRF.h | 11 +-
package_bgs/{tb => T2F}/T2FGMM.cpp | 134 +-
package_bgs/{tb => T2F}/T2FGMM.h | 26 +-
package_bgs/{tb => T2F}/T2FMRF.cpp | 154 +-
package_bgs/{tb => T2F}/T2FMRF.h | 30 +-
package_bgs/{tb => }/T2FGMM_UM.cpp | 60 +-
package_bgs/{tb => }/T2FGMM_UM.h | 71 +-
package_bgs/{tb => }/T2FGMM_UV.cpp | 60 +-
package_bgs/{tb => }/T2FGMM_UV.h | 71 +-
package_bgs/{tb => }/T2FMRF_UM.cpp | 91 +-
package_bgs/T2FMRF_UM.h | 64 +
package_bgs/{tb => }/T2FMRF_UV.cpp | 91 +-
package_bgs/T2FMRF_UV.h | 64 +
package_bgs/TwoPoints.cpp | 112 ++
package_bgs/TwoPoints.h | 46 +
package_bgs/TwoPoints/two_points.cpp | 394 +++++
package_bgs/TwoPoints/two_points.h | 50 +
package_bgs/ViBe.cpp | 98 ++
package_bgs/ViBe.h | 52 +
package_bgs/ViBe/LICENSE | 44 +
.../ViBe/vibe-background-sequential.cpp | 929 ++++++++++
package_bgs/ViBe/vibe-background-sequential.h | 293 ++++
package_bgs/{av => }/VuMeter.cpp | 79 +-
package_bgs/VuMeter.h | 52 +
package_bgs/{av => VuMeter}/TBackground.cpp | 36 +-
package_bgs/{av => VuMeter}/TBackground.h | 1 -
.../{av => VuMeter}/TBackgroundVuMeter.cpp | 132 +-
.../{av => VuMeter}/TBackgroundVuMeter.h | 6 +-
...vingMeanBGS.cpp => WeightedMovingMean.cpp} | 85 +-
package_bgs/WeightedMovingMean.h | 45 +
...anceBGS.cpp => WeightedMovingVariance.cpp} | 99 +-
package_bgs/WeightedMovingVariance.h | 46 +
package_bgs/WeightedMovingVarianceBGS.h | 48 -
package_bgs/_template_/Amber.cpp | 112 ++
package_bgs/_template_/Amber.h | 45 +
package_bgs/_template_/MyBGS.cpp | 44 +
.../{ck/LbpMrf.h => _template_/MyBGS.h} | 41 +-
package_bgs/_template_/amber/amber.c | 80 +
package_bgs/_template_/amber/amber.h | 64 +
package_bgs/ae/KDE.h | 58 -
package_bgs/ae/NPBGSubtractor.cpp | 1160 ------------
package_bgs/av/VuMeter.h | 53 -
package_bgs/bgslibrary.h | 65 +
package_bgs/bl/SigmaDeltaBGS.cpp | 85 -
package_bgs/bl/SigmaDeltaBGS.h | 42 -
package_bgs/bl/stdbool.h | 16 -
package_bgs/ck/MEDefs.cpp | 40 -
package_bgs/ck/README.TXT | 135 --
package_bgs/db/IndependentMultimodalBGS.cpp | 54 -
package_bgs/db/IndependentMultimodalBGS.h | 29 -
package_bgs/dp/AdaptiveMedianBGS.cpp | 148 +-
package_bgs/dp/AdaptiveMedianBGS.h | 89 +-
package_bgs/dp/Bgs.h | 54 +-
package_bgs/dp/BgsParams.h | 54 +-
package_bgs/dp/DPAdaptiveMedianBGS.cpp | 113 --
package_bgs/dp/DPAdaptiveMedianBGS.h | 56 -
package_bgs/dp/DPPratiMediodBGS.h | 57 -
package_bgs/dp/DPTextureBGS.h | 60 -
package_bgs/dp/Eigenbackground.cpp | 260 +--
package_bgs/dp/Eigenbackground.h | 18 +-
package_bgs/dp/Error.h | 7 +-
package_bgs/dp/GrimsonGMM.cpp | 486 +++---
package_bgs/dp/GrimsonGMM.h | 206 ++-
package_bgs/dp/Image.cpp | 42 +-
package_bgs/dp/Image.h | 126 +-
package_bgs/dp/MeanBGS.cpp | 150 +-
package_bgs/dp/MeanBGS.h | 22 +-
package_bgs/dp/PratiMediodBGS.cpp | 380 ++--
package_bgs/dp/PratiMediodBGS.h | 36 +-
package_bgs/dp/TextureBGS.cpp | 96 +-
package_bgs/dp/TextureBGS.h | 12 +-
package_bgs/dp/WrenGA.cpp | 210 +--
package_bgs/dp/WrenGA.h | 30 +-
package_bgs/dp/ZivkovicAGMM.cpp | 656 +++----
package_bgs/dp/ZivkovicAGMM.h | 46 +-
package_bgs/jmo/BlobResult.cpp | 847 ---------
package_bgs/jmo/MultiLayerBGS.h | 101 --
package_bgs/jmo/blob.cpp | 1149 ------------
package_bgs/lb/BGModel.cpp | 24 +-
package_bgs/lb/BGModel.h | 16 +-
package_bgs/lb/BGModelFuzzyGauss.cpp | 60 +-
package_bgs/lb/BGModelFuzzyGauss.h | 8 +-
package_bgs/lb/BGModelFuzzySom.cpp | 112 +-
package_bgs/lb/BGModelFuzzySom.h | 14 +-
package_bgs/lb/BGModelGauss.cpp | 64 +-
package_bgs/lb/BGModelGauss.h | 8 +-
package_bgs/lb/BGModelMog.cpp | 94 +-
package_bgs/lb/BGModelMog.h | 8 +-
package_bgs/lb/BGModelSom.cpp | 120 +-
package_bgs/lb/BGModelSom.h | 14 +-
package_bgs/lb/Types.h | 88 +-
package_bgs/my/MyBGS.cpp | 26 -
package_bgs/my/MyBGS.h | 22 -
package_bgs/pl/BackgroundSubtractorLBSP.cpp | 69 -
package_bgs/pl/BackgroundSubtractorLBSP.h | 85 -
.../pl/BackgroundSubtractorLOBSTER.cpp | 326 ----
package_bgs/pl/BackgroundSubtractorLOBSTER.h | 67 -
.../pl/BackgroundSubtractorSuBSENSE.cpp | 737 --------
package_bgs/pl/BackgroundSubtractorSuBSENSE.h | 113 --
package_bgs/pl/DistanceUtils.h | 316 ----
package_bgs/pl/LBSP.cpp | 318 ----
package_bgs/pl/LBSP.h | 118 --
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package_bgs/pl/RandUtils.h | 96 -
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.../backgroundSubtractor_wrapper.cpp | 395 +++++
wrapper_matlab/compile.m | 94 +
wrapper_matlab/config/.gitignore | 4 +
wrapper_matlab/demo.m | 65 +
wrapper_matlab/mxarray.h | 1555 +++++++++++++++++
wrapper_matlab/mxtypes.h | 345 ++++
wrapper_matlab/run_demo.m | 49 +
wrapper_python/bgslibrary_module.cpp | 265 +++
wrapper_python/np_opencv_converter.cpp | 103 ++
wrapper_python/np_opencv_converter.h | 122 ++
wrapper_python/utils/container.h | 208 +++
wrapper_python/utils/conversion.cpp | 349 ++++
wrapper_python/utils/conversion.h | 75 +
wrapper_python/utils/template.h | 44 +
551 files changed, 27350 insertions(+), 21312 deletions(-)
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create mode 100644 package_bgs/LBSP/DistanceUtils.h
create mode 100644 package_bgs/LBSP/LBSP.cpp
create mode 100644 package_bgs/LBSP/LBSP.h
create mode 100644 package_bgs/LBSP/LBSP_.cpp
create mode 100644 package_bgs/LBSP/LBSP_.h
rename package_bgs/{pl => LBSP}/LBSP_16bits_dbcross_1ch.i (100%)
rename package_bgs/{pl => LBSP}/LBSP_16bits_dbcross_3ch1t.i (100%)
rename package_bgs/{pl => LBSP}/LBSP_16bits_dbcross_3ch3t.i (100%)
rename package_bgs/{pl => LBSP}/LBSP_16bits_dbcross_s3ch.i (100%)
create mode 100644 package_bgs/LBSP/RandUtils.h
rename package_bgs/{lb => }/LBSimpleGaussian.cpp (61%)
rename package_bgs/{lb => }/LBSimpleGaussian.h (57%)
create mode 100644 package_bgs/LOBSTER.cpp
create mode 100644 package_bgs/LOBSTER.h
rename package_bgs/{MixtureOfGaussianV1BGS.cpp => MixtureOfGaussianV1.cpp} (53%)
rename package_bgs/{MixtureOfGaussianV1BGS.h => MixtureOfGaussianV1.h} (59%)
rename package_bgs/{MixtureOfGaussianV2BGS.cpp => MixtureOfGaussianV2.cpp} (60%)
rename package_bgs/{MixtureOfGaussianV2BGS.h => MixtureOfGaussianV2.h} (57%)
rename package_bgs/{sjn/SJN_MultiCueBGS.cpp => MultiCue.cpp} (83%)
create mode 100644 package_bgs/MultiCue.h
rename package_bgs/{jmo/MultiLayerBGS.cpp => MultiLayer.cpp} (65%)
create mode 100644 package_bgs/MultiLayer.h
rename package_bgs/{jmo => MultiLayer}/BGS.h (98%)
rename package_bgs/{jmo => MultiLayer}/BackgroundSubtractionAPI.h (89%)
rename package_bgs/{jmo => MultiLayer}/BlobExtraction.cpp (91%)
rename package_bgs/{jmo => MultiLayer}/BlobExtraction.h (96%)
rename package_bgs/{jmo => MultiLayer}/BlobLibraryConfiguration.h (95%)
create mode 100644 package_bgs/MultiLayer/BlobResult.cpp
rename package_bgs/{jmo => MultiLayer}/BlobResult.h (80%)
rename package_bgs/{jmo => MultiLayer}/CMultiLayerBGS.cpp (99%)
rename package_bgs/{jmo => MultiLayer}/CMultiLayerBGS.h (96%)
rename package_bgs/{jmo => MultiLayer}/LocalBinaryPattern.cpp (95%)
rename package_bgs/{jmo => MultiLayer}/LocalBinaryPattern.h (96%)
rename package_bgs/{jmo => MultiLayer}/OpenCvDataConversion.h (97%)
create mode 100644 package_bgs/MultiLayer/OpenCvLegacyIncludes.h
create mode 100644 package_bgs/MultiLayer/blob.cpp
rename package_bgs/{jmo => MultiLayer}/blob.h (87%)
create mode 100644 package_bgs/PAWCS.cpp
create mode 100644 package_bgs/PAWCS.h
create mode 100644 package_bgs/PBAS/PBAS.cpp
create mode 100644 package_bgs/PBAS/PBAS.h
create mode 100644 package_bgs/PixelBasedAdaptiveSegmenter.cpp
create mode 100644 package_bgs/PixelBasedAdaptiveSegmenter.h
create mode 100644 package_bgs/SigmaDelta.cpp
create mode 100644 package_bgs/SigmaDelta.h
rename package_bgs/{bl => SigmaDelta}/sdLaMa091.cpp (97%)
rename package_bgs/{bl => SigmaDelta}/sdLaMa091.h (96%)
rename package_bgs/{StaticFrameDifferenceBGS.cpp => StaticFrameDifference.cpp} (53%)
create mode 100644 package_bgs/StaticFrameDifference.h
create mode 100644 package_bgs/SuBSENSE.cpp
create mode 100644 package_bgs/SuBSENSE.h
create mode 100644 package_bgs/T2F/FuzzyUtils.cpp
rename package_bgs/{tb => T2F}/FuzzyUtils.h (86%)
rename package_bgs/{tb => T2F}/MRF.cpp (58%)
rename package_bgs/{tb => T2F}/MRF.h (95%)
rename package_bgs/{tb => T2F}/T2FGMM.cpp (69%)
rename package_bgs/{tb => T2F}/T2FGMM.h (92%)
rename package_bgs/{tb => T2F}/T2FMRF.cpp (70%)
rename package_bgs/{tb => T2F}/T2FMRF.h (91%)
rename package_bgs/{tb => }/T2FGMM_UM.cpp (64%)
rename package_bgs/{tb => }/T2FGMM_UM.h (52%)
rename package_bgs/{tb => }/T2FGMM_UV.cpp (64%)
rename package_bgs/{tb => }/T2FGMM_UV.h (52%)
rename package_bgs/{tb => }/T2FMRF_UM.cpp (59%)
create mode 100644 package_bgs/T2FMRF_UM.h
rename package_bgs/{tb => }/T2FMRF_UV.cpp (59%)
create mode 100644 package_bgs/T2FMRF_UV.h
create mode 100644 package_bgs/TwoPoints.cpp
create mode 100644 package_bgs/TwoPoints.h
create mode 100644 package_bgs/TwoPoints/two_points.cpp
create mode 100644 package_bgs/TwoPoints/two_points.h
create mode 100644 package_bgs/ViBe.cpp
create mode 100644 package_bgs/ViBe.h
create mode 100644 package_bgs/ViBe/LICENSE
create mode 100644 package_bgs/ViBe/vibe-background-sequential.cpp
create mode 100644 package_bgs/ViBe/vibe-background-sequential.h
rename package_bgs/{av => }/VuMeter.cpp (52%)
create mode 100644 package_bgs/VuMeter.h
rename package_bgs/{av => VuMeter}/TBackground.cpp (77%)
rename package_bgs/{av => VuMeter}/TBackground.h (99%)
rename package_bgs/{av => VuMeter}/TBackgroundVuMeter.cpp (74%)
rename package_bgs/{av => VuMeter}/TBackgroundVuMeter.h (95%)
rename package_bgs/{WeightedMovingMeanBGS.cpp => WeightedMovingMean.cpp} (51%)
create mode 100644 package_bgs/WeightedMovingMean.h
rename package_bgs/{WeightedMovingVarianceBGS.cpp => WeightedMovingVariance.cpp} (62%)
create mode 100644 package_bgs/WeightedMovingVariance.h
delete mode 100644 package_bgs/WeightedMovingVarianceBGS.h
create mode 100644 package_bgs/_template_/Amber.cpp
create mode 100644 package_bgs/_template_/Amber.h
create mode 100644 package_bgs/_template_/MyBGS.cpp
rename package_bgs/{ck/LbpMrf.h => _template_/MyBGS.h} (65%)
create mode 100644 package_bgs/_template_/amber/amber.c
create mode 100644 package_bgs/_template_/amber/amber.h
delete mode 100644 package_bgs/ae/KDE.h
delete mode 100644 package_bgs/ae/NPBGSubtractor.cpp
delete mode 100644 package_bgs/av/VuMeter.h
create mode 100644 package_bgs/bgslibrary.h
delete mode 100644 package_bgs/bl/SigmaDeltaBGS.cpp
delete mode 100644 package_bgs/bl/SigmaDeltaBGS.h
delete mode 100644 package_bgs/bl/stdbool.h
delete mode 100644 package_bgs/ck/MEDefs.cpp
delete mode 100644 package_bgs/ck/README.TXT
delete mode 100644 package_bgs/db/IndependentMultimodalBGS.cpp
delete mode 100644 package_bgs/db/IndependentMultimodalBGS.h
delete mode 100644 package_bgs/dp/DPAdaptiveMedianBGS.cpp
delete mode 100644 package_bgs/dp/DPAdaptiveMedianBGS.h
delete mode 100644 package_bgs/dp/DPPratiMediodBGS.h
delete mode 100644 package_bgs/dp/DPTextureBGS.h
delete mode 100644 package_bgs/jmo/BlobResult.cpp
delete mode 100644 package_bgs/jmo/MultiLayerBGS.h
delete mode 100644 package_bgs/jmo/blob.cpp
delete mode 100644 package_bgs/my/MyBGS.cpp
delete mode 100644 package_bgs/my/MyBGS.h
delete mode 100644 package_bgs/pl/BackgroundSubtractorLBSP.cpp
delete mode 100644 package_bgs/pl/BackgroundSubtractorLBSP.h
delete mode 100644 package_bgs/pl/BackgroundSubtractorLOBSTER.cpp
delete mode 100644 package_bgs/pl/BackgroundSubtractorLOBSTER.h
delete mode 100644 package_bgs/pl/BackgroundSubtractorSuBSENSE.cpp
delete mode 100644 package_bgs/pl/BackgroundSubtractorSuBSENSE.h
delete mode 100644 package_bgs/pl/DistanceUtils.h
delete mode 100644 package_bgs/pl/LBSP.cpp
delete mode 100644 package_bgs/pl/LBSP.h
delete mode 100644 package_bgs/pl/LOBSTER.cpp
delete mode 100644 package_bgs/pl/LOBSTER.h
delete mode 100644 package_bgs/pl/RandUtils.h
delete mode 100644 package_bgs/pl/SuBSENSE.cpp
delete mode 100644 package_bgs/pl/SuBSENSE.h
delete mode 100644 package_bgs/sjn/SJN_MultiCueBGS.h
delete mode 100644 package_bgs/tb/FuzzyChoquetIntegral.h
delete mode 100644 package_bgs/tb/FuzzySugenoIntegral.h
delete mode 100644 package_bgs/tb/FuzzyUtils.cpp
delete mode 100644 package_bgs/tb/PixelUtils.cpp
delete mode 100644 package_bgs/tb/T2FMRF_UM.h
delete mode 100644 package_bgs/tb/T2FMRF_UV.h
delete mode 100644 vs2010/.gitignore
delete mode 100644 vs2010/README.txt
delete mode 100644 vs2010/bgslibrary.sln
delete mode 100644 vs2010/bgslibrary.suo
delete mode 100644 vs2010/bgslibrary.vcxproj
delete mode 100644 vs2010/bgslibrary.vcxproj.filters
delete mode 100644 vs2010/bgslibrary.vcxproj.user
delete mode 100644 vs2010/bgslibrary_demo.vcxproj
delete mode 100644 vs2010/bgslibrary_demo.vcxproj.filters
delete mode 100644 vs2010/bgslibrary_demo.vcxproj.user
delete mode 100644 vs2010/bgslibrary_demo2.vcxproj
delete mode 100644 vs2010/bgslibrary_demo2.vcxproj.filters
delete mode 100644 vs2010/bgslibrary_demo2.vcxproj.user
delete mode 100644 vs2010mfc/outputs/background/KEEP_THIS_FOLDER
delete mode 100644 vs2010mfc/outputs/foreground/KEEP_THIS_FOLDER
delete mode 100644 vs2010mfc/outputs/input/KEEP_THIS_FOLDER
delete mode 100644 vs2010mfc/src/ReadMe.txt
delete mode 100644 vs2010mfc/src/bgslibrary_vs2010_mfc.rc
delete mode 100644 vs2010mfc/src/bgslibrary_vs2010_mfc.sln
delete mode 100644 vs2010mfc/src/bgslibrary_vs2010_mfc.v12.suo
delete mode 100644 vs2010mfc/src/bgslibrary_vs2010_mfc.vcxproj
delete mode 100644 vs2010mfc/src/bgslibrary_vs2010_mfc.vcxproj.filters
delete mode 100644 vs2010mfc/src/bgslibrary_vs2010_mfc.vcxproj.user
delete mode 100644 vs2010mfc/src/res/bgslibrary_vs2010_mfc.ico
delete mode 100644 vs2010mfc/src/res/bgslibrary_vs2010_mfc.rc2
delete mode 100644 vs2013/.gitignore
delete mode 100644 vs2013/README.txt
delete mode 100644 vs2013/bgslibrary.sln
delete mode 100644 vs2013/bgslibrary.suo
delete mode 100644 vs2013/bgslibrary.vcxproj
delete mode 100644 vs2013/bgslibrary.vcxproj.filters
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delete mode 100644 vs2013mfc/.gitignore
delete mode 100644 vs2013mfc/config/AdaptiveBackgroundLearning.xml
delete mode 100644 vs2013mfc/config/AdaptiveSelectiveBackgroundLearning.xml
delete mode 100644 vs2013mfc/config/DPAdaptiveMedianBGS.xml
delete mode 100644 vs2013mfc/config/DPEigenbackgroundBGS.xml
delete mode 100644 vs2013mfc/config/DPGrimsonGMMBGS.xml
delete mode 100644 vs2013mfc/config/DPMeanBGS.xml
delete mode 100644 vs2013mfc/config/DPPratiMediodBGS.xml
delete mode 100644 vs2013mfc/config/DPTextureBGS.xml
delete mode 100644 vs2013mfc/config/DPWrenGABGS.xml
delete mode 100644 vs2013mfc/config/DPZivkovicAGMMBGS.xml
delete mode 100644 vs2013mfc/config/FrameDifferenceBGS.xml
delete mode 100644 vs2013mfc/config/FuzzyChoquetIntegral.xml
delete mode 100644 vs2013mfc/config/FuzzySugenoIntegral.xml
delete mode 100644 vs2013mfc/config/GMG.xml
delete mode 100644 vs2013mfc/config/IndependentMultimodalBGS.xml
delete mode 100644 vs2013mfc/config/KDE.xml
delete mode 100644 vs2013mfc/config/LBAdaptiveSOM.xml
delete mode 100644 vs2013mfc/config/LBFuzzyAdaptiveSOM.xml
delete mode 100644 vs2013mfc/config/LBFuzzyGaussian.xml
delete mode 100644 vs2013mfc/config/LBMixtureOfGaussians.xml
delete mode 100644 vs2013mfc/config/LBSimpleGaussian.xml
delete mode 100644 vs2013mfc/config/LOBSTERBGS.xml
delete mode 100644 vs2013mfc/config/MixtureOfGaussianV1BGS.xml
delete mode 100644 vs2013mfc/config/MixtureOfGaussianV2BGS.xml
delete mode 100644 vs2013mfc/config/MultiCueBGS.xml
delete mode 100644 vs2013mfc/config/MultiLayerBGS.xml
delete mode 100644 vs2013mfc/config/SigmaDeltaBGS.xml
delete mode 100644 vs2013mfc/config/StaticFrameDifferenceBGS.xml
delete mode 100644 vs2013mfc/config/SuBSENSEBGS.xml
delete mode 100644 vs2013mfc/config/T2FGMM_UM.xml
delete mode 100644 vs2013mfc/config/T2FGMM_UV.xml
delete mode 100644 vs2013mfc/config/T2FMRF_UM.xml
delete mode 100644 vs2013mfc/config/T2FMRF_UV.xml
delete mode 100644 vs2013mfc/config/VuMeter.xml
delete mode 100644 vs2013mfc/config/WeightedMovingMeanBGS.xml
delete mode 100644 vs2013mfc/config/WeightedMovingVarianceBGS.xml
delete mode 100644 vs2013mfc/dataset/video.avi
delete mode 100644 vs2013mfc/src/.gitignore
delete mode 100644 vs2013mfc/src/App.cpp
delete mode 100644 vs2013mfc/src/App.h
delete mode 100644 vs2013mfc/src/Dlg.cpp
delete mode 100644 vs2013mfc/src/Dlg.h
delete mode 100644 vs2013mfc/src/resource.h
delete mode 100644 vs2013mfc/src/stdafx.cpp
delete mode 100644 vs2013mfc/src/stdafx.h
delete mode 100644 vs2013mfc/src/targetver.h
create mode 100644 wrapper_matlab/.gitignore
create mode 100644 wrapper_matlab/backgroundSubtractor.m
create mode 100644 wrapper_matlab/backgroundSubtractor_wrapper.cpp
create mode 100644 wrapper_matlab/compile.m
create mode 100644 wrapper_matlab/config/.gitignore
create mode 100644 wrapper_matlab/demo.m
create mode 100644 wrapper_matlab/mxarray.h
create mode 100644 wrapper_matlab/mxtypes.h
create mode 100644 wrapper_matlab/run_demo.m
create mode 100644 wrapper_python/bgslibrary_module.cpp
create mode 100644 wrapper_python/np_opencv_converter.cpp
create mode 100644 wrapper_python/np_opencv_converter.h
create mode 100644 wrapper_python/utils/container.h
create mode 100644 wrapper_python/utils/conversion.cpp
create mode 100644 wrapper_python/utils/conversion.h
create mode 100644 wrapper_python/utils/template.h
diff --git a/.gitignore b/.gitignore
index 3f5e0f7..f1d9cb4 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,7 @@
etc/
build_*/
-binaries/
+dataset_*/
+binaries*/
java_gui/dist/
java_gui/build/
java_gui/bgslibrary.exe
@@ -9,4 +10,5 @@ qt_gui/
fet/etc/
*.exe
*.pdb
-*.suo
\ No newline at end of file
+*.suo
+*.dll
diff --git a/CMakeLists.txt b/CMakeLists.txt
index d8e60da..6a01cce 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -2,24 +2,44 @@ cmake_minimum_required(VERSION 2.8)
project(bgslibrary)
-set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++0x")
+# cmake -D BGS_PYTHON_SUPPORT=ON ..
+if(NOT DEFINED BGS_PYTHON_SUPPORT)
+ set(BGS_PYTHON_SUPPORT OFF)
+elseif()
+ # add_definitions(-DBGS_PYTHON_SUPPORT)
+endif()
+message(STATUS "BGSLIBRARY WITH PYTHON SUPPORT: ${BGS_PYTHON_SUPPORT}")
+
+if(UNIX)
+ set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++0x")
+endif(UNIX)
+
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -std=c99")
#set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${CMAKE_CURRENT_SOURCE_DIR}/cmake-modules)
-set( bgs_out_dir "." )
+# compilation mode setup
+set(CMAKE_BUILD_TYPE Release)
+#set(CMAKE_BUILD_TYPE Debug)
+
+if(WIN32)
+ set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /MT")
+ set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /MTd")
+endif(WIN32)
+
+set(bgs_out_dir ".")
# First for the generic no-config case (e.g. with mingw)
-set( CMAKE_RUNTIME_OUTPUT_DIRECTORY ${bgs_out_dir} )
-set( CMAKE_LIBRARY_OUTPUT_DIRECTORY ${bgs_out_dir} )
-set( CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${bgs_out_dir} )
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${bgs_out_dir})
+set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${bgs_out_dir})
+set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${bgs_out_dir})
# Second, for multi-config builds (e.g. msvc)
-foreach( OUTPUTCONFIG ${CMAKE_CONFIGURATION_TYPES} )
- string( TOUPPER ${OUTPUTCONFIG} OUTPUTCONFIG )
- set( CMAKE_RUNTIME_OUTPUT_DIRECTORY_${OUTPUTCONFIG} ${bgs_out_dir} )
- set( CMAKE_LIBRARY_OUTPUT_DIRECTORY_${OUTPUTCONFIG} ${bgs_out_dir} )
- set( CMAKE_ARCHIVE_OUTPUT_DIRECTORY_${OUTPUTCONFIG} ${bgs_out_dir} )
-endforeach( OUTPUTCONFIG CMAKE_CONFIGURATION_TYPES )
-
-IF(UNIX)
+foreach(OUTPUTCONFIG ${CMAKE_CONFIGURATION_TYPES})
+ string(TOUPPER ${OUTPUTCONFIG} OUTPUTCONFIG)
+ set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_${OUTPUTCONFIG} ${bgs_out_dir})
+ set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_${OUTPUTCONFIG} ${bgs_out_dir})
+ set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY_${OUTPUTCONFIG} ${bgs_out_dir})
+endforeach(OUTPUTCONFIG CMAKE_CONFIGURATION_TYPES)
+
+if(UNIX)
# add some standard warnings
ADD_DEFINITIONS(-Wno-variadic-macros -Wno-long-long -Wall -Wextra -Winit-self -Woverloaded-virtual -Wsign-promo -Wno-unused-parameter -pedantic -Woverloaded-virtual -Wno-unknown-pragmas)
@@ -30,6 +50,7 @@ IF(UNIX)
#ADD_DEFINITIONS(-Wconversion -Wfloat-equal)
endif(UNIX)
+set(OpenCV_STATIC OFF)
find_package(OpenCV REQUIRED)
message(STATUS "OpenCV library status:")
@@ -37,24 +58,50 @@ message(STATUS " version: ${OpenCV_VERSION}")
message(STATUS " libraries: ${OpenCV_LIBS}")
message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}")
-if(${OpenCV_VERSION} VERSION_EQUAL 3 OR ${OpenCV_VERSION} VERSION_GREATER 3)
- message(FATAL_ERROR "OpenCV version is not compatible: ${OpenCV_VERSION}")
-endif()
+# if(${OpenCV_VERSION} VERSION_EQUAL 3 OR ${OpenCV_VERSION} VERSION_GREATER 3)
+# message(FATAL_ERROR "OpenCV version is not compatible: ${OpenCV_VERSION}")
+# endif()
if(${OpenCV_VERSION} VERSION_LESS 2.3.1)
message(FATAL_ERROR "OpenCV version is not compatible: ${OpenCV_VERSION}")
endif()
-file(GLOB sources FrameProcessor.cpp PreProcessor.cpp VideoAnalysis.cpp VideoCapture.cpp)
-file(GLOB main Main.cpp)
+if(BGS_PYTHON_SUPPORT)
+ set(Boost_USE_STATIC_LIBS OFF)
+ set(Boost_USE_MULTITHREADED ON)
+ set(Boost_USE_STATIC_RUNTIME OFF)
+
+ find_package(Boost REQUIRED COMPONENTS python)
+ find_package(PythonLibs REQUIRED)
+
+ message(STATUS "Boost library status:")
+ message(STATUS " version: ${Boost_VERSION}")
+ message(STATUS " libraries: ${Boost_LIBRARIES}")
+ message(STATUS " include path: ${Boost_INCLUDE_DIRS}")
+
+ message(STATUS "Python library status:")
+ message(STATUS " version: ${PYTHON_VERSION}")
+ message(STATUS " libraries: ${PYTHON_LIBRARIES}")
+ message(STATUS " include path: ${PYTHON_INCLUDE_DIRS}")
+endif()
+
+#file(GLOB sources FrameProcessor.cpp PreProcessor.cpp VideoAnalysis.cpp VideoCapture.cpp)
+file(GLOB main Main.cpp FrameProcessor.cpp PreProcessor.cpp VideoAnalysis.cpp VideoCapture.cpp)
file(GLOB demo Demo.cpp)
file(GLOB demo2 Demo2.cpp)
# list(REMOVE_ITEM sources ${demo} ${demo2})
file(GLOB_RECURSE analysis_src package_analysis/*.cpp)
-file(GLOB_RECURSE bgs_src package_bgs/*.cpp package_bgs/*.c)
-file(GLOB_RECURSE bgs_include package_bgs/*.h)
+if(BGS_PYTHON_SUPPORT)
+ file(GLOB_RECURSE bgs_src package_bgs/*.cpp package_bgs/*.c wrapper_python/*.cpp)
+ file(GLOB_RECURSE bgs_include package_bgs/*.h wrapper_python/*.h)
+ include_directories(${CMAKE_SOURCE_DIR} ${OpenCV_INCLUDE_DIRS} ${Boost_INCLUDE_DIRS} ${PYTHON_INCLUDE_DIRS})
+else()
+ file(GLOB_RECURSE bgs_src package_bgs/*.cpp package_bgs/*.c)
+ file(GLOB_RECURSE bgs_include package_bgs/*.h)
+ include_directories(${CMAKE_SOURCE_DIR} ${OpenCV_INCLUDE_DIRS})
+endif()
# GMG is not available in older OpenCV versions
if(${OpenCV_VERSION} VERSION_LESS 2.4.3)
@@ -62,10 +109,16 @@ if(${OpenCV_VERSION} VERSION_LESS 2.4.3)
list(REMOVE_ITEM bgs_src ${gmg})
endif()
-include_directories(${CMAKE_SOURCE_DIR})
-
-add_library(libbgs STATIC ${sources} ${bgs_src} ${analysis_src})
-target_link_libraries(libbgs ${OpenCV_LIBS})
+if(BGS_PYTHON_SUPPORT)
+ #add_library(libbgs SHARED ${sources} ${bgs_src} ${analysis_src})
+ add_library(libbgs SHARED ${bgs_src} ${analysis_src})
+ target_link_libraries(libbgs ${OpenCV_LIBS} ${Boost_LIBRARIES} ${PYTHON_LIBRARIES})
+ target_compile_definitions(libbgs PRIVATE BGS_PYTHON_SUPPORT=1)
+else()
+ #add_library(libbgs STATIC ${sources} ${bgs_src} ${analysis_src})
+ add_library(libbgs STATIC ${bgs_src} ${analysis_src})
+ target_link_libraries(libbgs ${OpenCV_LIBS})
+endif()
set_property(TARGET libbgs PROPERTY PUBLIC_HEADER ${bgs_include})
if(WIN32)
# set_property(TARGET libbgs PROPERTY SUFFIX ".lib")
@@ -83,7 +136,7 @@ target_link_libraries(bgs_demo ${OpenCV_LIBS} libbgs)
add_executable(bgs_demo2 ${demo2})
target_link_libraries(bgs_demo2 ${OpenCV_LIBS} libbgs)
-INSTALL(TARGETS libbgs
+install(TARGETS libbgs
bgslibrary
RUNTIME DESTINATION bin COMPONENT app
LIBRARY DESTINATION lib COMPONENT runtime
diff --git a/Demo.cpp b/Demo.cpp
index 61561be..fec54d8 100644
--- a/Demo.cpp
+++ b/Demo.cpp
@@ -17,178 +17,98 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <iostream>
#include <opencv2/opencv.hpp>
-
-#include "package_bgs/FrameDifferenceBGS.h"
-#include "package_bgs/StaticFrameDifferenceBGS.h"
-#include "package_bgs/WeightedMovingMeanBGS.h"
-#include "package_bgs/WeightedMovingVarianceBGS.h"
-#include "package_bgs/MixtureOfGaussianV1BGS.h"
-#include "package_bgs/MixtureOfGaussianV2BGS.h"
-#include "package_bgs/AdaptiveBackgroundLearning.h"
-#include "package_bgs/AdaptiveSelectiveBackgroundLearning.h"
-
-#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
-#include "package_bgs/GMG.h"
-#endif
-
-#include "package_bgs/dp/DPAdaptiveMedianBGS.h"
-#include "package_bgs/dp/DPGrimsonGMMBGS.h"
-#include "package_bgs/dp/DPZivkovicAGMMBGS.h"
-#include "package_bgs/dp/DPMeanBGS.h"
-#include "package_bgs/dp/DPWrenGABGS.h"
-#include "package_bgs/dp/DPPratiMediodBGS.h"
-#include "package_bgs/dp/DPEigenbackgroundBGS.h"
-#include "package_bgs/dp/DPTextureBGS.h"
-
-#include "package_bgs/tb/T2FGMM_UM.h"
-#include "package_bgs/tb/T2FGMM_UV.h"
-#include "package_bgs/tb/T2FMRF_UM.h"
-#include "package_bgs/tb/T2FMRF_UV.h"
-#include "package_bgs/tb/FuzzySugenoIntegral.h"
-#include "package_bgs/tb/FuzzyChoquetIntegral.h"
-
-#include "package_bgs/lb/LBSimpleGaussian.h"
-#include "package_bgs/lb/LBFuzzyGaussian.h"
-#include "package_bgs/lb/LBMixtureOfGaussians.h"
-#include "package_bgs/lb/LBAdaptiveSOM.h"
-#include "package_bgs/lb/LBFuzzyAdaptiveSOM.h"
-
-#include "package_bgs/ck/LbpMrf.h"
-#include "package_bgs/jmo/MultiLayerBGS.h"
-// The PBAS algorithm was removed from BGSLibrary because it is
-// based on patented algorithm ViBE
-// http://www2.ulg.ac.be/telecom/research/vibe/
-//#include "package_bgs/pt/PixelBasedAdaptiveSegmenter.h"
-#include "package_bgs/av/VuMeter.h"
-#include "package_bgs/ae/KDE.h"
-#include "package_bgs/db/IndependentMultimodalBGS.h"
-#include "package_bgs/sjn/SJN_MultiCueBGS.h"
-#include "package_bgs/bl/SigmaDeltaBGS.h"
-
-#include "package_bgs/pl/SuBSENSE.h"
-#include "package_bgs/pl/LOBSTER.h"
+#include "package_bgs/bgslibrary.h"
int main(int argc, char **argv)
{
std::cout << "Using OpenCV " << CV_MAJOR_VERSION << "." << CV_MINOR_VERSION << "." << CV_SUBMINOR_VERSION << std::endl;
- CvCapture *capture = 0;
- int resize_factor = 100;
+ VideoCapture capture;
- if(argc > 1)
+ if (argc > 1)
{
std::cout << "Openning: " << argv[1] << std::endl;
- capture = cvCaptureFromAVI(argv[1]);
+ capture.open(argv[1]);
}
else
- {
- capture = cvCaptureFromCAM(0);
- resize_factor = 50; // set size = 50% of original image
- }
+ capture.open(0);
- if(!capture)
+ if (!capture.isOpened())
{
std::cerr << "Cannot initialize video!" << std::endl;
return -1;
}
-
- IplImage *frame_aux = cvQueryFrame(capture);
- IplImage *frame = cvCreateImage(cvSize((int)((frame_aux->width*resize_factor)/100) , (int)((frame_aux->height*resize_factor)/100)), frame_aux->depth, frame_aux->nChannels);
- cvResize(frame_aux, frame);
/* Background Subtraction Methods */
IBGS *bgs;
- /*** Default Package ***/
- bgs = new FrameDifferenceBGS;
- //bgs = new StaticFrameDifferenceBGS;
- //bgs = new WeightedMovingMeanBGS;
- //bgs = new WeightedMovingVarianceBGS;
- //bgs = new MixtureOfGaussianV1BGS;
- //bgs = new MixtureOfGaussianV2BGS;
+ bgs = new FrameDifference;
+ //bgs = new StaticFrameDifference;
+ //bgs = new WeightedMovingMean;
+ //bgs = new WeightedMovingVariance;
+ //bgs = new MixtureOfGaussianV1; // only on OpenCV 2.x
+ //bgs = new MixtureOfGaussianV2;
//bgs = new AdaptiveBackgroundLearning;
//bgs = new AdaptiveSelectiveBackgroundLearning;
- //bgs = new GMG;
-
- /*** DP Package (thanks to Donovan Parks) ***/
- //bgs = new DPAdaptiveMedianBGS;
- //bgs = new DPGrimsonGMMBGS;
- //bgs = new DPZivkovicAGMMBGS;
- //bgs = new DPMeanBGS;
- //bgs = new DPWrenGABGS;
- //bgs = new DPPratiMediodBGS;
- //bgs = new DPEigenbackgroundBGS;
- //bgs = new DPTextureBGS;
-
- /*** TB Package (thanks to Thierry Bouwmans, Fida EL BAF and Zhenjie Zhao) ***/
+ //bgs = new GMG; // only on OpenCV 2.x
+ //bgs = new KNN; // only on OpenCV 3.x
+ //bgs = new DPAdaptiveMedian;
+ //bgs = new DPGrimsonGMM;
+ //bgs = new DPZivkovicAGMM;
+ //bgs = new DPMean;
+ //bgs = new DPWrenGA;
+ //bgs = new DPPratiMediod;
+ //bgs = new DPEigenbackground;
+ //bgs = new DPTexture;
//bgs = new T2FGMM_UM;
//bgs = new T2FGMM_UV;
//bgs = new T2FMRF_UM;
//bgs = new T2FMRF_UV;
//bgs = new FuzzySugenoIntegral;
//bgs = new FuzzyChoquetIntegral;
-
- /*** JMO Package (thanks to Jean-Marc Odobez) ***/
- //bgs = new MultiLayerBGS;
-
- /*** PT Package (thanks to Martin Hofmann, Philipp Tiefenbacher and Gerhard Rigoll) ***/
+ //bgs = new MultiLayer;
//bgs = new PixelBasedAdaptiveSegmenter;
-
- /*** LB Package (thanks to Laurence Bender) ***/
//bgs = new LBSimpleGaussian;
//bgs = new LBFuzzyGaussian;
//bgs = new LBMixtureOfGaussians;
//bgs = new LBAdaptiveSOM;
//bgs = new LBFuzzyAdaptiveSOM;
-
- /*** LBP-MRF Package (thanks to Csaba Kertész) ***/
- //bgs = new LbpMrf;
-
- /*** AV Package (thanks to Lionel Robinault and Antoine Vacavant) ***/
+ //bgs = new LBP_MRF;
//bgs = new VuMeter;
-
- /*** EG Package (thanks to Ahmed Elgammal) ***/
//bgs = new KDE;
-
- /*** DB Package (thanks to Domenico Daniele Bloisi) ***/
- //bgs = new IndependentMultimodalBGS;
-
- /*** SJN Package (thanks to SeungJong Noh) ***/
- //bgs = new SJN_MultiCueBGS;
-
- /*** BL Package (thanks to Benjamin Laugraud) ***/
- //bgs = new SigmaDeltaBGS;
-
- /*** PL Package (thanks to Pierre-Luc) ***/
- //bgs = new SuBSENSEBGS();
- //bgs = new LOBSTERBGS();
+ //bgs = new IndependentMultimodal;
+ //bgs = new MultiCue;
+ //bgs = new SigmaDelta;
+ //bgs = new SuBSENSE;
+ //bgs = new LOBSTER;
+ //bgs = new PAWCS;
+ //bgs = new TwoPoints;
+ //bgs = new ViBe;
int key = 0;
- while(key != 'q')
+ cv::Mat img_input;
+ while (key != 'q')
{
- frame_aux = cvQueryFrame(capture);
- if(!frame_aux) break;
+ capture >> img_input;
+ if (img_input.empty()) break;
- cvResize(frame_aux, frame);
-
- cv::Mat img_input(frame);
cv::imshow("input", img_input);
cv::Mat img_mask;
cv::Mat img_bkgmodel;
bgs->process(img_input, img_mask, img_bkgmodel); // by default, it shows automatically the foreground mask image
-
+
//if(!img_mask.empty())
// cv::imshow("Foreground", img_mask);
// do something
-
+
key = cvWaitKey(33);
}
delete bgs;
+ capture.release();
cvDestroyAllWindows();
- cvReleaseCapture(&capture);
return 0;
}
diff --git a/Demo.py b/Demo.py
new file mode 100644
index 0000000..71bc352
--- /dev/null
+++ b/Demo.py
@@ -0,0 +1,84 @@
+import numpy as np
+import cv2
+import libbgs
+
+## BGS Library algorithms
+bgs = libbgs.FrameDifference()
+#bgs = libbgs.StaticFrameDifference()
+#bgs = libbgs.AdaptiveBackgroundLearning()
+#bgs = libbgs.AdaptiveSelectiveBackgroundLearning()
+#bgs = libbgs.DPAdaptiveMedian()
+#bgs = libbgs.DPEigenbackground()
+#bgs = libbgs.DPGrimsonGMM()
+#bgs = libbgs.DPMean()
+#bgs = libbgs.DPPratiMediod()
+#bgs = libbgs.DPTexture()
+#bgs = libbgs.DPWrenGA()
+#bgs = libbgs.DPZivkovicAGMM()
+#bgs = libbgs.FuzzyChoquetIntegral()
+#bgs = libbgs.FuzzySugenoIntegral()
+#bgs = libbgs.GMG() # if opencv 2.x
+#bgs = libbgs.IndependentMultimodal()
+#bgs = libbgs.KDE()
+#bgs = libbgs.KNN() # if opencv 3.x
+#bgs = libbgs.LBAdaptiveSOM()
+#bgs = libbgs.LBFuzzyAdaptiveSOM()
+#bgs = libbgs.LBFuzzyGaussian()
+#bgs = libbgs.LBMixtureOfGaussians()
+#bgs = libbgs.LBSimpleGaussian()
+#bgs = libbgs.LBP_MRF()
+#bgs = libbgs.LOBSTER()
+#bgs = libbgs.MixtureOfGaussianV1() # if opencv 2.x
+#bgs = libbgs.MixtureOfGaussianV2()
+#bgs = libbgs.MultiCue()
+#bgs = libbgs.MultiLayer()
+#bgs = libbgs.PAWCS()
+#bgs = libbgs.PixelBasedAdaptiveSegmenter()
+#bgs = libbgs.SigmaDelta()
+#bgs = libbgs.SuBSENSE()
+#bgs = libbgs.T2FGMM_UM()
+#bgs = libbgs.T2FGMM_UV()
+#bgs = libbgs.T2FMRF_UM()
+#bgs = libbgs.T2FMRF_UV()
+#bgs = libbgs.VuMeter()
+#bgs = libbgs.WeightedMovingMean()
+#bgs = libbgs.WeightedMovingVariance()
+#bgs = libbgs.TwoPoints()
+#bgs = libbgs.ViBe()
+
+video_file = "dataset/video.avi"
+
+capture = cv2.VideoCapture(video_file)
+while not capture.isOpened():
+ capture = cv2.VideoCapture(video_file)
+ cv2.waitKey(1000)
+ print "Wait for the header"
+
+pos_frame = capture.get(cv2.cv.CV_CAP_PROP_POS_FRAMES)
+while True:
+ flag, frame = capture.read()
+
+ if flag:
+ cv2.imshow('video', frame)
+ pos_frame = capture.get(cv2.cv.CV_CAP_PROP_POS_FRAMES)
+ #print str(pos_frame)+" frames"
+
+ img_output = bgs.apply(frame)
+ img_bgmodel = bgs.getBackgroundModel();
+
+ cv2.imshow('img_output', img_output)
+ cv2.imshow('img_bgmodel', img_bgmodel)
+
+ else:
+ capture.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, pos_frame-1)
+ print "frame is not ready"
+ cv2.waitKey(1000)
+ # break
+
+ if 0xFF & cv2.waitKey(10) == 27:
+ break
+
+ if capture.get(cv2.cv.CV_CAP_PROP_POS_FRAMES) == capture.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT):
+ break
+
+cv2.destroyAllWindows()
diff --git a/Demo2.cpp b/Demo2.cpp
index fe95c52..22c6ffc 100644
--- a/Demo2.cpp
+++ b/Demo2.cpp
@@ -17,56 +17,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <iostream>
#include <opencv2/opencv.hpp>
-
-#include "package_bgs/FrameDifferenceBGS.h"
-#include "package_bgs/StaticFrameDifferenceBGS.h"
-#include "package_bgs/WeightedMovingMeanBGS.h"
-#include "package_bgs/WeightedMovingVarianceBGS.h"
-#include "package_bgs/MixtureOfGaussianV1BGS.h"
-#include "package_bgs/MixtureOfGaussianV2BGS.h"
-#include "package_bgs/AdaptiveBackgroundLearning.h"
-#include "package_bgs/AdaptiveSelectiveBackgroundLearning.h"
-
-#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
-#include "package_bgs/GMG.h"
-#endif
-
-#include "package_bgs/dp/DPAdaptiveMedianBGS.h"
-#include "package_bgs/dp/DPGrimsonGMMBGS.h"
-#include "package_bgs/dp/DPZivkovicAGMMBGS.h"
-#include "package_bgs/dp/DPMeanBGS.h"
-#include "package_bgs/dp/DPWrenGABGS.h"
-#include "package_bgs/dp/DPPratiMediodBGS.h"
-#include "package_bgs/dp/DPEigenbackgroundBGS.h"
-#include "package_bgs/dp/DPTextureBGS.h"
-
-#include "package_bgs/tb/T2FGMM_UM.h"
-#include "package_bgs/tb/T2FGMM_UV.h"
-#include "package_bgs/tb/T2FMRF_UM.h"
-#include "package_bgs/tb/T2FMRF_UV.h"
-#include "package_bgs/tb/FuzzySugenoIntegral.h"
-#include "package_bgs/tb/FuzzyChoquetIntegral.h"
-
-#include "package_bgs/lb/LBSimpleGaussian.h"
-#include "package_bgs/lb/LBFuzzyGaussian.h"
-#include "package_bgs/lb/LBMixtureOfGaussians.h"
-#include "package_bgs/lb/LBAdaptiveSOM.h"
-#include "package_bgs/lb/LBFuzzyAdaptiveSOM.h"
-
-#include "package_bgs/ck/LbpMrf.h"
-#include "package_bgs/jmo/MultiLayerBGS.h"
-// The PBAS algorithm was removed from BGSLibrary because it is
-// based on patented algorithm ViBE
-// http://www2.ulg.ac.be/telecom/research/vibe/
-//#include "package_bgs/pt/PixelBasedAdaptiveSegmenter.h"
-#include "package_bgs/av/VuMeter.h"
-#include "package_bgs/ae/KDE.h"
-#include "package_bgs/db/IndependentMultimodalBGS.h"
-#include "package_bgs/sjn/SJN_MultiCueBGS.h"
-#include "package_bgs/bl/SigmaDeltaBGS.h"
-
-#include "package_bgs/pl/SuBSENSE.h"
-#include "package_bgs/pl/LOBSTER.h"
+#include "package_bgs/bgslibrary.h"
int main(int argc, char **argv)
{
@@ -75,81 +26,60 @@ int main(int argc, char **argv)
/* Background Subtraction Methods */
IBGS *bgs;
- /*** Default Package ***/
- bgs = new FrameDifferenceBGS;
- //bgs = new StaticFrameDifferenceBGS;
- //bgs = new WeightedMovingMeanBGS;
- //bgs = new WeightedMovingVarianceBGS;
- //bgs = new MixtureOfGaussianV1BGS;
- //bgs = new MixtureOfGaussianV2BGS;
+ bgs = new FrameDifference;
+ //bgs = new StaticFrameDifference;
+ //bgs = new WeightedMovingMean;
+ //bgs = new WeightedMovingVariance;
+ //bgs = new MixtureOfGaussianV1; // only on OpenCV 2.x
+ //bgs = new MixtureOfGaussianV2;
//bgs = new AdaptiveBackgroundLearning;
//bgs = new AdaptiveSelectiveBackgroundLearning;
- //bgs = new GMG;
-
- /*** DP Package (thanks to Donovan Parks) ***/
- //bgs = new DPAdaptiveMedianBGS;
- //bgs = new DPGrimsonGMMBGS;
- //bgs = new DPZivkovicAGMMBGS;
- //bgs = new DPMeanBGS;
- //bgs = new DPWrenGABGS;
- //bgs = new DPPratiMediodBGS;
- //bgs = new DPEigenbackgroundBGS;
- //bgs = new DPTextureBGS;
-
- /*** TB Package (thanks to Thierry Bouwmans, Fida EL BAF and Zhenjie Zhao) ***/
+ //bgs = new GMG; // only on OpenCV 2.x
+ //bgs = new KNN; // only on OpenCV 3.x
+ //bgs = new DPAdaptiveMedian;
+ //bgs = new DPGrimsonGMM;
+ //bgs = new DPZivkovicAGMM;
+ //bgs = new DPMean;
+ //bgs = new DPWrenGA;
+ //bgs = new DPPratiMediod;
+ //bgs = new DPEigenbackground;
+ //bgs = new DPTexture;
//bgs = new T2FGMM_UM;
//bgs = new T2FGMM_UV;
//bgs = new T2FMRF_UM;
//bgs = new T2FMRF_UV;
//bgs = new FuzzySugenoIntegral;
//bgs = new FuzzyChoquetIntegral;
-
- /*** JMO Package (thanks to Jean-Marc Odobez) ***/
- //bgs = new MultiLayerBGS;
-
- /*** PT Package (thanks to Martin Hofmann, Philipp Tiefenbacher and Gerhard Rigoll) ***/
+ //bgs = new MultiLayer;
//bgs = new PixelBasedAdaptiveSegmenter;
-
- /*** LB Package (thanks to Laurence Bender) ***/
//bgs = new LBSimpleGaussian;
//bgs = new LBFuzzyGaussian;
//bgs = new LBMixtureOfGaussians;
//bgs = new LBAdaptiveSOM;
//bgs = new LBFuzzyAdaptiveSOM;
-
- /*** LBP-MRF Package (thanks to Csaba Kertész) ***/
- //bgs = new LbpMrf;
-
- /*** AV Package (thanks to Lionel Robinault and Antoine Vacavant) ***/
+ //bgs = new LBP_MRF;
//bgs = new VuMeter;
-
- /*** EG Package (thanks to Ahmed Elgammal) ***/
//bgs = new KDE;
-
- /*** DB Package (thanks to Domenico Daniele Bloisi) ***/
- //bgs = new IndependentMultimodalBGS;
-
- /*** SJN Package (thanks to SeungJong Noh) ***/
- //bgs = new SJN_MultiCueBGS;
-
- /*** BL Package (thanks to Benjamin Laugraud) ***/
- //bgs = new SigmaDeltaBGS;
-
- /*** PL Package (thanks to Pierre-Luc) ***/
- //bgs = new SuBSENSEBGS();
- //bgs = new LOBSTERBGS();
+ //bgs = new IndependentMultimodal;
+ //bgs = new MultiCue;
+ //bgs = new SigmaDelta;
+ //bgs = new SuBSENSE;
+ //bgs = new LOBSTER;
+ //bgs = new PAWCS;
+ //bgs = new TwoPoints;
+ //bgs = new ViBe;
int frameNumber = 1;
int key = 0;
- while(key != 'q')
+ while (key != 'q')
{
std::stringstream ss;
ss << frameNumber;
- std::string fileName = "frames/" + ss.str() + ".png";
+ std::string fileName = "dataset/frames/" + ss.str() + ".png";
std::cout << "reading " << fileName << std::endl;
cv::Mat img_input = cv::imread(fileName, CV_LOAD_IMAGE_COLOR);
-
+
if (img_input.empty())
break;
@@ -157,18 +87,19 @@ int main(int argc, char **argv)
cv::Mat img_mask;
cv::Mat img_bkgmodel;
- bgs->process(img_input, img_mask, img_bkgmodel); // by default, it shows automatically the foreground mask image
-
+ bgs->process(img_input, img_mask, img_bkgmodel);
+ // by default, "bgs->process(.)" automatically shows the foreground mask image
+ // or set "bgs->setShowOutput(false)" to disable
+
//if(!img_mask.empty())
// cv::imshow("Foreground", img_mask);
// do something
-
+
key = cvWaitKey(33);
frameNumber++;
}
cvWaitKey(0);
delete bgs;
-
cvDestroyAllWindows();
return 0;
diff --git a/FrameProcessor.cpp b/FrameProcessor.cpp
index 0cce652..5088121 100644
--- a/FrameProcessor.cpp
+++ b/FrameProcessor.cpp
@@ -37,23 +37,25 @@ namespace bgslibrary
if (enablePreProcessor)
preProcessor = new PreProcessor;
- if (enableFrameDifferenceBGS)
- frameDifference = new FrameDifferenceBGS;
+ if (enableFrameDifference)
+ frameDifference = new FrameDifference;
- if (enableStaticFrameDifferenceBGS)
- staticFrameDifference = new StaticFrameDifferenceBGS;
+ if (enableStaticFrameDifference)
+ staticFrameDifference = new StaticFrameDifference;
- if (enableWeightedMovingMeanBGS)
- weightedMovingMean = new WeightedMovingMeanBGS;
+ if (enableWeightedMovingMean)
+ weightedMovingMean = new WeightedMovingMean;
- if (enableWeightedMovingVarianceBGS)
- weightedMovingVariance = new WeightedMovingVarianceBGS;
+ if (enableWeightedMovingVariance)
+ weightedMovingVariance = new WeightedMovingVariance;
- if (enableMixtureOfGaussianV1BGS)
- mixtureOfGaussianV1BGS = new MixtureOfGaussianV1BGS;
+#if CV_MAJOR_VERSION == 2
+ if (enableMixtureOfGaussianV1)
+ mixtureOfGaussianV1 = new MixtureOfGaussianV1;
+#endif
- if (enableMixtureOfGaussianV2BGS)
- mixtureOfGaussianV2BGS = new MixtureOfGaussianV2BGS;
+ if (enableMixtureOfGaussianV2)
+ mixtureOfGaussianV2 = new MixtureOfGaussianV2;
if (enableAdaptiveBackgroundLearning)
adaptiveBackgroundLearning = new AdaptiveBackgroundLearning;
@@ -63,29 +65,29 @@ namespace bgslibrary
gmg = new GMG;
#endif
- if (enableDPAdaptiveMedianBGS)
- adaptiveMedian = new DPAdaptiveMedianBGS;
+ if (enableDPAdaptiveMedian)
+ dpAdaptiveMedian = new DPAdaptiveMedian;
- if (enableDPGrimsonGMMBGS)
- grimsonGMM = new DPGrimsonGMMBGS;
+ if (enableDPGrimsonGMM)
+ dpGrimsonGMM = new DPGrimsonGMM;
- if (enableDPZivkovicAGMMBGS)
- zivkovicAGMM = new DPZivkovicAGMMBGS;
+ if (enableDPZivkovicAGMM)
+ dpZivkovicAGMM = new DPZivkovicAGMM;
- if (enableDPMeanBGS)
- temporalMean = new DPMeanBGS;
+ if (enableDPMean)
+ dpTemporalMean = new DPMean;
- if (enableDPWrenGABGS)
- wrenGA = new DPWrenGABGS;
+ if (enableDPWrenGA)
+ dpWrenGA = new DPWrenGA;
- if (enableDPPratiMediodBGS)
- pratiMediod = new DPPratiMediodBGS;
+ if (enableDPPratiMediod)
+ dpPratiMediod = new DPPratiMediod;
- if (enableDPEigenbackgroundBGS)
- eigenBackground = new DPEigenbackgroundBGS;
+ if (enableDPEigenbackground)
+ dpEigenBackground = new DPEigenbackground;
- if (enableDPTextureBGS)
- textureBGS = new DPTextureBGS;
+ if (enableDPTexture)
+ dpTexture = new DPTexture;
if (enableT2FGMM_UM)
type2FuzzyGMM_UM = new T2FGMM_UM;
@@ -121,13 +123,15 @@ namespace bgslibrary
lbFuzzyAdaptiveSOM = new LBFuzzyAdaptiveSOM;
if (enableLbpMrf)
- lbpMrf = new LbpMrf;
+ lbpMrf = new LBP_MRF;
- if(enableMultiLayerBGS)
- multiLayerBGS = new MultiLayerBGS;
+#if CV_MAJOR_VERSION == 2
+ if (enableMultiLayer)
+ multiLayer = new MultiLayer;
+#endif
- //if(enablePBAS)
- // pixelBasedAdaptiveSegmenter = new PixelBasedAdaptiveSegmenter;
+ if (enablePBAS)
+ pixelBasedAdaptiveSegmenter = new PixelBasedAdaptiveSegmenter;
if (enableVuMeter)
vuMeter = new VuMeter;
@@ -136,19 +140,19 @@ namespace bgslibrary
kde = new KDE;
if (enableIMBS)
- imbs = new IndependentMultimodalBGS;
+ imbs = new IndependentMultimodal;
- if (enableMultiCueBGS)
- mcbgs = new SJN_MultiCueBGS;
+ if (enableMultiCue)
+ multiCue = new MultiCue;
- if (enableSigmaDeltaBGS)
- sdbgs = new SigmaDeltaBGS;
+ if (enableSigmaDelta)
+ sigmaDelta = new SigmaDelta;
- if (enableSuBSENSEBGS)
- ssbgs = new SuBSENSEBGS;
+ if (enableSuBSENSE)
+ subSENSE = new SuBSENSE;
- if (enableLOBSTERBGS)
- lobgs = new LOBSTERBGS;
+ if (enableLOBSTER)
+ lobster = new LOBSTER;
if (enableForegroundMaskAnalysis)
foregroundMaskAnalysis = new ForegroundMaskAnalysis;
@@ -171,169 +175,177 @@ namespace bgslibrary
frameNumber++;
if (enablePreProcessor)
- preProcessor->process(img_input, img_prep);
+ preProcessor->process(img_input, img_preProcessor);
- if (enableFrameDifferenceBGS)
- process("FrameDifferenceBGS", frameDifference, img_prep, img_framediff);
+ if (enableFrameDifference)
+ process("FrameDifference", frameDifference, img_preProcessor, img_frameDifference);
- if (enableStaticFrameDifferenceBGS)
- process("StaticFrameDifferenceBGS", staticFrameDifference, img_prep, img_staticfdiff);
+ if (enableStaticFrameDifference)
+ process("StaticFrameDifference", staticFrameDifference, img_preProcessor, img_staticFrameDifference);
- if (enableWeightedMovingMeanBGS)
- process("WeightedMovingMeanBGS", weightedMovingMean, img_prep, img_wmovmean);
+ if (enableWeightedMovingMean)
+ process("WeightedMovingMean", weightedMovingMean, img_preProcessor, img_weightedMovingMean);
- if (enableWeightedMovingVarianceBGS)
- process("WeightedMovingVarianceBGS", weightedMovingVariance, img_prep, img_movvar);
+ if (enableWeightedMovingVariance)
+ process("WeightedMovingVariance", weightedMovingVariance, img_preProcessor, img_weightedMovingVariance);
- if (enableMixtureOfGaussianV1BGS)
- process("MixtureOfGaussianV1BGS", mixtureOfGaussianV1BGS, img_prep, img_mog1);
+#if CV_MAJOR_VERSION == 2
+ if (enableMixtureOfGaussianV1)
+ process("MixtureOfGaussianV1", mixtureOfGaussianV1, img_preProcessor, img_mixtureOfGaussianV1);
+#endif
- if (enableMixtureOfGaussianV2BGS)
- process("MixtureOfGaussianV2BGS", mixtureOfGaussianV2BGS, img_prep, img_mog2);
+ if (enableMixtureOfGaussianV2)
+ process("MixtureOfGaussianV2", mixtureOfGaussianV2, img_preProcessor, img_mixtureOfGaussianV2);
if (enableAdaptiveBackgroundLearning)
- process("AdaptiveBackgroundLearning", adaptiveBackgroundLearning, img_prep, img_bkgl_fgmask);
+ process("AdaptiveBackgroundLearning", adaptiveBackgroundLearning, img_preProcessor, img_adaptiveBackgroundLearning);
#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
if (enableGMG)
- process("GMG", gmg, img_prep, img_gmg);
+ process("GMG", gmg, img_preProcessor, img_gmg);
#endif
- if (enableDPAdaptiveMedianBGS)
- process("DPAdaptiveMedianBGS", adaptiveMedian, img_prep, img_adpmed);
+ if (enableDPAdaptiveMedian)
+ process("DPAdaptiveMedian", dpAdaptiveMedian, img_preProcessor, img_dpAdaptiveMedian);
- if (enableDPGrimsonGMMBGS)
- process("DPGrimsonGMMBGS", grimsonGMM, img_prep, img_grigmm);
+ if (enableDPGrimsonGMM)
+ process("DPGrimsonGMM", dpGrimsonGMM, img_preProcessor, img_dpGrimsonGMM);
- if (enableDPZivkovicAGMMBGS)
- process("DPZivkovicAGMMBGS", zivkovicAGMM, img_prep, img_zivgmm);
+ if (enableDPZivkovicAGMM)
+ process("DPZivkovicAGMM", dpZivkovicAGMM, img_preProcessor, img_dpZivkovicAGMM);
- if (enableDPMeanBGS)
- process("DPMeanBGS", temporalMean, img_prep, img_tmpmean);
+ if (enableDPMean)
+ process("DPMean", dpTemporalMean, img_preProcessor, img_dpTemporalMean);
- if (enableDPWrenGABGS)
- process("DPWrenGABGS", wrenGA, img_prep, img_wrenga);
+ if (enableDPWrenGA)
+ process("DPWrenGA", dpWrenGA, img_preProcessor, img_dpWrenGA);
- if (enableDPPratiMediodBGS)
- process("DPPratiMediodBGS", pratiMediod, img_prep, img_pramed);
+ if (enableDPPratiMediod)
+ process("DPPratiMediod", dpPratiMediod, img_preProcessor, img_dpPratiMediod);
- if (enableDPEigenbackgroundBGS)
- process("DPEigenbackgroundBGS", eigenBackground, img_prep, img_eigbkg);
+ if (enableDPEigenbackground)
+ process("DPEigenbackground", dpEigenBackground, img_preProcessor, img_dpEigenBackground);
- if (enableDPTextureBGS)
- process("DPTextureBGS", textureBGS, img_prep, img_texbgs);
+ if (enableDPTexture)
+ process("DPTexture", dpTexture, img_preProcessor, img_dpTexture);
if (enableT2FGMM_UM)
- process("T2FGMM_UM", type2FuzzyGMM_UM, img_prep, img_t2fgmm_um);
+ process("T2FGMM_UM", type2FuzzyGMM_UM, img_preProcessor, img_type2FuzzyGMM_UM);
if (enableT2FGMM_UV)
- process("T2FGMM_UV", type2FuzzyGMM_UV, img_prep, img_t2fgmm_uv);
+ process("T2FGMM_UV", type2FuzzyGMM_UV, img_preProcessor, img_type2FuzzyGMM_UV);
if (enableT2FMRF_UM)
- process("T2FMRF_UM", type2FuzzyMRF_UM, img_prep, img_t2fmrf_um);
+ process("T2FMRF_UM", type2FuzzyMRF_UM, img_preProcessor, img_type2FuzzyMRF_UM);
if (enableT2FMRF_UV)
- process("T2FMRF_UV", type2FuzzyMRF_UV, img_prep, img_t2fmrf_uv);
+ process("T2FMRF_UV", type2FuzzyMRF_UV, img_preProcessor, img_type2FuzzyMRF_UV);
if (enableFuzzySugenoIntegral)
- process("FuzzySugenoIntegral", fuzzySugenoIntegral, img_prep, img_fsi);
+ process("FuzzySugenoIntegral", fuzzySugenoIntegral, img_preProcessor, img_fuzzySugenoIntegral);
if (enableFuzzyChoquetIntegral)
- process("FuzzyChoquetIntegral", fuzzyChoquetIntegral, img_prep, img_fci);
+ process("FuzzyChoquetIntegral", fuzzyChoquetIntegral, img_preProcessor, img_fuzzyChoquetIntegral);
if (enableLBSimpleGaussian)
- process("LBSimpleGaussian", lbSimpleGaussian, img_prep, img_lb_sg);
+ process("LBSimpleGaussian", lbSimpleGaussian, img_preProcessor, img_lbSimpleGaussian);
if (enableLBFuzzyGaussian)
- process("LBFuzzyGaussian", lbFuzzyGaussian, img_prep, img_lb_fg);
+ process("LBFuzzyGaussian", lbFuzzyGaussian, img_preProcessor, img_lbFuzzyGaussian);
if (enableLBMixtureOfGaussians)
- process("LBMixtureOfGaussians", lbMixtureOfGaussians, img_prep, img_lb_mog);
+ process("LBMixtureOfGaussians", lbMixtureOfGaussians, img_preProcessor, img_lbMixtureOfGaussians);
if (enableLBAdaptiveSOM)
- process("LBAdaptiveSOM", lbAdaptiveSOM, img_prep, img_lb_som);
+ process("LBAdaptiveSOM", lbAdaptiveSOM, img_preProcessor, img_lbAdaptiveSOM);
if (enableLBFuzzyAdaptiveSOM)
- process("LBFuzzyAdaptiveSOM", lbFuzzyAdaptiveSOM, img_prep, img_lb_fsom);
+ process("LBFuzzyAdaptiveSOM", lbFuzzyAdaptiveSOM, img_preProcessor, img_lbFuzzyAdaptiveSOM);
if (enableLbpMrf)
- process("LbpMrf", lbpMrf, img_prep, img_lbp_mrf);
+ process("LbpMrf", lbpMrf, img_preProcessor, img_lbpMrf);
- if(enableMultiLayerBGS)
+#if CV_MAJOR_VERSION == 2
+ if (enableMultiLayer)
{
- multiLayerBGS->setStatus(MultiLayerBGS::MLBGS_LEARN);
- //multiLayerBGS->setStatus(MultiLayerBGS::MLBGS_DETECT);
- process("MultiLayerBGS", multiLayerBGS, img_prep, img_mlbgs);
+ multiLayer->setStatus(MultiLayer::MLBGS_LEARN);
+ //multiLayer->setStatus(MultiLayer::MLBGS_DETECT);
+ process("MultiLayer", multiLayer, img_preProcessor, img_multiLayer);
}
+#endif
- //if(enablePBAS)
- // process("PBAS", pixelBasedAdaptiveSegmenter, img_prep, img_pt_pbas);
+ if (enablePBAS)
+ process("PBAS", pixelBasedAdaptiveSegmenter, img_preProcessor, img_pixelBasedAdaptiveSegmenter);
if (enableVuMeter)
- process("VuMeter", vuMeter, img_prep, img_vumeter);
+ process("VuMeter", vuMeter, img_preProcessor, img_vumeter);
if (enableKDE)
- process("KDE", kde, img_prep, img_kde);
+ process("KDE", kde, img_preProcessor, img_kde);
if (enableIMBS)
- process("IMBS", imbs, img_prep, img_imbs);
+ process("IMBS", imbs, img_preProcessor, img_imbs);
- if (enableMultiCueBGS)
- process("MultiCueBGS", mcbgs, img_prep, img_mcbgs);
+ if (enableMultiCue)
+ process("MultiCue", multiCue, img_preProcessor, img_multiCue);
- if (enableSigmaDeltaBGS)
- process("SigmaDeltaBGS", sdbgs, img_prep, img_sdbgs);
+ if (enableSigmaDelta)
+ process("SigmaDelta", sigmaDelta, img_preProcessor, img_sigmaDelta);
- if (enableSuBSENSEBGS)
- process("SuBSENSEBGS", ssbgs, img_prep, img_ssbgs);
+ if (enableSuBSENSE)
+ process("SuBSENSE", subSENSE, img_preProcessor, img_subSENSE);
- if (enableLOBSTERBGS)
- process("LOBSTERBGS", lobgs, img_prep, img_lobgs);
+ if (enableLOBSTER)
+ process("LOBSTER", lobster, img_preProcessor, img_lobster);
if (enableForegroundMaskAnalysis)
{
foregroundMaskAnalysis->stopAt = frameToStop;
foregroundMaskAnalysis->img_ref_path = imgref;
- foregroundMaskAnalysis->process(frameNumber, "FrameDifferenceBGS", img_framediff);
- foregroundMaskAnalysis->process(frameNumber, "StaticFrameDifferenceBGS", img_staticfdiff);
- foregroundMaskAnalysis->process(frameNumber, "WeightedMovingMeanBGS", img_wmovmean);
- foregroundMaskAnalysis->process(frameNumber, "WeightedMovingVarianceBGS", img_movvar);
- foregroundMaskAnalysis->process(frameNumber, "MixtureOfGaussianV1BGS", img_mog1);
- foregroundMaskAnalysis->process(frameNumber, "MixtureOfGaussianV2BGS", img_mog2);
- foregroundMaskAnalysis->process(frameNumber, "AdaptiveBackgroundLearning", img_bkgl_fgmask);
+ foregroundMaskAnalysis->process(frameNumber, "FrameDifference", img_frameDifference);
+ foregroundMaskAnalysis->process(frameNumber, "StaticFrameDifference", img_staticFrameDifference);
+ foregroundMaskAnalysis->process(frameNumber, "WeightedMovingMean", img_weightedMovingMean);
+ foregroundMaskAnalysis->process(frameNumber, "WeightedMovingVariance", img_weightedMovingVariance);
+#if CV_MAJOR_VERSION == 2
+ foregroundMaskAnalysis->process(frameNumber, "MixtureOfGaussianV1", img_mixtureOfGaussianV1);
+#endif
+ foregroundMaskAnalysis->process(frameNumber, "MixtureOfGaussianV2", img_mixtureOfGaussianV2);
+ foregroundMaskAnalysis->process(frameNumber, "AdaptiveBackgroundLearning", img_adaptiveBackgroundLearning);
#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
foregroundMaskAnalysis->process(frameNumber, "GMG", img_gmg);
#endif
- foregroundMaskAnalysis->process(frameNumber, "DPAdaptiveMedianBGS", img_adpmed);
- foregroundMaskAnalysis->process(frameNumber, "DPGrimsonGMMBGS", img_grigmm);
- foregroundMaskAnalysis->process(frameNumber, "DPZivkovicAGMMBGS", img_zivgmm);
- foregroundMaskAnalysis->process(frameNumber, "DPMeanBGS", img_tmpmean);
- foregroundMaskAnalysis->process(frameNumber, "DPWrenGABGS", img_wrenga);
- foregroundMaskAnalysis->process(frameNumber, "DPPratiMediodBGS", img_pramed);
- foregroundMaskAnalysis->process(frameNumber, "DPEigenbackgroundBGS", img_eigbkg);
- foregroundMaskAnalysis->process(frameNumber, "DPTextureBGS", img_texbgs);
- foregroundMaskAnalysis->process(frameNumber, "T2FGMM_UM", img_t2fgmm_um);
- foregroundMaskAnalysis->process(frameNumber, "T2FGMM_UV", img_t2fgmm_uv);
- foregroundMaskAnalysis->process(frameNumber, "T2FMRF_UM", img_t2fmrf_um);
- foregroundMaskAnalysis->process(frameNumber, "T2FMRF_UV", img_t2fmrf_uv);
- foregroundMaskAnalysis->process(frameNumber, "FuzzySugenoIntegral", img_fsi);
- foregroundMaskAnalysis->process(frameNumber, "FuzzyChoquetIntegral", img_fci);
- foregroundMaskAnalysis->process(frameNumber, "LBSimpleGaussian", img_lb_sg);
- foregroundMaskAnalysis->process(frameNumber, "LBFuzzyGaussian", img_lb_fg);
- foregroundMaskAnalysis->process(frameNumber, "LBMixtureOfGaussians", img_lb_mog);
- foregroundMaskAnalysis->process(frameNumber, "LBAdaptiveSOM", img_lb_som);
- foregroundMaskAnalysis->process(frameNumber, "LBFuzzyAdaptiveSOM", img_lb_fsom);
- foregroundMaskAnalysis->process(frameNumber, "LbpMrf", img_lbp_mrf);
- foregroundMaskAnalysis->process(frameNumber, "MultiLayerBGS", img_mlbgs);
- //foregroundMaskAnalysis->process(frameNumber, "PBAS", img_pt_pbas);
+ foregroundMaskAnalysis->process(frameNumber, "DPAdaptiveMedian", img_dpAdaptiveMedian);
+ foregroundMaskAnalysis->process(frameNumber, "DPGrimsonGMM", img_dpGrimsonGMM);
+ foregroundMaskAnalysis->process(frameNumber, "DPZivkovicAGMM", img_dpZivkovicAGMM);
+ foregroundMaskAnalysis->process(frameNumber, "DPMean", img_dpTemporalMean);
+ foregroundMaskAnalysis->process(frameNumber, "DPWrenGA", img_dpWrenGA);
+ foregroundMaskAnalysis->process(frameNumber, "DPPratiMediod", img_dpPratiMediod);
+ foregroundMaskAnalysis->process(frameNumber, "DPEigenbackground", img_dpEigenBackground);
+ foregroundMaskAnalysis->process(frameNumber, "DPTexture", img_dpTexture);
+ foregroundMaskAnalysis->process(frameNumber, "T2FGMM_UM", img_type2FuzzyGMM_UM);
+ foregroundMaskAnalysis->process(frameNumber, "T2FGMM_UV", img_type2FuzzyGMM_UV);
+ foregroundMaskAnalysis->process(frameNumber, "T2FMRF_UM", img_type2FuzzyMRF_UM);
+ foregroundMaskAnalysis->process(frameNumber, "T2FMRF_UV", img_type2FuzzyMRF_UV);
+ foregroundMaskAnalysis->process(frameNumber, "FuzzySugenoIntegral", img_fuzzySugenoIntegral);
+ foregroundMaskAnalysis->process(frameNumber, "FuzzyChoquetIntegral", img_fuzzyChoquetIntegral);
+ foregroundMaskAnalysis->process(frameNumber, "LBSimpleGaussian", img_lbSimpleGaussian);
+ foregroundMaskAnalysis->process(frameNumber, "LBFuzzyGaussian", img_lbFuzzyGaussian);
+ foregroundMaskAnalysis->process(frameNumber, "LBMixtureOfGaussians", img_lbMixtureOfGaussians);
+ foregroundMaskAnalysis->process(frameNumber, "LBAdaptiveSOM", img_lbAdaptiveSOM);
+ foregroundMaskAnalysis->process(frameNumber, "LBFuzzyAdaptiveSOM", img_lbFuzzyAdaptiveSOM);
+ foregroundMaskAnalysis->process(frameNumber, "LbpMrf", img_lbpMrf);
+#if CV_MAJOR_VERSION == 2
+ foregroundMaskAnalysis->process(frameNumber, "MultiLayer", img_multiLayer);
+#endif
+ foregroundMaskAnalysis->process(frameNumber, "PBAS", img_pixelBasedAdaptiveSegmenter);
foregroundMaskAnalysis->process(frameNumber, "VuMeter", img_vumeter);
foregroundMaskAnalysis->process(frameNumber, "KDE", img_kde);
foregroundMaskAnalysis->process(frameNumber, "IMBS", img_imbs);
- foregroundMaskAnalysis->process(frameNumber, "MultiCueBGS", img_mcbgs);
- foregroundMaskAnalysis->process(frameNumber, "SigmaDeltaBGS", img_sdbgs);
- foregroundMaskAnalysis->process(frameNumber, "SuBSENSEBGS", img_ssbgs);
- foregroundMaskAnalysis->process(frameNumber, "LOBSTERBGS", img_lobgs);
+ foregroundMaskAnalysis->process(frameNumber, "MultiCue", img_multiCue);
+ foregroundMaskAnalysis->process(frameNumber, "SigmaDelta", img_sigmaDelta);
+ foregroundMaskAnalysis->process(frameNumber, "SuBSENSE", img_subSENSE);
+ foregroundMaskAnalysis->process(frameNumber, "LOBSTER", img_lobster);
}
firstTime = false;
@@ -341,8 +353,8 @@ namespace bgslibrary
void FrameProcessor::finish(void)
{
- /*if(enableMultiLayerBGS)
- multiLayerBGS->finish();
+ /*if(enableMultiLayer)
+ multiLayer->finish();
if(enableLBSimpleGaussian)
lbSimpleGaussian->finish();
@@ -362,17 +374,17 @@ namespace bgslibrary
if (enableForegroundMaskAnalysis)
delete foregroundMaskAnalysis;
- if (enableLOBSTERBGS)
- delete lobgs;
+ if (enableLOBSTER)
+ delete lobster;
- if (enableSuBSENSEBGS)
- delete ssbgs;
+ if (enableSuBSENSE)
+ delete subSENSE;
- if (enableSigmaDeltaBGS)
- delete sdbgs;
+ if (enableSigmaDelta)
+ delete sigmaDelta;
- if (enableMultiCueBGS)
- delete mcbgs;
+ if (enableMultiCue)
+ delete multiCue;
if (enableIMBS)
delete imbs;
@@ -383,11 +395,13 @@ namespace bgslibrary
if (enableVuMeter)
delete vuMeter;
- //if(enablePBAS)
- // delete pixelBasedAdaptiveSegmenter;
+ if (enablePBAS)
+ delete pixelBasedAdaptiveSegmenter;
- if (enableMultiLayerBGS)
- delete multiLayerBGS;
+#if CV_MAJOR_VERSION == 2
+ if (enableMultiLayer)
+ delete multiLayer;
+#endif
if (enableLBFuzzyAdaptiveSOM)
delete lbFuzzyAdaptiveSOM;
@@ -409,7 +423,7 @@ namespace bgslibrary
delete lbpMrf;
#endif
- if(enableFuzzyChoquetIntegral)
+ if (enableFuzzyChoquetIntegral)
delete fuzzyChoquetIntegral;
if (enableFuzzySugenoIntegral)
@@ -427,29 +441,29 @@ namespace bgslibrary
if (enableT2FGMM_UM)
delete type2FuzzyGMM_UM;
- if (enableDPTextureBGS)
- delete textureBGS;
+ if (enableDPTexture)
+ delete dpTexture;
- if (enableDPEigenbackgroundBGS)
- delete eigenBackground;
+ if (enableDPEigenbackground)
+ delete dpEigenBackground;
- if (enableDPPratiMediodBGS)
- delete pratiMediod;
+ if (enableDPPratiMediod)
+ delete dpPratiMediod;
- if (enableDPWrenGABGS)
- delete wrenGA;
+ if (enableDPWrenGA)
+ delete dpWrenGA;
- if (enableDPMeanBGS)
- delete temporalMean;
+ if (enableDPMean)
+ delete dpTemporalMean;
- if (enableDPZivkovicAGMMBGS)
- delete zivkovicAGMM;
+ if (enableDPZivkovicAGMM)
+ delete dpZivkovicAGMM;
- if (enableDPGrimsonGMMBGS)
- delete grimsonGMM;
+ if (enableDPGrimsonGMM)
+ delete dpGrimsonGMM;
- if (enableDPAdaptiveMedianBGS)
- delete adaptiveMedian;
+ if (enableDPAdaptiveMedian)
+ delete dpAdaptiveMedian;
#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
if (enableGMG)
@@ -459,22 +473,24 @@ namespace bgslibrary
if (enableAdaptiveBackgroundLearning)
delete adaptiveBackgroundLearning;
- if (enableMixtureOfGaussianV2BGS)
- delete mixtureOfGaussianV2BGS;
+ if (enableMixtureOfGaussianV2)
+ delete mixtureOfGaussianV2;
- if (enableMixtureOfGaussianV1BGS)
- delete mixtureOfGaussianV1BGS;
+#if CV_MAJOR_VERSION == 2
+ if (enableMixtureOfGaussianV1)
+ delete mixtureOfGaussianV1;
+#endif
- if (enableWeightedMovingVarianceBGS)
+ if (enableWeightedMovingVariance)
delete weightedMovingVariance;
- if (enableWeightedMovingMeanBGS)
+ if (enableWeightedMovingMean)
delete weightedMovingMean;
- if (enableStaticFrameDifferenceBGS)
+ if (enableStaticFrameDifference)
delete staticFrameDifference;
- if (enableFrameDifferenceBGS)
+ if (enableFrameDifference)
delete frameDifference;
if (enablePreProcessor)
@@ -503,25 +519,27 @@ namespace bgslibrary
cvWriteInt(fs, "enableForegroundMaskAnalysis", enableForegroundMaskAnalysis);
- cvWriteInt(fs, "enableFrameDifferenceBGS", enableFrameDifferenceBGS);
- cvWriteInt(fs, "enableStaticFrameDifferenceBGS", enableStaticFrameDifferenceBGS);
- cvWriteInt(fs, "enableWeightedMovingMeanBGS", enableWeightedMovingMeanBGS);
- cvWriteInt(fs, "enableWeightedMovingVarianceBGS", enableWeightedMovingVarianceBGS);
- cvWriteInt(fs, "enableMixtureOfGaussianV1BGS", enableMixtureOfGaussianV1BGS);
- cvWriteInt(fs, "enableMixtureOfGaussianV2BGS", enableMixtureOfGaussianV2BGS);
+ cvWriteInt(fs, "enableFrameDifference", enableFrameDifference);
+ cvWriteInt(fs, "enableStaticFrameDifference", enableStaticFrameDifference);
+ cvWriteInt(fs, "enableWeightedMovingMean", enableWeightedMovingMean);
+ cvWriteInt(fs, "enableWeightedMovingVariance", enableWeightedMovingVariance);
+#if CV_MAJOR_VERSION == 2
+ cvWriteInt(fs, "enableMixtureOfGaussianV1", enableMixtureOfGaussianV1);
+#endif
+ cvWriteInt(fs, "enableMixtureOfGaussianV2", enableMixtureOfGaussianV2);
cvWriteInt(fs, "enableAdaptiveBackgroundLearning", enableAdaptiveBackgroundLearning);
#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
cvWriteInt(fs, "enableGMG", enableGMG);
#endif
- cvWriteInt(fs, "enableDPAdaptiveMedianBGS", enableDPAdaptiveMedianBGS);
- cvWriteInt(fs, "enableDPGrimsonGMMBGS", enableDPGrimsonGMMBGS);
- cvWriteInt(fs, "enableDPZivkovicAGMMBGS", enableDPZivkovicAGMMBGS);
- cvWriteInt(fs, "enableDPMeanBGS", enableDPMeanBGS);
- cvWriteInt(fs, "enableDPWrenGABGS", enableDPWrenGABGS);
- cvWriteInt(fs, "enableDPPratiMediodBGS", enableDPPratiMediodBGS);
- cvWriteInt(fs, "enableDPEigenbackgroundBGS", enableDPEigenbackgroundBGS);
- cvWriteInt(fs, "enableDPTextureBGS", enableDPTextureBGS);
+ cvWriteInt(fs, "enableDPAdaptiveMedian", enableDPAdaptiveMedian);
+ cvWriteInt(fs, "enableDPGrimsonGMM", enableDPGrimsonGMM);
+ cvWriteInt(fs, "enableDPZivkovicAGMM", enableDPZivkovicAGMM);
+ cvWriteInt(fs, "enableDPMean", enableDPMean);
+ cvWriteInt(fs, "enableDPWrenGA", enableDPWrenGA);
+ cvWriteInt(fs, "enableDPPratiMediod", enableDPPratiMediod);
+ cvWriteInt(fs, "enableDPEigenbackground", enableDPEigenbackground);
+ cvWriteInt(fs, "enableDPTexture", enableDPTexture);
cvWriteInt(fs, "enableT2FGMM_UM", enableT2FGMM_UM);
cvWriteInt(fs, "enableT2FGMM_UV", enableT2FGMM_UV);
@@ -538,15 +556,17 @@ namespace bgslibrary
cvWriteInt(fs, "enableLbpMrf", enableLbpMrf);
- cvWriteInt(fs, "enableMultiLayerBGS", enableMultiLayerBGS);
- //cvWriteInt(fs, "enablePBAS", enablePBAS);
+#if CV_MAJOR_VERSION == 2
+ cvWriteInt(fs, "enableMultiLayer", enableMultiLayer);
+#endif
+ cvWriteInt(fs, "enablePBAS", enablePBAS);
cvWriteInt(fs, "enableVuMeter", enableVuMeter);
cvWriteInt(fs, "enableKDE", enableKDE);
cvWriteInt(fs, "enableIMBS", enableIMBS);
- cvWriteInt(fs, "enableMultiCueBGS", enableMultiCueBGS);
- cvWriteInt(fs, "enableSigmaDeltaBGS", enableSigmaDeltaBGS);
- cvWriteInt(fs, "enableSuBSENSEBGS", enableSuBSENSEBGS);
- cvWriteInt(fs, "enableLOBSTERBGS", enableLOBSTERBGS);
+ cvWriteInt(fs, "enableMultiCue", enableMultiCue);
+ cvWriteInt(fs, "enableSigmaDelta", enableSigmaDelta);
+ cvWriteInt(fs, "enableSuBSENSE", enableSuBSENSE);
+ cvWriteInt(fs, "enableLOBSTER", enableLOBSTER);
cvReleaseFileStorage(&fs);
}
@@ -561,25 +581,27 @@ namespace bgslibrary
enableForegroundMaskAnalysis = cvReadIntByName(fs, 0, "enableForegroundMaskAnalysis", false);
- enableFrameDifferenceBGS = cvReadIntByName(fs, 0, "enableFrameDifferenceBGS", false);
- enableStaticFrameDifferenceBGS = cvReadIntByName(fs, 0, "enableStaticFrameDifferenceBGS", false);
- enableWeightedMovingMeanBGS = cvReadIntByName(fs, 0, "enableWeightedMovingMeanBGS", false);
- enableWeightedMovingVarianceBGS = cvReadIntByName(fs, 0, "enableWeightedMovingVarianceBGS", false);
- enableMixtureOfGaussianV1BGS = cvReadIntByName(fs, 0, "enableMixtureOfGaussianV1BGS", false);
- enableMixtureOfGaussianV2BGS = cvReadIntByName(fs, 0, "enableMixtureOfGaussianV2BGS", false);
+ enableFrameDifference = cvReadIntByName(fs, 0, "enableFrameDifference", false);
+ enableStaticFrameDifference = cvReadIntByName(fs, 0, "enableStaticFrameDifference", false);
+ enableWeightedMovingMean = cvReadIntByName(fs, 0, "enableWeightedMovingMean", false);
+ enableWeightedMovingVariance = cvReadIntByName(fs, 0, "enableWeightedMovingVariance", false);
+#if CV_MAJOR_VERSION == 2
+ enableMixtureOfGaussianV1 = cvReadIntByName(fs, 0, "enableMixtureOfGaussianV1", false);
+#endif
+ enableMixtureOfGaussianV2 = cvReadIntByName(fs, 0, "enableMixtureOfGaussianV2", false);
enableAdaptiveBackgroundLearning = cvReadIntByName(fs, 0, "enableAdaptiveBackgroundLearning", false);
#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
enableGMG = cvReadIntByName(fs, 0, "enableGMG", false);
#endif
- enableDPAdaptiveMedianBGS = cvReadIntByName(fs, 0, "enableDPAdaptiveMedianBGS", false);
- enableDPGrimsonGMMBGS = cvReadIntByName(fs, 0, "enableDPGrimsonGMMBGS", false);
- enableDPZivkovicAGMMBGS = cvReadIntByName(fs, 0, "enableDPZivkovicAGMMBGS", false);
- enableDPMeanBGS = cvReadIntByName(fs, 0, "enableDPMeanBGS", false);
- enableDPWrenGABGS = cvReadIntByName(fs, 0, "enableDPWrenGABGS", false);
- enableDPPratiMediodBGS = cvReadIntByName(fs, 0, "enableDPPratiMediodBGS", false);
- enableDPEigenbackgroundBGS = cvReadIntByName(fs, 0, "enableDPEigenbackgroundBGS", false);
- enableDPTextureBGS = cvReadIntByName(fs, 0, "enableDPTextureBGS", false);
+ enableDPAdaptiveMedian = cvReadIntByName(fs, 0, "enableDPAdaptiveMedian", false);
+ enableDPGrimsonGMM = cvReadIntByName(fs, 0, "enableDPGrimsonGMM", false);
+ enableDPZivkovicAGMM = cvReadIntByName(fs, 0, "enableDPZivkovicAGMM", false);
+ enableDPMean = cvReadIntByName(fs, 0, "enableDPMean", false);
+ enableDPWrenGA = cvReadIntByName(fs, 0, "enableDPWrenGA", false);
+ enableDPPratiMediod = cvReadIntByName(fs, 0, "enableDPPratiMediod", false);
+ enableDPEigenbackground = cvReadIntByName(fs, 0, "enableDPEigenbackground", false);
+ enableDPTexture = cvReadIntByName(fs, 0, "enableDPTexture", false);
enableT2FGMM_UM = cvReadIntByName(fs, 0, "enableT2FGMM_UM", false);
enableT2FGMM_UV = cvReadIntByName(fs, 0, "enableT2FGMM_UV", false);
@@ -596,15 +618,17 @@ namespace bgslibrary
enableLbpMrf = cvReadIntByName(fs, 0, "enableLbpMrf", false);
- enableMultiLayerBGS = cvReadIntByName(fs, 0, "enableMultiLayerBGS", false);
- //enablePBAS = cvReadIntByName(fs, 0, "enablePBAS", false);
+#if CV_MAJOR_VERSION == 2
+ enableMultiLayer = cvReadIntByName(fs, 0, "enableMultiLayer", false);
+#endif
+ enablePBAS = cvReadIntByName(fs, 0, "enablePBAS", false);
enableVuMeter = cvReadIntByName(fs, 0, "enableVuMeter", false);
enableKDE = cvReadIntByName(fs, 0, "enableKDE", false);
enableIMBS = cvReadIntByName(fs, 0, "enableIMBS", false);
- enableMultiCueBGS = cvReadIntByName(fs, 0, "enableMultiCueBGS", false);
- enableSigmaDeltaBGS = cvReadIntByName(fs, 0, "enableSigmaDeltaBGS", false);
- enableSuBSENSEBGS = cvReadIntByName(fs, 0, "enableSuBSENSEBGS", false);
- enableLOBSTERBGS = cvReadIntByName(fs, 0, "enableLOBSTERBGS", false);
+ enableMultiCue = cvReadIntByName(fs, 0, "enableMultiCue", false);
+ enableSigmaDelta = cvReadIntByName(fs, 0, "enableSigmaDelta", false);
+ enableSuBSENSE = cvReadIntByName(fs, 0, "enableSuBSENSE", false);
+ enableLOBSTER = cvReadIntByName(fs, 0, "enableLOBSTER", false);
cvReleaseFileStorage(&fs);
}
diff --git a/FrameProcessor.h b/FrameProcessor.h
index 0bb854e..228fa4c 100644
--- a/FrameProcessor.h
+++ b/FrameProcessor.h
@@ -21,56 +21,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include "PreProcessor.h"
#include "package_bgs/IBGS.h"
-
-#include "package_bgs/FrameDifferenceBGS.h"
-#include "package_bgs/StaticFrameDifferenceBGS.h"
-#include "package_bgs/WeightedMovingMeanBGS.h"
-#include "package_bgs/WeightedMovingVarianceBGS.h"
-#include "package_bgs/MixtureOfGaussianV1BGS.h"
-#include "package_bgs/MixtureOfGaussianV2BGS.h"
-#include "package_bgs/AdaptiveBackgroundLearning.h"
-#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
-#include "package_bgs/GMG.h"
-#endif
-
-#include "package_bgs/dp/DPAdaptiveMedianBGS.h"
-#include "package_bgs/dp/DPGrimsonGMMBGS.h"
-#include "package_bgs/dp/DPZivkovicAGMMBGS.h"
-#include "package_bgs/dp/DPMeanBGS.h"
-#include "package_bgs/dp/DPWrenGABGS.h"
-#include "package_bgs/dp/DPPratiMediodBGS.h"
-#include "package_bgs/dp/DPEigenbackgroundBGS.h"
-#include "package_bgs/dp/DPTextureBGS.h"
-
-#include "package_bgs/tb/T2FGMM_UM.h"
-#include "package_bgs/tb/T2FGMM_UV.h"
-#include "package_bgs/tb/T2FMRF_UM.h"
-#include "package_bgs/tb/T2FMRF_UV.h"
-#include "package_bgs/tb/FuzzySugenoIntegral.h"
-#include "package_bgs/tb/FuzzyChoquetIntegral.h"
-
-#include "package_bgs/lb/LBSimpleGaussian.h"
-#include "package_bgs/lb/LBFuzzyGaussian.h"
-#include "package_bgs/lb/LBMixtureOfGaussians.h"
-#include "package_bgs/lb/LBAdaptiveSOM.h"
-#include "package_bgs/lb/LBFuzzyAdaptiveSOM.h"
-
-#include "package_bgs/ck/LbpMrf.h"
-
-#include "package_bgs/jmo/MultiLayerBGS.h"
-// The PBAS algorithm was removed from BGSLibrary because it is
-// based on patented algorithm ViBE
-// http://www2.ulg.ac.be/telecom/research/vibe/
-//#include "package_bgs/pt/PixelBasedAdaptiveSegmenter.h"
-#include "package_bgs/av/VuMeter.h"
-#include "package_bgs/ae/KDE.h"
-#include "package_bgs/db/IndependentMultimodalBGS.h"
-#include "package_bgs/sjn/SJN_MultiCueBGS.h"
-#include "package_bgs/bl/SigmaDeltaBGS.h"
-
-#include "package_bgs/pl/SuBSENSE.h"
-#include "package_bgs/pl/LOBSTER.h"
-
+#include "package_bgs/bgslibrary.h"
#include "package_analysis/ForegroundMaskAnalysis.h"
namespace bgslibrary
@@ -84,35 +35,37 @@ namespace bgslibrary
double duration;
std::string tictoc;
- cv::Mat img_prep;
+ cv::Mat img_preProcessor;
PreProcessor* preProcessor;
bool enablePreProcessor;
- cv::Mat img_framediff;
- FrameDifferenceBGS* frameDifference;
- bool enableFrameDifferenceBGS;
+ cv::Mat img_frameDifference;
+ FrameDifference* frameDifference;
+ bool enableFrameDifference;
- cv::Mat img_staticfdiff;
- StaticFrameDifferenceBGS* staticFrameDifference;
- bool enableStaticFrameDifferenceBGS;
+ cv::Mat img_staticFrameDifference;
+ StaticFrameDifference* staticFrameDifference;
+ bool enableStaticFrameDifference;
- cv::Mat img_wmovmean;
- WeightedMovingMeanBGS* weightedMovingMean;
- bool enableWeightedMovingMeanBGS;
+ cv::Mat img_weightedMovingMean;
+ WeightedMovingMean* weightedMovingMean;
+ bool enableWeightedMovingMean;
- cv::Mat img_movvar;
- WeightedMovingVarianceBGS* weightedMovingVariance;
- bool enableWeightedMovingVarianceBGS;
+ cv::Mat img_weightedMovingVariance;
+ WeightedMovingVariance* weightedMovingVariance;
+ bool enableWeightedMovingVariance;
- cv::Mat img_mog1;
- MixtureOfGaussianV1BGS* mixtureOfGaussianV1BGS;
- bool enableMixtureOfGaussianV1BGS;
+#if CV_MAJOR_VERSION == 2
+ cv::Mat img_mixtureOfGaussianV1;
+ MixtureOfGaussianV1* mixtureOfGaussianV1;
+ bool enableMixtureOfGaussianV1;
+#endif
- cv::Mat img_mog2;
- MixtureOfGaussianV2BGS* mixtureOfGaussianV2BGS;
- bool enableMixtureOfGaussianV2BGS;
+ cv::Mat img_mixtureOfGaussianV2;
+ MixtureOfGaussianV2* mixtureOfGaussianV2;
+ bool enableMixtureOfGaussianV2;
- cv::Mat img_bkgl_fgmask;
+ cv::Mat img_adaptiveBackgroundLearning;
AdaptiveBackgroundLearning* adaptiveBackgroundLearning;
bool enableAdaptiveBackgroundLearning;
@@ -122,93 +75,95 @@ namespace bgslibrary
bool enableGMG;
#endif
- cv::Mat img_adpmed;
- DPAdaptiveMedianBGS* adaptiveMedian;
- bool enableDPAdaptiveMedianBGS;
+ cv::Mat img_dpAdaptiveMedian;
+ DPAdaptiveMedian* dpAdaptiveMedian;
+ bool enableDPAdaptiveMedian;
- cv::Mat img_grigmm;
- DPGrimsonGMMBGS* grimsonGMM;
- bool enableDPGrimsonGMMBGS;
+ cv::Mat img_dpGrimsonGMM;
+ DPGrimsonGMM* dpGrimsonGMM;
+ bool enableDPGrimsonGMM;
- cv::Mat img_zivgmm;
- DPZivkovicAGMMBGS* zivkovicAGMM;
- bool enableDPZivkovicAGMMBGS;
+ cv::Mat img_dpZivkovicAGMM;
+ DPZivkovicAGMM* dpZivkovicAGMM;
+ bool enableDPZivkovicAGMM;
- cv::Mat img_tmpmean;
- DPMeanBGS* temporalMean;
- bool enableDPMeanBGS;
+ cv::Mat img_dpTemporalMean;
+ DPMean* dpTemporalMean;
+ bool enableDPMean;
- cv::Mat img_wrenga;
- DPWrenGABGS* wrenGA;
- bool enableDPWrenGABGS;
+ cv::Mat img_dpWrenGA;
+ DPWrenGA* dpWrenGA;
+ bool enableDPWrenGA;
- cv::Mat img_pramed;
- DPPratiMediodBGS* pratiMediod;
- bool enableDPPratiMediodBGS;
+ cv::Mat img_dpPratiMediod;
+ DPPratiMediod* dpPratiMediod;
+ bool enableDPPratiMediod;
- cv::Mat img_eigbkg;
- DPEigenbackgroundBGS* eigenBackground;
- bool enableDPEigenbackgroundBGS;
+ cv::Mat img_dpEigenBackground;
+ DPEigenbackground* dpEigenBackground;
+ bool enableDPEigenbackground;
- cv::Mat img_texbgs;
- DPTextureBGS* textureBGS;
- bool enableDPTextureBGS;
+ cv::Mat img_dpTexture;
+ DPTexture* dpTexture;
+ bool enableDPTexture;
- cv::Mat img_t2fgmm_um;
+ cv::Mat img_type2FuzzyGMM_UM;
T2FGMM_UM* type2FuzzyGMM_UM;
bool enableT2FGMM_UM;
- cv::Mat img_t2fgmm_uv;
+ cv::Mat img_type2FuzzyGMM_UV;
T2FGMM_UV* type2FuzzyGMM_UV;
bool enableT2FGMM_UV;
- cv::Mat img_t2fmrf_um;
+ cv::Mat img_type2FuzzyMRF_UM;
T2FMRF_UM* type2FuzzyMRF_UM;
bool enableT2FMRF_UM;
- cv::Mat img_t2fmrf_uv;
+ cv::Mat img_type2FuzzyMRF_UV;
T2FMRF_UV* type2FuzzyMRF_UV;
bool enableT2FMRF_UV;
- cv::Mat img_fsi;
+ cv::Mat img_fuzzySugenoIntegral;
FuzzySugenoIntegral* fuzzySugenoIntegral;
bool enableFuzzySugenoIntegral;
- cv::Mat img_fci;
+ cv::Mat img_fuzzyChoquetIntegral;
FuzzyChoquetIntegral* fuzzyChoquetIntegral;
bool enableFuzzyChoquetIntegral;
- cv::Mat img_lb_sg;
+ cv::Mat img_lbSimpleGaussian;
LBSimpleGaussian* lbSimpleGaussian;
bool enableLBSimpleGaussian;
- cv::Mat img_lb_fg;
+ cv::Mat img_lbFuzzyGaussian;
LBFuzzyGaussian* lbFuzzyGaussian;
bool enableLBFuzzyGaussian;
- cv::Mat img_lb_mog;
+ cv::Mat img_lbMixtureOfGaussians;
LBMixtureOfGaussians* lbMixtureOfGaussians;
bool enableLBMixtureOfGaussians;
- cv::Mat img_lb_som;
+ cv::Mat img_lbAdaptiveSOM;
LBAdaptiveSOM* lbAdaptiveSOM;
bool enableLBAdaptiveSOM;
- cv::Mat img_lb_fsom;
+ cv::Mat img_lbFuzzyAdaptiveSOM;
LBFuzzyAdaptiveSOM* lbFuzzyAdaptiveSOM;
bool enableLBFuzzyAdaptiveSOM;
- cv::Mat img_lbp_mrf;
- LbpMrf* lbpMrf;
+ cv::Mat img_lbpMrf;
+ LBP_MRF* lbpMrf;
bool enableLbpMrf;
- cv::Mat img_mlbgs;
- MultiLayerBGS* multiLayerBGS;
- bool enableMultiLayerBGS;
+#if CV_MAJOR_VERSION == 2
+ cv::Mat img_multiLayer;
+ MultiLayer* multiLayer;
+ bool enableMultiLayer;
+#endif
- //cv::Mat img_pt_pbas;
- //PixelBasedAdaptiveSegmenter* pixelBasedAdaptiveSegmenter;
- //bool enablePBAS;
+ cv::Mat img_pixelBasedAdaptiveSegmenter;
+ PixelBasedAdaptiveSegmenter* pixelBasedAdaptiveSegmenter;
+ bool enablePBAS;
cv::Mat img_vumeter;
VuMeter* vuMeter;
@@ -219,24 +174,24 @@ namespace bgslibrary
bool enableKDE;
cv::Mat img_imbs;
- IndependentMultimodalBGS* imbs;
+ IndependentMultimodal* imbs;
bool enableIMBS;
- cv::Mat img_mcbgs;
- SJN_MultiCueBGS* mcbgs;
- bool enableMultiCueBGS;
+ cv::Mat img_multiCue;
+ MultiCue* multiCue;
+ bool enableMultiCue;
- cv::Mat img_sdbgs;
- SigmaDeltaBGS* sdbgs;
- bool enableSigmaDeltaBGS;
+ cv::Mat img_sigmaDelta;
+ SigmaDelta* sigmaDelta;
+ bool enableSigmaDelta;
- cv::Mat img_ssbgs;
- SuBSENSEBGS* ssbgs;
- bool enableSuBSENSEBGS;
+ cv::Mat img_subSENSE;
+ SuBSENSE* subSENSE;
+ bool enableSuBSENSE;
- cv::Mat img_lobgs;
- LOBSTERBGS* lobgs;
- bool enableLOBSTERBGS;
+ cv::Mat img_lobster;
+ LOBSTER* lobster;
+ bool enableLOBSTER;
ForegroundMaskAnalysis* foregroundMaskAnalysis;
bool enableForegroundMaskAnalysis;
diff --git a/Main.cpp b/Main.cpp
index 1d170ad..7a406d9 100644
--- a/Main.cpp
+++ b/Main.cpp
@@ -29,7 +29,7 @@ namespace bgslibrary
static void start(int argc, const char **argv)
{
std::cout << "-----------------------------------------" << std::endl;
- std::cout << "Background Subtraction Library v1.9.2 " << std::endl;
+ std::cout << "Background Subtraction Library v2.0.0 " << std::endl;
std::cout << "http://code.google.com/p/bgslibrary " << std::endl;
std::cout << "by: " << std::endl;
std::cout << "Andrews Sobral (andrewssobral@gmail.com) " << std::endl;
diff --git a/PreProcessor.cpp b/PreProcessor.cpp
index 6f4ebbe..4c13f7e 100644
--- a/PreProcessor.cpp
+++ b/PreProcessor.cpp
@@ -95,7 +95,7 @@ namespace bgslibrary
cv2DRotationMatrix(center, angle, 1.0, mapMatrix);
cvWarpAffine(image, rotatedImage, mapMatrix, CV_INTER_LINEAR + CV_WARP_FILL_OUTLIERS, cvScalarAll(0));
- cv::Mat img_rot(rotatedImage);
+ cv::Mat img_rot = cv::cvarrToMat(rotatedImage);
img_rot.copyTo(img_output);
cvReleaseImage(&image);
diff --git a/PreProcessor.h b/PreProcessor.h
index da46cce..2e6e61c 100644
--- a/PreProcessor.h
+++ b/PreProcessor.h
@@ -19,7 +19,6 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <iostream>
#include <opencv2/opencv.hpp>
-
namespace bgslibrary
{
class PreProcessor
diff --git a/README.md b/README.md
index a35389a..3b8a3cb 100644
--- a/README.md
+++ b/README.md
@@ -4,13 +4,13 @@ A Background Subtraction Library
[](https://youtu.be/_UbERwuQ0OU)
-Last Page Update: **12/03/2017**
+Last Page Update: **18/03/2017**
-Latest Library Version: **1.9.2** (see [Release Notes](https://github.com/andrewssobral/bgslibrary/wiki/Release-notes) for more info)
+Latest Library Version: **2.0.0** (see [Release Notes](https://github.com/andrewssobral/bgslibrary/wiki/Release-notes) for more info)
-The **BGSLibrary** was developed by [Andrews Sobral](http://andrewssobral.wixsite.com/home) and provides an easy-to-use C++ framework based on [OpenCV](http://www.opencv.org/) to perform foreground-background separation in videos. The bgslibrary compiles under Windows, Linux, and Mac OS X. Currently the library contains **37** algorithms. The source code is available under [GNU GPLv3 license](https://www.gnu.org/licenses/gpl-3.0.en.html), the library is free and open source for academic purposes.
+The **BGSLibrary** was developed by [Andrews Sobral](http://andrewssobral.wixsite.com/home) and provides an easy-to-use C++ framework based on [OpenCV](http://www.opencv.org/) to perform foreground-background separation in videos. The bgslibrary is compatible with OpenCV 2.x and 3.x, and compiles under Windows, Linux, and Mac OS X. Currently the library contains **40** algorithms. The source code is available under [GNU GPLv3 license](https://www.gnu.org/licenses/gpl-3.0.en.html), the library is free and open source for academic purposes.
-Note: the BGSLibrary is based on OpenCV 2.X, if you want to use with OpenCV 3.x please check-out our [opencv3](https://github.com/andrewssobral/bgslibrary/tree/opencv3) branch.
+***Note: The [opencv3](https://github.com/andrewssobral/bgslibrary/tree/opencv3) branch will be deprecated.***
* [List of available algorithms](https://github.com/andrewssobral/bgslibrary/wiki/List-of-available-algorithms)
* [Algorithms benchmark](https://github.com/andrewssobral/bgslibrary/wiki/Algorithms-benchmark)
@@ -77,6 +77,7 @@ Some algorithms of the BGSLibrary were used successfully in the following papers
* (2013) Sobral, Andrews; Oliveira, Luciano; Schnitman, Leizer; Souza, Felippe. (**Best Paper Award**) Highway Traffic Congestion Classification Using Holistic Properties. In International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA'2013), Innsbruck, Austria, Feb 2013. ([Online](http://dx.doi.org/10.2316/P.2013.798-105)) ([PDF](http://www.researchgate.net/publication/233427564_HIGHWAY_TRAFFIC_CONGESTION_CLASSIFICATION_USING_HOLISTIC_PROPERTIES))
+
Videos
------
diff --git a/VideoAnalysis.cpp b/VideoAnalysis.cpp
index 1e46542..9c8020a 100644
--- a/VideoAnalysis.cpp
+++ b/VideoAnalysis.cpp
@@ -18,7 +18,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
namespace bgslibrary
{
- VideoAnalysis::VideoAnalysis() : use_file(false), use_camera(false), cameraIndex(0), use_comp(false), frameToStop(0)
+ VideoAnalysis::VideoAnalysis() :
+ use_file(false), use_camera(false), cameraIndex(0),
+ use_comp(false), frameToStop(0)
{
std::cout << "VideoAnalysis()" << std::endl;
}
@@ -32,8 +34,9 @@ namespace bgslibrary
{
bool flag = false;
+#if CV_MAJOR_VERSION == 2
const char* keys =
- "{hp|help|false|Print help message}"
+ "{hp|help|false|Print this message}"
"{uf|use_file|false|Use video file}"
"{fn|filename||Specify video file}"
"{uc|use_cam|false|Use camera}"
@@ -42,21 +45,63 @@ namespace bgslibrary
"{st|stopAt|0|Frame number to stop}"
"{im|imgref||Specify image file}"
;
+#elif CV_MAJOR_VERSION == 3
+ const std::string keys =
+ "{h help ? | | Print this message }"
+ "{uf use_file |false| Use a video file }"
+ "{fn filename | | Specify a video file }"
+ "{uc use_cam |false| Use a webcamera }"
+ "{ca camera | 0 | Specify camera index }"
+ "{co use_comp |false| Use mask comparator }"
+ "{st stopAt | 0 | Frame number to stop }"
+ "{im imgref | | Specify a image file }"
+ ;
+#endif
+
cv::CommandLineParser cmd(argc, argv, keys);
+#if CV_MAJOR_VERSION == 2
if (argc <= 1 || cmd.get<bool>("help") == true)
{
std::cout << "Usage: " << argv[0] << " [options]" << std::endl;
- std::cout << "Avaible options:" << std::endl;
+ std::cout << "Available options:" << std::endl;
cmd.printParams();
return false;
}
+#elif CV_MAJOR_VERSION == 3
+ if (argc <= 1 || cmd.has("help"))
+ {
+ std::cout << "Usage: " << argv[0] << " [options]" << std::endl;
+ std::cout << "Available options:" << std::endl;
+ cmd.printMessage();
+ return false;
+ }
+ if (!cmd.check())
+ {
+ cmd.printErrors();
+ return false;
+ }
+#endif
+
+ use_file = cmd.get<bool>("uf"); //use_file
+ filename = cmd.get<std::string>("fn"); //filename
+ use_camera = cmd.get<bool>("uc"); //use_cam
+ cameraIndex = cmd.get<int>("ca"); //camera
+ use_comp = cmd.get<bool>("co"); //use_comp
+ frameToStop = cmd.get<int>("st"); //stopAt
+ imgref = cmd.get<std::string>("im"); //imgref
+
+ std::cout << "use_file: " << use_file << std::endl;
+ std::cout << "filename: " << filename << std::endl;
+ std::cout << "use_camera: " << use_camera << std::endl;
+ std::cout << "cameraIndex: " << cameraIndex << std::endl;
+ std::cout << "use_comp: " << use_comp << std::endl;
+ std::cout << "frameToStop: " << frameToStop << std::endl;
+ std::cout << "imgref: " << imgref << std::endl;
+ //return false;
- use_file = cmd.get<bool>("use_file");
if (use_file)
{
- filename = cmd.get<std::string>("filename");
-
if (filename.empty())
{
std::cout << "Specify filename" << std::endl;
@@ -66,26 +111,15 @@ namespace bgslibrary
flag = true;
}
- use_camera = cmd.get<bool>("use_cam");
if (use_camera)
- {
- cameraIndex = cmd.get<int>("camera");
flag = true;
- }
- if (flag == true)
+ if (flag && use_comp)
{
- use_comp = cmd.get<bool>("use_comp");
- if (use_comp)
+ if (imgref.empty())
{
- frameToStop = cmd.get<int>("stopAt");
- imgref = cmd.get<std::string>("imgref");
-
- if (imgref.empty())
- {
- std::cout << "Specify image reference" << std::endl;
- return false;
- }
+ std::cout << "Specify image reference" << std::endl;
+ return false;
}
}
diff --git a/VideoCapture.cpp b/VideoCapture.cpp
index 4de5b90..b302a3f 100644
--- a/VideoCapture.cpp
+++ b/VideoCapture.cpp
@@ -15,6 +15,7 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "VideoCapture.h"
+#include <opencv2/highgui/highgui_c.h>
namespace bgslibrary
{
@@ -74,8 +75,11 @@ namespace bgslibrary
}
}
- VideoCapture::VideoCapture() : key(0), start_time(0), delta_time(0), freq(0), fps(0), frameNumber(0), stopAt(0),
- useCamera(false), useVideo(false), input_resize_percent(100), showOutput(true), enableFlip(false)
+ VideoCapture::VideoCapture() :
+ key(0), start_time(0), delta_time(0), freq(0),
+ fps(0), frameNumber(0), stopAt(0), useCamera(false),
+ useVideo(false), input_resize_percent(100), showOutput(true),
+ enableFlip(false), cameraIndex(0)
{
std::cout << "VideoCapture()" << std::endl;
}
@@ -101,10 +105,10 @@ namespace bgslibrary
void VideoCapture::setUpCamera()
{
std::cout << "Camera index:" << cameraIndex << std::endl;
- capture = cvCaptureFromCAM(cameraIndex);
+ capture.open(cameraIndex);
- if (!capture)
- std::cerr << "Cannot open initialize webcam!\n" << std::endl;
+ if (!capture.isOpened())
+ std::cerr << "Cannot initialize webcam!\n" << std::endl;
}
void VideoCapture::setVideo(std::string filename)
@@ -117,10 +121,13 @@ namespace bgslibrary
void VideoCapture::setUpVideo()
{
- capture = cvCaptureFromFile(videoFileName.c_str());
+ std::cout << "Openning: " << videoFileName << std::endl;
+ capture.open(videoFileName.c_str());
- if (!capture)
+ if (!capture.isOpened())
std::cerr << "Cannot open video file " << videoFileName << std::endl;
+ else
+ std::cout << "OK" << std::endl;
}
void VideoCapture::start()
@@ -129,17 +136,21 @@ namespace bgslibrary
if (useCamera) setUpCamera();
if (useVideo) setUpVideo();
- if (!capture) std::cerr << "Capture error..." << std::endl;
+ //if (!capture) std::cerr << "Capture error..." << std::endl;
- int input_fps = cvGetCaptureProperty(capture, CV_CAP_PROP_FPS);
+ int input_fps = capture.get(CV_CAP_PROP_FPS);
std::cout << "input->fps:" << input_fps << std::endl;
+ /*
IplImage* frame1 = cvQueryFrame(capture);
- frame = cvCreateImage(cvSize((int)((frame1->width*input_resize_percent) / 100), (int)((frame1->height*input_resize_percent) / 100)), frame1->depth, frame1->nChannels);
+ frame = cvCreateImage(cvSize(
+ (int)((frame1->width*input_resize_percent) / 100),
+ (int)((frame1->height*input_resize_percent) / 100)), frame1->depth, frame1->nChannels);
//cvCreateImage(cvSize(frame1->width/input_resize_factor, frame1->height/input_resize_factor), frame1->depth, frame1->nChannels);
std::cout << "input->resize_percent:" << input_resize_percent << std::endl;
std::cout << "input->width:" << frame->width << std::endl;
std::cout << "input->height:" << frame->height << std::endl;
+ */
double loopDelay = 33.333;
if (input_fps > 0)
@@ -152,13 +163,14 @@ namespace bgslibrary
{
frameNumber++;
- frame1 = cvQueryFrame(capture);
- if (!frame1) break;
+ cv::Mat frame;
+ capture >> frame;
+ if (frame.empty()) break;
- cvResize(frame1, frame);
+ //cvResize(frame1, frame);
- if (enableFlip)
- cvFlip(frame, frame, 0);
+ //if (enableFlip)
+ // cvFlip(frame, frame, 0);
if (VC_ROI::use_roi == true && VC_ROI::roi_defined == false && firstTime == true)
{
@@ -166,7 +178,9 @@ namespace bgslibrary
do
{
- cv::Mat img_input(frame);
+ //cv::Mat img_input = cv::cvarrToMat(frame);
+ cv::Mat img_input;
+ frame.copyTo(img_input);
if (showOutput)
{
@@ -202,11 +216,13 @@ namespace bgslibrary
if (VC_ROI::use_roi == true && VC_ROI::roi_defined == true)
{
- CvRect rect = cvRect(VC_ROI::roi_x0, VC_ROI::roi_y0, VC_ROI::roi_x1 - VC_ROI::roi_x0, VC_ROI::roi_y1 - VC_ROI::roi_y0);
- cvSetImageROI(frame, rect);
+ cv::Rect roi(VC_ROI::roi_x0, VC_ROI::roi_y0, VC_ROI::roi_x1 - VC_ROI::roi_x0, VC_ROI::roi_y1 - VC_ROI::roi_y0);
+ frame = frame(roi);
}
- cv::Mat img_input(frame);
+ //cv::Mat img_input = cv::cvarrToMat(frame);
+ cv::Mat img_input;
+ frame.copyTo(img_input);
if (showOutput)
cv::imshow("Input", img_input);
@@ -221,7 +237,7 @@ namespace bgslibrary
fps = freq / delta_time;
//std::cout << "FPS: " << fps << std::endl;
- cvResetImageROI(frame);
+ //cvResetImageROI(frame);
key = cvWaitKey(loopDelay);
//std::cout << "key: " << key << std::endl;
@@ -238,7 +254,7 @@ namespace bgslibrary
firstTime = false;
} while (1);
- cvReleaseCapture(&capture);
+ capture.release();
}
void VideoCapture::saveConfig()
diff --git a/VideoCapture.h b/VideoCapture.h
index a8ba2ff..0e88c87 100644
--- a/VideoCapture.h
+++ b/VideoCapture.h
@@ -18,7 +18,8 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <iostream>
#include <opencv2/opencv.hpp>
-
+#include <opencv2/imgproc/imgproc_c.h>
+#include <opencv2/imgproc/types_c.h>
#include "Config.h"
#include "IFrameProcessor.h"
@@ -29,7 +30,7 @@ namespace bgslibrary
{
private:
IFrameProcessor* frameProcessor;
- CvCapture* capture;
+ cv::VideoCapture capture;
IplImage* frame;
int key;
int64 start_time;
diff --git a/config/FrameProcessor.xml b/config/FrameProcessor.xml
index 5155bbf..3cf398c 100644
--- a/config/FrameProcessor.xml
+++ b/config/FrameProcessor.xml
@@ -3,22 +3,22 @@
<tictoc>""</tictoc>
<enablePreProcessor>1</enablePreProcessor>
<enableForegroundMaskAnalysis>0</enableForegroundMaskAnalysis>
-<enableFrameDifferenceBGS>1</enableFrameDifferenceBGS>
-<enableStaticFrameDifferenceBGS>0</enableStaticFrameDifferenceBGS>
-<enableWeightedMovingMeanBGS>0</enableWeightedMovingMeanBGS>
-<enableWeightedMovingVarianceBGS>0</enableWeightedMovingVarianceBGS>
-<enableMixtureOfGaussianV1BGS>0</enableMixtureOfGaussianV1BGS>
-<enableMixtureOfGaussianV2BGS>0</enableMixtureOfGaussianV2BGS>
+<enableFrameDifference>1</enableFrameDifference>
+<enableStaticFrameDifference>0</enableStaticFrameDifference>
+<enableWeightedMovingMean>0</enableWeightedMovingMean>
+<enableWeightedMovingVariance>0</enableWeightedMovingVariance>
+<enableMixtureOfGaussianV1>0</enableMixtureOfGaussianV1>
+<enableMixtureOfGaussianV2>0</enableMixtureOfGaussianV2>
<enableAdaptiveBackgroundLearning>0</enableAdaptiveBackgroundLearning>
<enableGMG>0</enableGMG>
-<enableDPAdaptiveMedianBGS>0</enableDPAdaptiveMedianBGS>
-<enableDPGrimsonGMMBGS>0</enableDPGrimsonGMMBGS>
-<enableDPZivkovicAGMMBGS>0</enableDPZivkovicAGMMBGS>
-<enableDPMeanBGS>0</enableDPMeanBGS>
-<enableDPWrenGABGS>0</enableDPWrenGABGS>
-<enableDPPratiMediodBGS>0</enableDPPratiMediodBGS>
-<enableDPEigenbackgroundBGS>0</enableDPEigenbackgroundBGS>
-<enableDPTextureBGS>0</enableDPTextureBGS>
+<enableDPAdaptiveMedian>0</enableDPAdaptiveMedian>
+<enableDPGrimsonGMM>0</enableDPGrimsonGMM>
+<enableDPZivkovicAGMM>0</enableDPZivkovicAGMM>
+<enableDPMean>0</enableDPMean>
+<enableDPWrenGA>0</enableDPWrenGA>
+<enableDPPratiMediod>0</enableDPPratiMediod>
+<enableDPEigenbackground>0</enableDPEigenbackground>
+<enableDPTexture>0</enableDPTexture>
<enableT2FGMM_UM>0</enableT2FGMM_UM>
<enableT2FGMM_UV>0</enableT2FGMM_UV>
<enableT2FMRF_UM>0</enableT2FMRF_UM>
@@ -31,12 +31,13 @@
<enableLBAdaptiveSOM>0</enableLBAdaptiveSOM>
<enableLBFuzzyAdaptiveSOM>0</enableLBFuzzyAdaptiveSOM>
<enableLbpMrf>0</enableLbpMrf>
-<enableMultiLayerBGS>0</enableMultiLayerBGS>
+<enableMultiLayer>0</enableMultiLayer>
+<enablePBAS>0</enablePBAS>
<enableVuMeter>0</enableVuMeter>
<enableKDE>0</enableKDE>
<enableIMBS>0</enableIMBS>
-<enableMultiCueBGS>0</enableMultiCueBGS>
-<enableSigmaDeltaBGS>0</enableSigmaDeltaBGS>
-<enableSuBSENSEBGS>0</enableSuBSENSEBGS>
-<enableLOBSTERBGS>0</enableLOBSTERBGS>
+<enableMultiCue>0</enableMultiCue>
+<enableSigmaDelta>0</enableSigmaDelta>
+<enableSuBSENSE>0</enableSuBSENSE>
+<enableLOBSTER>0</enableLOBSTER>
</opencv_storage>
diff --git a/dataset/demo.avi b/dataset/demo.avi
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literal 0
HcmV?d00001
diff --git a/frames/1.png b/dataset/frames/1.png
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diff --git a/demos/DemoFrameDifferenceBGS.cpp b/demos/DemoFrameDifferenceBGS.cpp
deleted file mode 100644
index 5a449e2..0000000
--- a/demos/DemoFrameDifferenceBGS.cpp
+++ /dev/null
@@ -1,49 +0,0 @@
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "package_bgs/FrameDifferenceBGS.h"
-
-int main(int argc, char **argv)
-{
- CvCapture *capture = 0;
-
- capture = cvCaptureFromCAM(0);
- //capture = cvCaptureFromAVI("video.avi");
-
- if(!capture){
- std::cerr << "Cannot open initialize webcam!" << std::endl;
- return 1;
- }
-
- IplImage *frame = cvQueryFrame(capture);
-
- FrameDifferenceBGS* bgs = new FrameDifferenceBGS;
-
- int key = 0;
- while(key != 'q')
- {
- frame = cvQueryFrame(capture);
-
- if(!frame) break;
-
- cv::Mat img_input(frame,true);
- cv::resize(img_input,img_input,cv::Size(320,240));
- cv::imshow("input", img_input);
-
- cv::Mat img_mask;
- bgs->process(img_input, img_mask); // automatically shows the foreground mask image
-
- //if(!img_mask.empty())
- // do something
-
- key = cvWaitKey(1);
- }
-
- delete bgs;
-
- cvDestroyAllWindows();
- cvReleaseCapture(&capture);
-
- return 0;
-}
diff --git a/demos/DemoMultiLayerBGS.cpp b/demos/DemoMultiLayerBGS.cpp
deleted file mode 100644
index 08abe30..0000000
--- a/demos/DemoMultiLayerBGS.cpp
+++ /dev/null
@@ -1,49 +0,0 @@
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "package_bgs/jmo/MultiLayerBGS.h"
-
-int main(int argc, char **argv)
-{
- CvCapture *capture = 0;
-
- capture = cvCaptureFromCAM(0);
- //capture = cvCaptureFromAVI("video.avi");
-
- if(!capture){
- std::cerr << "Cannot open initialize webcam!" << std::endl;
- return 1;
- }
-
- IplImage *frame = cvQueryFrame(capture);
-
- MultiLayerBGS* bgs = new MultiLayerBGS;
-
- int key = 0;
- while(key != 'q')
- {
- frame = cvQueryFrame(capture);
-
- if(!frame) break;
-
- cv::Mat img_input(frame,true);
- cv::resize(img_input,img_input,cv::Size(320,240));
- cv::imshow("input", img_input);
-
- cv::Mat img_mask;
- bgs->process(img_input, img_mask); // automatically shows the foreground mask image
-
- //if(!img_mask.empty())
- // do something
-
- key = cvWaitKey(1);
- }
-
- delete bgs;
-
- cvDestroyAllWindows();
- cvReleaseCapture(&capture);
-
- return 0;
-}
diff --git a/demos/linux_ubuntu/.gitignore b/demos/linux_ubuntu/.gitignore
new file mode 100644
index 0000000..46d4288
--- /dev/null
+++ b/demos/linux_ubuntu/.gitignore
@@ -0,0 +1,8 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
+!CMakeLists.txt
+!FrameDifferenceTest.cpp
+!README.txt
+!config/
diff --git a/example_linux/CMakeLists.txt b/demos/linux_ubuntu/CMakeLists.txt
similarity index 66%
rename from example_linux/CMakeLists.txt
rename to demos/linux_ubuntu/CMakeLists.txt
index 9317e55..8cc38e8 100644
--- a/example_linux/CMakeLists.txt
+++ b/demos/linux_ubuntu/CMakeLists.txt
@@ -9,15 +9,14 @@ find_package(OpenCV REQUIRED)
file(GLOB source FrameDifferenceTest.cpp)
-file(GLOB_RECURSE bgs_src ../package_bgs/*.cpp ../package_bgs/*.c)
-file(GLOB_RECURSE bgs_include ../package_bgs/*.h)
+file(GLOB_RECURSE bgs_src ../../package_bgs/*.cpp ../../package_bgs/*.c ../../package_analysis/*.cpp)
+file(GLOB_RECURSE bgs_inc ../../package_bgs/*.h ../../package_analysis/*.h)
include_directories(${CMAKE_SOURCE_DIR})
add_library(bgs SHARED ${bgs_src})
target_link_libraries(bgs ${OpenCV_LIBS})
-set_property(TARGET bgs PROPERTY PUBLIC_HEADER ${bgs_include})
+set_property(TARGET bgs PROPERTY PUBLIC_HEADER ${bgs_inc})
add_executable(FrameDifferenceTest ${source})
target_link_libraries(FrameDifferenceTest ${OpenCV_LIBS} bgs)
-
diff --git a/example_macosx/FrameDifferenceTest.cpp b/demos/linux_ubuntu/FrameDifferenceTest.cpp
similarity index 87%
rename from example_macosx/FrameDifferenceTest.cpp
rename to demos/linux_ubuntu/FrameDifferenceTest.cpp
index 56f1e7c..7ebe8b1 100644
--- a/example_macosx/FrameDifferenceTest.cpp
+++ b/demos/linux_ubuntu/FrameDifferenceTest.cpp
@@ -2,7 +2,9 @@
#include <cv.h>
#include <highgui.h>
-#include "../package_bgs/FrameDifferenceBGS.h"
+#include "../../package_bgs/FrameDifference.h"
+
+using namespace bgslibrary::algorithms;
int main(int argc, char **argv)
{
@@ -15,7 +17,7 @@ int main(int argc, char **argv)
}
IBGS *bgs;
- bgs = new FrameDifferenceBGS;
+ bgs = new FrameDifference;
IplImage *frame;
while(1)
diff --git a/example_linux/README.txt b/demos/linux_ubuntu/README.txt
similarity index 100%
rename from example_linux/README.txt
rename to demos/linux_ubuntu/README.txt
diff --git a/demos/linux_ubuntu/config/.gitignore b/demos/linux_ubuntu/config/.gitignore
new file mode 100644
index 0000000..8ee04a0
--- /dev/null
+++ b/demos/linux_ubuntu/config/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
\ No newline at end of file
diff --git a/demos/macosx/.gitignore b/demos/macosx/.gitignore
new file mode 100644
index 0000000..46d4288
--- /dev/null
+++ b/demos/macosx/.gitignore
@@ -0,0 +1,8 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
+!CMakeLists.txt
+!FrameDifferenceTest.cpp
+!README.txt
+!config/
diff --git a/example_macosx/CMakeLists.txt b/demos/macosx/CMakeLists.txt
similarity index 79%
rename from example_macosx/CMakeLists.txt
rename to demos/macosx/CMakeLists.txt
index 107303f..a9775d8 100644
--- a/example_macosx/CMakeLists.txt
+++ b/demos/macosx/CMakeLists.txt
@@ -20,15 +20,14 @@ find_package(OpenCV REQUIRED)
file(GLOB source FrameDifferenceTest.cpp)
-file(GLOB_RECURSE bgs_src ../package_bgs/*.cpp ../package_bgs/*.c)
-file(GLOB_RECURSE bgs_include ../package_bgs/*.h)
+file(GLOB_RECURSE bgs_src ../../package_bgs/*.cpp ../../package_bgs/*.c ../../package_analysis/*.cpp)
+file(GLOB_RECURSE bgs_inc ../../package_bgs/*.h ../../package_analysis/*.h)
include_directories(${CMAKE_SOURCE_DIR})
add_library(bgs SHARED ${bgs_src})
target_link_libraries(bgs ${OpenCV_LIBS})
-set_property(TARGET bgs PROPERTY PUBLIC_HEADER ${bgs_include})
+set_property(TARGET bgs PROPERTY PUBLIC_HEADER ${bgs_inc})
add_executable(FrameDifferenceTest ${source})
target_link_libraries(FrameDifferenceTest ${OpenCV_LIBS} bgs)
-
diff --git a/example_linux/FrameDifferenceTest.cpp b/demos/macosx/FrameDifferenceTest.cpp
similarity index 87%
rename from example_linux/FrameDifferenceTest.cpp
rename to demos/macosx/FrameDifferenceTest.cpp
index 56f1e7c..7ebe8b1 100644
--- a/example_linux/FrameDifferenceTest.cpp
+++ b/demos/macosx/FrameDifferenceTest.cpp
@@ -2,7 +2,9 @@
#include <cv.h>
#include <highgui.h>
-#include "../package_bgs/FrameDifferenceBGS.h"
+#include "../../package_bgs/FrameDifference.h"
+
+using namespace bgslibrary::algorithms;
int main(int argc, char **argv)
{
@@ -15,7 +17,7 @@ int main(int argc, char **argv)
}
IBGS *bgs;
- bgs = new FrameDifferenceBGS;
+ bgs = new FrameDifference;
IplImage *frame;
while(1)
diff --git a/example_macosx/README.txt b/demos/macosx/README.txt
similarity index 100%
rename from example_macosx/README.txt
rename to demos/macosx/README.txt
diff --git a/demos/macosx/config/.gitignore b/demos/macosx/config/.gitignore
new file mode 100644
index 0000000..8ee04a0
--- /dev/null
+++ b/demos/macosx/config/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
\ No newline at end of file
diff --git a/README_CMAKE_USERS.txt b/docs/README_CMAKE_USERS_OPENCV2.txt
similarity index 70%
rename from README_CMAKE_USERS.txt
rename to docs/README_CMAKE_USERS_OPENCV2.txt
index 974e941..26c6997 100644
--- a/README_CMAKE_USERS.txt
+++ b/docs/README_CMAKE_USERS_OPENCV2.txt
@@ -15,18 +15,17 @@ Please follow the instructions below:
1) Go to Windows console.
2) Clone BGSLibrary git repository:
-e.g.: git clone https://github.com/andrewssobral/bgslibrary.git
+git clone https://github.com/andrewssobral/bgslibrary.git
3) Go to bgslibrary/build folder.
-e.g.: C:\bgslibrary\build>_
-2) Set your OpenCV PATH:
-e.g.:
-\> setlocal
-\> set OpenCV_DIR=C:\OpenCV2.4.10\build
-\> cmake -DOpenCV_DIR=%OpenCV_DIR% -G "Visual Studio 12" ..
-or:
-\> cmake -DOpenCV_DIR=%OpenCV_DIR% -G "Visual Studio 12 Win64" ..
+4) Set your OpenCV PATH:
+setlocal
+set OpenCV_DIR=C:\OpenCV2.4.10\build
+
+5) Launch CMAKE:
+(For Windows x86 32bits) cmake -DOpenCV_DIR=%OpenCV_DIR% -G "Visual Studio 12" ..
+(For Windows x64 64bits) cmake -DOpenCV_DIR=%OpenCV_DIR% -G "Visual Studio 12 Win64" ..
Now, you will see something like (for win64):
-------------------------------------------------
@@ -52,27 +51,25 @@ Now, you will see something like (for win64):
-- Build files have been written to: C:/bgslibrary/build
-------------------------------------------------
-3) Include OpenCV binaries in the system path:
-\> set PATH=%PATH%;%OpenCV_DIR%\x86\vc12\bin
-or:
-\> set PATH=%PATH%;%OpenCV_DIR%\x64\vc12\bin
+6) Include OpenCV binaries in the system path:
+(For Windows x86 32bits) set PATH=%PATH%;%OpenCV_DIR%\x86\vc12\bin
+(For Windows x64 64bits) set PATH=%PATH%;%OpenCV_DIR%\x64\vc12\bin
-4) Open 'bgs.sln' in Visual Studio and switch to 'RELEASE' mode
-4.1) Note if you are using a Visual Studio version superior than 2013, you will need to CANCEL the project wizard update. However, you can go to step (2) and change the Visual Studio version, e.g.: -G "Visual Studio XX", where XX is your Visual Studio version.
+7) Open 'bgs.sln' in Visual Studio and switch to 'RELEASE' mode
+7.1) Note if you are using a Visual Studio version superior than 2013, you will need to CANCEL the project wizard update. However, you can go to step (5) and change the Visual Studio version, e.g.: -G "Visual Studio XX", where XX is your Visual Studio version.
-5) Click on 'ALL_BUILD' project and build!
+8) Click on 'ALL_BUILD' project and build!
-6) If everything goes well, you can run bgslibrary in the Windows console as follows:
+9) If everything goes well, you can run bgslibrary in the Windows console as follows:
-6.1) Running BGSLibrary with a webcamera:
+9.1) Running BGSLibrary with a webcamera:
C:\bgslibrary> build\bgslibrary.exe --use_cam --camera=0
-6.2) Running demo code:
+9.2) Running demo code:
C:\bgslibrary> build\bgs_demo.exe dataset/video.avi
-6.3) Running demo2 code:
+9.3) Running demo2 code:
C:\bgslibrary> build\bgs_demo2.exe
Additional information:
* Note that bgslibrary requires a 'config' folder in the working directory.
-e.g.: C:\bgslibrary\config
diff --git a/docs/README_CMAKE_USERS_OPENCV3.txt b/docs/README_CMAKE_USERS_OPENCV3.txt
new file mode 100644
index 0000000..543fd86
--- /dev/null
+++ b/docs/README_CMAKE_USERS_OPENCV3.txt
@@ -0,0 +1,77 @@
+-------------------------------------------------
+-------------- WINDOWS CMAKE USERS --------------
+
+How to build BGSLibrary with OpenCV 3.2.0 and Visual Studio 2015 from CMAKE.
+
+For Linux users, please see the instruction in README_LINUX_USERS.txt file.
+
+Dependencies:
+* GIT (tested with git version 2.7.2.windows.1).
+* CMAKE for Windows (tested with cmake version 3.1.1).
+* Microsoft Visual Studio (tested with VS2015).
+
+Please follow the instructions below:
+
+1) Go to Windows console.
+
+2) Clone BGSLibrary git repository:
+git clone https://github.com/andrewssobral/bgslibrary.git
+
+3) Go to bgslibrary/build folder.
+
+4) Set your OpenCV PATH:
+setlocal
+set OpenCV_DIR=C:\OpenCV3.2.0\build
+
+5) Launch CMAKE:
+cmake -DOpenCV_DIR=%OpenCV_DIR% -G "Visual Studio 14 Win64" ..
+
+Now, you will see something like:
+-------------------------------------------------
+-- The C compiler identification is MSVC 19.0.24215.1
+-- The CXX compiler identification is MSVC 19.0.24215.1
+-- Check for working C compiler using: Visual Studio 14 2015 Win64
+-- Check for working C compiler using: Visual Studio 14 2015 Win64 -- works
+-- Detecting C compiler ABI info
+-- Detecting C compiler ABI info - done
+-- Check for working CXX compiler using: Visual Studio 14 2015 Win64
+-- Check for working CXX compiler using: Visual Studio 14 2015 Win64 -- works
+-- Detecting CXX compiler ABI info
+-- Detecting CXX compiler ABI info - done
+-- Detecting CXX compile features
+-- Detecting CXX compile features - done
+-- OpenCV ARCH: x64
+-- OpenCV RUNTIME: vc14
+-- OpenCV STATIC: ON
+-- Found OpenCV 3.2.0 in C:/OpenCV3.2.0/build/x64/vc14/lib
+-- You might need to add C:\OpenCV3.2.0\build\x64\vc14\bin to your PATH to be able to run your applications.
+-- OpenCV library status:
+-- version: 3.2.0
+-- libraries: opencv_world;opencv_videostab;opencv_videoio;opencv_video;opencv_superres;opencv_stitching;opencv_shape;opencv_photo;opencv_objdetect;opencv_ml;opencv_imgproc;opencv_imgcodecs;opencv_highgui;opencv_flann;opencv_features2d;opencv_core;opencv_calib3d
+-- include path: C:/OpenCV3.2.0/build/include;C:/OpenCV3.2.0/build/include/opencv
+-- Configuring done
+-- Generating done
+-- Build files have been written to: C:/bgslibrary/build
+-------------------------------------------------
+
+6) Include OpenCV binaries in the system path:
+set PATH=%PATH%;%OpenCV_DIR%\x64\vc14\bin
+
+7) Open 'bgs.sln' in Visual Studio and switch to 'RELEASE' mode
+7.1) Note if you are using a Visual Studio version superior than 2015, you will need to CANCEL the project wizard update. However, you can go to step (2) and change the Visual Studio version, e.g.: -G "Visual Studio XX", where XX is your Visual Studio version.
+
+8) Click on 'ALL_BUILD' project and build!
+
+9) If everything goes well, you can run bgslibrary in the Windows console as follows:
+
+9.1) Running BGSLibrary with a webcamera:
+C:\bgslibrary> build\bgslibrary.exe --use_cam --camera=0
+
+9.2) Running demo code:
+C:\bgslibrary> build\bgs_demo.exe dataset/video.avi
+
+9.3) Running demo2 code:
+C:\bgslibrary> build\bgs_demo2.exe
+
+Additional information:
+* Note that bgslibrary requires a 'config' folder in the working directory.
diff --git a/README_LINUX_USERS.txt b/docs/README_LINUX_USERS.txt
similarity index 85%
rename from README_LINUX_USERS.txt
rename to docs/README_LINUX_USERS.txt
index 5a2611f..9482f33 100644
--- a/README_LINUX_USERS.txt
+++ b/docs/README_LINUX_USERS.txt
@@ -4,6 +4,8 @@
# Requirements:
# cmake >= 2.8
# opencv >= 2.3.1
+#
+# Tested with: Ubuntu 14.04 and Ubuntu 16.04
cd build
cmake ..
@@ -17,7 +19,8 @@ export LD_LIBRARY_PATH
# Now you can run bgslibrary by: bgs -i video.avi
########################
cd ..
-chmod +x run_video.sh run_camera.sh run_demo.sh
+chmod +x *.sh
./run_video.sh
./run_camera.sh
./run_demo.sh
+./run_demo2.sh
diff --git a/README_VISUAL_STUDIO_USERS.txt b/docs/README_VS2010_OPENCV2.txt
similarity index 81%
rename from README_VISUAL_STUDIO_USERS.txt
rename to docs/README_VS2010_OPENCV2.txt
index ee9fe12..66ee0f4 100644
--- a/README_VISUAL_STUDIO_USERS.txt
+++ b/docs/README_VS2010_OPENCV2.txt
@@ -1,16 +1,13 @@
---------------------------------------------------
BGSLibrary with Visual Studio 2010 and Opencv 2.4.x
---------------------------------------------------
-
-1) Clone our VS2010 example project at [vs2010] folder
-https://github.com/andrewssobral/bgslibrary/tree/master/vs2010
-
-Or configure manually by:
+--- Tutorial for Windows x86 32 bits ---
+----------------------------------------
1) Install OpenCV
1.a) Download OpenCV 2.4.x from http://opencv.org/
-2.b) Install in: C:\OpenCV2.4.x
-2.c) Add OpenCV binaries in your Path
+1.b) Install in: C:\OpenCV2.4.x
+1.c) Add OpenCV binaries in your Path
C:\OpenCV2.4.x\build\x86\vc10\bin
2) Download BGSLibrary
@@ -22,7 +19,7 @@ C:\OpenCV2.4.x\build\x86\vc10\bin
3.c) Set project location: C:\bgslibrary
3.d) Set project name: bgslibrary
3.e) Set Empty project
-3.f) Add Demo.cpp in [Source Files]
+3.f) Add Main.cpp in [Source Files]
3.g) Add content of c:\bgslibrary\package_bgs\*.* in [Header Files]
3.h) Add content of c:\bgslibrary\package_analysis\*.* in [Header Files]
3.i) Change to [Release] [Win32] mode
diff --git a/example_linux/config/KEEP_THIS_FOLDER b/example_linux/config/KEEP_THIS_FOLDER
deleted file mode 100644
index 24353bc..0000000
--- a/example_linux/config/KEEP_THIS_FOLDER
+++ /dev/null
@@ -1 +0,0 @@
-bgslibrary uses this folder to store the configuration files
\ No newline at end of file
diff --git a/example_macosx/config/KEEP_THIS_FOLDER b/example_macosx/config/KEEP_THIS_FOLDER
deleted file mode 100644
index 24353bc..0000000
--- a/example_macosx/config/KEEP_THIS_FOLDER
+++ /dev/null
@@ -1 +0,0 @@
-bgslibrary uses this folder to store the configuration files
\ No newline at end of file
diff --git a/java_gui/README.txt b/gui_java/README.txt
similarity index 100%
rename from java_gui/README.txt
rename to gui_java/README.txt
diff --git a/java_gui/_COPY_bgslibrary.exe_HERE_ b/gui_java/_COPY_bgslibrary.exe_HERE_
similarity index 100%
rename from java_gui/_COPY_bgslibrary.exe_HERE_
rename to gui_java/_COPY_bgslibrary.exe_HERE_
diff --git a/java_gui/bgslibrary_gui.jar b/gui_java/bgslibrary_gui.jar
similarity index 100%
rename from java_gui/bgslibrary_gui.jar
rename to gui_java/bgslibrary_gui.jar
diff --git a/java_gui/bgslibrary_gui.properties b/gui_java/bgslibrary_gui.properties
similarity index 100%
rename from java_gui/bgslibrary_gui.properties
rename to gui_java/bgslibrary_gui.properties
diff --git a/java_gui/build.xml b/gui_java/build.xml
similarity index 100%
rename from java_gui/build.xml
rename to gui_java/build.xml
diff --git a/java_gui/config/.gitignore b/gui_java/config/.gitignore
similarity index 100%
rename from java_gui/config/.gitignore
rename to gui_java/config/.gitignore
diff --git a/java_gui/config/FrameProcessor.xml b/gui_java/config/FrameProcessor.xml
similarity index 100%
rename from java_gui/config/FrameProcessor.xml
rename to gui_java/config/FrameProcessor.xml
diff --git a/java_gui/config/PreProcessor.xml b/gui_java/config/PreProcessor.xml
similarity index 100%
rename from java_gui/config/PreProcessor.xml
rename to gui_java/config/PreProcessor.xml
diff --git a/java_gui/config/VideoCapture.xml b/gui_java/config/VideoCapture.xml
similarity index 100%
rename from java_gui/config/VideoCapture.xml
rename to gui_java/config/VideoCapture.xml
diff --git a/java_gui/images/bgslibrary_gui_screen01.png b/gui_java/images/bgslibrary_gui_screen01.png
similarity index 100%
rename from java_gui/images/bgslibrary_gui_screen01.png
rename to gui_java/images/bgslibrary_gui_screen01.png
diff --git a/java_gui/images/bgslibrary_gui_screen02.png b/gui_java/images/bgslibrary_gui_screen02.png
similarity index 100%
rename from java_gui/images/bgslibrary_gui_screen02.png
rename to gui_java/images/bgslibrary_gui_screen02.png
diff --git a/java_gui/images/bgslibrary_gui_screen03.png b/gui_java/images/bgslibrary_gui_screen03.png
similarity index 100%
rename from java_gui/images/bgslibrary_gui_screen03.png
rename to gui_java/images/bgslibrary_gui_screen03.png
diff --git a/java_gui/images/bgslibrary_gui_screen04.png b/gui_java/images/bgslibrary_gui_screen04.png
similarity index 100%
rename from java_gui/images/bgslibrary_gui_screen04.png
rename to gui_java/images/bgslibrary_gui_screen04.png
diff --git a/java_gui/images/logo.jpg b/gui_java/images/logo.jpg
similarity index 100%
rename from java_gui/images/logo.jpg
rename to gui_java/images/logo.jpg
diff --git a/java_gui/lib/commons-configuration-1.8.jar b/gui_java/lib/commons-configuration-1.8.jar
similarity index 100%
rename from java_gui/lib/commons-configuration-1.8.jar
rename to gui_java/lib/commons-configuration-1.8.jar
diff --git a/java_gui/lib/commons-io-2.3.jar b/gui_java/lib/commons-io-2.3.jar
similarity index 100%
rename from java_gui/lib/commons-io-2.3.jar
rename to gui_java/lib/commons-io-2.3.jar
diff --git a/java_gui/lib/commons-lang-2.6.jar b/gui_java/lib/commons-lang-2.6.jar
similarity index 100%
rename from java_gui/lib/commons-lang-2.6.jar
rename to gui_java/lib/commons-lang-2.6.jar
diff --git a/java_gui/lib/commons-logging-1.1.1.jar b/gui_java/lib/commons-logging-1.1.1.jar
similarity index 100%
rename from java_gui/lib/commons-logging-1.1.1.jar
rename to gui_java/lib/commons-logging-1.1.1.jar
diff --git a/java_gui/lib/swingx-all-1.6.3.jar b/gui_java/lib/swingx-all-1.6.3.jar
similarity index 100%
rename from java_gui/lib/swingx-all-1.6.3.jar
rename to gui_java/lib/swingx-all-1.6.3.jar
diff --git a/java_gui/lib/swingx-beaninfo-1.6.3.jar b/gui_java/lib/swingx-beaninfo-1.6.3.jar
similarity index 100%
rename from java_gui/lib/swingx-beaninfo-1.6.3.jar
rename to gui_java/lib/swingx-beaninfo-1.6.3.jar
diff --git a/java_gui/manifest.mf b/gui_java/manifest.mf
similarity index 100%
rename from java_gui/manifest.mf
rename to gui_java/manifest.mf
diff --git a/java_gui/nbproject/build-impl.xml b/gui_java/nbproject/build-impl.xml
similarity index 100%
rename from java_gui/nbproject/build-impl.xml
rename to gui_java/nbproject/build-impl.xml
diff --git a/java_gui/nbproject/genfiles.properties b/gui_java/nbproject/genfiles.properties
similarity index 100%
rename from java_gui/nbproject/genfiles.properties
rename to gui_java/nbproject/genfiles.properties
diff --git a/java_gui/nbproject/private/config.properties b/gui_java/nbproject/private/config.properties
similarity index 100%
rename from java_gui/nbproject/private/config.properties
rename to gui_java/nbproject/private/config.properties
diff --git a/java_gui/nbproject/private/private.properties b/gui_java/nbproject/private/private.properties
similarity index 100%
rename from java_gui/nbproject/private/private.properties
rename to gui_java/nbproject/private/private.properties
diff --git a/java_gui/nbproject/private/private.xml b/gui_java/nbproject/private/private.xml
similarity index 100%
rename from java_gui/nbproject/private/private.xml
rename to gui_java/nbproject/private/private.xml
diff --git a/java_gui/nbproject/project.properties b/gui_java/nbproject/project.properties
similarity index 100%
rename from java_gui/nbproject/project.properties
rename to gui_java/nbproject/project.properties
diff --git a/java_gui/nbproject/project.xml b/gui_java/nbproject/project.xml
similarity index 100%
rename from java_gui/nbproject/project.xml
rename to gui_java/nbproject/project.xml
diff --git a/java_gui/run_camera.bat b/gui_java/run_camera.bat
similarity index 100%
rename from java_gui/run_camera.bat
rename to gui_java/run_camera.bat
diff --git a/java_gui/run_java_gui.bat b/gui_java/run_java_gui.bat
similarity index 100%
rename from java_gui/run_java_gui.bat
rename to gui_java/run_java_gui.bat
diff --git a/java_gui/run_java_gui_with_console.bat b/gui_java/run_java_gui_with_console.bat
similarity index 100%
rename from java_gui/run_java_gui_with_console.bat
rename to gui_java/run_java_gui_with_console.bat
diff --git a/java_gui/run_video.bat b/gui_java/run_video.bat
similarity index 100%
rename from java_gui/run_video.bat
rename to gui_java/run_video.bat
diff --git a/java_gui/src/br/com/bgslibrary/Main.java b/gui_java/src/br/com/bgslibrary/Main.java
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/Main.java
rename to gui_java/src/br/com/bgslibrary/Main.java
diff --git a/java_gui/src/br/com/bgslibrary/entity/Command.java b/gui_java/src/br/com/bgslibrary/entity/Command.java
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/entity/Command.java
rename to gui_java/src/br/com/bgslibrary/entity/Command.java
diff --git a/java_gui/src/br/com/bgslibrary/entity/Configuration.java b/gui_java/src/br/com/bgslibrary/entity/Configuration.java
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/entity/Configuration.java
rename to gui_java/src/br/com/bgslibrary/entity/Configuration.java
diff --git a/java_gui/src/br/com/bgslibrary/gui/AboutDialog.form b/gui_java/src/br/com/bgslibrary/gui/AboutDialog.form
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/gui/AboutDialog.form
rename to gui_java/src/br/com/bgslibrary/gui/AboutDialog.form
diff --git a/java_gui/src/br/com/bgslibrary/gui/AboutDialog.java b/gui_java/src/br/com/bgslibrary/gui/AboutDialog.java
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/gui/AboutDialog.java
rename to gui_java/src/br/com/bgslibrary/gui/AboutDialog.java
diff --git a/java_gui/src/br/com/bgslibrary/gui/MainFrame.form b/gui_java/src/br/com/bgslibrary/gui/MainFrame.form
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/gui/MainFrame.form
rename to gui_java/src/br/com/bgslibrary/gui/MainFrame.form
diff --git a/java_gui/src/br/com/bgslibrary/gui/MainFrame.java b/gui_java/src/br/com/bgslibrary/gui/MainFrame.java
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/gui/MainFrame.java
rename to gui_java/src/br/com/bgslibrary/gui/MainFrame.java
diff --git a/java_gui/src/br/com/bgslibrary/resources/logo.jpg b/gui_java/src/br/com/bgslibrary/resources/logo.jpg
similarity index 100%
rename from java_gui/src/br/com/bgslibrary/resources/logo.jpg
rename to gui_java/src/br/com/bgslibrary/resources/logo.jpg
diff --git a/vs2010mfc/.gitignore b/gui_mfc/.gitignore
similarity index 100%
rename from vs2010mfc/.gitignore
rename to gui_mfc/.gitignore
diff --git a/vs2013mfc/ReadMe.txt b/gui_mfc/ReadMe.txt
similarity index 100%
rename from vs2013mfc/ReadMe.txt
rename to gui_mfc/ReadMe.txt
diff --git a/vs2010mfc/config/AdaptiveBackgroundLearning.xml b/gui_mfc/config/AdaptiveBackgroundLearning.xml
similarity index 100%
rename from vs2010mfc/config/AdaptiveBackgroundLearning.xml
rename to gui_mfc/config/AdaptiveBackgroundLearning.xml
diff --git a/vs2010mfc/config/AdaptiveSelectiveBackgroundLearning.xml b/gui_mfc/config/AdaptiveSelectiveBackgroundLearning.xml
similarity index 100%
rename from vs2010mfc/config/AdaptiveSelectiveBackgroundLearning.xml
rename to gui_mfc/config/AdaptiveSelectiveBackgroundLearning.xml
diff --git a/vs2010mfc/config/DPAdaptiveMedianBGS.xml b/gui_mfc/config/DPAdaptiveMedianBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPAdaptiveMedianBGS.xml
rename to gui_mfc/config/DPAdaptiveMedianBGS.xml
diff --git a/vs2010mfc/config/DPEigenbackgroundBGS.xml b/gui_mfc/config/DPEigenbackgroundBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPEigenbackgroundBGS.xml
rename to gui_mfc/config/DPEigenbackgroundBGS.xml
diff --git a/vs2010mfc/config/DPGrimsonGMMBGS.xml b/gui_mfc/config/DPGrimsonGMMBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPGrimsonGMMBGS.xml
rename to gui_mfc/config/DPGrimsonGMMBGS.xml
diff --git a/vs2010mfc/config/DPMeanBGS.xml b/gui_mfc/config/DPMeanBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPMeanBGS.xml
rename to gui_mfc/config/DPMeanBGS.xml
diff --git a/vs2010mfc/config/DPPratiMediodBGS.xml b/gui_mfc/config/DPPratiMediodBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPPratiMediodBGS.xml
rename to gui_mfc/config/DPPratiMediodBGS.xml
diff --git a/vs2010mfc/config/DPTextureBGS.xml b/gui_mfc/config/DPTextureBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPTextureBGS.xml
rename to gui_mfc/config/DPTextureBGS.xml
diff --git a/vs2010mfc/config/DPWrenGABGS.xml b/gui_mfc/config/DPWrenGABGS.xml
similarity index 100%
rename from vs2010mfc/config/DPWrenGABGS.xml
rename to gui_mfc/config/DPWrenGABGS.xml
diff --git a/vs2010mfc/config/DPZivkovicAGMMBGS.xml b/gui_mfc/config/DPZivkovicAGMMBGS.xml
similarity index 100%
rename from vs2010mfc/config/DPZivkovicAGMMBGS.xml
rename to gui_mfc/config/DPZivkovicAGMMBGS.xml
diff --git a/vs2010mfc/config/FrameDifferenceBGS.xml b/gui_mfc/config/FrameDifferenceBGS.xml
similarity index 100%
rename from vs2010mfc/config/FrameDifferenceBGS.xml
rename to gui_mfc/config/FrameDifferenceBGS.xml
diff --git a/vs2010mfc/config/FuzzyChoquetIntegral.xml b/gui_mfc/config/FuzzyChoquetIntegral.xml
similarity index 100%
rename from vs2010mfc/config/FuzzyChoquetIntegral.xml
rename to gui_mfc/config/FuzzyChoquetIntegral.xml
diff --git a/vs2010mfc/config/FuzzySugenoIntegral.xml b/gui_mfc/config/FuzzySugenoIntegral.xml
similarity index 100%
rename from vs2010mfc/config/FuzzySugenoIntegral.xml
rename to gui_mfc/config/FuzzySugenoIntegral.xml
diff --git a/vs2010mfc/config/GMG.xml b/gui_mfc/config/GMG.xml
similarity index 100%
rename from vs2010mfc/config/GMG.xml
rename to gui_mfc/config/GMG.xml
diff --git a/vs2010mfc/config/IndependentMultimodalBGS.xml b/gui_mfc/config/IndependentMultimodalBGS.xml
similarity index 100%
rename from vs2010mfc/config/IndependentMultimodalBGS.xml
rename to gui_mfc/config/IndependentMultimodalBGS.xml
diff --git a/vs2010mfc/config/KDE.xml b/gui_mfc/config/KDE.xml
similarity index 100%
rename from vs2010mfc/config/KDE.xml
rename to gui_mfc/config/KDE.xml
diff --git a/vs2010mfc/config/LBAdaptiveSOM.xml b/gui_mfc/config/LBAdaptiveSOM.xml
similarity index 100%
rename from vs2010mfc/config/LBAdaptiveSOM.xml
rename to gui_mfc/config/LBAdaptiveSOM.xml
diff --git a/vs2010mfc/config/LBFuzzyAdaptiveSOM.xml b/gui_mfc/config/LBFuzzyAdaptiveSOM.xml
similarity index 100%
rename from vs2010mfc/config/LBFuzzyAdaptiveSOM.xml
rename to gui_mfc/config/LBFuzzyAdaptiveSOM.xml
diff --git a/vs2010mfc/config/LBFuzzyGaussian.xml b/gui_mfc/config/LBFuzzyGaussian.xml
similarity index 100%
rename from vs2010mfc/config/LBFuzzyGaussian.xml
rename to gui_mfc/config/LBFuzzyGaussian.xml
diff --git a/vs2010mfc/config/LBMixtureOfGaussians.xml b/gui_mfc/config/LBMixtureOfGaussians.xml
similarity index 100%
rename from vs2010mfc/config/LBMixtureOfGaussians.xml
rename to gui_mfc/config/LBMixtureOfGaussians.xml
diff --git a/vs2010mfc/config/LBSimpleGaussian.xml b/gui_mfc/config/LBSimpleGaussian.xml
similarity index 100%
rename from vs2010mfc/config/LBSimpleGaussian.xml
rename to gui_mfc/config/LBSimpleGaussian.xml
diff --git a/vs2010mfc/config/LOBSTERBGS.xml b/gui_mfc/config/LOBSTERBGS.xml
similarity index 100%
rename from vs2010mfc/config/LOBSTERBGS.xml
rename to gui_mfc/config/LOBSTERBGS.xml
diff --git a/vs2010mfc/config/MixtureOfGaussianV1BGS.xml b/gui_mfc/config/MixtureOfGaussianV1BGS.xml
similarity index 100%
rename from vs2010mfc/config/MixtureOfGaussianV1BGS.xml
rename to gui_mfc/config/MixtureOfGaussianV1BGS.xml
diff --git a/vs2010mfc/config/MixtureOfGaussianV2BGS.xml b/gui_mfc/config/MixtureOfGaussianV2BGS.xml
similarity index 100%
rename from vs2010mfc/config/MixtureOfGaussianV2BGS.xml
rename to gui_mfc/config/MixtureOfGaussianV2BGS.xml
diff --git a/vs2010mfc/config/MultiCueBGS.xml b/gui_mfc/config/MultiCueBGS.xml
similarity index 100%
rename from vs2010mfc/config/MultiCueBGS.xml
rename to gui_mfc/config/MultiCueBGS.xml
diff --git a/vs2010mfc/config/MultiLayerBGS.xml b/gui_mfc/config/MultiLayerBGS.xml
similarity index 100%
rename from vs2010mfc/config/MultiLayerBGS.xml
rename to gui_mfc/config/MultiLayerBGS.xml
diff --git a/vs2010mfc/config/SigmaDeltaBGS.xml b/gui_mfc/config/SigmaDeltaBGS.xml
similarity index 100%
rename from vs2010mfc/config/SigmaDeltaBGS.xml
rename to gui_mfc/config/SigmaDeltaBGS.xml
diff --git a/vs2010mfc/config/StaticFrameDifferenceBGS.xml b/gui_mfc/config/StaticFrameDifferenceBGS.xml
similarity index 100%
rename from vs2010mfc/config/StaticFrameDifferenceBGS.xml
rename to gui_mfc/config/StaticFrameDifferenceBGS.xml
diff --git a/vs2010mfc/config/SuBSENSEBGS.xml b/gui_mfc/config/SuBSENSEBGS.xml
similarity index 100%
rename from vs2010mfc/config/SuBSENSEBGS.xml
rename to gui_mfc/config/SuBSENSEBGS.xml
diff --git a/vs2010mfc/config/T2FGMM_UM.xml b/gui_mfc/config/T2FGMM_UM.xml
similarity index 100%
rename from vs2010mfc/config/T2FGMM_UM.xml
rename to gui_mfc/config/T2FGMM_UM.xml
diff --git a/vs2010mfc/config/T2FGMM_UV.xml b/gui_mfc/config/T2FGMM_UV.xml
similarity index 100%
rename from vs2010mfc/config/T2FGMM_UV.xml
rename to gui_mfc/config/T2FGMM_UV.xml
diff --git a/vs2010mfc/config/T2FMRF_UM.xml b/gui_mfc/config/T2FMRF_UM.xml
similarity index 100%
rename from vs2010mfc/config/T2FMRF_UM.xml
rename to gui_mfc/config/T2FMRF_UM.xml
diff --git a/vs2010mfc/config/T2FMRF_UV.xml b/gui_mfc/config/T2FMRF_UV.xml
similarity index 100%
rename from vs2010mfc/config/T2FMRF_UV.xml
rename to gui_mfc/config/T2FMRF_UV.xml
diff --git a/vs2010mfc/config/VuMeter.xml b/gui_mfc/config/VuMeter.xml
similarity index 100%
rename from vs2010mfc/config/VuMeter.xml
rename to gui_mfc/config/VuMeter.xml
diff --git a/vs2010mfc/config/WeightedMovingMeanBGS.xml b/gui_mfc/config/WeightedMovingMeanBGS.xml
similarity index 100%
rename from vs2010mfc/config/WeightedMovingMeanBGS.xml
rename to gui_mfc/config/WeightedMovingMeanBGS.xml
diff --git a/vs2010mfc/config/WeightedMovingVarianceBGS.xml b/gui_mfc/config/WeightedMovingVarianceBGS.xml
similarity index 100%
rename from vs2010mfc/config/WeightedMovingVarianceBGS.xml
rename to gui_mfc/config/WeightedMovingVarianceBGS.xml
diff --git a/vs2010mfc/dataset/video.avi b/gui_mfc/dataset/video.avi
similarity index 100%
rename from vs2010mfc/dataset/video.avi
rename to gui_mfc/dataset/video.avi
diff --git a/vs2013mfc/outputs/background/.gitignore b/gui_mfc/outputs/background/.gitignore
similarity index 100%
rename from vs2013mfc/outputs/background/.gitignore
rename to gui_mfc/outputs/background/.gitignore
diff --git a/vs2013mfc/outputs/foreground/.gitignore b/gui_mfc/outputs/foreground/.gitignore
similarity index 100%
rename from vs2013mfc/outputs/foreground/.gitignore
rename to gui_mfc/outputs/foreground/.gitignore
diff --git a/vs2013mfc/outputs/input/.gitignore b/gui_mfc/outputs/input/.gitignore
similarity index 100%
rename from vs2013mfc/outputs/input/.gitignore
rename to gui_mfc/outputs/input/.gitignore
diff --git a/vs2010mfc/src/.gitignore b/gui_mfc/src/.gitignore
similarity index 100%
rename from vs2010mfc/src/.gitignore
rename to gui_mfc/src/.gitignore
diff --git a/vs2010mfc/src/App.cpp b/gui_mfc/src/App.cpp
similarity index 100%
rename from vs2010mfc/src/App.cpp
rename to gui_mfc/src/App.cpp
diff --git a/vs2010mfc/src/App.h b/gui_mfc/src/App.h
similarity index 100%
rename from vs2010mfc/src/App.h
rename to gui_mfc/src/App.h
diff --git a/vs2010mfc/src/Dlg.cpp b/gui_mfc/src/Dlg.cpp
similarity index 100%
rename from vs2010mfc/src/Dlg.cpp
rename to gui_mfc/src/Dlg.cpp
diff --git a/vs2010mfc/src/Dlg.h b/gui_mfc/src/Dlg.h
similarity index 100%
rename from vs2010mfc/src/Dlg.h
rename to gui_mfc/src/Dlg.h
diff --git a/vs2013mfc/src/ReadMe.txt b/gui_mfc/src/ReadMe.txt
similarity index 100%
rename from vs2013mfc/src/ReadMe.txt
rename to gui_mfc/src/ReadMe.txt
diff --git a/vs2013mfc/src/bgslibrary_vs2013_mfc.rc b/gui_mfc/src/bgslibrary_vs2013_mfc.rc
similarity index 100%
rename from vs2013mfc/src/bgslibrary_vs2013_mfc.rc
rename to gui_mfc/src/bgslibrary_vs2013_mfc.rc
diff --git a/vs2013mfc/src/bgslibrary_vs2013_mfc.sln b/gui_mfc/src/bgslibrary_vs2013_mfc.sln
similarity index 100%
rename from vs2013mfc/src/bgslibrary_vs2013_mfc.sln
rename to gui_mfc/src/bgslibrary_vs2013_mfc.sln
diff --git a/vs2013mfc/src/bgslibrary_vs2013_mfc.vcxproj b/gui_mfc/src/bgslibrary_vs2013_mfc.vcxproj
similarity index 100%
rename from vs2013mfc/src/bgslibrary_vs2013_mfc.vcxproj
rename to gui_mfc/src/bgslibrary_vs2013_mfc.vcxproj
diff --git a/vs2013mfc/src/bgslibrary_vs2013_mfc.vcxproj.filters b/gui_mfc/src/bgslibrary_vs2013_mfc.vcxproj.filters
similarity index 100%
rename from vs2013mfc/src/bgslibrary_vs2013_mfc.vcxproj.filters
rename to gui_mfc/src/bgslibrary_vs2013_mfc.vcxproj.filters
diff --git a/vs2013mfc/src/bgslibrary_vs2013_mfc.vcxproj.user b/gui_mfc/src/bgslibrary_vs2013_mfc.vcxproj.user
similarity index 100%
rename from vs2013mfc/src/bgslibrary_vs2013_mfc.vcxproj.user
rename to gui_mfc/src/bgslibrary_vs2013_mfc.vcxproj.user
diff --git a/vs2013mfc/src/res/bgslibrary_vs2013_mfc.ico b/gui_mfc/src/res/bgslibrary_vs2013_mfc.ico
similarity index 100%
rename from vs2013mfc/src/res/bgslibrary_vs2013_mfc.ico
rename to gui_mfc/src/res/bgslibrary_vs2013_mfc.ico
diff --git a/vs2013mfc/src/res/bgslibrary_vs2013_mfc.rc2 b/gui_mfc/src/res/bgslibrary_vs2013_mfc.rc2
similarity index 100%
rename from vs2013mfc/src/res/bgslibrary_vs2013_mfc.rc2
rename to gui_mfc/src/res/bgslibrary_vs2013_mfc.rc2
diff --git a/vs2010mfc/src/resource.h b/gui_mfc/src/resource.h
similarity index 100%
rename from vs2010mfc/src/resource.h
rename to gui_mfc/src/resource.h
diff --git a/vs2010mfc/src/stdafx.cpp b/gui_mfc/src/stdafx.cpp
similarity index 100%
rename from vs2010mfc/src/stdafx.cpp
rename to gui_mfc/src/stdafx.cpp
diff --git a/vs2010mfc/src/stdafx.h b/gui_mfc/src/stdafx.h
similarity index 100%
rename from vs2010mfc/src/stdafx.h
rename to gui_mfc/src/stdafx.h
diff --git a/vs2010mfc/src/targetver.h b/gui_mfc/src/targetver.h
similarity index 100%
rename from vs2010mfc/src/targetver.h
rename to gui_mfc/src/targetver.h
diff --git a/gui_qt/.gitignore b/gui_qt/.gitignore
new file mode 100644
index 0000000..9c28032
--- /dev/null
+++ b/gui_qt/.gitignore
@@ -0,0 +1,9 @@
+_*/
+debug/
+release/
+build_*/
+dataset*/
+binaries*/
+Makefile*
+*.exe
+*.dll
diff --git a/gui_qt/CMakeLists.txt b/gui_qt/CMakeLists.txt
new file mode 100644
index 0000000..83c8920
--- /dev/null
+++ b/gui_qt/CMakeLists.txt
@@ -0,0 +1,52 @@
+cmake_minimum_required(VERSION 2.8.11)
+
+project(bgslibrary_gui)
+
+# Find includes in corresponding build directories
+set(CMAKE_INCLUDE_CURRENT_DIR ON)
+
+# Instruct CMake to run moc automatically when needed.
+set(CMAKE_AUTOMOC ON)
+
+# Handle the Qt uic code generator automatically
+set(CMAKE_AUTOUIC ON)
+
+# Find the Qt5Widgets library
+find_package(Qt5Widgets)
+
+SET(app_RESOURCES application.qrc)
+QT5_ADD_RESOURCES(app_RESOURCES_RCC ${app_RESOURCES})
+
+# Find the OpenCV library
+set(OpenCV_STATIC OFF)
+find_package(OpenCV REQUIRED)
+
+message(STATUS "OpenCV library status:")
+message(STATUS " version: ${OpenCV_VERSION}")
+message(STATUS " libraries: ${OpenCV_LIBS}")
+message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}")
+
+file(GLOB main bgslibrary_gui.cpp mainwindow.cpp qt_utils.cpp texteditor.cpp)
+
+file(GLOB_RECURSE analysis_src ../package_analysis/*.cpp)
+file(GLOB_RECURSE analysis_inc ../package_analysis/*.h)
+file(GLOB_RECURSE bgs_src ../package_bgs/*.cpp ../package_bgs/*.c)
+file(GLOB_RECURSE bgs_inc ../package_bgs/*.h)
+
+include_directories(${CMAKE_SOURCE_DIR} ${OpenCV_INCLUDE_DIRS})
+
+add_library(libbgs STATIC ${bgs_src} ${analysis_src})
+target_link_libraries(libbgs ${OpenCV_LIBS})
+set_property(TARGET libbgs PROPERTY PUBLIC_HEADER ${bgs_inc} ${analysis_inc})
+
+if(WIN32)
+ # set_property(TARGET libbgs PROPERTY SUFFIX ".lib")
+else()
+ set_property(TARGET libbgs PROPERTY OUTPUT_NAME "bgs")
+endif()
+
+# Tell CMake to create the bgslibrary_gui executable
+add_executable(bgslibrary_gui ${main} ${app_RESOURCES_RCC})
+
+# Use the Widgets module from Qt 5.
+target_link_libraries(bgslibrary_gui Qt5::Widgets ${OpenCV_LIBS} libbgs)
diff --git a/gui_qt/README.txt b/gui_qt/README.txt
new file mode 100644
index 0000000..41a4cd2
--- /dev/null
+++ b/gui_qt/README.txt
@@ -0,0 +1,17 @@
+#-------------------------------------------------
+#
+# Project created with Qt 5.6.2
+#
+# Compiling BGSLibrary QT GUI with CMAKE
+#
+#-------------------------------------------------
+# Qt 5.x 64-bit for Desktop (MSVC 2015)
+#-------------------------------------------------
+
+mkdir build
+
+cd build
+
+set OpenCV_DIR=C:\OpenCV3.2.0\build
+
+cmake -DOpenCV_DIR=%OpenCV_DIR% -G "Visual Studio 14 Win64" ..
diff --git a/gui_qt/application.qrc b/gui_qt/application.qrc
new file mode 100644
index 0000000..3e8687f
--- /dev/null
+++ b/gui_qt/application.qrc
@@ -0,0 +1,10 @@
+<!DOCTYPE RCC><RCC version="1.0">
+<qresource>
+ <file>figs/copy.png</file>
+ <file>figs/cut.png</file>
+ <file>figs/new.png</file>
+ <file>figs/open.png</file>
+ <file>figs/paste.png</file>
+ <file>figs/save.png</file>
+</qresource>
+</RCC>
\ No newline at end of file
diff --git a/gui_qt/bgslibrary_gui.cpp b/gui_qt/bgslibrary_gui.cpp
new file mode 100644
index 0000000..e886262
--- /dev/null
+++ b/gui_qt/bgslibrary_gui.cpp
@@ -0,0 +1,38 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "mainwindow.h"
+
+int main(int argc, char *argv[])
+{
+ std::cout << "--------------------------------------------" << std::endl;
+ std::cout << "Background Subtraction Library v2.0.0 " << std::endl;
+ std::cout << "https://github.com/andrewssobral/bgslibrary " << std::endl;
+ std::cout << "by: " << std::endl;
+ std::cout << "Andrews Sobral (andrewssobral@gmail.com) " << std::endl;
+ std::cout << "--------------------------------------------" << std::endl;
+ std::cout << "Using OpenCV version " << CV_VERSION << std::endl;
+
+ QApplication a(argc, argv);
+
+ QCoreApplication::setApplicationName("BGSLibrary");
+ QCoreApplication::setApplicationVersion("2.0.0");
+
+ MainWindow w;
+ w.show();
+
+ return a.exec();
+}
diff --git a/gui_qt/bgslibrary_gui.pro b/gui_qt/bgslibrary_gui.pro
new file mode 100644
index 0000000..feedbf6
--- /dev/null
+++ b/gui_qt/bgslibrary_gui.pro
@@ -0,0 +1,248 @@
+#-------------------------------------------------
+#
+# Project created by QtCreator
+#
+#-------------------------------------------------
+
+QT += core gui
+
+greaterThan(QT_MAJOR_VERSION, 4): QT += widgets
+
+TARGET = bgslibrary_gui
+TEMPLATE = app
+
+# For Windows x64 + Visual Studio 2015 + OpenCV 3.1.0
+#INCLUDEPATH += C:/OpenCV3.1.0/build/include
+#LIBS += -LC:/OpenCV3.1.0/build/x64/vc14/lib -lopencv_world310
+
+# For Windows x64 + Visual Studio 2015 + OpenCV 3.2.0
+INCLUDEPATH += C:/OpenCV3.2.0/build/include
+LIBS += -LC:/OpenCV3.2.0/build/x64/vc14/lib -lopencv_world320
+
+# For Linux
+# INCLUDEPATH += /usr/local/include/opencv
+# LIBS += -L/usr/local/lib
+
+RESOURCES = application.qrc
+
+SOURCES += bgslibrary_gui.cpp\
+ mainwindow.cpp \
+ qt_utils.cpp \
+ texteditor.cpp \
+ ../package_analysis/ForegroundMaskAnalysis.cpp \
+ ../package_analysis/PerformanceUtils.cpp \
+ ../package_analysis/PixelUtils.cpp \
+ ../package_bgs/_template_/Amber.cpp \
+ ../package_bgs/_template_/MyBGS.cpp \
+ ../package_bgs/dp/AdaptiveMedianBGS.cpp \
+ ../package_bgs/dp/Eigenbackground.cpp \
+ ../package_bgs/dp/Error.cpp \
+ ../package_bgs/dp/GrimsonGMM.cpp \
+ ../package_bgs/dp/Image.cpp \
+ ../package_bgs/dp/MeanBGS.cpp \
+ ../package_bgs/dp/PratiMediodBGS.cpp \
+ ../package_bgs/dp/TextureBGS.cpp \
+ ../package_bgs/dp/WrenGA.cpp \
+ ../package_bgs/dp/ZivkovicAGMM.cpp \
+ ../package_bgs/IMBS/IMBS.cpp \
+ ../package_bgs/KDE/KernelTable.cpp \
+ ../package_bgs/KDE/NPBGmodel.cpp \
+ ../package_bgs/KDE/NPBGSubtractor.cpp \
+ ../package_bgs/lb/BGModel.cpp \
+ ../package_bgs/lb/BGModelFuzzyGauss.cpp \
+ ../package_bgs/lb/BGModelFuzzySom.cpp \
+ ../package_bgs/lb/BGModelGauss.cpp \
+ ../package_bgs/lb/BGModelMog.cpp \
+ ../package_bgs/lb/BGModelSom.cpp \
+ ../package_bgs/LBP_MRF/graph.cpp \
+ ../package_bgs/LBP_MRF/maxflow.cpp \
+ ../package_bgs/LBP_MRF/MEDefs.cpp \
+ ../package_bgs/LBP_MRF/MEHistogram.cpp \
+ ../package_bgs/LBP_MRF/MEImage.cpp \
+ ../package_bgs/LBP_MRF/MotionDetection.cpp \
+ ../package_bgs/LBSP/BackgroundSubtractorLBSP.cpp \
+ ../package_bgs/LBSP/BackgroundSubtractorLBSP_.cpp \
+ ../package_bgs/LBSP/BackgroundSubtractorLOBSTER.cpp \
+ ../package_bgs/LBSP/BackgroundSubtractorPAWCS.cpp \
+ ../package_bgs/LBSP/BackgroundSubtractorSuBSENSE.cpp \
+ ../package_bgs/LBSP/LBSP.cpp \
+ ../package_bgs/LBSP/LBSP_.cpp \
+ ../package_bgs/MultiLayer/blob.cpp \
+ ../package_bgs/MultiLayer/BlobExtraction.cpp \
+ ../package_bgs/MultiLayer/BlobResult.cpp \
+ ../package_bgs/MultiLayer/CMultiLayerBGS.cpp \
+ ../package_bgs/MultiLayer/LocalBinaryPattern.cpp \
+ ../package_bgs/PBAS/PBAS.cpp \
+ ../package_bgs/SigmaDelta/sdLaMa091.cpp \
+ ../package_bgs/T2F/FuzzyUtils.cpp \
+ ../package_bgs/T2F/MRF.cpp \
+ ../package_bgs/T2F/T2FGMM.cpp \
+ ../package_bgs/T2F/T2FMRF.cpp \
+ ../package_bgs/TwoPoints/two_points.cpp \
+ ../package_bgs/ViBe/vibe-background-sequential.cpp \
+ ../package_bgs/VuMeter/TBackground.cpp \
+ ../package_bgs/VuMeter/TBackgroundVuMeter.cpp \
+ ../package_bgs/AdaptiveBackgroundLearning.cpp \
+ ../package_bgs/AdaptiveSelectiveBackgroundLearning.cpp \
+ ../package_bgs/DPAdaptiveMedian.cpp \
+ ../package_bgs/DPEigenbackground.cpp \
+ ../package_bgs/DPGrimsonGMM.cpp \
+ ../package_bgs/DPMean.cpp \
+ ../package_bgs/DPPratiMediod.cpp \
+ ../package_bgs/DPTexture.cpp \
+ ../package_bgs/DPWrenGA.cpp \
+ ../package_bgs/DPZivkovicAGMM.cpp \
+ ../package_bgs/FrameDifference.cpp \
+ ../package_bgs/FuzzyChoquetIntegral.cpp \
+ ../package_bgs/FuzzySugenoIntegral.cpp \
+ ../package_bgs/GMG.cpp \
+ ../package_bgs/IndependentMultimodal.cpp \
+ ../package_bgs/KDE.cpp \
+ ../package_bgs/KNN.cpp \
+ ../package_bgs/LBAdaptiveSOM.cpp \
+ ../package_bgs/LBFuzzyAdaptiveSOM.cpp \
+ ../package_bgs/LBFuzzyGaussian.cpp \
+ ../package_bgs/LBMixtureOfGaussians.cpp \
+ ../package_bgs/LBP_MRF.cpp \
+ ../package_bgs/LBSimpleGaussian.cpp \
+ ../package_bgs/LOBSTER.cpp \
+ ../package_bgs/MixtureOfGaussianV1.cpp \
+ ../package_bgs/MixtureOfGaussianV2.cpp \
+ ../package_bgs/MultiCue.cpp \
+ ../package_bgs/MultiLayer.cpp \
+ ../package_bgs/PAWCS.cpp \
+ ../package_bgs/PixelBasedAdaptiveSegmenter.cpp \
+ ../package_bgs/SigmaDelta.cpp \
+ ../package_bgs/StaticFrameDifference.cpp \
+ ../package_bgs/SuBSENSE.cpp \
+ ../package_bgs/T2FGMM_UM.cpp \
+ ../package_bgs/T2FGMM_UV.cpp \
+ ../package_bgs/T2FMRF_UM.cpp \
+ ../package_bgs/T2FMRF_UV.cpp \
+ ../package_bgs/TwoPoints.cpp \
+ ../package_bgs/ViBe.cpp \
+ ../package_bgs/VuMeter.cpp \
+ ../package_bgs/WeightedMovingMean.cpp \
+ ../package_bgs/WeightedMovingVariance.cpp \
+ ../package_bgs/_template_/amber/amber.c
+
+HEADERS += mainwindow.h \
+ qt_utils.h \
+ texteditor.h \
+ ../package_analysis/ForegroundMaskAnalysis.h \
+ ../package_analysis/PerformanceUtils.h \
+ ../package_analysis/PixelUtils.h \
+ ../package_bgs/_template_/amber/amber.h \
+ ../package_bgs/_template_/Amber.h \
+ ../package_bgs/_template_/MyBGS.h \
+ ../package_bgs/dp/AdaptiveMedianBGS.h \
+ ../package_bgs/dp/Bgs.h \
+ ../package_bgs/dp/BgsParams.h \
+ ../package_bgs/dp/Eigenbackground.h \
+ ../package_bgs/dp/Error.h \
+ ../package_bgs/dp/GrimsonGMM.h \
+ ../package_bgs/dp/Image.h \
+ ../package_bgs/dp/MeanBGS.h \
+ ../package_bgs/dp/PratiMediodBGS.h \
+ ../package_bgs/dp/TextureBGS.h \
+ ../package_bgs/dp/WrenGA.h \
+ ../package_bgs/dp/ZivkovicAGMM.h \
+ ../package_bgs/IMBS/IMBS.hpp \
+ ../package_bgs/KDE/KernelTable.h \
+ ../package_bgs/KDE/NPBGmodel.h \
+ ../package_bgs/KDE/NPBGSubtractor.h \
+ ../package_bgs/lb/BGModel.h \
+ ../package_bgs/lb/BGModelFuzzyGauss.h \
+ ../package_bgs/lb/BGModelFuzzySom.h \
+ ../package_bgs/lb/BGModelGauss.h \
+ ../package_bgs/lb/BGModelMog.h \
+ ../package_bgs/lb/BGModelSom.h \
+ ../package_bgs/lb/Types.h \
+ ../package_bgs/LBP_MRF/block.h \
+ ../package_bgs/LBP_MRF/graph.h \
+ ../package_bgs/LBP_MRF/MEDefs.hpp \
+ ../package_bgs/LBP_MRF/MEHistogram.hpp \
+ ../package_bgs/LBP_MRF/MEImage.hpp \
+ ../package_bgs/LBP_MRF/MotionDetection.hpp \
+ ../package_bgs/LBSP/BackgroundSubtractorLBSP.h \
+ ../package_bgs/LBSP/BackgroundSubtractorLBSP_.h \
+ ../package_bgs/LBSP/BackgroundSubtractorLOBSTER.h \
+ ../package_bgs/LBSP/BackgroundSubtractorPAWCS.h \
+ ../package_bgs/LBSP/BackgroundSubtractorSuBSENSE.h \
+ ../package_bgs/LBSP/DistanceUtils.h \
+ ../package_bgs/LBSP/LBSP.h \
+ ../package_bgs/LBSP/LBSP_.h \
+ ../package_bgs/LBSP/RandUtils.h \
+ ../package_bgs/MultiLayer/BackgroundSubtractionAPI.h \
+ ../package_bgs/MultiLayer/BGS.h \
+ ../package_bgs/MultiLayer/blob.h \
+ ../package_bgs/MultiLayer/BlobExtraction.h \
+ ../package_bgs/MultiLayer/BlobLibraryConfiguration.h \
+ ../package_bgs/MultiLayer/BlobResult.h \
+ ../package_bgs/MultiLayer/CMultiLayerBGS.h \
+ ../package_bgs/MultiLayer/LocalBinaryPattern.h \
+ ../package_bgs/MultiLayer/OpenCvDataConversion.h \
+ ../package_bgs/MultiLayer/OpenCvLegacyIncludes.h \
+ ../package_bgs/PBAS/PBAS.h \
+ ../package_bgs/SigmaDelta/sdLaMa091.h \
+ ../package_bgs/T2F/FuzzyUtils.h \
+ ../package_bgs/T2F/MRF.h \
+ ../package_bgs/T2F/T2FGMM.h \
+ ../package_bgs/T2F/T2FMRF.h \
+ ../package_bgs/TwoPoints/two_points.h \
+ ../package_bgs/ViBe/vibe-background-sequential.h \
+ ../package_bgs/VuMeter/TBackground.h \
+ ../package_bgs/VuMeter/TBackgroundVuMeter.h \
+ ../package_bgs/AdaptiveBackgroundLearning.h \
+ ../package_bgs/AdaptiveSelectiveBackgroundLearning.h \
+ ../package_bgs/bgslibrary.h \
+ ../package_bgs/DPAdaptiveMedian.h \
+ ../package_bgs/DPEigenbackground.h \
+ ../package_bgs/DPGrimsonGMM.h \
+ ../package_bgs/DPMean.h \
+ ../package_bgs/DPPratiMediod.h \
+ ../package_bgs/DPTexture.h \
+ ../package_bgs/DPWrenGA.h \
+ ../package_bgs/DPZivkovicAGMM.h \
+ ../package_bgs/FrameDifference.h \
+ ../package_bgs/FuzzyChoquetIntegral.h \
+ ../package_bgs/FuzzySugenoIntegral.h \
+ ../package_bgs/GMG.h \
+ ../package_bgs/IBGS.h \
+ ../package_bgs/IndependentMultimodal.h \
+ ../package_bgs/KDE.h \
+ ../package_bgs/KNN.h \
+ ../package_bgs/LBAdaptiveSOM.h \
+ ../package_bgs/LBFuzzyAdaptiveSOM.h \
+ ../package_bgs/LBFuzzyGaussian.h \
+ ../package_bgs/LBMixtureOfGaussians.h \
+ ../package_bgs/LBP_MRF.h \
+ ../package_bgs/LBSimpleGaussian.h \
+ ../package_bgs/LOBSTER.h \
+ ../package_bgs/MixtureOfGaussianV1.h \
+ ../package_bgs/MixtureOfGaussianV2.h \
+ ../package_bgs/MultiCue.h \
+ ../package_bgs/MultiLayer.h \
+ ../package_bgs/PAWCS.h \
+ ../package_bgs/PixelBasedAdaptiveSegmenter.h \
+ ../package_bgs/SigmaDelta.h \
+ ../package_bgs/StaticFrameDifference.h \
+ ../package_bgs/SuBSENSE.h \
+ ../package_bgs/T2FGMM_UM.h \
+ ../package_bgs/T2FGMM_UV.h \
+ ../package_bgs/T2FMRF_UM.h \
+ ../package_bgs/T2FMRF_UV.h \
+ ../package_bgs/TwoPoints.h \
+ ../package_bgs/ViBe.h \
+ ../package_bgs/VuMeter.h \
+ ../package_bgs/WeightedMovingMean.h \
+ ../package_bgs/WeightedMovingVariance.h
+
+FORMS += mainwindow.ui
+
+DISTFILES += \
+ ../package_bgs/LBSP/LBSP_16bits_dbcross_1ch.i \
+ ../package_bgs/LBSP/LBSP_16bits_dbcross_3ch1t.i \
+ ../package_bgs/LBSP/LBSP_16bits_dbcross_3ch3t.i \
+ ../package_bgs/LBSP/LBSP_16bits_dbcross_s3ch.i \
+ ../package_bgs/ViBe/LICENSE
diff --git a/gui_qt/build/.gitignore b/gui_qt/build/.gitignore
new file mode 100644
index 0000000..4e2a98b
--- /dev/null
+++ b/gui_qt/build/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
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diff --git a/gui_qt/mainwindow.cpp b/gui_qt/mainwindow.cpp
new file mode 100644
index 0000000..bb7eac8
--- /dev/null
+++ b/gui_qt/mainwindow.cpp
@@ -0,0 +1,571 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "mainwindow.h"
+#include "ui_mainwindow.h"
+
+namespace bgslibrary
+{
+ //template<typename T> IBGS* createInstance() { return new T; }
+ //typedef std::map<std::string, IBGS*(*)()> map_ibgs;
+
+ IBGS* get_alg(std::string alg_name) {
+ map_ibgs map;
+ map["FrameDifference"] = &createInstance<FrameDifference>;
+ map["StaticFrameDifference"] = &createInstance<StaticFrameDifference>;
+ map["WeightedMovingMean"] = &createInstance<WeightedMovingMean>;
+ map["WeightedMovingVariance"] = &createInstance<WeightedMovingVariance>;
+#if CV_MAJOR_VERSION == 2
+ map["MixtureOfGaussianV1"] = &createInstance<MixtureOfGaussianV1>; // only for OpenCV 2.x
+#endif
+ map["MixtureOfGaussianV2"] = &createInstance<MixtureOfGaussianV2>;
+ map["AdaptiveBackgroundLearning"] = &createInstance<AdaptiveBackgroundLearning>;
+ map["AdaptiveSelectiveBackgroundLearning"] = &createInstance<AdaptiveSelectiveBackgroundLearning>;
+#if CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
+ map["GMG"] = &createInstance<GMG>; // only for OpenCV >= 2.4.3
+#endif
+#if CV_MAJOR_VERSION == 3
+ map["KNN"] = &createInstance<KNN>; // only on OpenCV 3.x
+#endif
+ map["DPAdaptiveMedian"] = &createInstance<DPAdaptiveMedian>;
+ map["DPGrimsonGMM"] = &createInstance<DPGrimsonGMM>;
+ map["DPZivkovicAGMM"] = &createInstance<DPZivkovicAGMM>;
+ map["DPMean"] = &createInstance<DPMean>;
+ map["DPWrenGA"] = &createInstance<DPWrenGA>;
+ map["DPPratiMediod"] = &createInstance<DPPratiMediod>;
+ map["DPEigenbackground"] = &createInstance<DPEigenbackground>;
+ map["DPTexture"] = &createInstance<DPTexture>;
+ map["T2FGMM_UM"] = &createInstance<T2FGMM_UM>;
+ map["T2FGMM_UV"] = &createInstance<T2FGMM_UV>;
+ map["T2FMRF_UM"] = &createInstance<T2FMRF_UM>;
+ map["T2FMRF_UV"] = &createInstance<T2FMRF_UV>;
+ map["FuzzySugenoIntegral"] = &createInstance<FuzzySugenoIntegral>;
+ map["FuzzyChoquetIntegral"] = &createInstance<FuzzyChoquetIntegral>;
+ map["MultiLayer"] = &createInstance<MultiLayer>;
+ map["PixelBasedAdaptiveSegmenter"] = &createInstance<PixelBasedAdaptiveSegmenter>;
+ map["LBSimpleGaussian"] = &createInstance<LBSimpleGaussian>;
+ map["LBFuzzyGaussian"] = &createInstance<LBFuzzyGaussian>;
+ map["LBMixtureOfGaussians"] = &createInstance<LBMixtureOfGaussians>;
+ map["LBAdaptiveSOM"] = &createInstance<LBAdaptiveSOM>;
+ map["LBFuzzyAdaptiveSOM"] = &createInstance<LBFuzzyAdaptiveSOM>;
+ map["LBP_MRF"] = &createInstance<LBP_MRF>;
+ map["VuMeter"] = &createInstance<VuMeter>;
+ map["KDE"] = &createInstance<KDE>;
+ map["IndependentMultimodal"] = &createInstance<IndependentMultimodal>;
+ map["MultiCue"] = &createInstance<MultiCue>;
+ map["SigmaDelta"] = &createInstance<SigmaDelta>;
+ map["SuBSENSE"] = &createInstance<SuBSENSE>;
+ map["LOBSTER"] = &createInstance<LOBSTER>;
+ map["PAWCS"] = &createInstance<PAWCS>;
+ map["TwoPoints"] = &createInstance<TwoPoints>;
+ map["ViBe"] = &createInstance<ViBe>;
+
+ return map[alg_name]();
+ }
+
+ QStringList get_algs_name()
+ {
+ QStringList stringList;
+ stringList.append("FrameDifference");
+ stringList.append("StaticFrameDifference");
+ stringList.append("WeightedMovingMean");
+ stringList.append("WeightedMovingVariance");
+#if CV_MAJOR_VERSION == 2
+ stringList.append("MixtureOfGaussianV1"); // only for OpenCV 2.x
+#endif
+ stringList.append("MixtureOfGaussianV2");
+ stringList.append("AdaptiveBackgroundLearning");
+ stringList.append("AdaptiveSelectiveBackgroundLearning");
+#if CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
+ stringList.append("GMG"); // only for OpenCV >= 2.4.3
+#endif
+#if CV_MAJOR_VERSION == 3
+ stringList.append("KNN"); // only on OpenCV 3.x
+#endif
+ stringList.append("DPAdaptiveMedian");
+ stringList.append("DPGrimsonGMM");
+ stringList.append("DPZivkovicAGMM");
+ stringList.append("DPMean");
+ stringList.append("DPWrenGA");
+ stringList.append("DPPratiMediod");
+ stringList.append("DPEigenbackground");
+ stringList.append("DPTexture");
+ stringList.append("T2FGMM_UM");
+ stringList.append("T2FGMM_UV");
+ stringList.append("T2FMRF_UM");
+ stringList.append("T2FMRF_UV");
+ stringList.append("FuzzySugenoIntegral");
+ stringList.append("FuzzyChoquetIntegral");
+ stringList.append("MultiLayer");
+ stringList.append("PixelBasedAdaptiveSegmenter");
+ stringList.append("LBSimpleGaussian");
+ stringList.append("LBFuzzyGaussian");
+ stringList.append("LBMixtureOfGaussians");
+ stringList.append("LBAdaptiveSOM");
+ stringList.append("LBFuzzyAdaptiveSOM");
+ stringList.append("LBP_MRF");
+ stringList.append("VuMeter");
+ stringList.append("KDE");
+ stringList.append("IndependentMultimodal");
+ stringList.append("MultiCue");
+ stringList.append("SigmaDelta");
+ stringList.append("SuBSENSE");
+ stringList.append("LOBSTER");
+ stringList.append("PAWCS");
+ stringList.append("TwoPoints");
+ stringList.append("ViBe");
+ return stringList;
+ }
+}
+
+MainWindow::MainWindow(QWidget *parent) :
+ QMainWindow(parent),
+ ui(new Ui::MainWindow)
+{
+ ui->setupUi(this);
+ //QDir applicationPath(QCoreApplication::applicationDirPath());
+ fileName = QDir(".").filePath("dataset/video.avi");
+ //fileName = applicationPath.absolutePath() + "dataset";
+ ui->lineEdit_inputdata->setText(fileName);
+ //fileName = ui->lineEdit_inputdata->text();
+ timer = new QTimer(this); connect(timer, SIGNAL(timeout()), this, SLOT(startCapture()));
+ QStringListModel* listModel = new QStringListModel(bgslibrary::get_algs_name(), NULL);
+ listModel->sort(0);
+ ui->listView_algorithms->setModel(listModel);
+ QModelIndex index = listModel->index(0);
+ ui->listView_algorithms->selectionModel()->select(index, QItemSelectionModel::Select);
+}
+
+MainWindow::~MainWindow()
+{
+ delete ui;
+}
+
+void MainWindow::on_actionExit_triggered()
+{
+ this->close();
+}
+
+void MainWindow::on_pushButton_inputdata_clicked()
+{
+ QFileDialog dialog(this);
+
+ if (ui->checkBox_imageseq->isChecked())
+ dialog.setFileMode(QFileDialog::Directory);
+ else
+ dialog.setFileMode(QFileDialog::ExistingFile);
+ //dialog.setFileMode(QFileDialog::AnyFile);
+
+ dialog.exec();
+ QStringList list = dialog.selectedFiles();
+ /*
+ for(int index = 0; index < list.length(); index++)
+ std::cout << list.at(index).toStdString() << std::endl;
+ */
+ if (list.size() > 0)
+ {
+ fileName = list.at(0);
+ ui->lineEdit_inputdata->setText(fileName);
+ }
+}
+
+void MainWindow::on_pushButton_out_in_clicked()
+{
+ QFileDialog dialog(this);
+ dialog.setDirectory(".");
+ dialog.setFileMode(QFileDialog::Directory);
+ dialog.exec();
+ QStringList list = dialog.selectedFiles();
+ if (list.size() > 0)
+ {
+ fileName = list.at(0);
+ ui->lineEdit_out_in->setText(fileName);
+ }
+}
+
+void MainWindow::on_pushButton_out_fg_clicked()
+{
+ QFileDialog dialog(this);
+ dialog.setDirectory(".");
+ dialog.setFileMode(QFileDialog::Directory);
+ dialog.exec();
+ QStringList list = dialog.selectedFiles();
+ if (list.size() > 0)
+ {
+ fileName = list.at(0);
+ ui->lineEdit_out_fg->setText(fileName);
+ }
+}
+
+void MainWindow::on_pushButton_out_bg_clicked()
+{
+ QFileDialog dialog(this);
+ dialog.setDirectory(".");
+ dialog.setFileMode(QFileDialog::Directory);
+ dialog.exec();
+ QStringList list = dialog.selectedFiles();
+ if (list.size() > 0)
+ {
+ fileName = list.at(0);
+ ui->lineEdit_out_bg->setText(fileName);
+ }
+}
+
+void MainWindow::on_pushButton_start_clicked()
+{
+ useCamera = false;
+ useVideo = false;
+ useSequence = false;
+
+ if (ui->checkBox_webcamera->isChecked())
+ useCamera = true;
+ else
+ {
+ if (ui->checkBox_imageseq->isChecked())
+ useSequence = true;
+ else
+ useVideo = true;
+ }
+
+ if (!timer->isActive() && setUpCapture())
+ {
+ createBGS();
+ startTimer();
+ }
+}
+
+void MainWindow::on_pushButton_stop_clicked()
+{
+ stopTimer();
+}
+
+void MainWindow::createBGS()
+{
+ QString algorithm_name = getSelectedAlgorithmName();
+ bgs = bgslibrary::get_alg(algorithm_name.toStdString());
+ bgs->setShowOutput(false);
+}
+
+void MainWindow::destroyBGS()
+{
+ delete bgs;
+}
+
+void MainWindow::startTimer()
+{
+ std::cout << "startTimer()" << std::endl;
+
+ ui->progressBar->setValue(0);
+ setFrameNumber(0);
+ frameNumber_aux = 0;
+ timer->start(33);
+
+ // disable options
+}
+
+void MainWindow::stopTimer()
+{
+ if (!timer->isActive())
+ return;
+
+ std::cout << "stopTimer()" << std::endl;
+
+ timer->stop();
+ //setFrameNumber(0);
+ //ui->progressBar->setValue(0);
+
+ destroyBGS();
+
+ if (useCamera || useVideo)
+ capture.release();
+
+ // enable options
+}
+
+void MainWindow::setFrameNumber(long long _frameNumber)
+{
+ //std::cout << "setFrameNumber()" << std::endl;
+ frameNumber = _frameNumber;
+ QString txt_frameNumber = QString::fromStdString(its(frameNumber));
+ ui->label_framenumber_txt->setText(txt_frameNumber);
+}
+
+bool MainWindow::setUpCapture()
+{
+ capture_length = 0;
+
+ if (useCamera && !setUpCamera()) {
+ std::cout << "Cannot initialize webcamera!" << std::endl;
+ return false;
+ }
+
+ if (useVideo && !setUpVideo()) {
+ std::cout << "Cannot open video file " << fileName.toStdString() << std::endl;
+ return false;
+ }
+
+ if (useSequence && !setUpSequence()) {
+ std::cout << "Cannot process images at " << fileName.toStdString() << std::endl;
+ return false;
+ }
+
+ if (useCamera || useVideo) {
+ int capture_fps = capture.get(CV_CAP_PROP_FPS);
+ std::cout << "capture_fps: " << capture_fps << std::endl;
+ }
+
+ if (useVideo) {
+ capture_length = capture.get(CV_CAP_PROP_FRAME_COUNT);
+ std::cout << "capture_length: " << capture_length << std::endl;
+ }
+
+ std::cout << "OK!" << std::endl;
+ return true;
+}
+
+void MainWindow::startCapture()
+{
+ //std::cout << "startCapture()" << std::endl;
+ setFrameNumber(frameNumber + 1);
+ cv::Mat cv_frame;
+
+ if (useCamera || useVideo)
+ capture >> cv_frame;
+
+ if (useSequence && (frameNumber - 1) < entryList.length())
+ {
+ QString file = entryList.at(frameNumber - 1);
+ QString filePath = QDir(fileName).filePath(file);
+
+ std::cout << "Processing: " << filePath.toStdString() << std::endl;
+ if (fileExists(filePath))
+ cv_frame = cv::imread(filePath.toStdString());
+ }
+
+ if (cv_frame.empty())
+ {
+ stopTimer();
+ return;
+ }
+
+ if (frameNumber == 1)
+ {
+ int frame_width = cv_frame.size().width;
+ int frame_height = cv_frame.size().height;
+ ui->label_frameresw_txt->setText(QString::fromStdString(its(frame_width)));
+ ui->label_frameresh_txt->setText(QString::fromStdString(its(frame_height)));
+ }
+
+ if (useVideo && capture_length > 0)
+ {
+ double perc = (double(frameNumber) / double(capture_length)) * 100.0;
+ //std::cout << "perc: " << perc << std::endl;
+ ui->progressBar->setValue(perc);
+ }
+
+ int startAt = ui->spinBox_startat->value();
+ if (startAt > 0 && frameNumber < startAt)
+ {
+ timer->setInterval(1);
+ return;
+ }
+ else
+ timer->setInterval(33);
+
+ int stopAt = ui->spinBox_stopat->value();
+ if (stopAt > 0 && frameNumber >= stopAt)
+ {
+ stopTimer();
+ return;
+ }
+
+ cv::Mat cv_frame_small;
+ cv::resize(cv_frame, cv_frame_small, cv::Size(250, 250));
+
+ QImage qt_frame = cv2qimage(cv_frame_small);
+ ui->label_img_in->setPixmap(QPixmap::fromImage(qt_frame, Qt::MonoOnly));
+
+ processFrame(cv_frame);
+}
+
+QImage MainWindow::cv2qimage(const cv::Mat &cv_frame)
+{
+ if (cv_frame.channels() == 3)
+ return Mat2QImage(cv_frame);
+ else
+ return GrayMat2QImage(cv_frame);
+}
+
+void MainWindow::processFrame(const cv::Mat &cv_frame)
+{
+ cv::Mat cv_fg;
+ cv::Mat cv_bg;
+ tic();
+ bgs->process(cv_frame, cv_fg, cv_bg);
+ toc();
+ ui->label_fps_txt->setText(QString::fromStdString(its(fps())));
+
+ cv::Mat cv_fg_small;
+ cv::resize(cv_fg, cv_fg_small, cv::Size(250, 250));
+ QImage qt_fg = cv2qimage(cv_fg_small);
+ ui->label_img_fg->setPixmap(QPixmap::fromImage(qt_fg, Qt::MonoOnly));
+
+ cv::Mat cv_bg_small;
+ cv::resize(cv_bg, cv_bg_small, cv::Size(250, 250));
+ QImage qt_bg = cv2qimage(cv_bg_small);
+ ui->label_img_bg->setPixmap(QPixmap::fromImage(qt_bg, Qt::MonoOnly));
+
+ if (ui->checkBox_save_im->isChecked() || ui->checkBox_save_fg->isChecked() || ui->checkBox_save_bg->isChecked())
+ {
+ if (ui->checkBox_kfn->isChecked())
+ frameNumber_aux = frameNumber;
+ else
+ frameNumber_aux = frameNumber_aux + 1;
+ }
+ if (ui->checkBox_save_im->isChecked())
+ {
+ QString out_im_path = ui->lineEdit_out_in->text();
+ QString out_im_file = QDir(out_im_path).filePath(QString::number(frameNumber_aux) + ".png");
+ cv::imwrite(out_im_file.toStdString(), cv_frame);
+ }
+ if (ui->checkBox_save_fg->isChecked())
+ {
+ QString out_im_path = ui->lineEdit_out_fg->text();
+ QString out_im_file = QDir(out_im_path).filePath(QString::number(frameNumber_aux) + ".png");
+ cv::imwrite(out_im_file.toStdString(), cv_fg);
+ }
+ if (ui->checkBox_save_bg->isChecked())
+ {
+ QString out_im_path = ui->lineEdit_out_bg->text();
+ QString out_im_file = QDir(out_im_path).filePath(QString::number(frameNumber) + ".png");
+ cv::imwrite(out_im_file.toStdString(), cv_bg);
+ }
+}
+
+void MainWindow::tic()
+{
+ duration = static_cast<double>(cv::getTickCount());
+}
+
+void MainWindow::toc()
+{
+ duration = (static_cast<double>(cv::getTickCount()) - duration) / cv::getTickFrequency();
+ //std::cout << "time(sec):" << std::fixed << std::setprecision(6) << duration << std::endl;
+ //std::cout << duration << std::endl;
+}
+
+double MainWindow::fps()
+{
+ //double fps = frameNumber / duration;
+ double fps = 1 / duration;
+ //std::cout << "Estimated frames per second : " << fps << std::endl;
+ return fps;
+}
+
+bool MainWindow::setUpCamera()
+{
+ int cameraIndex = ui->spinBox_webcamera->value();
+ std::cout << "Camera index: " << cameraIndex << std::endl;
+
+ capture.open(cameraIndex);
+ return capture.isOpened();
+}
+
+bool MainWindow::setUpVideo()
+{
+ std::string videoFileName = fileName.toStdString();
+ std::cout << "Openning: " << videoFileName << std::endl;
+ capture.open(videoFileName.c_str());
+ return capture.isOpened();
+}
+
+bool MainWindow::setUpSequence()
+{
+ std::cout << "Directory path: " << fileName.toStdString() << std::endl;
+ if (QDir(fileName).exists())
+ {
+ QDir dir(fileName);
+ QStringList filters;
+ filters << "*.png" << "*.jpg" << "*.bmp" << "*.gif";
+ dir.setNameFilters(filters);
+ //entryList = dir.entryList(QDir::NoDotAndDotDot | QDir::System | QDir::Hidden | QDir::AllDirs | QDir::Files, QDir::DirsFirst);
+ //entryList = dir.entryList(QDir::Filter::Files, QDir::SortFlag::NoSort);
+ dir.setFilter(QDir::Files | QDir::NoSymLinks);
+ dir.setSorting(QDir::NoSort); // will sort manually with std::sort
+ //dir.setSorting(QDir::LocaleAware);
+ entryList = dir.entryList();
+
+ std::cout << entryList.length() << std::endl;
+ if (entryList.length() == 0)
+ {
+ QMessageBox::warning(this, "Warning", "No image found! (png, jpg, bmp, gif)");
+ return false;
+ }
+
+ QCollator collator;
+ collator.setNumericMode(true);
+ std::sort(
+ entryList.begin(),
+ entryList.end(),
+ [&collator](const QString &file1, const QString &file2)
+ {
+ return collator.compare(file1, file2) < 0;
+ });
+
+ // for(int i = 0; i < entryList.length(); i++)
+ // {
+ // QString file = entryList.at(i);
+ // std::cout << file.toStdString() << std::endl;
+ // }
+ return true;
+ }
+ else
+ {
+ QMessageBox::warning(this, "Warning", "Directory path doesn't exist!");
+ return false;
+ }
+}
+
+QString MainWindow::getSelectedAlgorithmName()
+{
+ QModelIndex index = ui->listView_algorithms->currentIndex();
+ QString algorithm_name = index.data(Qt::DisplayRole).toString();
+ return algorithm_name;
+}
+
+void MainWindow::on_listView_algorithms_doubleClicked(const QModelIndex &index)
+{
+ QString algorithm_name = index.data(Qt::DisplayRole).toString();
+ std::cout << "Selected algorithm: " << algorithm_name.toStdString() << std::endl;
+
+ // CodeEditor editor;
+ // editor.setWindowTitle(QObject::tr("Code Editor Example"));
+ // editor.show();
+
+ QString configFileName = QDir(".").filePath("config/" + algorithm_name + ".xml");
+ std::cout << "Looking for: " << configFileName.toStdString() << std::endl;
+
+ if (fileExists(configFileName))
+ {
+ textEditor.loadFile(configFileName);
+ textEditor.show();
+ }
+ else
+ {
+ QMessageBox::warning(this, "Warning", "XML configuration file not found!\nPlease run the algorithm first!");
+ return;
+ }
+}
diff --git a/gui_qt/mainwindow.h b/gui_qt/mainwindow.h
new file mode 100644
index 0000000..a834882
--- /dev/null
+++ b/gui_qt/mainwindow.h
@@ -0,0 +1,110 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <QApplication>
+#include <QCommandLineParser>
+#include <QCommandLineOption>
+#include <QMainWindow>
+#include <QFileDialog>
+#include <QDebug>
+#include <QFile>
+#include <QMessageBox>
+#include <QImage>
+#include <QTimer>
+#include <QStringList>
+#include <QStringListModel>
+#include <QCollator>
+
+#include <opencv2/opencv.hpp>
+
+#include "qt_utils.h"
+#include "texteditor.h"
+#include "../package_bgs/bgslibrary.h"
+
+namespace bgslibrary
+{
+ template<typename T> IBGS * createInstance() { return new T; }
+ typedef std::map<std::string, IBGS*(*)()> map_ibgs;
+
+ IBGS* get_alg(std::string alg_name);
+ QStringList get_algs_name();
+}
+
+namespace Ui {
+ class MainWindow;
+}
+
+class MainWindow : public QMainWindow
+{
+ Q_OBJECT
+
+public:
+ explicit MainWindow(QWidget *parent = 0);
+ ~MainWindow();
+
+ private slots:
+ void on_actionExit_triggered();
+
+ void on_pushButton_inputdata_clicked();
+
+ void on_pushButton_start_clicked();
+
+ void on_pushButton_stop_clicked();
+
+ void on_pushButton_out_in_clicked();
+
+ void on_pushButton_out_fg_clicked();
+
+ void on_pushButton_out_bg_clicked();
+
+ void on_listView_algorithms_doubleClicked(const QModelIndex &index);
+
+private:
+ Ui::MainWindow *ui;
+ QString fileName;
+ cv::VideoCapture capture;
+ bool useCamera = false;
+ bool useVideo = false;
+ bool useSequence = false;
+ QStringList entryList;
+ long long frameNumber = 0;
+ long long frameNumber_aux = 0;
+ bool setUpCapture();
+ bool setUpCamera();
+ bool setUpVideo();
+ bool setUpSequence();
+ QString getSelectedAlgorithmName();
+ QTimer* timer;
+ void startTimer();
+ void stopTimer();
+ void setFrameNumber(long long frameNumber);
+ QImage cv2qimage(const cv::Mat &cv_frame);
+ void processFrame(const cv::Mat &cv_frame);
+ IBGS *bgs;
+ void createBGS();
+ void destroyBGS();
+ double duration = 0;
+ void tic();
+ void toc();
+ double fps();
+ int capture_length = 0;
+ TextEditor textEditor;
+
+ public slots:
+ void startCapture();
+};
diff --git a/gui_qt/mainwindow.ui b/gui_qt/mainwindow.ui
new file mode 100644
index 0000000..75e9e61
--- /dev/null
+++ b/gui_qt/mainwindow.ui
@@ -0,0 +1,631 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<ui version="4.0">
+ <class>MainWindow</class>
+ <widget class="QMainWindow" name="MainWindow">
+ <property name="geometry">
+ <rect>
+ <x>0</x>
+ <y>0</y>
+ <width>1070</width>
+ <height>559</height>
+ </rect>
+ </property>
+ <property name="windowTitle">
+ <string>BGSLibrary QT GUI</string>
+ </property>
+ <widget class="QWidget" name="centralWidget">
+ <widget class="QLabel" name="label_algorithms">
+ <property name="geometry">
+ <rect>
+ <x>10</x>
+ <y>10</y>
+ <width>251</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Algorithms</string>
+ </property>
+ </widget>
+ <widget class="QListView" name="listView_algorithms">
+ <property name="geometry">
+ <rect>
+ <x>10</x>
+ <y>30</y>
+ <width>256</width>
+ <height>361</height>
+ </rect>
+ </property>
+ <property name="editTriggers">
+ <set>QAbstractItemView::NoEditTriggers</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_inputdata">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>10</y>
+ <width>601</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Input (specify a video file or a directory path containing the sequence of images)</string>
+ </property>
+ </widget>
+ <widget class="QLineEdit" name="lineEdit_inputdata">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>30</y>
+ <width>721</width>
+ <height>22</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>./dataset/video.avi</string>
+ </property>
+ </widget>
+ <widget class="QPushButton" name="pushButton_inputdata">
+ <property name="geometry">
+ <rect>
+ <x>1010</x>
+ <y>30</y>
+ <width>40</width>
+ <height>21</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>...</string>
+ </property>
+ </widget>
+ <widget class="QCheckBox" name="checkBox_webcamera">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>60</y>
+ <width>131</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Use web camera</string>
+ </property>
+ </widget>
+ <widget class="QSpinBox" name="spinBox_webcamera">
+ <property name="geometry">
+ <rect>
+ <x>410</x>
+ <y>60</y>
+ <width>42</width>
+ <height>20</height>
+ </rect>
+ </property>
+ </widget>
+ <widget class="QCheckBox" name="checkBox_imageseq">
+ <property name="geometry">
+ <rect>
+ <x>470</x>
+ <y>60</y>
+ <width>151</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Sequence of images?</string>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_startat">
+ <property name="geometry">
+ <rect>
+ <x>945</x>
+ <y>60</y>
+ <width>55</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Start at:</string>
+ </property>
+ </widget>
+ <widget class="QSpinBox" name="spinBox_startat">
+ <property name="geometry">
+ <rect>
+ <x>1000</x>
+ <y>60</y>
+ <width>50</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="maximum">
+ <number>9999</number>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_stopat">
+ <property name="geometry">
+ <rect>
+ <x>945</x>
+ <y>85</y>
+ <width>55</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Stop at:</string>
+ </property>
+ </widget>
+ <widget class="QSpinBox" name="spinBox_stopat">
+ <property name="geometry">
+ <rect>
+ <x>1000</x>
+ <y>85</y>
+ <width>50</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="maximum">
+ <number>9999</number>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_input">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>120</y>
+ <width>250</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Input</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_img_in">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>140</y>
+ <width>250</width>
+ <height>250</height>
+ </rect>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>IMG_INPUT</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_img_fg">
+ <property name="geometry">
+ <rect>
+ <x>540</x>
+ <y>140</y>
+ <width>250</width>
+ <height>250</height>
+ </rect>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>IMG_FOREGROUND</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_img_bg">
+ <property name="geometry">
+ <rect>
+ <x>800</x>
+ <y>140</y>
+ <width>250</width>
+ <height>250</height>
+ </rect>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>IMG_BACKGROUND</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_foreground">
+ <property name="geometry">
+ <rect>
+ <x>540</x>
+ <y>120</y>
+ <width>250</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Foreground mask</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_background">
+ <property name="geometry">
+ <rect>
+ <x>800</x>
+ <y>120</y>
+ <width>250</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Background model</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QCheckBox" name="checkBox_save_im">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>400</y>
+ <width>52</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Save</string>
+ </property>
+ </widget>
+ <widget class="QCheckBox" name="checkBox_save_fg">
+ <property name="geometry">
+ <rect>
+ <x>540</x>
+ <y>400</y>
+ <width>52</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Save</string>
+ </property>
+ </widget>
+ <widget class="QCheckBox" name="checkBox_save_bg">
+ <property name="geometry">
+ <rect>
+ <x>800</x>
+ <y>400</y>
+ <width>52</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Save</string>
+ </property>
+ </widget>
+ <widget class="QPushButton" name="pushButton_stop">
+ <property name="geometry">
+ <rect>
+ <x>960</x>
+ <y>470</y>
+ <width>93</width>
+ <height>23</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Stop</string>
+ </property>
+ </widget>
+ <widget class="QPushButton" name="pushButton_start">
+ <property name="geometry">
+ <rect>
+ <x>850</x>
+ <y>470</y>
+ <width>93</width>
+ <height>23</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Start</string>
+ </property>
+ </widget>
+ <widget class="QProgressBar" name="progressBar">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>470</y>
+ <width>550</width>
+ <height>23</height>
+ </rect>
+ </property>
+ <property name="value">
+ <number>0</number>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_exectime">
+ <property name="geometry">
+ <rect>
+ <x>10</x>
+ <y>400</y>
+ <width>121</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Estimated FPS:</string>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_fps_txt">
+ <property name="geometry">
+ <rect>
+ <x>210</x>
+ <y>400</y>
+ <width>55</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="layoutDirection">
+ <enum>Qt::LeftToRight</enum>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>0</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_framenumber">
+ <property name="geometry">
+ <rect>
+ <x>10</x>
+ <y>420</y>
+ <width>121</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Frame number:</string>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_framenumber_txt">
+ <property name="geometry">
+ <rect>
+ <x>210</x>
+ <y>420</y>
+ <width>55</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="layoutDirection">
+ <enum>Qt::LeftToRight</enum>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>0</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_status">
+ <property name="geometry">
+ <rect>
+ <x>209</x>
+ <y>470</y>
+ <width>61</width>
+ <height>23</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Progress:</string>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_frameres">
+ <property name="geometry">
+ <rect>
+ <x>10</x>
+ <y>440</y>
+ <width>121</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Frame resolution:</string>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_frameresw_txt">
+ <property name="geometry">
+ <rect>
+ <x>140</x>
+ <y>440</y>
+ <width>55</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="layoutDirection">
+ <enum>Qt::LeftToRight</enum>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>0</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_frameresh_txt">
+ <property name="geometry">
+ <rect>
+ <x>210</x>
+ <y>440</y>
+ <width>55</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="layoutDirection">
+ <enum>Qt::LeftToRight</enum>
+ </property>
+ <property name="frameShape">
+ <enum>QFrame::Box</enum>
+ </property>
+ <property name="text">
+ <string>0</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter</set>
+ </property>
+ </widget>
+ <widget class="QLabel" name="label_frameres_2">
+ <property name="geometry">
+ <rect>
+ <x>193</x>
+ <y>440</y>
+ <width>21</width>
+ <height>16</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>x</string>
+ </property>
+ <property name="alignment">
+ <set>Qt::AlignCenter</set>
+ </property>
+ </widget>
+ <widget class="QLineEdit" name="lineEdit_out_in">
+ <property name="geometry">
+ <rect>
+ <x>348</x>
+ <y>400</y>
+ <width>140</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>./output/in/</string>
+ </property>
+ </widget>
+ <widget class="QPushButton" name="pushButton_out_in">
+ <property name="geometry">
+ <rect>
+ <x>490</x>
+ <y>400</y>
+ <width>40</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>...</string>
+ </property>
+ </widget>
+ <widget class="QLineEdit" name="lineEdit_out_fg">
+ <property name="geometry">
+ <rect>
+ <x>608</x>
+ <y>400</y>
+ <width>140</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>./output/fg/</string>
+ </property>
+ </widget>
+ <widget class="QPushButton" name="pushButton_out_fg">
+ <property name="geometry">
+ <rect>
+ <x>750</x>
+ <y>400</y>
+ <width>40</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>...</string>
+ </property>
+ </widget>
+ <widget class="QPushButton" name="pushButton_out_bg">
+ <property name="geometry">
+ <rect>
+ <x>1010</x>
+ <y>400</y>
+ <width>40</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>...</string>
+ </property>
+ </widget>
+ <widget class="QLineEdit" name="lineEdit_out_bg">
+ <property name="geometry">
+ <rect>
+ <x>868</x>
+ <y>400</y>
+ <width>140</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>./output/bg/</string>
+ </property>
+ </widget>
+ <widget class="QCheckBox" name="checkBox_kfn">
+ <property name="geometry">
+ <rect>
+ <x>280</x>
+ <y>420</y>
+ <width>141</width>
+ <height>20</height>
+ </rect>
+ </property>
+ <property name="text">
+ <string>Keep frame number</string>
+ </property>
+ <property name="checked">
+ <bool>true</bool>
+ </property>
+ </widget>
+ </widget>
+ <widget class="QMenuBar" name="menuBar">
+ <property name="geometry">
+ <rect>
+ <x>0</x>
+ <y>0</y>
+ <width>1070</width>
+ <height>26</height>
+ </rect>
+ </property>
+ <widget class="QMenu" name="menuBGSLibrary">
+ <property name="title">
+ <string>BGSLibrary</string>
+ </property>
+ <addaction name="actionExit"/>
+ </widget>
+ <addaction name="menuBGSLibrary"/>
+ </widget>
+ <widget class="QStatusBar" name="statusBar"/>
+ <action name="actionExit">
+ <property name="text">
+ <string>Exit</string>
+ </property>
+ </action>
+ </widget>
+ <layoutdefault spacing="6" margin="11"/>
+ <resources/>
+ <connections/>
+</ui>
diff --git a/gui_qt/qt_utils.cpp b/gui_qt/qt_utils.cpp
new file mode 100644
index 0000000..2464d78
--- /dev/null
+++ b/gui_qt/qt_utils.cpp
@@ -0,0 +1,74 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+
+#include "qt_utils.h"
+
+QImage GrayMat2QImage(cv::Mat const& src) {
+ cv::Mat temp;
+ src.copyTo(temp);
+ QImage dest((const uchar *)temp.data, temp.cols, temp.rows, temp.step, QImage::Format_Indexed8);
+ dest.bits();
+ return dest;
+}
+QImage Mat2QImage(cv::Mat const& src) {
+ cv::Mat temp;
+ cvtColor(src, temp, CV_BGR2RGB);
+ QImage dest((const uchar *)temp.data, temp.cols, temp.rows, temp.step, QImage::Format_RGB888);
+ dest.bits();
+ return dest;
+}
+cv::Mat QImage2Mat(QImage const& src) {
+ cv::Mat tmp(src.height(), src.width(), CV_8UC3, (uchar*)src.bits(), src.bytesPerLine());
+ cv::Mat result;
+ cvtColor(tmp, result, CV_RGB2BGR);
+ return result;
+}
+
+QString base64_encode(const QString string) {
+ QByteArray ba;
+ ba.append(string);
+ return ba.toBase64();
+}
+QString base64_decode(const QString string) {
+ QByteArray ba;
+ ba.append(string);
+ return QByteArray::fromBase64(ba);
+}
+QString md5_encode(const QString string) {
+ QByteArray ba;
+ ba.append(string);
+ return QString(QCryptographicHash::hash((ba), QCryptographicHash::Md5).toHex());
+}
+
+int sti(const std::string &s) {
+ int i;
+ std::stringstream ss;
+ ss << s;
+ ss >> i;
+ return i;
+}
+std::string its(int i) {
+ std::stringstream ss;
+ ss << i;
+ return ss.str();
+}
+
+bool fileExists(QString path) {
+ QFileInfo check_file(path);
+ // check if file exists and if yes: Is it really a file and no directory?
+ return check_file.exists() && check_file.isFile();
+}
diff --git a/gui_qt/qt_utils.h b/gui_qt/qt_utils.h
new file mode 100644
index 0000000..84128c5
--- /dev/null
+++ b/gui_qt/qt_utils.h
@@ -0,0 +1,99 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <sstream>
+#include <string>
+#include <QByteArray>
+#include <QImage>
+#include <QCryptographicHash>
+#include <QFileInfo>
+#include <opencv2/opencv.hpp>
+
+QImage GrayMat2QImage(cv::Mat const& src);
+QImage Mat2QImage(cv::Mat const& src);
+cv::Mat QImage2Mat(QImage const& src);
+
+QString base64_encode(const QString string);
+QString base64_decode(const QString string);
+QString md5_encode(const QString);
+
+int sti(const std::string &s);
+std::string its(int i);
+
+bool fileExists(QString path);
+
+/*
+#include <QFileDialog>
+#include <QApplication>
+#include <QWidget>
+#include <QTreeWidget>
+#include <QPushButton>
+#include <QStringList>
+#include <QModelIndex>
+#include <QDir>
+#include <QDebug>
+
+class FileDialog : public QFileDialog
+{
+ Q_OBJECT
+ public:
+ explicit FileDialog(QWidget *parent = Q_NULLPTR)
+ : QFileDialog(parent)
+ {
+ setOption(QFileDialog::DontUseNativeDialog);
+ setFileMode(QFileDialog::Directory);
+ //setFileMode(QFileDialog::ExistingFiles);
+ //setFileMode(QFileDialog::Directory|QFileDialog::ExistingFiles);
+ for (auto *pushButton : findChildren<QPushButton*>()) {
+ qDebug() << pushButton->text();
+ if (pushButton->text() == "&Open" || pushButton->text() == "&Choose") {
+ openButton = pushButton;
+ break;
+ }
+ }
+ disconnect(openButton, SIGNAL(clicked(bool)));
+ connect(openButton, &QPushButton::clicked, this, &FileDialog::openClicked);
+ treeView = findChild<QTreeView*>();
+ }
+
+ QStringList selected() const
+ {
+ return selectedFilePaths;
+ }
+
+ public slots:
+ void openClicked()
+ {
+ selectedFilePaths.clear();
+ qDebug() << treeView->selectionModel()->selection();
+ for (const auto& modelIndex : treeView->selectionModel()->selectedIndexes()) {
+ qDebug() << modelIndex.column();
+ if (modelIndex.column() == 0)
+ selectedFilePaths.append(directory().absolutePath() + modelIndex.data().toString());
+ }
+ emit filesSelected(selectedFilePaths);
+ hide();
+ qDebug() << selectedFilePaths;
+ }
+
+ private:
+ QTreeView *treeView;
+ QPushButton *openButton;
+ QStringList selectedFilePaths;
+};
+*/
diff --git a/gui_qt/texteditor.cpp b/gui_qt/texteditor.cpp
new file mode 100644
index 0000000..80f45e1
--- /dev/null
+++ b/gui_qt/texteditor.cpp
@@ -0,0 +1,320 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+
+#include <QtWidgets>
+
+#include "texteditor.h"
+
+TextEditor::TextEditor()
+ : textEdit(new QPlainTextEdit)
+{
+ setCentralWidget(textEdit);
+
+ createActions();
+ createStatusBar();
+
+ readSettings();
+
+ connect(textEdit->document(), &QTextDocument::contentsChanged,
+ this, &TextEditor::documentWasModified);
+
+#ifndef QT_NO_SESSIONMANAGER
+ QGuiApplication::setFallbackSessionManagementEnabled(false);
+ connect(qApp, &QGuiApplication::commitDataRequest,
+ this, &TextEditor::commitData);
+#endif
+
+ setCurrentFile(QString());
+ setUnifiedTitleAndToolBarOnMac(true);
+}
+
+void TextEditor::closeEvent(QCloseEvent *event)
+{
+ if (maybeSave()) {
+ writeSettings();
+ event->accept();
+ }
+ else {
+ event->ignore();
+ }
+}
+
+void TextEditor::newFile()
+{
+ if (maybeSave()) {
+ textEdit->clear();
+ setCurrentFile(QString());
+ }
+}
+
+void TextEditor::open()
+{
+ if (maybeSave()) {
+ QString fileName = QFileDialog::getOpenFileName(this);
+ if (!fileName.isEmpty())
+ loadFile(fileName);
+ }
+}
+
+bool TextEditor::save()
+{
+ if (curFile.isEmpty()) {
+ return saveAs();
+ }
+ else {
+ return saveFile(curFile);
+ }
+}
+
+bool TextEditor::saveAs()
+{
+ QFileDialog dialog(this);
+ dialog.setWindowModality(Qt::WindowModal);
+ dialog.setAcceptMode(QFileDialog::AcceptSave);
+ if (dialog.exec() != QDialog::Accepted)
+ return false;
+ return saveFile(dialog.selectedFiles().first());
+}
+
+void TextEditor::about()
+{
+ QMessageBox::about(this, tr("About BGSLibrary"),
+ tr("The <b>BGSLibrary</b> provides an easy-to-use framework "
+ "to perform foreground-background separation in videos."));
+}
+
+void TextEditor::documentWasModified()
+{
+ setWindowModified(textEdit->document()->isModified());
+}
+
+void TextEditor::createActions()
+{
+
+ QMenu *fileMenu = menuBar()->addMenu(tr("&File"));
+ QToolBar *fileToolBar = addToolBar(tr("File"));
+ const QIcon newIcon = QIcon::fromTheme("document-new", QIcon(":/figs/new.png"));
+ QAction *newAct = new QAction(newIcon, tr("&New"), this);
+ newAct->setShortcuts(QKeySequence::New);
+ newAct->setStatusTip(tr("Create a new file"));
+ connect(newAct, &QAction::triggered, this, &TextEditor::newFile);
+ fileMenu->addAction(newAct);
+ fileToolBar->addAction(newAct);
+
+ const QIcon openIcon = QIcon::fromTheme("document-open", QIcon(":/figs/open.png"));
+ QAction *openAct = new QAction(openIcon, tr("&Open..."), this);
+ openAct->setShortcuts(QKeySequence::Open);
+ openAct->setStatusTip(tr("Open an existing file"));
+ connect(openAct, &QAction::triggered, this, &TextEditor::open);
+ fileMenu->addAction(openAct);
+ fileToolBar->addAction(openAct);
+
+ const QIcon saveIcon = QIcon::fromTheme("document-save", QIcon(":/figs/save.png"));
+ QAction *saveAct = new QAction(saveIcon, tr("&Save"), this);
+ saveAct->setShortcuts(QKeySequence::Save);
+ saveAct->setStatusTip(tr("Save the document to disk"));
+ connect(saveAct, &QAction::triggered, this, &TextEditor::save);
+ fileMenu->addAction(saveAct);
+ fileToolBar->addAction(saveAct);
+
+ const QIcon saveAsIcon = QIcon::fromTheme("document-save-as");
+ QAction *saveAsAct = fileMenu->addAction(saveAsIcon, tr("Save &As..."), this, &TextEditor::saveAs);
+ saveAsAct->setShortcuts(QKeySequence::SaveAs);
+ saveAsAct->setStatusTip(tr("Save the document under a new name"));
+
+
+ fileMenu->addSeparator();
+
+ const QIcon exitIcon = QIcon::fromTheme("application-exit");
+ QAction *exitAct = fileMenu->addAction(exitIcon, tr("E&xit"), this, &QWidget::close);
+ exitAct->setShortcuts(QKeySequence::Quit);
+ exitAct->setStatusTip(tr("Exit the application"));
+
+ QMenu *editMenu = menuBar()->addMenu(tr("&Edit"));
+ QToolBar *editToolBar = addToolBar(tr("Edit"));
+#ifndef QT_NO_CLIPBOARD
+ const QIcon cutIcon = QIcon::fromTheme("edit-cut", QIcon(":/figs/cut.png"));
+ QAction *cutAct = new QAction(cutIcon, tr("Cu&t"), this);
+ cutAct->setShortcuts(QKeySequence::Cut);
+ cutAct->setStatusTip(tr("Cut the current selection's contents to the "
+ "clipboard"));
+ connect(cutAct, &QAction::triggered, textEdit, &QPlainTextEdit::cut);
+ editMenu->addAction(cutAct);
+ editToolBar->addAction(cutAct);
+
+ const QIcon copyIcon = QIcon::fromTheme("edit-copy", QIcon(":/figs/copy.png"));
+ QAction *copyAct = new QAction(copyIcon, tr("&Copy"), this);
+ copyAct->setShortcuts(QKeySequence::Copy);
+ copyAct->setStatusTip(tr("Copy the current selection's contents to the "
+ "clipboard"));
+ connect(copyAct, &QAction::triggered, textEdit, &QPlainTextEdit::copy);
+ editMenu->addAction(copyAct);
+ editToolBar->addAction(copyAct);
+
+ const QIcon pasteIcon = QIcon::fromTheme("edit-paste", QIcon(":/figs/paste.png"));
+ QAction *pasteAct = new QAction(pasteIcon, tr("&Paste"), this);
+ pasteAct->setShortcuts(QKeySequence::Paste);
+ pasteAct->setStatusTip(tr("Paste the clipboard's contents into the current "
+ "selection"));
+ connect(pasteAct, &QAction::triggered, textEdit, &QPlainTextEdit::paste);
+ editMenu->addAction(pasteAct);
+ editToolBar->addAction(pasteAct);
+
+ menuBar()->addSeparator();
+
+#endif // !QT_NO_CLIPBOARD
+
+ QMenu *helpMenu = menuBar()->addMenu(tr("&Help"));
+ QAction *aboutAct = helpMenu->addAction(tr("&About"), this, &TextEditor::about);
+ aboutAct->setStatusTip(tr("Show the application's About box"));
+
+
+ QAction *aboutQtAct = helpMenu->addAction(tr("About &Qt"), qApp, &QApplication::aboutQt);
+ aboutQtAct->setStatusTip(tr("Show the Qt library's About box"));
+
+#ifndef QT_NO_CLIPBOARD
+ cutAct->setEnabled(false);
+ copyAct->setEnabled(false);
+ connect(textEdit, &QPlainTextEdit::copyAvailable, cutAct, &QAction::setEnabled);
+ connect(textEdit, &QPlainTextEdit::copyAvailable, copyAct, &QAction::setEnabled);
+#endif // !QT_NO_CLIPBOARD
+}
+
+void TextEditor::createStatusBar()
+{
+ statusBar()->showMessage(tr("Ready"));
+}
+
+void TextEditor::readSettings()
+{
+ QSettings settings(QCoreApplication::organizationName(), QCoreApplication::applicationName());
+ const QByteArray geometry = settings.value("geometry", QByteArray()).toByteArray();
+ if (geometry.isEmpty()) {
+ const QRect availableGeometry = QApplication::desktop()->availableGeometry(this);
+ resize(availableGeometry.width() / 3, availableGeometry.height() / 2);
+ move((availableGeometry.width() - width()) / 2,
+ (availableGeometry.height() - height()) / 2);
+ }
+ else {
+ restoreGeometry(geometry);
+ }
+}
+
+void TextEditor::writeSettings()
+{
+ QSettings settings(QCoreApplication::organizationName(), QCoreApplication::applicationName());
+ settings.setValue("geometry", saveGeometry());
+}
+
+bool TextEditor::maybeSave()
+{
+ if (!textEdit->document()->isModified())
+ return true;
+ const QMessageBox::StandardButton ret
+ = QMessageBox::warning(this, tr("Application"),
+ tr("The document has been modified.\n"
+ "Do you want to save your changes?"),
+ QMessageBox::Save | QMessageBox::Discard | QMessageBox::Cancel);
+ switch (ret) {
+ case QMessageBox::Save:
+ return save();
+ case QMessageBox::Cancel:
+ return false;
+ default:
+ break;
+ }
+ return true;
+}
+
+void TextEditor::loadFile(const QString &fileName)
+{
+ QFile file(fileName);
+ if (!file.open(QFile::ReadOnly | QFile::Text)) {
+ QMessageBox::warning(this, tr("Application"),
+ tr("Cannot read file %1:\n%2.")
+ .arg(QDir::toNativeSeparators(fileName), file.errorString()));
+ return;
+ }
+
+ QTextStream in(&file);
+#ifndef QT_NO_CURSOR
+ QApplication::setOverrideCursor(Qt::WaitCursor);
+#endif
+ textEdit->setPlainText(in.readAll());
+#ifndef QT_NO_CURSOR
+ QApplication::restoreOverrideCursor();
+#endif
+
+ setCurrentFile(fileName);
+ statusBar()->showMessage(tr("File loaded"), 2000);
+}
+
+bool TextEditor::saveFile(const QString &fileName)
+{
+ QFile file(fileName);
+ if (!file.open(QFile::WriteOnly | QFile::Text)) {
+ QMessageBox::warning(this, tr("Application"),
+ tr("Cannot write file %1:\n%2.")
+ .arg(QDir::toNativeSeparators(fileName),
+ file.errorString()));
+ return false;
+ }
+
+ QTextStream out(&file);
+#ifndef QT_NO_CURSOR
+ QApplication::setOverrideCursor(Qt::WaitCursor);
+#endif
+ out << textEdit->toPlainText();
+#ifndef QT_NO_CURSOR
+ QApplication::restoreOverrideCursor();
+#endif
+
+ setCurrentFile(fileName);
+ statusBar()->showMessage(tr("File saved"), 2000);
+ return true;
+}
+
+void TextEditor::setCurrentFile(const QString &fileName)
+{
+ curFile = fileName;
+ textEdit->document()->setModified(false);
+ setWindowModified(false);
+
+ QString shownName = curFile;
+ if (curFile.isEmpty())
+ shownName = "untitled.txt";
+ setWindowFilePath(shownName);
+}
+
+QString TextEditor::strippedName(const QString &fullFileName)
+{
+ return QFileInfo(fullFileName).fileName();
+}
+#ifndef QT_NO_SESSIONMANAGER
+void TextEditor::commitData(QSessionManager &manager)
+{
+ if (manager.allowsInteraction()) {
+ if (!maybeSave())
+ manager.cancel();
+ }
+ else {
+ // Non-interactive: save without asking
+ if (textEdit->document()->isModified())
+ save();
+ }
+}
+#endif
diff --git a/gui_qt/texteditor.h b/gui_qt/texteditor.h
new file mode 100644
index 0000000..c0d5d8f
--- /dev/null
+++ b/gui_qt/texteditor.h
@@ -0,0 +1,64 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#ifndef TEXTEDITOR_H
+#define TEXTEDITOR_H
+
+#include <QMainWindow>
+
+class QAction;
+class QMenu;
+class QPlainTextEdit;
+class QSessionManager;
+
+class TextEditor : public QMainWindow
+{
+ Q_OBJECT
+
+public:
+ TextEditor();
+
+ void loadFile(const QString &fileName);
+
+protected:
+ void closeEvent(QCloseEvent *event) override;
+
+ private slots:
+ void newFile();
+ void open();
+ bool save();
+ bool saveAs();
+ void about();
+ void documentWasModified();
+#ifndef QT_NO_SESSIONMANAGER
+ void commitData(QSessionManager &);
+#endif
+
+private:
+ void createActions();
+ void createStatusBar();
+ void readSettings();
+ void writeSettings();
+ bool maybeSave();
+ bool saveFile(const QString &fileName);
+ void setCurrentFile(const QString &fileName);
+ QString strippedName(const QString &fullFileName);
+
+ QPlainTextEdit *textEdit;
+ QString curFile;
+};
+
+#endif // TEXTEDITOR_H
diff --git a/gui_qt/ui_mainwindow.h b/gui_qt/ui_mainwindow.h
new file mode 100644
index 0000000..eb3f468
--- /dev/null
+++ b/gui_qt/ui_mainwindow.h
@@ -0,0 +1,306 @@
+/********************************************************************************
+** Form generated from reading UI file 'mainwindow.ui'
+**
+** Created by: Qt User Interface Compiler version 5.6.2
+**
+** WARNING! All changes made in this file will be lost when recompiling UI file!
+********************************************************************************/
+
+#ifndef UI_MAINWINDOW_H
+#define UI_MAINWINDOW_H
+
+#include <QtCore/QVariant>
+#include <QtWidgets/QAction>
+#include <QtWidgets/QApplication>
+#include <QtWidgets/QButtonGroup>
+#include <QtWidgets/QCheckBox>
+#include <QtWidgets/QHeaderView>
+#include <QtWidgets/QLabel>
+#include <QtWidgets/QLineEdit>
+#include <QtWidgets/QListView>
+#include <QtWidgets/QMainWindow>
+#include <QtWidgets/QMenu>
+#include <QtWidgets/QMenuBar>
+#include <QtWidgets/QProgressBar>
+#include <QtWidgets/QPushButton>
+#include <QtWidgets/QSpinBox>
+#include <QtWidgets/QStatusBar>
+#include <QtWidgets/QWidget>
+
+QT_BEGIN_NAMESPACE
+
+class Ui_MainWindow
+{
+public:
+ QAction *actionExit;
+ QWidget *centralWidget;
+ QLabel *label_algorithms;
+ QListView *listView_algorithms;
+ QLabel *label_inputdata;
+ QLineEdit *lineEdit_inputdata;
+ QPushButton *pushButton_inputdata;
+ QCheckBox *checkBox_webcamera;
+ QSpinBox *spinBox_webcamera;
+ QCheckBox *checkBox_imageseq;
+ QLabel *label_startat;
+ QSpinBox *spinBox_startat;
+ QLabel *label_stopat;
+ QSpinBox *spinBox_stopat;
+ QLabel *label_input;
+ QLabel *label_img_in;
+ QLabel *label_img_fg;
+ QLabel *label_img_bg;
+ QLabel *label_foreground;
+ QLabel *label_background;
+ QCheckBox *checkBox_save_im;
+ QCheckBox *checkBox_save_fg;
+ QCheckBox *checkBox_save_bg;
+ QPushButton *pushButton_stop;
+ QPushButton *pushButton_start;
+ QProgressBar *progressBar;
+ QLabel *label_exectime;
+ QLabel *label_fps_txt;
+ QLabel *label_framenumber;
+ QLabel *label_framenumber_txt;
+ QLabel *label_status;
+ QLabel *label_frameres;
+ QLabel *label_frameresw_txt;
+ QLabel *label_frameresh_txt;
+ QLabel *label_frameres_2;
+ QLineEdit *lineEdit_out_in;
+ QPushButton *pushButton_out_in;
+ QLineEdit *lineEdit_out_fg;
+ QPushButton *pushButton_out_fg;
+ QPushButton *pushButton_out_bg;
+ QLineEdit *lineEdit_out_bg;
+ QCheckBox *checkBox_kfn;
+ QMenuBar *menuBar;
+ QMenu *menuBGSLibrary;
+ QStatusBar *statusBar;
+
+ void setupUi(QMainWindow *MainWindow)
+ {
+ if (MainWindow->objectName().isEmpty())
+ MainWindow->setObjectName(QStringLiteral("MainWindow"));
+ MainWindow->resize(1070, 559);
+ actionExit = new QAction(MainWindow);
+ actionExit->setObjectName(QStringLiteral("actionExit"));
+ centralWidget = new QWidget(MainWindow);
+ centralWidget->setObjectName(QStringLiteral("centralWidget"));
+ label_algorithms = new QLabel(centralWidget);
+ label_algorithms->setObjectName(QStringLiteral("label_algorithms"));
+ label_algorithms->setGeometry(QRect(10, 10, 251, 16));
+ listView_algorithms = new QListView(centralWidget);
+ listView_algorithms->setObjectName(QStringLiteral("listView_algorithms"));
+ listView_algorithms->setGeometry(QRect(10, 30, 256, 361));
+ listView_algorithms->setEditTriggers(QAbstractItemView::NoEditTriggers);
+ label_inputdata = new QLabel(centralWidget);
+ label_inputdata->setObjectName(QStringLiteral("label_inputdata"));
+ label_inputdata->setGeometry(QRect(280, 10, 601, 16));
+ lineEdit_inputdata = new QLineEdit(centralWidget);
+ lineEdit_inputdata->setObjectName(QStringLiteral("lineEdit_inputdata"));
+ lineEdit_inputdata->setGeometry(QRect(280, 30, 721, 22));
+ pushButton_inputdata = new QPushButton(centralWidget);
+ pushButton_inputdata->setObjectName(QStringLiteral("pushButton_inputdata"));
+ pushButton_inputdata->setGeometry(QRect(1010, 30, 40, 21));
+ checkBox_webcamera = new QCheckBox(centralWidget);
+ checkBox_webcamera->setObjectName(QStringLiteral("checkBox_webcamera"));
+ checkBox_webcamera->setGeometry(QRect(280, 60, 131, 20));
+ spinBox_webcamera = new QSpinBox(centralWidget);
+ spinBox_webcamera->setObjectName(QStringLiteral("spinBox_webcamera"));
+ spinBox_webcamera->setGeometry(QRect(410, 60, 42, 20));
+ checkBox_imageseq = new QCheckBox(centralWidget);
+ checkBox_imageseq->setObjectName(QStringLiteral("checkBox_imageseq"));
+ checkBox_imageseq->setGeometry(QRect(470, 60, 151, 20));
+ label_startat = new QLabel(centralWidget);
+ label_startat->setObjectName(QStringLiteral("label_startat"));
+ label_startat->setGeometry(QRect(945, 60, 55, 20));
+ spinBox_startat = new QSpinBox(centralWidget);
+ spinBox_startat->setObjectName(QStringLiteral("spinBox_startat"));
+ spinBox_startat->setGeometry(QRect(1000, 60, 50, 20));
+ spinBox_startat->setMaximum(9999);
+ label_stopat = new QLabel(centralWidget);
+ label_stopat->setObjectName(QStringLiteral("label_stopat"));
+ label_stopat->setGeometry(QRect(945, 85, 55, 20));
+ spinBox_stopat = new QSpinBox(centralWidget);
+ spinBox_stopat->setObjectName(QStringLiteral("spinBox_stopat"));
+ spinBox_stopat->setGeometry(QRect(1000, 85, 50, 20));
+ spinBox_stopat->setMaximum(9999);
+ label_input = new QLabel(centralWidget);
+ label_input->setObjectName(QStringLiteral("label_input"));
+ label_input->setGeometry(QRect(280, 120, 250, 16));
+ label_input->setAlignment(Qt::AlignCenter);
+ label_img_in = new QLabel(centralWidget);
+ label_img_in->setObjectName(QStringLiteral("label_img_in"));
+ label_img_in->setGeometry(QRect(280, 140, 250, 250));
+ label_img_in->setFrameShape(QFrame::Box);
+ label_img_in->setAlignment(Qt::AlignCenter);
+ label_img_fg = new QLabel(centralWidget);
+ label_img_fg->setObjectName(QStringLiteral("label_img_fg"));
+ label_img_fg->setGeometry(QRect(540, 140, 250, 250));
+ label_img_fg->setFrameShape(QFrame::Box);
+ label_img_fg->setAlignment(Qt::AlignCenter);
+ label_img_bg = new QLabel(centralWidget);
+ label_img_bg->setObjectName(QStringLiteral("label_img_bg"));
+ label_img_bg->setGeometry(QRect(800, 140, 250, 250));
+ label_img_bg->setFrameShape(QFrame::Box);
+ label_img_bg->setAlignment(Qt::AlignCenter);
+ label_foreground = new QLabel(centralWidget);
+ label_foreground->setObjectName(QStringLiteral("label_foreground"));
+ label_foreground->setGeometry(QRect(540, 120, 250, 16));
+ label_foreground->setAlignment(Qt::AlignCenter);
+ label_background = new QLabel(centralWidget);
+ label_background->setObjectName(QStringLiteral("label_background"));
+ label_background->setGeometry(QRect(800, 120, 250, 16));
+ label_background->setAlignment(Qt::AlignCenter);
+ checkBox_save_im = new QCheckBox(centralWidget);
+ checkBox_save_im->setObjectName(QStringLiteral("checkBox_save_im"));
+ checkBox_save_im->setGeometry(QRect(280, 400, 52, 20));
+ checkBox_save_fg = new QCheckBox(centralWidget);
+ checkBox_save_fg->setObjectName(QStringLiteral("checkBox_save_fg"));
+ checkBox_save_fg->setGeometry(QRect(540, 400, 52, 20));
+ checkBox_save_bg = new QCheckBox(centralWidget);
+ checkBox_save_bg->setObjectName(QStringLiteral("checkBox_save_bg"));
+ checkBox_save_bg->setGeometry(QRect(800, 400, 52, 20));
+ pushButton_stop = new QPushButton(centralWidget);
+ pushButton_stop->setObjectName(QStringLiteral("pushButton_stop"));
+ pushButton_stop->setGeometry(QRect(960, 470, 93, 23));
+ pushButton_start = new QPushButton(centralWidget);
+ pushButton_start->setObjectName(QStringLiteral("pushButton_start"));
+ pushButton_start->setGeometry(QRect(850, 470, 93, 23));
+ progressBar = new QProgressBar(centralWidget);
+ progressBar->setObjectName(QStringLiteral("progressBar"));
+ progressBar->setGeometry(QRect(280, 470, 550, 23));
+ progressBar->setValue(0);
+ label_exectime = new QLabel(centralWidget);
+ label_exectime->setObjectName(QStringLiteral("label_exectime"));
+ label_exectime->setGeometry(QRect(10, 400, 121, 16));
+ label_fps_txt = new QLabel(centralWidget);
+ label_fps_txt->setObjectName(QStringLiteral("label_fps_txt"));
+ label_fps_txt->setGeometry(QRect(210, 400, 55, 16));
+ label_fps_txt->setLayoutDirection(Qt::LeftToRight);
+ label_fps_txt->setFrameShape(QFrame::Box);
+ label_fps_txt->setAlignment(Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter);
+ label_framenumber = new QLabel(centralWidget);
+ label_framenumber->setObjectName(QStringLiteral("label_framenumber"));
+ label_framenumber->setGeometry(QRect(10, 420, 121, 16));
+ label_framenumber_txt = new QLabel(centralWidget);
+ label_framenumber_txt->setObjectName(QStringLiteral("label_framenumber_txt"));
+ label_framenumber_txt->setGeometry(QRect(210, 420, 55, 16));
+ label_framenumber_txt->setLayoutDirection(Qt::LeftToRight);
+ label_framenumber_txt->setFrameShape(QFrame::Box);
+ label_framenumber_txt->setAlignment(Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter);
+ label_status = new QLabel(centralWidget);
+ label_status->setObjectName(QStringLiteral("label_status"));
+ label_status->setGeometry(QRect(209, 470, 61, 23));
+ label_frameres = new QLabel(centralWidget);
+ label_frameres->setObjectName(QStringLiteral("label_frameres"));
+ label_frameres->setGeometry(QRect(10, 440, 121, 16));
+ label_frameresw_txt = new QLabel(centralWidget);
+ label_frameresw_txt->setObjectName(QStringLiteral("label_frameresw_txt"));
+ label_frameresw_txt->setGeometry(QRect(140, 440, 55, 16));
+ label_frameresw_txt->setLayoutDirection(Qt::LeftToRight);
+ label_frameresw_txt->setFrameShape(QFrame::Box);
+ label_frameresw_txt->setAlignment(Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter);
+ label_frameresh_txt = new QLabel(centralWidget);
+ label_frameresh_txt->setObjectName(QStringLiteral("label_frameresh_txt"));
+ label_frameresh_txt->setGeometry(QRect(210, 440, 55, 16));
+ label_frameresh_txt->setLayoutDirection(Qt::LeftToRight);
+ label_frameresh_txt->setFrameShape(QFrame::Box);
+ label_frameresh_txt->setAlignment(Qt::AlignRight|Qt::AlignTrailing|Qt::AlignVCenter);
+ label_frameres_2 = new QLabel(centralWidget);
+ label_frameres_2->setObjectName(QStringLiteral("label_frameres_2"));
+ label_frameres_2->setGeometry(QRect(193, 440, 21, 16));
+ label_frameres_2->setAlignment(Qt::AlignCenter);
+ lineEdit_out_in = new QLineEdit(centralWidget);
+ lineEdit_out_in->setObjectName(QStringLiteral("lineEdit_out_in"));
+ lineEdit_out_in->setGeometry(QRect(348, 400, 140, 20));
+ pushButton_out_in = new QPushButton(centralWidget);
+ pushButton_out_in->setObjectName(QStringLiteral("pushButton_out_in"));
+ pushButton_out_in->setGeometry(QRect(490, 400, 40, 20));
+ lineEdit_out_fg = new QLineEdit(centralWidget);
+ lineEdit_out_fg->setObjectName(QStringLiteral("lineEdit_out_fg"));
+ lineEdit_out_fg->setGeometry(QRect(608, 400, 140, 20));
+ pushButton_out_fg = new QPushButton(centralWidget);
+ pushButton_out_fg->setObjectName(QStringLiteral("pushButton_out_fg"));
+ pushButton_out_fg->setGeometry(QRect(750, 400, 40, 20));
+ pushButton_out_bg = new QPushButton(centralWidget);
+ pushButton_out_bg->setObjectName(QStringLiteral("pushButton_out_bg"));
+ pushButton_out_bg->setGeometry(QRect(1010, 400, 40, 20));
+ lineEdit_out_bg = new QLineEdit(centralWidget);
+ lineEdit_out_bg->setObjectName(QStringLiteral("lineEdit_out_bg"));
+ lineEdit_out_bg->setGeometry(QRect(868, 400, 140, 20));
+ checkBox_kfn = new QCheckBox(centralWidget);
+ checkBox_kfn->setObjectName(QStringLiteral("checkBox_kfn"));
+ checkBox_kfn->setGeometry(QRect(280, 420, 141, 20));
+ checkBox_kfn->setChecked(true);
+ MainWindow->setCentralWidget(centralWidget);
+ menuBar = new QMenuBar(MainWindow);
+ menuBar->setObjectName(QStringLiteral("menuBar"));
+ menuBar->setGeometry(QRect(0, 0, 1070, 26));
+ menuBGSLibrary = new QMenu(menuBar);
+ menuBGSLibrary->setObjectName(QStringLiteral("menuBGSLibrary"));
+ MainWindow->setMenuBar(menuBar);
+ statusBar = new QStatusBar(MainWindow);
+ statusBar->setObjectName(QStringLiteral("statusBar"));
+ MainWindow->setStatusBar(statusBar);
+
+ menuBar->addAction(menuBGSLibrary->menuAction());
+ menuBGSLibrary->addAction(actionExit);
+
+ retranslateUi(MainWindow);
+
+ QMetaObject::connectSlotsByName(MainWindow);
+ } // setupUi
+
+ void retranslateUi(QMainWindow *MainWindow)
+ {
+ MainWindow->setWindowTitle(QApplication::translate("MainWindow", "BGSLibrary QT GUI", 0));
+ actionExit->setText(QApplication::translate("MainWindow", "Exit", 0));
+ label_algorithms->setText(QApplication::translate("MainWindow", "Algorithms", 0));
+ label_inputdata->setText(QApplication::translate("MainWindow", "Input (specify a video file or a directory path containing the sequence of images)", 0));
+ lineEdit_inputdata->setText(QApplication::translate("MainWindow", "./dataset/video.avi", 0));
+ pushButton_inputdata->setText(QApplication::translate("MainWindow", "...", 0));
+ checkBox_webcamera->setText(QApplication::translate("MainWindow", "Use web camera", 0));
+ checkBox_imageseq->setText(QApplication::translate("MainWindow", "Sequence of images?", 0));
+ label_startat->setText(QApplication::translate("MainWindow", "Start at:", 0));
+ label_stopat->setText(QApplication::translate("MainWindow", "Stop at:", 0));
+ label_input->setText(QApplication::translate("MainWindow", "Input", 0));
+ label_img_in->setText(QApplication::translate("MainWindow", "IMG_INPUT", 0));
+ label_img_fg->setText(QApplication::translate("MainWindow", "IMG_FOREGROUND", 0));
+ label_img_bg->setText(QApplication::translate("MainWindow", "IMG_BACKGROUND", 0));
+ label_foreground->setText(QApplication::translate("MainWindow", "Foreground mask", 0));
+ label_background->setText(QApplication::translate("MainWindow", "Background model", 0));
+ checkBox_save_im->setText(QApplication::translate("MainWindow", "Save", 0));
+ checkBox_save_fg->setText(QApplication::translate("MainWindow", "Save", 0));
+ checkBox_save_bg->setText(QApplication::translate("MainWindow", "Save", 0));
+ pushButton_stop->setText(QApplication::translate("MainWindow", "Stop", 0));
+ pushButton_start->setText(QApplication::translate("MainWindow", "Start", 0));
+ label_exectime->setText(QApplication::translate("MainWindow", "Estimated FPS:", 0));
+ label_fps_txt->setText(QApplication::translate("MainWindow", "0", 0));
+ label_framenumber->setText(QApplication::translate("MainWindow", "Frame number:", 0));
+ label_framenumber_txt->setText(QApplication::translate("MainWindow", "0", 0));
+ label_status->setText(QApplication::translate("MainWindow", "Progress:", 0));
+ label_frameres->setText(QApplication::translate("MainWindow", "Frame resolution:", 0));
+ label_frameresw_txt->setText(QApplication::translate("MainWindow", "0", 0));
+ label_frameresh_txt->setText(QApplication::translate("MainWindow", "0", 0));
+ label_frameres_2->setText(QApplication::translate("MainWindow", "x", 0));
+ lineEdit_out_in->setText(QApplication::translate("MainWindow", "./output/in/", 0));
+ pushButton_out_in->setText(QApplication::translate("MainWindow", "...", 0));
+ lineEdit_out_fg->setText(QApplication::translate("MainWindow", "./output/fg/", 0));
+ pushButton_out_fg->setText(QApplication::translate("MainWindow", "...", 0));
+ pushButton_out_bg->setText(QApplication::translate("MainWindow", "...", 0));
+ lineEdit_out_bg->setText(QApplication::translate("MainWindow", "./output/bg/", 0));
+ checkBox_kfn->setText(QApplication::translate("MainWindow", "Keep frame number", 0));
+ menuBGSLibrary->setTitle(QApplication::translate("MainWindow", "BGSLibrary", 0));
+ } // retranslateUi
+
+};
+
+namespace Ui {
+ class MainWindow: public Ui_MainWindow {};
+} // namespace Ui
+
+QT_END_NAMESPACE
+
+#endif // UI_MAINWINDOW_H
diff --git a/output/bg/.gitignore b/output/bg/.gitignore
new file mode 100644
index 0000000..4e2a98b
--- /dev/null
+++ b/output/bg/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
diff --git a/output/fg/.gitignore b/output/fg/.gitignore
new file mode 100644
index 0000000..4e2a98b
--- /dev/null
+++ b/output/fg/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
diff --git a/output/in/.gitignore b/output/in/.gitignore
new file mode 100644
index 0000000..4e2a98b
--- /dev/null
+++ b/output/in/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
diff --git a/package_bgs/tb/PerformanceUtils.cpp b/package_analysis/PerformanceUtils.cpp
similarity index 59%
rename from package_bgs/tb/PerformanceUtils.cpp
rename to package_analysis/PerformanceUtils.cpp
index 0d7cf77..6ad5e5f 100644
--- a/package_bgs/tb/PerformanceUtils.cpp
+++ b/package_analysis/PerformanceUtils.cpp
@@ -15,15 +15,16 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "PerformanceUtils.h"
-#include <opencv2/legacy/compat.hpp>
+//#include <opencv2/legacy/compat.hpp>
+//#include <opencv2/highgui/highgui_c.h>
-PerformanceUtils::PerformanceUtils(void){}
+PerformanceUtils::PerformanceUtils(void) {}
-PerformanceUtils::~PerformanceUtils(void){}
+PerformanceUtils::~PerformanceUtils(void) {}
float PerformanceUtils::NrPixels(IplImage *image)
{
- return (float) (image->width * image->height);
+ return (float)(image->width * image->height);
}
float PerformanceUtils::NrAllDetectedPixNotNULL(IplImage *image, IplImage *ground_truth)
@@ -31,19 +32,19 @@ float PerformanceUtils::NrAllDetectedPixNotNULL(IplImage *image, IplImage *groun
//Nombre de tous les pixels non nuls dans Groundthruth et dans image
float Union12 = 0.0;
- unsigned char *pixelGT = (unsigned char*) malloc(1*sizeof(unsigned char));
- unsigned char *pixelI = (unsigned char*) malloc(1*sizeof(unsigned char));
+ unsigned char *pixelGT = (unsigned char*)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelI = (unsigned char*)malloc(1 * sizeof(unsigned char));
PixelUtils p;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
- {
- p.GetGrayPixel(ground_truth,x,y,pixelGT);
- p.GetGrayPixel(image,x,y,pixelI);
+ for (int x = 0; x < image->width; x++)
+ {
+ p.GetGrayPixel(ground_truth, x, y, pixelGT);
+ p.GetGrayPixel(image, x, y, pixelI);
- if((pixelGT[0] != 0) || (pixelI[0] != 0))
+ if ((pixelGT[0] != 0) || (pixelI[0] != 0))
Union12++;
}
}
@@ -51,44 +52,44 @@ float PerformanceUtils::NrAllDetectedPixNotNULL(IplImage *image, IplImage *groun
free(pixelGT);
free(pixelI);
- return Union12;
+ return Union12;
}
float PerformanceUtils::NrTruePositives(IplImage *image, IplImage *ground_truth, bool debug)
{
float nTP = 0.0;
- unsigned char *pixelGT = (unsigned char*) malloc(1*sizeof(unsigned char));
- unsigned char *pixelI = (unsigned char*) malloc(1*sizeof(unsigned char));
+ unsigned char *pixelGT = (unsigned char*)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelI = (unsigned char*)malloc(1 * sizeof(unsigned char));
IplImage *TPimage = 0;
- if(debug)
+ if (debug)
{
- TPimage = cvCreateImage(cvSize(image->width,image->height),image->depth,image->nChannels);
- cvFillImage(TPimage,0.0);
+ TPimage = cvCreateImage(cvSize(image->width, image->height), image->depth, image->nChannels);
+ cvSetZero(TPimage);
}
PixelUtils p;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
- {
- p.GetGrayPixel(ground_truth,x,y,pixelGT);
- p.GetGrayPixel(image,x,y,pixelI);
+ for (int x = 0; x < image->width; x++)
+ {
+ p.GetGrayPixel(ground_truth, x, y, pixelGT);
+ p.GetGrayPixel(image, x, y, pixelI);
- if((pixelGT[0] != 0) && (pixelI[0] != 0))
+ if ((pixelGT[0] != 0) && (pixelI[0] != 0))
{
- if(debug)
- p.PutGrayPixel(TPimage,x,y,*pixelI);
+ if (debug)
+ p.PutGrayPixel(TPimage, x, y, *pixelI);
nTP++;
}
}
}
- if(debug)
+ if (debug)
{
cvNamedWindow("TPImage", 0);
cvShowImage("TPImage", TPimage);
@@ -101,46 +102,46 @@ float PerformanceUtils::NrTruePositives(IplImage *image, IplImage *ground_truth,
free(pixelGT);
free(pixelI);
- return nTP;
+ return nTP;
}
float PerformanceUtils::NrTrueNegatives(IplImage* image, IplImage* ground_truth, bool debug)
{
float nTN = 0.0;
- unsigned char *pixelGT = (unsigned char *)malloc(1*sizeof(unsigned char));
- unsigned char *pixelI = (unsigned char *)malloc(1*sizeof(unsigned char));
+ unsigned char *pixelGT = (unsigned char *)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelI = (unsigned char *)malloc(1 * sizeof(unsigned char));
IplImage *TNimage = 0;
- if(debug)
+ if (debug)
{
- TNimage = cvCreateImage(cvSize(image->width,image->height),image->depth,image->nChannels);
- cvFillImage(TNimage, 0.0);
+ TNimage = cvCreateImage(cvSize(image->width, image->height), image->depth, image->nChannels);
+ cvSetZero(TNimage);
}
PixelUtils p;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
+ for (int x = 0; x < image->width; x++)
{
- p.GetGrayPixel(ground_truth,x,y,pixelGT);
- p.GetGrayPixel(image,x,y,pixelI);
+ p.GetGrayPixel(ground_truth, x, y, pixelGT);
+ p.GetGrayPixel(image, x, y, pixelI);
- if((pixelGT[0] == 0) && (pixelI[0] == 0.0))
+ if ((pixelGT[0] == 0) && (pixelI[0] == 0.0))
{
*pixelI = 255;
- if(debug)
- p.PutGrayPixel(TNimage,x,y,*pixelI);
+ if (debug)
+ p.PutGrayPixel(TNimage, x, y, *pixelI);
nTN++;
- }
+ }
}
}
- if(debug)
+ if (debug)
{
cvNamedWindow("TNImage", 0);
cvShowImage("TNImage", TNimage);
@@ -156,41 +157,41 @@ float PerformanceUtils::NrTrueNegatives(IplImage* image, IplImage* ground_truth,
return nTN;
}
-float PerformanceUtils::NrFalsePositives(IplImage *image, IplImage *ground_truth,bool debug)
+float PerformanceUtils::NrFalsePositives(IplImage *image, IplImage *ground_truth, bool debug)
{
float nFP = 0.0;
- unsigned char *pixelGT = (unsigned char*) malloc(1*sizeof(unsigned char));
- unsigned char *pixelI = (unsigned char*) malloc(1*sizeof(unsigned char));
+ unsigned char *pixelGT = (unsigned char*)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelI = (unsigned char*)malloc(1 * sizeof(unsigned char));
IplImage *FPimage = 0;
- if(debug)
+ if (debug)
{
- FPimage = cvCreateImage(cvSize(image->width,image->height),image->depth,image->nChannels);
- cvFillImage(FPimage, 0.0);
+ FPimage = cvCreateImage(cvSize(image->width, image->height), image->depth, image->nChannels);
+ cvSetZero(FPimage);
}
PixelUtils p;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
+ for (int x = 0; x < image->width; x++)
{
- p.GetGrayPixel(ground_truth,x,y,pixelGT);
- p.GetGrayPixel(image,x,y,pixelI);
+ p.GetGrayPixel(ground_truth, x, y, pixelGT);
+ p.GetGrayPixel(image, x, y, pixelI);
- if((pixelGT[0] == 0) && (pixelI[0] != 0))
+ if ((pixelGT[0] == 0) && (pixelI[0] != 0))
{
- if(debug)
- p.PutGrayPixel(FPimage,x,y,*pixelI);
+ if (debug)
+ p.PutGrayPixel(FPimage, x, y, *pixelI);
nFP++;
}
}
}
- if(debug)
+ if (debug)
{
cvNamedWindow("FPImage", 0);
cvShowImage("FPImage", FPimage);
@@ -203,44 +204,44 @@ float PerformanceUtils::NrFalsePositives(IplImage *image, IplImage *ground_truth
free(pixelGT);
free(pixelI);
- return nFP;
+ return nFP;
}
float PerformanceUtils::NrFalseNegatives(IplImage * image, IplImage *ground_truth, bool debug)
{
float nFN = 0.0;
- unsigned char *pixelGT = (unsigned char*) malloc(1*sizeof(unsigned char));
- unsigned char *pixelI = (unsigned char*) malloc(1*sizeof(unsigned char));
+ unsigned char *pixelGT = (unsigned char*)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelI = (unsigned char*)malloc(1 * sizeof(unsigned char));
IplImage *FNimage = 0;
- if(debug)
+ if (debug)
{
- FNimage = cvCreateImage(cvSize(image->width,image->height),image->depth,image->nChannels);
- cvFillImage(FNimage, 0.0);
+ FNimage = cvCreateImage(cvSize(image->width, image->height), image->depth, image->nChannels);
+ cvSetZero(FNimage);
}
PixelUtils p;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
+ for (int x = 0; x < image->width; x++)
{
- p.GetGrayPixel(ground_truth,x,y,pixelGT);
- p.GetGrayPixel(image,x,y,pixelI);
+ p.GetGrayPixel(ground_truth, x, y, pixelGT);
+ p.GetGrayPixel(image, x, y, pixelI);
- if((pixelGT[0] != 0) && (pixelI[0] == 0))
+ if ((pixelGT[0] != 0) && (pixelI[0] == 0))
{
- if(debug)
- p.PutGrayPixel(FNimage,x,y,*pixelGT);
+ if (debug)
+ p.PutGrayPixel(FNimage, x, y, *pixelGT);
nFN++;
}
}
}
- if(debug)
+ if (debug)
{
cvNamedWindow("FNImage", 0);
cvShowImage("FNImage", FNimage);
@@ -253,19 +254,19 @@ float PerformanceUtils::NrFalseNegatives(IplImage * image, IplImage *ground_trut
free(pixelGT);
free(pixelI);
- return nFN;
+ return nFN;
}
float PerformanceUtils::SimilarityMeasure(IplImage *image, IplImage *ground_truth, bool debug)
{
- cv::Mat img_input(image,true);
- cv::Mat img_ref(ground_truth,true);
+ cv::Mat img_input = cv::cvarrToMat(image, true);
+ cv::Mat img_ref = cv::cvarrToMat(ground_truth, true);
int rn = cv::countNonZero(img_ref);
cv::Mat i;
cv::Mat u;
- if(rn > 0)
+ if (rn > 0)
{
i = img_input & img_ref;
u = img_input | img_ref;
@@ -278,16 +279,16 @@ float PerformanceUtils::SimilarityMeasure(IplImage *image, IplImage *ground_trut
int in = cv::countNonZero(i);
int un = cv::countNonZero(u);
-
+
double s = (((double)in) / ((double)un));
-
- if(debug)
+
+ if (debug)
{
cv::imshow("A^B", i);
cv::imshow("AvB", u);
//std::cout << "Similarity Measure: " << s << std::endl;
-
+
//<< " press ENTER to continue" << std::endl;
//cv::waitKey(0);
}
@@ -295,45 +296,45 @@ float PerformanceUtils::SimilarityMeasure(IplImage *image, IplImage *ground_trut
return s;
}
-void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool saveResults, char* filename)
+void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool saveResults, std::string filename)
{
- unsigned char *pixelGT = (unsigned char*) malloc(1*sizeof(unsigned char));
- unsigned char *pixelI = (unsigned char*) malloc(1*sizeof(unsigned char));
+ unsigned char *pixelGT = (unsigned char*)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelI = (unsigned char*)malloc(1 * sizeof(unsigned char));
- IplImage *ROCimage = cvCreateImage(cvSize(image->width,image->height),image->depth,image->nChannels);
- cvFillImage(ROCimage, 0.0);
+ IplImage *ROCimage = cvCreateImage(cvSize(image->width, image->height), image->depth, image->nChannels);
+ cvSetZero(ROCimage);
PixelUtils p;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
+ for (int x = 0; x < image->width; x++)
{
- p.GetGrayPixel(ground_truth,x,y,pixelGT);
- p.GetGrayPixel(image,x,y,pixelI);
+ p.GetGrayPixel(ground_truth, x, y, pixelGT);
+ p.GetGrayPixel(image, x, y, pixelI);
- if((pixelGT[0] != 0) && (pixelI[0] != 0)) // TP
+ if ((pixelGT[0] != 0) && (pixelI[0] != 0)) // TP
{
*pixelI = 30;
- p.PutGrayPixel(ROCimage,x,y,*pixelI);
+ p.PutGrayPixel(ROCimage, x, y, *pixelI);
}
- if((pixelGT[0] == 0) && (pixelI[0] == 0.0)) // TN
+ if ((pixelGT[0] == 0) && (pixelI[0] == 0.0)) // TN
{
*pixelI = 0;
- p.PutGrayPixel(ROCimage,x,y,*pixelI);
- }
+ p.PutGrayPixel(ROCimage, x, y, *pixelI);
+ }
- if((pixelGT[0] == 0) && (pixelI[0] != 0)) // FP
+ if ((pixelGT[0] == 0) && (pixelI[0] != 0)) // FP
{
*pixelI = 255;
- p.PutGrayPixel(ROCimage,x,y,*pixelI);
+ p.PutGrayPixel(ROCimage, x, y, *pixelI);
}
- if((pixelGT[0] != 0) && (pixelI[0] == 0)) // FN
+ if ((pixelGT[0] != 0) && (pixelI[0] == 0)) // FN
{
*pixelI = 100;
- p.PutGrayPixel(ROCimage,x,y,*pixelI);
+ p.PutGrayPixel(ROCimage, x, y, *pixelI);
}
}
}
@@ -341,10 +342,10 @@ void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool sa
cvNamedWindow("ROC image", 0);
cvShowImage("ROC image", ROCimage);
- if(saveResults)
+ if (saveResults)
{
- unsigned char *pixelOI = (unsigned char*) malloc(1*sizeof(unsigned char));
- unsigned char *pixelROC = (unsigned char*) malloc(1*sizeof(unsigned char));
+ unsigned char *pixelOI = (unsigned char*)malloc(1 * sizeof(unsigned char));
+ unsigned char *pixelROC = (unsigned char*)malloc(1 * sizeof(unsigned char));
float** freq;
float nTP = 0.0;
@@ -352,45 +353,45 @@ void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool sa
float nFP = 0.0;
float nFN = 0.0;
- freq = (float**) malloc(256*(sizeof(float*)));
- for(int i = 0; i < 256; i++)
- freq[i] = (float*) malloc(7 * (sizeof(float)));
+ freq = (float**)malloc(256 * (sizeof(float*)));
+ for (int i = 0; i < 256; i++)
+ freq[i] = (float*)malloc(7 * (sizeof(float)));
- for(int i = 0; i < 256; i++)
- for(int j = 0; j < 6; j++)
+ for (int i = 0; i < 256; i++)
+ for (int j = 0; j < 6; j++)
freq[i][j] = 0.0;
- for(int y = 0; y < image->height; y++)
+ for (int y = 0; y < image->height; y++)
{
- for(int x = 0; x < image->width; x++)
+ for (int x = 0; x < image->width; x++)
{
- for(int i = 0; i < 256; i++)
+ for (int i = 0; i < 256; i++)
{
- p.GetGrayPixel(image,x,y,pixelOI);
- p.GetGrayPixel(ROCimage,x,y,pixelROC);
+ p.GetGrayPixel(image, x, y, pixelOI);
+ p.GetGrayPixel(ROCimage, x, y, pixelROC);
- if((pixelOI[0] == i) && (pixelROC[0] == 30.0)) // TP
+ if ((pixelOI[0] == i) && (pixelROC[0] == 30.0)) // TP
{
nTP++;
freq[i][0] = nTP;
break;
}
- if((pixelOI[0] == i) && (pixelROC[0] == 0.0)) // TN
+ if ((pixelOI[0] == i) && (pixelROC[0] == 0.0)) // TN
{
nTN++;
freq[i][1] = nTN;
break;
}
- if((pixelOI[0] == i) && (pixelROC[0] == 255.0)) // FP
+ if ((pixelOI[0] == i) && (pixelROC[0] == 255.0)) // FP
{
nFP++;
freq[i][2] = nFP;
break;
}
- if((pixelOI[0] == i) && (pixelROC[0] == 100)) // FN
+ if ((pixelOI[0] == i) && (pixelROC[0] == 100)) // FN
{
nFN++;
freq[i][3] = nFN;
@@ -409,17 +410,17 @@ void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool sa
std::ofstream f(filename);
- if(!f.is_open())
+ if (!f.is_open())
std::cout << "Failed to open file " << filename << " for writing!" << std::endl;
else
{
f << " I TP TN FP FN FPR FNR DR \n" << std::endl;
-
- for(int i = 0; i < 256; i++)
+
+ for (int i = 0; i < 256; i++)
{
//printf("%4d - TP:%5.0f, TN:%5.0f, FP:%5.0f, FN:%5.0f,", i, freq[i][0], freq[i][1], freq[i][2], freq[i][3]);
- if((freq[i][3] + freq[i][0] != 0.0) && (freq[i][2] + freq[i][1] != 0.0))
+ if ((freq[i][3] + freq[i][0] != 0.0) && (freq[i][2] + freq[i][1] != 0.0))
{
freq[i][4] = freq[i][3] / (freq[i][3] + freq[i][0]); // FNR = FN / (TP + FN);
freq[i][5] = freq[i][2] / (freq[i][2] + freq[i][1]); // FPR = FP / (FP + TN);
@@ -429,12 +430,12 @@ void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool sa
////fprintf(f," %4d %1.6f %1.6f\n",i,freq[i][5],freq[i][4]);
////fprintf(f," %1.6f %1.6f\n",freq[i][5],freq[i][4]);
char line[255];
- sprintf(line,"%3d %6.0f %6.0f %6.0f %6.0f %1.6f %1.6f %1.6f\n",
+ sprintf(line, "%3d %6.0f %6.0f %6.0f %6.0f %1.6f %1.6f %1.6f\n",
i, freq[i][0], freq[i][1], freq[i][2], freq[i][3], freq[i][5], freq[i][4], freq[i][6]);
f << line;
}
//else
- //printf("\n");
+ //printf("\n");
}
std::cout << "Results saved in " << filename << std::endl;
@@ -454,36 +455,36 @@ void PerformanceUtils::ImageROC(IplImage *image, IplImage* ground_truth, bool sa
free(pixelI);
}
-void PerformanceUtils::PerformanceEvaluation(IplImage *image, IplImage *ground_truth, bool saveResults, char* filename, bool debug)
+void PerformanceUtils::PerformanceEvaluation(IplImage *image, IplImage *ground_truth, bool saveResults, std::string filename, bool debug)
{
float N = 0;
N = NrPixels(image);
float U = 0;
U = NrAllDetectedPixNotNULL(image, ground_truth);
-
+
float TP = 0;
TP = NrTruePositives(image, ground_truth, debug);
-
+
float TN = 0;
TN = NrTrueNegatives(image, ground_truth, debug);
-
+
float FP = 0;
FP = NrFalsePositives(image, ground_truth, debug);
-
+
float FN = 0;
FN = NrFalseNegatives(image, ground_truth, debug);
-
+
float DetectionRate = TP / (TP + FN);
float Precision = TP / (TP + FP);
float Fmeasure = (2 * DetectionRate * Precision) / (DetectionRate + Precision);
float Accuracy = (TN + TP) / N;
float FalseNegativeRate = FN / (TP + FN);
-
+
float FalsePositiveRate = FP / (FP + TN);
float TruePositiveRate = TP / (TP + FN);
-
+
float SM = 0;
SM = SimilarityMeasure(image, ground_truth, debug);
@@ -506,11 +507,11 @@ void PerformanceUtils::PerformanceEvaluation(IplImage *image, IplImage *ground_t
std::string results = sstm.str();
std::cout << results;
- if(saveResults)
+ if (saveResults)
{
std::ofstream f(filename);
- if(!f.is_open())
+ if (!f.is_open())
std::cout << "Failed to open file " << filename << " for writing!" << std::endl;
else
{
diff --git a/package_bgs/tb/PerformanceUtils.h b/package_analysis/PerformanceUtils.h
similarity index 82%
rename from package_bgs/tb/PerformanceUtils.h
rename to package_analysis/PerformanceUtils.h
index 9257098..4be392f 100644
--- a/package_bgs/tb/PerformanceUtils.h
+++ b/package_analysis/PerformanceUtils.h
@@ -15,23 +15,11 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-/*
-Code provided by Thierry BOUWMANS
-
-Maitre de Conf�rences
-Laboratoire MIA
-Universit� de La Rochelle
-17000 La Rochelle
-France
-tbouwman@univ-lr.fr
-http://sites.google.com/site/thierrybouwmans/
-*/
#include <stdio.h>
#include <fstream>
#include <opencv2/opencv.hpp>
-
#include "PixelUtils.h"
class PerformanceUtils
@@ -48,7 +36,7 @@ public:
float NrFalseNegatives(IplImage *image, IplImage *ground_truth, bool debug = false);
float SimilarityMeasure(IplImage *image, IplImage *ground_truth, bool debug = false);
- void ImageROC(IplImage *image, IplImage* ground_truth, bool saveResults = false, char* filename = "");
- void PerformanceEvaluation(IplImage *image, IplImage *ground_truth, bool saveResults = false, char* filename = "", bool debug = false);
+ void ImageROC(IplImage *image, IplImage* ground_truth, bool saveResults = false, std::string filename = "");
+ void PerformanceEvaluation(IplImage *image, IplImage *ground_truth, bool saveResults = false, std::string filename = "", bool debug = false);
};
diff --git a/package_analysis/PixelUtils.cpp b/package_analysis/PixelUtils.cpp
new file mode 100644
index 0000000..adce122
--- /dev/null
+++ b/package_analysis/PixelUtils.cpp
@@ -0,0 +1,351 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "PixelUtils.h"
+
+PixelUtils::PixelUtils(void) {}
+PixelUtils::~PixelUtils(void) {}
+
+void PixelUtils::ColorConversion(IplImage* RGBImage, IplImage* ConvertedImage, int color_space)
+{
+ // Space Color RGB - Nothing to do!
+ if (color_space == 1)
+ cvCopy(RGBImage, ConvertedImage);
+
+ // Space Color Ohta
+ if (color_space == 2)
+ cvttoOTHA(RGBImage, ConvertedImage);
+
+ // Space Color HSV - V Intensity - (H,S) Chromaticity
+ if (color_space == 3)
+ cvCvtColor(RGBImage, ConvertedImage, CV_BGR2HSV);
+
+ // Space Color YCrCb - Y Intensity - (Cr,Cb) Chromaticity
+ if (color_space == 4)
+ cvCvtColor(RGBImage, ConvertedImage, CV_BGR2YCrCb);
+}
+
+void PixelUtils::cvttoOTHA(IplImage* RGBImage, IplImage* OthaImage)
+{
+ float* OhtaPixel = (float*)malloc(3 * (sizeof(float)));
+ float* RGBPixel = (float*)malloc(3 * (sizeof(float)));
+
+ for (int i = 0; i < RGBImage->width; i++)
+ {
+ for (int j = 0; j < RGBImage->height; j++)
+ {
+ GetPixel(RGBImage, i, j, RGBPixel);
+
+ // I1 = (R + G + B) / 3
+ *OhtaPixel = (*(RGBPixel)+(*(RGBPixel + 1)) + (*(RGBPixel + 2))) / 3.0;
+
+ // I2 = (R - B) / 2
+ *(OhtaPixel + 1) = (*RGBPixel - (*(RGBPixel + 2))) / 2.0;
+
+ // I3 = (2G - R - B) / 4
+ *(OhtaPixel + 2) = (2 * (*(RGBPixel + 1)) - (*RGBPixel) - (*(RGBPixel + 2))) / 4.0;
+
+ PutPixel(OthaImage, i, j, OhtaPixel);
+ }
+ }
+
+ free(OhtaPixel);
+ free(RGBPixel);
+}
+
+void PixelUtils::PostProcessing(IplImage *InputImage)
+{
+ IplImage *ResultImage = cvCreateImage(cvSize(InputImage->width, InputImage->height), IPL_DEPTH_32F, 3);
+
+ cvErode(InputImage, ResultImage, NULL, 1);
+ cvDilate(ResultImage, InputImage, NULL, 0);
+
+ cvReleaseImage(&ResultImage);
+}
+
+void PixelUtils::GetPixel(IplImage *image, int m, int n, unsigned char *pixelcourant)
+{
+ for (int k = 0; k < 3; k++)
+ pixelcourant[k] = ((unsigned char*)(image->imageData + image->widthStep*n))[m * 3 + k];
+}
+
+void PixelUtils::GetGrayPixel(IplImage *image, int m, int n, unsigned char *pixelcourant)
+{
+ *pixelcourant = ((unsigned char*)(image->imageData + image->widthStep*n))[m];
+}
+
+void PixelUtils::PutPixel(IplImage *image, int p, int q, unsigned char *pixelcourant)
+{
+ for (int r = 0; r < 3; r++)
+ ((unsigned char*)(image->imageData + image->widthStep*q))[p * 3 + r] = pixelcourant[r];
+}
+
+void PixelUtils::PutGrayPixel(IplImage *image, int p, int q, unsigned char pixelcourant)
+{
+ ((unsigned char*)(image->imageData + image->widthStep*q))[p] = pixelcourant;
+}
+
+void PixelUtils::GetPixel(IplImage *image, int m, int n, float *pixelcourant)
+{
+ for (int k = 0; k < 3; k++)
+ pixelcourant[k] = ((float*)(image->imageData + image->widthStep*n))[m * 3 + k];
+}
+
+void PixelUtils::GetGrayPixel(IplImage *image, int m, int n, float *pixelcourant)
+{
+ *pixelcourant = ((float*)(image->imageData + image->widthStep*n))[m];
+}
+
+void PixelUtils::PutPixel(IplImage *image, int p, int q, float *pixelcourant)
+{
+ for (int r = 0; r < 3; r++)
+ ((float*)(image->imageData + image->widthStep*q))[p * 3 + r] = pixelcourant[r];
+}
+
+void PixelUtils::PutGrayPixel(IplImage *image, int p, int q, float pixelcourant)
+{
+ ((float*)(image->imageData + image->widthStep*q))[p] = pixelcourant;
+}
+
+void PixelUtils::getNeighberhoodGrayPixel(IplImage* InputImage, int x, int y, float* neighberPixel)
+{
+ int i, j, k;
+
+ float* pixelCourant = (float*)malloc(1 * (sizeof(float)));
+
+ //le calcul de voisinage pour les 4 coins;
+ /* 1.*/
+ if (x == 0 && y == 0)
+ {
+ k = 0;
+ for (i = x; i < x + 2; i++)
+ for (j = y; j < y + 2; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ /* 2.*/
+ if (x == 0 && y == InputImage->width)
+ {
+ k = 0;
+ for (i = x; i < x + 2; i++)
+ for (j = y - 1; j < y + 1; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ /* 3.*/
+ if (x == InputImage->height && y == 0)
+ {
+ k = 0;
+ for (i = x - 1; i < x + 1; i++)
+ for (j = y; j < y + 2; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ /* 4.*/
+ if (x == InputImage->height && y == InputImage->width)
+ {
+ k = 0;
+ for (i = x - 1; i < x + 1; i++)
+ for (j = y - 1; j < y + 1; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ // Voisinage de la premiere ligne : L(0)
+ if (x == 0 && (y != 0 && y != InputImage->width))
+ {
+ k = 0;
+ for (i = x + 1; i >= x; i--)
+ for (j = y - 1; j < y + 2; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ // Voisinage de la dernière colonne : C(w)
+ if ((x != 0 && x != InputImage->height) && y == InputImage->width)
+ {
+ k = 0;
+ for (i = x + 1; i > x - 2; i--)
+ for (j = y - 1; j < y + 1; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ // Voisinage de la dernière ligne : L(h)
+ if (x == InputImage->height && (y != 0 && y != InputImage->width))
+ {
+ k = 0;
+ for (i = x; i > x - 2; i--)
+ for (j = y - 1; j < y + 2; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ // Voisinage de la premiere colonne : C(0)
+ if ((x != 0 && x != InputImage->height) && y == 0)
+ {
+ k = 0;
+ for (i = x - 1; i < x + 2; i++)
+ for (j = y; j < y + 2; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ //le calcul du voisinage pour le reste des elementes d'image
+ if ((x != 0 && x != InputImage->height) && (y != 0 && y != InputImage->width))
+ {
+ k = 0;
+ for (i = x + 1; i > x - 2; i--)
+ for (j = y - 1; j < y + 2; j++)
+ {
+ GetGrayPixel(InputImage, i, j, pixelCourant);
+ *(neighberPixel + k) = *pixelCourant;
+ k++;
+ }
+ }
+
+ free(pixelCourant);
+}
+
+void PixelUtils::ForegroundMinimum(IplImage *Foreground, float *Minimum, int n)
+{
+ int i, j, k;
+ float *pixelcourant;
+
+ pixelcourant = (float *)malloc(n * sizeof(float));
+
+ for (k = 0; k < n; k++)
+ *(Minimum + k) = 255;
+
+ for (i = 0; i < Foreground->width; i++)
+ for (j = 0; j < Foreground->height; j++)
+ {
+ if (n == 3)
+ {
+ GetPixel(Foreground, i, j, pixelcourant);
+
+ for (k = 0; k < n; k++)
+ if (*(pixelcourant + k) < *(Minimum + k))
+ *(Minimum + k) = *(pixelcourant + k);
+ }
+
+ if (n == 1)
+ {
+ GetGrayPixel(Foreground, i, j, pixelcourant);
+
+ if (*pixelcourant < *Minimum)
+ *Minimum = *pixelcourant;
+ }
+ }
+
+ free(pixelcourant);
+}
+
+void PixelUtils::ForegroundMaximum(IplImage *Foreground, float *Maximum, int n)
+{
+ int i, j, k;
+ float *pixelcourant;
+
+ pixelcourant = (float *)malloc(n * sizeof(float));
+
+ for (k = 0; k < n; k++)
+ *(Maximum + k) = 0;
+
+ for (i = 0; i < Foreground->width; i++)
+ for (j = 0; j < Foreground->height; j++)
+ {
+ if (n == 3)
+ {
+ GetPixel(Foreground, i, j, pixelcourant);
+
+ for (k = 0; k < n; k++)
+ if (*(pixelcourant + k) > *(Maximum + k))
+ *(Maximum + k) = *(pixelcourant + k);
+ }
+
+ if (n == 1)
+ {
+ GetGrayPixel(Foreground, i, j, pixelcourant);
+
+ if (*pixelcourant > *Maximum)
+ *Maximum = *pixelcourant;
+ }
+ }
+
+ free(pixelcourant);
+}
+
+void PixelUtils::ComplementaryAlphaImageCreation(IplImage *AlphaImage, IplImage *ComplementaryAlphaImage, int n)
+{
+ int i, j, k;
+ float *pixelcourant, *pixelcourant1;
+
+ pixelcourant = (float *)malloc(n * sizeof(float));
+ pixelcourant1 = (float *)malloc(n * sizeof(float));
+
+ for (i = 0; i < AlphaImage->width; i++)
+ for (j = 0; j < AlphaImage->height; j++)
+ {
+ if (n == 1)
+ {
+ GetGrayPixel(AlphaImage, i, j, pixelcourant);
+ *pixelcourant1 = 1 - *(pixelcourant);
+ PutGrayPixel(ComplementaryAlphaImage, i, j, *pixelcourant1);
+ }
+
+ if (n == 3)
+ {
+ GetPixel(AlphaImage, i, j, pixelcourant);
+ for (k = 0; k < 3; k++)
+ {
+ *pixelcourant1 = 1.0 - *(pixelcourant);
+ *(pixelcourant1 + 1) = 1.0 - *(pixelcourant + 1);
+ *(pixelcourant1 + 2) = 1.0 - *(pixelcourant + 2);
+ }
+ PutPixel(ComplementaryAlphaImage, i, j, pixelcourant1);
+ }
+ }
+
+ free(pixelcourant);
+ free(pixelcourant1);
+}
diff --git a/package_bgs/tb/PixelUtils.h b/package_analysis/PixelUtils.h
similarity index 90%
rename from package_bgs/tb/PixelUtils.h
rename to package_analysis/PixelUtils.h
index a2d3a4a..0e35c40 100644
--- a/package_bgs/tb/PixelUtils.h
+++ b/package_analysis/PixelUtils.h
@@ -15,22 +15,10 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-/*
-Code provided by Thierry BOUWMANS
-
-Maitre de Conf�rences
-Laboratoire MIA
-Universit� de La Rochelle
-17000 La Rochelle
-France
-tbouwman@univ-lr.fr
-http://sites.google.com/site/thierrybouwmans/
-*/
#include <stdio.h>
#include <opencv2/opencv.hpp>
-
class PixelUtils
{
public:
@@ -39,9 +27,9 @@ public:
void ColorConversion(IplImage* RGBImage, IplImage* ConvertedImage, int color_space);
void cvttoOTHA(IplImage* RGBImage, IplImage* OthaImage);
-
+
void PostProcessing(IplImage *InputImage);
-
+
void GetPixel(IplImage *image, int m, int n, unsigned char *pixelcourant);
void GetGrayPixel(IplImage *image, int m, int n, unsigned char *pixelcourant);
@@ -58,4 +46,4 @@ public:
void ForegroundMaximum(IplImage *Foreground, float *Maximum, int n);
void ForegroundMinimum(IplImage *Foreground, float *Minimum, int n);
void ComplementaryAlphaImageCreation(IplImage *AlphaImage, IplImage *ComplementaryAlphaImage, int n);
-};
\ No newline at end of file
+};
diff --git a/package_bgs/AdaptiveBackgroundLearning.cpp b/package_bgs/AdaptiveBackgroundLearning.cpp
index b111e65..d2cb8a0 100644
--- a/package_bgs/AdaptiveBackgroundLearning.cpp
+++ b/package_bgs/AdaptiveBackgroundLearning.cpp
@@ -16,10 +16,14 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "AdaptiveBackgroundLearning.h"
-AdaptiveBackgroundLearning::AdaptiveBackgroundLearning() : firstTime(true), alpha(0.05), limit(-1), counter(0), minVal(0.0), maxVal(1.0),
- enableThreshold(true), threshold(15), showForeground(true), showBackground(true)
+using namespace bgslibrary::algorithms;
+
+AdaptiveBackgroundLearning::AdaptiveBackgroundLearning() :
+ alpha(0.05), limit(-1), counter(0), minVal(0.0), maxVal(1.0),
+ enableThreshold(true), threshold(15)
{
std::cout << "AdaptiveBackgroundLearning()" << std::endl;
+ setup("./config/AdaptiveBackgroundLearning.xml");
}
AdaptiveBackgroundLearning::~AdaptiveBackgroundLearning()
@@ -29,52 +33,48 @@ AdaptiveBackgroundLearning::~AdaptiveBackgroundLearning()
void AdaptiveBackgroundLearning::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
- if(img_background.empty())
+ if (img_background.empty())
img_input.copyTo(img_background);
cv::Mat img_input_f(img_input.size(), CV_32F);
- img_input.convertTo(img_input_f, CV_32F, 1./255.);
+ img_input.convertTo(img_input_f, CV_32F, 1. / 255.);
cv::Mat img_background_f(img_background.size(), CV_32F);
- img_background.convertTo(img_background_f, CV_32F, 1./255.);
+ img_background.convertTo(img_background_f, CV_32F, 1. / 255.);
cv::Mat img_diff_f(img_input.size(), CV_32F);
cv::absdiff(img_input_f, img_background_f, img_diff_f);
- if((limit > 0 && limit < counter) || limit == -1)
+ if ((limit > 0 && limit < counter) || limit == -1)
{
- img_background_f = alpha*img_input_f + (1-alpha)*img_background_f;
-
+ img_background_f = alpha*img_input_f + (1 - alpha)*img_background_f;
+
cv::Mat img_new_background(img_input.size(), CV_8U);
- img_background_f.convertTo(img_new_background, CV_8U, 255.0/(maxVal - minVal), -minVal);
+ img_background_f.convertTo(img_new_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
img_new_background.copyTo(img_background);
- if(limit > 0 && limit < counter)
+ if (limit > 0 && limit < counter)
counter++;
}
-
- cv::Mat img_foreground(img_input.size(), CV_8U);
- img_diff_f.convertTo(img_foreground, CV_8U, 255.0/(maxVal - minVal), -minVal);
- if(img_foreground.channels() == 3)
+ //cv::Mat img_foreground(img_input.size(), CV_8U);
+ img_diff_f.convertTo(img_foreground, CV_8UC1, 255.0 / (maxVal - minVal), -minVal);
+
+ if (img_foreground.channels() == 3)
cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
- if(enableThreshold)
+ if (enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
-
- if(showForeground)
- cv::imshow("A-Learning FG", img_foreground);
- if(showBackground)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ cv::imshow("A-Learning FG", img_foreground);
cv::imshow("A-Learning BG", img_background);
+ }
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -84,28 +84,26 @@ void AdaptiveBackgroundLearning::process(const cv::Mat &img_input, cv::Mat &img_
void AdaptiveBackgroundLearning::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/AdaptiveBackgroundLearning.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), 0, CV_STORAGE_WRITE);
cvWriteReal(fs, "alpha", alpha);
cvWriteInt(fs, "limit", limit);
cvWriteInt(fs, "enableThreshold", enableThreshold);
cvWriteInt(fs, "threshold", threshold);
- cvWriteInt(fs, "showForeground", showForeground);
- cvWriteInt(fs, "showBackground", showBackground);
+ cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
}
void AdaptiveBackgroundLearning::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/AdaptiveBackgroundLearning.xml", 0, CV_STORAGE_READ);
-
- alpha = cvReadRealByName(fs, 0, "alpha", 0.05);
- limit = cvReadIntByName(fs, 0, "limit", -1);
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showForeground = cvReadIntByName(fs, 0, "showForeground", true);
- showBackground = cvReadIntByName(fs, 0, "showBackground", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.05);
+ limit = cvReadIntByName(fs, nullptr, "limit", -1);
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/AdaptiveBackgroundLearning.h b/package_bgs/AdaptiveBackgroundLearning.h
index 4bbac54..3cfc686 100644
--- a/package_bgs/AdaptiveBackgroundLearning.h
+++ b/package_bgs/AdaptiveBackgroundLearning.h
@@ -16,35 +16,32 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
#include "IBGS.h"
-class AdaptiveBackgroundLearning : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::Mat img_background;
- double alpha;
- long limit;
- long counter;
- double minVal;
- double maxVal;
- bool enableThreshold;
- int threshold;
- bool showForeground;
- bool showBackground;
-
-public:
- AdaptiveBackgroundLearning();
- ~AdaptiveBackgroundLearning();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class AdaptiveBackgroundLearning : public IBGS
+ {
+ private:
+ double alpha;
+ long limit;
+ long counter;
+ double minVal;
+ double maxVal;
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ AdaptiveBackgroundLearning();
+ ~AdaptiveBackgroundLearning();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/AdaptiveSelectiveBackgroundLearning.cpp b/package_bgs/AdaptiveSelectiveBackgroundLearning.cpp
index cd3e7d3..2f6f9fe 100644
--- a/package_bgs/AdaptiveSelectiveBackgroundLearning.cpp
+++ b/package_bgs/AdaptiveSelectiveBackgroundLearning.cpp
@@ -16,11 +16,14 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "AdaptiveSelectiveBackgroundLearning.h"
-AdaptiveSelectiveBackgroundLearning::AdaptiveSelectiveBackgroundLearning() : firstTime(true),
-alphaLearn(0.05), alphaDetection(0.05), learningFrames(-1), counter(0), minVal(0.0), maxVal(1.0),
-threshold(15), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+AdaptiveSelectiveBackgroundLearning::AdaptiveSelectiveBackgroundLearning() :
+ alphaLearn(0.05), alphaDetection(0.05), learningFrames(-1), counter(0), minVal(0.0), maxVal(1.0),
+ threshold(15)
{
std::cout << "AdaptiveSelectiveBackgroundLearning()" << std::endl;
+ setup("./config/AdaptiveSelectiveBackgroundLearning.xml");
}
AdaptiveSelectiveBackgroundLearning::~AdaptiveSelectiveBackgroundLearning()
@@ -30,8 +33,7 @@ AdaptiveSelectiveBackgroundLearning::~AdaptiveSelectiveBackgroundLearning()
void AdaptiveSelectiveBackgroundLearning::process(const cv::Mat &img_input_, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input_.empty())
- return;
+ init(img_input_, img_output, img_bgmodel);
cv::Mat img_input;
if (img_input_.channels() == 3)
@@ -39,24 +41,19 @@ void AdaptiveSelectiveBackgroundLearning::process(const cv::Mat &img_input_, cv:
else
img_input_.copyTo(img_input);
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
- if(img_background.empty())
+ if (img_background.empty())
img_input.copyTo(img_background);
cv::Mat img_input_f(img_input.size(), CV_32F);
- img_input.convertTo(img_input_f, CV_32F, 1./255.);
+ img_input.convertTo(img_input_f, CV_32F, 1. / 255.);
cv::Mat img_background_f(img_background.size(), CV_32F);
- img_background.convertTo(img_background_f, CV_32F, 1./255.);
+ img_background.convertTo(img_background_f, CV_32F, 1. / 255.);
cv::Mat img_diff_f(img_input.size(), CV_32F);
cv::absdiff(img_input_f, img_background_f, img_diff_f);
- cv::Mat img_foreground(img_input.size(), CV_8U);
+ //cv::Mat img_foreground(img_input.size(), CV_8U);
img_diff_f.convertTo(img_foreground, CV_8U, 255.0 / (maxVal - minVal), -minVal);
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
@@ -88,15 +85,17 @@ void AdaptiveSelectiveBackgroundLearning::process(const cv::Mat &img_input_, cv:
}
}
- cv::Mat img_new_background(img_input.size(), CV_8U);
- img_background_f.convertTo(img_new_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
- img_new_background.copyTo(img_background);
-
- if(showOutput)
+ //cv::Mat img_new_background(img_input.size(), CV_8U);
+ img_background_f.convertTo(img_background, CV_8UC1, 255.0 / (maxVal - minVal), -minVal);
+ //img_new_background.copyTo(img_background);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cv::imshow("AS-Learning FG", img_foreground);
cv::imshow("AS-Learning BG", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -106,7 +105,7 @@ void AdaptiveSelectiveBackgroundLearning::process(const cv::Mat &img_input_, cv:
void AdaptiveSelectiveBackgroundLearning::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/AdaptiveSelectiveBackgroundLearning.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "learningFrames", learningFrames);
cvWriteReal(fs, "alphaLearn", alphaLearn);
@@ -119,13 +118,13 @@ void AdaptiveSelectiveBackgroundLearning::saveConfig()
void AdaptiveSelectiveBackgroundLearning::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/AdaptiveSelectiveBackgroundLearning.xml", 0, CV_STORAGE_READ);
-
- learningFrames = cvReadIntByName(fs, 0, "learningFrames", 90);
- alphaLearn = cvReadRealByName(fs, 0, "alphaLearn", 0.05);
- alphaDetection = cvReadRealByName(fs, 0, "alphaDetection", 0.05);
- threshold = cvReadIntByName(fs, 0, "threshold", 25);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), 0, CV_STORAGE_READ);
+
+ learningFrames = cvReadIntByName(fs, nullptr, "learningFrames", 90);
+ alphaLearn = cvReadRealByName(fs, nullptr, "alphaLearn", 0.05);
+ alphaDetection = cvReadRealByName(fs, nullptr, "alphaDetection", 0.05);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 25);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/AdaptiveSelectiveBackgroundLearning.h b/package_bgs/AdaptiveSelectiveBackgroundLearning.h
index 2276747..24da44c 100644
--- a/package_bgs/AdaptiveSelectiveBackgroundLearning.h
+++ b/package_bgs/AdaptiveSelectiveBackgroundLearning.h
@@ -16,34 +16,32 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
#include "IBGS.h"
-class AdaptiveSelectiveBackgroundLearning : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::Mat img_background;
- double alphaLearn;
- double alphaDetection;
- long learningFrames;
- long counter;
- double minVal;
- double maxVal;
- int threshold;
- bool showOutput;
-
-public:
- AdaptiveSelectiveBackgroundLearning();
- ~AdaptiveSelectiveBackgroundLearning();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class AdaptiveSelectiveBackgroundLearning : public IBGS
+ {
+ private:
+ double alphaLearn;
+ double alphaDetection;
+ long learningFrames;
+ long counter;
+ double minVal;
+ double maxVal;
+ int threshold;
+
+ public:
+ AdaptiveSelectiveBackgroundLearning();
+ ~AdaptiveSelectiveBackgroundLearning();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/DPAdaptiveMedian.cpp b/package_bgs/DPAdaptiveMedian.cpp
new file mode 100644
index 0000000..0885580
--- /dev/null
+++ b/package_bgs/DPAdaptiveMedian.cpp
@@ -0,0 +1,110 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "DPAdaptiveMedian.h"
+
+using namespace bgslibrary::algorithms;
+
+DPAdaptiveMedian::DPAdaptiveMedian() :
+ frameNumber(0), threshold(40), samplingRate(7), learningFrames(30)
+{
+ std::cout << "DPAdaptiveMedian()" << std::endl;
+ setup("./config/DPAdaptiveMedian.xml");
+}
+
+DPAdaptiveMedian::~DPAdaptiveMedian()
+{
+ std::cout << "~DPAdaptiveMedian()" << std::endl;
+}
+
+void DPAdaptiveMedian::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ frame = new IplImage(img_input);
+
+ if (firstTime)
+ frame_data.ReleaseMemory(false);
+ frame_data = frame;
+
+ if (firstTime)
+ {
+ int width = img_input.size().width;
+ int height = img_input.size().height;
+
+ lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
+ lowThresholdMask.Ptr()->origin = IPL_ORIGIN_BL;
+
+ highThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
+ highThresholdMask.Ptr()->origin = IPL_ORIGIN_BL;
+
+ params.SetFrameSize(width, height);
+ params.LowThreshold() = threshold;
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.SamplingRate() = samplingRate;
+ params.LearningFrames() = learningFrames;
+
+ bgs.Initalize(params);
+ bgs.InitModel(frame_data);
+ }
+
+ bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
+ lowThresholdMask.Clear();
+ bgs.Update(frameNumber, frame_data, lowThresholdMask);
+
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ //bitwise_not(img_foreground, img_foreground);
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ cv::imshow("Adaptive Median FG (McFarlane&Schofield)", img_foreground);
+ cv::imshow("Adaptive Median BG (McFarlane&Schofield)", img_background);
+ }
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+
+ delete frame;
+ firstTime = false;
+ frameNumber++;
+}
+
+void DPAdaptiveMedian::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "threshold", threshold);
+ cvWriteInt(fs, "samplingRate", samplingRate);
+ cvWriteInt(fs, "learningFrames", learningFrames);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void DPAdaptiveMedian::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 40);
+ samplingRate = cvReadIntByName(fs, nullptr, "samplingRate", 7);
+ learningFrames = cvReadIntByName(fs, nullptr, "learningFrames", 30);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/DPAdaptiveMedian.h b/package_bgs/DPAdaptiveMedian.h
new file mode 100644
index 0000000..7d2b7fa
--- /dev/null
+++ b/package_bgs/DPAdaptiveMedian.h
@@ -0,0 +1,53 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "dp/AdaptiveMedianBGS.h"
+
+using namespace Algorithms::BackgroundSubtraction;
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class DPAdaptiveMedian : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+ AdaptiveMedianParams params;
+ AdaptiveMedianBGS bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+ int threshold;
+ int samplingRate;
+ int learningFrames;
+
+ public:
+ DPAdaptiveMedian();
+ ~DPAdaptiveMedian();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPEigenbackgroundBGS.cpp b/package_bgs/DPEigenbackground.cpp
similarity index 53%
rename from package_bgs/dp/DPEigenbackgroundBGS.cpp
rename to package_bgs/DPEigenbackground.cpp
index 630d9cc..75763ce 100644
--- a/package_bgs/dp/DPEigenbackgroundBGS.cpp
+++ b/package_bgs/DPEigenbackground.cpp
@@ -14,37 +14,35 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPEigenbackgroundBGS.h"
+#include "DPEigenbackground.h"
-DPEigenbackgroundBGS::DPEigenbackgroundBGS() : firstTime(true), frameNumber(0), threshold(225), historySize(20), embeddedDim(10), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+DPEigenbackground::DPEigenbackground() :
+ frameNumber(0), threshold(225), historySize(20), embeddedDim(10)
{
- std::cout << "DPEigenbackgroundBGS()" << std::endl;
+ std::cout << "DPEigenbackground()" << std::endl;
+ setup("./config/DPEigenbackground.xml");
}
-DPEigenbackgroundBGS::~DPEigenbackgroundBGS()
+DPEigenbackground::~DPEigenbackground()
{
- std::cout << "~DPEigenbackgroundBGS()" << std::endl;
+ std::cout << "~DPEigenbackground()" << std::endl;
}
-void DPEigenbackgroundBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPEigenbackground::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +53,7 @@ void DPEigenbackgroundBGS::process(const cv::Mat &img_input, cv::Mat &img_output
params.SetFrameSize(width, height);
params.LowThreshold() = threshold; //15*15;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
//params.HistorySize() = 100;
params.HistorySize() = historySize;
//params.EmbeddedDim() = 20;
@@ -68,22 +66,27 @@ void DPEigenbackgroundBGS::process(const cv::Mat &img_input, cv::Mat &img_output
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("Eigenbackground (Oliver)", foreground);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Eigenbackground (Oliver)", img_foreground);
+#endif
- foreground.copyTo(img_output);
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
frameNumber++;
}
-void DPEigenbackgroundBGS::saveConfig()
+void DPEigenbackground::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPEigenbackgroundBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "threshold", threshold);
cvWriteInt(fs, "historySize", historySize);
@@ -93,14 +96,14 @@ void DPEigenbackgroundBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPEigenbackgroundBGS::loadConfig()
+void DPEigenbackground::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPEigenbackgroundBGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadIntByName(fs, 0, "threshold", 225);
- historySize = cvReadIntByName(fs, 0, "historySize", 20);
- embeddedDim = cvReadIntByName(fs, 0, "embeddedDim", 10);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 225);
+ historySize = cvReadIntByName(fs, nullptr, "historySize", 20);
+ embeddedDim = cvReadIntByName(fs, nullptr, "embeddedDim", 10);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/DPEigenbackground.h b/package_bgs/DPEigenbackground.h
new file mode 100644
index 0000000..f84fee7
--- /dev/null
+++ b/package_bgs/DPEigenbackground.h
@@ -0,0 +1,55 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "dp/Eigenbackground.h"
+
+using namespace Algorithms::BackgroundSubtraction;
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class DPEigenbackground : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ EigenbackgroundParams params;
+ Eigenbackground bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ int threshold;
+ int historySize;
+ int embeddedDim;
+
+ public:
+ DPEigenbackground();
+ ~DPEigenbackground();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPGrimsonGMMBGS.cpp b/package_bgs/DPGrimsonGMM.cpp
similarity index 54%
rename from package_bgs/dp/DPGrimsonGMMBGS.cpp
rename to package_bgs/DPGrimsonGMM.cpp
index ae54860..c72b4d2 100644
--- a/package_bgs/dp/DPGrimsonGMMBGS.cpp
+++ b/package_bgs/DPGrimsonGMM.cpp
@@ -14,37 +14,35 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPGrimsonGMMBGS.h"
+#include "DPGrimsonGMM.h"
-DPGrimsonGMMBGS::DPGrimsonGMMBGS() : firstTime(true), frameNumber(0), threshold(9.0), alpha(0.01), gaussians(3), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+DPGrimsonGMM::DPGrimsonGMM() :
+ frameNumber(0), threshold(9.0), alpha(0.01), gaussians(3)
{
- std::cout << "DPGrimsonGMMBGS()" << std::endl;
+ std::cout << "DPGrimsonGMM()" << std::endl;
+ setup("./config/DPGrimsonGMM.xml");
}
-DPGrimsonGMMBGS::~DPGrimsonGMMBGS()
+DPGrimsonGMM::~DPGrimsonGMM()
{
- std::cout << "~DPGrimsonGMMBGS()" << std::endl;
+ std::cout << "~DPGrimsonGMM()" << std::endl;
}
-void DPGrimsonGMMBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPGrimsonGMM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +53,7 @@ void DPGrimsonGMMBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv:
params.SetFrameSize(width, height);
params.LowThreshold() = threshold; //3.0f*3.0f;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
//params.Alpha() = 0.001f;
params.Alpha() = alpha; //0.01f;
params.MaxModes() = gaussians; //3;
@@ -67,22 +65,27 @@ void DPGrimsonGMMBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv:
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("GMM (Grimson)", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("GMM (Grimson)", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
frameNumber++;
}
-void DPGrimsonGMMBGS::saveConfig()
+void DPGrimsonGMM::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPGrimsonGMMBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -92,14 +95,14 @@ void DPGrimsonGMMBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPGrimsonGMMBGS::loadConfig()
+void DPGrimsonGMM::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPGrimsonGMMBGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 9.0);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.01);
- gaussians = cvReadIntByName(fs, 0, "gaussians", 3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 9.0);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.01);
+ gaussians = cvReadIntByName(fs, nullptr, "gaussians", 3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/dp/DPEigenbackgroundBGS.h b/package_bgs/DPGrimsonGMM.h
similarity index 53%
rename from package_bgs/dp/DPEigenbackgroundBGS.h
rename to package_bgs/DPGrimsonGMM.h
index cd4e54c..dcc05eb 100644
--- a/package_bgs/dp/DPEigenbackgroundBGS.h
+++ b/package_bgs/DPGrimsonGMM.h
@@ -16,41 +16,40 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "Eigenbackground.h"
+#include "IBGS.h"
+#include "dp/GrimsonGMM.h"
using namespace Algorithms::BackgroundSubtraction;
-class DPEigenbackgroundBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- EigenbackgroundParams params;
- Eigenbackground bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- int threshold;
- int historySize;
- int embeddedDim;
- bool showOutput;
-
-public:
- DPEigenbackgroundBGS();
- ~DPEigenbackgroundBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class DPGrimsonGMM : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ GrimsonParams params;
+ GrimsonGMM bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ int gaussians;
+
+ public:
+ DPGrimsonGMM();
+ ~DPGrimsonGMM();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPMeanBGS.cpp b/package_bgs/DPMean.cpp
similarity index 55%
rename from package_bgs/dp/DPMeanBGS.cpp
rename to package_bgs/DPMean.cpp
index 13260b4..3af1fb6 100644
--- a/package_bgs/dp/DPMeanBGS.cpp
+++ b/package_bgs/DPMean.cpp
@@ -14,37 +14,35 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPMeanBGS.h"
+#include "DPMean.h"
-DPMeanBGS::DPMeanBGS() : firstTime(true), frameNumber(0), threshold(2700), alpha(1e-6f), learningFrames(30), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+DPMean::DPMean() :
+ frameNumber(0), threshold(2700), alpha(1e-6f), learningFrames(30)
{
- std::cout << "DPMeanBGS()" << std::endl;
+ std::cout << "DPMean()" << std::endl;
+ setup("./config/DPMean.xml");
}
-DPMeanBGS::~DPMeanBGS()
+DPMean::~DPMean()
{
- std::cout << "~DPMeanBGS()" << std::endl;
+ std::cout << "~DPMean()" << std::endl;
}
-void DPMeanBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPMean::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +53,7 @@ void DPMeanBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
params.SetFrameSize(width, height);
params.LowThreshold() = threshold; //3*30*30; // 2700
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
//params.Alpha() = 1e-6f;
params.Alpha() = alpha;
params.LearningFrames() = learningFrames;//30;
@@ -67,22 +65,27 @@ void DPMeanBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("Temporal Mean (Donovan Parks)", foreground);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Temporal Mean (Donovan Parks)", img_foreground);
+#endif
- foreground.copyTo(img_output);
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
frameNumber++;
}
-void DPMeanBGS::saveConfig()
+void DPMean::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPMeanBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -92,14 +95,14 @@ void DPMeanBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPMeanBGS::loadConfig()
+void DPMean::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPMeanBGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadIntByName(fs, 0, "threshold", 2700);
- alpha = cvReadRealByName(fs, 0, "alpha", 1e-6f);
- learningFrames = cvReadIntByName(fs, 0, "learningFrames", 30);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 2700);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 1e-6f);
+ learningFrames = cvReadIntByName(fs, nullptr, "learningFrames", 30);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/dp/DPZivkovicAGMMBGS.h b/package_bgs/DPMean.h
similarity index 56%
rename from package_bgs/dp/DPZivkovicAGMMBGS.h
rename to package_bgs/DPMean.h
index 775226a..6029968 100644
--- a/package_bgs/dp/DPZivkovicAGMMBGS.h
+++ b/package_bgs/DPMean.h
@@ -16,41 +16,40 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "ZivkovicAGMM.h"
+#include "IBGS.h"
+#include "dp/MeanBGS.h"
using namespace Algorithms::BackgroundSubtraction;
-class DPZivkovicAGMMBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- ZivkovicParams params;
- ZivkovicAGMM bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- int gaussians;
- bool showOutput;
-
-public:
- DPZivkovicAGMMBGS();
- ~DPZivkovicAGMMBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class DPMean : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ MeanParams params;
+ MeanBGS bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ int threshold;
+ double alpha;
+ int learningFrames;
+
+ public:
+ DPMean();
+ ~DPMean();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPPratiMediodBGS.cpp b/package_bgs/DPPratiMediod.cpp
similarity index 53%
rename from package_bgs/dp/DPPratiMediodBGS.cpp
rename to package_bgs/DPPratiMediod.cpp
index ba1d6be..d1942c5 100644
--- a/package_bgs/dp/DPPratiMediodBGS.cpp
+++ b/package_bgs/DPPratiMediod.cpp
@@ -14,37 +14,35 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPPratiMediodBGS.h"
+#include "DPPratiMediod.h"
-DPPratiMediodBGS::DPPratiMediodBGS() : firstTime(true), frameNumber(0), threshold(30), samplingRate(5), historySize(16), weight(5), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+DPPratiMediod::DPPratiMediod() :
+ frameNumber(0), threshold(30), samplingRate(5), historySize(16), weight(5)
{
- std::cout << "DPPratiMediodBGS()" << std::endl;
+ std::cout << "DPPratiMediod()" << std::endl;
+ setup("./config/DPPratiMediod.xml");
}
-DPPratiMediodBGS::~DPPratiMediodBGS()
+DPPratiMediod::~DPPratiMediod()
{
- std::cout << "~DPPratiMediodBGS()" << std::endl;
+ std::cout << "~DPPratiMediod()" << std::endl;
}
-void DPPratiMediodBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPPratiMediod::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +53,7 @@ void DPPratiMediodBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv
params.SetFrameSize(width, height);
params.LowThreshold() = threshold;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
params.SamplingRate() = samplingRate;
params.HistorySize() = historySize;
params.Weight() = weight;
@@ -67,26 +65,29 @@ void DPPratiMediodBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- cv::Mat background(bgs.Background()->Ptr());
- if(showOutput){
- cv::imshow("Temporal Median FG (Cucchiara&Calderara)", foreground);
- cv::imshow("Temporal Median BG (Cucchiara&Calderara)", background);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ cv::imshow("Temporal Median FG (Cucchiara&Calderara)", img_foreground);
+ cv::imshow("Temporal Median BG (Cucchiara&Calderara)", img_background);
}
+#endif
- foreground.copyTo(img_output);
- background.copyTo(img_bgmodel);
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
frameNumber++;
}
-void DPPratiMediodBGS::saveConfig()
+void DPPratiMediod::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPPratiMediodBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "threshold", threshold);
cvWriteInt(fs, "samplingRate", samplingRate);
@@ -97,15 +98,15 @@ void DPPratiMediodBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPPratiMediodBGS::loadConfig()
+void DPPratiMediod::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPPratiMediodBGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadIntByName(fs, 0, "threshold", 30);
- samplingRate = cvReadIntByName(fs, 0, "samplingRate", 5);
- historySize = cvReadIntByName(fs, 0, "historySize", 16);
- weight = cvReadIntByName(fs, 0, "weight", 5);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 30);
+ samplingRate = cvReadIntByName(fs, nullptr, "samplingRate", 5);
+ historySize = cvReadIntByName(fs, nullptr, "historySize", 16);
+ weight = cvReadIntByName(fs, nullptr, "weight", 5);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/dp/DPMeanBGS.h b/package_bgs/DPPratiMediod.h
similarity index 52%
rename from package_bgs/dp/DPMeanBGS.h
rename to package_bgs/DPPratiMediod.h
index 8829686..d37a77a 100644
--- a/package_bgs/dp/DPMeanBGS.h
+++ b/package_bgs/DPPratiMediod.h
@@ -16,41 +16,41 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "MeanBGS.h"
+#include "IBGS.h"
+#include "dp/PratiMediodBGS.h"
using namespace Algorithms::BackgroundSubtraction;
-class DPMeanBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- MeanParams params;
- MeanBGS bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- int threshold;
- double alpha;
- int learningFrames;
- bool showOutput;
-
-public:
- DPMeanBGS();
- ~DPMeanBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class DPPratiMediod : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ PratiParams params;
+ PratiMediodBGS bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ int threshold;
+ int samplingRate;
+ int historySize;
+ int weight;
+
+ public:
+ DPPratiMediod();
+ ~DPPratiMediod();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPTextureBGS.cpp b/package_bgs/DPTexture.cpp
similarity index 65%
rename from package_bgs/dp/DPTextureBGS.cpp
rename to package_bgs/DPTexture.cpp
index 2d34342..3285ccf 100644
--- a/package_bgs/dp/DPTextureBGS.cpp
+++ b/package_bgs/DPTexture.cpp
@@ -14,15 +14,18 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPTextureBGS.h"
+#include "DPTexture.h"
-DPTextureBGS::DPTextureBGS() : firstTime(true), showOutput(true)
- //, enableFiltering(true)
+using namespace bgslibrary::algorithms;
+
+DPTexture::DPTexture()
+// : enableFiltering(true)
{
- std::cout << "DPTextureBGS()" << std::endl;
+ std::cout << "DPTexture()" << std::endl;
+ setup("./config/DPTexture.xml");
}
-DPTextureBGS::~DPTextureBGS()
+DPTexture::~DPTexture()
{
delete[] bgModel; // ~10Kb (25.708-15.968)
delete[] modeArray;
@@ -33,34 +36,31 @@ DPTextureBGS::~DPTextureBGS()
fgMask.ReleaseImage();
tempMask.ReleaseImage();
texture.ReleaseImage();
- std::cout << "~DPTextureBGS()" << std::endl;
+ std::cout << "~DPTexture()" << std::endl;
}
-void DPTextureBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPTexture::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
{
- width = img_input.size().width;
+ width = img_input.size().width;
height = img_input.size().height;
size = width * height;
// input image
image = cvCreateImage(cvSize(width, height), 8, 3);
- cvCopy(frame, image.Ptr());
+ cvCopy(frame, image.Ptr());
// foreground masks
fgMask = cvCreateImage(cvSize(width, height), 8, 1);
tempMask = cvCreateImage(cvSize(width, height), 8, 1);
cvZero(fgMask.Ptr());
cvZero(tempMask.Ptr());
-
+
// create background model
bgModel = new TextureArray[size];
texture = cvCreateImage(cvSize(width, height), 8, 3);
@@ -71,16 +71,16 @@ void DPTextureBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Ma
// initialize background model
bgs.LBP(image, texture);
bgs.Histogram(texture, curTextureHist);
- for(int y = REGION_R+TEXTURE_R; y < height-REGION_R-TEXTURE_R; ++y)
+ for (int y = REGION_R + TEXTURE_R; y < height - REGION_R - TEXTURE_R; ++y)
{
- for(int x = REGION_R+TEXTURE_R; x < width-REGION_R-TEXTURE_R; ++x)
+ for (int x = REGION_R + TEXTURE_R; x < width - REGION_R - TEXTURE_R; ++x)
{
- int index = x+y*width;
-
- for(int m = 0; m < NUM_MODES; ++m)
+ int index = x + y*width;
+
+ for (int m = 0; m < NUM_MODES; ++m)
{
- for(int i = 0; i < NUM_BINS; ++i)
- {
+ for (int i = 0; i < NUM_BINS; ++i)
+ {
bgModel[index].mode[m].r[i] = curTextureHist[index].r[i];
bgModel[index].mode[m].g[i] = curTextureHist[index].g[i];
bgModel[index].mode[m].b[i] = curTextureHist[index].b[i];
@@ -91,18 +91,16 @@ void DPTextureBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Ma
//dilateElement = cvCreateStructuringElementEx(7, 7, 3, 3, CV_SHAPE_RECT);
//erodeElement = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT);
-
- saveConfig();
firstTime = false;
}
-
- cvCopy(frame, image.Ptr());
+
+ cvCopy(frame, image.Ptr());
// perform background subtraction
bgs.LBP(image, texture);
bgs.Histogram(texture, curTextureHist);
bgs.BgsCompare(bgModel, curTextureHist, modeArray, THRESHOLD, fgMask);
-
+
//if(enableFiltering)
//{
// // size filtering
@@ -120,22 +118,27 @@ void DPTextureBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Ma
// cvErode(fgMask.Ptr(), fgMask.Ptr(), erodeElement, 1);
//}
- cv::Mat foreground(fgMask.Ptr());
- if(!foreground.empty())
- foreground.copyTo(img_output);
-
- if(showOutput)
- cv::imshow("Texture BGS (Donovan Parks)", foreground);
+ img_foreground = cv::cvarrToMat(fgMask.Ptr());
+ //img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Texture BGS (Donovan Parks)", img_foreground);
+#endif
- // update background subtraction
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+
+ // update background subtraction
bgs.UpdateModel(fgMask, bgModel, curTextureHist, modeArray);
-
+
delete frame;
}
-void DPTextureBGS::saveConfig()
+void DPTexture::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPTextureBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
//cvWriteReal(fs, "alpha", alpha);
//cvWriteInt(fs, "enableFiltering", enableFiltering);
@@ -144,13 +147,13 @@ void DPTextureBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPTextureBGS::loadConfig()
+void DPTexture::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPTextureBGS.xml", 0, CV_STORAGE_READ);
-
- //alpha = cvReadRealByName(fs, 0, "alpha", 1e-6f);
- //enableFiltering = cvReadIntByName(fs, 0, "enableFiltering", true);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ //alpha = cvReadRealByName(fs, nullptr, "alpha", 1e-6f);
+ //enableFiltering = cvReadIntByName(fs, nullptr, "enableFiltering", true);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/DPTexture.h b/package_bgs/DPTexture.h
new file mode 100644
index 0000000..3cfdcea
--- /dev/null
+++ b/package_bgs/DPTexture.h
@@ -0,0 +1,59 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "dp/TextureBGS.h"
+//#include "ConnectedComponents.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class DPTexture : public IBGS
+ {
+ private:
+ int width;
+ int height;
+ int size;
+ TextureBGS bgs;
+ IplImage* frame;
+ RgbImage image;
+ BwImage fgMask;
+ BwImage tempMask;
+ TextureArray* bgModel;
+ RgbImage texture;
+ unsigned char* modeArray;
+ TextureHistogram* curTextureHist;
+ //ConnectedComponents cc;
+ //CBlobResult largeBlobs;
+ //IplConvKernel* dilateElement;
+ //IplConvKernel* erodeElement;
+ //bool enableFiltering;
+
+ public:
+ DPTexture();
+ ~DPTexture();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPWrenGABGS.cpp b/package_bgs/DPWrenGA.cpp
similarity index 54%
rename from package_bgs/dp/DPWrenGABGS.cpp
rename to package_bgs/DPWrenGA.cpp
index d7241b1..7fc3313 100644
--- a/package_bgs/dp/DPWrenGABGS.cpp
+++ b/package_bgs/DPWrenGA.cpp
@@ -14,37 +14,35 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPWrenGABGS.h"
+#include "DPWrenGA.h"
-DPWrenGABGS::DPWrenGABGS() : firstTime(true), frameNumber(0), threshold(12.25f), alpha(0.005f), learningFrames(30), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+DPWrenGA::DPWrenGA() :
+ frameNumber(0), threshold(12.25f), alpha(0.005f), learningFrames(30)
{
- std::cout << "DPWrenGABGS()" << std::endl;
+ std::cout << "DPWrenGA()" << std::endl;
+ setup("./config/DPWrenGA.xml");
}
-DPWrenGABGS::~DPWrenGABGS()
+DPWrenGA::~DPWrenGA()
{
- std::cout << "~DPWrenGABGS()" << std::endl;
+ std::cout << "~DPWrenGA()" << std::endl;
}
-void DPWrenGABGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPWrenGA::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +53,7 @@ void DPWrenGABGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat
params.SetFrameSize(width, height);
params.LowThreshold() = threshold; //3.5f*3.5f;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
params.Alpha() = alpha; //0.005f;
params.LearningFrames() = learningFrames; //30;
@@ -66,22 +64,27 @@ void DPWrenGABGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("Gaussian Average (Wren)", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Gaussian Average (Wren)", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
frameNumber++;
}
-void DPWrenGABGS::saveConfig()
+void DPWrenGA::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPWrenGABGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -91,15 +94,14 @@ void DPWrenGABGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPWrenGABGS::loadConfig()
+void DPWrenGA::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPWrenGABGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 12.25f);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.005f);
- learningFrames = cvReadIntByName(fs, 0, "learningFrames", 30);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 12.25f);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.005f);
+ learningFrames = cvReadIntByName(fs, nullptr, "learningFrames", 30);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
-
diff --git a/package_bgs/dp/DPWrenGABGS.h b/package_bgs/DPWrenGA.h
similarity index 54%
rename from package_bgs/dp/DPWrenGABGS.h
rename to package_bgs/DPWrenGA.h
index 30ab614..e4b0b5f 100644
--- a/package_bgs/dp/DPWrenGABGS.h
+++ b/package_bgs/DPWrenGA.h
@@ -16,41 +16,40 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "WrenGA.h"
+#include "IBGS.h"
+#include "dp/WrenGA.h"
using namespace Algorithms::BackgroundSubtraction;
-class DPWrenGABGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- WrenParams params;
- WrenGA bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- int learningFrames;
- bool showOutput;
-
-public:
- DPWrenGABGS();
- ~DPWrenGABGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class DPWrenGA : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ WrenParams params;
+ WrenGA bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ int learningFrames;
+
+ public:
+ DPWrenGA();
+ ~DPWrenGA();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/dp/DPZivkovicAGMMBGS.cpp b/package_bgs/DPZivkovicAGMM.cpp
similarity index 53%
rename from package_bgs/dp/DPZivkovicAGMMBGS.cpp
rename to package_bgs/DPZivkovicAGMM.cpp
index e8276f6..a5a9735 100644
--- a/package_bgs/dp/DPZivkovicAGMMBGS.cpp
+++ b/package_bgs/DPZivkovicAGMM.cpp
@@ -14,37 +14,35 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "DPZivkovicAGMMBGS.h"
+#include "DPZivkovicAGMM.h"
-DPZivkovicAGMMBGS::DPZivkovicAGMMBGS() : firstTime(true), frameNumber(0), threshold(25.0f), alpha(0.001f), gaussians(3), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+DPZivkovicAGMM::DPZivkovicAGMM() :
+ frameNumber(0), threshold(25.0f), alpha(0.001f), gaussians(3)
{
- std::cout << "DPZivkovicAGMMBGS()" << std::endl;
+ std::cout << "DPZivkovicAGMM()" << std::endl;
+ setup("./config/DPZivkovicAGMM.xml");
}
-DPZivkovicAGMMBGS::~DPZivkovicAGMMBGS()
+DPZivkovicAGMM::~DPZivkovicAGMM()
{
- std::cout << "~DPZivkovicAGMMBGS()" << std::endl;
+ std::cout << "~DPZivkovicAGMM()" << std::endl;
}
-void DPZivkovicAGMMBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void DPZivkovicAGMM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +53,7 @@ void DPZivkovicAGMMBGS::process(const cv::Mat &img_input, cv::Mat &img_output, c
params.SetFrameSize(width, height);
params.LowThreshold() = threshold; //5.0f*5.0f;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.HighThreshold() = 2 * params.LowThreshold(); // Note: high threshold is used by post-processing
params.Alpha() = alpha; //0.001f;
params.MaxModes() = gaussians; //3;
@@ -66,22 +64,27 @@ void DPZivkovicAGMMBGS::process(const cv::Mat &img_input, cv::Mat &img_output, c
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("Gaussian Mixture Model (Zivkovic)", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Gaussian Mixture Model (Zivkovic)", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
frameNumber++;
}
-void DPZivkovicAGMMBGS::saveConfig()
+void DPZivkovicAGMM::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPZivkovicAGMMBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -91,14 +94,14 @@ void DPZivkovicAGMMBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void DPZivkovicAGMMBGS::loadConfig()
+void DPZivkovicAGMM::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPZivkovicAGMMBGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 25.0f);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.001f);
- gaussians = cvReadIntByName(fs, 0, "gaussians", 3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 25.0f);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.001f);
+ gaussians = cvReadIntByName(fs, nullptr, "gaussians", 3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/dp/DPGrimsonGMMBGS.h b/package_bgs/DPZivkovicAGMM.h
similarity index 53%
rename from package_bgs/dp/DPGrimsonGMMBGS.h
rename to package_bgs/DPZivkovicAGMM.h
index 4f955b9..f35504b 100644
--- a/package_bgs/dp/DPGrimsonGMMBGS.h
+++ b/package_bgs/DPZivkovicAGMM.h
@@ -16,41 +16,40 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "GrimsonGMM.h"
+#include "IBGS.h"
+#include "dp/ZivkovicAGMM.h"
using namespace Algorithms::BackgroundSubtraction;
-class DPGrimsonGMMBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- GrimsonParams params;
- GrimsonGMM bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- int gaussians;
- bool showOutput;
-
-public:
- DPGrimsonGMMBGS();
- ~DPGrimsonGMMBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class DPZivkovicAGMM : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ ZivkovicParams params;
+ ZivkovicAGMM bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ int gaussians;
+
+ public:
+ DPZivkovicAGMM();
+ ~DPZivkovicAGMM();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/FrameDifference.cpp b/package_bgs/FrameDifference.cpp
new file mode 100644
index 0000000..4d5c076
--- /dev/null
+++ b/package_bgs/FrameDifference.cpp
@@ -0,0 +1,84 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "FrameDifference.h"
+
+using namespace bgslibrary::algorithms;
+
+FrameDifference::FrameDifference() :
+ enableThreshold(true), threshold(15)
+{
+ std::cout << "FrameDifference()" << std::endl;
+ setup("./config/FrameDifference.xml");
+}
+
+FrameDifference::~FrameDifference()
+{
+ std::cout << "~FrameDifference()" << std::endl;
+}
+
+void FrameDifference::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (img_background.empty())
+ {
+ img_input.copyTo(img_background);
+ return;
+ }
+
+ cv::absdiff(img_background, img_input, img_foreground);
+
+ if (img_foreground.channels() == 3)
+ cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
+
+ if (enableThreshold)
+ cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Frame Difference", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+
+ img_input.copyTo(img_background);
+ img_background.copyTo(img_bgmodel);
+
+ firstTime = false;
+}
+
+void FrameDifference::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "enableThreshold", enableThreshold);
+ cvWriteInt(fs, "threshold", threshold);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void FrameDifference::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/FrameDifferenceBGS.h b/package_bgs/FrameDifference.h
similarity index 61%
rename from package_bgs/FrameDifferenceBGS.h
rename to package_bgs/FrameDifference.h
index 338979f..07bed8e 100644
--- a/package_bgs/FrameDifferenceBGS.h
+++ b/package_bgs/FrameDifference.h
@@ -16,29 +16,28 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
#include "IBGS.h"
-class FrameDifferenceBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::Mat img_input_prev;
- cv::Mat img_foreground;
- bool enableThreshold;
- int threshold;
- bool showOutput;
-
-public:
- FrameDifferenceBGS();
- ~FrameDifferenceBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
+ namespace algorithms
+ {
+ class FrameDifference : public IBGS
+ {
+ private:
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ FrameDifference();
+ ~FrameDifference();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
+
diff --git a/package_bgs/FrameDifferenceBGS.cpp b/package_bgs/FrameDifferenceBGS.cpp
deleted file mode 100644
index e871651..0000000
--- a/package_bgs/FrameDifferenceBGS.cpp
+++ /dev/null
@@ -1,83 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#include "FrameDifferenceBGS.h"
-
-FrameDifferenceBGS::FrameDifferenceBGS() : firstTime(true), enableThreshold(true), threshold(15), showOutput(true)
-{
- std::cout << "FrameDifferenceBGS()" << std::endl;
-}
-
-FrameDifferenceBGS::~FrameDifferenceBGS()
-{
- std::cout << "~FrameDifferenceBGS()" << std::endl;
-}
-
-void FrameDifferenceBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
-{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
- if(img_input_prev.empty())
- {
- img_input.copyTo(img_input_prev);
- return;
- }
-
- cv::absdiff(img_input_prev, img_input, img_foreground);
-
- if(img_foreground.channels() == 3)
- cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
-
- if(enableThreshold)
- cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
-
- if(showOutput)
- cv::imshow("Frame Difference", img_foreground);
-
- img_foreground.copyTo(img_output);
-
- img_input.copyTo(img_input_prev);
-
- firstTime = false;
-}
-
-void FrameDifferenceBGS::saveConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/FrameDifferenceBGS.xml", 0, CV_STORAGE_WRITE);
-
- cvWriteInt(fs, "enableThreshold", enableThreshold);
- cvWriteInt(fs, "threshold", threshold);
- cvWriteInt(fs, "showOutput", showOutput);
-
- cvReleaseFileStorage(&fs);
-}
-
-void FrameDifferenceBGS::loadConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/FrameDifferenceBGS.xml", 0, CV_STORAGE_READ);
-
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
- cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
diff --git a/package_bgs/tb/FuzzyChoquetIntegral.cpp b/package_bgs/FuzzyChoquetIntegral.cpp
similarity index 62%
rename from package_bgs/tb/FuzzyChoquetIntegral.cpp
rename to package_bgs/FuzzyChoquetIntegral.cpp
index c97e174..3d24126 100644
--- a/package_bgs/tb/FuzzyChoquetIntegral.cpp
+++ b/package_bgs/FuzzyChoquetIntegral.cpp
@@ -15,12 +15,15 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "FuzzyChoquetIntegral.h"
-#include <opencv2/legacy/compat.hpp>
-FuzzyChoquetIntegral::FuzzyChoquetIntegral() : firstTime(true), frameNumber(0), showOutput(true),
- framesToLearn(10), alphaLearn(0.1), alphaUpdate(0.01), colorSpace(1), option(2), smooth(true), threshold(0.67)
+using namespace bgslibrary::algorithms;
+
+FuzzyChoquetIntegral::FuzzyChoquetIntegral() :
+ frameNumber(0), framesToLearn(10), alphaLearn(0.1), alphaUpdate(0.01),
+ colorSpace(1), option(2), smooth(true), threshold(0.67)
{
std::cout << "FuzzyChoquetIntegral()" << std::endl;
+ setup("./config/FuzzyChoquetIntegral.xml");
}
FuzzyChoquetIntegral::~FuzzyChoquetIntegral()
@@ -30,48 +33,52 @@ FuzzyChoquetIntegral::~FuzzyChoquetIntegral()
void FuzzyChoquetIntegral::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
cv::Mat img_input_f3(img_input.size(), CV_32F);
- img_input.convertTo(img_input_f3, CV_32F, 1./255.);
-
- loadConfig();
+ img_input.convertTo(img_input_f3, CV_32F, 1. / 255.);
- if(firstTime)
+ if (firstTime)
{
std::cout << "FuzzyChoquetIntegral parameters:" << std::endl;
-
+
std::string colorSpaceName = "";
- switch(colorSpace)
+ switch (colorSpace)
{
- case 1: colorSpaceName = "RGB"; break;
- case 2: colorSpaceName = "OHTA"; break;
- case 3: colorSpaceName = "HSV"; break;
- case 4: colorSpaceName = "YCrCb"; break;
+ case 1: colorSpaceName = "RGB"; break;
+ case 2: colorSpaceName = "OHTA"; break;
+ case 3: colorSpaceName = "HSV"; break;
+ case 4: colorSpaceName = "YCrCb"; break;
}
std::cout << "Color space: " << colorSpaceName << std::endl;
- if(option == 1)
+ if (option == 1)
std::cout << "Fuzzing by 3 color components" << std::endl;
- if(option == 2)
+ if (option == 2)
std::cout << "Fuzzing by 2 color components + 1 texture component" << std::endl;
-
- saveConfig();
}
- if(frameNumber <= framesToLearn)
+ if (frameNumber <= framesToLearn)
{
- if(frameNumber == 0)
+ if (frameNumber == 0)
std::cout << "FuzzyChoquetIntegral initializing background model by adaptive learning..." << std::endl;
- if(img_background_f3.empty())
+ if (img_background_f3.empty())
img_input_f3.copyTo(img_background_f3);
else
- img_background_f3 = alphaLearn*img_input_f3 + (1-alphaLearn)*img_background_f3;
+ img_background_f3 = alphaLearn*img_input_f3 + (1 - alphaLearn)*img_background_f3;
+
+ double minVal = 0., maxVal = 1.;
+ img_background_f3.convertTo(img_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
+ img_background.copyTo(img_bgmodel);
+
+ img_foreground = cv::Mat::zeros(img_input.size(), img_input.type());
+ img_foreground.copyTo(img_output);
- if(showOutput)
- cv::imshow("CI BG Model", img_background_f3);
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("CI BG Model", img_background);
+#endif
}
else
{
@@ -87,72 +94,74 @@ void FuzzyChoquetIntegral::process(const cv::Mat &img_input, cv::Mat &img_output
IplImage* background_f1 = new IplImage(img_background_f1);
IplImage* lbp_input_f1 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 1);
- cvFillImage(lbp_input_f1, 0.0);
+ cvSetZero(lbp_input_f1);
fu.LBP(input_f1, lbp_input_f1);
- IplImage* lbp_background_f1 = cvCreateImage(cvSize(background_f1->width, background_f1->height), IPL_DEPTH_32F , 1);
- cvFillImage(lbp_background_f1, 0.0);
+ IplImage* lbp_background_f1 = cvCreateImage(cvSize(background_f1->width, background_f1->height), IPL_DEPTH_32F, 1);
+ cvSetZero(lbp_background_f1);
fu.LBP(background_f1, lbp_background_f1);
IplImage* sim_texture_f1 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 1);
fu.SimilarityDegreesImage(lbp_input_f1, lbp_background_f1, sim_texture_f1, 1, colorSpace);
IplImage* sim_color_f3 = cvCreateImage(cvSize(input_f3->width, input_f3->height), IPL_DEPTH_32F, 3);
- fu.SimilarityDegreesImage(input_f3, background_f3, sim_color_f3, 3, colorSpace);
+ fu.SimilarityDegreesImage(input_f3, background_f3, sim_color_f3, 3, colorSpace);
- float* measureG = (float*) malloc(3*(sizeof(float)));
+ float* measureG = (float*)malloc(3 * (sizeof(float)));
IplImage* integral_choquet_f1 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 1);
// 3 color components
- if(option == 1)
+ if (option == 1)
{
fu.FuzzyMeasureG(0.4f, 0.3f, 0.3f, measureG);
fu.getFuzzyIntegralChoquet(sim_texture_f1, sim_color_f3, option, measureG, integral_choquet_f1);
}
// 2 color components + 1 texture component
- if(option == 2)
+ if (option == 2)
{
fu.FuzzyMeasureG(0.6f, 0.3f, 0.1f, measureG);
fu.getFuzzyIntegralChoquet(sim_texture_f1, sim_color_f3, option, measureG, integral_choquet_f1);
}
free(measureG);
- cv::Mat img_integral_choquet_f1(integral_choquet_f1);
+ cv::Mat img_integral_choquet_f1 = cv::cvarrToMat(integral_choquet_f1);
- if(smooth)
+ if (smooth)
cv::medianBlur(img_integral_choquet_f1, img_integral_choquet_f1, 3);
cv::Mat img_foreground_f1(img_input.size(), CV_32F);
cv::threshold(img_integral_choquet_f1, img_foreground_f1, threshold, 255, cv::THRESH_BINARY_INV);
- cv::Mat img_foreground_u1(img_input.size(), CV_8U);
+ //cv::Mat img_foreground_u1(img_input.size(), CV_8U);
double minVal = 0., maxVal = 1.;
- img_foreground_f1.convertTo(img_foreground_u1, CV_8U, 255.0/(maxVal - minVal), -minVal);
- img_foreground_u1.copyTo(img_output);
+ img_foreground_f1.convertTo(img_foreground, CV_8U, 255.0 / (maxVal - minVal), -minVal);
+ img_foreground.copyTo(img_output);
- cv::Mat img_background_u3(img_input.size(), CV_8U);
+ //cv::Mat img_background_u3(img_input.size(), CV_8U);
//double minVal = 0., maxVal = 1.;
- img_background_f3.convertTo(img_background_u3, CV_8U, 255.0/(maxVal - minVal), -minVal);
- img_background_u3.copyTo(img_bgmodel);
+ img_background_f3.convertTo(img_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
+ img_background.copyTo(img_bgmodel);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cvShowImage("CI LBP Input", lbp_input_f1);
cvShowImage("CI LBP Background", lbp_background_f1);
cvShowImage("CI Prob FG Mask", integral_choquet_f1);
- cv::imshow("CI BG Model", img_background_f3);
- cv::imshow("CI FG Mask", img_foreground_u1);
+ cv::imshow("CI BG Model", img_background);
+ cv::imshow("CI FG Mask", img_foreground);
}
+#endif
- if(frameNumber == (framesToLearn + 1))
+ if (frameNumber == (framesToLearn + 1))
std::cout << "FuzzyChoquetIntegral updating background model by adaptive-selective learning..." << std::endl;
IplImage* updated_background_f3 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 3);
- cvFillImage(updated_background_f3, 0.0);
+ cvSetZero(updated_background_f3);
fu.AdaptativeSelectiveBackgroundModelUpdate(input_f3, background_f3, updated_background_f3, integral_choquet_f1, threshold, alphaUpdate);
- cv::Mat img_updated_background_f3(updated_background_f3);
+ cv::Mat img_updated_background_f3 = cv::cvarrToMat(updated_background_f3);
img_updated_background_f3.copyTo(img_background_f3);
cvReleaseImage(&lbp_input_f1);
@@ -161,7 +170,7 @@ void FuzzyChoquetIntegral::process(const cv::Mat &img_input, cv::Mat &img_output
cvReleaseImage(&sim_color_f3);
cvReleaseImage(&integral_choquet_f1);
cvReleaseImage(&updated_background_f3);
-
+
delete background_f1;
delete background_f3;
delete input_f1;
@@ -174,8 +183,8 @@ void FuzzyChoquetIntegral::process(const cv::Mat &img_input, cv::Mat &img_output
void FuzzyChoquetIntegral::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/FuzzyChoquetIntegral.xml", 0, CV_STORAGE_WRITE);
-
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
cvWriteInt(fs, "showOutput", showOutput);
cvWriteInt(fs, "framesToLearn", framesToLearn);
cvWriteReal(fs, "alphaLearn", alphaLearn);
@@ -190,16 +199,16 @@ void FuzzyChoquetIntegral::saveConfig()
void FuzzyChoquetIntegral::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/FuzzyChoquetIntegral.xml", 0, CV_STORAGE_READ);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
- framesToLearn = cvReadIntByName(fs, 0, "framesToLearn", 10);
- alphaLearn = cvReadRealByName(fs, 0, "alphaLearn", 0.1);
- alphaUpdate = cvReadRealByName(fs, 0, "alphaUpdate", 0.01);
- colorSpace = cvReadIntByName(fs, 0, "colorSpace", 1);
- option = cvReadIntByName(fs, 0, "option", 2);
- smooth = cvReadIntByName(fs, 0, "smooth", true);
- threshold = cvReadRealByName(fs, 0, "threshold", 0.67);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+ framesToLearn = cvReadIntByName(fs, nullptr, "framesToLearn", 10);
+ alphaLearn = cvReadRealByName(fs, nullptr, "alphaLearn", 0.1);
+ alphaUpdate = cvReadRealByName(fs, nullptr, "alphaUpdate", 0.01);
+ colorSpace = cvReadIntByName(fs, nullptr, "colorSpace", 1);
+ option = cvReadIntByName(fs, nullptr, "option", 2);
+ smooth = cvReadIntByName(fs, nullptr, "smooth", true);
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 0.67);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/FuzzyChoquetIntegral.h b/package_bgs/FuzzyChoquetIntegral.h
new file mode 100644
index 0000000..25681b0
--- /dev/null
+++ b/package_bgs/FuzzyChoquetIntegral.h
@@ -0,0 +1,53 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "T2F/FuzzyUtils.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class FuzzyChoquetIntegral : public IBGS
+ {
+ private:
+ long frameNumber;
+
+ int framesToLearn;
+ double alphaLearn;
+ double alphaUpdate;
+ int colorSpace;
+ int option;
+ bool smooth;
+ double threshold;
+
+ FuzzyUtils fu;
+ cv::Mat img_background_f3;
+
+ public:
+ FuzzyChoquetIntegral();
+ ~FuzzyChoquetIntegral();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/tb/FuzzySugenoIntegral.cpp b/package_bgs/FuzzySugenoIntegral.cpp
similarity index 62%
rename from package_bgs/tb/FuzzySugenoIntegral.cpp
rename to package_bgs/FuzzySugenoIntegral.cpp
index 859f14e..e62fa02 100644
--- a/package_bgs/tb/FuzzySugenoIntegral.cpp
+++ b/package_bgs/FuzzySugenoIntegral.cpp
@@ -15,12 +15,15 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "FuzzySugenoIntegral.h"
-#include <opencv2/legacy/compat.hpp>
-FuzzySugenoIntegral::FuzzySugenoIntegral() : firstTime(true), frameNumber(0), showOutput(true),
- framesToLearn(10), alphaLearn(0.1), alphaUpdate(0.01), colorSpace(1), option(2), smooth(true), threshold(0.67)
+using namespace bgslibrary::algorithms;
+
+FuzzySugenoIntegral::FuzzySugenoIntegral() :
+ frameNumber(0), framesToLearn(10), alphaLearn(0.1), alphaUpdate(0.01),
+ colorSpace(1), option(2), smooth(true), threshold(0.67)
{
std::cout << "FuzzySugenoIntegral()" << std::endl;
+ setup("./config/FuzzySugenoIntegral.xml");
}
FuzzySugenoIntegral::~FuzzySugenoIntegral()
@@ -30,48 +33,52 @@ FuzzySugenoIntegral::~FuzzySugenoIntegral()
void FuzzySugenoIntegral::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
cv::Mat img_input_f3(img_input.size(), CV_32F);
- img_input.convertTo(img_input_f3, CV_32F, 1./255.);
-
- loadConfig();
+ img_input.convertTo(img_input_f3, CV_32F, 1. / 255.);
- if(firstTime)
+ if (firstTime)
{
std::cout << "FuzzySugenoIntegral parameters:" << std::endl;
-
+
std::string colorSpaceName = "";
- switch(colorSpace)
+ switch (colorSpace)
{
- case 1: colorSpaceName = "RGB"; break;
- case 2: colorSpaceName = "OHTA"; break;
- case 3: colorSpaceName = "HSV"; break;
- case 4: colorSpaceName = "YCrCb"; break;
+ case 1: colorSpaceName = "RGB"; break;
+ case 2: colorSpaceName = "OHTA"; break;
+ case 3: colorSpaceName = "HSV"; break;
+ case 4: colorSpaceName = "YCrCb"; break;
}
std::cout << "Color space: " << colorSpaceName << std::endl;
- if(option == 1)
+ if (option == 1)
std::cout << "Fuzzing by 3 color components" << std::endl;
- if(option == 2)
+ if (option == 2)
std::cout << "Fuzzing by 2 color components + 1 texture component" << std::endl;
-
- saveConfig();
}
- if(frameNumber <= framesToLearn)
+ if (frameNumber <= framesToLearn)
{
- if(frameNumber == 0)
+ if (frameNumber == 0)
std::cout << "FuzzySugenoIntegral initializing background model by adaptive learning..." << std::endl;
- if(img_background_f3.empty())
+ if (img_background_f3.empty())
img_input_f3.copyTo(img_background_f3);
else
- img_background_f3 = alphaLearn*img_input_f3 + (1-alphaLearn)*img_background_f3;
+ img_background_f3 = alphaLearn*img_input_f3 + (1 - alphaLearn)*img_background_f3;
+
+ double minVal = 0., maxVal = 1.;
+ img_background_f3.convertTo(img_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
+ img_background.copyTo(img_bgmodel);
+
+ img_foreground = cv::Mat::zeros(img_input.size(), img_input.type());
+ img_foreground.copyTo(img_output);
- if(showOutput)
- cv::imshow("SI BG Model", img_background_f3);
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("SI BG Model", img_background);
+#endif
}
else
{
@@ -87,72 +94,74 @@ void FuzzySugenoIntegral::process(const cv::Mat &img_input, cv::Mat &img_output,
IplImage* background_f1 = new IplImage(img_background_f1);
IplImage* lbp_input_f1 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 1);
- cvFillImage(lbp_input_f1, 0.0);
+ cvSetZero(lbp_input_f1);
fu.LBP(input_f1, lbp_input_f1);
- IplImage* lbp_background_f1 = cvCreateImage(cvSize(background_f1->width, background_f1->height), IPL_DEPTH_32F , 1);
- cvFillImage(lbp_background_f1, 0.0);
+ IplImage* lbp_background_f1 = cvCreateImage(cvSize(background_f1->width, background_f1->height), IPL_DEPTH_32F, 1);
+ cvSetZero(lbp_background_f1);
fu.LBP(background_f1, lbp_background_f1);
IplImage* sim_texture_f1 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 1);
fu.SimilarityDegreesImage(lbp_input_f1, lbp_background_f1, sim_texture_f1, 1, colorSpace);
IplImage* sim_color_f3 = cvCreateImage(cvSize(input_f3->width, input_f3->height), IPL_DEPTH_32F, 3);
- fu.SimilarityDegreesImage(input_f3, background_f3, sim_color_f3, 3, colorSpace);
+ fu.SimilarityDegreesImage(input_f3, background_f3, sim_color_f3, 3, colorSpace);
- float* measureG = (float*) malloc(3*(sizeof(float)));
+ float* measureG = (float*)malloc(3 * (sizeof(float)));
IplImage* integral_sugeno_f1 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 1);
// 3 color components
- if(option == 1)
+ if (option == 1)
{
fu.FuzzyMeasureG(0.4f, 0.3f, 0.3f, measureG);
fu.getFuzzyIntegralSugeno(sim_texture_f1, sim_color_f3, option, measureG, integral_sugeno_f1);
}
// 2 color components + 1 texture component
- if(option == 2)
+ if (option == 2)
{
fu.FuzzyMeasureG(0.6f, 0.3f, 0.1f, measureG);
fu.getFuzzyIntegralSugeno(sim_texture_f1, sim_color_f3, option, measureG, integral_sugeno_f1);
}
free(measureG);
- cv::Mat img_integral_sugeno_f1(integral_sugeno_f1);
+ cv::Mat img_integral_sugeno_f1 = cv::cvarrToMat(integral_sugeno_f1);
- if(smooth)
+ if (smooth)
cv::medianBlur(img_integral_sugeno_f1, img_integral_sugeno_f1, 3);
cv::Mat img_foreground_f1(img_input.size(), CV_32F);
cv::threshold(img_integral_sugeno_f1, img_foreground_f1, threshold, 255, cv::THRESH_BINARY_INV);
- cv::Mat img_foreground_u1(img_input.size(), CV_8U);
+ //cv::Mat img_foreground_u1(img_input.size(), CV_8U);
double minVal = 0., maxVal = 1.;
- img_foreground_f1.convertTo(img_foreground_u1, CV_8U, 255.0/(maxVal - minVal), -minVal);
- img_foreground_u1.copyTo(img_output);
-
- cv::Mat img_background_u3(img_input.size(), CV_8U);
+ img_foreground_f1.convertTo(img_foreground, CV_8U, 255.0 / (maxVal - minVal), -minVal);
+ img_foreground.copyTo(img_output);
+
+ //cv::Mat img_background_u3(img_input.size(), CV_8U);
//double minVal = 0., maxVal = 1.;
- img_background_f3.convertTo(img_background_u3, CV_8U, 255.0/(maxVal - minVal), -minVal);
- img_background_u3.copyTo(img_bgmodel);
+ img_background_f3.convertTo(img_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
+ img_background.copyTo(img_bgmodel);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cvShowImage("SI LBP Input", lbp_input_f1);
cvShowImage("SI LBP Background", lbp_background_f1);
cvShowImage("SI Prob FG Mask", integral_sugeno_f1);
- cv::imshow("SI BG Model", img_background_f3);
- cv::imshow("SI FG Mask", img_foreground_u1);
+ cv::imshow("SI BG Model", img_background);
+ cv::imshow("SI FG Mask", img_foreground);
}
+#endif
- if(frameNumber == (framesToLearn + 1))
+ if (frameNumber == (framesToLearn + 1))
std::cout << "FuzzySugenoIntegral updating background model by adaptive-selective learning..." << std::endl;
IplImage* updated_background_f3 = cvCreateImage(cvSize(input_f1->width, input_f1->height), IPL_DEPTH_32F, 3);
- cvFillImage(updated_background_f3, 0.0);
+ cvSetZero(updated_background_f3);
fu.AdaptativeSelectiveBackgroundModelUpdate(input_f3, background_f3, updated_background_f3, integral_sugeno_f1, threshold, alphaUpdate);
- cv::Mat img_updated_background_f3(updated_background_f3);
+ cv::Mat img_updated_background_f3 = cv::cvarrToMat(updated_background_f3);
img_updated_background_f3.copyTo(img_background_f3);
cvReleaseImage(&lbp_input_f1);
@@ -161,7 +170,7 @@ void FuzzySugenoIntegral::process(const cv::Mat &img_input, cv::Mat &img_output,
cvReleaseImage(&sim_color_f3);
cvReleaseImage(&integral_sugeno_f1);
cvReleaseImage(&updated_background_f3);
-
+
delete background_f1;
delete background_f3;
delete input_f1;
@@ -174,8 +183,8 @@ void FuzzySugenoIntegral::process(const cv::Mat &img_input, cv::Mat &img_output,
void FuzzySugenoIntegral::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/FuzzySugenoIntegral.xml", 0, CV_STORAGE_WRITE);
-
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
cvWriteInt(fs, "showOutput", showOutput);
cvWriteInt(fs, "framesToLearn", framesToLearn);
cvWriteReal(fs, "alphaLearn", alphaLearn);
@@ -184,22 +193,22 @@ void FuzzySugenoIntegral::saveConfig()
cvWriteInt(fs, "option", option);
cvWriteInt(fs, "smooth", smooth);
cvWriteReal(fs, "threshold", threshold);
-
+
cvReleaseFileStorage(&fs);
}
void FuzzySugenoIntegral::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/FuzzySugenoIntegral.xml", 0, CV_STORAGE_READ);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
- framesToLearn = cvReadIntByName(fs, 0, "framesToLearn", 10);
- alphaLearn = cvReadRealByName(fs, 0, "alphaLearn", 0.1);
- alphaUpdate = cvReadRealByName(fs, 0, "alphaUpdate", 0.01);
- colorSpace = cvReadIntByName(fs, 0, "colorSpace", 1);
- option = cvReadIntByName(fs, 0, "option", 2);
- smooth = cvReadIntByName(fs, 0, "smooth", true);
- threshold = cvReadRealByName(fs, 0, "threshold", 0.67);
-
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+ framesToLearn = cvReadIntByName(fs, nullptr, "framesToLearn", 10);
+ alphaLearn = cvReadRealByName(fs, nullptr, "alphaLearn", 0.1);
+ alphaUpdate = cvReadRealByName(fs, nullptr, "alphaUpdate", 0.01);
+ colorSpace = cvReadIntByName(fs, nullptr, "colorSpace", 1);
+ option = cvReadIntByName(fs, nullptr, "option", 2);
+ smooth = cvReadIntByName(fs, nullptr, "smooth", true);
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 0.67);
+
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/FuzzySugenoIntegral.h b/package_bgs/FuzzySugenoIntegral.h
new file mode 100644
index 0000000..70bde15
--- /dev/null
+++ b/package_bgs/FuzzySugenoIntegral.h
@@ -0,0 +1,53 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "T2F/FuzzyUtils.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class FuzzySugenoIntegral : public IBGS
+ {
+ private:
+ long long frameNumber;
+
+ int framesToLearn;
+ double alphaLearn;
+ double alphaUpdate;
+ int colorSpace;
+ int option;
+ bool smooth;
+ double threshold;
+
+ FuzzyUtils fu;
+ cv::Mat img_background_f3;
+
+ public:
+ FuzzySugenoIntegral();
+ ~FuzzySugenoIntegral();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/GMG.cpp b/package_bgs/GMG.cpp
index 675b23c..19bd8ab 100644
--- a/package_bgs/GMG.cpp
+++ b/package_bgs/GMG.cpp
@@ -16,9 +16,14 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "GMG.h"
-GMG::GMG() : firstTime(true), initializationFrames(20), decisionThreshold(0.7), showOutput(true)
+#if CV_MAJOR_VERSION == 2
+
+using namespace bgslibrary::algorithms;
+
+GMG::GMG() : initializationFrames(20), decisionThreshold(0.7)
{
std::cout << "GMG()" << std::endl;
+ setup("./config/GMG.xml");
cv::initModule_video();
cv::setUseOptimized(true);
@@ -34,41 +39,33 @@ GMG::~GMG()
void GMG::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- loadConfig();
-
- if(firstTime)
+ if (firstTime)
{
fgbg->set("initializationFrames", initializationFrames);
fgbg->set("decisionThreshold", decisionThreshold);
-
- saveConfig();
}
-
- if(fgbg.empty())
+
+ if (fgbg.empty())
{
std::cerr << "Failed to create BackgroundSubtractor.GMG Algorithm." << std::endl;
return;
}
(*fgbg)(img_input, img_foreground);
-
- cv::Mat img_background;
(*fgbg).getBackgroundImage(img_background);
img_input.copyTo(img_segmentation);
cv::add(img_input, cv::Scalar(100, 100, 0), img_segmentation, img_foreground);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
- if (!img_foreground.empty())
- cv::imshow("GMG FG (Godbehere-Matsukawa-Goldberg)", img_foreground);
-
- if (!img_background.empty())
- cv::imshow("GMG BG (Godbehere-Matsukawa-Goldberg)", img_background);
+ cv::imshow("GMG FG (Godbehere-Matsukawa-Goldberg)", img_foreground);
+ cv::imshow("GMG BG (Godbehere-Matsukawa-Goldberg)", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -78,7 +75,7 @@ void GMG::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bg
void GMG::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/GMG.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "initializationFrames", initializationFrames);
cvWriteReal(fs, "decisionThreshold", decisionThreshold);
@@ -89,11 +86,13 @@ void GMG::saveConfig()
void GMG::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/GMG.xml", 0, CV_STORAGE_READ);
-
- initializationFrames = cvReadIntByName(fs, 0, "initializationFrames", 20);
- decisionThreshold = cvReadRealByName(fs, 0, "decisionThreshold", 0.7);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ initializationFrames = cvReadIntByName(fs, nullptr, "initializationFrames", 20);
+ decisionThreshold = cvReadRealByName(fs, nullptr, "decisionThreshold", 0.7);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
cvReleaseFileStorage(&fs);
}
+
+#endif
diff --git a/package_bgs/GMG.h b/package_bgs/GMG.h
index 9da28ad..1b4af30 100644
--- a/package_bgs/GMG.h
+++ b/package_bgs/GMG.h
@@ -16,30 +16,34 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
+#include "opencv2/core/version.hpp"
+#if CV_MAJOR_VERSION == 2
#include "IBGS.h"
-class GMG : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::Ptr<cv::BackgroundSubtractorGMG> fgbg;
- int initializationFrames;
- double decisionThreshold;
- cv::Mat img_foreground;
- cv::Mat img_segmentation;
- bool showOutput;
-
-public:
- GMG();
- ~GMG();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class GMG : public IBGS
+ {
+ private:
+ cv::Ptr<cv::BackgroundSubtractorGMG> fgbg;
+ int initializationFrames;
+ double decisionThreshold;
+ cv::Mat img_segmentation;
+
+ public:
+ GMG();
+ ~GMG();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
+
+#endif
diff --git a/package_bgs/IBGS.h b/package_bgs/IBGS.h
index 073ce18..718bf51 100644
--- a/package_bgs/IBGS.h
+++ b/package_bgs/IBGS.h
@@ -16,18 +16,59 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
+#include <iostream>
+#include <fstream>
#include <opencv2/opencv.hpp>
-class IBGS
+namespace bgslibrary
{
-public:
- virtual void process(const cv::Mat &img_input, cv::Mat &img_foreground, cv::Mat &img_background) = 0;
- /*virtual void process(const cv::Mat &img_input, cv::Mat &img_foreground){
- process(img_input, img_foreground, cv::Mat());
- }*/
- virtual ~IBGS(){}
+ namespace algorithms
+ {
+ class IBGS
+ {
+ public:
+ void setShowOutput(const bool _showOutput) {
+ showOutput = _showOutput;
+ }
+ cv::Mat apply(const cv::Mat &img_input) {
+ setShowOutput(false);
+ cv::Mat _img_foreground;
+ cv::Mat _img_background;
+ process(img_input, _img_foreground, _img_background);
+ _img_background.copyTo(img_background);
+ return _img_foreground;
+ }
+ cv::Mat getBackgroundModel() {
+ return img_background;
+ }
+ virtual void process(const cv::Mat &img_input, cv::Mat &img_foreground, cv::Mat &img_background) = 0;
+ virtual ~IBGS() {}
-private:
- virtual void saveConfig() = 0;
- virtual void loadConfig() = 0;
-};
+ protected:
+ bool firstTime = true;
+ bool showOutput = true;
+ cv::Mat img_background;
+ cv::Mat img_foreground;
+ std::string config_xml;
+ void setup(const std::string _config_xml) {
+ config_xml = _config_xml;
+ if (!config_xml.empty()) {
+ if (!std::ifstream(config_xml))
+ saveConfig();
+ loadConfig();
+ }
+ }
+ void init(const cv::Mat &img_input, cv::Mat &img_outfg, cv::Mat &img_outbg) {
+ assert(img_input.empty() == false);
+ //img_outfg = cv::Mat::zeros(img_input.size(), img_input.type());
+ //img_outbg = cv::Mat::zeros(img_input.size(), img_input.type());
+ img_outfg = cv::Mat::zeros(img_input.size(), CV_8UC1);
+ img_outbg = cv::Mat::zeros(img_input.size(), CV_8UC3);
+ }
+
+ private:
+ virtual void saveConfig() = 0;
+ virtual void loadConfig() = 0;
+ };
+ }
+}
diff --git a/package_bgs/db/imbs.cpp b/package_bgs/IMBS/IMBS.cpp
similarity index 74%
rename from package_bgs/db/imbs.cpp
rename to package_bgs/IMBS/IMBS.cpp
index f5fc0d0..b1e177b 100644
--- a/package_bgs/db/imbs.cpp
+++ b/package_bgs/IMBS/IMBS.cpp
@@ -1,5 +1,21 @@
/*
-* IMBS Background Subtraction Library
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/*
+* IMBS Background Subtraction Library
*
* This file imbs.hpp contains the C++ OpenCV based implementation for
* IMBS algorithm described in
@@ -8,8 +24,8 @@
* In Proc. of the Third Int. Conf. on Computational Modeling of Objects
* Presented in Images: Fundamentals, Methods and Applications, pp. 39-44, 2012.
* Please, cite the above paper if you use IMBS.
-*
-* This software is provided without any warranty about its usability.
+*
+* This software is provided without any warranty about its usability.
* It is for educational purposes and should be regarded as such.
*
* Written by Domenico D. Bloisi
@@ -19,7 +35,7 @@
*
*/
-#include "imbs.hpp"
+#include "IMBS.hpp"
using namespace std;
using namespace cv;
@@ -29,15 +45,15 @@ BackgroundSubtractorIMBS::BackgroundSubtractorIMBS()
fps = 0.;
fgThreshold = 15;
associationThreshold = 5;
- samplingPeriod = 250.;//500.ms
+ samplingPeriod = 250;//500.ms
minBinHeight = 2;
numSamples = 10; //30
alpha = 0.65f;
beta = 1.15f;
- tau_s = 60.;
- tau_h = 40.;
+ tau_s = 60;
+ tau_h = 40;
minArea = 30.;
- persistencePeriod = samplingPeriod*numSamples/3.;//ms
+ persistencePeriod = samplingPeriod*numSamples / 3.;//ms
initial_tick_count = (double)getTickCount();
@@ -63,7 +79,7 @@ BackgroundSubtractorIMBS::BackgroundSubtractorIMBS(
this->fps = fps;
this->fgThreshold = fgThreshold;
this->persistencePeriod = persistencePeriod;
- if(minBinHeight <= 1){
+ if (minBinHeight <= 1) {
this->minBinHeight = 1;
}
else {
@@ -79,7 +95,7 @@ BackgroundSubtractorIMBS::BackgroundSubtractorIMBS(
this->tau_h = tau_h;
this->minArea = minArea;
- if(fps == 0.)
+ if (fps == 0.)
initial_tick_count = (double)getTickCount();
else
initial_tick_count = 0;
@@ -106,7 +122,7 @@ void BackgroundSubtractorIMBS::initialize(Size frameSize, int frameType)
this->numPixels = frameSize.width*frameSize.height;
persistenceMap = new unsigned int[numPixels];
- for(unsigned int i = 0; i < numPixels; i++) {
+ for (unsigned int i = 0; i < numPixels; i++) {
persistenceMap[i] = 0;
}
@@ -134,20 +150,20 @@ void BackgroundSubtractorIMBS::initialize(Size frameSize, int frameType)
//initial message to be shown until the first fg mask is computed
initialMsgGray = Mat::zeros(frameSize, CV_8UC1);
- putText(initialMsgGray, "Creating", Point(10,20), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
- putText(initialMsgGray, "initial", Point(10,40), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
- putText(initialMsgGray, "background...", Point(10,60), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
+ putText(initialMsgGray, "Creating", Point(10, 20), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
+ putText(initialMsgGray, "initial", Point(10, 40), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
+ putText(initialMsgGray, "background...", Point(10, 60), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
initialMsgRGB = Mat::zeros(frameSize, CV_8UC3);
- putText(initialMsgRGB, "Creating", Point(10,20), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
- putText(initialMsgRGB, "initial", Point(10,40), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
- putText(initialMsgRGB, "background...", Point(10,60), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
+ putText(initialMsgRGB, "Creating", Point(10, 20), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
+ putText(initialMsgRGB, "initial", Point(10, 40), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
+ putText(initialMsgRGB, "background...", Point(10, 60), FONT_HERSHEY_SIMPLEX, 0.4, CV_RGB(255, 255, 255));
- if(minBinHeight <= 1){
+ if (minBinHeight <= 1) {
minBinHeight = 1;
}
- for(unsigned int p = 0; p < numPixels; ++p)
+ for (unsigned int p = 0; p < numPixels; ++p)
{
bgBins[p].binValues = new Vec3b[numSamples];
bgBins[p].binHeights = new uchar[numSamples];
@@ -169,7 +185,7 @@ void BackgroundSubtractorIMBS::apply(InputArray _frame, OutputArray _fgmask, dou
CV_Assert(frame.channels() == 3);
bool needToInitialize = nframes == 0 || frame.type() != frameType;
- if( needToInitialize ) {
+ if (needToInitialize) {
initialize(frame.size(), frame.type());
}
@@ -179,29 +195,29 @@ void BackgroundSubtractorIMBS::apply(InputArray _frame, OutputArray _fgmask, dou
//get current time
prev_timestamp = timestamp;
- if(fps == 0.) {
+ if (fps == 0.) {
timestamp = getTimestamp();//ms
}
else {
- timestamp += 1000./fps;//ms
+ timestamp += 1000. / fps;//ms
}
//check for global changes
- if(sudden_change) {
+ if (sudden_change) {
changeBg();
}
//wait for the first model to be generated
- if(bgModel[0].isValid[0]) {
- getFg();
+ if (bgModel[0].isValid[0]) {
+ getFg();
hsvSuppression();
filterFg();
- }
+ }
//update the bg model
updateBg();
//show an initial message if the first bg is not yet ready
- if(!bgModel[0].isValid[0]) {
+ if (!bgModel[0].isValid[0]) {
initialMsgGray.copyTo(fgmask);
initialMsgRGB.copyTo(bgImage);
}
@@ -209,23 +225,23 @@ void BackgroundSubtractorIMBS::apply(InputArray _frame, OutputArray _fgmask, dou
}
void BackgroundSubtractorIMBS::updateBg() {
- if(bg_reset) {
- if(bg_frame_counter > numSamples - 1) {
+ if (bg_reset) {
+ if (bg_frame_counter > numSamples - 1) {
bg_frame_counter = numSamples - 1;
}
}
- if(prev_bg_frame_time > timestamp) {
+ if (prev_bg_frame_time > timestamp) {
prev_bg_frame_time = timestamp;
}
- if(bg_frame_counter == numSamples - 1) {
+ if (bg_frame_counter == numSamples - 1) {
createBg(bg_frame_counter);
bg_frame_counter = 0;
}
else { //bg_frame_counter < (numSamples - 1)
- if((timestamp - prev_bg_frame_time) >= samplingPeriod)
+ if ((timestamp - prev_bg_frame_time) >= samplingPeriod)
{
//get a new sample for creating the bg model
prev_bg_frame_time = timestamp;
@@ -237,7 +253,7 @@ void BackgroundSubtractorIMBS::updateBg() {
}
double BackgroundSubtractorIMBS::getTimestamp() {
- return ((double)getTickCount() - initial_tick_count)*1000./getTickFrequency();
+ return ((double)getTickCount() - initial_tick_count)*1000. / getTickFrequency();
}
void BackgroundSubtractorIMBS::hsvSuppression() {
@@ -251,35 +267,35 @@ void BackgroundSubtractorIMBS::hsvSuppression() {
vector<Mat> imHSV;
cv::split(convertImageRGBtoHSV(frame), imHSV);
- for(unsigned int p = 0; p < numPixels; ++p) {
- if(fgmask.data[p]) {
+ for (unsigned int p = 0; p < numPixels; ++p) {
+ if (fgmask.data[p]) {
h_i = imHSV[0].data[p];
s_i = imHSV[1].data[p];
v_i = imHSV[2].data[p];
- for(unsigned int n = 0; n < maxBgBins; ++n) {
- if(!bgModel[p].isValid[n]) {
+ for (unsigned int n = 0; n < maxBgBins; ++n) {
+ if (!bgModel[p].isValid[n]) {
break;
}
- if(bgModel[p].isFg[n]) {
+ if (bgModel[p].isFg[n]) {
continue;
}
- bgrPixel.at<cv::Vec3b>(0,0) = bgModel[p].values[n];
+ bgrPixel.at<cv::Vec3b>(0, 0) = bgModel[p].values[n];
cv::Mat hsvPixel = convertImageRGBtoHSV(bgrPixel);
- h_b = hsvPixel.at<cv::Vec3b>(0,0)[0];
- s_b = hsvPixel.at<cv::Vec3b>(0,0)[1];
- v_b = hsvPixel.at<cv::Vec3b>(0,0)[2];
+ h_b = hsvPixel.at<cv::Vec3b>(0, 0)[0];
+ s_b = hsvPixel.at<cv::Vec3b>(0, 0)[1];
+ v_b = hsvPixel.at<cv::Vec3b>(0, 0)[2];
v_ratio = (float)v_i / (float)v_b;
s_diff = std::abs(s_i - s_b);
- h_diff = std::min( std::abs(h_i - h_b), 255 - std::abs(h_i - h_b));
+ h_diff = std::min(std::abs(h_i - h_b), 255 - std::abs(h_i - h_b));
- if( h_diff <= tau_h &&
+ if (h_diff <= tau_h &&
s_diff <= tau_s &&
v_ratio >= alpha &&
v_ratio < beta)
@@ -293,7 +309,7 @@ void BackgroundSubtractorIMBS::hsvSuppression() {
}
void BackgroundSubtractorIMBS::createBg(unsigned int bg_sample_number) {
- if(!bgSample.data) {
+ if (!bgSample.data) {
//cerr << "createBg -- an error occurred: " <<
// " unable to retrieve frame no. " << bg_sample_number << endl;
@@ -305,18 +321,18 @@ void BackgroundSubtractorIMBS::createBg(unsigned int bg_sample_number) {
//split bgSample in channels
cv::split(bgSample, bgSampleBGR);
//create a statistical model for each pixel (a set of bins of variable size)
- for(unsigned int p = 0; p < numPixels; ++p) {
+ for (unsigned int p = 0; p < numPixels; ++p) {
//create an initial bin for each pixel from the first sample (bg_sample_number = 0)
- if(bg_sample_number == 0) {
- for(int k = 0; k < 3; ++k) {
+ if (bg_sample_number == 0) {
+ for (int k = 0; k < 3; ++k) {
bgBins[p].binValues[0][k] = bgSampleBGR[k].data[p];
}
bgBins[p].binHeights[0] = 1;
- for(unsigned int s = 1; s < numSamples; ++s) {
+ for (unsigned int s = 1; s < numSamples; ++s) {
bgBins[p].binHeights[s] = 0;
}
//if the sample pixel is from foreground keep track of that situation
- if(fgmask.data[p] == FOREGROUND_LABEL) {
+ if (fgmask.data[p] == FOREGROUND_LABEL) {
bgBins[p].isFg[0] = true;
}
else {
@@ -324,32 +340,32 @@ void BackgroundSubtractorIMBS::createBg(unsigned int bg_sample_number) {
}
}//if(bg_sample_number == 0)
else { //bg_sample_number > 0
- for(int k = 0; k < 3; ++k) {
+ for (int k = 0; k < 3; ++k) {
currentPixel[k] = bgSampleBGR[k].data[p];
}
int den = 0;
- for(unsigned int s = 0; s < bg_sample_number; ++s) {
+ for (unsigned int s = 0; s < bg_sample_number; ++s) {
//try to associate the current pixel values to an existing bin
- if( std::abs(currentPixel[2] - bgBins[p].binValues[s][2]) <= associationThreshold &&
+ if (std::abs(currentPixel[2] - bgBins[p].binValues[s][2]) <= associationThreshold &&
std::abs(currentPixel[1] - bgBins[p].binValues[s][1]) <= associationThreshold &&
- std::abs(currentPixel[0] - bgBins[p].binValues[s][0]) <= associationThreshold )
+ std::abs(currentPixel[0] - bgBins[p].binValues[s][0]) <= associationThreshold)
{
den = (bgBins[p].binHeights[s] + 1);
- for(int k = 0; k < 3; ++k) {
+ for (int k = 0; k < 3; ++k) {
bgBins[p].binValues[s][k] =
(bgBins[p].binValues[s][k] * bgBins[p].binHeights[s] + currentPixel[k]) / den;
}
bgBins[p].binHeights[s]++; //increment the height of the bin
- if(fgmask.data[p] == FOREGROUND_LABEL) {
+ if (fgmask.data[p] == FOREGROUND_LABEL) {
bgBins[p].isFg[s] = true;
}
break;
}
//if the association is not possible, create a new bin
- else if(bgBins[p].binHeights[s] == 0) {
+ else if (bgBins[p].binHeights[s] == 0) {
bgBins[p].binValues[s] = currentPixel;
bgBins[p].binHeights[s]++;
- if(fgmask.data[p] == FOREGROUND_LABEL) {
+ if (fgmask.data[p] == FOREGROUND_LABEL) {
bgBins[p].isFg[s] = true;
}
else {
@@ -362,44 +378,44 @@ void BackgroundSubtractorIMBS::createBg(unsigned int bg_sample_number) {
//if all samples have been processed
//it is time to compute the fg mask
- if(bg_sample_number == (numSamples - 1)) {
+ if (bg_sample_number == (numSamples - 1)) {
unsigned int index = 0;
int max_height = -1;
- for(unsigned int s = 0; s < numSamples; ++s){
- if(bgBins[p].binHeights[s] == 0) {
+ for (unsigned int s = 0; s < numSamples; ++s) {
+ if (bgBins[p].binHeights[s] == 0) {
bgModel[p].isValid[index] = false;
break;
}
- if(index == maxBgBins) {
+ if (index == maxBgBins) {
break;
}
- else if(bgBins[p].binHeights[s] >= minBinHeight) {
- if(fgmask.data[p] == PERSISTENCE_LABEL) {
- for(unsigned int n = 0; n < maxBgBins; n++) {
- if(!bgModel[p].isValid[n]) {
+ else if (bgBins[p].binHeights[s] >= minBinHeight) {
+ if (fgmask.data[p] == PERSISTENCE_LABEL) {
+ for (unsigned int n = 0; n < maxBgBins; n++) {
+ if (!bgModel[p].isValid[n]) {
break;
}
unsigned int d = std::max((int)std::abs(bgModel[p].values[n][0] - bgBins[p].binValues[s][0]),
- std::abs(bgModel[p].values[n][1] - bgBins[p].binValues[s][1]) );
- d = std::max((int)d, std::abs(bgModel[p].values[n][2] - bgBins[p].binValues[s][2]) );
- if(d < fgThreshold){
+ std::abs(bgModel[p].values[n][1] - bgBins[p].binValues[s][1]));
+ d = std::max((int)d, std::abs(bgModel[p].values[n][2] - bgBins[p].binValues[s][2]));
+ if (d < fgThreshold) {
bgModel[p].isFg[n] = false;
bgBins[p].isFg[s] = false;
}
}
}
- if(bgBins[p].binHeights[s] > max_height) {
+ if (bgBins[p].binHeights[s] > max_height) {
max_height = bgBins[p].binHeights[s];
- for(int k = 0; k < 3; ++k) {
+ for (int k = 0; k < 3; ++k) {
bgModel[p].values[index][k] = bgModel[p].values[0][k];
}
bgModel[p].isValid[index] = true;
bgModel[p].isFg[index] = bgModel[p].isFg[0];
bgModel[p].counter[index] = bgModel[p].counter[0];
- for(int k = 0; k < 3; ++k) {
+ for (int k = 0; k < 3; ++k) {
bgModel[p].values[0][k] = bgBins[p].binValues[s][k];
}
bgModel[p].isValid[0] = true;
@@ -407,7 +423,7 @@ void BackgroundSubtractorIMBS::createBg(unsigned int bg_sample_number) {
bgModel[p].counter[0] = bgBins[p].binHeights[s];
}
else {
- for(int k = 0; k < 3; ++k) {
+ for (int k = 0; k < 3; ++k) {
bgModel[p].values[index][k] = bgBins[p].binValues[s][k];
}
bgModel[p].isValid[index] = true;
@@ -421,25 +437,25 @@ void BackgroundSubtractorIMBS::createBg(unsigned int bg_sample_number) {
}//else --> if(frame_number == 0)
}//numPixels
- if(bg_sample_number == (numSamples - 1)) {
- //std::cout << "new bg created" << std::endl;
+ if (bg_sample_number == (numSamples - 1)) {
+ //std::cout << "new bg created" << std::endl;
persistenceImage = Scalar(0);
bg_reset = false;
- if(sudden_change) {
+ if (sudden_change) {
numSamples *= 3.;
samplingPeriod *= 2.;
sudden_change = false;
}
- for(unsigned int i = 0; i < numPixels; i++) {
+ for (unsigned int i = 0; i < numPixels; i++) {
persistenceMap[i] = 0;
}
unsigned int p = 0;
- for(int i = 0; i < bgImage.rows; ++i) {
- for(int j = 0; j < bgImage.cols; ++j, ++p) {
- bgImage.at<cv::Vec3b>(i,j) = bgModel[p].values[0];
+ for (int i = 0; i < bgImage.rows; ++i) {
+ for (int j = 0; j < bgImage.cols; ++j, ++p) {
+ bgImage.at<cv::Vec3b>(i, j) = bgModel[p].values[0];
}
}
}
@@ -452,13 +468,13 @@ void BackgroundSubtractorIMBS::getFg() {
bool isFg = true;
bool conditionalUpdated = false;
unsigned int d = 0;
- for(unsigned int p = 0; p < numPixels; ++p) {
+ for (unsigned int p = 0; p < numPixels; ++p) {
isFg = true;
conditionalUpdated = false;
d = 0;
- for(unsigned int n = 0; n < maxBgBins; ++n) {
- if(!bgModel[p].isValid[n]) {
- if(n == 0) {
+ for (unsigned int n = 0; n < maxBgBins; ++n) {
+ if (!bgModel[p].isValid[n]) {
+ if (n == 0) {
isFg = false;
}
break;
@@ -466,13 +482,13 @@ void BackgroundSubtractorIMBS::getFg() {
else { //the model is valid
d = std::max(
(int)std::abs(bgModel[p].values[n][0] - frameBGR[0].data[p]),
- std::abs(bgModel[p].values[n][1] - frameBGR[1].data[p]) );
+ std::abs(bgModel[p].values[n][1] - frameBGR[1].data[p]));
d = std::max(
- (int)d, std::abs(bgModel[p].values[n][2] - frameBGR[2].data[p]) );
- if(d < fgThreshold){
+ (int)d, std::abs(bgModel[p].values[n][2] - frameBGR[2].data[p]));
+ if (d < fgThreshold) {
//check if it is a potential background pixel
//from stationary object
- if(bgModel[p].isFg[n]) {
+ if (bgModel[p].isFg[n]) {
conditionalUpdated = true;
break;
}
@@ -483,13 +499,13 @@ void BackgroundSubtractorIMBS::getFg() {
}
}
}
- if(isFg) {
- if(conditionalUpdated) {
+ if (isFg) {
+ if (conditionalUpdated) {
fgmask.data[p] = PERSISTENCE_LABEL;
persistenceMap[p] += (timestamp - prev_timestamp);
- if(persistenceMap[p] > persistencePeriod) {
- for(unsigned int n = 0; n < maxBgBins; ++n) {
- if(!bgModel[p].isValid[n]) {
+ if (persistenceMap[p] > persistencePeriod) {
+ for (unsigned int n = 0; n < maxBgBins; ++n) {
+ if (!bgModel[p].isValid[n]) {
break;
}
bgModel[p].isFg[n] = false;
@@ -521,13 +537,13 @@ void BackgroundSubtractorIMBS::areaThresholding()
if (area < minArea || area >= maxArea)
continue;
else {
- drawContours( tmpBinaryImage, contours, contourIdx, Scalar(255), CV_FILLED );
+ drawContours(tmpBinaryImage, contours, contourIdx, Scalar(255), CV_FILLED);
}
- }
- for(int i = 0; i < fgfiltered.rows; ++i) {
- for(int j = 0; j < fgfiltered.cols; ++j) {
- if(!tmpBinaryImage.at<uchar>(i,j)) {
- fgfiltered.at<uchar>(i,j) = 0;
+ }
+ for (int i = 0; i < fgfiltered.rows; ++i) {
+ for (int j = 0; j < fgfiltered.cols; ++j) {
+ if (!tmpBinaryImage.at<uchar>(i, j)) {
+ fgfiltered.at<uchar>(i, j) = 0;
}
}
}
@@ -560,9 +576,9 @@ Mat BackgroundSubtractorIMBS::convertImageRGBtoHSV(const Mat& imageRGB)
for (int x = 0; x < w; ++x) {
// Get the RGB pixel components. NOTE that OpenCV stores RGB pixels in B,G,R order.
//uchar *pRGB = (uchar*)(imRGB + y*rowSizeRGB + x*3);
- int bB = imageRGB.at<Vec3b>(y,x)[0]; //*(uchar*)(pRGB+0); // Blue component
- int bG = imageRGB.at<Vec3b>(y,x)[1]; //*(uchar*)(pRGB+1); // Green component
- int bR = imageRGB.at<Vec3b>(y,x)[2]; //*(uchar*)(pRGB+2); // Red component
+ int bB = imageRGB.at<Vec3b>(y, x)[0]; //*(uchar*)(pRGB+0); // Blue component
+ int bG = imageRGB.at<Vec3b>(y, x)[1]; //*(uchar*)(pRGB+1); // Green component
+ int bR = imageRGB.at<Vec3b>(y, x)[2]; //*(uchar*)(pRGB+2); // Red component
// Convert from 8-bit integers to floats.
fR = bR * BYTE_TO_FLOAT;
@@ -619,10 +635,10 @@ Mat BackgroundSubtractorIMBS::convertImageRGBtoHSV(const Mat& imageRGB)
fH = (fG - fB) * ANGLE_TO_UNIT;
}
else if (iMax == bG) { // between cyan and yellow.
- fH = (2.0f/6.0f) + ( fB - fR ) * ANGLE_TO_UNIT;
+ fH = (2.0f / 6.0f) + (fB - fR) * ANGLE_TO_UNIT;
}
else { // between magenta and cyan.
- fH = (4.0f/6.0f) + ( fR - fG ) * ANGLE_TO_UNIT;
+ fH = (4.0f / 6.0f) + (fR - fG) * ANGLE_TO_UNIT;
}
// Wrap outlier Hues around the circle.
if (fH < 0.0f)
@@ -666,14 +682,14 @@ Mat BackgroundSubtractorIMBS::convertImageRGBtoHSV(const Mat& imageRGB)
void BackgroundSubtractorIMBS::getBackgroundImage(OutputArray backgroundImage) const
{
- bgImage.copyTo(backgroundImage);
+ bgImage.copyTo(backgroundImage);
}
void BackgroundSubtractorIMBS::filterFg() {
unsigned int cnt = 0;
- for(unsigned int p = 0; p < numPixels; ++p) {
- if(fgmask.data[p] == (uchar)255) {
+ for (unsigned int p = 0; p < numPixels; ++p) {
+ if (fgmask.data[p] == (uchar)255) {
fgfiltered.data[p] = 255;
cnt++;
}
@@ -682,23 +698,23 @@ void BackgroundSubtractorIMBS::filterFg() {
}
}
- if(cnt > numPixels*0.5) {
+ if (cnt > numPixels*0.5) {
sudden_change = true;
}
- if(morphologicalFiltering) {
- cv::Mat element3(3,3,CV_8U,cv::Scalar(1));
+ if (morphologicalFiltering) {
+ cv::Mat element3(3, 3, CV_8U, cv::Scalar(1));
cv::morphologyEx(fgfiltered, fgfiltered, cv::MORPH_OPEN, element3);
cv::morphologyEx(fgfiltered, fgfiltered, cv::MORPH_CLOSE, element3);
}
areaThresholding();
- for(unsigned int p = 0; p < numPixels; ++p) {
- if(fgmask.data[p] == PERSISTENCE_LABEL) {
+ for (unsigned int p = 0; p < numPixels; ++p) {
+ if (fgmask.data[p] == PERSISTENCE_LABEL) {
fgfiltered.data[p] = PERSISTENCE_LABEL;
}
- else if(fgmask.data[p] == SHADOW_LABEL) {
+ else if (fgmask.data[p] == SHADOW_LABEL) {
fgfiltered.data[p] = SHADOW_LABEL;
}
}
@@ -715,7 +731,7 @@ void BackgroundSubtractorIMBS::changeBg() {
//bg_reset = true;
//cout << "qua" << endl;
- if(!bg_reset) {
+ if (!bg_reset) {
numSamples /= 3.;
samplingPeriod /= 2.;
bg_frame_counter = 0;
@@ -724,19 +740,19 @@ void BackgroundSubtractorIMBS::changeBg() {
}
void BackgroundSubtractorIMBS::getBgModel(BgModel bgModel_copy[], int size) {
- if(size != numPixels) {
+ if (size != numPixels) {
return;
}
- for(unsigned int i = 0; i < numPixels; ++i){
+ for (unsigned int i = 0; i < numPixels; ++i) {
bgModel_copy[i].values = new Vec3b[maxBgBins];
bgModel_copy[i].isValid = new bool[maxBgBins];
bgModel_copy[i].isValid[0] = false;
bgModel_copy[i].isFg = new bool[maxBgBins];
bgModel_copy[i].counter = new uchar[maxBgBins];
}
- for(unsigned int p = 0; p < numPixels; ++p) {
- for(unsigned int n = 0; n < maxBgBins; ++n) {
- if(!bgModel[p].isValid[n]) {
+ for (unsigned int p = 0; p < numPixels; ++p) {
+ for (unsigned int n = 0; n < maxBgBins; ++n) {
+ if (!bgModel[p].isValid[n]) {
break;
}
bgModel_copy[p].values[n] = bgModel[p].values[n];
diff --git a/package_bgs/db/imbs.hpp b/package_bgs/IMBS/IMBS.hpp
similarity index 77%
rename from package_bgs/db/imbs.hpp
rename to package_bgs/IMBS/IMBS.hpp
index fd7faf1..383e0ae 100644
--- a/package_bgs/db/imbs.hpp
+++ b/package_bgs/IMBS/IMBS.hpp
@@ -1,5 +1,21 @@
/*
-* IMBS Background Subtraction Library
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/*
+* IMBS Background Subtraction Library
*
* This file imbs.hpp contains the C++ OpenCV based implementation for
* IMBS algorithm described in
@@ -8,8 +24,8 @@
* In Proc. of the Third Int. Conf. on Computational Modeling of Objects
* Presented in Images: Fundamentals, Methods and Applications, pp. 39-44, 2012.
* Please, cite the above paper if you use IMBS.
-*
-* This software is provided without any warranty about its usability.
+*
+* This software is provided without any warranty about its usability.
* It is for educational purposes and should be regarded as such.
*
* Written by Domenico D. Bloisi
@@ -18,9 +34,7 @@
* domenico.bloisi@gmail.com
*
*/
-
-#ifndef __IMBS_HPP__
-#define __IMBS_HPP__
+#pragma once
//OPENCV
#include <opencv2/core/core.hpp>
@@ -41,23 +55,23 @@ public:
BackgroundSubtractorIMBS();
//! the full constructor
BackgroundSubtractorIMBS(double fps,
- unsigned int fgThreshold=15,
- unsigned int associationThreshold=5,
- double samplingPeriod=500.,
- unsigned int minBinHeight=2,
- unsigned int numSamples=30,
- double alpha=0.65,
- double beta=1.15,
- double tau_s=60.,
- double tau_h=40.,
- double minArea=30.,
- double persistencePeriod=10000.,
- bool morphologicalFiltering=false
- );
+ unsigned int fgThreshold = 15,
+ unsigned int associationThreshold = 5,
+ double samplingPeriod = 500.,
+ unsigned int minBinHeight = 2,
+ unsigned int numSamples = 30,
+ double alpha = 0.65,
+ double beta = 1.15,
+ double tau_s = 60.,
+ double tau_h = 40.,
+ double minArea = 30.,
+ double persistencePeriod = 10000.,
+ bool morphologicalFiltering = false
+ );
//! the destructor
~BackgroundSubtractorIMBS();
//! the update operator
- void apply(InputArray image, OutputArray fgmask, double learningRate=-1.);
+ void apply(InputArray image, OutputArray fgmask, double learningRate = -1.);
//! computes a background image which shows only the highest bin for each pixel
void getBackgroundImage(OutputArray backgroundImage) const;
@@ -73,7 +87,7 @@ private:
//method for computing the foreground mask
void getFg();
//method for suppressing shadows and highlights
- void hsvSuppression();
+ void hsvSuppression();
//method for refining foreground mask
void filterFg();
//method for filtering out blobs smaller than a given area
@@ -82,7 +96,7 @@ private:
double getTimestamp();
//method for converting from RGB to HSV
Mat convertImageRGBtoHSV(const Mat& imageRGB);
- //method for changing the bg in case of sudden changes
+ //method for changing the bg in case of sudden changes
void changeBg();
//current input RGB frame
@@ -112,7 +126,7 @@ private:
//previous time stamp in milliseconds (ms)
double prev_timestamp;
double initial_tick_count;
- //initial message to be shown until the first bg model is ready
+ //initial message to be shown until the first bg model is ready
Mat initialMsgGray;
Mat initialMsgRGB;
@@ -174,5 +188,3 @@ public:
}
void getBgModel(BgModel bgModel_copy[], int size);
};
-
-#endif //__IMBS_HPP__
diff --git a/package_bgs/IndependentMultimodal.cpp b/package_bgs/IndependentMultimodal.cpp
new file mode 100644
index 0000000..7b4de4c
--- /dev/null
+++ b/package_bgs/IndependentMultimodal.cpp
@@ -0,0 +1,74 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "IndependentMultimodal.h"
+
+using namespace bgslibrary::algorithms;
+
+IndependentMultimodal::IndependentMultimodal() : fps(10)
+{
+ std::cout << "IndependentMultimodal()" << std::endl;
+ pIMBS = new BackgroundSubtractorIMBS(fps);
+ setup("./config/IndependentMultimodal.xml");
+}
+
+IndependentMultimodal::~IndependentMultimodal()
+{
+ std::cout << "~IndependentMultimodal()" << std::endl;
+ delete pIMBS;
+}
+
+void IndependentMultimodal::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ //get the fgmask and update the background model
+ pIMBS->apply(img_input, img_foreground);
+
+ //get background image
+ pIMBS->getBackgroundImage(img_background);
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ cv::imshow("IMBS FG", img_foreground);
+ cv::imshow("IMBS BG", img_background);
+ }
+#endif
+
+ firstTime = false;
+}
+
+void IndependentMultimodal::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void IndependentMultimodal::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/StaticFrameDifferenceBGS.h b/package_bgs/IndependentMultimodal.h
similarity index 60%
rename from package_bgs/StaticFrameDifferenceBGS.h
rename to package_bgs/IndependentMultimodal.h
index 55f7bf1..4e2e3a3 100644
--- a/package_bgs/StaticFrameDifferenceBGS.h
+++ b/package_bgs/IndependentMultimodal.h
@@ -16,30 +16,28 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
#include "IBGS.h"
+#include "IMBS/IMBS.hpp"
-class StaticFrameDifferenceBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::Mat img_background;
- cv::Mat img_foreground;
- bool enableThreshold;
- int threshold;
- bool showOutput;
-
-public:
- StaticFrameDifferenceBGS();
- ~StaticFrameDifferenceBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class IndependentMultimodal : public IBGS
+ {
+ private:
+ BackgroundSubtractorIMBS* pIMBS;
+ int fps;
+
+ public:
+ IndependentMultimodal();
+ ~IndependentMultimodal();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/ae/KDE.cpp b/package_bgs/KDE.cpp
similarity index 56%
rename from package_bgs/ae/KDE.cpp
rename to package_bgs/KDE.cpp
index 2cbbd8c..28564a0 100644
--- a/package_bgs/ae/KDE.cpp
+++ b/package_bgs/KDE.cpp
@@ -16,11 +16,15 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "KDE.h"
-KDE::KDE() : SequenceLength(50), TimeWindowSize(100), SDEstimationFlag(1), lUseColorRatiosFlag(1),
- th(10e-8), alpha(0.3), framesToLearn(10), frameNumber(0), firstTime(true), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+KDE::KDE() :
+ SequenceLength(50), TimeWindowSize(100), SDEstimationFlag(1), lUseColorRatiosFlag(1),
+ th(10e-8), alpha(0.3), framesToLearn(10), frameNumber(0)
{
p = new NPBGSubtractor;
std::cout << "KDE()" << std::endl;
+ setup("./config/KDE.xml");
}
KDE::~KDE()
@@ -32,72 +36,73 @@ KDE::~KDE()
void KDE::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
+ init(img_input, img_output, img_bgmodel);
- if(firstTime)
+ if (firstTime)
{
rows = img_input.size().height;
cols = img_input.size().width;
color_channels = img_input.channels();
// SequenceLength: number of samples for each pixel.
- // TimeWindowSize: Time window for sampling. for example in the call above, the bg will sample 50 points out of 100 frames.
+ // TimeWindowSize: Time window for sampling. for example in the call above, the bg will sample 50 points out of 100 frames.
// this rate will affect how fast the model adapt.
// SDEstimationFlag: True means to estimate suitable kernel bandwidth to each pixel, False uses a default value.
// lUseColorRatiosFlag: True means use normalized RGB for color (recommended.)
- p->Intialize(rows,cols,color_channels,SequenceLength,TimeWindowSize,SDEstimationFlag,lUseColorRatiosFlag);
+ p->Intialize(rows, cols, color_channels, SequenceLength, TimeWindowSize, SDEstimationFlag, lUseColorRatiosFlag);
// th: 0-1 is the probability threshold for a pixel to be a foregroud. typically make it small as 10e-8. the smaller the value the less false positive and more false negative.
// alpha: 0-1, for color. typically set to 0.3. this affect shadow suppression.
- p->SetThresholds(th,alpha);
+ p->SetThresholds(th, alpha);
FGImage = new unsigned char[rows*cols];
//FilteredFGImage = new unsigned char[rows*cols];
FilteredFGImage = 0;
DisplayBuffers = 0;
- img_foreground = cv::Mat::zeros(rows,cols,CV_8UC1);
+ img_foreground = cv::Mat::zeros(img_input.size(), CV_8UC1);
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
frameNumber = 0;
- saveConfig();
firstTime = false;
}
// Stores the first N frames to build the background model
- if(frameNumber < framesToLearn)
+ if (frameNumber < framesToLearn)
{
p->AddFrame(img_input.data);
frameNumber++;
- return;
}
-
- // Build the background model with first 10 frames
- if(frameNumber == framesToLearn)
+ else
{
- p->Estimation();
- frameNumber++;
- }
+ // Build the background model with first 10 frames
+ if (frameNumber == framesToLearn)
+ {
+ p->Estimation();
+ frameNumber++;
+ }
+
+ // Now, we can subtract the background
+ ((NPBGSubtractor*)p)->NBBGSubtraction(img_input.data, FGImage, FilteredFGImage, DisplayBuffers);
- // Now, we can subtract the background
- ((NPBGSubtractor *)p)->NBBGSubtraction(img_input.data,FGImage,FilteredFGImage,DisplayBuffers);
-
- // At each frame also you can call the update function to adapt the bg
- // here you pass a mask where pixels with true value will be masked out of the update.
- ((NPBGSubtractor *)p)->Update(FGImage);
+ // At each frame also you can call the update function to adapt the bg
+ // here you pass a mask where pixels with true value will be masked out of the update.
+ ((NPBGSubtractor*)p)->Update(FGImage);
- img_foreground.data = FGImage;
+ img_foreground.data = FGImage;
+ }
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
cv::imshow("KDE", img_foreground);
+#endif
img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
}
void KDE::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/KDE.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "framesToLearn", framesToLearn);
cvWriteInt(fs, "SequenceLength", SequenceLength);
@@ -113,16 +118,16 @@ void KDE::saveConfig()
void KDE::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/KDE.xml", 0, CV_STORAGE_READ);
-
- framesToLearn = cvReadIntByName(fs, 0, "framesToLearn", 10);
- SequenceLength = cvReadIntByName(fs, 0, "SequenceLength", 50);
- TimeWindowSize = cvReadIntByName(fs, 0, "TimeWindowSize", 100);
- SDEstimationFlag = cvReadIntByName(fs, 0, "SDEstimationFlag", 1);
- lUseColorRatiosFlag = cvReadIntByName(fs, 0, "lUseColorRatiosFlag", 1);
- th = cvReadRealByName(fs, 0, "th", 10e-8);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ framesToLearn = cvReadIntByName(fs, nullptr, "framesToLearn", 10);
+ SequenceLength = cvReadIntByName(fs, nullptr, "SequenceLength", 50);
+ TimeWindowSize = cvReadIntByName(fs, nullptr, "TimeWindowSize", 100);
+ SDEstimationFlag = cvReadIntByName(fs, nullptr, "SDEstimationFlag", 1);
+ lUseColorRatiosFlag = cvReadIntByName(fs, nullptr, "lUseColorRatiosFlag", 1);
+ th = cvReadRealByName(fs, nullptr, "th", 10e-8);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/KDE.h b/package_bgs/KDE.h
new file mode 100644
index 0000000..e77996f
--- /dev/null
+++ b/package_bgs/KDE.h
@@ -0,0 +1,57 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "KDE/NPBGSubtractor.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class KDE : public IBGS
+ {
+ private:
+ NPBGSubtractor *p;
+ int rows;
+ int cols;
+ int color_channels;
+ int SequenceLength;
+ int TimeWindowSize;
+ int SDEstimationFlag;
+ int lUseColorRatiosFlag;
+ double th;
+ double alpha;
+ int framesToLearn;
+ int frameNumber;
+
+ unsigned char *FGImage;
+ unsigned char *FilteredFGImage;
+ unsigned char **DisplayBuffers;
+
+ public:
+ KDE();
+ ~KDE();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/ae/KernelTable.cpp b/package_bgs/KDE/KernelTable.cpp
similarity index 75%
rename from package_bgs/ae/KernelTable.cpp
rename to package_bgs/KDE/KernelTable.cpp
index 9e20d7c..bd9c368 100644
--- a/package_bgs/ae/KernelTable.cpp
+++ b/package_bgs/KDE/KernelTable.cpp
@@ -26,21 +26,21 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* copyright notice must be included. For any other uses of this software,
* in original or modified form, including but not limited to distribution
* in whole or in part, specific prior permission must be obtained from
-* Author or UMIACS. These programs shall not be used, rewritten, or
-* adapted as the basis of a commercial software or hardware product
-* without first obtaining appropriate licenses from Author.
+* Author or UMIACS. These programs shall not be used, rewritten, or
+* adapted as the basis of a commercial software or hardware product
+* without first obtaining appropriate licenses from Author.
* Other than these cases, no part of this software may be used or
* distributed without written permission of the author.
*
-* Neither the author nor UMIACS make any representations about the
-* suitability of this software for any purpose. It is provided
+* Neither the author nor UMIACS make any representations about the
+* suitability of this software for any purpose. It is provided
* "as is" without express or implied warranty.
*
* Ahmed Elgammal
-*
+*
* University of Maryland at College Park
* UMIACS
-* A.V. Williams Bldg.
+* A.V. Williams Bldg.
* CollegePark, MD 20742
* E-mail: elgammal@umiacs.umd.edu
*
@@ -67,8 +67,8 @@ KernelLUTable::KernelLUTable(int KernelHalfWidth, double Segmamin, double Segmam
{
std::cout << "KernelLUTable()" << std::endl;
- double C1,C2,v,segma,sum;
- int bin,b;
+ double C1, C2, v, segma, sum;
+ int bin, b;
minsegma = Segmamin;
maxsegma = Segmamax;
@@ -78,27 +78,27 @@ KernelLUTable::KernelLUTable(int KernelHalfWidth, double Segmamin, double Segmam
// Generate the Kernel
// allocate memory for the Kernal Table
- kerneltable = new double[segmabins*(2*KernelHalfWidth+1)];
+ kerneltable = new double[segmabins*(2 * KernelHalfWidth + 1)];
kernelsums = new double[segmabins];
double segmastep = (maxsegma - minsegma) / segmabins;
double y;
- for(segma = minsegma, bin = 0; bin < segmabins; segma += segmastep, bin++)
+ for (segma = minsegma, bin = 0; bin < segmabins; segma += segmastep, bin++)
{
- C1 = 1/(sqrt(2*PI)*segma);
- C2 = -1/(2*segma*segma);
+ C1 = 1 / (sqrt(2 * PI)*segma);
+ C2 = -1 / (2 * segma*segma);
- b = (2*KernelHalfWidth+1)*bin;
+ b = (2 * KernelHalfWidth + 1)*bin;
sum = 0;
-
- for(int x = 0; x <= KernelHalfWidth; x++)
+
+ for (int x = 0; x <= KernelHalfWidth; x++)
{
- y = x/1.0;
+ y = x / 1.0;
v = C1*exp(C2*y*y);
- kerneltable[b+KernelHalfWidth+x]=v;
- kerneltable[b+KernelHalfWidth-x]=v;
- sum += 2*v;
+ kerneltable[b + KernelHalfWidth + x] = v;
+ kerneltable[b + KernelHalfWidth - x] = v;
+ sum += 2 * v;
}
sum -= C1;
@@ -106,11 +106,11 @@ KernelLUTable::KernelLUTable(int KernelHalfWidth, double Segmamin, double Segmam
kernelsums[bin] = sum;
// Normailization
- for(int x = 0; x <= KernelHalfWidth; x++)
+ for (int x = 0; x <= KernelHalfWidth; x++)
{
- v = kerneltable[b+KernelHalfWidth+x] / sum;
- kerneltable[b+KernelHalfWidth+x]=v;
- kerneltable[b+KernelHalfWidth-x]=v;
+ v = kerneltable[b + KernelHalfWidth + x] / sum;
+ kerneltable[b + KernelHalfWidth + x] = v;
+ kerneltable[b + KernelHalfWidth - x] = v;
}
}
}
diff --git a/package_bgs/ae/KernelTable.h b/package_bgs/KDE/KernelTable.h
similarity index 86%
rename from package_bgs/ae/KernelTable.h
rename to package_bgs/KDE/KernelTable.h
index bc37cc4..63a20dc 100644
--- a/package_bgs/ae/KernelTable.h
+++ b/package_bgs/KDE/KernelTable.h
@@ -26,28 +26,26 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* copyright notice must be included. For any other uses of this software,
* in original or modified form, including but not limited to distribution
* in whole or in part, specific prior permission must be obtained from
-* Author or UMIACS. These programs shall not be used, rewritten, or
-* adapted as the basis of a commercial software or hardware product
-* without first obtaining appropriate licenses from Author.
+* Author or UMIACS. These programs shall not be used, rewritten, or
+* adapted as the basis of a commercial software or hardware product
+* without first obtaining appropriate licenses from Author.
* Other than these cases, no part of this software may be used or
* distributed without written permission of the author.
*
-* Neither the author nor UMIACS make any representations about the
-* suitability of this software for any purpose. It is provided
+* Neither the author nor UMIACS make any representations about the
+* suitability of this software for any purpose. It is provided
* "as is" without express or implied warranty.
*
* Ahmed Elgammal
-*
+*
* University of Maryland at College Park
* UMIACS
-* A.V. Williams Bldg.
+* A.V. Williams Bldg.
* CollegePark, MD 20742
* E-mail: elgammal@umiacs.umd.edu
*
**/
-
-#ifndef __KERNEL_TABLE__
-#define __KERNEL_TABLE__
+#pragma once
#include <iostream>
@@ -65,7 +63,5 @@ public:
KernelLUTable();
~KernelLUTable();
- KernelLUTable(int KernelHalfWidth,double Segmamin,double Segmamax,int Segmabins);
+ KernelLUTable(int KernelHalfWidth, double Segmamin, double Segmamax, int Segmabins);
};
-
-#endif
diff --git a/package_bgs/KDE/NPBGSubtractor.cpp b/package_bgs/KDE/NPBGSubtractor.cpp
new file mode 100644
index 0000000..5f004b9
--- /dev/null
+++ b/package_bgs/KDE/NPBGSubtractor.cpp
@@ -0,0 +1,1160 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/*
+*
+* Copyright 2001 by Ahmed Elgammal All rights reserved.
+*
+* Permission to use, copy, or modify this software and its documentation
+* for educational and research purposes only and without fee is hereby
+* granted, provided that this copyright notice and the original authors's
+* name appear on all copies and supporting documentation. If individual
+* files are separated from this distribution directory structure, this
+* copyright notice must be included. For any other uses of this software,
+* in original or modified form, including but not limited to distribution
+* in whole or in part, specific prior permission must be obtained from
+* Author or UMIACS. These programs shall not be used, rewritten, or
+* adapted as the basis of a commercial software or hardware product
+* without first obtaining appropriate licenses from Author.
+* Other than these cases, no part of this software may be used or
+* distributed without written permission of the author.
+*
+* Neither the author nor UMIACS make any representations about the
+* suitability of this software for any purpose. It is provided
+* "as is" without express or implied warranty.
+*
+* Ahmed Elgammal
+*
+* University of Maryland at College Park
+* UMIACS
+* A.V. Williams Bldg.
+* CollegePark, MD 20742
+* E-mail: elgammal@umiacs.umd.edu
+*
+**/
+
+// NPBGSubtractor.cpp: implementation of the NPBGSubtractor class.
+//
+//////////////////////////////////////////////////////////////////////
+
+#include "NPBGSubtractor.h"
+#include <assert.h>
+#include <math.h>
+#include <string.h>
+
+//#ifdef _DEBUG
+//#undef THIS_FILE
+//static char THIS_FILE[]=__FILE__;
+//#define new DEBUG_NEW
+//#endif
+
+void BGR2SnGnRn(unsigned char * in_image,
+ unsigned char * out_image,
+ unsigned int rows,
+ unsigned int cols)
+{
+ unsigned int i;
+ unsigned int r2, r3;
+ unsigned int r, g, b;
+ double s;
+
+ for (i = 0; i < rows*cols * 3; i += 3)
+ {
+ b = in_image[i];
+ g = in_image[i + 1];
+ r = in_image[i + 2];
+
+ // calculate color ratios
+ s = (double)255 / (double)(b + g + r + 30);
+
+ r2 = (unsigned int)((g + 10) * s);
+ r3 = (unsigned int)((r + 10) * s);
+
+ out_image[i] = (unsigned char)(((unsigned int)b + g + r) / 3);
+ out_image[i + 1] = (unsigned char)(r2 > 255 ? 255 : r2);
+ out_image[i + 2] = (unsigned char)(r3 > 255 ? 255 : r3);
+ }
+}
+
+void UpdateDiffHist(unsigned char * image1, unsigned char * image2, DynamicMedianHistogram * pHist)
+{
+ unsigned int j;
+ int bin, diff;
+
+ unsigned int imagesize = pHist->imagesize;
+ unsigned char histbins = pHist->histbins;
+ unsigned char *pAbsDiffHist = pHist->Hist;
+
+ int histbins_1 = histbins - 1;
+
+ for (j = 0; j < imagesize; j++)
+ {
+ diff = (int)image1[j] - (int)image2[j];
+ diff = abs(diff);
+ // update histogram
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[j*histbins + bin]++;
+ }
+}
+
+void FindHistMedians(DynamicMedianHistogram * pAbsDiffHist)
+{
+ unsigned char * Hist = pAbsDiffHist->Hist;
+ unsigned char * MedianBins = pAbsDiffHist->MedianBins;
+ unsigned char * AccSum = pAbsDiffHist->AccSum;
+ unsigned char histsum = pAbsDiffHist->histsum;
+ unsigned char histbins = pAbsDiffHist->histbins;
+ unsigned int imagesize = pAbsDiffHist->imagesize;
+
+ int sum;
+ int bin;
+ unsigned int histindex;
+ unsigned char medianCount = histsum / 2;
+ unsigned int j;
+
+ // find medians
+ for (j = 0; j < imagesize; j++)
+ {
+ // find the median
+ bin = 0;
+ sum = 0;
+
+ histindex = j*histbins;
+
+ while (sum < medianCount)
+ {
+ sum += Hist[histindex + bin];
+ bin++;
+ }
+
+ bin--;
+
+ MedianBins[j] = bin;
+ AccSum[j] = sum;
+ }
+}
+
+DynamicMedianHistogram BuildAbsDiffHist(unsigned char * pSequence,
+ unsigned int rows,
+ unsigned int cols,
+ unsigned int color_channels,
+ unsigned int SequenceLength,
+ unsigned int histbins)
+{
+
+ unsigned int imagesize = rows*cols*color_channels;
+ unsigned int i;
+
+ DynamicMedianHistogram Hist;
+
+ unsigned char *pAbsDiffHist = new unsigned char[rows*cols*color_channels*histbins];
+ unsigned char *pMedianBins = new unsigned char[rows*cols*color_channels];
+ unsigned char *pMedianFreq = new unsigned char[rows*cols*color_channels];
+ unsigned char *pAccSum = new unsigned char[rows*cols*color_channels];
+
+ memset(pAbsDiffHist, 0, rows*cols*color_channels*histbins);
+
+ Hist.Hist = pAbsDiffHist;
+ Hist.MedianBins = pMedianBins;
+ Hist.MedianFreq = pMedianFreq;
+ Hist.AccSum = pAccSum;
+ Hist.histbins = histbins;
+ Hist.imagesize = rows*cols*color_channels;
+ Hist.histsum = SequenceLength - 1;
+
+ unsigned char *image1, *image2;
+ for (i = 1; i < SequenceLength; i++)
+ {
+ // find diff between frame i,i-1;
+ image1 = pSequence + (i - 1)*imagesize;
+ image2 = pSequence + (i)*imagesize;
+
+ UpdateDiffHist(image1, image2, &Hist);
+ }
+
+ FindHistMedians(&Hist);
+
+ return Hist;
+}
+
+void EstimateSDsFromAbsDiffHist(DynamicMedianHistogram * pAbsDiffHist,
+ unsigned char * pSDs,
+ unsigned int imagesize,
+ double MinSD,
+ double MaxSD,
+ unsigned int kernelbins)
+{
+ double v;
+ double kernelbinfactor = (kernelbins - 1) / (MaxSD - MinSD);
+ int medianCount;
+ int sum;
+ int bin;
+ unsigned int histindex;
+ unsigned int j;
+ unsigned int x1, x2;
+
+ unsigned char *Hist = pAbsDiffHist->Hist;
+ unsigned char *MedianBins = pAbsDiffHist->MedianBins;
+ unsigned char *AccSum = pAbsDiffHist->AccSum;
+ unsigned char histsum = pAbsDiffHist->histsum;
+ unsigned char histbins = pAbsDiffHist->histbins;
+
+ medianCount = (histsum) / 2;
+
+ for (j = 0; j < imagesize; j++)
+ {
+ histindex = j*histbins;
+
+ bin = MedianBins[j];
+ sum = AccSum[j];
+
+ x1 = sum - Hist[histindex + bin];
+ x2 = sum;
+
+ // interpolate to get the median
+ // x1 < 50 % < x2
+
+ v = 1.04 * ((double)bin - (double)(x2 - medianCount) / (double)(x2 - x1));
+ v = (v <= MinSD ? MinSD : v);
+
+ // convert sd to kernel table bin
+
+ bin = (int)(v >= MaxSD ? kernelbins - 1 : floor((v - MinSD)*kernelbinfactor + .5));
+
+ assert(bin >= 0 && bin < kernelbins);
+
+ pSDs[j] = bin;
+ }
+}
+
+//////////////////////////////////////////////////////////////////////
+// Construction/Destruction
+//////////////////////////////////////////////////////////////////////
+
+NPBGSubtractor::NPBGSubtractor() {}
+
+NPBGSubtractor::~NPBGSubtractor()
+{
+ delete AbsDiffHist.Hist;
+ delete AbsDiffHist.MedianBins;
+ delete AbsDiffHist.MedianFreq;
+ delete AbsDiffHist.AccSum;
+ delete KernelTable;
+ delete BGModel->SDbinsImage;
+ delete BGModel;
+ delete Pimage1;
+ delete Pimage2;
+ delete tempFrame;
+ delete imageindex->List;
+ delete imageindex;
+}
+
+int NPBGSubtractor::Intialize(unsigned int prows,
+ unsigned int pcols,
+ unsigned int pcolor_channels,
+ unsigned int SequenceLength,
+ unsigned int pTimeWindowSize,
+ unsigned char pSDEstimationFlag,
+ unsigned char pUseColorRatiosFlag)
+{
+
+ rows = prows;
+ cols = pcols;
+ color_channels = pcolor_channels;
+ imagesize = rows*cols*color_channels;
+ SdEstimateFlag = pSDEstimationFlag;
+ UseColorRatiosFlag = pUseColorRatiosFlag;
+ //SampleSize = SequenceLength;
+
+ AdaptBGFlag = FALSE;
+ //
+ SubsetFlag = TRUE;
+
+ UpdateSDRate = 0;
+
+ BGModel = new NPBGmodel(rows, cols, color_channels, SequenceLength, pTimeWindowSize, 500);
+
+ Pimage1 = new double[rows*cols];
+ Pimage2 = new double[rows*cols];
+
+ tempFrame = new unsigned char[rows*cols * 3];
+
+ imageindex = new ImageIndex;
+ imageindex->List = new unsigned int[rows*cols];
+
+ // error checking
+ if (BGModel == NULL)
+ return 0;
+
+ return 1;
+}
+
+void NPBGSubtractor::AddFrame(unsigned char *ImageBuffer)
+{
+ if (UseColorRatiosFlag && color_channels == 3)
+ BGR2SnGnRn(ImageBuffer, ImageBuffer, rows, cols);
+
+ BGModel->AddFrame(ImageBuffer);
+}
+
+void NPBGSubtractor::Estimation()
+{
+ int SampleSize = BGModel->SampleSize;
+
+ memset(BGModel->TemporalMask, 0, rows*cols*BGModel->TemporalBufferLength);
+
+ //BGModel->AccMask= new unsigned int [rows*cols];
+ memset(BGModel->AccMask, 0, rows*cols * sizeof(unsigned int));
+
+ unsigned char *pSDs = new unsigned char[rows*cols*color_channels];
+
+ //DynamicMedianHistogram AbsDiffHist;
+
+ int Abshistbins = 20;
+
+ TimeIndex = 0;
+
+ // estimate standard deviations
+
+ if (SdEstimateFlag)
+ {
+ AbsDiffHist = BuildAbsDiffHist(BGModel->Sequence, rows, cols, color_channels, SampleSize, Abshistbins);
+ EstimateSDsFromAbsDiffHist(&AbsDiffHist, pSDs, imagesize, SEGMAMIN, SEGMAMAX, SEGMABINS);
+ }
+ else
+ {
+ unsigned int bin;
+ bin = (unsigned int)floor(((DEFAULTSEGMA - SEGMAMIN)*SEGMABINS) / (SEGMAMAX - SEGMAMIN));
+ memset(pSDs, bin, rows*cols*color_channels * sizeof(unsigned char));
+ }
+
+ BGModel->SDbinsImage = pSDs;
+
+ // Generate the Kernel
+ KernelTable = new KernelLUTable(KERNELHALFWIDTH, SEGMAMIN, SEGMAMAX, SEGMABINS);
+}
+
+/*********************************************************************/
+
+void BuildImageIndex(unsigned char * Image,
+ ImageIndex * imageIndex,
+ unsigned int rows,
+ unsigned int cols)
+{
+ unsigned int i, j;
+ unsigned int r, c;
+ unsigned int * image_list;
+
+ j = cols + 1;
+ i = 0;
+ image_list = imageIndex->List;
+
+ for (r = 1; r < rows - 1; r++)
+ {
+ for (c = 1; c < cols - 1; c++)
+ {
+ if (Image[j])
+ image_list[i++] = j;
+
+ j++;
+ }
+ j += 2;
+ }
+
+ imageIndex->cnt = i;
+}
+
+/*********************************************************************/
+
+void HystExpandOperatorIndexed(unsigned char * inImage,
+ ImageIndex * inIndex,
+ double * Pimage,
+ double hyst_th,
+ unsigned char * outImage,
+ ImageIndex * outIndex,
+ unsigned int urows,
+ unsigned int ucols)
+{
+ unsigned int * in_list;
+ unsigned int in_cnt;
+ unsigned int * out_list;
+
+ int rows, cols;
+
+ int Nbr[9];
+ unsigned int i, j;
+ unsigned int k;
+ unsigned int idx;
+
+ rows = (int)urows;
+ cols = (int)ucols;
+
+ in_cnt = inIndex->cnt;
+ in_list = inIndex->List;
+
+ Nbr[0] = -cols - 1;
+ Nbr[1] = -cols;
+ Nbr[2] = -cols + 1;
+ Nbr[3] = -1;
+ Nbr[4] = 0;
+ Nbr[5] = 1;
+ Nbr[6] = cols - 1;
+ Nbr[7] = cols;
+ Nbr[8] = cols + 1;
+
+ memset(outImage, 0, rows*cols);
+
+ out_list = outIndex->List;
+ k = 0;
+
+ for (i = 0; i < in_cnt; i++)
+ {
+ for (j = 0; j < 9; j++)
+ {
+ idx = in_list[i] + Nbr[j];
+
+ if (Pimage[idx] < hyst_th)
+ outImage[idx] = 255;
+ }
+ }
+
+ // build index for out image
+ BuildImageIndex(outImage, outIndex, urows, ucols);
+}
+
+/*********************************************************************/
+
+void HystShrinkOperatorIndexed(unsigned char * inImage,
+ ImageIndex * inIndex,
+ double * Pimage,
+ double hyst_th,
+ unsigned char * outImage,
+ ImageIndex * outIndex,
+ unsigned int urows,
+ unsigned int ucols)
+{
+ unsigned int * in_list;
+ unsigned int in_cnt;
+ unsigned int * out_list;
+
+ int rows, cols;
+
+ int Nbr[9];
+ unsigned int i, j;
+ unsigned int k, idx;
+
+ rows = (int)urows;
+ cols = (int)ucols;
+
+ in_cnt = inIndex->cnt;
+ in_list = inIndex->List;
+
+ Nbr[0] = -cols - 1;
+ Nbr[1] = -cols;
+ Nbr[2] = -cols + 1;
+ Nbr[3] = -1;
+ Nbr[4] = 0;
+ Nbr[5] = 1;
+ Nbr[6] = cols - 1;
+ Nbr[7] = cols;
+ Nbr[8] = cols + 1;
+
+ memset(outImage, 0, rows*cols);
+
+ out_list = outIndex->List;
+ k = 0;
+
+ for (i = 0; i < in_cnt; i++)
+ {
+ idx = in_list[i];
+ j = 0;
+
+ while (j < 9 && inImage[idx + Nbr[j]])
+ j++;
+
+ if (j >= 9 || Pimage[idx] <= hyst_th)
+ outImage[idx] = 255;
+ }
+
+ BuildImageIndex(outImage, outIndex, rows, cols);
+}
+
+/*********************************************************************/
+
+void ExpandOperatorIndexed(unsigned char * inImage,
+ ImageIndex * inIndex,
+ unsigned char * outImage,
+ ImageIndex * outIndex,
+ unsigned int urows,
+ unsigned int ucols)
+{
+ unsigned int * in_list;
+ unsigned int in_cnt;
+ unsigned int * out_list;
+
+ int rows, cols;
+
+ int Nbr[9];
+ unsigned int i, j;
+ unsigned int k;
+ unsigned int idx;
+
+ rows = (int)urows;
+ cols = (int)ucols;
+
+ in_cnt = inIndex->cnt;
+ in_list = inIndex->List;
+
+ Nbr[0] = -cols - 1;
+ Nbr[1] = -cols;
+ Nbr[2] = -cols + 1;
+ Nbr[3] = -1;
+ Nbr[4] = 0;
+ Nbr[5] = 1;
+ Nbr[6] = cols - 1;
+ Nbr[7] = cols;
+ Nbr[8] = cols + 1;
+
+
+ memset(outImage, 0, rows*cols);
+
+
+ out_list = outIndex->List;
+ k = 0;
+ for (i = 0; i < in_cnt; i++)
+ for (j = 0; j < 9; j++) {
+ idx = in_list[i] + Nbr[j];
+ outImage[idx] = 255;
+ }
+
+
+ // build index for out image
+
+ BuildImageIndex(outImage, outIndex, rows, cols);
+
+}
+
+/*********************************************************************/
+
+void ShrinkOperatorIndexed(unsigned char * inImage,
+ ImageIndex * inIndex,
+ unsigned char * outImage,
+ ImageIndex * outIndex,
+ unsigned int urows,
+ unsigned int ucols)
+{
+
+ unsigned int * in_list;
+ unsigned int in_cnt;
+ unsigned int * out_list;
+
+ int rows, cols;
+
+ int Nbr[9];
+ unsigned int i, j;
+ unsigned int k, idx;
+
+ rows = (int)urows;
+ cols = (int)ucols;
+
+ in_cnt = inIndex->cnt;
+ in_list = inIndex->List;
+
+ Nbr[0] = -cols - 1;
+ Nbr[1] = -cols;
+ Nbr[2] = -cols + 1;
+ Nbr[3] = -1;
+ Nbr[4] = 0;
+ Nbr[5] = 1;
+ Nbr[6] = cols - 1;
+ Nbr[7] = cols;
+ Nbr[8] = cols + 1;
+
+
+ memset(outImage, 0, rows*cols);
+
+ out_list = outIndex->List;
+ k = 0;
+ for (i = 0; i < in_cnt; i++) {
+ idx = in_list[i];
+ j = 0;
+
+ while (j < 9 && inImage[idx + Nbr[j]]) {
+ j++;
+ }
+
+ if (j >= 9) {
+ outImage[idx] = 255;
+ }
+ }
+
+ BuildImageIndex(outImage, outIndex, rows, cols);
+}
+
+/*********************************************************************/
+
+void NoiseFilter_o(unsigned char * Image,
+ unsigned char * ResultIm,
+ int rows,
+ int cols,
+ unsigned char th)
+{
+ /* assuming input is 1 for on, 0 for off */
+
+
+ int r, c;
+ unsigned char *p, *n, *nw, *ne, *e, *w, *s, *sw, *se;
+ unsigned int v;
+ unsigned int TH;
+
+ unsigned char * ResultPtr;
+
+ TH = 255 * th;
+
+ memset(ResultIm, 0, rows*cols);
+
+ p = Image + cols + 1;
+ ResultPtr = ResultIm + cols + 1;
+
+ for (r = 1; r < rows - 1; r++)
+ {
+ for (c = 1; c < cols - 1; c++)
+ {
+ if (*p)
+ {
+ n = p - cols;
+ ne = n + 1;
+ nw = n - 1;
+ e = p + 1;
+ w = p - 1;
+ s = p + cols;
+ se = s + 1;
+ sw = s - 1;
+
+ v = (unsigned int)*nw + *n + *ne + *w + *e + *sw + *s + *se;
+
+ if (v >= TH)
+ *ResultPtr = 255;
+ else
+ *ResultPtr = 0;
+ }
+ p++;
+ ResultPtr++;
+ }
+ p += 2;
+ ResultPtr += 2;
+ }
+}
+
+/*********************************************************************/
+
+void NPBGSubtractor::SequenceBGUpdate_Pairs(unsigned char * image,
+ unsigned char * Mask)
+{
+ unsigned int i, ic;
+ unsigned char * pSequence = BGModel->Sequence;
+ unsigned char * PixelQTop = BGModel->PixelQTop;
+ unsigned int Top = BGModel->Top;
+ unsigned int rate;
+
+ int TemporalBufferTop = (int)BGModel->TemporalBufferTop;
+ unsigned char * pTemporalBuffer = BGModel->TemporalBuffer;
+ unsigned char * pTemporalMask = BGModel->TemporalMask;
+ int TemporalBufferLength = BGModel->TemporalBufferLength;
+
+ unsigned int * AccMask = BGModel->AccMask;
+ unsigned int ResetMaskTh = BGModel->ResetMaskTh;
+
+ unsigned char *pAbsDiffHist = AbsDiffHist.Hist;
+ unsigned char histbins = AbsDiffHist.histbins;
+ int histbins_1 = histbins - 1;
+
+ int TimeWindowSize = BGModel->TimeWindowSize;
+ int SampleSize = BGModel->SampleSize;
+
+ int TemporalBufferNext;
+
+ unsigned int imagebuffersize = rows*cols*color_channels;
+ unsigned int imagespatialsize = rows*cols;
+
+ unsigned char mask;
+
+ unsigned int histindex;
+ unsigned char diff;
+ unsigned char bin;
+
+ static int TBCount = 0;
+
+ unsigned char * pTBbase1, *pTBbase2;
+ unsigned char * pModelbase1, *pModelbase2;
+
+ rate = TimeWindowSize / SampleSize;
+ rate = (rate > 2) ? rate : 2;
+
+
+ TemporalBufferNext = (TemporalBufferTop + 1)
+ % TemporalBufferLength;
+
+ // pointers to Masks : Top and Next
+ unsigned char * pTMaskTop = pTemporalMask + TemporalBufferTop*imagespatialsize;
+ unsigned char * pTMaskNext = pTemporalMask + TemporalBufferNext*imagespatialsize;
+
+ // pointers to TB frames: Top and Next
+ unsigned char * pTBTop = pTemporalBuffer + TemporalBufferTop*imagebuffersize;
+ unsigned char * pTBNext = pTemporalBuffer + TemporalBufferNext*imagebuffersize;
+
+ if (((TimeIndex) % rate == 0) && TBCount >= TemporalBufferLength)
+ {
+ for (i = 0, ic = 0; i < imagespatialsize; i++, ic += color_channels)
+ {
+ mask = *(pTMaskTop + i) || *(pTMaskNext + i);
+
+ if (!mask)
+ {
+ // pointer to TB pixels to be added to the model
+ pTBbase1 = pTBTop + ic;
+ pTBbase2 = pTBNext + ic;
+
+ // pointers to Model pixels to be replaced
+ pModelbase1 = pSequence + PixelQTop[i] * imagebuffersize + ic;
+ pModelbase2 = pSequence + ((PixelQTop[i] + 1) % SampleSize)*imagebuffersize + ic;
+
+ // update Deviation Histogram
+ if (SdEstimateFlag)
+ {
+ if (color_channels == 1)
+ {
+ histindex = i*histbins;
+
+ // add new pair from temporal buffer
+ diff = (unsigned char)abs((int)*pTBbase1 - (int)*pTBbase2);
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]++;
+
+
+ // remove old pair from the model
+ diff = (unsigned char)abs((int)*pModelbase1 - (int)*pModelbase2);
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]--;
+ }
+ else
+ {
+ // color
+
+ // add new pair from temporal buffer
+ histindex = ic*histbins;
+ diff = abs(*pTBbase1 -
+ *pTBbase2);
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]++;
+
+ histindex += histbins;
+ diff = abs(*(pTBbase1 + 1) -
+ *(pTBbase2 + 1));
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]++;
+
+ histindex += histbins;
+ diff = abs(*(pTBbase1 + 2) -
+ *(pTBbase2 + 2));
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]++;
+
+ // remove old pair from the model
+ histindex = ic*histbins;
+
+ diff = abs(*pModelbase1 -
+ *pModelbase2);
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]--;
+
+ histindex += histbins;
+ diff = abs(*(pModelbase1 + 1) -
+ *(pModelbase2 + 1));
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]--;
+
+ histindex += histbins;
+ diff = abs(*(pModelbase1 + 2) -
+ *(pModelbase2 + 2));
+ bin = (diff < histbins ? diff : histbins_1);
+ pAbsDiffHist[histindex + bin]--;
+ }
+ }
+
+ // add new pair into the model
+ memcpy(pModelbase1, pTBbase1, color_channels * sizeof(unsigned char));
+
+ memcpy(pModelbase2, pTBbase2, color_channels * sizeof(unsigned char));
+
+ PixelQTop[i] = (PixelQTop[i] + 2) % SampleSize;
+ }
+ }
+ } // end if (sampling event)
+
+ // update temporal buffer
+ // add new frame to Temporal buffer.
+ memcpy(pTBTop, image, imagebuffersize);
+
+ // update AccMask
+ // update new Mask with information in AccMask
+
+ for (i = 0; i < rows*cols; i++)
+ {
+ if (Mask[i])
+ AccMask[i]++;
+ else
+ AccMask[i] = 0;
+
+ if (AccMask[i] > ResetMaskTh)
+ Mask[i] = 0;
+ }
+
+ // add new mask
+ memcpy(pTMaskTop, Mask, imagespatialsize);
+
+ // advance Temporal buffer pointer
+ TemporalBufferTop = (TemporalBufferTop + 1) % TemporalBufferLength;
+
+ BGModel->TemporalBufferTop = TemporalBufferTop;
+
+ TBCount++;
+
+ // estimate SDs
+
+ if (SdEstimateFlag && UpdateSDRate && ((TimeIndex) % UpdateSDRate == 0))
+ {
+ double MaxSD = KernelTable->maxsegma;
+ double MinSD = KernelTable->minsegma;
+ int KernelBins = KernelTable->segmabins;
+
+ unsigned char * pSDs = BGModel->SDbinsImage;
+
+ FindHistMedians(&(AbsDiffHist));
+ EstimateSDsFromAbsDiffHist(&(AbsDiffHist), pSDs, imagebuffersize, MinSD, MaxSD, KernelBins);
+ }
+
+ TimeIndex++;
+}
+
+/*********************************************************************/
+
+void DisplayPropabilityImageWithThresholding(double * Pimage,
+ unsigned char * DisplayImage,
+ double Threshold,
+ unsigned int rows,
+ unsigned int cols)
+{
+ double p;
+
+ for (unsigned int i = 0; i < rows*cols; i++)
+ {
+ p = Pimage[i];
+
+ DisplayImage[i] = (p > Threshold) ? 0 : 255;
+ }
+}
+
+/*********************************************************************/
+
+void NPBGSubtractor::NPBGSubtraction_Subset_Kernel(
+ unsigned char * image,
+ unsigned char * FGImage,
+ unsigned char * FilteredFGImage)
+{
+ unsigned int i, j;
+ unsigned char *pSequence = BGModel->Sequence;
+
+ unsigned int SampleSize = BGModel->SampleSize;
+
+ double *kerneltable = KernelTable->kerneltable;
+ int KernelHalfWidth = KernelTable->tablehalfwidth;
+ double *KernelSum = KernelTable->kernelsums;
+ double KernelMaxSigma = KernelTable->maxsegma;
+ double KernelMinSigma = KernelTable->minsegma;
+ int KernelBins = KernelTable->segmabins;
+ unsigned char * SDbins = BGModel->SDbinsImage;
+
+ unsigned char * SaturationImage = FilteredFGImage;
+
+ // default sigmas .. to be removed.
+ double sigma1;
+ double sigma2;
+ double sigma3;
+
+ sigma1 = 2.25;
+ sigma2 = 2.25;
+ sigma3 = 2.25;
+
+ double p;
+ double th;
+
+ double alpha;
+
+ alpha = AlphaValue;
+
+ /* intialize FG image */
+
+ memset(FGImage, 0, rows*cols);
+
+ //Threshold=1;
+ th = Threshold * SampleSize;
+
+ double sum = 0, kernel1, kernel2, kernel3;
+ int k, g;
+
+
+ if (color_channels == 1)
+ {
+ // gray scale
+
+ int kernelbase;
+
+ for (i = 0; i < rows*cols; i++)
+ {
+ kernelbase = SDbins[i] * (2 * KernelHalfWidth + 1);
+ sum = 0;
+ j = 0;
+
+ while (j < SampleSize && sum < th)
+ {
+ g = pSequence[j*imagesize + i];
+ k = g - image[i] + KernelHalfWidth;
+ sum += kerneltable[kernelbase + k];
+ j++;
+ }
+
+ p = sum / j;
+ Pimage1[i] = p;
+ }
+ }
+ else if (UseColorRatiosFlag && SubsetFlag)
+ {
+ // color ratios
+
+ unsigned int ig;
+ int base;
+
+ int kernelbase1;
+ int kernelbase2;
+ int kernelbase3;
+
+ unsigned int kerneltablewidth = 2 * KernelHalfWidth + 1;
+
+ double beta = 3.0; // minimum bound on the range.
+ double betau = 100.0;
+
+ double beta_over_alpha = beta / alpha;
+ double betau_over_alpha = betau / alpha;
+
+
+ double brightness_lowerbound = 1 - alpha;
+ double brightness_upperbound = 1 + alpha;
+ int x1, x2;
+ unsigned int SubsampleCount;
+
+ for (i = 0, ig = 0; i < imagesize; i += 3, ig++)
+ {
+ kernelbase1 = SDbins[i] * kerneltablewidth;
+ kernelbase2 = SDbins[i + 1] * kerneltablewidth;
+ kernelbase3 = SDbins[i + 2] * kerneltablewidth;
+
+ sum = 0;
+ j = 0;
+ SubsampleCount = 0;
+
+ while (j < SampleSize && sum < th)
+ {
+ base = j*imagesize + i;
+ g = pSequence[base];
+
+ if (g < beta_over_alpha)
+ {
+ x1 = (int)(g - beta);
+ x2 = (int)(g + beta);
+ }
+ else if (g > betau_over_alpha)
+ {
+ x1 = (int)(g - betau);
+ x2 = (int)(g + betau);
+ }
+ else
+ {
+ x1 = (int)(g*brightness_lowerbound + 0.5);
+ x2 = (int)(g*brightness_upperbound + 0.5);
+ }
+
+ if (x1 < image[i] && image[i] < x2)
+ {
+ g = pSequence[base + 1];
+ k = (g - image[i + 1]) + KernelHalfWidth;
+ kernel2 = kerneltable[kernelbase2 + k];
+
+ g = pSequence[base + 2];
+ k = (g - image[i + 2]) + KernelHalfWidth;
+ kernel3 = kerneltable[kernelbase3 + k];
+
+ sum += kernel2*kernel3;
+
+ SubsampleCount++;
+ }
+ j++;
+ }
+
+ p = sum / j;
+ Pimage1[ig] = p;
+ }
+ }
+ else if (UseColorRatiosFlag && !SubsetFlag)
+ {
+ // color ratios
+
+ unsigned int ig;
+ int base;
+ int bin;
+
+ int kernelbase1;
+ int kernelbase2;
+ int kernelbase3;
+
+ unsigned int kerneltablewidth = 2 * KernelHalfWidth + 1;
+
+ int gmin, gmax;
+ double gfactor;
+
+ gmax = 200;
+ gmin = 10;
+
+ gfactor = (KernelMaxSigma - KernelMinSigma) / (double)(gmax - gmin);
+
+ for (i = 0, ig = 0; i < imagesize; i += 3, ig++)
+ {
+
+ bin = (int)floor(((alpha * 16 - KernelMinSigma)*KernelBins) / (KernelMaxSigma - KernelMinSigma));
+
+ kernelbase1 = bin*kerneltablewidth;
+ kernelbase2 = SDbins[i + 1] * kerneltablewidth;
+ kernelbase3 = SDbins[i + 2] * kerneltablewidth;
+
+ sum = 0;
+ j = 0;
+
+ while (j < SampleSize && sum < th)
+ {
+ base = j*imagesize + i;
+ g = pSequence[base];
+
+ if (g < gmin)
+ bin = 0;
+ else if (g > gmax)
+ bin = KernelBins - 1;
+ else
+ bin = (int)((g - gmin) * gfactor + 0.5);
+
+ kernelbase1 = bin*kerneltablewidth;
+
+ k = (g - image[i]) + KernelHalfWidth;
+ kernel1 = kerneltable[kernelbase1 + k];
+
+ g = pSequence[base + 1];
+ k = (g - image[i + 1]) + KernelHalfWidth;
+ kernel2 = kerneltable[kernelbase2 + k];
+
+ g = pSequence[base + 2];
+ k = (g - image[i + 2]) + KernelHalfWidth;
+ kernel3 = kerneltable[kernelbase3 + k];
+
+ sum += kernel1*kernel2*kernel3;
+ j++;
+ }
+
+ p = sum / j;
+ Pimage1[ig] = p;
+ }
+ }
+ else // RGB color
+ {
+ unsigned int ig;
+ int base;
+
+ int kernelbase1;
+ int kernelbase2;
+ int kernelbase3;
+ unsigned int kerneltablewidth = 2 * KernelHalfWidth + 1;
+
+ for (i = 0, ig = 0; i < imagesize; i += 3, ig++)
+ {
+ // used extimated kernel width to access the right kernel
+ kernelbase1 = SDbins[i] * kerneltablewidth;
+ kernelbase2 = SDbins[i + 1] * kerneltablewidth;
+ kernelbase3 = SDbins[i + 2] * kerneltablewidth;
+
+ sum = 0;
+ j = 0;
+ while (j < SampleSize && sum < th)
+ {
+ base = j*imagesize + i;
+ g = pSequence[base];
+ k = (g - image[i]) + KernelHalfWidth;
+ kernel1 = kerneltable[kernelbase1 + k];
+
+ g = pSequence[base + 1];
+ k = (g - image[i + 1]) + KernelHalfWidth;
+ kernel2 = kerneltable[kernelbase2 + k];
+
+ g = pSequence[base + 2];
+ k = (g - image[i + 2]) + KernelHalfWidth;
+ kernel3 = kerneltable[kernelbase3 + k];
+
+ sum += kernel1*kernel2*kernel3;
+ j++;
+ }
+
+ p = sum / j;
+ Pimage1[ig] = p;
+ }
+ }
+
+ DisplayPropabilityImageWithThresholding(Pimage1, FGImage, Threshold, rows, cols);
+}
+
+/*********************************************************************/
+
+void NPBGSubtractor::NBBGSubtraction(unsigned char * Frame,
+ unsigned char * FGImage,
+ unsigned char * FilteredFGImage,
+ unsigned char ** DisplayBuffers)
+{
+ if (UseColorRatiosFlag)
+ BGR2SnGnRn(Frame, tempFrame, rows, cols);
+ else
+ memcpy(tempFrame, Frame, rows*cols*color_channels);
+
+ NPBGSubtraction_Subset_Kernel(tempFrame, FGImage, FilteredFGImage);
+ /*NoiseFilter_o(FGImage,DisplayBuffers[3],rows,cols,4);
+ BuildImageIndex(DisplayBuffers[3],imageindex,rows,cols);
+
+ ExpandOperatorIndexed(DisplayBuffers[3],imageindex,DisplayBuffers[4],imageindex,rows,cols);
+ ShrinkOperatorIndexed(DisplayBuffers[4],imageindex,FilteredFGImage,imageindex,rows,cols);
+
+ memset(DisplayBuffers[3],0,rows*cols);*/
+}
+
+void NPBGSubtractor::Update(unsigned char * FGMask)
+{
+ if (UpdateBGFlag)
+ SequenceBGUpdate_Pairs(tempFrame, FGMask);
+}
diff --git a/package_bgs/ae/NPBGSubtractor.h b/package_bgs/KDE/NPBGSubtractor.h
similarity index 87%
rename from package_bgs/ae/NPBGSubtractor.h
rename to package_bgs/KDE/NPBGSubtractor.h
index e7f3795..ce4bffc 100644
--- a/package_bgs/ae/NPBGSubtractor.h
+++ b/package_bgs/KDE/NPBGSubtractor.h
@@ -26,21 +26,21 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* copyright notice must be included. For any other uses of this software,
* in original or modified form, including but not limited to distribution
* in whole or in part, specific prior permission must be obtained from
-* Author or UMIACS. These programs shall not be used, rewritten, or
-* adapted as the basis of a commercial software or hardware product
-* without first obtaining appropriate licenses from Author.
+* Author or UMIACS. These programs shall not be used, rewritten, or
+* adapted as the basis of a commercial software or hardware product
+* without first obtaining appropriate licenses from Author.
* Other than these cases, no part of this software may be used or
* distributed without written permission of the author.
*
-* Neither the author nor UMIACS make any representations about the
-* suitability of this software for any purpose. It is provided
+* Neither the author nor UMIACS make any representations about the
+* suitability of this software for any purpose. It is provided
* "as is" without express or implied warranty.
*
* Ahmed Elgammal
-*
+*
* University of Maryland at College Park
* UMIACS
-* A.V. Williams Bldg.
+* A.V. Williams Bldg.
* CollegePark, MD 20742
* E-mail: elgammal@umiacs.umd.edu
*
@@ -49,13 +49,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// NPBGSubtractor.h: interface for the NPBGSubtractor class.
//
//////////////////////////////////////////////////////////////////////
-
-#if !defined(AFX_NPBGSUBTRACTOR_H__84B0F51E_6E65_41E4_AC01_723B406363C4__INCLUDED_)
-#define AFX_NPBGSUBTRACTOR_H__84B0F51E_6E65_41E4_AC01_723B406363C4__INCLUDED_
-
-#if _MSC_VER > 1000
#pragma once
-#endif // _MSC_VER > 1000
#include "NPBGmodel.h"
#include "KernelTable.h"
@@ -87,7 +81,7 @@ typedef struct
unsigned int *List;
} ImageIndex;
-class NPBGSubtractor
+class NPBGSubtractor
{
private:
unsigned int rows;
@@ -146,9 +140,7 @@ public:
AlphaValue = alpha;
};
- void SetUpdateFlag(unsigned int bgflag){
+ void SetUpdateFlag(unsigned int bgflag) {
UpdateBGFlag = bgflag;
};
};
-
-#endif // !defined(AFX_NPBGSUBTRACTOR_H__84B0F51E_6E65_41E4_AC01_723B406363C4__INCLUDED_)
diff --git a/package_bgs/ae/NPBGmodel.cpp b/package_bgs/KDE/NPBGmodel.cpp
similarity index 78%
rename from package_bgs/ae/NPBGmodel.cpp
rename to package_bgs/KDE/NPBGmodel.cpp
index 2c8b074..a79a7b4 100644
--- a/package_bgs/ae/NPBGmodel.cpp
+++ b/package_bgs/KDE/NPBGmodel.cpp
@@ -26,21 +26,21 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* copyright notice must be included. For any other uses of this software,
* in original or modified form, including but not limited to distribution
* in whole or in part, specific prior permission must be obtained from
-* Author or UMIACS. These programs shall not be used, rewritten, or
-* adapted as the basis of a commercial software or hardware product
-* without first obtaining appropriate licenses from Author.
+* Author or UMIACS. These programs shall not be used, rewritten, or
+* adapted as the basis of a commercial software or hardware product
+* without first obtaining appropriate licenses from Author.
* Other than these cases, no part of this software may be used or
* distributed without written permission of the author.
*
-* Neither the author nor UMIACS make any representations about the
-* suitability of this software for any purpose. It is provided
+* Neither the author nor UMIACS make any representations about the
+* suitability of this software for any purpose. It is provided
* "as is" without express or implied warranty.
*
* Ahmed Elgammal
-*
+*
* University of Maryland at College Park
* UMIACS
-* A.V. Williams Bldg.
+* A.V. Williams Bldg.
* CollegePark, MD 20742
* E-mail: elgammal@umiacs.umd.edu
*
@@ -55,7 +55,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#ifdef _DEBUG
#undef THIS_FILE
-static char THIS_FILE[]=__FILE__;
+static char THIS_FILE[] = __FILE__;
//#define new DEBUG_NEW
#endif
@@ -80,11 +80,11 @@ NPBGmodel::~NPBGmodel()
}
NPBGmodel::NPBGmodel(unsigned int Rows,
- unsigned int Cols,
- unsigned int ColorChannels,
- unsigned int Length,
- unsigned int pTimeWindowSize,
- unsigned int bg_suppression_time)
+ unsigned int Cols,
+ unsigned int ColorChannels,
+ unsigned int Length,
+ unsigned int pTimeWindowSize,
+ unsigned int bg_suppression_time)
{
std::cout << "NPBGmodel()" << std::endl;
@@ -98,14 +98,14 @@ NPBGmodel::NPBGmodel(unsigned int Rows,
TimeWindowSize = pTimeWindowSize;
- Sequence = new unsigned char[imagesize*Length];
+ Sequence = new unsigned char[imagesize*Length];
Top = 0;
- memset(Sequence,0,imagesize*Length);
+ memset(Sequence, 0, imagesize*Length);
PixelQTop = new unsigned char[rows*cols];
// temporalBuffer
- TemporalBufferLength = (TimeWindowSize/Length > 2 ? TimeWindowSize/Length:2);
+ TemporalBufferLength = (TimeWindowSize / Length > 2 ? TimeWindowSize / Length : 2);
TemporalBuffer = new unsigned char[imagesize*TemporalBufferLength];
TemporalMask = new unsigned char[rows*cols*TemporalBufferLength];
@@ -116,12 +116,12 @@ NPBGmodel::NPBGmodel(unsigned int Rows,
ResetMaskTh = bg_suppression_time;
}
-void NPBGmodel::AddFrame(unsigned char *ImageBuffer)
+void NPBGmodel::AddFrame(unsigned char *ImageBuffer)
{
- memcpy(Sequence+Top*imagesize,ImageBuffer,imagesize);
- Top = (Top + 1) % SampleSize;
+ memcpy(Sequence + Top*imagesize, ImageBuffer, imagesize);
+ Top = (Top + 1) % SampleSize;
- memset(PixelQTop, (unsigned char) Top, rows*cols);
+ memset(PixelQTop, (unsigned char)Top, rows*cols);
- memcpy(TemporalBuffer,ImageBuffer,imagesize);
+ memcpy(TemporalBuffer, ImageBuffer, imagesize);
}
diff --git a/package_bgs/ae/NPBGmodel.h b/package_bgs/KDE/NPBGmodel.h
similarity index 84%
rename from package_bgs/ae/NPBGmodel.h
rename to package_bgs/KDE/NPBGmodel.h
index 9e28510..ba4a927 100644
--- a/package_bgs/ae/NPBGmodel.h
+++ b/package_bgs/KDE/NPBGmodel.h
@@ -26,21 +26,21 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* copyright notice must be included. For any other uses of this software,
* in original or modified form, including but not limited to distribution
* in whole or in part, specific prior permission must be obtained from
-* Author or UMIACS. These programs shall not be used, rewritten, or
-* adapted as the basis of a commercial software or hardware product
-* without first obtaining appropriate licenses from Author.
+* Author or UMIACS. These programs shall not be used, rewritten, or
+* adapted as the basis of a commercial software or hardware product
+* without first obtaining appropriate licenses from Author.
* Other than these cases, no part of this software may be used or
* distributed without written permission of the author.
*
-* Neither the author nor UMIACS make any representations about the
-* suitability of this software for any purpose. It is provided
+* Neither the author nor UMIACS make any representations about the
+* suitability of this software for any purpose. It is provided
* "as is" without express or implied warranty.
*
* Ahmed Elgammal
-*
+*
* University of Maryland at College Park
* UMIACS
-* A.V. Williams Bldg.
+* A.V. Williams Bldg.
* CollegePark, MD 20742
* E-mail: elgammal@umiacs.umd.edu
*
@@ -49,24 +49,18 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// NPBGmodel.h: interface for the NPBGmodel class.
//
//////////////////////////////////////////////////////////////////////
-
-#if !defined(AFX_NPBGMODEL_H__CCAF05D4_D06E_44C2_95D8_979E2249953A__INCLUDED_)
-#define AFX_NPBGMODEL_H__CCAF05D4_D06E_44C2_95D8_979E2249953A__INCLUDED_
-
-#if _MSC_VER > 1000
#pragma once
-#endif // _MSC_VER > 1000
#include <iostream>
-class NPBGmodel
+class NPBGmodel
{
private:
unsigned char *Sequence;
unsigned int SampleSize;
unsigned int TimeWindowSize;
- unsigned int rows,cols,color_channels;
+ unsigned int rows, cols, color_channels;
unsigned int imagesize;
unsigned int Top;
@@ -74,7 +68,7 @@ private:
//unsigned int *PixelUpdateCounter;
- unsigned char *SDbinsImage;
+ unsigned char *SDbinsImage;
unsigned char *TemporalBuffer;
unsigned char TemporalBufferLength;
@@ -107,5 +101,3 @@ public:
friend class NPBGSubtractor;
};
-
-#endif // !defined(AFX_NPBGMODEL_H__CCAF05D4_D06E_44C2_95D8_979E2249953A__INCLUDED_)
diff --git a/package_bgs/KNN.cpp b/package_bgs/KNN.cpp
new file mode 100644
index 0000000..d2e1412
--- /dev/null
+++ b/package_bgs/KNN.cpp
@@ -0,0 +1,111 @@
+/*
+ This file is part of BGSLibrary.
+
+ BGSLibrary is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ BGSLibrary is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+ */
+#include "KNN.h"
+
+#if CV_MAJOR_VERSION == 3
+
+using namespace bgslibrary::algorithms;
+
+KNN::KNN() :
+ history(500), nSamples(7), dist2Threshold(20.0f * 20.0f), knnSamples(0),
+ doShadowDetection(true), shadowValue(127), shadowThreshold(0.5f)
+{
+ std::cout << "KNN()" << std::endl;
+ setup("./config/KNN.xml");
+}
+
+KNN::~KNN()
+{
+ std::cout << "~KNN()" << std::endl;
+}
+
+void KNN::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ //------------------------------------------------------------------
+ // BackgroundSubtractorKNN
+ // http://docs.opencv.org/trunk/modules/video/doc/motion_analysis_and_object_tracking.html#backgroundsubtractorknn
+ //
+ // The class implements the K nearest neigbours algorithm from:
+ // "Efficient Adaptive Density Estimation per Image Pixel for the Task of Background Subtraction"
+ // Z.Zivkovic, F. van der Heijden
+ // Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006
+ // http: //www.zoranz.net/Publications/zivkovicPRL2006.pdf
+ //
+ // Fast for small foreground object. Results on the benchmark data is at http://www.changedetection.net.
+ //------------------------------------------------------------------
+
+ int prevNSamples = nSamples;
+ if (firstTime)
+ knn = cv::createBackgroundSubtractorKNN(history, dist2Threshold, doShadowDetection);
+
+ knn->setNSamples(nSamples);
+ knn->setkNNSamples(knnSamples);
+ knn->setShadowValue(shadowValue);
+ knn->setShadowThreshold(shadowThreshold);
+
+ knn->apply(img_input, img_foreground, prevNSamples != nSamples ? 0.f : 1.f);
+ knn->getBackgroundImage(img_background);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ cv::imshow("KNN FG", img_foreground);
+ cv::imshow("KNN BG", img_background);
+ }
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+
+ firstTime = false;
+}
+
+void KNN::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "history", history);
+ cvWriteInt(fs, "nSamples", nSamples);
+ cvWriteReal(fs, "dist2Threshold", dist2Threshold);
+ cvWriteInt(fs, "knnSamples", knnSamples);
+ cvWriteInt(fs, "doShadowDetection", doShadowDetection);
+ cvWriteInt(fs, "shadowValue", shadowValue);
+ cvWriteReal(fs, "shadowThreshold", shadowThreshold);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void KNN::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ history = cvReadIntByName(fs, nullptr, "history", 500);
+ nSamples = cvReadIntByName(fs, nullptr, "nSamples", 7);
+ dist2Threshold = cvReadRealByName(fs, nullptr, "dist2Threshold", 20.0f * 20.0f);
+ knnSamples = cvReadIntByName(fs, nullptr, "knnSamples", 0);
+ doShadowDetection = cvReadIntByName(fs, nullptr, "doShadowDetection", 1);
+ shadowValue = cvReadIntByName(fs, nullptr, "shadowValue", 127);
+ shadowThreshold = cvReadRealByName(fs, nullptr, "shadowThreshold", 0.5f);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
+
+#endif
diff --git a/package_bgs/KNN.h b/package_bgs/KNN.h
new file mode 100644
index 0000000..87f20b2
--- /dev/null
+++ b/package_bgs/KNN.h
@@ -0,0 +1,57 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "opencv2/core/version.hpp"
+#if CV_MAJOR_VERSION == 3
+
+#include <iostream>
+#include <opencv2/opencv.hpp>
+#include <opencv2/video/background_segm.hpp>
+
+#include "IBGS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class KNN : public IBGS
+ {
+ private:
+ cv::Ptr<cv::BackgroundSubtractorKNN> knn;
+ int history;
+ int nSamples;
+ float dist2Threshold;
+ int knnSamples;
+ bool doShadowDetection;
+ int shadowValue;
+ float shadowThreshold;
+
+ public:
+ KNN();
+ ~KNN();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
+
+#endif
diff --git a/package_bgs/lb/LBAdaptiveSOM.cpp b/package_bgs/LBAdaptiveSOM.cpp
similarity index 61%
rename from package_bgs/lb/LBAdaptiveSOM.cpp
rename to package_bgs/LBAdaptiveSOM.cpp
index ce06433..188e11d 100644
--- a/package_bgs/lb/LBAdaptiveSOM.cpp
+++ b/package_bgs/LBAdaptiveSOM.cpp
@@ -16,10 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "LBAdaptiveSOM.h"
-LBAdaptiveSOM::LBAdaptiveSOM() : firstTime(true), showOutput(true),
+using namespace bgslibrary::algorithms;
+
+LBAdaptiveSOM::LBAdaptiveSOM() :
sensitivity(75), trainingSensitivity(245), learningRate(62), trainingLearningRate(255), trainingSteps(55)
{
std::cout << "LBAdaptiveSOM()" << std::endl;
+ setup("./config/LBAdaptiveSOM.xml");
}
LBAdaptiveSOM::~LBAdaptiveSOM()
@@ -30,64 +33,55 @@ LBAdaptiveSOM::~LBAdaptiveSOM()
void LBAdaptiveSOM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- loadConfig();
-
IplImage *frame = new IplImage(img_input);
-
- if(firstTime)
- {
- saveConfig();
+ if (firstTime)
+ {
int w = cvGetSize(frame).width;
int h = cvGetSize(frame).height;
- m_pBGModel = new BGModelSom(w,h);
+ m_pBGModel = new BGModelSom(w, h);
m_pBGModel->InitModel(frame);
}
-
- m_pBGModel->setBGModelParameter(0,sensitivity);
- m_pBGModel->setBGModelParameter(1,trainingSensitivity);
- m_pBGModel->setBGModelParameter(2,learningRate);
- m_pBGModel->setBGModelParameter(3,trainingLearningRate);
- m_pBGModel->setBGModelParameter(5,trainingSteps);
+
+ m_pBGModel->setBGModelParameter(0, sensitivity);
+ m_pBGModel->setBGModelParameter(1, trainingSensitivity);
+ m_pBGModel->setBGModelParameter(2, learningRate);
+ m_pBGModel->setBGModelParameter(3, trainingLearningRate);
+ m_pBGModel->setBGModelParameter(5, trainingSteps);
m_pBGModel->UpdateModel(frame);
- img_foreground = cv::Mat(m_pBGModel->GetFG());
- img_background = cv::Mat(m_pBGModel->GetBG());
-
- if(showOutput)
+ img_foreground = cv::cvarrToMat(m_pBGModel->GetFG());
+ img_background = cv::cvarrToMat(m_pBGModel->GetBG());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cv::imshow("SOM Mask", img_foreground);
cv::imshow("SOM Model", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
-
+
delete frame;
-
+
firstTime = false;
}
-//void LBAdaptiveSOM::finish(void)
-//{
-// delete m_pBGModel;
-//}
-
void LBAdaptiveSOM::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBAdaptiveSOM.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "sensitivity", sensitivity);
cvWriteInt(fs, "trainingSensitivity", trainingSensitivity);
cvWriteInt(fs, "learningRate", learningRate);
cvWriteInt(fs, "trainingLearningRate", trainingLearningRate);
cvWriteInt(fs, "trainingSteps", trainingSteps);
-
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
@@ -95,15 +89,14 @@ void LBAdaptiveSOM::saveConfig()
void LBAdaptiveSOM::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBAdaptiveSOM.xml", 0, CV_STORAGE_READ);
-
- sensitivity = cvReadIntByName(fs, 0, "sensitivity", 75);
- trainingSensitivity = cvReadIntByName(fs, 0, "trainingSensitivity", 245);
- learningRate = cvReadIntByName(fs, 0, "learningRate", 62);
- trainingLearningRate = cvReadIntByName(fs, 0, "trainingLearningRate", 255);
- trainingSteps = cvReadIntByName(fs, 0, "trainingSteps", 55);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+ sensitivity = cvReadIntByName(fs, nullptr, "sensitivity", 75);
+ trainingSensitivity = cvReadIntByName(fs, nullptr, "trainingSensitivity", 245);
+ learningRate = cvReadIntByName(fs, nullptr, "learningRate", 62);
+ trainingLearningRate = cvReadIntByName(fs, nullptr, "trainingLearningRate", 255);
+ trainingSteps = cvReadIntByName(fs, nullptr, "trainingSteps", 55);
showOutput = cvReadIntByName(fs, 0, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/LBAdaptiveSOM.h b/package_bgs/LBAdaptiveSOM.h
similarity index 55%
rename from package_bgs/lb/LBAdaptiveSOM.h
rename to package_bgs/LBAdaptiveSOM.h
index beaf77b..7671ae1 100644
--- a/package_bgs/lb/LBAdaptiveSOM.h
+++ b/package_bgs/LBAdaptiveSOM.h
@@ -16,41 +16,35 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "BGModelSom.h"
-
-#include "../IBGS.h"
+#include "lb/BGModelSom.h"
+#include "IBGS.h"
using namespace lb_library;
using namespace lb_library::AdaptiveSOM;
-class LBAdaptiveSOM : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- bool showOutput;
-
- BGModel* m_pBGModel;
- int sensitivity;
- int trainingSensitivity;
- int learningRate;
- int trainingLearningRate;
- int trainingSteps;
-
- cv::Mat img_foreground;
- cv::Mat img_background;
-
-public:
- LBAdaptiveSOM();
- ~LBAdaptiveSOM();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
- //void finish(void);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
+ namespace algorithms
+ {
+ class LBAdaptiveSOM : public IBGS
+ {
+ private:
+ BGModel* m_pBGModel;
+ int sensitivity;
+ int trainingSensitivity;
+ int learningRate;
+ int trainingLearningRate;
+ int trainingSteps;
+
+ public:
+ LBAdaptiveSOM();
+ ~LBAdaptiveSOM();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/lb/LBFuzzyAdaptiveSOM.cpp b/package_bgs/LBFuzzyAdaptiveSOM.cpp
similarity index 59%
rename from package_bgs/lb/LBFuzzyAdaptiveSOM.cpp
rename to package_bgs/LBFuzzyAdaptiveSOM.cpp
index 4ef8560..73df1d7 100644
--- a/package_bgs/lb/LBFuzzyAdaptiveSOM.cpp
+++ b/package_bgs/LBFuzzyAdaptiveSOM.cpp
@@ -16,10 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "LBFuzzyAdaptiveSOM.h"
-LBFuzzyAdaptiveSOM::LBFuzzyAdaptiveSOM() : firstTime(true), showOutput(true),
+using namespace bgslibrary::algorithms;
+
+LBFuzzyAdaptiveSOM::LBFuzzyAdaptiveSOM() :
sensitivity(90), trainingSensitivity(240), learningRate(38), trainingLearningRate(255), trainingSteps(81)
{
std::cout << "LBFuzzyAdaptiveSOM()" << std::endl;
+ setup("./config/LBFuzzyAdaptiveSOM.xml");
}
LBFuzzyAdaptiveSOM::~LBFuzzyAdaptiveSOM()
@@ -30,64 +33,55 @@ LBFuzzyAdaptiveSOM::~LBFuzzyAdaptiveSOM()
void LBFuzzyAdaptiveSOM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- loadConfig();
-
IplImage *frame = new IplImage(img_input);
-
- if(firstTime)
- {
- saveConfig();
+ if (firstTime)
+ {
int w = cvGetSize(frame).width;
int h = cvGetSize(frame).height;
- m_pBGModel = new BGModelFuzzySom(w,h);
+ m_pBGModel = new BGModelFuzzySom(w, h);
m_pBGModel->InitModel(frame);
}
-
- m_pBGModel->setBGModelParameter(0,sensitivity);
- m_pBGModel->setBGModelParameter(1,trainingSensitivity);
- m_pBGModel->setBGModelParameter(2,learningRate);
- m_pBGModel->setBGModelParameter(3,trainingLearningRate);
- m_pBGModel->setBGModelParameter(5,trainingSteps);
+
+ m_pBGModel->setBGModelParameter(0, sensitivity);
+ m_pBGModel->setBGModelParameter(1, trainingSensitivity);
+ m_pBGModel->setBGModelParameter(2, learningRate);
+ m_pBGModel->setBGModelParameter(3, trainingLearningRate);
+ m_pBGModel->setBGModelParameter(5, trainingSteps);
m_pBGModel->UpdateModel(frame);
- img_foreground = cv::Mat(m_pBGModel->GetFG());
- img_background = cv::Mat(m_pBGModel->GetBG());
-
- if(showOutput)
+ img_foreground = cv::cvarrToMat(m_pBGModel->GetFG());
+ img_background = cv::cvarrToMat(m_pBGModel->GetBG());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cv::imshow("FSOM Mask", img_foreground);
cv::imshow("FSOM Model", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
-
+
delete frame;
-
+
firstTime = false;
}
-//void LBFuzzyAdaptiveSOM::finish(void)
-//{
-// //delete m_pBGModel;
-//}
-
void LBFuzzyAdaptiveSOM::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBFuzzyAdaptiveSOM.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "sensitivity", sensitivity);
cvWriteInt(fs, "trainingSensitivity", trainingSensitivity);
cvWriteInt(fs, "learningRate", learningRate);
cvWriteInt(fs, "trainingLearningRate", trainingLearningRate);
cvWriteInt(fs, "trainingSteps", trainingSteps);
-
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
@@ -95,15 +89,14 @@ void LBFuzzyAdaptiveSOM::saveConfig()
void LBFuzzyAdaptiveSOM::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBFuzzyAdaptiveSOM.xml", 0, CV_STORAGE_READ);
-
- sensitivity = cvReadIntByName(fs, 0, "sensitivity", 90);
- trainingSensitivity = cvReadIntByName(fs, 0, "trainingSensitivity", 240);
- learningRate = cvReadIntByName(fs, 0, "learningRate", 38);
- trainingLearningRate = cvReadIntByName(fs, 0, "trainingLearningRate", 255);
- trainingSteps = cvReadIntByName(fs, 0, "trainingSteps", 81);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ sensitivity = cvReadIntByName(fs, nullptr, "sensitivity", 90);
+ trainingSensitivity = cvReadIntByName(fs, nullptr, "trainingSensitivity", 240);
+ learningRate = cvReadIntByName(fs, nullptr, "learningRate", 38);
+ trainingLearningRate = cvReadIntByName(fs, nullptr, "trainingLearningRate", 255);
+ trainingSteps = cvReadIntByName(fs, nullptr, "trainingSteps", 81);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/LBFuzzyAdaptiveSOM.h b/package_bgs/LBFuzzyAdaptiveSOM.h
similarity index 55%
rename from package_bgs/lb/LBFuzzyAdaptiveSOM.h
rename to package_bgs/LBFuzzyAdaptiveSOM.h
index 9c11d75..6a4a85c 100644
--- a/package_bgs/lb/LBFuzzyAdaptiveSOM.h
+++ b/package_bgs/LBFuzzyAdaptiveSOM.h
@@ -16,41 +16,35 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "BGModelFuzzySom.h"
-
-#include "../IBGS.h"
+#include "IBGS.h"
+#include "lb/BGModelFuzzySom.h"
using namespace lb_library;
using namespace lb_library::FuzzyAdaptiveSOM;
-class LBFuzzyAdaptiveSOM : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- bool showOutput;
-
- BGModel* m_pBGModel;
- int sensitivity;
- int trainingSensitivity;
- int learningRate;
- int trainingLearningRate;
- int trainingSteps;
-
- cv::Mat img_foreground;
- cv::Mat img_background;
-
-public:
- LBFuzzyAdaptiveSOM();
- ~LBFuzzyAdaptiveSOM();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
- //void finish(void);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
+ namespace algorithms
+ {
+ class LBFuzzyAdaptiveSOM : public IBGS
+ {
+ private:
+ BGModel* m_pBGModel;
+ int sensitivity;
+ int trainingSensitivity;
+ int learningRate;
+ int trainingLearningRate;
+ int trainingSteps;
+
+ public:
+ LBFuzzyAdaptiveSOM();
+ ~LBFuzzyAdaptiveSOM();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/lb/LBFuzzyGaussian.cpp b/package_bgs/LBFuzzyGaussian.cpp
similarity index 59%
rename from package_bgs/lb/LBFuzzyGaussian.cpp
rename to package_bgs/LBFuzzyGaussian.cpp
index dc257bf..b161026 100644
--- a/package_bgs/lb/LBFuzzyGaussian.cpp
+++ b/package_bgs/LBFuzzyGaussian.cpp
@@ -16,9 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "LBFuzzyGaussian.h"
-LBFuzzyGaussian::LBFuzzyGaussian() : firstTime(true), showOutput(true), sensitivity(72), bgThreshold(162), learningRate(49), noiseVariance(195)
+using namespace bgslibrary::algorithms;
+
+LBFuzzyGaussian::LBFuzzyGaussian() :
+ sensitivity(72), bgThreshold(162), learningRate(49), noiseVariance(195)
{
std::cout << "LBFuzzyGaussian()" << std::endl;
+ setup("./config/LBFuzzyGaussian.xml");
}
LBFuzzyGaussian::~LBFuzzyGaussian()
@@ -29,62 +33,53 @@ LBFuzzyGaussian::~LBFuzzyGaussian()
void LBFuzzyGaussian::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- loadConfig();
-
IplImage *frame = new IplImage(img_input);
-
- if(firstTime)
- {
- saveConfig();
+ if (firstTime)
+ {
int w = cvGetSize(frame).width;
int h = cvGetSize(frame).height;
- m_pBGModel = new BGModelFuzzyGauss(w,h);
+ m_pBGModel = new BGModelFuzzyGauss(w, h);
m_pBGModel->InitModel(frame);
}
-
- m_pBGModel->setBGModelParameter(0,sensitivity);
- m_pBGModel->setBGModelParameter(1,bgThreshold);
- m_pBGModel->setBGModelParameter(2,learningRate);
- m_pBGModel->setBGModelParameter(3,noiseVariance);
+
+ m_pBGModel->setBGModelParameter(0, sensitivity);
+ m_pBGModel->setBGModelParameter(1, bgThreshold);
+ m_pBGModel->setBGModelParameter(2, learningRate);
+ m_pBGModel->setBGModelParameter(3, noiseVariance);
m_pBGModel->UpdateModel(frame);
- img_foreground = cv::Mat(m_pBGModel->GetFG());
- img_background = cv::Mat(m_pBGModel->GetBG());
-
- if(showOutput)
+ img_foreground = cv::cvarrToMat(m_pBGModel->GetFG());
+ img_background = cv::cvarrToMat(m_pBGModel->GetBG());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cv::imshow("FG Mask", img_foreground);
cv::imshow("FG Model", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
-
+
delete frame;
-
+
firstTime = false;
}
-//void LBFuzzyGaussian::finish(void)
-//{
-// delete m_pBGModel;
-//}
-
void LBFuzzyGaussian::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBFuzzyGaussian.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "sensitivity", sensitivity);
cvWriteInt(fs, "bgThreshold", bgThreshold);
cvWriteInt(fs, "learningRate", learningRate);
cvWriteInt(fs, "noiseVariance", noiseVariance);
-
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
@@ -92,14 +87,13 @@ void LBFuzzyGaussian::saveConfig()
void LBFuzzyGaussian::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBFuzzyGaussian.xml", 0, CV_STORAGE_READ);
-
- sensitivity = cvReadIntByName(fs, 0, "sensitivity", 72);
- bgThreshold = cvReadIntByName(fs, 0, "bgThreshold", 162);
- learningRate = cvReadIntByName(fs, 0, "learningRate", 49);
- noiseVariance = cvReadIntByName(fs, 0, "noiseVariance", 195);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ sensitivity = cvReadIntByName(fs, nullptr, "sensitivity", 72);
+ bgThreshold = cvReadIntByName(fs, nullptr, "bgThreshold", 162);
+ learningRate = cvReadIntByName(fs, nullptr, "learningRate", 49);
+ noiseVariance = cvReadIntByName(fs, nullptr, "noiseVariance", 195);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/lb/LBFuzzyGaussian.h b/package_bgs/LBFuzzyGaussian.h
similarity index 56%
rename from package_bgs/lb/LBFuzzyGaussian.h
rename to package_bgs/LBFuzzyGaussian.h
index f76156e..53c2667 100644
--- a/package_bgs/lb/LBFuzzyGaussian.h
+++ b/package_bgs/LBFuzzyGaussian.h
@@ -16,40 +16,34 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "BGModelFuzzyGauss.h"
-
-#include "../IBGS.h"
+#include "IBGS.h"
+#include "lb/BGModelFuzzyGauss.h"
using namespace lb_library;
using namespace lb_library::FuzzyGaussian;
-class LBFuzzyGaussian : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- bool showOutput;
-
- BGModel* m_pBGModel;
- int sensitivity;
- int bgThreshold;
- int learningRate;
- int noiseVariance;
-
- cv::Mat img_foreground;
- cv::Mat img_background;
-
-public:
- LBFuzzyGaussian();
- ~LBFuzzyGaussian();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
- //void finish(void);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
+ namespace algorithms
+ {
+ class LBFuzzyGaussian : public IBGS
+ {
+ private:
+ BGModel* m_pBGModel;
+ int sensitivity;
+ int bgThreshold;
+ int learningRate;
+ int noiseVariance;
+
+ public:
+ LBFuzzyGaussian();
+ ~LBFuzzyGaussian();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/lb/LBMixtureOfGaussians.cpp b/package_bgs/LBMixtureOfGaussians.cpp
similarity index 59%
rename from package_bgs/lb/LBMixtureOfGaussians.cpp
rename to package_bgs/LBMixtureOfGaussians.cpp
index 8d235c5..6cd9c91 100644
--- a/package_bgs/lb/LBMixtureOfGaussians.cpp
+++ b/package_bgs/LBMixtureOfGaussians.cpp
@@ -16,9 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "LBMixtureOfGaussians.h"
-LBMixtureOfGaussians::LBMixtureOfGaussians() : firstTime(true), showOutput(true), sensitivity(81), bgThreshold(83), learningRate(59), noiseVariance(206)
+using namespace bgslibrary::algorithms;
+
+LBMixtureOfGaussians::LBMixtureOfGaussians() :
+ sensitivity(81), bgThreshold(83), learningRate(59), noiseVariance(206)
{
std::cout << "LBMixtureOfGaussians()" << std::endl;
+ setup("./config/LBMixtureOfGaussians.xml");
}
LBMixtureOfGaussians::~LBMixtureOfGaussians()
@@ -29,62 +33,53 @@ LBMixtureOfGaussians::~LBMixtureOfGaussians()
void LBMixtureOfGaussians::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- loadConfig();
-
IplImage *frame = new IplImage(img_input);
-
- if(firstTime)
- {
- saveConfig();
+ if (firstTime)
+ {
int w = cvGetSize(frame).width;
int h = cvGetSize(frame).height;
- m_pBGModel = new BGModelMog(w,h);
+ m_pBGModel = new BGModelMog(w, h);
m_pBGModel->InitModel(frame);
}
-
- m_pBGModel->setBGModelParameter(0,sensitivity);
- m_pBGModel->setBGModelParameter(1,bgThreshold);
- m_pBGModel->setBGModelParameter(2,learningRate);
- m_pBGModel->setBGModelParameter(3,noiseVariance);
+
+ m_pBGModel->setBGModelParameter(0, sensitivity);
+ m_pBGModel->setBGModelParameter(1, bgThreshold);
+ m_pBGModel->setBGModelParameter(2, learningRate);
+ m_pBGModel->setBGModelParameter(3, noiseVariance);
m_pBGModel->UpdateModel(frame);
- img_foreground = cv::Mat(m_pBGModel->GetFG());
- img_background = cv::Mat(m_pBGModel->GetBG());
-
- if(showOutput)
+ img_foreground = cv::cvarrToMat(m_pBGModel->GetFG());
+ img_background = cv::cvarrToMat(m_pBGModel->GetBG());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cv::imshow("MOG Mask", img_foreground);
cv::imshow("MOG Model", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
-
+
delete frame;
-
+
firstTime = false;
}
-//void LBMixtureOfGaussians::finish(void)
-//{
-// delete m_pBGModel;
-//}
-
void LBMixtureOfGaussians::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBMixtureOfGaussians.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "sensitivity", sensitivity);
cvWriteInt(fs, "bgThreshold", bgThreshold);
cvWriteInt(fs, "learningRate", learningRate);
cvWriteInt(fs, "noiseVariance", noiseVariance);
-
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
@@ -92,14 +87,13 @@ void LBMixtureOfGaussians::saveConfig()
void LBMixtureOfGaussians::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBMixtureOfGaussians.xml", 0, CV_STORAGE_READ);
-
- sensitivity = cvReadIntByName(fs, 0, "sensitivity", 81);
- bgThreshold = cvReadIntByName(fs, 0, "bgThreshold", 83);
- learningRate = cvReadIntByName(fs, 0, "learningRate", 59);
- noiseVariance = cvReadIntByName(fs, 0, "noiseVariance", 206);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ sensitivity = cvReadIntByName(fs, nullptr, "sensitivity", 81);
+ bgThreshold = cvReadIntByName(fs, nullptr, "bgThreshold", 83);
+ learningRate = cvReadIntByName(fs, nullptr, "learningRate", 59);
+ noiseVariance = cvReadIntByName(fs, nullptr, "noiseVariance", 206);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/LBMixtureOfGaussians.h b/package_bgs/LBMixtureOfGaussians.h
similarity index 56%
rename from package_bgs/lb/LBMixtureOfGaussians.h
rename to package_bgs/LBMixtureOfGaussians.h
index 3b1a96d..8d4cb56 100644
--- a/package_bgs/lb/LBMixtureOfGaussians.h
+++ b/package_bgs/LBMixtureOfGaussians.h
@@ -16,40 +16,35 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "BGModelMog.h"
-
-#include "../IBGS.h"
+#include "IBGS.h"
+#include "lb/BGModelMog.h"
using namespace lb_library;
using namespace lb_library::MixtureOfGaussians;
-class LBMixtureOfGaussians : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- bool showOutput;
-
- BGModel* m_pBGModel;
- int sensitivity;
- int bgThreshold;
- int learningRate;
- int noiseVariance;
-
- cv::Mat img_foreground;
- cv::Mat img_background;
-
-public:
- LBMixtureOfGaussians();
- ~LBMixtureOfGaussians();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
- //void finish(void);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
+ namespace algorithms
+ {
+ class LBMixtureOfGaussians : public IBGS
+ {
+ private:
+ BGModel* m_pBGModel;
+ int sensitivity;
+ int bgThreshold;
+ int learningRate;
+ int noiseVariance;
+
+ public:
+ LBMixtureOfGaussians();
+ ~LBMixtureOfGaussians();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
+
diff --git a/package_bgs/ck/LbpMrf.cpp b/package_bgs/LBP_MRF.cpp
similarity index 57%
rename from package_bgs/ck/LbpMrf.cpp
rename to package_bgs/LBP_MRF.cpp
index f3d068c..b9e6bbe 100644
--- a/package_bgs/ck/LbpMrf.cpp
+++ b/package_bgs/LBP_MRF.cpp
@@ -18,35 +18,29 @@ Csaba, Kertész: Texture-Based Foreground Detection, International Journal of Si
Image Processing and Pattern Recognition (IJSIP), Vol. 4, No. 4, 2011.
*/
-#include "LbpMrf.h"
+#include "LBP_MRF.h"
-#include "MotionDetection.hpp"
+using namespace bgslibrary::algorithms;
-LbpMrf::LbpMrf() : firstTime(true), Detector(NULL), showOutput(true)
+LBP_MRF::LBP_MRF() :
+ Detector(nullptr)
{
- std::cout << "LbpMrf()" << std::endl;
+ std::cout << "LBP_MRF()" << std::endl;
+ setup("./config/LBP_MRF.xml");
Detector = new MotionDetection();
Detector->SetMode(MotionDetection::md_LBPHistograms);
}
-LbpMrf::~LbpMrf()
+LBP_MRF::~LBP_MRF()
{
- std::cout << "~LbpMrf()" << std::endl;
+ std::cout << "~LBP_MRF()" << std::endl;
delete Detector;
- Detector = NULL;
+ Detector = nullptr;
}
-void LbpMrf::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void LBP_MRF::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- {
- saveConfig();
- }
+ init(img_input, img_output, img_bgmodel);
IplImage TempImage(img_input);
MEImage InputImage(img_input.cols, img_input.rows, img_input.channels());
@@ -56,32 +50,35 @@ void LbpMrf::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img
Detector->DetectMotions(InputImage);
Detector->GetMotionsMask(OutputImage);
- img_output = (IplImage*)OutputImage.GetIplImage();
- bitwise_not(img_output, img_bgmodel);
+ img_foreground = cv::cvarrToMat((IplImage*)OutputImage.GetIplImage());
+ //bitwise_not(img_foreground, img_background);
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("LBP-MRF FG", img_foreground);
+#endif
- if(showOutput)
- {
- cv::imshow("LBP-MRF FG", img_output);
- cv::imshow("LBP-MRF BG", img_bgmodel);
- }
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
firstTime = false;
}
-void LbpMrf::saveConfig()
+void LBP_MRF::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LbpMrf.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
}
-void LbpMrf::loadConfig()
+void LBP_MRF::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LbpMrf.xml", 0, CV_STORAGE_READ);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/WeightedMovingMeanBGS.h b/package_bgs/LBP_MRF.h
similarity index 58%
rename from package_bgs/WeightedMovingMeanBGS.h
rename to package_bgs/LBP_MRF.h
index 6f72306..a6e5c05 100644
--- a/package_bgs/WeightedMovingMeanBGS.h
+++ b/package_bgs/LBP_MRF.h
@@ -16,32 +16,28 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
#include "IBGS.h"
+#include "LBP_MRF/MotionDetection.hpp"
-class WeightedMovingMeanBGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::Mat img_input_prev_1;
- cv::Mat img_input_prev_2;
- bool enableWeight;
- bool enableThreshold;
- int threshold;
- bool showOutput;
- bool showBackground;
-
-public:
- WeightedMovingMeanBGS();
- ~WeightedMovingMeanBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class LBP_MRF : public IBGS
+ {
+ private:
+ MotionDetection* Detector;
+ cv::Mat img_segmentation;
+
+ public:
+ LBP_MRF();
+ ~LBP_MRF();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/LBP_MRF/MEDefs.cpp b/package_bgs/LBP_MRF/MEDefs.cpp
new file mode 100644
index 0000000..95b8033
--- /dev/null
+++ b/package_bgs/LBP_MRF/MEDefs.cpp
@@ -0,0 +1,57 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/*
+ * This file is part of the AiBO+ project
+ *
+ * Copyright (C) 2005-2013 Csaba Kertész (csaba.kertesz@gmail.com)
+ *
+ * AiBO+ is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * AiBO+ is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 59 Temple Street #330, Boston, MA 02111-1307, USA.
+ *
+ */
+
+#include "MEDefs.hpp"
+
+#include <math.h>
+
+float MERound(float number)
+{
+ double FracPart = 0.0;
+ double IntPart = 0.0;
+ float Ret = 0.0;
+
+ FracPart = modf((double)number, &IntPart);
+ if (number >= 0)
+ {
+ Ret = (float)(FracPart >= 0.5 ? IntPart + 1 : IntPart);
+ }
+ else {
+ Ret = (float)(FracPart <= -0.5 ? IntPart - 1 : IntPart);
+ }
+ return Ret;
+}
diff --git a/package_bgs/ck/MEDefs.hpp b/package_bgs/LBP_MRF/MEDefs.hpp
similarity index 73%
rename from package_bgs/ck/MEDefs.hpp
rename to package_bgs/LBP_MRF/MEDefs.hpp
index d5bc246..a886ee9 100644
--- a/package_bgs/ck/MEDefs.hpp
+++ b/package_bgs/LBP_MRF/MEDefs.hpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/*
* This file is part of the AiBO+ project
*
@@ -18,16 +34,9 @@
* Foundation, Inc., 59 Temple Street #330, Boston, MA 02111-1307, USA.
*
*/
+#pragma once
-#ifndef MEDefs_hpp
-#define MEDefs_hpp
-
-/**
- * @addtogroup mindeye
- * @{
- */
-
-/// Pi value
+ /// Pi value
#ifndef ME_PI_VALUE
#define ME_PI_VALUE 3.14159265
#endif
@@ -79,5 +88,3 @@ const T& MEBound(const T& min, const T& val, const T& max)
float MERound(float number);
/** @} */
-
-#endif
diff --git a/package_bgs/ck/MEHistogram.cpp b/package_bgs/LBP_MRF/MEHistogram.cpp
similarity index 54%
rename from package_bgs/ck/MEHistogram.cpp
rename to package_bgs/LBP_MRF/MEHistogram.cpp
index 09a9672..17c77fd 100644
--- a/package_bgs/ck/MEHistogram.cpp
+++ b/package_bgs/LBP_MRF/MEHistogram.cpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/*
* This file is part of the AiBO+ project
*
@@ -45,7 +61,7 @@ MEHistogram::~MEHistogram()
void MEHistogram::Clear()
{
- memset(&HistogramData, 0, 256*sizeof(int));
+ memset(&HistogramData, 0, 256 * sizeof(int));
}
@@ -77,11 +93,11 @@ void MEHistogram::Calculate(MEImage& image, int channel, HistogramType mode)
unsigned char *ImageData = image.GetImageData();
int rowStart = 0;
- for (int i = image.GetHeight()-1; i >= 0; i--)
+ for (int i = image.GetHeight() - 1; i >= 0; i--)
{
- for (int i1 = (image.GetWidth()-1)*image.GetLayers()+Channel-1; i1 >= Channel-1; i1 -= image.GetLayers())
+ for (int i1 = (image.GetWidth() - 1)*image.GetLayers() + Channel - 1; i1 >= Channel - 1; i1 -= image.GetLayers())
{
- HistogramData[ImageData[rowStart+i1]]++;
+ HistogramData[ImageData[rowStart + i1]]++;
}
rowStart += image.GetRowWidth();
}
@@ -99,11 +115,11 @@ void MEHistogram::Calculate(MEImage& image, HistogramType mode)
int RowStart = 0;
int RowWidth = image.GetRowWidth();
- for (int i = image.GetHeight()-1; i >= 0; i--)
+ for (int i = image.GetHeight() - 1; i >= 0; i--)
{
- for (int i1 = image.GetWidth()*image.GetLayers()-1; i1 >= 0; i1--)
+ for (int i1 = image.GetWidth()*image.GetLayers() - 1; i1 >= 0; i1--)
{
- HistogramData[ImageData[RowStart+i1]]++;
+ HistogramData[ImageData[RowStart + i1]]++;
}
RowStart += RowWidth;
}
@@ -126,16 +142,16 @@ void MEHistogram::Calculate(MEImage& image, int channel, int x0, int y0, int x1,
// Compute the correct region coordinates and check them
X0 = X0 < 0 ? 0 : X0;
Y0 = Y0 < 0 ? 0 : Y0;
- X1 = X1 > image.GetWidth()-1 ? image.GetWidth()-1 : X1;
- Y1 = Y1 > image.GetHeight()-1 ? image.GetHeight()-1 : Y1;
+ X1 = X1 > image.GetWidth() - 1 ? image.GetWidth() - 1 : X1;
+ Y1 = Y1 > image.GetHeight() - 1 ? image.GetHeight() - 1 : Y1;
RowStart = Y0*image.GetRowWidth();
for (int i = Y1; i >= Y0; --i)
{
- for (int i1 = X1*image.GetLayers()+Channel-1; i1 >= X0*image.GetLayers()+Channel-1;
- i1 -= image.GetLayers())
+ for (int i1 = X1*image.GetLayers() + Channel - 1; i1 >= X0*image.GetLayers() + Channel - 1;
+ i1 -= image.GetLayers())
{
- HistogramData[ImageData[RowStart+i1]]++;
+ HistogramData[ImageData[RowStart + i1]]++;
}
RowStart += RowWidth;
}
@@ -242,70 +258,70 @@ bool MEHistogram::Stretch(StretchType mode)
switch (mode)
{
- case s_OwnMode:
- Percent = 20;
+ case s_OwnMode:
+ Percent = 20;
+ MinIndex = GetLowestLimitIndex(Percent);
+ MaxIndex = GetHighestLimitIndex(Percent);
+
+ while ((abs(MaxIndex - MinIndex) < 52) && (Percent > 1))
+ {
+ Percent = Percent / 2;
MinIndex = GetLowestLimitIndex(Percent);
MaxIndex = GetHighestLimitIndex(Percent);
- while ((abs(MaxIndex-MinIndex) < 52) && (Percent > 1))
+ // The calculation gives wrong answer back
+ if (MinIndex == 0 && MaxIndex == 255)
{
- Percent = Percent / 2;
- MinIndex = GetLowestLimitIndex(Percent);
- MaxIndex = GetHighestLimitIndex(Percent);
-
- // The calculation gives wrong answer back
- if (MinIndex == 0 && MaxIndex == 255)
- {
- MinIndex = 128;
- MaxIndex = 128;
- Ret = false;
- }
+ MinIndex = 128;
+ MaxIndex = 128;
+ Ret = false;
}
- break;
+ }
+ break;
- case s_GimpMode:
- Count = GetPowerAmount(0, 255);
- NewCount = 0;
+ case s_GimpMode:
+ Count = GetPowerAmount(0, 255);
+ NewCount = 0;
- for (int i = 0; i < 255; i++)
- {
- double Value = 0.0;
- double NextValue = 0.0;
+ for (int i = 0; i < 255; i++)
+ {
+ double Value = 0.0;
+ double NextValue = 0.0;
- Value = HistogramData[i];
- NextValue = HistogramData[i+1];
- NewCount += Value;
- Percentage = NewCount / Count;
- NextPercentage = (NewCount+NextValue) / Count;
+ Value = HistogramData[i];
+ NextValue = HistogramData[i + 1];
+ NewCount += Value;
+ Percentage = NewCount / Count;
+ NextPercentage = (NewCount + NextValue) / Count;
- if (fabs(Percentage-0.006) < fabs(NextPercentage-0.006))
- {
- MinIndex = i+1;
- break;
- }
- }
- NewCount = 0.0;
- for (int i = 255; i > 0; i--)
+ if (fabs(Percentage - 0.006) < fabs(NextPercentage - 0.006))
{
- double Value = 0.0;
- double NextValue = 0.0;
+ MinIndex = i + 1;
+ break;
+ }
+ }
+ NewCount = 0.0;
+ for (int i = 255; i > 0; i--)
+ {
+ double Value = 0.0;
+ double NextValue = 0.0;
- Value = HistogramData[i];
- NextValue = HistogramData[i-1];
- NewCount += Value;
- Percentage = NewCount / Count;
- NextPercentage = (NewCount+NextValue) / Count;
+ Value = HistogramData[i];
+ NextValue = HistogramData[i - 1];
+ NewCount += Value;
+ Percentage = NewCount / Count;
+ NextPercentage = (NewCount + NextValue) / Count;
- if (fabs(Percentage-0.006) < fabs(NextPercentage-0.006))
- {
- MaxIndex = i-1;
- break;
- }
+ if (fabs(Percentage - 0.006) < fabs(NextPercentage - 0.006))
+ {
+ MaxIndex = i - 1;
+ break;
}
- break;
+ }
+ break;
- default:
- break;
+ default:
+ break;
}
if (MaxIndex <= MinIndex)
@@ -314,8 +330,8 @@ bool MEHistogram::Stretch(StretchType mode)
MaxIndex = 255;
Ret = false;
}
- if (MaxIndex-MinIndex <= 10 ||
- (MaxIndex-MinIndex <= 20 && (float)GetPowerAmount(MinIndex, MaxIndex) / GetPowerAmount(0, 255) < 0.20))
+ if (MaxIndex - MinIndex <= 10 ||
+ (MaxIndex - MinIndex <= 20 && (float)GetPowerAmount(MinIndex, MaxIndex) / GetPowerAmount(0, 255) < 0.20))
{
MinIndex = 0;
MaxIndex = 255;
@@ -327,7 +343,7 @@ bool MEHistogram::Stretch(StretchType mode)
for (int i = 0; i < 256; ++i)
{
- TransformedHistogram[i] = (unsigned char)MEBound(0, 255*(i-MinIndex) / (MaxIndex-MinIndex), 255);
+ TransformedHistogram[i] = (unsigned char)MEBound(0, 255 * (i - MinIndex) / (MaxIndex - MinIndex), 255);
}
for (int i = 0; i < 256; ++i)
{
@@ -371,7 +387,7 @@ void MEHistogramTransform::HistogramStretch(MEImage& image, TransformType time_m
for (int l = 1; l < image.GetLayers(); l++)
{
- RedChannel.Calculate(image, l+1, MEHistogram::h_Add);
+ RedChannel.Calculate(image, l + 1, MEHistogram::h_Add);
}
RedChannel.Stretch(StretchMode);
if (time_mode == t_Discrete && !DiscreteStretchingDone)
@@ -383,45 +399,46 @@ void MEHistogramTransform::HistogramStretch(MEImage& image, TransformType time_m
int RowStart = 0;
int RowWidth = image.GetRowWidth();
- for (int i = image.GetHeight()-1; i >= 0; i--)
+ for (int i = image.GetHeight() - 1; i >= 0; i--)
{
- for (int i1 = image.GetWidth()*image.GetLayers()-1; i1 >= 0; i1--)
+ for (int i1 = image.GetWidth()*image.GetLayers() - 1; i1 >= 0; i1--)
{
- ImageData[RowStart+i1] = RedChannel.HistogramData[ImageData[RowStart+i1]];
+ ImageData[RowStart + i1] = RedChannel.HistogramData[ImageData[RowStart + i1]];
}
RowStart += RowWidth;
}
- } else
- if (ChannelMode == p_SeparateChannels)
- {
- if (time_mode == t_Continuous || (time_mode == t_Discrete && !DiscreteStretchingDone))
+ }
+ else
+ if (ChannelMode == p_SeparateChannels)
{
- RedChannel.Calculate(image, 1, MEHistogram::h_Overwrite);
- GreenChannel.Calculate(image, 2, MEHistogram::h_Overwrite);
- BlueChannel.Calculate(image, 3, MEHistogram::h_Overwrite);
- RedChannel.Stretch(StretchMode);
- GreenChannel.Stretch(StretchMode);
- BlueChannel.Stretch(StretchMode);
- if (time_mode == t_Discrete && !DiscreteStretchingDone)
+ if (time_mode == t_Continuous || (time_mode == t_Discrete && !DiscreteStretchingDone))
{
- DiscreteStretchingDone = true;
+ RedChannel.Calculate(image, 1, MEHistogram::h_Overwrite);
+ GreenChannel.Calculate(image, 2, MEHistogram::h_Overwrite);
+ BlueChannel.Calculate(image, 3, MEHistogram::h_Overwrite);
+ RedChannel.Stretch(StretchMode);
+ GreenChannel.Stretch(StretchMode);
+ BlueChannel.Stretch(StretchMode);
+ if (time_mode == t_Discrete && !DiscreteStretchingDone)
+ {
+ DiscreteStretchingDone = true;
+ }
}
- }
- unsigned char *ImageData = image.GetImageData();
- int RowStart = 0;
- int RowWidth = image.GetRowWidth();
+ unsigned char *ImageData = image.GetImageData();
+ int RowStart = 0;
+ int RowWidth = image.GetRowWidth();
- for (int i = image.GetHeight()-1; i >= 0; i--)
- {
- for (int i1 = image.GetWidth()*image.GetLayers()-3; i1 >= 0; i1 -= 3)
+ for (int i = image.GetHeight() - 1; i >= 0; i--)
{
- ImageData[RowStart+i1] = RedChannel.HistogramData[ImageData[RowStart+i1]];
- ImageData[RowStart+i1+1] = GreenChannel.HistogramData[ImageData[RowStart+i1+1]];
- ImageData[RowStart+i1+2] = BlueChannel.HistogramData[ImageData[RowStart+i1+2]];
+ for (int i1 = image.GetWidth()*image.GetLayers() - 3; i1 >= 0; i1 -= 3)
+ {
+ ImageData[RowStart + i1] = RedChannel.HistogramData[ImageData[RowStart + i1]];
+ ImageData[RowStart + i1 + 1] = GreenChannel.HistogramData[ImageData[RowStart + i1 + 1]];
+ ImageData[RowStart + i1 + 2] = BlueChannel.HistogramData[ImageData[RowStart + i1 + 2]];
+ }
+ RowStart += RowWidth;
}
- RowStart += RowWidth;
}
- }
}
@@ -433,72 +450,72 @@ void MEHistogramTransform::HistogramEqualize(MEImage& image)
switch (image.GetLayers())
{
- case 1:
- // Grayscale image
- cvDest8bitImg = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
- cvEqualizeHist((IplImage*)image.GetIplImage(), cvDest8bitImg);
- image.SetIplImage((void*)cvDest8bitImg);
- cvReleaseImage(&cvDest8bitImg);
- break;
-
- case 3:
- // RGB image
- cvDestImg = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 3);
- IplImage *cvR, *cvG, *cvB;
-
- cvR = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
- cvG = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
- cvB = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
-
- cvSplit((IplImage*)image.GetIplImage(), cvR, cvG, cvB, NULL);
- cvEqualizeHist(cvR, cvR);
- cvEqualizeHist(cvG, cvG);
- cvEqualizeHist(cvB, cvB);
- cvMerge(cvR, cvG, cvB, NULL, cvDestImg);
-
- image.SetIplImage((void*)cvDestImg);
- cvReleaseImage(&cvR);
- cvReleaseImage(&cvG);
- cvReleaseImage(&cvB);
- cvReleaseImage(&cvDestImg);
- break;
-
- default:
- break;
+ case 1:
+ // Grayscale image
+ cvDest8bitImg = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
+ cvEqualizeHist((IplImage*)image.GetIplImage(), cvDest8bitImg);
+ image.SetIplImage((void*)cvDest8bitImg);
+ cvReleaseImage(&cvDest8bitImg);
+ break;
+
+ case 3:
+ // RGB image
+ cvDestImg = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 3);
+ IplImage *cvR, *cvG, *cvB;
+
+ cvR = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
+ cvG = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
+ cvB = cvCreateImage(cvSize(image.GetWidth(), image.GetHeight()), 8, 1);
+
+ cvSplit((IplImage*)image.GetIplImage(), cvR, cvG, cvB, NULL);
+ cvEqualizeHist(cvR, cvR);
+ cvEqualizeHist(cvG, cvG);
+ cvEqualizeHist(cvB, cvB);
+ cvMerge(cvR, cvG, cvB, NULL, cvDestImg);
+
+ image.SetIplImage((void*)cvDestImg);
+ cvReleaseImage(&cvR);
+ cvReleaseImage(&cvG);
+ cvReleaseImage(&cvB);
+ cvReleaseImage(&cvDestImg);
+ break;
+
+ default:
+ break;
}
}
void MEHistogramTransform::SetStretchProcessingMode(ProcessingType new_channel_mode,
- MEHistogram::StretchType new_stretch_mode)
+ MEHistogram::StretchType new_stretch_mode)
{
DiscreteStretchingDone = false;
- switch(new_channel_mode)
+ switch (new_channel_mode)
{
- case p_SeparateChannels:
- ChannelMode = new_channel_mode;
- break;
+ case p_SeparateChannels:
+ ChannelMode = new_channel_mode;
+ break;
- case p_Average:
- ChannelMode = new_channel_mode;
- break;
+ case p_Average:
+ ChannelMode = new_channel_mode;
+ break;
- default:
- break;
+ default:
+ break;
}
- switch(new_stretch_mode)
+ switch (new_stretch_mode)
{
- case MEHistogram::s_OwnMode:
- StretchMode = new_stretch_mode;
- break;
+ case MEHistogram::s_OwnMode:
+ StretchMode = new_stretch_mode;
+ break;
- case MEHistogram::s_GimpMode:
- StretchMode = new_stretch_mode;
- break;
+ case MEHistogram::s_GimpMode:
+ StretchMode = new_stretch_mode;
+ break;
- default:
- break;
+ default:
+ break;
}
}
diff --git a/package_bgs/ck/MEHistogram.hpp b/package_bgs/LBP_MRF/MEHistogram.hpp
similarity index 93%
rename from package_bgs/ck/MEHistogram.hpp
rename to package_bgs/LBP_MRF/MEHistogram.hpp
index 5b2b47f..0b2fb0d 100644
--- a/package_bgs/ck/MEHistogram.hpp
+++ b/package_bgs/LBP_MRF/MEHistogram.hpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/*
* This file is part of the AiBO+ project
*
@@ -18,14 +34,12 @@
* Foundation, Inc., 59 Temple Street #330, Boston, MA 02111-1307, USA.
*
*/
+#pragma once
-#ifndef MEHistogram_hpp
-#define MEHistogram_hpp
-
-/**
- * @addtogroup mindeye
- * @{
- */
+ /**
+ * @addtogroup mindeye
+ * @{
+ */
class MEImage;
@@ -344,5 +358,3 @@ private:
};
/** @} */
-
-#endif
diff --git a/package_bgs/ck/MEImage.cpp b/package_bgs/LBP_MRF/MEImage.cpp
similarity index 50%
rename from package_bgs/ck/MEImage.cpp
rename to package_bgs/LBP_MRF/MEImage.cpp
index 7373834..b01d494 100644
--- a/package_bgs/ck/MEImage.cpp
+++ b/package_bgs/LBP_MRF/MEImage.cpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/*
* This file is part of the AiBO+ project
*
@@ -30,17 +46,17 @@
cvReleaseImage((IplImage**)&image_ptr); \
image_ptr = NULL;
-// RGB to YUV transform
+ // RGB to YUV transform
const float RGBtoYUVMatrix[3][3] =
- {{ 0.299, 0.587, 0.114 },
- { -0.147, -0.289, 0.436 },
- { 0.615, -0.515, -0.100 }};
+{ { 0.299, 0.587, 0.114 },
+ { -0.147, -0.289, 0.436 },
+ { 0.615, -0.515, -0.100 } };
// RGB to YIQ transform
const float RGBtoYIQMatrix[3][3] =
- {{ 0.299, 0.587, 0.114 },
- { 0.596, -0.274, -0.322 },
- { 0.212, -0.523, 0.311 }};
+{ { 0.299, 0.587, 0.114 },
+ { 0.596, -0.274, -0.322 },
+ { 0.212, -0.523, 0.311 } };
MEImage::MEImage(int width, int height, int layers) : cvImg(NULL)
{
@@ -74,15 +90,15 @@ void MEImage::GetLayer(MEImage& new_layer, int layer_number) const
int LayerNumber = layer_number;
if ((new_layer.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width) ||
- (new_layer.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height) ||
- (new_layer.GetLayers() != 1))
+ (new_layer.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height) ||
+ (new_layer.GetLayers() != 1))
{
new_layer.Realloc(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height, 1);
}
if (ME_CAST_TO_IPLIMAGE(cvImg)->nChannels < LayerNumber)
{
printf("The given layer number is too large (%d > %d)\n",
- LayerNumber, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ LayerNumber, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
LayerNumber = ME_CAST_TO_IPLIMAGE(cvImg)->nChannels;
}
@@ -103,17 +119,17 @@ void MEImage::SetLayer(MEImage& layer, int layer_number)
int LayerNumber = layer_number;
if (layer.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- layer.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height)
+ layer.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height)
{
printf("The dimensions of the layer and "
- "destination image is different (%dx%d <> %dx%d)\n",
- layer.GetWidth(), layer.GetHeight(), ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height);
+ "destination image is different (%dx%d <> %dx%d)\n",
+ layer.GetWidth(), layer.GetHeight(), ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height);
return;
}
if (ME_CAST_TO_IPLIMAGE(cvImg)->nChannels < LayerNumber)
{
printf("The given layer number is too large (%d > %d)\n",
- LayerNumber, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ LayerNumber, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
LayerNumber = ME_CAST_TO_IPLIMAGE(cvImg)->nChannels;
}
if (LayerNumber <= 0)
@@ -124,7 +140,7 @@ void MEImage::SetLayer(MEImage& layer, int layer_number)
if (layer.GetLayers() != 1)
{
printf("The layer image has not one color channel (1 != %d)\n",
- layer.GetLayers());
+ layer.GetLayers());
return;
}
cvSetImageCOI(ME_CAST_TO_IPLIMAGE(cvImg), LayerNumber);
@@ -223,7 +239,7 @@ void MEImage::SetData(unsigned char* image_data, int width, int height, int chan
{
_Init(width, height, channels);
- for (int y = height-1; y >= 0; --y)
+ for (int y = height - 1; y >= 0; --y)
{
int Start = GetRowWidth()*y;
int Start2 = width*channels*y;
@@ -235,7 +251,7 @@ void MEImage::SetData(unsigned char* image_data, int width, int height, int chan
float MEImage::GetRatio() const
{
- return ME_CAST_TO_IPLIMAGE(cvImg) ? (float)ME_CAST_TO_IPLIMAGE(cvImg)->height/(float)ME_CAST_TO_IPLIMAGE(cvImg)->width : 0.0;
+ return ME_CAST_TO_IPLIMAGE(cvImg) ? (float)ME_CAST_TO_IPLIMAGE(cvImg)->height / (float)ME_CAST_TO_IPLIMAGE(cvImg)->width : 0.0;
}
@@ -289,7 +305,7 @@ void MEImage::ResizeScaleY(int new_height)
printf("Invalid new height: %d < 1\n", new_height);
return;
}
- Resize((int)((float)new_height*1/GetRatio()), new_height);
+ Resize((int)((float)new_height * 1 / GetRatio()), new_height);
}
@@ -322,19 +338,19 @@ void MEImage::Crop(int x1, int y1, int x2, int y2)
NewY2 = (NewY2 < 0) ? 0 : NewY2;
NewY2 = (NewY2 > ME_CAST_TO_IPLIMAGE(cvImg)->height) ? ME_CAST_TO_IPLIMAGE(cvImg)->height : NewY2;
- if ((NewX2-NewX1) <= 0)
+ if ((NewX2 - NewX1) <= 0)
{
- printf("Invalid new width: %d <= 0\n", NewX2-NewX1);
+ printf("Invalid new width: %d <= 0\n", NewX2 - NewX1);
return;
}
- if ((NewY2-NewY1) <= 0)
+ if ((NewY2 - NewY1) <= 0)
{
- printf("Invalid new height: %d <= 0\n", NewY2-NewY1);
+ printf("Invalid new height: %d <= 0\n", NewY2 - NewY1);
return;
}
- IplImage* TempImg = cvCreateImage(cvSize(NewX2-NewX1, NewY2-NewY1), 8, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ IplImage* TempImg = cvCreateImage(cvSize(NewX2 - NewX1, NewY2 - NewY1), 8, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvSetImageROI(ME_CAST_TO_IPLIMAGE(cvImg), cvRect(NewX1, NewY1, NewX2-NewX1, NewY2-NewY1));
+ cvSetImageROI(ME_CAST_TO_IPLIMAGE(cvImg), cvRect(NewX1, NewY1, NewX2 - NewX1, NewY2 - NewY1));
cvCopy(ME_CAST_TO_IPLIMAGE(cvImg), TempImg);
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
@@ -367,13 +383,13 @@ void MEImage::CopyImageInside(int x, int y, MEImage& source_image)
NewY = 0;
if (NewY > ME_CAST_TO_IPLIMAGE(cvImg)->height)
NewY = ME_CAST_TO_IPLIMAGE(cvImg)->height;
- if (NewX+PasteLengthX > ME_CAST_TO_IPLIMAGE(cvImg)->width)
- PasteLengthX = ME_CAST_TO_IPLIMAGE(cvImg)->width-NewX;
- if (NewY+PasteLengthY > ME_CAST_TO_IPLIMAGE(cvImg)->height)
- PasteLengthY = ME_CAST_TO_IPLIMAGE(cvImg)->height-NewY;
+ if (NewX + PasteLengthX > ME_CAST_TO_IPLIMAGE(cvImg)->width)
+ PasteLengthX = ME_CAST_TO_IPLIMAGE(cvImg)->width - NewX;
+ if (NewY + PasteLengthY > ME_CAST_TO_IPLIMAGE(cvImg)->height)
+ PasteLengthY = ME_CAST_TO_IPLIMAGE(cvImg)->height - NewY;
if (PasteLengthX != source_image.GetWidth() ||
- PasteLengthY != source_image.GetHeight())
+ PasteLengthY != source_image.GetHeight())
{
source_image.Resize(PasteLengthX, PasteLengthY);
}
@@ -386,8 +402,8 @@ void MEImage::CopyImageInside(int x, int y, MEImage& source_image)
void MEImage::Erode(int iterations)
{
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height),
- 8, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->height),
+ 8, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
cvErode(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, NULL, iterations);
ME_RELEASE_IPLIMAGE(cvImg);
@@ -398,8 +414,8 @@ void MEImage::Erode(int iterations)
void MEImage::Dilate(int iterations)
{
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height),
- 8, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->height),
+ 8, ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
cvDilate(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, NULL, iterations);
ME_RELEASE_IPLIMAGE(cvImg);
@@ -416,22 +432,22 @@ void MEImage::Smooth()
void MEImage::SmoothAdvanced(SmoothType filtermode, int filtersize)
{
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
switch (filtermode)
{
- case s_Blur:
- cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_BLUR, filtersize, filtersize, 0);
- break;
- case s_Median:
- cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_MEDIAN, filtersize, 0, 0);
- break;
- case s_Gaussian:
- cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_GAUSSIAN, filtersize, filtersize, 0);
- break;
- default:
- cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_MEDIAN, filtersize, 0, 0);
- break;
+ case s_Blur:
+ cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_BLUR, filtersize, filtersize, 0);
+ break;
+ case s_Median:
+ cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_MEDIAN, filtersize, 0, 0);
+ break;
+ case s_Gaussian:
+ cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_GAUSSIAN, filtersize, filtersize, 0);
+ break;
+ default:
+ cvSmooth(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_MEDIAN, filtersize, 0, 0);
+ break;
}
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
@@ -446,7 +462,7 @@ void MEImage::Canny()
}
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
cvCanny(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, 800, 1100, 5);
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
@@ -460,8 +476,8 @@ void MEImage::Laplace()
ConvertToGrayscale(g_OpenCV);
}
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height),
- IPL_DEPTH_16S, 1);
+ ME_CAST_TO_IPLIMAGE(cvImg)->height),
+ IPL_DEPTH_16S, 1);
cvLaplace(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, 3);
cvConvertScale(TempImg, ME_CAST_TO_IPLIMAGE(cvImg), 1, 0);
ME_RELEASE_IPLIMAGE(cvImg);
@@ -482,7 +498,7 @@ void MEImage::Quantize(int levels)
}
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height-1; i >= 0; --i)
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; i >= 0; --i)
{
ImageData[i] = ImageData[i] / (256 / levels)*(256 / levels);
}
@@ -503,7 +519,7 @@ void MEImage::Threshold(int threshold_limit)
}
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height-1; i >= 0; --i)
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; i >= 0; --i)
{
if (ImageData[i] < threshold_limit)
{
@@ -520,9 +536,9 @@ void MEImage::AdaptiveThreshold()
ConvertToGrayscale(g_OpenCV);
}
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
cvAdaptiveThreshold(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, 25,
- CV_ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY, 7, -7);
+ CV_ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY, 7, -7);
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
}
@@ -531,7 +547,7 @@ void MEImage::AdaptiveThreshold()
void MEImage::ThresholdByMask(MEImage& mask_image)
{
if (mask_image.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- mask_image.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height)
+ mask_image.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height)
{
printf("Image properties are different\n");
return;
@@ -543,7 +559,7 @@ void MEImage::ThresholdByMask(MEImage& mask_image)
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
unsigned char* MaskImageData = mask_image.GetImageData();
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height-1; i >= 0; --i)
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; i >= 0; --i)
{
if (MaskImageData[i] == 0)
{
@@ -567,123 +583,123 @@ void MEImage::ColorSpace(ColorSpaceConvertType mode)
}
switch (mode)
{
- case csc_RGBtoXYZCIED65:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2XYZ);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_XYZCIED65toRGB:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_XYZ2RGB);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_RGBtoHSV:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2HSV);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_HSVtoRGB:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
- ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_HSV2RGB);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_RGBtoHLS:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2HLS);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_HLStoRGB:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_HLS2RGB);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_RGBtoCIELab:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2Lab);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_CIELabtoRGB:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_Lab2RGB);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_RGBtoCIELuv:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2Luv);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_CIELuvtoRGB:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_Luv2RGB);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
-
- case csc_RGBtoYUV:
- ComputeColorSpace(csc_RGBtoYUV);
- break;
-
- case csc_RGBtoYIQ:
- ComputeColorSpace(csc_RGBtoYIQ);
- break;
-
- case csc_RGBtorgI:
- ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
- RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ case csc_RGBtoXYZCIED65:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
+ ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2XYZ);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_XYZCIED65toRGB:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
+ ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_XYZ2RGB);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_RGBtoHSV:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
+ ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2HSV);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_HSVtoRGB:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width,
+ ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_HSV2RGB);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_RGBtoHLS:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2HLS);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_HLStoRGB:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_HLS2RGB);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_RGBtoCIELab:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2Lab);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_CIELabtoRGB:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_Lab2RGB);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_RGBtoCIELuv:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2Luv);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_CIELuvtoRGB:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_Luv2RGB);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
+
+ case csc_RGBtoYUV:
+ ComputeColorSpace(csc_RGBtoYUV);
+ break;
+
+ case csc_RGBtoYIQ:
+ ComputeColorSpace(csc_RGBtoYIQ);
+ break;
+
+ case csc_RGBtorgI:
+ ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
+ WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
+ RowStart = 0;
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
+ {
+ for (int x = (ME_CAST_TO_IPLIMAGE(cvImg)->width - 1) * 3; x >= 0; x -= 3)
{
- for (int x = (ME_CAST_TO_IPLIMAGE(cvImg)->width-1)*3; x >= 0; x -= 3)
- {
- int r = 0;
- int g = 0;
- int I = 0;
-
- I = (int)ImageData[RowStart+x]+(int)ImageData[RowStart+x+1]+(int)ImageData[RowStart+x+2];
- r = (int)((float)ImageData[RowStart+x] / I*255);
- g = (int)((float)ImageData[RowStart+x+1] / I*255);
- ImageData[RowStart+x] = (unsigned char)r;
- ImageData[RowStart+x+1] = (unsigned char)g;
- ImageData[RowStart+x+2] = (unsigned char)(I / 3);
- }
- RowStart += WidthStep;
+ int r = 0;
+ int g = 0;
+ int I = 0;
+
+ I = (int)ImageData[RowStart + x] + (int)ImageData[RowStart + x + 1] + (int)ImageData[RowStart + x + 2];
+ r = (int)((float)ImageData[RowStart + x] / I * 255);
+ g = (int)((float)ImageData[RowStart + x + 1] / I * 255);
+ ImageData[RowStart + x] = (unsigned char)r;
+ ImageData[RowStart + x + 1] = (unsigned char)g;
+ ImageData[RowStart + x + 2] = (unsigned char)(I / 3);
}
- break;
+ RowStart += WidthStep;
+ }
+ break;
- default:
- break;
+ default:
+ break;
}
}
@@ -701,27 +717,27 @@ void MEImage::ConvertToGrayscale(GrayscaleType grayscale_mode)
switch (grayscale_mode)
{
- case g_Average:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8, 1);
- ImageData = (unsigned char*)TempImg->imageData;
+ case g_Average:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8, 1);
+ ImageData = (unsigned char*)TempImg->imageData;
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height-3; i >= 0; i -= 3)
- {
- ImageData[i / 3] = (ImgData[i]+ImgData[i+1]+ImgData[i+2]) / 3;
- }
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height - 3; i >= 0; i -= 3)
+ {
+ ImageData[i / 3] = (ImgData[i] + ImgData[i + 1] + ImgData[i + 2]) / 3;
+ }
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
- case g_OpenCV:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8, 1);
- cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2GRAY);
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
+ case g_OpenCV:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8, 1);
+ cvCvtColor(ME_CAST_TO_IPLIMAGE(cvImg), TempImg, CV_RGB2GRAY);
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
- default:
- break;
+ default:
+ break;
}
}
@@ -760,60 +776,60 @@ void MEImage::LBP(LBPType mode)
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8, 1);
unsigned char* TempImgData = (unsigned char*)TempImg->imageData;
int WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
- int WidthStep_2 = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*2;
+ int WidthStep_2 = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep * 2;
cvSetZero(TempImg);
switch (mode)
{
- case lbp_Normal:
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*(ME_CAST_TO_IPLIMAGE(cvImg)->height-2)-1; i >= ME_CAST_TO_IPLIMAGE(cvImg)->widthStep+1; --i)
- {
- TempImgData[i] =
- (ImageData[i] <= ImageData[i-ME_CAST_TO_IPLIMAGE(cvImg)->widthStep-1])+
- ((ImageData[i] <= ImageData[i-ME_CAST_TO_IPLIMAGE(cvImg)->widthStep])*2)+
- ((ImageData[i] <= ImageData[i-ME_CAST_TO_IPLIMAGE(cvImg)->widthStep+1])*4)+
- ((ImageData[i] <= ImageData[i-1])*8)+
- ((ImageData[i] <= ImageData[i+1])*16)+
- ((ImageData[i] <= ImageData[i+ME_CAST_TO_IPLIMAGE(cvImg)->widthStep-1])*32)+
- ((ImageData[i] <= ImageData[i+ME_CAST_TO_IPLIMAGE(cvImg)->widthStep])*64)+
- ((ImageData[i] <= ImageData[i+ME_CAST_TO_IPLIMAGE(cvImg)->widthStep+1])*128);
- }
- break;
+ case lbp_Normal:
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*(ME_CAST_TO_IPLIMAGE(cvImg)->height - 2) - 1; i >= ME_CAST_TO_IPLIMAGE(cvImg)->widthStep + 1; --i)
+ {
+ TempImgData[i] =
+ (ImageData[i] <= ImageData[i - ME_CAST_TO_IPLIMAGE(cvImg)->widthStep - 1]) +
+ ((ImageData[i] <= ImageData[i - ME_CAST_TO_IPLIMAGE(cvImg)->widthStep]) * 2) +
+ ((ImageData[i] <= ImageData[i - ME_CAST_TO_IPLIMAGE(cvImg)->widthStep + 1]) * 4) +
+ ((ImageData[i] <= ImageData[i - 1]) * 8) +
+ ((ImageData[i] <= ImageData[i + 1]) * 16) +
+ ((ImageData[i] <= ImageData[i + ME_CAST_TO_IPLIMAGE(cvImg)->widthStep - 1]) * 32) +
+ ((ImageData[i] <= ImageData[i + ME_CAST_TO_IPLIMAGE(cvImg)->widthStep]) * 64) +
+ ((ImageData[i] <= ImageData[i + ME_CAST_TO_IPLIMAGE(cvImg)->widthStep + 1]) * 128);
+ }
+ break;
- case lbp_Special:
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*(ME_CAST_TO_IPLIMAGE(cvImg)->height-3)-2; i >= ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*2+2; --i)
- {
- int CenterPixel = (ImageData[i+1]+ImageData[i-1]+
- ImageData[i-WidthStep]+ImageData[i+WidthStep]) / 4;
- TempImgData[i] = ((CenterPixel <= (ImageData[i-(WidthStep_2)-2]+
- ImageData[i-(WidthStep_2)-1]+
- ImageData[i-WidthStep-2]+
- ImageData[i-WidthStep-1]) / 4))+
- ((CenterPixel <= (ImageData[i-WidthStep]+
- ImageData[i-(WidthStep_2)]) / 2)*2)+
- ((CenterPixel <= ((ImageData[i-(WidthStep_2)+2]+
- ImageData[i-(WidthStep_2)+1]+
- ImageData[i-WidthStep+2]+
- ImageData[i-WidthStep+1]) / 4))*4)+
- ((CenterPixel <= (ImageData[i-1]+
- ImageData[i-2]) / 2)*8)+
- ((CenterPixel <= (ImageData[i+1]+
- ImageData[i+2]) / 2)*16)+
- ((CenterPixel <= ((ImageData[i+(WidthStep_2)-2]+
- ImageData[i+(WidthStep_2)-1]+
- ImageData[i+WidthStep-2]+
- ImageData[i+WidthStep-1]) / 4))*32)+
- ((CenterPixel <= (ImageData[i+WidthStep]+
- ImageData[i-WidthStep_2]) / 2)*64)+
- ((CenterPixel <= ((ImageData[i+(WidthStep_2)+2]+
- ImageData[i+(WidthStep_2)+1]+
- ImageData[i+WidthStep+2]+
- ImageData[i+WidthStep+1]) / 4))*128);
- }
- break;
+ case lbp_Special:
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*(ME_CAST_TO_IPLIMAGE(cvImg)->height - 3) - 2; i >= ME_CAST_TO_IPLIMAGE(cvImg)->widthStep * 2 + 2; --i)
+ {
+ int CenterPixel = (ImageData[i + 1] + ImageData[i - 1] +
+ ImageData[i - WidthStep] + ImageData[i + WidthStep]) / 4;
+ TempImgData[i] = ((CenterPixel <= (ImageData[i - (WidthStep_2)-2] +
+ ImageData[i - (WidthStep_2)-1] +
+ ImageData[i - WidthStep - 2] +
+ ImageData[i - WidthStep - 1]) / 4)) +
+ ((CenterPixel <= (ImageData[i - WidthStep] +
+ ImageData[i - (WidthStep_2)]) / 2) * 2) +
+ ((CenterPixel <= ((ImageData[i - (WidthStep_2)+2] +
+ ImageData[i - (WidthStep_2)+1] +
+ ImageData[i - WidthStep + 2] +
+ ImageData[i - WidthStep + 1]) / 4)) * 4) +
+ ((CenterPixel <= (ImageData[i - 1] +
+ ImageData[i - 2]) / 2) * 8) +
+ ((CenterPixel <= (ImageData[i + 1] +
+ ImageData[i + 2]) / 2) * 16) +
+ ((CenterPixel <= ((ImageData[i + (WidthStep_2)-2] +
+ ImageData[i + (WidthStep_2)-1] +
+ ImageData[i + WidthStep - 2] +
+ ImageData[i + WidthStep - 1]) / 4)) * 32) +
+ ((CenterPixel <= (ImageData[i + WidthStep] +
+ ImageData[i - WidthStep_2]) / 2) * 64) +
+ ((CenterPixel <= ((ImageData[i + (WidthStep_2)+2] +
+ ImageData[i + (WidthStep_2)+1] +
+ ImageData[i + WidthStep + 2] +
+ ImageData[i + WidthStep + 1]) / 4)) * 128);
+ }
+ break;
- default:
- break;
+ default:
+ break;
}
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
@@ -824,12 +840,13 @@ void MEImage::Binarize(int threshold)
{
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep-1; i >= 0; --i)
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep - 1; i >= 0; --i)
{
if (ImageData[i] >= threshold)
{
ImageData[i] = 255;
- } else {
+ }
+ else {
ImageData[i] = 0;
}
}
@@ -839,8 +856,8 @@ void MEImage::Binarize(int threshold)
void MEImage::Subtract(MEImage& source, SubtractModeType mode)
{
if (source.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- source.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
- source.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
+ source.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
+ source.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
{
printf("Image properties are different.\n");
return;
@@ -852,42 +869,42 @@ void MEImage::Subtract(MEImage& source, SubtractModeType mode)
switch (mode)
{
- case sub_Normal:
- ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- DstData = source.GetImageData();
- RowStart = 0;
+ case sub_Normal:
+ ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
+ DstData = source.GetImageData();
+ RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
+ {
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
- {
- ImageData[RowStart+x] =
- ImageData[RowStart+x]-DstData[RowStart+x] < 0 ? 0 :
- ImageData[RowStart+x]-DstData[RowStart+x];
- }
- RowStart += WidthStep;
+ ImageData[RowStart + x] =
+ ImageData[RowStart + x] - DstData[RowStart + x] < 0 ? 0 :
+ ImageData[RowStart + x] - DstData[RowStart + x];
}
- break;
+ RowStart += WidthStep;
+ }
+ break;
- case sub_Absolut:
- ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- DstData = source.GetImageData();
- RowStart = 0;
+ case sub_Absolut:
+ ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
+ DstData = source.GetImageData();
+ RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
+ {
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
- {
- ImageData[RowStart+x] = ImageData[RowStart+x]-
- DstData[RowStart+x] < 0 ? -ImageData[RowStart+x]+
- DstData[RowStart+x] : ImageData[RowStart+x]-DstData[RowStart+x];
- }
- RowStart += WidthStep;
+ ImageData[RowStart + x] = ImageData[RowStart + x] -
+ DstData[RowStart + x] < 0 ? -ImageData[RowStart + x] +
+ DstData[RowStart + x] : ImageData[RowStart + x] - DstData[RowStart + x];
}
- break;
+ RowStart += WidthStep;
+ }
+ break;
- default:
- break;
+ default:
+ break;
}
}
@@ -895,8 +912,8 @@ void MEImage::Subtract(MEImage& source, SubtractModeType mode)
void MEImage::Multiple(MEImage& source, MultiplicationType mode)
{
if (source.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- source.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
- source.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
+ source.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
+ source.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
{
printf("Image properties are different.\n");
return;
@@ -910,57 +927,59 @@ void MEImage::Multiple(MEImage& source, MultiplicationType mode)
switch (mode)
{
- case m_Normal:
- Result = 0;
- ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- DstData = source.GetImageData();
+ case m_Normal:
+ Result = 0;
+ ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
+ DstData = source.GetImageData();
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep-1; i >= 0; --i)
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep - 1; i >= 0; --i)
+ {
+ if ((ImageData[i] >= 128) && (DstData[i] >= 128))
{
- if ((ImageData[i] >= 128) && (DstData[i] >= 128))
- {
- Result = (float)ImageData[i]/128*(float)DstData[i]/128;
+ Result = (float)ImageData[i] / 128 * (float)DstData[i] / 128;
- if (Result >= 1)
- {
- ImageData[i] = 255;
- } else {
- ImageData[i] = 0;
- }
- } else {
+ if (Result >= 1)
+ {
+ ImageData[i] = 255;
+ }
+ else {
ImageData[i] = 0;
}
}
- break;
-
- case m_Neighbourhood:
- TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
- ImageData2 = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- DstData = source.GetImageData();
- ImageData3 = (unsigned char*)TempImg->imageData;
-
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width-1; x >= 0; --x)
- for (int l = ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; l >= 0; --l)
- {
- if (((DstData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+
- x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] == 255) ||
- (ImageData2[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+
- x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] == 255)) &&
- (NeighbourhoodCounter(x-2, y-2, n_5x5) > 3) &&
- (source.NeighbourhoodCounter(x-2, y-2, n_5x5) > 3))
+ else {
+ ImageData[i] = 0;
+ }
+ }
+ break;
+
+ case m_Neighbourhood:
+ TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ImageData2 = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
+ DstData = source.GetImageData();
+ ImageData3 = (unsigned char*)TempImg->imageData;
+
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width - 1; x >= 0; --x)
+ for (int l = ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; l >= 0; --l)
{
- ImageData3[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+
- x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] = 255;
+ if (((DstData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels +
+ x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] == 255) ||
+ (ImageData2[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels +
+ x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] == 255)) &&
+ (NeighbourhoodCounter(x - 2, y - 2, n_5x5) > 3) &&
+ (source.NeighbourhoodCounter(x - 2, y - 2, n_5x5) > 3))
+ {
+ ImageData3[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels +
+ x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] = 255;
+ }
}
- }
- ME_RELEASE_IPLIMAGE(cvImg);
- cvImg = TempImg;
- break;
+ ME_RELEASE_IPLIMAGE(cvImg);
+ cvImg = TempImg;
+ break;
- default:
- break;
+ default:
+ break;
}
}
@@ -968,8 +987,8 @@ void MEImage::Multiple(MEImage& source, MultiplicationType mode)
void MEImage::Addition(MEImage& source, AdditionType mode)
{
if (source.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- source.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
- source.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
+ source.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
+ source.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
{
printf("Image properties are different.\n");
return;
@@ -979,25 +998,25 @@ void MEImage::Addition(MEImage& source, AdditionType mode)
switch (mode)
{
- case a_Average:
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep-1; i >= 0; --i)
- {
- ImageData[i] = (ImageData[i]+DstData[i]) / 2;
- }
- break;
+ case a_Average:
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep - 1; i >= 0; --i)
+ {
+ ImageData[i] = (ImageData[i] + DstData[i]) / 2;
+ }
+ break;
- case a_Union:
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep-1; i >= 0; --i)
+ case a_Union:
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep - 1; i >= 0; --i)
+ {
+ if (DstData[i] > ImageData[i])
{
- if (DstData[i] > ImageData[i])
- {
- ImageData[i] = DstData[i];
- }
+ ImageData[i] = DstData[i];
}
- break;
+ }
+ break;
- default:
- break;
+ default:
+ break;
}
}
@@ -1005,42 +1024,44 @@ void MEImage::Addition(MEImage& source, AdditionType mode)
void MEImage::EliminateSinglePixels()
{
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
unsigned char* DstData = (unsigned char*)TempImg->imageData;
int sum = 0;
int xy = 0;
int ywidth = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width-1; x >= 0; --x)
- {
- xy = y*ywidth+x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels;
-
- for (int l = ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; l >= 0; --l)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width - 1; x >= 0; --x)
{
- if ((ImageData[xy+l] > 0) && (x > 0) && (y > 0) && (x < ME_CAST_TO_IPLIMAGE(cvImg)->width-1) && (y < ME_CAST_TO_IPLIMAGE(cvImg)->height-1))
+ xy = y*ywidth + x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels;
+
+ for (int l = ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; l >= 0; --l)
{
- sum = (ImageData[xy-ywidth-ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] > 0)+
- (ImageData[xy-ywidth+l] > 0)+
- (ImageData[xy-ywidth+ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] > 0)+
- (ImageData[xy-ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] > 0)+
- (ImageData[xy+ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] > 0)+
- (ImageData[xy+ywidth-ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] > 0)+
- (ImageData[xy+ywidth+l] > 0)+
- (ImageData[xy+ywidth+ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l] > 0);
-
- if (sum > 3)
+ if ((ImageData[xy + l] > 0) && (x > 0) && (y > 0) && (x < ME_CAST_TO_IPLIMAGE(cvImg)->width - 1) && (y < ME_CAST_TO_IPLIMAGE(cvImg)->height - 1))
{
- DstData[xy+l] = 255;
- } else {
- DstData[xy+l] = 0;
+ sum = (ImageData[xy - ywidth - ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] > 0) +
+ (ImageData[xy - ywidth + l] > 0) +
+ (ImageData[xy - ywidth + ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] > 0) +
+ (ImageData[xy - ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] > 0) +
+ (ImageData[xy + ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] > 0) +
+ (ImageData[xy + ywidth - ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] > 0) +
+ (ImageData[xy + ywidth + l] > 0) +
+ (ImageData[xy + ywidth + ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l] > 0);
+
+ if (sum > 3)
+ {
+ DstData[xy + l] = 255;
+ }
+ else {
+ DstData[xy + l] = 0;
+ }
+ }
+ else {
+ DstData[xy + l] = 0;
}
- } else {
- DstData[xy+l] = 0;
}
}
- }
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
}
@@ -1049,8 +1070,8 @@ void MEImage::EliminateSinglePixels()
float MEImage::DifferenceAreas(MEImage& reference, int difference) const
{
if (reference.GetWidth() != GetWidth() ||
- reference.GetHeight() != GetHeight() ||
- reference.GetLayers() != GetLayers())
+ reference.GetHeight() != GetHeight() ||
+ reference.GetLayers() != GetLayers())
{
printf("Image dimensions or channels are different\n");
return -1.0;
@@ -1062,16 +1083,16 @@ float MEImage::DifferenceAreas(MEImage& reference, int difference) const
int WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
int RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- if (abs(OrigImgData[RowStart+x]-RefImgData[RowStart+x]) > difference)
+ if (abs(OrigImgData[RowStart + x] - RefImgData[RowStart + x]) > difference)
Pixels++;
}
RowStart += WidthStep;
}
- PixelDiff = (float)Pixels / (ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep)*100;
+ PixelDiff = (float)Pixels / (ME_CAST_TO_IPLIMAGE(cvImg)->height*ME_CAST_TO_IPLIMAGE(cvImg)->widthStep) * 100;
return PixelDiff;
}
@@ -1079,8 +1100,8 @@ float MEImage::DifferenceAreas(MEImage& reference, int difference) const
int MEImage::AverageDifference(MEImage& reference) const
{
if (reference.GetWidth() != GetWidth() ||
- reference.GetHeight() != GetHeight() ||
- reference.GetLayers() != GetLayers())
+ reference.GetHeight() != GetHeight() ||
+ reference.GetLayers() != GetLayers())
{
printf("Image dimensions or channels are different\n");
return -1;
@@ -1091,11 +1112,11 @@ int MEImage::AverageDifference(MEImage& reference) const
int WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
int RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- Difference += abs(OrigImgData[RowStart+x]-RefImgData[RowStart+x]);
+ Difference += abs(OrigImgData[RowStart + x] - RefImgData[RowStart + x]);
}
RowStart += WidthStep;
}
@@ -1107,8 +1128,8 @@ int MEImage::AverageDifference(MEImage& reference) const
void MEImage::Minimum(MEImage& image)
{
if (image.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- image.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
- image.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
+ image.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
+ image.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
{
printf("Image properties are different\n");
return;
@@ -1118,12 +1139,12 @@ void MEImage::Minimum(MEImage& image)
int WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
int RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- ImageData[RowStart+x] = ImageData[RowStart+x] > SecData[RowStart+x] ?
- SecData[RowStart+x] : ImageData[RowStart+x];
+ ImageData[RowStart + x] = ImageData[RowStart + x] > SecData[RowStart + x] ?
+ SecData[RowStart + x] : ImageData[RowStart + x];
}
RowStart += WidthStep;
}
@@ -1137,11 +1158,11 @@ float MEImage::AverageBrightnessLevel() const
int RowStart = 0;
int BrightnessLevel = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- BrightnessLevel += (int)ImageData[RowStart+x];
+ BrightnessLevel += (int)ImageData[RowStart + x];
}
RowStart += WidthStep;
}
@@ -1160,8 +1181,8 @@ bool MEImage::Equal(const MEImage& reference, int maxabsdiff) const
bool Ret = true;
if (reference.GetWidth() != ME_CAST_TO_IPLIMAGE(cvImg)->width ||
- reference.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
- reference.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
+ reference.GetHeight() != ME_CAST_TO_IPLIMAGE(cvImg)->height ||
+ reference.GetLayers() != ME_CAST_TO_IPLIMAGE(cvImg)->nChannels)
{
printf("Image properties are different\n");
return false;
@@ -1171,11 +1192,11 @@ bool MEImage::Equal(const MEImage& reference, int maxabsdiff) const
int WidthStep = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep;
int RowStart = 0;
- for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height-1; y >= 0; --y)
+ for (int y = ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; y >= 0; --y)
{
- for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels-1; x >= 0; --x)
+ for (int x = ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels - 1; x >= 0; --x)
{
- if (abs(ImageData[RowStart+x]-RefData[RowStart+x]) >= maxabsdiff)
+ if (abs(ImageData[RowStart + x] - RefData[RowStart + x]) >= maxabsdiff)
{
Ret = false;
return Ret;
@@ -1193,16 +1214,16 @@ unsigned char MEImage::GrayscalePixel(int x, int y) const
int NewY = y;
NewX = NewX < 0 ? 0 : NewX;
- NewX = NewX > ME_CAST_TO_IPLIMAGE(cvImg)->width-1 ? ME_CAST_TO_IPLIMAGE(cvImg)->width-1 : NewX;
+ NewX = NewX > ME_CAST_TO_IPLIMAGE(cvImg)->width - 1 ? ME_CAST_TO_IPLIMAGE(cvImg)->width - 1 : NewX;
NewY = NewY < 0 ? 0 : NewY;
- NewY = NewY > ME_CAST_TO_IPLIMAGE(cvImg)->height-1 ? ME_CAST_TO_IPLIMAGE(cvImg)->height-1 : NewY;
+ NewY = NewY > ME_CAST_TO_IPLIMAGE(cvImg)->height - 1 ? ME_CAST_TO_IPLIMAGE(cvImg)->height - 1 : NewY;
float Sum = 0;
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
for (int l = 0; l < ME_CAST_TO_IPLIMAGE(cvImg)->nChannels; l++)
{
- Sum = Sum + (int)ImageData[NewY*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+NewX*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+l];
+ Sum = Sum + (int)ImageData[NewY*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + NewX*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + l];
}
Sum = Sum / ME_CAST_TO_IPLIMAGE(cvImg)->nChannels;
return (unsigned char)(Sum);
@@ -1210,7 +1231,7 @@ unsigned char MEImage::GrayscalePixel(int x, int y) const
int MEImage::NeighbourhoodCounter(int startx, int starty,
- NeighbourhoodType neighbourhood) const
+ NeighbourhoodType neighbourhood) const
{
int IterX = 0;
int IterY = 0;
@@ -1219,60 +1240,60 @@ int MEImage::NeighbourhoodCounter(int startx, int starty,
// Determine the iteration numbers
switch (neighbourhood)
{
- case n_2x2:
- IterX = 2;
- IterY = 2;
- break;
+ case n_2x2:
+ IterX = 2;
+ IterY = 2;
+ break;
- case n_3x3:
- IterX = 3;
- IterY = 3;
- break;
+ case n_3x3:
+ IterX = 3;
+ IterY = 3;
+ break;
- case n_3x2:
- IterX = 2;
- IterY = 3;
- break;
+ case n_3x2:
+ IterX = 2;
+ IterY = 3;
+ break;
- case n_5x5:
- IterX = 5;
- IterY = 5;
- break;
+ case n_5x5:
+ IterX = 5;
+ IterY = 5;
+ break;
- case n_7x7:
- IterX = 7;
- IterY = 7;
- break;
+ case n_7x7:
+ IterX = 7;
+ IterY = 7;
+ break;
- default:
- IterX = 3;
- IterY = 3;
- break;
+ default:
+ IterX = 3;
+ IterY = 3;
+ break;
}
- int NewStartX = startx ;
+ int NewStartX = startx;
int NewStartY = starty;
NewStartX = startx < 0 ? 0 : startx;
- NewStartX = startx >= ME_CAST_TO_IPLIMAGE(cvImg)->width-IterX ? ME_CAST_TO_IPLIMAGE(cvImg)->width-IterX-1 : startx;
+ NewStartX = startx >= ME_CAST_TO_IPLIMAGE(cvImg)->width - IterX ? ME_CAST_TO_IPLIMAGE(cvImg)->width - IterX - 1 : startx;
NewStartY = starty < 0 ? 0 : starty;
- NewStartY = starty >= ME_CAST_TO_IPLIMAGE(cvImg)->height-IterY ? ME_CAST_TO_IPLIMAGE(cvImg)->height-IterY-1 : starty;
+ NewStartY = starty >= ME_CAST_TO_IPLIMAGE(cvImg)->height - IterY ? ME_CAST_TO_IPLIMAGE(cvImg)->height - IterY - 1 : starty;
int Value = 0;
unsigned char* ImageData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
- for (int x = NewStartX; x < NewStartX+IterX; x++)
- for (int y = NewStartY; y < NewStartY+IterY; y++)
- {
- Value = ((int)ImageData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels]+
- (int)ImageData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+1]+
- (int)ImageData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels+2]) / 3;
-
- if (Value == 255)
+ for (int x = NewStartX; x < NewStartX + IterX; x++)
+ for (int y = NewStartY; y < NewStartY + IterY; y++)
{
- Counter++;
+ Value = ((int)ImageData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels] +
+ (int)ImageData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + 1] +
+ (int)ImageData[y*ME_CAST_TO_IPLIMAGE(cvImg)->width*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + x*ME_CAST_TO_IPLIMAGE(cvImg)->nChannels + 2]) / 3;
+
+ if (Value == 255)
+ {
+ Counter++;
+ }
}
- }
return Counter;
}
@@ -1288,24 +1309,24 @@ void MEImage::GradientVector(bool smooth, int x, int y, int mask_size, int& resu
}
if (smooth)
{
- SmoothAdvanced(s_Gaussian, mask_size*3-(mask_size*3-1) % 2);
+ SmoothAdvanced(s_Gaussian, mask_size * 3 - (mask_size * 3 - 1) % 2);
}
- Results[0] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x,y-mask_size);
- Results[1] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x+DiagonalMaskSize,y-DiagonalMaskSize);
- Results[2] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x+mask_size,y);
- Results[3] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x+DiagonalMaskSize,y+DiagonalMaskSize);
- Results[4] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x,y+mask_size);
- Results[5] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x-DiagonalMaskSize,y+DiagonalMaskSize);
- Results[6] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x-mask_size,y);
- Results[7] = (int)GrayscalePixel(x,y)-(int)GrayscalePixel(x+DiagonalMaskSize,y-DiagonalMaskSize);
+ Results[0] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x, y - mask_size);
+ Results[1] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x + DiagonalMaskSize, y - DiagonalMaskSize);
+ Results[2] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x + mask_size, y);
+ Results[3] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x + DiagonalMaskSize, y + DiagonalMaskSize);
+ Results[4] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x, y + mask_size);
+ Results[5] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x - DiagonalMaskSize, y + DiagonalMaskSize);
+ Results[6] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x - mask_size, y);
+ Results[7] = (int)GrayscalePixel(x, y) - (int)GrayscalePixel(x + DiagonalMaskSize, y - DiagonalMaskSize);
- result_x = (DiagonalMaskSize*Results[1]+mask_size*Results[2]+
- DiagonalMaskSize*Results[3]-DiagonalMaskSize*Results[5]-
- mask_size*Results[6]+DiagonalMaskSize*Results[7]) / 256;
- result_y = (-mask_size*Results[0]-DiagonalMaskSize*Results[1]+
- DiagonalMaskSize*Results[3]+mask_size*Results[4]+
- DiagonalMaskSize*Results[5]-DiagonalMaskSize*Results[7]) / 256;
+ result_x = (DiagonalMaskSize*Results[1] + mask_size*Results[2] +
+ DiagonalMaskSize*Results[3] - DiagonalMaskSize*Results[5] -
+ mask_size*Results[6] + DiagonalMaskSize*Results[7]) / 256;
+ result_y = (-mask_size*Results[0] - DiagonalMaskSize*Results[1] +
+ DiagonalMaskSize*Results[3] + mask_size*Results[4] +
+ DiagonalMaskSize*Results[5] - DiagonalMaskSize*Results[7]) / 256;
}
@@ -1327,28 +1348,28 @@ void MEImage::GradientVisualize(int vector_x, int vector_y)
}
int masksize = (ME_CAST_TO_IPLIMAGE(cvImg)->width < ME_CAST_TO_IPLIMAGE(cvImg)->height) ?
- ME_CAST_TO_IPLIMAGE(cvImg)->width / (vector_x+1) :
- ME_CAST_TO_IPLIMAGE(cvImg)->height / (vector_y+1);
+ ME_CAST_TO_IPLIMAGE(cvImg)->width / (vector_x + 1) :
+ ME_CAST_TO_IPLIMAGE(cvImg)->height / (vector_y + 1);
- SmoothAdvanced(s_Gaussian, masksize*2-1);
+ SmoothAdvanced(s_Gaussian, masksize * 2 - 1);
for (int i = 1; i < vector_x; i++)
for (int i1 = 1; i1 < vector_y; i1++)
- {
- int Resultx = 0, Resulty = 0;
- int x = (int)(((float)ME_CAST_TO_IPLIMAGE(cvImg)->width*i / (vector_x)));
- int y = (int)(((float)ME_CAST_TO_IPLIMAGE(cvImg)->height*i1 / (vector_y)));
+ {
+ int Resultx = 0, Resulty = 0;
+ int x = (int)(((float)ME_CAST_TO_IPLIMAGE(cvImg)->width*i / (vector_x)));
+ int y = (int)(((float)ME_CAST_TO_IPLIMAGE(cvImg)->height*i1 / (vector_y)));
- GradientVector(false, x, y, (int)(0.707*masksize), Resultx, Resulty);
+ GradientVector(false, x, y, (int)(0.707*masksize), Resultx, Resulty);
- CvPoint Point1;
- CvPoint Point2;
+ CvPoint Point1;
+ CvPoint Point2;
- Point1.x = x-Resultx / 2;
- Point1.y = y-Resulty / 2;
- Point2.x = x+Resultx / 2;
- Point2.y = y+Resulty / 2;
- cvLine(ME_CAST_TO_IPLIMAGE(cvImg), Point1, Point2, CV_RGB(255, 255, 255), 1, 8);
- }
+ Point1.x = x - Resultx / 2;
+ Point1.y = y - Resulty / 2;
+ Point2.x = x + Resultx / 2;
+ Point2.y = y + Resulty / 2;
+ cvLine(ME_CAST_TO_IPLIMAGE(cvImg), Point1, Point2, CV_RGB(255, 255, 255), 1, 8);
+ }
}
@@ -1400,16 +1421,16 @@ void MEImage::ComputeColorSpace(ColorSpaceConvertType mode)
return;
}
IplImage* TempImg = cvCreateImage(cvSize(ME_CAST_TO_IPLIMAGE(cvImg)->width, ME_CAST_TO_IPLIMAGE(cvImg)->height), 8,
- ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
+ ME_CAST_TO_IPLIMAGE(cvImg)->nChannels);
for (int i = 0; i < 3; i++)
for (int i1 = 0; i1 < 3; i1++)
- {
- if (mode == csc_RGBtoYUV)
- TransformMatrix[i][i1] = RGBtoYUVMatrix[i][i1];
- if (mode == csc_RGBtoYIQ)
- TransformMatrix[i][i1] = RGBtoYIQMatrix[i][i1];
- }
+ {
+ if (mode == csc_RGBtoYUV)
+ TransformMatrix[i][i1] = RGBtoYUVMatrix[i][i1];
+ if (mode == csc_RGBtoYIQ)
+ TransformMatrix[i][i1] = RGBtoYIQMatrix[i][i1];
+ }
float x = 0.0;
float y = 0.0;
float z = 0.0;
@@ -1441,25 +1462,25 @@ void MEImage::ComputeColorSpace(ColorSpaceConvertType mode)
unsigned char* SrcData = (unsigned char*)ME_CAST_TO_IPLIMAGE(cvImg)->imageData;
unsigned char* DstData = (unsigned char*)TempImg->imageData;
- for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height-1; i >= 0; i-=3)
+ for (int i = ME_CAST_TO_IPLIMAGE(cvImg)->widthStep*ME_CAST_TO_IPLIMAGE(cvImg)->height - 1; i >= 0; i -= 3)
{
- x = (float)SrcData[i]*TransformMatrix[0][0]+
- (float)SrcData[i+1]*TransformMatrix[0][1]+
- (float)SrcData[i+2]*TransformMatrix[0][2];
- y = (float)SrcData[i]*TransformMatrix[1][0]+
- (float)SrcData[i+1]*TransformMatrix[1][1]+
- (float)SrcData[i+2]*TransformMatrix[1][2];
- z = (float)SrcData[i]*TransformMatrix[2][0]+
- (float)SrcData[i+1]*TransformMatrix[2][1]+
- (float)SrcData[i+2]*TransformMatrix[2][2];
+ x = (float)SrcData[i] * TransformMatrix[0][0] +
+ (float)SrcData[i + 1] * TransformMatrix[0][1] +
+ (float)SrcData[i + 2] * TransformMatrix[0][2];
+ y = (float)SrcData[i] * TransformMatrix[1][0] +
+ (float)SrcData[i + 1] * TransformMatrix[1][1] +
+ (float)SrcData[i + 2] * TransformMatrix[1][2];
+ z = (float)SrcData[i] * TransformMatrix[2][0] +
+ (float)SrcData[i + 1] * TransformMatrix[2][1] +
+ (float)SrcData[i + 2] * TransformMatrix[2][2];
- x = xmax-xmin != 0.0 ? 255.0 : (x-xmin) / (xmax-xmin)*255.0;
- y = ymax-ymin != 0.0 ? 255.0 : (y-xmin) / (ymax-ymin)*255.0;
- z = zmax-zmin != 0.0 ? 255.0 : (z-xmin) / (zmax-zmin)*255.0;
+ x = xmax - xmin != 0.0 ? 255.0 : (x - xmin) / (xmax - xmin)*255.0;
+ y = ymax - ymin != 0.0 ? 255.0 : (y - xmin) / (ymax - ymin)*255.0;
+ z = zmax - zmin != 0.0 ? 255.0 : (z - xmin) / (zmax - zmin)*255.0;
DstData[i] = (unsigned char)MEBound(0, (int)x, 255);
- DstData[i+1] = (unsigned char)MEBound(0, (int)y, 255);
- DstData[i+2] = (unsigned char)MEBound(0, (int)z, 255);
+ DstData[i + 1] = (unsigned char)MEBound(0, (int)y, 255);
+ DstData[i + 2] = (unsigned char)MEBound(0, (int)z, 255);
}
ME_RELEASE_IPLIMAGE(cvImg);
cvImg = TempImg;
diff --git a/package_bgs/ck/MEImage.hpp b/package_bgs/LBP_MRF/MEImage.hpp
similarity index 97%
rename from package_bgs/ck/MEImage.hpp
rename to package_bgs/LBP_MRF/MEImage.hpp
index 41ada3b..3a52a77 100644
--- a/package_bgs/ck/MEImage.hpp
+++ b/package_bgs/LBP_MRF/MEImage.hpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/*
* This file is part of the AiBO+ project
*
@@ -18,19 +34,17 @@
* Foundation, Inc., 59 Temple Street #330, Boston, MA 02111-1307, USA.
*
*/
+#pragma once
-#ifndef MEImage_H
-#define MEImage_H
-
-/**
- * @addtogroup mindeye
- * @{
- */
+ /**
+ * @addtogroup mindeye
+ * @{
+ */
-/**
- * MEImage
- * @brief Basic image functions
- */
+ /**
+ * MEImage
+ * @brief Basic image functions
+ */
class MEImage
{
public:
@@ -995,5 +1009,3 @@ private:
};
/** @} */
-
-#endif
diff --git a/package_bgs/ck/MotionDetection.cpp b/package_bgs/LBP_MRF/MotionDetection.cpp
similarity index 91%
rename from package_bgs/ck/MotionDetection.cpp
rename to package_bgs/LBP_MRF/MotionDetection.cpp
index 5ac096a..e591faa 100644
--- a/package_bgs/ck/MotionDetection.cpp
+++ b/package_bgs/LBP_MRF/MotionDetection.cpp
@@ -1,4 +1,20 @@
/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/*
* This file is part of the AiBO+ project
*
* Copyright (C) 2005-2013 Csaba Kertész (csaba.kertesz@gmail.com)
@@ -52,15 +68,15 @@ struct MEPixelDataType
};
MotionDetection::MotionDetection(DetectorType mode) :
-MDMode(md_NotDefined), MDDataState(ps_Uninitialized), Frames(0), ReadyMask(false),
-HUColorSpace(MEImage::csc_RGBtoCIELuv), HULBPMode(MEImage::lbp_Special),
-HUHistogramsPerPixel(3), HUHistogramArea(5), HUHistogramBins(8),
-HUImageWidth(-1), HUImageHeight(-1), HULBPPixelData(NULL),
-HUPrThres(0.75), HUBackgrThres(0.95), HUHistLRate(0.01), HUWeightsLRate(0.01),
-HUSamplePixels(-1), HUDesiredSamplePixels(-1), HUMinCutWeight(8.0),
-HUOFDataState(ps_Uninitialized), HUOFPointsNumber(-1),
-HUOFCamMovementX(0), MaxTrackedPoints(0), HUOFFrames(-1),
-HUOFCamMovement(false)
+ MDMode(md_NotDefined), MDDataState(ps_Uninitialized), Frames(0), ReadyMask(false),
+ HUColorSpace(MEImage::csc_RGBtoCIELuv), HULBPMode(MEImage::lbp_Special),
+ HUHistogramsPerPixel(3), HUHistogramArea(5), HUHistogramBins(8),
+ HUImageWidth(-1), HUImageHeight(-1), HULBPPixelData(NULL),
+ HUPrThres(0.75), HUBackgrThres(0.95), HUHistLRate(0.01), HUWeightsLRate(0.01),
+ HUSamplePixels(-1), HUDesiredSamplePixels(-1), HUMinCutWeight(8.0),
+ HUOFDataState(ps_Uninitialized), HUOFPointsNumber(-1),
+ HUOFCamMovementX(0), MaxTrackedPoints(0), HUOFFrames(-1),
+ HUOFCamMovement(false)
{
HUOFPyramid = NULL;
HUOFPrevPyramid = NULL;
@@ -357,13 +373,13 @@ void MotionDetection::InitHUData(int imagewidth, int imageheight)
for (int i = 0; i < HUImageWidth / 2; ++i)
for (int i1 = 0; i1 < HUImageHeight; ++i1)
{
- HULBPPixelData[i][i1] = new MEPixelDataType;
- HULBPPixelData[i][i1]->Weights = new float[HUHistogramsPerPixel];
- HULBPPixelData[i][i1]->BackgroundHistogram = new bool[HUHistogramsPerPixel];
- HULBPPixelData[i][i1]->Histograms = new float*[HUHistogramsPerPixel];
- for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
- HULBPPixelData[i][i1]->Histograms[i2] = new float[HUHistogramBins];
- HULBPPixelData[i][i1]->PreviousHistogram = new float[HUHistogramBins];
+ HULBPPixelData[i][i1] = new MEPixelDataType;
+ HULBPPixelData[i][i1]->Weights = new float[HUHistogramsPerPixel];
+ HULBPPixelData[i][i1]->BackgroundHistogram = new bool[HUHistogramsPerPixel];
+ HULBPPixelData[i][i1]->Histograms = new float*[HUHistogramsPerPixel];
+ for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
+ HULBPPixelData[i][i1]->Histograms[i2] = new float[HUHistogramBins];
+ HULBPPixelData[i][i1]->PreviousHistogram = new float[HUHistogramBins];
}
// Allocate auxiliary variables
@@ -399,8 +415,8 @@ void MotionDetection::InitHUOFData(int imagewidth, int imageheight)
HUOFPointsNumber = imagewidth*imageheight / 1000;
HUOFPyramid = cvCreateImage(cvSize(imagewidth, imageheight), 8, 1);
HUOFPrevPyramid = cvCreateImage(cvSize(imagewidth, imageheight), 8, 1);
- HUOFPoints[0] = (CvPoint2D32f*)cvAlloc(HUOFPointsNumber*sizeof(HUOFPoints[0][0]));
- HUOFPoints[1] = (CvPoint2D32f*)cvAlloc(HUOFPointsNumber*sizeof(HUOFPoints[1][0]));
+ HUOFPoints[0] = (CvPoint2D32f*)cvAlloc(HUOFPointsNumber * sizeof(HUOFPoints[0][0]));
+ HUOFPoints[1] = (CvPoint2D32f*)cvAlloc(HUOFPointsNumber * sizeof(HUOFPoints[1][0]));
}
}
@@ -412,13 +428,13 @@ void MotionDetection::ReleaseHUData()
for (int i = 0; i < HUImageWidth / 2; i++)
for (int i1 = 0; i1 < HUImageHeight; i1++)
{
- delete[] HULBPPixelData[i][i1]->PreviousHistogram;
- for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
- delete[] HULBPPixelData[i][i1]->Histograms[i2];
- delete[] HULBPPixelData[i][i1]->Histograms;
- delete[] HULBPPixelData[i][i1]->BackgroundHistogram;
- delete[] HULBPPixelData[i][i1]->Weights;
- delete HULBPPixelData[i][i1];
+ delete[] HULBPPixelData[i][i1]->PreviousHistogram;
+ for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
+ delete[] HULBPPixelData[i][i1]->Histograms[i2];
+ delete[] HULBPPixelData[i][i1]->Histograms;
+ delete[] HULBPPixelData[i][i1]->BackgroundHistogram;
+ delete[] HULBPPixelData[i][i1]->Weights;
+ delete HULBPPixelData[i][i1];
}
for (int i = 0; i < HUImageWidth / 2; i++)
@@ -486,15 +502,15 @@ void MotionDetection::ClearHUData()
for (int i = (HUImageWidth / 2) - 1; i >= 0; --i)
for (int i1 = HUImageHeight - 1; i1 >= 0; --i1)
{
- for (int i2 = HUHistogramsPerPixel - 1; i2 >= 0; --i2)
- {
- memset(HULBPPixelData[i][i1]->Histograms[i2], 0,
- HUHistogramBins*sizeof(float));
- HULBPPixelData[i][i1]->Weights[i2] = 1.0 / HUHistogramsPerPixel;
- HULBPPixelData[i][i1]->BackgroundHistogram[i2] = true;
- }
- HULBPPixelData[i][i1]->BackgroundRate = 1.0;
- HULBPPixelData[i][i1]->LifeCycle = 0;
+ for (int i2 = HUHistogramsPerPixel - 1; i2 >= 0; --i2)
+ {
+ memset(HULBPPixelData[i][i1]->Histograms[i2], 0,
+ HUHistogramBins * sizeof(float));
+ HULBPPixelData[i][i1]->Weights[i2] = 1.0 / HUHistogramsPerPixel;
+ HULBPPixelData[i][i1]->BackgroundHistogram[i2] = true;
+ }
+ HULBPPixelData[i][i1]->BackgroundRate = 1.0;
+ HULBPPixelData[i][i1]->LifeCycle = 0;
}
MDDataState = ps_Initialized;
}
@@ -563,13 +579,13 @@ void MotionDetection::DetectMotionsHU(MEImage& image)
else
if (Frames > 1)
{
- PreviousImage = CurrentImage;
- CurrentImage = image;
- // Optical flow correction of the camera movements
- if (MDMode == md_DLBPHistograms)
- {
- OpticalFlowCorrection();
- }
+ PreviousImage = CurrentImage;
+ CurrentImage = image;
+ // Optical flow correction of the camera movements
+ if (MDMode == md_DLBPHistograms)
+ {
+ OpticalFlowCorrection();
+ }
}
newimage.ConvertToGrayscale(MEImage::g_OpenCV);
@@ -915,17 +931,17 @@ void MotionDetection::UpdateHUPixelData(MEPixelDataType* PixelData, const float
for (int i1 = HUHistogramsPerPixel - 1; i1 >= 2; --i1)
for (int i = i1; i >= 1; --i)
{
- if (Weights[i][1] <= Weights[i - 1][1])
- {
- float tmp = Weights[i][0];
- float tmp2 = Weights[i][1];
+ if (Weights[i][1] <= Weights[i - 1][1])
+ {
+ float tmp = Weights[i][0];
+ float tmp2 = Weights[i][1];
- Weights[i][0] = Weights[i - 1][0];
- Weights[i][1] = Weights[i - 1][1];
+ Weights[i][0] = Weights[i - 1][0];
+ Weights[i][1] = Weights[i - 1][1];
- Weights[i - 1][0] = tmp;
- Weights[i - 1][1] = tmp2;
- }
+ Weights[i - 1][0] = tmp;
+ Weights[i - 1][1] = tmp2;
+ }
}
float Sum = 0;
@@ -1056,7 +1072,7 @@ void MotionDetection::OpticalFlowCorrection()
if ((Distances[i][2] > Distances[i - 1][2]) ||
((Distances[i][2] == Distances[i - 1][2]) &&
(abs(Distances[i][0]) + abs(Distances[i][1]) <
- abs(Distances[i - 1][0]) + abs(Distances[i - 1][1]))))
+ abs(Distances[i - 1][0]) + abs(Distances[i - 1][1]))))
{
int tmp = Distances[i][0];
int tmp2 = Distances[i][1];
@@ -1331,10 +1347,10 @@ void MotionDetection::GetMotionsMaskHU(MEImage& mask_image)
MaskImgData[RowStart + x + (HUHistogramArea / 2)] =
((int)(x > 1 && HULBPPixelData[(x / 2) - 1][y]->BackgroundRate == 0.0) +
(int)(x < mask_image.GetWidth() - HUHistogramArea - 1 &&
- HULBPPixelData[(x / 2) + 1][y]->BackgroundRate == 0.0) +
- (int)(y > 0 && HULBPPixelData[x / 2][y - 1]->BackgroundRate == 0.0) +
- (int)(y < mask_image.GetHeight() - HUHistogramArea &&
- HULBPPixelData[x / 2][y + 1]->BackgroundRate == 0.0) > 1)
+ HULBPPixelData[(x / 2) + 1][y]->BackgroundRate == 0.0) +
+ (int)(y > 0 && HULBPPixelData[x / 2][y - 1]->BackgroundRate == 0.0) +
+ (int)(y < mask_image.GetHeight() - HUHistogramArea &&
+ HULBPPixelData[x / 2][y + 1]->BackgroundRate == 0.0) > 1)
? 255 : 0;
}
}
diff --git a/package_bgs/ck/MotionDetection.hpp b/package_bgs/LBP_MRF/MotionDetection.hpp
similarity index 93%
rename from package_bgs/ck/MotionDetection.hpp
rename to package_bgs/LBP_MRF/MotionDetection.hpp
index 6e11521..e58c93c 100644
--- a/package_bgs/ck/MotionDetection.hpp
+++ b/package_bgs/LBP_MRF/MotionDetection.hpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/*
* This file is part of the AiBO+ project
*
@@ -18,14 +34,12 @@
* Foundation, Inc., 59 Temple Street #330, Boston, MA 02111-1307, USA.
*
*/
+#pragma once
-#ifndef MotionDetection_hpp
-#define MotionDetection_hpp
-
-/**
- * @addtogroup mindeye
- * @{
- */
+ /**
+ * @addtogroup mindeye
+ * @{
+ */
#include "MEDefs.hpp"
#include "MEImage.hpp"
@@ -181,7 +195,7 @@ public:
*/
void CalculateResults(MEImage& referenceimage, int& tnegatives, int& tpositives,
- int& ttnegatives, int& ttpositives);
+ int& ttnegatives, int& ttpositives);
private:
@@ -397,5 +411,3 @@ private:
};
/** @} */
-
-#endif
diff --git a/package_bgs/ck/block.h b/package_bgs/LBP_MRF/block.h
similarity index 51%
rename from package_bgs/ck/block.h
rename to package_bgs/LBP_MRF/block.h
index 98b1201..bd1ab67 100644
--- a/package_bgs/ck/block.h
+++ b/package_bgs/LBP_MRF/block.h
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/* block.h */
/*
Copyright 2001 Vladimir Kolmogorov (vnk@cs.cornell.edu), Yuri Boykov (yuri@csd.uwo.ca).
@@ -16,8 +32,6 @@
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-
/*
Template classes Block and DBlock
Implement adding and deleting items of the same type in blocks.
@@ -105,9 +119,7 @@
simultaneously at earlier moments. All memory is
deallocated only when the destructor is called.
*/
-
-#ifndef __BLOCK_H__
-#define __BLOCK_H__
+#pragma once
#include <stdlib.h>
#include <stdio.h>
@@ -118,170 +130,168 @@
namespace ck
{
- template <class Type> class Block
- {
- public:
- /* Constructor. Arguments are the block size and
+template <class Type> class Block
+{
+public:
+ /* Constructor. Arguments are the block size and
(optionally) the pointer to the function which
will be called if allocation failed; the message
passed to this function is "Not enough memory!" */
- Block(int size, void(*err_function)(char *) = NULL) { first = last = NULL; block_size = size; error_function = err_function; }
+ Block(int size, void(*err_function)(char *) = NULL) { first = last = NULL; block_size = size; error_function = err_function; }
- /* Destructor. Deallocates all items added so far */
- ~Block() { while (first) { block *next = first->next; delete first; first = next; } }
+ /* Destructor. Deallocates all items added so far */
+ ~Block() { while (first) { block *next = first->next; delete first; first = next; } }
- /* Allocates 'num' consecutive items; returns pointer
+ /* Allocates 'num' consecutive items; returns pointer
to the first item. 'num' cannot be greater than the
block size since items must fit in one block */
- Type *New(int num = 1)
- {
- Type *t;
+ Type *New(int num = 1)
+ {
+ Type *t;
- if (!last || last->current + num > last->last)
+ if (!last || last->current + num > last->last)
+ {
+ if (last && last->next) last = last->next;
+ else
{
- if (last && last->next) last = last->next;
- else
- {
- block *next = (block *) new char[sizeof(block) + (block_size - 1)*sizeof(Type)];
- if (!next) { fprintf(stderr, "Not enough memory!"); exit(1); }
- if (last) last->next = next;
- else first = next;
- last = next;
- last->current = &(last->data[0]);
- last->last = last->current + block_size;
- last->next = NULL;
- }
+ block *next = (block *) new char[sizeof(block) + (block_size - 1)*sizeof(Type)];
+ if (!next) { fprintf(stderr, "Not enough memory!"); exit(1); }
+ if (last) last->next = next;
+ else first = next;
+ last = next;
+ last->current = &(last->data[0]);
+ last->last = last->current + block_size;
+ last->next = NULL;
}
-
- t = last->current;
- last->current += num;
- return t;
}
- /* Returns the first item (or NULL, if no items were added) */
- Type *ScanFirst()
- {
- scan_current_block = first;
- if (!scan_current_block) return NULL;
- scan_current_data = &(scan_current_block->data[0]);
- return scan_current_data++;
- }
+ t = last->current;
+ last->current += num;
+ return t;
+ }
+
+ /* Returns the first item (or NULL, if no items were added) */
+ Type *ScanFirst()
+ {
+ scan_current_block = first;
+ if (!scan_current_block) return NULL;
+ scan_current_data = &(scan_current_block->data[0]);
+ return scan_current_data++;
+ }
- /* Returns the next item (or NULL, if all items have been read)
+ /* Returns the next item (or NULL, if all items have been read)
Can be called only if previous ScanFirst() or ScanNext()
call returned not NULL. */
- Type *ScanNext()
+ Type *ScanNext()
+ {
+ if (scan_current_data >= scan_current_block->current)
{
- if (scan_current_data >= scan_current_block->current)
- {
- scan_current_block = scan_current_block->next;
- if (!scan_current_block) return NULL;
- scan_current_data = &(scan_current_block->data[0]);
- }
- return scan_current_data++;
+ scan_current_block = scan_current_block->next;
+ if (!scan_current_block) return NULL;
+ scan_current_data = &(scan_current_block->data[0]);
}
+ return scan_current_data++;
+ }
- /* Marks all elements as empty */
- void Reset()
+ /* Marks all elements as empty */
+ void Reset()
+ {
+ block *b;
+ if (!first) return;
+ for (b = first;; b = b->next)
{
- block *b;
- if (!first) return;
- for (b = first;; b = b->next)
- {
- b->current = &(b->data[0]);
- if (b == last) break;
- }
- last = first;
+ b->current = &(b->data[0]);
+ if (b == last) break;
}
+ last = first;
+ }
- /***********************************************************************/
+ /***********************************************************************/
- private:
+private:
- typedef struct block_st
- {
- Type *current, *last;
- struct block_st *next;
- Type data[1];
- } block;
+ typedef struct block_st
+ {
+ Type *current, *last;
+ struct block_st *next;
+ Type data[1];
+ } block;
- int block_size;
- block *first;
- block *last;
+ int block_size;
+ block *first;
+ block *last;
- block *scan_current_block;
- Type *scan_current_data;
+ block *scan_current_block;
+ Type *scan_current_data;
- void(*error_function)(char *);
- };
+ void(*error_function)(char *);
+};
- /***********************************************************************/
- /***********************************************************************/
- /***********************************************************************/
+/***********************************************************************/
+/***********************************************************************/
+/***********************************************************************/
- template <class Type> class DBlock
- {
- public:
- /* Constructor. Arguments are the block size and
+template <class Type> class DBlock
+{
+public:
+ /* Constructor. Arguments are the block size and
(optionally) the pointer to the function which
will be called if allocation failed; the message
passed to this function is "Not enough memory!" */
- DBlock(int size, void(*err_function)(char *) = NULL) { first = NULL; first_free = NULL; block_size = size; error_function = err_function; }
-
- /* Destructor. Deallocates all items added so far */
- ~DBlock() { while (first) { block *next = first->next; delete first; first = next; } }
-
- /* Allocates one item */
- Type *New()
- {
- block_item *item;
+ DBlock(int size, void(*err_function)(char *) = NULL) { first = NULL; first_free = NULL; block_size = size; error_function = err_function; }
- if (!first_free)
- {
- block *next = first;
- first = (block *) new char[sizeof(block) + (block_size - 1)*sizeof(block_item)];
- if (!first) { fprintf(stderr, "Not enough memory!"); exit(1); }
- first_free = &(first->data[0]);
- for (item = first_free; item < first_free + block_size - 1; item++)
- item->next_free = item + 1;
- item->next_free = NULL;
- first->next = next;
- }
+ /* Destructor. Deallocates all items added so far */
+ ~DBlock() { while (first) { block *next = first->next; delete first; first = next; } }
- item = first_free;
- first_free = item->next_free;
- return (Type *)item;
- }
+ /* Allocates one item */
+ Type *New()
+ {
+ block_item *item;
- /* Deletes an item allocated previously */
- void Delete(Type *t)
+ if (!first_free)
{
- ((block_item *)t)->next_free = first_free;
- first_free = (block_item *)t;
+ block *next = first;
+ first = (block *) new char[sizeof(block) + (block_size - 1)*sizeof(block_item)];
+ if (!first) { fprintf(stderr, "Not enough memory!"); exit(1); }
+ first_free = &(first->data[0]);
+ for (item = first_free; item < first_free + block_size - 1; item++)
+ item->next_free = item + 1;
+ item->next_free = NULL;
+ first->next = next;
}
- /***********************************************************************/
+ item = first_free;
+ first_free = item->next_free;
+ return (Type *)item;
+ }
- private:
+ /* Deletes an item allocated previously */
+ void Delete(Type *t)
+ {
+ ((block_item *)t)->next_free = first_free;
+ first_free = (block_item *)t;
+ }
- typedef union block_item_st
- {
- Type t;
- block_item_st *next_free;
- } block_item;
+ /***********************************************************************/
- typedef struct block_st
- {
- struct block_st *next;
- block_item data[1];
- } block;
+private:
- int block_size;
- block *first;
- block_item *first_free;
+ typedef union block_item_st
+ {
+ Type t;
+ block_item_st *next_free;
+ } block_item;
- void(*error_function)(char *);
- };
-}
+ typedef struct block_st
+ {
+ struct block_st *next;
+ block_item data[1];
+ } block;
+
+ int block_size;
+ block *first;
+ block_item *first_free;
-#endif
+ void(*error_function)(char *);
+};
+}
diff --git a/package_bgs/ck/graph.cpp b/package_bgs/LBP_MRF/graph.cpp
similarity index 78%
rename from package_bgs/ck/graph.cpp
rename to package_bgs/LBP_MRF/graph.cpp
index daed395..9301250 100644
--- a/package_bgs/ck/graph.cpp
+++ b/package_bgs/LBP_MRF/graph.cpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/* graph.cpp */
/*
Copyright 2001 Vladimir Kolmogorov (vnk@cs.cornell.edu), Yuri Boykov (yuri@csd.uwo.ca).
@@ -80,4 +96,4 @@ namespace ck
flow += (cap_source < cap_sink) ? cap_source : cap_sink;
((node*)i)->tr_cap = cap_source - cap_sink;
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/ck/graph.h b/package_bgs/LBP_MRF/graph.h
similarity index 60%
rename from package_bgs/ck/graph.h
rename to package_bgs/LBP_MRF/graph.h
index b6799e4..e7b83c7 100644
--- a/package_bgs/ck/graph.h
+++ b/package_bgs/LBP_MRF/graph.h
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/* graph.h */
/*
This software library implements the maxflow algorithm
@@ -16,41 +32,36 @@
If you use this software for research purposes, you should cite
the aforementioned paper in any resulting publication.
*/
-
-/*
- Copyright 2001 Vladimir Kolmogorov (vnk@cs.cornell.edu), Yuri Boykov (yuri@csd.uwo.ca).
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation; either version 2 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program; if not, write to the Free Software
- Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
- */
-
-
-/*
- For description, example usage, discussion of graph representation
- and memory usage see README.TXT.
- */
-
-#ifndef __GRAPH_H__
-#define __GRAPH_H__
+ /*
+ Copyright 2001 Vladimir Kolmogorov (vnk@cs.cornell.edu), Yuri Boykov (yuri@csd.uwo.ca).
+
+ This program is free software; you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation; either version 2 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program; if not, write to the Free Software
+ Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+ */
+ /*
+ For description, example usage, discussion of graph representation
+ and memory usage see README.TXT.
+ */
+#pragma once
#include "block.h"
-/*
- Nodes, arcs and pointers to nodes are
- added in blocks for memory and time efficiency.
- Below are numbers of items in blocks
- */
+ /*
+ Nodes, arcs and pointers to nodes are
+ added in blocks for memory and time efficiency.
+ Below are numbers of items in blocks
+ */
#define NODE_BLOCK_SIZE 512
#define ARC_BLOCK_SIZE 1024
#define NODEPTR_BLOCK_SIZE 128
@@ -67,7 +78,7 @@ namespace ck
} termtype; /* terminals */
/* Type of edge weights.
- Can be changed to char, int, float, double, ... */
+ Can be changed to char, int, float, double, ... */
typedef short captype;
/* Type of total flow */
typedef int flowtype;
@@ -77,9 +88,9 @@ namespace ck
/* interface functions */
/* Constructor. Optional argument is the pointer to the
- function which will be called if an error occurs;
- an error message is passed to this function. If this
- argument is omitted, exit(1) will be called. */
+ function which will be called if an error occurs;
+ an error message is passed to this function. If this
+ argument is omitted, exit(1) will be called. */
Graph(void(*err_function)(char *) = NULL);
/* Destructor */
@@ -89,21 +100,21 @@ namespace ck
node_id add_node();
/* Adds a bidirectional edge between 'from' and 'to'
- with the weights 'cap' and 'rev_cap' */
+ with the weights 'cap' and 'rev_cap' */
void add_edge(node_id from, node_id to, captype cap, captype rev_cap);
/* Sets the weights of the edges 'SOURCE->i' and 'i->SINK'
- Can be called at most once for each node before any call to 'add_tweights'.
- Weights can be negative */
+ Can be called at most once for each node before any call to 'add_tweights'.
+ Weights can be negative */
void set_tweights(node_id i, captype cap_source, captype cap_sink);
/* Adds new edges 'SOURCE->i' and 'i->SINK' with corresponding weights
- Can be called multiple times for each node.
- Weights can be negative */
+ Can be called multiple times for each node.
+ Weights can be negative */
void add_tweights(node_id i, captype cap_source, captype cap_sink);
/* After the maxflow is computed, this function returns to which
- segment the node 'i' belongs (Graph::SOURCE or Graph::SINK) */
+ segment the node 'i' belongs (Graph::SOURCE or Graph::SINK) */
termtype what_segment(node_id i);
/* Computes the maxflow. Can be called only once. */
@@ -125,13 +136,13 @@ namespace ck
arc_st *parent; /* node's parent */
node_st *next; /* pointer to the next active node
- (or to itself if it is the last node in the list) */
+ (or to itself if it is the last node in the list) */
int TS; /* timestamp showing when DIST was computed */
int DIST; /* distance to the terminal */
short is_sink; /* flag showing whether the node is in the source or in the sink tree */
captype tr_cap; /* if tr_cap > 0 then tr_cap is residual capacity of the arc SOURCE->node
- otherwise -tr_cap is residual capacity of the arc node->SINK */
+ otherwise -tr_cap is residual capacity of the arc node->SINK */
} node;
/* arc structure */
@@ -156,8 +167,8 @@ namespace ck
DBlock<nodeptr> *nodeptr_block;
void(*error_function)(char *); /* this function is called if a error occurs,
- with a corresponding error message
- (or exit(1) is called if it's NULL) */
+ with a corresponding error message
+ (or exit(1) is called if it's NULL) */
flowtype flow; /* total flow */
@@ -179,5 +190,3 @@ namespace ck
void process_sink_orphan(node *i);
};
}
-
-#endif
diff --git a/package_bgs/ck/maxflow.cpp b/package_bgs/LBP_MRF/maxflow.cpp
similarity index 67%
rename from package_bgs/ck/maxflow.cpp
rename to package_bgs/LBP_MRF/maxflow.cpp
index 53d3705..6ddec50 100644
--- a/package_bgs/ck/maxflow.cpp
+++ b/package_bgs/LBP_MRF/maxflow.cpp
@@ -1,3 +1,19 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
/* maxflow.cpp */
/*
Copyright 2001 Vladimir Kolmogorov (vnk@cs.cornell.edu), Yuri Boykov (yuri@csd.uwo.ca).
@@ -16,33 +32,31 @@
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-
#include <stdio.h>
#include "graph.h"
-/*
- special constants for node->parent
- */
+ /*
+ special constants for node->parent
+ */
#define TERMINAL ( (arc *) 1 ) /* to terminal */
#define ORPHAN ( (arc *) 2 ) /* orphan */
#define INFINITE_D 1000000000 /* infinite distance to the terminal */
-/***********************************************************************/
+ /***********************************************************************/
-/*
- Functions for processing active list.
- i->next points to the next node in the list
- (or to i, if i is the last node in the list).
- If i->next is NULL iff i is not in the list.
-
- There are two queues. Active nodes are added
- to the end of the second queue and read from
- the front of the first queue. If the first queue
- is empty, it is replaced by the second queue
- (and the second queue becomes empty).
- */
+ /*
+ Functions for processing active list.
+ i->next points to the next node in the list
+ (or to i, if i is the last node in the list).
+ If i->next is NULL iff i is not in the list.
+
+ There are two queues. Active nodes are added
+ to the end of the second queue and read from
+ the front of the first queue. If the first queue
+ is empty, it is replaced by the second queue
+ (and the second queue becomes empty).
+ */
namespace ck
{
inline void Graph::set_active(node *i)
@@ -58,10 +72,10 @@ namespace ck
}
/*
- Returns the next active node.
- If it is connected to the sink, it stays in the list,
- otherwise it is removed from the list
- */
+ Returns the next active node.
+ If it is connected to the sink, it stays in the list,
+ otherwise it is removed from the list
+ */
inline Graph::node * Graph::next_active()
{
node *i;
@@ -232,45 +246,45 @@ namespace ck
for (a0 = i->first; a0; a0 = a0->next)
if (a0->sister->r_cap)
{
- j = a0->head;
- if (!j->is_sink && (a = j->parent))
- {
- /* checking the origin of j */
- d = 0;
- while (1)
- {
- if (j->TS == TIME)
- {
- d += j->DIST;
- break;
- }
- a = j->parent;
- d++;
- if (a == TERMINAL)
- {
- j->TS = TIME;
- j->DIST = 1;
- break;
- }
- if (a == ORPHAN) { d = INFINITE_D; break; }
- j = a->head;
- }
- if (d < INFINITE_D) /* j originates from the source - done */
+ j = a0->head;
+ if (!j->is_sink && (a = j->parent))
{
- if (d < d_min)
+ /* checking the origin of j */
+ d = 0;
+ while (1)
{
- a0_min = a0;
- d_min = d;
+ if (j->TS == TIME)
+ {
+ d += j->DIST;
+ break;
+ }
+ a = j->parent;
+ d++;
+ if (a == TERMINAL)
+ {
+ j->TS = TIME;
+ j->DIST = 1;
+ break;
+ }
+ if (a == ORPHAN) { d = INFINITE_D; break; }
+ j = a->head;
}
- /* set marks along the path */
- for (j = a0->head; j->TS != TIME; j = j->parent->head)
+ if (d < INFINITE_D) /* j originates from the source - done */
{
- j->TS = TIME;
- j->DIST = d--;
+ if (d < d_min)
+ {
+ a0_min = a0;
+ d_min = d;
+ }
+ /* set marks along the path */
+ for (j = a0->head; j->TS != TIME; j = j->parent->head)
+ {
+ j->TS = TIME;
+ j->DIST = d--;
+ }
}
}
}
- }
if ((i->parent = a0_min))
{
@@ -316,45 +330,45 @@ namespace ck
for (a0 = i->first; a0; a0 = a0->next)
if (a0->r_cap)
{
- j = a0->head;
- if (j->is_sink && (a = j->parent))
- {
- /* checking the origin of j */
- d = 0;
- while (1)
- {
- if (j->TS == TIME)
- {
- d += j->DIST;
- break;
- }
- a = j->parent;
- d++;
- if (a == TERMINAL)
- {
- j->TS = TIME;
- j->DIST = 1;
- break;
- }
- if (a == ORPHAN) { d = INFINITE_D; break; }
- j = a->head;
- }
- if (d < INFINITE_D) /* j originates from the sink - done */
+ j = a0->head;
+ if (j->is_sink && (a = j->parent))
{
- if (d < d_min)
+ /* checking the origin of j */
+ d = 0;
+ while (1)
{
- a0_min = a0;
- d_min = d;
+ if (j->TS == TIME)
+ {
+ d += j->DIST;
+ break;
+ }
+ a = j->parent;
+ d++;
+ if (a == TERMINAL)
+ {
+ j->TS = TIME;
+ j->DIST = 1;
+ break;
+ }
+ if (a == ORPHAN) { d = INFINITE_D; break; }
+ j = a->head;
}
- /* set marks along the path */
- for (j = a0->head; j->TS != TIME; j = j->parent->head)
+ if (d < INFINITE_D) /* j originates from the sink - done */
{
- j->TS = TIME;
- j->DIST = d--;
+ if (d < d_min)
+ {
+ a0_min = a0;
+ d_min = d;
+ }
+ /* set marks along the path */
+ for (j = a0->head; j->TS != TIME; j = j->parent->head)
+ {
+ j->TS = TIME;
+ j->DIST = d--;
+ }
}
}
}
- }
if ((i->parent = a0_min))
{
@@ -419,24 +433,24 @@ namespace ck
for (a = i->first; a; a = a->next)
if (a->r_cap)
{
- j = a->head;
- if (!j->parent)
- {
- j->is_sink = 0;
- j->parent = a->sister;
- j->TS = i->TS;
- j->DIST = i->DIST + 1;
- set_active(j);
- }
- else if (j->is_sink) break;
- else if (j->TS <= i->TS &&
- j->DIST > i->DIST)
- {
- /* heuristic - trying to make the distance from j to the source shorter */
- j->parent = a->sister;
- j->TS = i->TS;
- j->DIST = i->DIST + 1;
- }
+ j = a->head;
+ if (!j->parent)
+ {
+ j->is_sink = 0;
+ j->parent = a->sister;
+ j->TS = i->TS;
+ j->DIST = i->DIST + 1;
+ set_active(j);
+ }
+ else if (j->is_sink) break;
+ else if (j->TS <= i->TS &&
+ j->DIST > i->DIST)
+ {
+ /* heuristic - trying to make the distance from j to the source shorter */
+ j->parent = a->sister;
+ j->TS = i->TS;
+ j->DIST = i->DIST + 1;
+ }
}
}
else
@@ -445,24 +459,24 @@ namespace ck
for (a = i->first; a; a = a->next)
if (a->sister->r_cap)
{
- j = a->head;
- if (!j->parent)
- {
- j->is_sink = 1;
- j->parent = a->sister;
- j->TS = i->TS;
- j->DIST = i->DIST + 1;
- set_active(j);
- }
- else if (!j->is_sink) { a = a->sister; break; }
- else if (j->TS <= i->TS &&
- j->DIST > i->DIST)
- {
- /* heuristic - trying to make the distance from j to the sink shorter */
- j->parent = a->sister;
- j->TS = i->TS;
- j->DIST = i->DIST + 1;
- }
+ j = a->head;
+ if (!j->parent)
+ {
+ j->is_sink = 1;
+ j->parent = a->sister;
+ j->TS = i->TS;
+ j->DIST = i->DIST + 1;
+ set_active(j);
+ }
+ else if (!j->is_sink) { a = a->sister; break; }
+ else if (j->TS <= i->TS &&
+ j->DIST > i->DIST)
+ {
+ /* heuristic - trying to make the distance from j to the sink shorter */
+ j->parent = a->sister;
+ j->TS = i->TS;
+ j->DIST = i->DIST + 1;
+ }
}
}
@@ -513,4 +527,4 @@ namespace ck
return SINK;
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/LBSP/BackgroundSubtractorLBSP.cpp b/package_bgs/LBSP/BackgroundSubtractorLBSP.cpp
new file mode 100644
index 0000000..2865a30
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorLBSP.cpp
@@ -0,0 +1,85 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "BackgroundSubtractorLBSP.h"
+#include "DistanceUtils.h"
+#include "RandUtils.h"
+#include <iostream>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <iomanip>
+#include <exception>
+
+#ifndef SIZE_MAX
+# if __WORDSIZE == 64
+# define SIZE_MAX (18446744073709551615UL)
+# else
+# define SIZE_MAX (4294967295U)
+# endif
+#endif
+
+// local define used to determine the default median blur kernel size
+#define DEFAULT_MEDIAN_BLUR_KERNEL_SIZE (9)
+
+BackgroundSubtractorLBSP::BackgroundSubtractorLBSP(float fRelLBSPThreshold, size_t nLBSPThresholdOffset)
+ : m_nImgChannels(0)
+ , m_nImgType(0)
+ , m_nLBSPThresholdOffset(nLBSPThresholdOffset)
+ , m_fRelLBSPThreshold(fRelLBSPThreshold)
+ , m_nTotPxCount(0)
+ , m_nTotRelevantPxCount(0)
+ , m_nFrameIndex(SIZE_MAX)
+ , m_nFramesSinceLastReset(0)
+ , m_nModelResetCooldown(0)
+ , m_aPxIdxLUT(nullptr)
+ , m_aPxInfoLUT(nullptr)
+ , m_nDefaultMedianBlurKernelSize(DEFAULT_MEDIAN_BLUR_KERNEL_SIZE)
+ , m_bInitialized(false)
+ , m_bAutoModelResetEnabled(true)
+ , m_bUsingMovingCamera(false)
+ , nDebugCoordX(0), nDebugCoordY(0) {
+ CV_Assert(m_fRelLBSPThreshold >= 0);
+}
+
+BackgroundSubtractorLBSP::~BackgroundSubtractorLBSP() {}
+
+void BackgroundSubtractorLBSP::initialize(const cv::Mat& oInitImg) {
+ this->initialize(oInitImg, cv::Mat());
+}
+
+/*cv::AlgorithmInfo* BackgroundSubtractorLBSP::info() const {
+ return nullptr;
+}*/
+
+cv::Mat BackgroundSubtractorLBSP::getROICopy() const {
+ return m_oROI.clone();
+}
+
+void BackgroundSubtractorLBSP::setROI(cv::Mat& oROI) {
+ LBSP::validateROI(oROI);
+ CV_Assert(cv::countNonZero(oROI) > 0);
+ if (m_bInitialized) {
+ cv::Mat oLatestBackgroundImage;
+ getBackgroundImage(oLatestBackgroundImage);
+ initialize(oLatestBackgroundImage, oROI);
+ }
+ else
+ m_oROI = oROI.clone();
+}
+
+void BackgroundSubtractorLBSP::setAutomaticModelReset(bool bVal) {
+ m_bAutoModelResetEnabled = bVal;
+}
diff --git a/package_bgs/LBSP/BackgroundSubtractorLBSP.h b/package_bgs/LBSP/BackgroundSubtractorLBSP.h
new file mode 100644
index 0000000..ef0576c
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorLBSP.h
@@ -0,0 +1,101 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <opencv2/features2d/features2d.hpp>
+#include <opencv2/video/background_segm.hpp>
+#include "LBSP.h"
+
+/*!
+ Local Binary Similarity Pattern (LBSP)-based change detection algorithm (abstract version/base class).
+
+ For more details on the different parameters, see P.-L. St-Charles and G.-A. Bilodeau, "Improving Background
+ Subtraction using Local Binary Similarity Patterns", in WACV 2014, or G.-A. Bilodeau et al, "Change Detection
+ in Feature Space Using Local Binary Similarity Patterns", in CRV 2013.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class BackgroundSubtractorLBSP : public cv::BackgroundSubtractor {
+public:
+ //! full constructor
+ BackgroundSubtractorLBSP(float fRelLBSPThreshold, size_t nLBSPThresholdOffset = 0);
+ //! default destructor
+ virtual ~BackgroundSubtractorLBSP();
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg);
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) = 0;
+ //! primary model update function; the learning param is used to override the internal learning speed (ignored when <= 0)
+ virtual void apply(cv::InputArray image, cv::OutputArray fgmask, double learningRate = 0) = 0;
+ //! unused, always returns nullptr
+ //virtual cv::AlgorithmInfo* info() const;
+ //! returns a copy of the ROI used for descriptor extraction
+ virtual cv::Mat getROICopy() const;
+ //! sets the ROI to be used for descriptor extraction (note: this function will reinit the model and return the usable ROI)
+ virtual void setROI(cv::Mat& oROI);
+ //! turns automatic model reset on or off
+ void setAutomaticModelReset(bool);
+
+protected:
+ struct PxInfoBase {
+ int nImgCoord_Y;
+ int nImgCoord_X;
+ size_t nModelIdx;
+ };
+ //! background model ROI used for LBSP descriptor extraction (specific to the input image size)
+ cv::Mat m_oROI;
+ //! input image size
+ cv::Size m_oImgSize;
+ //! input image channel size
+ size_t m_nImgChannels;
+ //! input image type
+ int m_nImgType;
+ //! LBSP internal threshold offset value, used to reduce texture noise in dark regions
+ const size_t m_nLBSPThresholdOffset;
+ //! LBSP relative internal threshold (kept here since we don't keep an LBSP object)
+ const float m_fRelLBSPThreshold;
+ //! total number of pixels (depends on the input frame size) & total number of relevant pixels
+ size_t m_nTotPxCount, m_nTotRelevantPxCount;
+ //! current frame index, frame count since last model reset & model reset cooldown counters
+ size_t m_nFrameIndex, m_nFramesSinceLastReset, m_nModelResetCooldown;
+ //! pre-allocated internal LBSP threshold values LUT for all possible 8-bit intensities
+ size_t m_anLBSPThreshold_8bitLUT[UCHAR_MAX + 1];
+ //! internal pixel index LUT for all relevant analysis regions (based on the provided ROI)
+ size_t* m_aPxIdxLUT;
+ //! internal pixel info LUT for all possible pixel indexes
+ PxInfoBase* m_aPxInfoLUT;
+ //! default kernel size for median blur post-proc filtering
+ const int m_nDefaultMedianBlurKernelSize;
+ //! specifies whether the algorithm is fully initialized or not
+ bool m_bInitialized;
+ //! specifies whether automatic model resets are enabled or not
+ bool m_bAutoModelResetEnabled;
+ //! specifies whether the camera is considered moving or not
+ bool m_bUsingMovingCamera;
+ //! copy of latest pixel intensities (used when refreshing model)
+ cv::Mat m_oLastColorFrame;
+ //! copy of latest descriptors (used when refreshing model)
+ cv::Mat m_oLastDescFrame;
+ //! the foreground mask generated by the method at [t-1]
+ cv::Mat m_oLastFGMask;
+
+public:
+ // ######## DEBUG PURPOSES ONLY ##########
+ int nDebugCoordX, nDebugCoordY;
+ std::string sDebugName;
+};
+
diff --git a/package_bgs/LBSP/BackgroundSubtractorLBSP_.cpp b/package_bgs/LBSP/BackgroundSubtractorLBSP_.cpp
new file mode 100644
index 0000000..4e5d4a6
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorLBSP_.cpp
@@ -0,0 +1,79 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "BackgroundSubtractorLBSP_.h"
+#include "DistanceUtils.h"
+#include "RandUtils.h"
+#include <iostream>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <iomanip>
+#include <exception>
+
+// local define used to determine the default median blur kernel size
+#define DEFAULT_MEDIAN_BLUR_KERNEL_SIZE (9)
+
+BackgroundSubtractorLBSP_::BackgroundSubtractorLBSP_(float fRelLBSPThreshold, size_t nLBSPThresholdOffset)
+ : m_nImgChannels(0)
+ , m_nImgType(0)
+ , m_nLBSPThresholdOffset(nLBSPThresholdOffset)
+ , m_fRelLBSPThreshold(fRelLBSPThreshold)
+ , m_nTotPxCount(0)
+ , m_nTotRelevantPxCount(0)
+ , m_nFrameIndex(SIZE_MAX)
+ , m_nFramesSinceLastReset(0)
+ , m_nModelResetCooldown(0)
+ , m_aPxIdxLUT(nullptr)
+ , m_aPxInfoLUT(nullptr)
+ , m_nDefaultMedianBlurKernelSize(DEFAULT_MEDIAN_BLUR_KERNEL_SIZE)
+ , m_bInitialized(false)
+ , m_bAutoModelResetEnabled(true)
+ , m_bUsingMovingCamera(false)
+ , m_nDebugCoordX(0)
+ , m_nDebugCoordY(0)
+ , m_pDebugFS(nullptr) {
+ CV_Assert(m_fRelLBSPThreshold >= 0);
+}
+
+BackgroundSubtractorLBSP_::~BackgroundSubtractorLBSP_() {}
+
+void BackgroundSubtractorLBSP_::initialize(const cv::Mat& oInitImg) {
+ this->initialize(oInitImg, cv::Mat());
+}
+/*
+cv::AlgorithmInfo* BackgroundSubtractorLBSP_::info() const {
+ return nullptr;
+}
+*/
+cv::Mat BackgroundSubtractorLBSP_::getROICopy() const {
+ return m_oROI.clone();
+}
+
+void BackgroundSubtractorLBSP_::setROI(cv::Mat& oROI) {
+ LBSP_::validateROI(oROI);
+ CV_Assert(cv::countNonZero(oROI) > 0);
+ if (m_bInitialized) {
+ cv::Mat oLatestBackgroundImage;
+ getBackgroundImage(oLatestBackgroundImage);
+ initialize(oLatestBackgroundImage, oROI);
+ }
+ else
+ m_oROI = oROI.clone();
+}
+
+void BackgroundSubtractorLBSP_::setAutomaticModelReset(bool bVal) {
+ m_bAutoModelResetEnabled = bVal;
+}
diff --git a/package_bgs/LBSP/BackgroundSubtractorLBSP_.h b/package_bgs/LBSP/BackgroundSubtractorLBSP_.h
new file mode 100644
index 0000000..861f78a
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorLBSP_.h
@@ -0,0 +1,107 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <opencv2/features2d/features2d.hpp>
+#include <opencv2/video/background_segm.hpp>
+#include "LBSP_.h"
+
+/*!
+ Local Binary Similarity Pattern (LBSP)-based change detection algorithm (abstract version/base class).
+
+ For more details on the different parameters, see P.-L. St-Charles and G.-A. Bilodeau, "Improving Background
+ Subtraction using Local Binary Similarity Patterns", in WACV 2014, or G.-A. Bilodeau et al, "Change Detection
+ in Feature Space Using Local Binary Similarity Patterns", in CRV 2013.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class BackgroundSubtractorLBSP_ : public cv::BackgroundSubtractor {
+public:
+ //! full constructor
+ BackgroundSubtractorLBSP_(float fRelLBSPThreshold, size_t nLBSPThresholdOffset = 0);
+ //! default destructor
+ virtual ~BackgroundSubtractorLBSP_();
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg);
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) = 0;
+ //! primary model update function; the learning param is used to override the internal learning speed (ignored when <= 0)
+ virtual void apply(cv::InputArray image, cv::OutputArray fgmask, double learningRate = 0) = 0;
+ //! unused, always returns nullptr
+ //virtual cv::AlgorithmInfo* info() const;
+ //! returns a copy of the ROI used for descriptor extraction
+ virtual cv::Mat getROICopy() const;
+ //! sets the ROI to be used for descriptor extraction (note: this function will reinit the model and return the usable ROI)
+ virtual void setROI(cv::Mat& oROI);
+ //! turns automatic model reset on or off
+ void setAutomaticModelReset(bool);
+
+protected:
+ struct PxInfoBase {
+ int nImgCoord_Y;
+ int nImgCoord_X;
+ size_t nModelIdx;
+ };
+ //! background model ROI used for LBSP descriptor extraction (specific to the input image size)
+ cv::Mat m_oROI;
+ //! input image size
+ cv::Size m_oImgSize;
+ //! input image channel size
+ size_t m_nImgChannels;
+ //! input image type
+ int m_nImgType;
+ //! LBSP internal threshold offset value, used to reduce texture noise in dark regions
+ const size_t m_nLBSPThresholdOffset;
+ //! LBSP relative internal threshold (kept here since we don't keep an LBSP object)
+ const float m_fRelLBSPThreshold;
+ //! total number of pixels (depends on the input frame size) & total number of relevant pixels
+ size_t m_nTotPxCount, m_nTotRelevantPxCount;
+ //! current frame index, frame count since last model reset & model reset cooldown counters
+ size_t m_nFrameIndex, m_nFramesSinceLastReset, m_nModelResetCooldown;
+ //! pre-allocated internal LBSP threshold values LUT for all possible 8-bit intensities
+ size_t m_anLBSPThreshold_8bitLUT[UCHAR_MAX + 1];
+ //! internal pixel index LUT for all relevant analysis regions (based on the provided ROI)
+ size_t* m_aPxIdxLUT;
+ //! internal pixel info LUT for all possible pixel indexes
+ PxInfoBase* m_aPxInfoLUT;
+ //! default kernel size for median blur post-proc filtering
+ const int m_nDefaultMedianBlurKernelSize;
+ //! specifies whether the algorithm is fully initialized or not
+ bool m_bInitialized;
+ //! specifies whether automatic model resets are enabled or not
+ bool m_bAutoModelResetEnabled;
+ //! specifies whether the camera is considered moving or not
+ bool m_bUsingMovingCamera;
+ //! copy of latest pixel intensities (used when refreshing model)
+ cv::Mat m_oLastColorFrame;
+ //! copy of latest descriptors (used when refreshing model)
+ cv::Mat m_oLastDescFrame;
+ //! the foreground mask generated by the method at [t-1]
+ cv::Mat m_oLastFGMask;
+
+private:
+ //! copy constructor -- disabled since this class (and its children) use lots of dynamic structs based on raw pointers
+ BackgroundSubtractorLBSP_(const BackgroundSubtractorLBSP_&);
+ //! assignment operator -- disabled since this class (and its children) use lots of dynamic structs based on raw pointers
+ BackgroundSubtractorLBSP_& operator=(const BackgroundSubtractorLBSP_&);
+
+public:
+ // ######## DEBUG PURPOSES ONLY ##########
+ int m_nDebugCoordX, m_nDebugCoordY;
+ std::string m_sDebugName;
+ cv::FileStorage* m_pDebugFS;
+};
diff --git a/package_bgs/LBSP/BackgroundSubtractorLOBSTER.cpp b/package_bgs/LBSP/BackgroundSubtractorLOBSTER.cpp
new file mode 100644
index 0000000..9648c5c
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorLOBSTER.cpp
@@ -0,0 +1,342 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "BackgroundSubtractorLOBSTER.h"
+#include "DistanceUtils.h"
+#include "RandUtils.h"
+#include <iostream>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <iomanip>
+
+BackgroundSubtractorLOBSTER::BackgroundSubtractorLOBSTER(float fRelLBSPThreshold
+ , size_t nLBSPThresholdOffset
+ , size_t nDescDistThreshold
+ , size_t nColorDistThreshold
+ , size_t nBGSamples
+ , size_t nRequiredBGSamples)
+ : BackgroundSubtractorLBSP(fRelLBSPThreshold, nLBSPThresholdOffset)
+ , m_nColorDistThreshold(nColorDistThreshold)
+ , m_nDescDistThreshold(nDescDistThreshold)
+ , m_nBGSamples(nBGSamples)
+ , m_nRequiredBGSamples(nRequiredBGSamples) {
+ CV_Assert(m_nRequiredBGSamples <= m_nBGSamples);
+ m_bAutoModelResetEnabled = false; // @@@@@@ not supported here for now
+}
+
+BackgroundSubtractorLOBSTER::~BackgroundSubtractorLOBSTER() {
+ if (m_aPxIdxLUT)
+ delete[] m_aPxIdxLUT;
+ if (m_aPxInfoLUT)
+ delete[] m_aPxInfoLUT;
+}
+
+void BackgroundSubtractorLOBSTER::initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) {
+ CV_Assert(!oInitImg.empty() && oInitImg.cols > 0 && oInitImg.rows > 0);
+ CV_Assert(oInitImg.isContinuous());
+ CV_Assert(oInitImg.type() == CV_8UC1 || oInitImg.type() == CV_8UC3);
+ if (oInitImg.type() == CV_8UC3) {
+ std::vector<cv::Mat> voInitImgChannels;
+ cv::split(oInitImg, voInitImgChannels);
+ if (!cv::countNonZero((voInitImgChannels[0] != voInitImgChannels[1]) | (voInitImgChannels[2] != voInitImgChannels[1])))
+ std::cout << std::endl << "\tBackgroundSubtractorLOBSTER : Warning, grayscale images should always be passed in CV_8UC1 format for optimal performance." << std::endl;
+ }
+ cv::Mat oNewBGROI;
+ if (oROI.empty() && (m_oROI.empty() || oROI.size() != oInitImg.size())) {
+ oNewBGROI.create(oInitImg.size(), CV_8UC1);
+ oNewBGROI = cv::Scalar_<uchar>(UCHAR_MAX);
+ }
+ else if (oROI.empty())
+ oNewBGROI = m_oROI;
+ else {
+ CV_Assert(oROI.size() == oInitImg.size() && oROI.type() == CV_8UC1);
+ CV_Assert(cv::countNonZero((oROI < UCHAR_MAX)&(oROI > 0)) == 0);
+ oNewBGROI = oROI.clone();
+ }
+ LBSP::validateROI(oNewBGROI);
+ const size_t nROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
+ CV_Assert(nROIPxCount > 0);
+ m_oROI = oNewBGROI;
+ m_oImgSize = oInitImg.size();
+ m_nImgType = oInitImg.type();
+ m_nImgChannels = oInitImg.channels();
+ m_nTotPxCount = m_oImgSize.area();
+ m_nTotRelevantPxCount = nROIPxCount;
+ m_nFrameIndex = 0;
+ m_nFramesSinceLastReset = 0;
+ m_nModelResetCooldown = 0;
+ m_oLastFGMask.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask = cv::Scalar_<uchar>(0);
+ m_oLastColorFrame.create(m_oImgSize, CV_8UC((int)m_nImgChannels));
+ m_oLastColorFrame = cv::Scalar_<uchar>::all(0);
+ m_oLastDescFrame.create(m_oImgSize, CV_16UC((int)m_nImgChannels));
+ m_oLastDescFrame = cv::Scalar_<ushort>::all(0);
+ m_voBGColorSamples.resize(m_nBGSamples);
+ m_voBGDescSamples.resize(m_nBGSamples);
+ for (size_t s = 0; s < m_nBGSamples; ++s) {
+ m_voBGColorSamples[s].create(m_oImgSize, CV_8UC((int)m_nImgChannels));
+ m_voBGColorSamples[s] = cv::Scalar_<uchar>::all(0);
+ m_voBGDescSamples[s].create(m_oImgSize, CV_16UC((int)m_nImgChannels));
+ m_voBGDescSamples[s] = cv::Scalar_<ushort>::all(0);
+ }
+ if (m_aPxIdxLUT)
+ delete[] m_aPxIdxLUT;
+ if (m_aPxInfoLUT)
+ delete[] m_aPxInfoLUT;
+ m_aPxIdxLUT = new size_t[m_nTotRelevantPxCount];
+ m_aPxInfoLUT = new PxInfoBase[m_nTotPxCount];
+ if (m_nImgChannels == 1) {
+ CV_Assert(m_oLastColorFrame.step.p[0] == (size_t)m_oImgSize.width && m_oLastColorFrame.step.p[1] == 1);
+ CV_Assert(m_oLastDescFrame.step.p[0] == m_oLastColorFrame.step.p[0] * 2 && m_oLastDescFrame.step.p[1] == m_oLastColorFrame.step.p[1] * 2);
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>((t*m_fRelLBSPThreshold + m_nLBSPThresholdOffset) / 2);
+ for (size_t nPxIter = 0, nModelIter = 0; nPxIter < m_nTotPxCount; ++nPxIter) {
+ if (m_oROI.data[nPxIter]) {
+ m_aPxIdxLUT[nModelIter] = nPxIter;
+ m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter / m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
+ m_oLastColorFrame.data[nPxIter] = oInitImg.data[nPxIter];
+ const size_t nDescIter = nPxIter * 2;
+ LBSP::computeGrayscaleDescriptor(oInitImg, oInitImg.data[nPxIter], m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxIter]], *((ushort*)(m_oLastDescFrame.data + nDescIter)));
+ ++nModelIter;
+ }
+ }
+ }
+ else { //m_nImgChannels==3
+ CV_Assert(m_oLastColorFrame.step.p[0] == (size_t)m_oImgSize.width * 3 && m_oLastColorFrame.step.p[1] == 3);
+ CV_Assert(m_oLastDescFrame.step.p[0] == m_oLastColorFrame.step.p[0] * 2 && m_oLastDescFrame.step.p[1] == m_oLastColorFrame.step.p[1] * 2);
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>(t*m_fRelLBSPThreshold + m_nLBSPThresholdOffset);
+ for (size_t nPxIter = 0, nModelIter = 0; nPxIter < m_nTotPxCount; ++nPxIter) {
+ if (m_oROI.data[nPxIter]) {
+ m_aPxIdxLUT[nModelIter] = nPxIter;
+ m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter / m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
+ const size_t nPxRGBIter = nPxIter * 3;
+ const size_t nDescRGBIter = nPxRGBIter * 2;
+ for (size_t c = 0; c < 3; ++c) {
+ m_oLastColorFrame.data[nPxRGBIter + c] = oInitImg.data[nPxRGBIter + c];
+ LBSP::computeSingleRGBDescriptor(oInitImg, oInitImg.data[nPxRGBIter + c], m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, c, m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxRGBIter + c]], ((ushort*)(m_oLastDescFrame.data + nDescRGBIter))[c]);
+ }
+ ++nModelIter;
+ }
+ }
+ }
+ m_bInitialized = true;
+ refreshModel(1.0f);
+}
+
+void BackgroundSubtractorLOBSTER::refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate) {
+ // == refresh
+ CV_Assert(m_bInitialized);
+ CV_Assert(fSamplesRefreshFrac > 0.0f && fSamplesRefreshFrac <= 1.0f);
+ const size_t nModelsToRefresh = fSamplesRefreshFrac < 1.0f ? (size_t)(fSamplesRefreshFrac*m_nBGSamples) : m_nBGSamples;
+ const size_t nRefreshStartPos = fSamplesRefreshFrac < 1.0f ? rand() % m_nBGSamples : 0;
+ if (m_nImgChannels == 1) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if (bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
+ for (size_t nCurrModelIdx = nRefreshStartPos; nCurrModelIdx < nRefreshStartPos + nModelsToRefresh; ++nCurrModelIdx) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandSamplePosition(nSampleImgCoord_X, nSampleImgCoord_Y, m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
+ const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
+ m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter] = m_oLastColorFrame.data[nSamplePxIdx];
+ *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data + nPxIter * 2)) = *((ushort*)(m_oLastDescFrame.data + nSamplePxIdx * 2));
+ }
+ }
+ }
+ }
+ }
+ else { //m_nImgChannels==3
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if (bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
+ for (size_t nCurrModelIdx = nRefreshStartPos; nCurrModelIdx < nRefreshStartPos + nModelsToRefresh; ++nCurrModelIdx) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandSamplePosition(nSampleImgCoord_X, nSampleImgCoord_Y, m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
+ const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
+ for (size_t c = 0; c < 3; ++c) {
+ m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter * 3 + c] = m_oLastColorFrame.data[nSamplePxIdx * 3 + c];
+ *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data + (nPxIter * 3 + c) * 2)) = *((ushort*)(m_oLastDescFrame.data + (nSamplePxIdx * 3 + c) * 2));
+ }
+ }
+ }
+ }
+ }
+ }
+}
+
+void BackgroundSubtractorLOBSTER::apply(cv::InputArray _image, cv::OutputArray _fgmask, double learningRate) {
+ CV_Assert(m_bInitialized);
+ CV_Assert(learningRate > 0);
+ cv::Mat oInputImg = _image.getMat();
+ CV_Assert(oInputImg.type() == m_nImgType && oInputImg.size() == m_oImgSize);
+ CV_Assert(oInputImg.isContinuous());
+ _fgmask.create(m_oImgSize, CV_8UC1);
+ cv::Mat oCurrFGMask = _fgmask.getMat();
+ oCurrFGMask = cv::Scalar_<uchar>(0);
+ const size_t nLearningRate = (size_t)ceil(learningRate);
+ if (m_nImgChannels == 1) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nDescIter = nPxIter * 2;
+ const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
+ const uchar nCurrColor = oInputImg.data[nPxIter];
+ size_t nGoodSamplesCount = 0, nModelIdx = 0;
+ ushort nCurrInputDesc;
+ while (nGoodSamplesCount < m_nRequiredBGSamples && nModelIdx < m_nBGSamples) {
+ const uchar nBGColor = m_voBGColorSamples[nModelIdx].data[nPxIter];
+ {
+ const size_t nColorDist = L1dist(nCurrColor, nBGColor);
+ if (nColorDist > m_nColorDistThreshold / 2)
+ goto failedcheck1ch;
+ LBSP::computeGrayscaleDescriptor(oInputImg, nBGColor, nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[nBGColor], nCurrInputDesc);
+ const size_t nDescDist = hdist(nCurrInputDesc, *((ushort*)(m_voBGDescSamples[nModelIdx].data + nDescIter)));
+ if (nDescDist > m_nDescDistThreshold)
+ goto failedcheck1ch;
+ nGoodSamplesCount++;
+ }
+ failedcheck1ch:
+ nModelIdx++;
+ }
+ if (nGoodSamplesCount < m_nRequiredBGSamples)
+ oCurrFGMask.data[nPxIter] = UCHAR_MAX;
+ else {
+ if ((rand() % nLearningRate) == 0) {
+ const size_t nSampleModelIdx = rand() % m_nBGSamples;
+ ushort& nRandInputDesc = *((ushort*)(m_voBGDescSamples[nSampleModelIdx].data + nDescIter));
+ LBSP::computeGrayscaleDescriptor(oInputImg, nCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[nCurrColor], nRandInputDesc);
+ m_voBGColorSamples[nSampleModelIdx].data[nPxIter] = nCurrColor;
+ }
+ if ((rand() % nLearningRate) == 0) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandNeighborPosition_3x3(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSampleModelIdx = rand() % m_nBGSamples;
+ ushort& nRandInputDesc = m_voBGDescSamples[nSampleModelIdx].at<ushort>(nSampleImgCoord_Y, nSampleImgCoord_X);
+ LBSP::computeGrayscaleDescriptor(oInputImg, nCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[nCurrColor], nRandInputDesc);
+ m_voBGColorSamples[nSampleModelIdx].at<uchar>(nSampleImgCoord_Y, nSampleImgCoord_X) = nCurrColor;
+ }
+ }
+ }
+ }
+ else { //m_nImgChannels==3
+ const size_t nCurrDescDistThreshold = m_nDescDistThreshold * 3;
+ const size_t nCurrColorDistThreshold = m_nColorDistThreshold * 3;
+ const size_t nCurrSCDescDistThreshold = nCurrDescDistThreshold / 2;
+ const size_t nCurrSCColorDistThreshold = nCurrColorDistThreshold / 2;
+ const size_t desc_row_step = m_voBGDescSamples[0].step.p[0];
+ const size_t img_row_step = m_voBGColorSamples[0].step.p[0];
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
+ const size_t nPxIterRGB = nPxIter * 3;
+ const size_t nDescIterRGB = nPxIterRGB * 2;
+ const uchar* const anCurrColor = oInputImg.data + nPxIterRGB;
+ size_t nGoodSamplesCount = 0, nModelIdx = 0;
+ ushort anCurrInputDesc[3];
+ while (nGoodSamplesCount < m_nRequiredBGSamples && nModelIdx < m_nBGSamples) {
+ const ushort* const anBGDesc = (ushort*)(m_voBGDescSamples[nModelIdx].data + nDescIterRGB);
+ const uchar* const anBGColor = m_voBGColorSamples[nModelIdx].data + nPxIterRGB;
+ size_t nTotColorDist = 0;
+ size_t nTotDescDist = 0;
+ for (size_t c = 0; c < 3; ++c) {
+ const size_t nColorDist = L1dist(anCurrColor[c], anBGColor[c]);
+ if (nColorDist > nCurrSCColorDistThreshold)
+ goto failedcheck3ch;
+ LBSP::computeSingleRGBDescriptor(oInputImg, anBGColor[c], nCurrImgCoord_X, nCurrImgCoord_Y, c, m_anLBSPThreshold_8bitLUT[anBGColor[c]], anCurrInputDesc[c]);
+ const size_t nDescDist = hdist(anCurrInputDesc[c], anBGDesc[c]);
+ if (nDescDist > nCurrSCDescDistThreshold)
+ goto failedcheck3ch;
+ nTotColorDist += nColorDist;
+ nTotDescDist += nDescDist;
+ }
+ if (nTotDescDist <= nCurrDescDistThreshold && nTotColorDist <= nCurrColorDistThreshold)
+ nGoodSamplesCount++;
+ failedcheck3ch:
+ nModelIdx++;
+ }
+ if (nGoodSamplesCount < m_nRequiredBGSamples)
+ oCurrFGMask.data[nPxIter] = UCHAR_MAX;
+ else {
+ if ((rand() % nLearningRate) == 0) {
+ const size_t nSampleModelIdx = rand() % m_nBGSamples;
+ ushort* anRandInputDesc = ((ushort*)(m_voBGDescSamples[nSampleModelIdx].data + nDescIterRGB));
+ const size_t anCurrIntraLBSPThresholds[3] = { m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]] };
+ LBSP::computeRGBDescriptor(oInputImg, anCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, anCurrIntraLBSPThresholds, anRandInputDesc);
+ for (size_t c = 0; c < 3; ++c)
+ *(m_voBGColorSamples[nSampleModelIdx].data + nPxIterRGB + c) = anCurrColor[c];
+ }
+ if ((rand() % nLearningRate) == 0) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandNeighborPosition_3x3(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSampleModelIdx = rand() % m_nBGSamples;
+ ushort* anRandInputDesc = ((ushort*)(m_voBGDescSamples[nSampleModelIdx].data + desc_row_step*nSampleImgCoord_Y + 6 * nSampleImgCoord_X));
+ const size_t anCurrIntraLBSPThresholds[3] = { m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]] };
+ LBSP::computeRGBDescriptor(oInputImg, anCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, anCurrIntraLBSPThresholds, anRandInputDesc);
+ for (size_t c = 0; c < 3; ++c)
+ *(m_voBGColorSamples[nSampleModelIdx].data + img_row_step*nSampleImgCoord_Y + 3 * nSampleImgCoord_X + c) = anCurrColor[c];
+ }
+ }
+ }
+ }
+ cv::medianBlur(oCurrFGMask, m_oLastFGMask, m_nDefaultMedianBlurKernelSize);
+ m_oLastFGMask.copyTo(oCurrFGMask);
+}
+
+void BackgroundSubtractorLOBSTER::getBackgroundImage(cv::OutputArray backgroundImage) const {
+ CV_DbgAssert(m_bInitialized);
+ cv::Mat oAvgBGImg = cv::Mat::zeros(m_oImgSize, CV_32FC((int)m_nImgChannels));
+ for (size_t s = 0; s < m_nBGSamples; ++s) {
+ for (int y = 0; y < m_oImgSize.height; ++y) {
+ for (int x = 0; x < m_oImgSize.width; ++x) {
+ const size_t idx_nimg = m_voBGColorSamples[s].step.p[0] * y + m_voBGColorSamples[s].step.p[1] * x;
+ const size_t idx_flt32 = idx_nimg * 4;
+ float* oAvgBgImgPtr = (float*)(oAvgBGImg.data + idx_flt32);
+ const uchar* const oBGImgPtr = m_voBGColorSamples[s].data + idx_nimg;
+ for (size_t c = 0; c < m_nImgChannels; ++c)
+ oAvgBgImgPtr[c] += ((float)oBGImgPtr[c]) / m_nBGSamples;
+ }
+ }
+ }
+ oAvgBGImg.convertTo(backgroundImage, CV_8U);
+}
+
+void BackgroundSubtractorLOBSTER::getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const {
+ CV_Assert(LBSP::DESC_SIZE == 2);
+ CV_Assert(m_bInitialized);
+ cv::Mat oAvgBGDesc = cv::Mat::zeros(m_oImgSize, CV_32FC((int)m_nImgChannels));
+ for (size_t n = 0; n < m_voBGDescSamples.size(); ++n) {
+ for (int y = 0; y < m_oImgSize.height; ++y) {
+ for (int x = 0; x < m_oImgSize.width; ++x) {
+ const size_t idx_ndesc = m_voBGDescSamples[n].step.p[0] * y + m_voBGDescSamples[n].step.p[1] * x;
+ const size_t idx_flt32 = idx_ndesc * 2;
+ float* oAvgBgDescPtr = (float*)(oAvgBGDesc.data + idx_flt32);
+ const ushort* const oBGDescPtr = (ushort*)(m_voBGDescSamples[n].data + idx_ndesc);
+ for (size_t c = 0; c < m_nImgChannels; ++c)
+ oAvgBgDescPtr[c] += ((float)oBGDescPtr[c]) / m_voBGDescSamples.size();
+ }
+ }
+ }
+ oAvgBGDesc.convertTo(backgroundDescImage, CV_16U);
+}
diff --git a/package_bgs/LBSP/BackgroundSubtractorLOBSTER.h b/package_bgs/LBSP/BackgroundSubtractorLOBSTER.h
new file mode 100644
index 0000000..d69fd1c
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorLOBSTER.h
@@ -0,0 +1,83 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "BackgroundSubtractorLBSP.h"
+
+//! defines the default value for BackgroundSubtractorLBSP::m_fRelLBSPThreshold
+#define BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD (0.365f)
+//! defines the default value for BackgroundSubtractorLBSP::m_nLBSPThresholdOffset
+#define BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD (0)
+//! defines the default value for BackgroundSubtractorLOBSTER::m_nDescDistThreshold
+#define BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD (4)
+//! defines the default value for BackgroundSubtractorLOBSTER::m_nColorDistThreshold
+#define BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD (30)
+//! defines the default value for BackgroundSubtractorLOBSTER::m_nBGSamples
+#define BGSLOBSTER_DEFAULT_NB_BG_SAMPLES (35)
+//! defines the default value for BackgroundSubtractorLOBSTER::m_nRequiredBGSamples
+#define BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES (2)
+//! defines the default value for the learning rate passed to BackgroundSubtractorLOBSTER::operator()
+#define BGSLOBSTER_DEFAULT_LEARNING_RATE (16)
+
+/*!
+ LOcal Binary Similarity segmenTER (LOBSTER) change detection algorithm.
+
+ Note: both grayscale and RGB/BGR images may be used with this extractor (parameters are adjusted automatically).
+ For optimal grayscale results, use CV_8UC1 frames instead of CV_8UC3.
+
+ For more details on the different parameters or on the algorithm itself, see P.-L. St-Charles and
+ G.-A. Bilodeau, "Improving Background Subtraction using Local Binary Similarity Patterns", in WACV 2014.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class BackgroundSubtractorLOBSTER : public BackgroundSubtractorLBSP {
+public:
+ //! full constructor
+ BackgroundSubtractorLOBSTER(float fRelLBSPThreshold = BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD,
+ size_t nLBSPThresholdOffset = BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD,
+ size_t nDescDistThreshold = BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD,
+ size_t nColorDistThreshold = BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD,
+ size_t nBGSamples = BGSLOBSTER_DEFAULT_NB_BG_SAMPLES,
+ size_t nRequiredBGSamples = BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES);
+ //! default destructor
+ virtual ~BackgroundSubtractorLOBSTER();
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI);
+ //! refreshes all samples based on the last analyzed frame
+ virtual void refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate = false);
+ //! primary model update function; the learning param is reinterpreted as an integer and should be > 0 (smaller values == faster adaptation)
+ virtual void apply(cv::InputArray image, cv::OutputArray fgmask, double learningRateOverride = BGSLOBSTER_DEFAULT_LEARNING_RATE);
+ //! returns a copy of the latest reconstructed background image
+ void getBackgroundImage(cv::OutputArray backgroundImage) const;
+ //! returns a copy of the latest reconstructed background descriptors image
+ virtual void getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const;
+
+protected:
+ //! absolute color distance threshold
+ const size_t m_nColorDistThreshold;
+ //! absolute descriptor distance threshold
+ const size_t m_nDescDistThreshold;
+ //! number of different samples per pixel/block to be taken from input frames to build the background model
+ const size_t m_nBGSamples;
+ //! number of similar samples needed to consider the current pixel/block as 'background'
+ const size_t m_nRequiredBGSamples;
+ //! background model pixel intensity samples
+ std::vector<cv::Mat> m_voBGColorSamples;
+ //! background model descriptors samples
+ std::vector<cv::Mat> m_voBGDescSamples;
+};
+
diff --git a/package_bgs/LBSP/BackgroundSubtractorPAWCS.cpp b/package_bgs/LBSP/BackgroundSubtractorPAWCS.cpp
new file mode 100644
index 0000000..6c48df3
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorPAWCS.cpp
@@ -0,0 +1,1349 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "BackgroundSubtractorPAWCS.h"
+#include "DistanceUtils.h"
+#include "RandUtils.h"
+#include <iostream>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <iomanip>
+
+/*
+ *
+ * Intrinsic configuration parameters are defined here; tuning these for better
+ * performance should not be required in most cases -- although improvements in
+ * very specific scenarios are always possible.
+ *
+ */
+ //! parameter used for dynamic distance threshold adjustments ('R(x)')
+#define FEEDBACK_R_VAR (0.01f)
+//! parameters used to adjust the variation step size of 'v(x)'
+#define FEEDBACK_V_INCR (1.000f)
+#define FEEDBACK_V_DECR (0.100f)
+//! parameters used to scale dynamic learning rate adjustments ('T(x)')
+#define FEEDBACK_T_DECR (0.2500f)
+#define FEEDBACK_T_INCR (0.5000f)
+#define FEEDBACK_T_LOWER (1.0000f)
+#define FEEDBACK_T_UPPER (256.00f)
+//! parameters used to define 'unstable' regions, based on segm noise/bg dynamics and local dist threshold values
+#define UNSTABLE_REG_RATIO_MIN (0.100f)
+#define UNSTABLE_REG_RDIST_MIN (3.000f)
+//! parameters used to scale the relative LBSP intensity threshold used for internal comparisons
+#define LBSPDESC_RATIO_MIN (0.100f)
+#define LBSPDESC_RATIO_MAX (0.500f)
+//! parameters used to trigger auto model resets in our frame-level component
+#define FRAMELEVEL_MIN_L1DIST_THRES (45)
+#define FRAMELEVEL_MIN_CDIST_THRES (FRAMELEVEL_MIN_L1DIST_THRES/10)
+#define FRAMELEVEL_DOWNSAMPLE_RATIO (8)
+//! parameters used to downscale gword maps & scale thresholds to make comparisons easier
+#define GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO (2)
+#define GWORD_DEFAULT_NB_INIT_SAMPL_PASSES (2)
+#define GWORD_DESC_THRES_BITS_MATCH_FACTOR (4)
+
+// local define used to specify the default frame size (320x240 = QVGA)
+#define DEFAULT_FRAME_SIZE cv::Size(320,240)
+// local define used to specify the default lword/gword update rate (16 = like vibe)
+#define DEFAULT_RESAMPLING_RATE (16)
+// local define used to specify the bootstrap window size for faster model stabilization
+#define DEFAULT_BOOTSTRAP_WIN_SIZE (500)
+// local define for the amount of weight offset to apply to words, making sure new words aren't always better than old ones
+#define DEFAULT_LWORD_WEIGHT_OFFSET (DEFAULT_BOOTSTRAP_WIN_SIZE*2)
+// local define used to set the default local word occurrence increment
+#define DEFAULT_LWORD_OCC_INCR 1
+// local define for the maximum weight a word can achieve before cutting off occ incr (used to make sure model stays good for long-term uses)
+#define DEFAULT_LWORD_MAX_WEIGHT (1.0f)
+// local define for the initial weight of a new word (used to make sure old words aren't worse off than new seeds)
+#define DEFAULT_LWORD_INIT_WEIGHT (1.0f/m_nLocalWordWeightOffset)
+// local define used to specify the desc dist threshold offset used for unstable regions
+#define UNSTAB_DESC_DIST_OFFSET (m_nDescDistThresholdOffset)
+// local define used to specify the min descriptor bit count for flat regions
+#define FLAT_REGION_BIT_COUNT (s_nDescMaxDataRange_1ch/8)
+
+static const size_t s_nColorMaxDataRange_1ch = UCHAR_MAX;
+static const size_t s_nDescMaxDataRange_1ch = LBSP_::DESC_SIZE * 8;
+static const size_t s_nColorMaxDataRange_3ch = s_nColorMaxDataRange_1ch * 3;
+static const size_t s_nDescMaxDataRange_3ch = s_nDescMaxDataRange_1ch * 3;
+
+BackgroundSubtractorPAWCS::BackgroundSubtractorPAWCS(float fRelLBSPThreshold
+ , size_t nDescDistThresholdOffset
+ , size_t nMinColorDistThreshold
+ , size_t nMaxNbWords
+ , size_t nSamplesForMovingAvgs)
+ : BackgroundSubtractorLBSP_(fRelLBSPThreshold)
+ , m_nMinColorDistThreshold(nMinColorDistThreshold)
+ , m_nDescDistThresholdOffset(nDescDistThresholdOffset)
+ , m_nMaxLocalWords(nMaxNbWords)
+ , m_nCurrLocalWords(0)
+ , m_nMaxGlobalWords(nMaxNbWords / 2)
+ , m_nCurrGlobalWords(0)
+ , m_nSamplesForMovingAvgs(nSamplesForMovingAvgs)
+ , m_fLastNonFlatRegionRatio(0.0f)
+ , m_nMedianBlurKernelSize(m_nDefaultMedianBlurKernelSize)
+ , m_nDownSampledROIPxCount(0)
+ , m_nLocalWordWeightOffset(DEFAULT_LWORD_WEIGHT_OFFSET)
+ , m_apLocalWordDict(nullptr)
+ , m_aLocalWordList_1ch(nullptr)
+ , m_pLocalWordListIter_1ch(nullptr)
+ , m_aLocalWordList_3ch(nullptr)
+ , m_pLocalWordListIter_3ch(nullptr)
+ , m_apGlobalWordDict(nullptr)
+ , m_aGlobalWordList_1ch(nullptr)
+ , m_pGlobalWordListIter_1ch(nullptr)
+ , m_aGlobalWordList_3ch(nullptr)
+ , m_pGlobalWordListIter_3ch(nullptr)
+ , m_aPxInfoLUT_PAWCS(nullptr) {
+ CV_Assert(m_nMaxLocalWords > 0 && m_nMaxGlobalWords > 0);
+}
+
+BackgroundSubtractorPAWCS::~BackgroundSubtractorPAWCS() {
+ CleanupDictionaries();
+}
+
+void BackgroundSubtractorPAWCS::initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) {
+ // == init
+ CV_Assert(!oInitImg.empty() && oInitImg.cols > 0 && oInitImg.rows > 0);
+ CV_Assert(oInitImg.isContinuous());
+ CV_Assert(oInitImg.type() == CV_8UC3 || oInitImg.type() == CV_8UC1);
+ if (oInitImg.type() == CV_8UC3) {
+ std::vector<cv::Mat> voInitImgChannels;
+ cv::split(oInitImg, voInitImgChannels);
+ if (!cv::countNonZero((voInitImgChannels[0] != voInitImgChannels[1]) | (voInitImgChannels[2] != voInitImgChannels[1])))
+ std::cout << std::endl << "\tBackgroundSubtractorPAWCS : Warning, grayscale images should always be passed in CV_8UC1 format for optimal performance." << std::endl;
+ }
+ cv::Mat oNewBGROI;
+ if (oROI.empty() && (m_oROI.empty() || oROI.size() != oInitImg.size())) {
+ oNewBGROI.create(oInitImg.size(), CV_8UC1);
+ oNewBGROI = cv::Scalar_<uchar>(UCHAR_MAX);
+ }
+ else if (oROI.empty())
+ oNewBGROI = m_oROI;
+ else {
+ CV_Assert(oROI.size() == oInitImg.size() && oROI.type() == CV_8UC1);
+ CV_Assert(cv::countNonZero((oROI < UCHAR_MAX)&(oROI > 0)) == 0);
+ oNewBGROI = oROI.clone();
+ cv::Mat oTempROI;
+ cv::dilate(oNewBGROI, oTempROI, cv::Mat(), cv::Point(-1, -1), LBSP_::PATCH_SIZE / 2);
+ cv::bitwise_or(oNewBGROI, oTempROI / 2, oNewBGROI);
+ }
+ const size_t nOrigROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
+ CV_Assert(nOrigROIPxCount > 0);
+ LBSP_::validateROI(oNewBGROI);
+ const size_t nFinalROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
+ CV_Assert(nFinalROIPxCount > 0);
+ CleanupDictionaries();
+ m_oROI = oNewBGROI;
+ m_oImgSize = oInitImg.size();
+ m_nImgType = oInitImg.type();
+ m_nImgChannels = oInitImg.channels();
+ m_nTotPxCount = m_oImgSize.area();
+ m_nTotRelevantPxCount = nFinalROIPxCount;
+ m_nFrameIndex = 0;
+ m_nFramesSinceLastReset = 0;
+ m_nModelResetCooldown = 0;
+ m_bUsingMovingCamera = false;
+ m_oDownSampledFrameSize_MotionAnalysis = cv::Size(m_oImgSize.width / FRAMELEVEL_DOWNSAMPLE_RATIO, m_oImgSize.height / FRAMELEVEL_DOWNSAMPLE_RATIO);
+ m_oDownSampledFrameSize_GlobalWordLookup = cv::Size(m_oImgSize.width / GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO, m_oImgSize.height / GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO);
+ cv::resize(m_oROI, m_oDownSampledROI_MotionAnalysis, m_oDownSampledFrameSize_MotionAnalysis, 0, 0, cv::INTER_AREA);
+ m_fLastNonFlatRegionRatio = 0.0f;
+ m_nCurrLocalWords = m_nMaxLocalWords;
+ if (nOrigROIPxCount >= m_nTotPxCount / 2 && (int)m_nTotPxCount >= DEFAULT_FRAME_SIZE.area()) {
+ const float fRegionSizeScaleFactor = (float)m_nTotPxCount / DEFAULT_FRAME_SIZE.area();
+ const int nRawMedianBlurKernelSize = std::min((int)floor(0.5f + fRegionSizeScaleFactor) + m_nDefaultMedianBlurKernelSize, m_nDefaultMedianBlurKernelSize + 4);
+ m_nMedianBlurKernelSize = (nRawMedianBlurKernelSize % 2) ? nRawMedianBlurKernelSize : nRawMedianBlurKernelSize - 1;
+ m_nCurrGlobalWords = m_nMaxGlobalWords;
+ m_oDownSampledROI_MotionAnalysis |= UCHAR_MAX / 2;
+ }
+ else {
+ const float fRegionSizeScaleFactor = (float)nOrigROIPxCount / DEFAULT_FRAME_SIZE.area();
+ const int nRawMedianBlurKernelSize = std::min((int)floor(0.5f + m_nDefaultMedianBlurKernelSize*fRegionSizeScaleFactor * 2) + (m_nDefaultMedianBlurKernelSize - 4), m_nDefaultMedianBlurKernelSize);
+ m_nMedianBlurKernelSize = (nRawMedianBlurKernelSize % 2) ? nRawMedianBlurKernelSize : nRawMedianBlurKernelSize - 1;
+ m_nCurrGlobalWords = std::min((size_t)std::pow(m_nMaxGlobalWords*fRegionSizeScaleFactor, 2) + 1, m_nMaxGlobalWords);
+ }
+ if (m_nImgChannels == 1) {
+ m_nCurrLocalWords = std::max(m_nCurrLocalWords / 2, (size_t)1);
+ m_nCurrGlobalWords = std::max(m_nCurrGlobalWords / 2, (size_t)1);
+ }
+ m_nDownSampledROIPxCount = (size_t)cv::countNonZero(m_oDownSampledROI_MotionAnalysis);
+ m_nLocalWordWeightOffset = DEFAULT_LWORD_WEIGHT_OFFSET;
+ m_oIllumUpdtRegionMask.create(m_oImgSize, CV_8UC1);
+ m_oIllumUpdtRegionMask = cv::Scalar_<uchar>(0);
+ m_oUpdateRateFrame.create(m_oImgSize, CV_32FC1);
+ m_oUpdateRateFrame = cv::Scalar(FEEDBACK_T_LOWER);
+ m_oDistThresholdFrame.create(m_oImgSize, CV_32FC1);
+ m_oDistThresholdFrame = cv::Scalar(2.0f);
+ m_oDistThresholdVariationFrame.create(m_oImgSize, CV_32FC1);
+ m_oDistThresholdVariationFrame = cv::Scalar(FEEDBACK_V_INCR * 10);
+ m_oMeanMinDistFrame_LT.create(m_oImgSize, CV_32FC1);
+ m_oMeanMinDistFrame_LT = cv::Scalar(0.0f);
+ m_oMeanMinDistFrame_ST.create(m_oImgSize, CV_32FC1);
+ m_oMeanMinDistFrame_ST = cv::Scalar(0.0f);
+ m_oMeanDownSampledLastDistFrame_LT.create(m_oDownSampledFrameSize_MotionAnalysis, CV_32FC((int)m_nImgChannels));
+ m_oMeanDownSampledLastDistFrame_LT = cv::Scalar(0.0f);
+ m_oMeanDownSampledLastDistFrame_ST.create(m_oDownSampledFrameSize_MotionAnalysis, CV_32FC((int)m_nImgChannels));
+ m_oMeanDownSampledLastDistFrame_ST = cv::Scalar(0.0f);
+ m_oMeanRawSegmResFrame_LT.create(m_oImgSize, CV_32FC1);
+ m_oMeanRawSegmResFrame_LT = cv::Scalar(0.0f);
+ m_oMeanRawSegmResFrame_ST.create(m_oImgSize, CV_32FC1);
+ m_oMeanRawSegmResFrame_ST = cv::Scalar(0.0f);
+ m_oMeanFinalSegmResFrame_LT.create(m_oImgSize, CV_32FC1);
+ m_oMeanFinalSegmResFrame_LT = cv::Scalar(0.0f);
+ m_oMeanFinalSegmResFrame_ST.create(m_oImgSize, CV_32FC1);
+ m_oMeanFinalSegmResFrame_ST = cv::Scalar(0.0f);
+ m_oUnstableRegionMask.create(m_oImgSize, CV_8UC1);
+ m_oUnstableRegionMask = cv::Scalar_<uchar>(0);
+ m_oBlinksFrame.create(m_oImgSize, CV_8UC1);
+ m_oBlinksFrame = cv::Scalar_<uchar>(0);
+ m_oDownSampledFrame_MotionAnalysis.create(m_oDownSampledFrameSize_MotionAnalysis, CV_8UC((int)m_nImgChannels));
+ m_oDownSampledFrame_MotionAnalysis = cv::Scalar_<uchar>::all(0);
+ m_oLastColorFrame.create(m_oImgSize, CV_8UC((int)m_nImgChannels));
+ m_oLastColorFrame = cv::Scalar_<uchar>::all(0);
+ m_oLastDescFrame.create(m_oImgSize, CV_16UC((int)m_nImgChannels));
+ m_oLastDescFrame = cv::Scalar_<ushort>::all(0);
+ m_oLastRawFGMask.create(m_oImgSize, CV_8UC1);
+ m_oLastRawFGMask = cv::Scalar_<uchar>(0);
+ m_oLastFGMask.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask = cv::Scalar_<uchar>(0);
+ m_oLastFGMask_dilated.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask_dilated = cv::Scalar_<uchar>(0);
+ m_oLastFGMask_dilated_inverted.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask_dilated_inverted = cv::Scalar_<uchar>(0);
+ m_oFGMask_FloodedHoles.create(m_oImgSize, CV_8UC1);
+ m_oFGMask_FloodedHoles = cv::Scalar_<uchar>(0);
+ m_oFGMask_PreFlood.create(m_oImgSize, CV_8UC1);
+ m_oFGMask_PreFlood = cv::Scalar_<uchar>(0);
+ m_oCurrRawFGBlinkMask.create(m_oImgSize, CV_8UC1);
+ m_oCurrRawFGBlinkMask = cv::Scalar_<uchar>(0);
+ m_oLastRawFGBlinkMask.create(m_oImgSize, CV_8UC1);
+ m_oLastRawFGBlinkMask = cv::Scalar_<uchar>(0);
+ m_oTempGlobalWordWeightDiffFactor.create(m_oDownSampledFrameSize_GlobalWordLookup, CV_32FC1);
+ m_oTempGlobalWordWeightDiffFactor = cv::Scalar(-0.1f);
+ m_oMorphExStructElement = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3));
+ m_aPxIdxLUT = new size_t[m_nTotRelevantPxCount];
+ memset(m_aPxIdxLUT, 0, sizeof(size_t)*m_nTotRelevantPxCount);
+ m_aPxInfoLUT_PAWCS = new PxInfo_PAWCS[m_nTotPxCount];
+ memset(m_aPxInfoLUT_PAWCS, 0, sizeof(PxInfo_PAWCS)*m_nTotPxCount);
+ m_aPxInfoLUT = m_aPxInfoLUT_PAWCS;
+ m_apLocalWordDict = new LocalWordBase*[m_nTotRelevantPxCount*m_nCurrLocalWords];
+ memset(m_apLocalWordDict, 0, sizeof(LocalWordBase*)*m_nTotRelevantPxCount*m_nCurrLocalWords);
+ m_apGlobalWordDict = new GlobalWordBase*[m_nCurrGlobalWords];
+ memset(m_apGlobalWordDict, 0, sizeof(GlobalWordBase*)*m_nCurrGlobalWords);
+ if (m_nImgChannels == 1) {
+ CV_DbgAssert(m_oLastColorFrame.step.p[0] == (size_t)m_oImgSize.width && m_oLastColorFrame.step.p[1] == 1);
+ CV_DbgAssert(m_oLastDescFrame.step.p[0] == m_oLastColorFrame.step.p[0] * 2 && m_oLastDescFrame.step.p[1] == m_oLastColorFrame.step.p[1] * 2);
+ m_aLocalWordList_1ch = new LocalWord_1ch[m_nTotRelevantPxCount*m_nCurrLocalWords];
+ memset(m_aLocalWordList_1ch, 0, sizeof(LocalWord_1ch)*m_nTotRelevantPxCount*m_nCurrLocalWords);
+ m_pLocalWordListIter_1ch = m_aLocalWordList_1ch;
+ m_aGlobalWordList_1ch = new GlobalWord_1ch[m_nCurrGlobalWords];
+ m_pGlobalWordListIter_1ch = m_aGlobalWordList_1ch;
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>((m_nLBSPThresholdOffset + t*m_fRelLBSPThreshold) / 3);
+ for (size_t nPxIter = 0, nModelIter = 0; nPxIter < m_nTotPxCount; ++nPxIter) {
+ if (m_oROI.data[nPxIter]) {
+ m_aPxIdxLUT[nModelIter] = nPxIter;
+ m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y = (int)nPxIter / m_oImgSize.width;
+ m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
+ m_aPxInfoLUT_PAWCS[nPxIter].nModelIdx = nModelIter;
+ m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx = (size_t)((m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y / GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO)*m_oDownSampledFrameSize_GlobalWordLookup.width + (m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X / GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO)) * 4;
+ m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT = new GlobalWordBase*[m_nCurrGlobalWords];
+ for (size_t nGlobalWordIdxIter = 0; nGlobalWordIdxIter < m_nCurrGlobalWords; ++nGlobalWordIdxIter)
+ m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordIdxIter] = &(m_aGlobalWordList_1ch[nGlobalWordIdxIter]);
+ m_oLastColorFrame.data[nPxIter] = oInitImg.data[nPxIter];
+ const size_t nDescIter = nPxIter * 2;
+ LBSP_::computeGrayscaleDescriptor(oInitImg, oInitImg.data[nPxIter], m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X, m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y, m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxIter]], *((ushort*)(m_oLastDescFrame.data + nDescIter)));
+ ++nModelIter;
+ }
+ }
+ }
+ else { //m_nImgChannels==3
+ CV_DbgAssert(m_oLastColorFrame.step.p[0] == (size_t)m_oImgSize.width * 3 && m_oLastColorFrame.step.p[1] == 3);
+ CV_DbgAssert(m_oLastDescFrame.step.p[0] == m_oLastColorFrame.step.p[0] * 2 && m_oLastDescFrame.step.p[1] == m_oLastColorFrame.step.p[1] * 2);
+ m_aLocalWordList_3ch = new LocalWord_3ch[m_nTotRelevantPxCount*m_nCurrLocalWords];
+ memset(m_aLocalWordList_3ch, 0, sizeof(LocalWord_3ch)*m_nTotRelevantPxCount*m_nCurrLocalWords);
+ m_pLocalWordListIter_3ch = m_aLocalWordList_3ch;
+ m_aGlobalWordList_3ch = new GlobalWord_3ch[m_nCurrGlobalWords];
+ m_pGlobalWordListIter_3ch = m_aGlobalWordList_3ch;
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>(m_nLBSPThresholdOffset + t*m_fRelLBSPThreshold);
+ for (size_t nPxIter = 0, nModelIter = 0; nPxIter < m_nTotPxCount; ++nPxIter) {
+ if (m_oROI.data[nPxIter]) {
+ m_aPxIdxLUT[nModelIter] = nPxIter;
+ m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y = (int)nPxIter / m_oImgSize.width;
+ m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
+ m_aPxInfoLUT_PAWCS[nPxIter].nModelIdx = nModelIter;
+ m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx = (size_t)((m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y / GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO)*m_oDownSampledFrameSize_GlobalWordLookup.width + (m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X / GWORD_LOOKUP_MAPS_DOWNSAMPLE_RATIO)) * 4;
+ m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT = new GlobalWordBase*[m_nCurrGlobalWords];
+ for (size_t nGlobalWordIdxIter = 0; nGlobalWordIdxIter < m_nCurrGlobalWords; ++nGlobalWordIdxIter)
+ m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordIdxIter] = &(m_aGlobalWordList_3ch[nGlobalWordIdxIter]);
+ const size_t nPxRGBIter = nPxIter * 3;
+ const size_t nDescRGBIter = nPxRGBIter * 2;
+ for (size_t c = 0; c < 3; ++c) {
+ m_oLastColorFrame.data[nPxRGBIter + c] = oInitImg.data[nPxRGBIter + c];
+ LBSP_::computeSingleRGBDescriptor(oInitImg, oInitImg.data[nPxRGBIter + c], m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X, m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y, c, m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxRGBIter + c]], ((ushort*)(m_oLastDescFrame.data + nDescRGBIter))[c]);
+ }
+ ++nModelIter;
+ }
+ }
+ }
+ m_bInitialized = true;
+ refreshModel(1, 0);
+}
+
+void BackgroundSubtractorPAWCS::refreshModel(size_t nBaseOccCount, float fOccDecrFrac, bool bForceFGUpdate) {
+ // == refresh
+ CV_Assert(m_bInitialized);
+ CV_Assert(fOccDecrFrac >= 0.0f && fOccDecrFrac <= 1.0f);
+ if (m_nImgChannels == 1) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if (bForceFGUpdate || !m_oLastFGMask_dilated.data[nPxIter]) {
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const size_t nFloatIter = nPxIter * 4;
+ uchar& bCurrRegionIsUnstable = m_oUnstableRegionMask.data[nPxIter];
+ const float fCurrDistThresholdFactor = *(float*)(m_oDistThresholdFrame.data + nFloatIter);
+ const size_t nCurrColorDistThreshold = (size_t)(sqrt(fCurrDistThresholdFactor)*m_nMinColorDistThreshold) / 2;
+ const size_t nCurrDescDistThreshold = ((size_t)1 << ((size_t)floor(fCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (bCurrRegionIsUnstable*UNSTAB_DESC_DIST_OFFSET);
+ // == refresh: local decr
+ if (fOccDecrFrac > 0.0f) {
+ for (size_t nLocalWordIdx = 0; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ LocalWord_1ch* pCurrLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ if (pCurrLocalWord)
+ pCurrLocalWord->nOccurrences -= (size_t)(fOccDecrFrac*pCurrLocalWord->nOccurrences);
+ }
+ }
+ const size_t nCurrWordOccIncr = DEFAULT_LWORD_OCC_INCR;
+ const size_t nTotLocalSamplingIterCount = (s_nSamplesInitPatternWidth*s_nSamplesInitPatternHeight) * 2;
+ for (size_t nLocalSamplingIter = 0; nLocalSamplingIter < nTotLocalSamplingIterCount; ++nLocalSamplingIter) {
+ // == refresh: local resampling
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandSamplePosition(nSampleImgCoord_X, nSampleImgCoord_Y, m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X, m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y, LBSP_::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (bForceFGUpdate || !m_oLastFGMask_dilated.data[nSamplePxIdx]) {
+ const uchar nSampleColor = m_oLastColorFrame.data[nSamplePxIdx];
+ const size_t nSampleDescIdx = nSamplePxIdx * 2;
+ const ushort nSampleIntraDesc = *((ushort*)(m_oLastDescFrame.data + nSampleDescIdx));
+ bool bFoundUninitd = false;
+ size_t nLocalWordIdx;
+ for (nLocalWordIdx = 0; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ LocalWord_1ch* pCurrLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ if (pCurrLocalWord
+ && L1dist(nSampleColor, pCurrLocalWord->oFeature.anColor[0]) <= nCurrColorDistThreshold
+ && hdist(nSampleIntraDesc, pCurrLocalWord->oFeature.anDesc[0]) <= nCurrDescDistThreshold) {
+ pCurrLocalWord->nOccurrences += nCurrWordOccIncr;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ break;
+ }
+ else if (!pCurrLocalWord)
+ bFoundUninitd = true;
+ }
+ if (nLocalWordIdx == m_nCurrLocalWords) {
+ nLocalWordIdx = m_nCurrLocalWords - 1;
+ LocalWord_1ch* pCurrLocalWord = bFoundUninitd ? m_pLocalWordListIter_1ch++ : (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ pCurrLocalWord->oFeature.anColor[0] = nSampleColor;
+ pCurrLocalWord->oFeature.anDesc[0] = nSampleIntraDesc;
+ pCurrLocalWord->nOccurrences = nBaseOccCount;
+ pCurrLocalWord->nFirstOcc = m_nFrameIndex;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx] = pCurrLocalWord;
+ }
+ while (nLocalWordIdx > 0 && (!m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1] || GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_nFrameIndex, m_nLocalWordWeightOffset) > GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1], m_nFrameIndex, m_nLocalWordWeightOffset))) {
+ std::swap(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1]);
+ --nLocalWordIdx;
+ }
+ }
+ }
+ CV_Assert(m_apLocalWordDict[nLocalDictIdx]);
+ for (size_t nLocalWordIdx = 1; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ // == refresh: local random resampling
+ LocalWord_1ch* pCurrLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ if (!pCurrLocalWord) {
+ const size_t nRandLocalWordIdx = (rand() % nLocalWordIdx);
+ const LocalWord_1ch* pRefLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nRandLocalWordIdx];
+ const int nRandColorOffset = (rand() % (nCurrColorDistThreshold + 1)) - (int)nCurrColorDistThreshold / 2;
+ pCurrLocalWord = m_pLocalWordListIter_1ch++;
+ pCurrLocalWord->oFeature.anColor[0] = cv::saturate_cast<uchar>((int)pRefLocalWord->oFeature.anColor[0] + nRandColorOffset);
+ pCurrLocalWord->oFeature.anDesc[0] = pRefLocalWord->oFeature.anDesc[0];
+ pCurrLocalWord->nOccurrences = std::max((size_t)(pRefLocalWord->nOccurrences*((float)(m_nCurrLocalWords - nLocalWordIdx) / m_nCurrLocalWords)), (size_t)1);
+ pCurrLocalWord->nFirstOcc = m_nFrameIndex;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx] = pCurrLocalWord;
+ }
+ }
+ }
+ }
+ CV_Assert(m_aLocalWordList_1ch == (m_pLocalWordListIter_1ch - m_nTotRelevantPxCount*m_nCurrLocalWords));
+ cv::Mat oGlobalDictPresenceLookupMap(m_oImgSize, CV_8UC1, cv::Scalar_<uchar>(0));
+ size_t nPxIterIncr = std::max(m_nTotPxCount / m_nCurrGlobalWords, (size_t)1);
+ for (size_t nSamplingPasses = 0; nSamplingPasses < GWORD_DEFAULT_NB_INIT_SAMPL_PASSES; ++nSamplingPasses) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ // == refresh: global resampling
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if ((nPxIter%nPxIterIncr) == 0) { // <=(m_nCurrGlobalWords) gwords from (m_nCurrGlobalWords) equally spaced pixels
+ if (bForceFGUpdate || !m_oLastFGMask_dilated.data[nPxIter]) {
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const size_t nGlobalWordMapLookupIdx = m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx;
+ const size_t nFloatIter = nPxIter * 4;
+ uchar& bCurrRegionIsUnstable = m_oUnstableRegionMask.data[nPxIter];
+ const float fCurrDistThresholdFactor = *(float*)(m_oDistThresholdFrame.data + nFloatIter);
+ const size_t nCurrColorDistThreshold = (size_t)(sqrt(fCurrDistThresholdFactor)*m_nMinColorDistThreshold) / 2;
+ const size_t nCurrDescDistThreshold = ((size_t)1 << ((size_t)floor(fCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (bCurrRegionIsUnstable*UNSTAB_DESC_DIST_OFFSET);
+ CV_Assert(m_apLocalWordDict[nLocalDictIdx]);
+ const LocalWord_1ch* pRefBestLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx];
+ const float fRefBestLocalWordWeight = GetLocalWordWeight(pRefBestLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ const uchar nRefBestLocalWordDescBITS = (uchar)popcount(pRefBestLocalWord->oFeature.anDesc[0]);
+ bool bFoundUninitd = false;
+ size_t nGlobalWordIdx;
+ for (nGlobalWordIdx = 0; nGlobalWordIdx < m_nCurrGlobalWords; ++nGlobalWordIdx) {
+ GlobalWord_1ch* pCurrGlobalWord = (GlobalWord_1ch*)m_apGlobalWordDict[nGlobalWordIdx];
+ if (pCurrGlobalWord
+ && L1dist(pCurrGlobalWord->oFeature.anColor[0], pRefBestLocalWord->oFeature.anColor[0]) <= nCurrColorDistThreshold
+ && L1dist(nRefBestLocalWordDescBITS, pCurrGlobalWord->nDescBITS) <= nCurrDescDistThreshold / GWORD_DESC_THRES_BITS_MATCH_FACTOR)
+ break;
+ else if (!pCurrGlobalWord)
+ bFoundUninitd = true;
+ }
+ if (nGlobalWordIdx == m_nCurrGlobalWords) {
+ nGlobalWordIdx = m_nCurrGlobalWords - 1;
+ GlobalWord_1ch* pCurrGlobalWord = bFoundUninitd ? m_pGlobalWordListIter_1ch++ : (GlobalWord_1ch*)m_apGlobalWordDict[nGlobalWordIdx];
+ pCurrGlobalWord->oFeature.anColor[0] = pRefBestLocalWord->oFeature.anColor[0];
+ pCurrGlobalWord->oFeature.anDesc[0] = pRefBestLocalWord->oFeature.anDesc[0];
+ pCurrGlobalWord->nDescBITS = nRefBestLocalWordDescBITS;
+ pCurrGlobalWord->oSpatioOccMap.create(m_oDownSampledFrameSize_GlobalWordLookup, CV_32FC1);
+ pCurrGlobalWord->oSpatioOccMap = cv::Scalar(0.0f);
+ pCurrGlobalWord->fLatestWeight = 0.0f;
+ m_apGlobalWordDict[nGlobalWordIdx] = pCurrGlobalWord;
+ }
+ float& fCurrGlobalWordLocalWeight = *(float*)(m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fCurrGlobalWordLocalWeight < fRefBestLocalWordWeight) {
+ m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight += fRefBestLocalWordWeight;
+ fCurrGlobalWordLocalWeight += fRefBestLocalWordWeight;
+ }
+ oGlobalDictPresenceLookupMap.data[nPxIter] = UCHAR_MAX;
+ while (nGlobalWordIdx > 0 && (!m_apGlobalWordDict[nGlobalWordIdx - 1] || m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight > m_apGlobalWordDict[nGlobalWordIdx - 1]->fLatestWeight)) {
+ std::swap(m_apGlobalWordDict[nGlobalWordIdx], m_apGlobalWordDict[nGlobalWordIdx - 1]);
+ --nGlobalWordIdx;
+ }
+ }
+ }
+ }
+ nPxIterIncr = std::max(nPxIterIncr / 3, (size_t)1);
+ }
+ for (size_t nGlobalWordIdx = 0; nGlobalWordIdx < m_nCurrGlobalWords; ++nGlobalWordIdx) {
+ GlobalWord_1ch* pCurrGlobalWord = (GlobalWord_1ch*)m_apGlobalWordDict[nGlobalWordIdx];
+ if (!pCurrGlobalWord) {
+ pCurrGlobalWord = m_pGlobalWordListIter_1ch++;
+ pCurrGlobalWord->oFeature.anColor[0] = 0;
+ pCurrGlobalWord->oFeature.anDesc[0] = 0;
+ pCurrGlobalWord->nDescBITS = 0;
+ pCurrGlobalWord->oSpatioOccMap.create(m_oDownSampledFrameSize_GlobalWordLookup, CV_32FC1);
+ pCurrGlobalWord->oSpatioOccMap = cv::Scalar(0.0f);
+ pCurrGlobalWord->fLatestWeight = 0.0f;
+ m_apGlobalWordDict[nGlobalWordIdx] = pCurrGlobalWord;
+ }
+ }
+ CV_Assert((size_t)(m_pGlobalWordListIter_1ch - m_aGlobalWordList_1ch) == m_nCurrGlobalWords && m_aGlobalWordList_1ch == (m_pGlobalWordListIter_1ch - m_nCurrGlobalWords));
+ }
+ else { //m_nImgChannels==3
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if (bForceFGUpdate || !m_oLastFGMask_dilated.data[nPxIter]) {
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const size_t nFloatIter = nPxIter * 4;
+ uchar& bCurrRegionIsUnstable = m_oUnstableRegionMask.data[nPxIter];
+ const float fCurrDistThresholdFactor = *(float*)(m_oDistThresholdFrame.data + nFloatIter);
+ const size_t nCurrTotColorDistThreshold = (size_t)(sqrt(fCurrDistThresholdFactor)*m_nMinColorDistThreshold) * 3;
+ const size_t nCurrTotDescDistThreshold = (((size_t)1 << ((size_t)floor(fCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (bCurrRegionIsUnstable*UNSTAB_DESC_DIST_OFFSET)) * 3;
+ // == refresh: local decr
+ if (fOccDecrFrac > 0.0f) {
+ for (size_t nLocalWordIdx = 0; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ LocalWord_3ch* pCurrLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ if (pCurrLocalWord)
+ pCurrLocalWord->nOccurrences -= (size_t)(fOccDecrFrac*pCurrLocalWord->nOccurrences);
+ }
+ }
+ const size_t nCurrWordOccIncr = DEFAULT_LWORD_OCC_INCR;
+ const size_t nTotLocalSamplingIterCount = (s_nSamplesInitPatternWidth*s_nSamplesInitPatternHeight) * 2;
+ for (size_t nLocalSamplingIter = 0; nLocalSamplingIter < nTotLocalSamplingIterCount; ++nLocalSamplingIter) {
+ // == refresh: local resampling
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandSamplePosition(nSampleImgCoord_X, nSampleImgCoord_Y, m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X, m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y, LBSP_::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (bForceFGUpdate || !m_oLastFGMask_dilated.data[nSamplePxIdx]) {
+ const size_t nSamplePxRGBIdx = nSamplePxIdx * 3;
+ const size_t nSampleDescRGBIdx = nSamplePxRGBIdx * 2;
+ const uchar* const anSampleColor = m_oLastColorFrame.data + nSamplePxRGBIdx;
+ const ushort* const anSampleIntraDesc = ((ushort*)(m_oLastDescFrame.data + nSampleDescRGBIdx));
+ bool bFoundUninitd = false;
+ size_t nLocalWordIdx;
+ for (nLocalWordIdx = 0; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ LocalWord_3ch* pCurrLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ if (pCurrLocalWord
+ && cmixdist<3>(anSampleColor, pCurrLocalWord->oFeature.anColor) <= nCurrTotColorDistThreshold
+ && hdist<3>(anSampleIntraDesc, pCurrLocalWord->oFeature.anDesc) <= nCurrTotDescDistThreshold) {
+ pCurrLocalWord->nOccurrences += nCurrWordOccIncr;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ break;
+ }
+ else if (!pCurrLocalWord)
+ bFoundUninitd = true;
+ }
+ if (nLocalWordIdx == m_nCurrLocalWords) {
+ nLocalWordIdx = m_nCurrLocalWords - 1;
+ LocalWord_3ch* pCurrLocalWord = bFoundUninitd ? m_pLocalWordListIter_3ch++ : (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ for (size_t c = 0; c < 3; ++c) {
+ pCurrLocalWord->oFeature.anColor[c] = anSampleColor[c];
+ pCurrLocalWord->oFeature.anDesc[c] = anSampleIntraDesc[c];
+ }
+ pCurrLocalWord->nOccurrences = nBaseOccCount;
+ pCurrLocalWord->nFirstOcc = m_nFrameIndex;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx] = pCurrLocalWord;
+ }
+ while (nLocalWordIdx > 0 && (!m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1] || GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_nFrameIndex, m_nLocalWordWeightOffset) > GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1], m_nFrameIndex, m_nLocalWordWeightOffset))) {
+ std::swap(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1]);
+ --nLocalWordIdx;
+ }
+ }
+ }
+ CV_Assert(m_apLocalWordDict[nLocalDictIdx]);
+ for (size_t nLocalWordIdx = 1; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ // == refresh: local random resampling
+ LocalWord_3ch* pCurrLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ if (!pCurrLocalWord) {
+ const size_t nRandLocalWordIdx = (rand() % nLocalWordIdx);
+ const LocalWord_3ch* pRefLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nRandLocalWordIdx];
+ const int nRandColorOffset = (rand() % (nCurrTotColorDistThreshold / 3 + 1)) - (int)(nCurrTotColorDistThreshold / 6);
+ pCurrLocalWord = m_pLocalWordListIter_3ch++;
+ for (size_t c = 0; c < 3; ++c) {
+ pCurrLocalWord->oFeature.anColor[c] = cv::saturate_cast<uchar>((int)pRefLocalWord->oFeature.anColor[c] + nRandColorOffset);
+ pCurrLocalWord->oFeature.anDesc[c] = pRefLocalWord->oFeature.anDesc[c];
+ }
+ pCurrLocalWord->nOccurrences = std::max((size_t)(pRefLocalWord->nOccurrences*((float)(m_nCurrLocalWords - nLocalWordIdx) / m_nCurrLocalWords)), (size_t)1);
+ pCurrLocalWord->nFirstOcc = m_nFrameIndex;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx] = pCurrLocalWord;
+ }
+ }
+ }
+ }
+ CV_Assert(m_aLocalWordList_3ch == (m_pLocalWordListIter_3ch - m_nTotRelevantPxCount*m_nCurrLocalWords));
+ cv::Mat oGlobalDictPresenceLookupMap(m_oImgSize, CV_8UC1, cv::Scalar_<uchar>(0));
+ size_t nPxIterIncr = std::max(m_nTotPxCount / m_nCurrGlobalWords, (size_t)1);
+ for (size_t nSamplingPasses = 0; nSamplingPasses < GWORD_DEFAULT_NB_INIT_SAMPL_PASSES; ++nSamplingPasses) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ // == refresh: global resampling
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if ((nPxIter%nPxIterIncr) == 0) { // <=(m_nCurrGlobalWords) gwords from (m_nCurrGlobalWords) equally spaced pixels
+ if (bForceFGUpdate || !m_oLastFGMask_dilated.data[nPxIter]) {
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const size_t nGlobalWordMapLookupIdx = m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx;
+ const size_t nFloatIter = nPxIter * 4;
+ uchar& bCurrRegionIsUnstable = m_oUnstableRegionMask.data[nPxIter];
+ const float fCurrDistThresholdFactor = *(float*)(m_oDistThresholdFrame.data + nFloatIter);
+ const size_t nCurrTotColorDistThreshold = (size_t)(sqrt(fCurrDistThresholdFactor)*m_nMinColorDistThreshold) * 3;
+ const size_t nCurrTotDescDistThreshold = (((size_t)1 << ((size_t)floor(fCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (bCurrRegionIsUnstable*UNSTAB_DESC_DIST_OFFSET)) * 3;
+ CV_Assert(m_apLocalWordDict[nLocalDictIdx]);
+ const LocalWord_3ch* pRefBestLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx];
+ const float fRefBestLocalWordWeight = GetLocalWordWeight(pRefBestLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ const uchar nRefBestLocalWordDescBITS = (uchar)popcount<3>(pRefBestLocalWord->oFeature.anDesc);
+ bool bFoundUninitd = false;
+ size_t nGlobalWordIdx;
+ for (nGlobalWordIdx = 0; nGlobalWordIdx < m_nCurrGlobalWords; ++nGlobalWordIdx) {
+ GlobalWord_3ch* pCurrGlobalWord = (GlobalWord_3ch*)m_apGlobalWordDict[nGlobalWordIdx];
+ if (pCurrGlobalWord
+ && L1dist(nRefBestLocalWordDescBITS, pCurrGlobalWord->nDescBITS) <= nCurrTotDescDistThreshold / GWORD_DESC_THRES_BITS_MATCH_FACTOR
+ && cmixdist<3>(pRefBestLocalWord->oFeature.anColor, pCurrGlobalWord->oFeature.anColor) <= nCurrTotColorDistThreshold)
+ break;
+ else if (!pCurrGlobalWord)
+ bFoundUninitd = true;
+ }
+ if (nGlobalWordIdx == m_nCurrGlobalWords) {
+ nGlobalWordIdx = m_nCurrGlobalWords - 1;
+ GlobalWord_3ch* pCurrGlobalWord = bFoundUninitd ? m_pGlobalWordListIter_3ch++ : (GlobalWord_3ch*)m_apGlobalWordDict[nGlobalWordIdx];
+ for (size_t c = 0; c < 3; ++c) {
+ pCurrGlobalWord->oFeature.anColor[c] = pRefBestLocalWord->oFeature.anColor[c];
+ pCurrGlobalWord->oFeature.anDesc[c] = pRefBestLocalWord->oFeature.anDesc[c];
+ }
+ pCurrGlobalWord->nDescBITS = nRefBestLocalWordDescBITS;
+ pCurrGlobalWord->oSpatioOccMap.create(m_oDownSampledFrameSize_GlobalWordLookup, CV_32FC1);
+ pCurrGlobalWord->oSpatioOccMap = cv::Scalar(0.0f);
+ pCurrGlobalWord->fLatestWeight = 0.0f;
+ m_apGlobalWordDict[nGlobalWordIdx] = pCurrGlobalWord;
+ }
+ float& fCurrGlobalWordLocalWeight = *(float*)(m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fCurrGlobalWordLocalWeight < fRefBestLocalWordWeight) {
+ m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight += fRefBestLocalWordWeight;
+ fCurrGlobalWordLocalWeight += fRefBestLocalWordWeight;
+ }
+ oGlobalDictPresenceLookupMap.data[nPxIter] = UCHAR_MAX;
+ while (nGlobalWordIdx > 0 && (!m_apGlobalWordDict[nGlobalWordIdx - 1] || m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight > m_apGlobalWordDict[nGlobalWordIdx - 1]->fLatestWeight)) {
+ std::swap(m_apGlobalWordDict[nGlobalWordIdx], m_apGlobalWordDict[nGlobalWordIdx - 1]);
+ --nGlobalWordIdx;
+ }
+ }
+ }
+ }
+ nPxIterIncr = std::max(nPxIterIncr / 3, (size_t)1);
+ }
+ for (size_t nGlobalWordIdx = 0; nGlobalWordIdx < m_nCurrGlobalWords; ++nGlobalWordIdx) {
+ GlobalWord_3ch* pCurrGlobalWord = (GlobalWord_3ch*)m_apGlobalWordDict[nGlobalWordIdx];
+ if (!pCurrGlobalWord) {
+ pCurrGlobalWord = m_pGlobalWordListIter_3ch++;
+ for (size_t c = 0; c < 3; ++c) {
+ pCurrGlobalWord->oFeature.anColor[c] = 0;
+ pCurrGlobalWord->oFeature.anDesc[c] = 0;
+ }
+ pCurrGlobalWord->nDescBITS = 0;
+ pCurrGlobalWord->oSpatioOccMap.create(m_oDownSampledFrameSize_GlobalWordLookup, CV_32FC1);
+ pCurrGlobalWord->oSpatioOccMap = cv::Scalar(0.0f);
+ pCurrGlobalWord->fLatestWeight = 0.0f;
+ m_apGlobalWordDict[nGlobalWordIdx] = pCurrGlobalWord;
+ }
+ }
+ CV_Assert((size_t)(m_pGlobalWordListIter_3ch - m_aGlobalWordList_3ch) == m_nCurrGlobalWords && m_aGlobalWordList_3ch == (m_pGlobalWordListIter_3ch - m_nCurrGlobalWords));
+ }
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ // == refresh: per-px global word sort
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nGlobalWordMapLookupIdx = m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx;
+ float fLastGlobalWordLocalWeight = *(float*)(m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[0]->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ for (size_t nGlobalWordLUTIdx = 1; nGlobalWordLUTIdx < m_nCurrGlobalWords; ++nGlobalWordLUTIdx) {
+ const float fCurrGlobalWordLocalWeight = *(float*)(m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx]->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fCurrGlobalWordLocalWeight > fLastGlobalWordLocalWeight)
+ std::swap(m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx], m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx - 1]);
+ else
+ fLastGlobalWordLocalWeight = fCurrGlobalWordLocalWeight;
+ }
+ }
+}
+
+void BackgroundSubtractorPAWCS::apply(cv::InputArray _image, cv::OutputArray _fgmask, double learningRateOverride) {
+ // == process
+ CV_Assert(m_bInitialized);
+ cv::Mat oInputImg = _image.getMat();
+ CV_Assert(oInputImg.type() == m_nImgType && oInputImg.size() == m_oImgSize);
+ CV_Assert(oInputImg.isContinuous());
+ _fgmask.create(m_oImgSize, CV_8UC1);
+ cv::Mat oCurrFGMask = _fgmask.getMat();
+ memset(oCurrFGMask.data, 0, oCurrFGMask.cols*oCurrFGMask.rows);
+ const bool bBootstrapping = ++m_nFrameIndex <= DEFAULT_BOOTSTRAP_WIN_SIZE;
+ const size_t nCurrSamplesForMovingAvg_LT = bBootstrapping ? m_nSamplesForMovingAvgs / 2 : m_nSamplesForMovingAvgs;
+ const size_t nCurrSamplesForMovingAvg_ST = nCurrSamplesForMovingAvg_LT / 4;
+ const float fRollAvgFactor_LT = 1.0f / std::min(m_nFrameIndex, nCurrSamplesForMovingAvg_LT);
+ const float fRollAvgFactor_ST = 1.0f / std::min(m_nFrameIndex, nCurrSamplesForMovingAvg_ST);
+ const size_t nCurrGlobalWordUpdateRate = bBootstrapping ? DEFAULT_RESAMPLING_RATE / 2 : DEFAULT_RESAMPLING_RATE;
+ size_t nFlatRegionCount = 0;
+ if (m_nImgChannels == 1) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nDescIter = nPxIter * 2;
+ const size_t nFloatIter = nPxIter * 4;
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const size_t nGlobalWordMapLookupIdx = m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx;
+ const uchar nCurrColor = oInputImg.data[nPxIter];
+ uchar& nLastColor = m_oLastColorFrame.data[nPxIter];
+ ushort& nLastIntraDesc = *((ushort*)(m_oLastDescFrame.data + nDescIter));
+ size_t nMinColorDist = s_nColorMaxDataRange_1ch;
+ size_t nMinDescDist = s_nDescMaxDataRange_1ch;
+ float& fCurrMeanRawSegmRes_LT = *(float*)(m_oMeanRawSegmResFrame_LT.data + nFloatIter);
+ float& fCurrMeanRawSegmRes_ST = *(float*)(m_oMeanRawSegmResFrame_ST.data + nFloatIter);
+ float& fCurrMeanFinalSegmRes_LT = *(float*)(m_oMeanFinalSegmResFrame_LT.data + nFloatIter);
+ float& fCurrMeanFinalSegmRes_ST = *(float*)(m_oMeanFinalSegmResFrame_ST.data + nFloatIter);
+ float& fCurrDistThresholdFactor = *(float*)(m_oDistThresholdFrame.data + nFloatIter);
+ float& fCurrDistThresholdVariationFactor = *(float*)(m_oDistThresholdVariationFrame.data + nFloatIter);
+ float& fCurrLearningRate = *(float*)(m_oUpdateRateFrame.data + nFloatIter);
+ float& fCurrMeanMinDist_LT = *(float*)(m_oMeanMinDistFrame_LT.data + nFloatIter);
+ float& fCurrMeanMinDist_ST = *(float*)(m_oMeanMinDistFrame_ST.data + nFloatIter);
+ const float fBestLocalWordWeight = GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx], m_nFrameIndex, m_nLocalWordWeightOffset);
+ const float fLocalWordsWeightSumThreshold = fBestLocalWordWeight / (fCurrDistThresholdFactor * 2);
+ uchar& bCurrRegionIsUnstable = m_oUnstableRegionMask.data[nPxIter];
+ uchar& nCurrRegionIllumUpdtVal = m_oIllumUpdtRegionMask.data[nPxIter];
+ uchar& nCurrRegionSegmVal = oCurrFGMask.data[nPxIter];
+ const bool bCurrRegionIsROIBorder = m_oROI.data[nPxIter] < UCHAR_MAX;
+ const int nCurrImgCoord_X = m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y;
+ ushort nCurrInterDesc, nCurrIntraDesc;
+ LBSP_::computeGrayscaleDescriptor(oInputImg, nCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[nCurrColor], nCurrIntraDesc);
+ const uchar nCurrIntraDescBITS = (uchar)popcount(nCurrIntraDesc);
+ const bool bCurrRegionIsFlat = nCurrIntraDescBITS < FLAT_REGION_BIT_COUNT;
+ if (bCurrRegionIsFlat)
+ ++nFlatRegionCount;
+ const size_t nCurrWordOccIncr = (DEFAULT_LWORD_OCC_INCR + m_nModelResetCooldown) << int(bCurrRegionIsFlat || bBootstrapping);
+ const size_t nCurrLocalWordUpdateRate = learningRateOverride > 0 ? (size_t)ceil(learningRateOverride) : bCurrRegionIsFlat ? (size_t)ceil(fCurrLearningRate + FEEDBACK_T_LOWER) / 2 : (size_t)ceil(fCurrLearningRate);
+ const size_t nCurrColorDistThreshold = (size_t)(sqrt(fCurrDistThresholdFactor)*m_nMinColorDistThreshold) / 2;
+ const size_t nCurrDescDistThreshold = ((size_t)1 << ((size_t)floor(fCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (bCurrRegionIsUnstable*UNSTAB_DESC_DIST_OFFSET);
+ size_t nLocalWordIdx = 0;
+ float fPotentialLocalWordsWeightSum = 0.0f;
+ float fLastLocalWordWeight = FLT_MAX;
+ while (nLocalWordIdx < m_nCurrLocalWords && fPotentialLocalWordsWeightSum < fLocalWordsWeightSumThreshold) {
+ LocalWord_1ch* pCurrLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ const float fCurrLocalWordWeight = GetLocalWordWeight(pCurrLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ {
+ const size_t nColorDist = L1dist(nCurrColor, pCurrLocalWord->oFeature.anColor[0]);
+ const size_t nIntraDescDist = hdist(nCurrIntraDesc, pCurrLocalWord->oFeature.anDesc[0]);
+ LBSP_::computeGrayscaleDescriptor(oInputImg, pCurrLocalWord->oFeature.anColor[0], nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[pCurrLocalWord->oFeature.anColor[0]], nCurrInterDesc);
+ const size_t nInterDescDist = hdist(nCurrInterDesc, pCurrLocalWord->oFeature.anDesc[0]);
+ const size_t nDescDist = (nIntraDescDist + nInterDescDist) / 2;
+ if ((!bCurrRegionIsUnstable || bCurrRegionIsFlat || bCurrRegionIsROIBorder)
+ && nColorDist <= nCurrColorDistThreshold
+ && nColorDist >= nCurrColorDistThreshold / 2
+ && nIntraDescDist <= nCurrDescDistThreshold / 2
+ && (rand() % (nCurrRegionIllumUpdtVal ? (nCurrLocalWordUpdateRate / 2 + 1) : nCurrLocalWordUpdateRate)) == 0) {
+ // == illum updt
+ pCurrLocalWord->oFeature.anColor[0] = nCurrColor;
+ pCurrLocalWord->oFeature.anDesc[0] = nCurrIntraDesc;
+ m_oIllumUpdtRegionMask.data[nPxIter - 1] = 1 & m_oROI.data[nPxIter - 1];
+ m_oIllumUpdtRegionMask.data[nPxIter + 1] = 1 & m_oROI.data[nPxIter + 1];
+ m_oIllumUpdtRegionMask.data[nPxIter] = 2;
+ }
+ if (nDescDist <= nCurrDescDistThreshold && nColorDist <= nCurrColorDistThreshold) {
+ fPotentialLocalWordsWeightSum += fCurrLocalWordWeight;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ if ((!m_oLastFGMask.data[nPxIter] || m_bUsingMovingCamera) && fCurrLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pCurrLocalWord->nOccurrences += nCurrWordOccIncr;
+ nMinColorDist = std::min(nMinColorDist, nColorDist);
+ nMinDescDist = std::min(nMinDescDist, nDescDist);
+ }
+ }
+ if (fCurrLocalWordWeight > fLastLocalWordWeight) {
+ std::swap(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1]);
+ }
+ else
+ fLastLocalWordWeight = fCurrLocalWordWeight;
+ ++nLocalWordIdx;
+ }
+ while (nLocalWordIdx < m_nCurrLocalWords) {
+ const float fCurrLocalWordWeight = GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_nFrameIndex, m_nLocalWordWeightOffset);
+ if (fCurrLocalWordWeight > fLastLocalWordWeight) {
+ std::swap(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1]);
+ }
+ else
+ fLastLocalWordWeight = fCurrLocalWordWeight;
+ ++nLocalWordIdx;
+ }
+ if (fPotentialLocalWordsWeightSum >= fLocalWordsWeightSumThreshold || bCurrRegionIsROIBorder) {
+ // == background
+ const float fNormalizedMinDist = std::max((float)nMinColorDist / s_nColorMaxDataRange_1ch, (float)nMinDescDist / s_nDescMaxDataRange_1ch);
+ fCurrMeanMinDist_LT = fCurrMeanMinDist_LT*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ fCurrMeanMinDist_ST = fCurrMeanMinDist_ST*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ fCurrMeanRawSegmRes_LT = fCurrMeanRawSegmRes_LT*(1.0f - fRollAvgFactor_LT);
+ fCurrMeanRawSegmRes_ST = fCurrMeanRawSegmRes_ST*(1.0f - fRollAvgFactor_ST);
+ if ((rand() % nCurrLocalWordUpdateRate) == 0) {
+ size_t nGlobalWordLUTIdx;
+ GlobalWord_1ch* pCurrGlobalWord = nullptr;
+ for (nGlobalWordLUTIdx = 0; nGlobalWordLUTIdx < m_nCurrGlobalWords; ++nGlobalWordLUTIdx) {
+ pCurrGlobalWord = (GlobalWord_1ch*)m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx];
+ if (L1dist(pCurrGlobalWord->oFeature.anColor[0], nCurrColor) <= nCurrColorDistThreshold
+ && L1dist(nCurrIntraDescBITS, pCurrGlobalWord->nDescBITS) <= nCurrDescDistThreshold / GWORD_DESC_THRES_BITS_MATCH_FACTOR)
+ break;
+ }
+ if (nGlobalWordLUTIdx != m_nCurrGlobalWords || (rand() % (nCurrLocalWordUpdateRate * 2)) == 0) {
+ if (nGlobalWordLUTIdx == m_nCurrGlobalWords) {
+ pCurrGlobalWord = (GlobalWord_1ch*)m_apGlobalWordDict[m_nCurrGlobalWords - 1];
+ pCurrGlobalWord->oFeature.anColor[0] = nCurrColor;
+ pCurrGlobalWord->oFeature.anDesc[0] = nCurrIntraDesc;
+ pCurrGlobalWord->nDescBITS = nCurrIntraDescBITS;
+ pCurrGlobalWord->oSpatioOccMap = cv::Scalar(0.0f);
+ pCurrGlobalWord->fLatestWeight = 0.0f;
+ }
+ float& fCurrGlobalWordLocalWeight = *(float*)(pCurrGlobalWord->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fCurrGlobalWordLocalWeight < fPotentialLocalWordsWeightSum) {
+ pCurrGlobalWord->fLatestWeight += fPotentialLocalWordsWeightSum;
+ fCurrGlobalWordLocalWeight += fPotentialLocalWordsWeightSum;
+ }
+ }
+ }
+ }
+ else {
+ // == foreground
+ const float fNormalizedMinDist = std::max(std::max((float)nMinColorDist / s_nColorMaxDataRange_1ch, (float)nMinDescDist / s_nDescMaxDataRange_1ch), (fLocalWordsWeightSumThreshold - fPotentialLocalWordsWeightSum) / fLocalWordsWeightSumThreshold);
+ fCurrMeanMinDist_LT = fCurrMeanMinDist_LT*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ fCurrMeanMinDist_ST = fCurrMeanMinDist_ST*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ fCurrMeanRawSegmRes_LT = fCurrMeanRawSegmRes_LT*(1.0f - fRollAvgFactor_LT) + fRollAvgFactor_LT;
+ fCurrMeanRawSegmRes_ST = fCurrMeanRawSegmRes_ST*(1.0f - fRollAvgFactor_ST) + fRollAvgFactor_ST;
+ if (bCurrRegionIsFlat || (rand() % nCurrLocalWordUpdateRate) == 0) {
+ size_t nGlobalWordLUTIdx;
+ GlobalWord_1ch* pCurrGlobalWord;
+ for (nGlobalWordLUTIdx = 0; nGlobalWordLUTIdx < m_nCurrGlobalWords; ++nGlobalWordLUTIdx) {
+ pCurrGlobalWord = (GlobalWord_1ch*)m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx];
+ if (L1dist(pCurrGlobalWord->oFeature.anColor[0], nCurrColor) <= nCurrColorDistThreshold
+ && L1dist(nCurrIntraDescBITS, pCurrGlobalWord->nDescBITS) <= nCurrDescDistThreshold / GWORD_DESC_THRES_BITS_MATCH_FACTOR)
+ break;
+ }
+ if (nGlobalWordLUTIdx == m_nCurrGlobalWords)
+ nCurrRegionSegmVal = UCHAR_MAX;
+ else {
+ const float fGlobalWordLocalizedWeight = *(float*)(pCurrGlobalWord->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fPotentialLocalWordsWeightSum + fGlobalWordLocalizedWeight / (bCurrRegionIsFlat ? 2 : 4) < fLocalWordsWeightSumThreshold)
+ nCurrRegionSegmVal = UCHAR_MAX;
+ }
+ }
+ else
+ nCurrRegionSegmVal = UCHAR_MAX;
+ if (fPotentialLocalWordsWeightSum < DEFAULT_LWORD_INIT_WEIGHT) {
+ const size_t nNewLocalWordIdx = m_nCurrLocalWords - 1;
+ LocalWord_1ch* pNewLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nNewLocalWordIdx];
+ pNewLocalWord->oFeature.anColor[0] = nCurrColor;
+ pNewLocalWord->oFeature.anDesc[0] = nCurrIntraDesc;
+ pNewLocalWord->nOccurrences = nCurrWordOccIncr;
+ pNewLocalWord->nFirstOcc = m_nFrameIndex;
+ pNewLocalWord->nLastOcc = m_nFrameIndex;
+ }
+ }
+ // == neighb updt
+ if ((!nCurrRegionSegmVal && (rand() % nCurrLocalWordUpdateRate) == 0) || bCurrRegionIsROIBorder || m_bUsingMovingCamera) {
+ //if((!nCurrRegionSegmVal && (rand()%(nCurrRegionIllumUpdtVal?(nCurrLocalWordUpdateRate/2+1):nCurrLocalWordUpdateRate))==0) || bCurrRegionIsROIBorder) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ if (bCurrRegionIsFlat || bCurrRegionIsROIBorder || m_bUsingMovingCamera)
+ getRandNeighborPosition_5x5(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP_::PATCH_SIZE / 2, m_oImgSize);
+ else
+ getRandNeighborPosition_3x3(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP_::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (m_oROI.data[nSamplePxIdx]) {
+ const size_t nNeighborLocalDictIdx = m_aPxInfoLUT_PAWCS[nSamplePxIdx].nModelIdx*m_nCurrLocalWords;
+ size_t nNeighborLocalWordIdx = 0;
+ float fNeighborPotentialLocalWordsWeightSum = 0.0f;
+ while (nNeighborLocalWordIdx < m_nCurrLocalWords && fNeighborPotentialLocalWordsWeightSum < fLocalWordsWeightSumThreshold) {
+ LocalWord_1ch* pNeighborLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nNeighborLocalDictIdx + nNeighborLocalWordIdx];
+ const size_t nNeighborColorDist = L1dist(nCurrColor, pNeighborLocalWord->oFeature.anColor[0]);
+ const size_t nNeighborIntraDescDist = hdist(nCurrIntraDesc, pNeighborLocalWord->oFeature.anDesc[0]);
+ const bool bNeighborRegionIsFlat = popcount(pNeighborLocalWord->oFeature.anDesc[0]) < FLAT_REGION_BIT_COUNT;
+ const size_t nNeighborWordOccIncr = bNeighborRegionIsFlat ? nCurrWordOccIncr * 2 : nCurrWordOccIncr;
+ if (nNeighborColorDist <= nCurrColorDistThreshold && nNeighborIntraDescDist <= nCurrDescDistThreshold) {
+ const float fNeighborLocalWordWeight = GetLocalWordWeight(pNeighborLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ fNeighborPotentialLocalWordsWeightSum += fNeighborLocalWordWeight;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ if (fNeighborLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pNeighborLocalWord->nOccurrences += nNeighborWordOccIncr;
+ }
+ else if (!oCurrFGMask.data[nSamplePxIdx] && bCurrRegionIsFlat && (bBootstrapping || (rand() % nCurrLocalWordUpdateRate) == 0)) {
+ const size_t nSampleDescIdx = nSamplePxIdx * 2;
+ ushort& nNeighborLastIntraDesc = *((ushort*)(m_oLastDescFrame.data + nSampleDescIdx));
+ const size_t nNeighborLastIntraDescDist = hdist(nCurrIntraDesc, nNeighborLastIntraDesc);
+ if (nNeighborColorDist <= nCurrColorDistThreshold && nNeighborLastIntraDescDist <= nCurrDescDistThreshold / 2) {
+ const float fNeighborLocalWordWeight = GetLocalWordWeight(pNeighborLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ fNeighborPotentialLocalWordsWeightSum += fNeighborLocalWordWeight;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ if (fNeighborLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pNeighborLocalWord->nOccurrences += nNeighborWordOccIncr;
+ pNeighborLocalWord->oFeature.anDesc[0] = nCurrIntraDesc;
+ }
+ }
+ ++nNeighborLocalWordIdx;
+ }
+ if (fNeighborPotentialLocalWordsWeightSum < DEFAULT_LWORD_INIT_WEIGHT) {
+ nNeighborLocalWordIdx = m_nCurrLocalWords - 1;
+ LocalWord_1ch* pNeighborLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nNeighborLocalDictIdx + nNeighborLocalWordIdx];
+ pNeighborLocalWord->oFeature.anColor[0] = nCurrColor;
+ pNeighborLocalWord->oFeature.anDesc[0] = nCurrIntraDesc;
+ pNeighborLocalWord->nOccurrences = nCurrWordOccIncr;
+ pNeighborLocalWord->nFirstOcc = m_nFrameIndex;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ }
+ }
+ }
+ if (nCurrRegionIllumUpdtVal)
+ nCurrRegionIllumUpdtVal -= 1;
+ // == feedback adj
+ bCurrRegionIsUnstable = fCurrDistThresholdFactor > UNSTABLE_REG_RDIST_MIN || (fCurrMeanRawSegmRes_LT - fCurrMeanFinalSegmRes_LT) > UNSTABLE_REG_RATIO_MIN || (fCurrMeanRawSegmRes_ST - fCurrMeanFinalSegmRes_ST) > UNSTABLE_REG_RATIO_MIN;
+ if (m_oLastFGMask.data[nPxIter] || (std::min(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST) < UNSTABLE_REG_RATIO_MIN && nCurrRegionSegmVal))
+ fCurrLearningRate = std::min(fCurrLearningRate + FEEDBACK_T_INCR / (std::max(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST)*fCurrDistThresholdVariationFactor), FEEDBACK_T_UPPER);
+ else
+ fCurrLearningRate = std::max(fCurrLearningRate - FEEDBACK_T_DECR*fCurrDistThresholdVariationFactor / std::max(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST), FEEDBACK_T_LOWER);
+ if (std::max(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST) > UNSTABLE_REG_RATIO_MIN && m_oBlinksFrame.data[nPxIter])
+ (fCurrDistThresholdVariationFactor) += bBootstrapping ? FEEDBACK_V_INCR * 2 : FEEDBACK_V_INCR;
+ else
+ fCurrDistThresholdVariationFactor = std::max(fCurrDistThresholdVariationFactor - FEEDBACK_V_DECR*((bBootstrapping || bCurrRegionIsFlat) ? 2 : m_oLastFGMask.data[nPxIter] ? 0.5f : 1), FEEDBACK_V_DECR);
+ if (fCurrDistThresholdFactor < std::pow(1.0f + std::min(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST) * 2, 2))
+ fCurrDistThresholdFactor += FEEDBACK_R_VAR*(fCurrDistThresholdVariationFactor - FEEDBACK_V_DECR);
+ else
+ fCurrDistThresholdFactor = std::max(fCurrDistThresholdFactor - FEEDBACK_R_VAR / fCurrDistThresholdVariationFactor, 1.0f);
+ nLastIntraDesc = nCurrIntraDesc;
+ nLastColor = nCurrColor;
+ }
+ }
+ else { //m_nImgChannels==3
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nPxRGBIter = nPxIter * 3;
+ const size_t nDescRGBIter = nPxRGBIter * 2;
+ const size_t nFloatIter = nPxIter * 4;
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const size_t nGlobalWordMapLookupIdx = m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx;
+ const uchar* const anCurrColor = oInputImg.data + nPxRGBIter;
+ uchar* anLastColor = m_oLastColorFrame.data + nPxRGBIter;
+ ushort* anLastIntraDesc = ((ushort*)(m_oLastDescFrame.data + nDescRGBIter));
+ size_t nMinTotColorDist = s_nColorMaxDataRange_3ch;
+ size_t nMinTotDescDist = s_nDescMaxDataRange_3ch;
+ float& fCurrMeanRawSegmRes_LT = *(float*)(m_oMeanRawSegmResFrame_LT.data + nFloatIter);
+ float& fCurrMeanRawSegmRes_ST = *(float*)(m_oMeanRawSegmResFrame_ST.data + nFloatIter);
+ float& fCurrMeanFinalSegmRes_LT = *(float*)(m_oMeanFinalSegmResFrame_LT.data + nFloatIter);
+ float& fCurrMeanFinalSegmRes_ST = *(float*)(m_oMeanFinalSegmResFrame_ST.data + nFloatIter);
+ float& fCurrDistThresholdFactor = *(float*)(m_oDistThresholdFrame.data + nFloatIter);
+ float& fCurrDistThresholdVariationFactor = *(float*)(m_oDistThresholdVariationFrame.data + nFloatIter);
+ float& fCurrLearningRate = *(float*)(m_oUpdateRateFrame.data + nFloatIter);
+ float& fCurrMeanMinDist_LT = *(float*)(m_oMeanMinDistFrame_LT.data + nFloatIter);
+ float& fCurrMeanMinDist_ST = *(float*)(m_oMeanMinDistFrame_ST.data + nFloatIter);
+ const float fBestLocalWordWeight = GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx], m_nFrameIndex, m_nLocalWordWeightOffset);
+ const float fLocalWordsWeightSumThreshold = fBestLocalWordWeight / (fCurrDistThresholdFactor * 2);
+ uchar& bCurrRegionIsUnstable = m_oUnstableRegionMask.data[nPxIter];
+ uchar& nCurrRegionIllumUpdtVal = m_oIllumUpdtRegionMask.data[nPxIter];
+ uchar& nCurrRegionSegmVal = oCurrFGMask.data[nPxIter];
+ const bool bCurrRegionIsROIBorder = m_oROI.data[nPxIter] < UCHAR_MAX;
+ const int nCurrImgCoord_X = m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y;
+ ushort anCurrInterDesc[3], anCurrIntraDesc[3];
+ const size_t anCurrIntraLBSPThresholds[3] = { m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]] };
+ LBSP_::computeRGBDescriptor(oInputImg, anCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, anCurrIntraLBSPThresholds, anCurrIntraDesc);
+ const uchar nCurrIntraDescBITS = (uchar)popcount<3>(anCurrIntraDesc);
+ const bool bCurrRegionIsFlat = nCurrIntraDescBITS < FLAT_REGION_BIT_COUNT * 2;
+ if (bCurrRegionIsFlat)
+ ++nFlatRegionCount;
+ const size_t nCurrWordOccIncr = (DEFAULT_LWORD_OCC_INCR + m_nModelResetCooldown) << int(bCurrRegionIsFlat || bBootstrapping);
+ const size_t nCurrLocalWordUpdateRate = learningRateOverride > 0 ? (size_t)ceil(learningRateOverride) : bCurrRegionIsFlat ? (size_t)ceil(fCurrLearningRate + FEEDBACK_T_LOWER) / 2 : (size_t)ceil(fCurrLearningRate);
+ const size_t nCurrTotColorDistThreshold = (size_t)(sqrt(fCurrDistThresholdFactor)*m_nMinColorDistThreshold) * 3;
+ const size_t nCurrTotDescDistThreshold = (((size_t)1 << ((size_t)floor(fCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (bCurrRegionIsUnstable*UNSTAB_DESC_DIST_OFFSET)) * 3;
+ size_t nLocalWordIdx = 0;
+ float fPotentialLocalWordsWeightSum = 0.0f;
+ float fLastLocalWordWeight = FLT_MAX;
+ while (nLocalWordIdx < m_nCurrLocalWords && fPotentialLocalWordsWeightSum < fLocalWordsWeightSumThreshold) {
+ LocalWord_3ch* pCurrLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ const float fCurrLocalWordWeight = GetLocalWordWeight(pCurrLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ {
+ const size_t nTotColorL1Dist = L1dist<3>(anCurrColor, pCurrLocalWord->oFeature.anColor);
+ const size_t nColorDistortion = cdist<3>(anCurrColor, pCurrLocalWord->oFeature.anColor);
+ const size_t nTotColorMixDist = cmixdist(nTotColorL1Dist, nColorDistortion);
+ const size_t nTotIntraDescDist = hdist<3>(anCurrIntraDesc, pCurrLocalWord->oFeature.anDesc);
+ const size_t anCurrInterLBSPThresholds[3] = { m_anLBSPThreshold_8bitLUT[pCurrLocalWord->oFeature.anColor[0]],m_anLBSPThreshold_8bitLUT[pCurrLocalWord->oFeature.anColor[1]],m_anLBSPThreshold_8bitLUT[pCurrLocalWord->oFeature.anColor[2]] };
+ LBSP_::computeRGBDescriptor(oInputImg, pCurrLocalWord->oFeature.anColor, nCurrImgCoord_X, nCurrImgCoord_Y, anCurrInterLBSPThresholds, anCurrInterDesc);
+ const size_t nTotInterDescDist = hdist<3>(anCurrInterDesc, pCurrLocalWord->oFeature.anDesc);
+ const size_t nTotDescDist = (nTotIntraDescDist + nTotInterDescDist) / 2;
+ if ((!bCurrRegionIsUnstable || bCurrRegionIsFlat || bCurrRegionIsROIBorder)
+ && nTotColorMixDist <= nCurrTotColorDistThreshold
+ && nTotColorL1Dist >= nCurrTotColorDistThreshold / 2
+ && nTotIntraDescDist <= nCurrTotDescDistThreshold / 2
+ && (rand() % (nCurrRegionIllumUpdtVal ? (nCurrLocalWordUpdateRate / 2 + 1) : nCurrLocalWordUpdateRate)) == 0) {
+ // == illum updt
+ for (size_t c = 0; c < 3; ++c) {
+ pCurrLocalWord->oFeature.anColor[c] = anCurrColor[c];
+ pCurrLocalWord->oFeature.anDesc[c] = anCurrIntraDesc[c];
+ }
+ m_oIllumUpdtRegionMask.data[nPxIter - 1] = 1 & m_oROI.data[nPxIter - 1];
+ m_oIllumUpdtRegionMask.data[nPxIter + 1] = 1 & m_oROI.data[nPxIter + 1];
+ m_oIllumUpdtRegionMask.data[nPxIter] = 2;
+ }
+ if (nTotDescDist <= nCurrTotDescDistThreshold && nTotColorMixDist <= nCurrTotColorDistThreshold) {
+ fPotentialLocalWordsWeightSum += fCurrLocalWordWeight;
+ pCurrLocalWord->nLastOcc = m_nFrameIndex;
+ if ((!m_oLastFGMask.data[nPxIter] || m_bUsingMovingCamera) && fCurrLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pCurrLocalWord->nOccurrences += nCurrWordOccIncr;
+ nMinTotColorDist = std::min(nMinTotColorDist, nTotColorMixDist);
+ nMinTotDescDist = std::min(nMinTotDescDist, nTotDescDist);
+ }
+ }
+ if (fCurrLocalWordWeight > fLastLocalWordWeight) {
+ std::swap(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1]);
+ }
+ else
+ fLastLocalWordWeight = fCurrLocalWordWeight;
+ ++nLocalWordIdx;
+ }
+ while (nLocalWordIdx < m_nCurrLocalWords) {
+ const float fCurrLocalWordWeight = GetLocalWordWeight(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_nFrameIndex, m_nLocalWordWeightOffset);
+ if (fCurrLocalWordWeight > fLastLocalWordWeight) {
+ std::swap(m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx], m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx - 1]);
+ }
+ else
+ fLastLocalWordWeight = fCurrLocalWordWeight;
+ ++nLocalWordIdx;
+ }
+ if (fPotentialLocalWordsWeightSum >= fLocalWordsWeightSumThreshold || bCurrRegionIsROIBorder) {
+ // == background
+ const float fNormalizedMinDist = std::max((float)nMinTotColorDist / s_nColorMaxDataRange_3ch, (float)nMinTotDescDist / s_nDescMaxDataRange_3ch);
+ fCurrMeanMinDist_LT = fCurrMeanMinDist_LT*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ fCurrMeanMinDist_ST = fCurrMeanMinDist_ST*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ fCurrMeanRawSegmRes_LT = fCurrMeanRawSegmRes_LT*(1.0f - fRollAvgFactor_LT);
+ fCurrMeanRawSegmRes_ST = fCurrMeanRawSegmRes_ST*(1.0f - fRollAvgFactor_ST);
+ if ((rand() % nCurrLocalWordUpdateRate) == 0) {
+ size_t nGlobalWordLUTIdx;
+ GlobalWord_3ch* pCurrGlobalWord = nullptr;
+ for (nGlobalWordLUTIdx = 0; nGlobalWordLUTIdx < m_nCurrGlobalWords; ++nGlobalWordLUTIdx) {
+ pCurrGlobalWord = (GlobalWord_3ch*)m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx];
+ if (L1dist(nCurrIntraDescBITS, pCurrGlobalWord->nDescBITS) <= nCurrTotDescDistThreshold / GWORD_DESC_THRES_BITS_MATCH_FACTOR
+ && cmixdist<3>(anCurrColor, pCurrGlobalWord->oFeature.anColor) <= nCurrTotColorDistThreshold)
+ break;
+ }
+ if (nGlobalWordLUTIdx != m_nCurrGlobalWords || (rand() % (nCurrLocalWordUpdateRate * 2)) == 0) {
+ if (nGlobalWordLUTIdx == m_nCurrGlobalWords) {
+ pCurrGlobalWord = (GlobalWord_3ch*)m_apGlobalWordDict[m_nCurrGlobalWords - 1];
+ for (size_t c = 0; c < 3; ++c) {
+ pCurrGlobalWord->oFeature.anColor[c] = anCurrColor[c];
+ pCurrGlobalWord->oFeature.anDesc[c] = anCurrIntraDesc[c];
+ }
+ pCurrGlobalWord->nDescBITS = nCurrIntraDescBITS;
+ pCurrGlobalWord->oSpatioOccMap = cv::Scalar(0.0f);
+ pCurrGlobalWord->fLatestWeight = 0.0f;
+ }
+ float& fCurrGlobalWordLocalWeight = *(float*)(pCurrGlobalWord->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fCurrGlobalWordLocalWeight < fPotentialLocalWordsWeightSum) {
+ pCurrGlobalWord->fLatestWeight += fPotentialLocalWordsWeightSum;
+ fCurrGlobalWordLocalWeight += fPotentialLocalWordsWeightSum;
+ }
+ }
+ }
+ }
+ else {
+ // == foreground
+ const float fNormalizedMinDist = std::max(std::max((float)nMinTotColorDist / s_nColorMaxDataRange_3ch, (float)nMinTotDescDist / s_nDescMaxDataRange_3ch), (fLocalWordsWeightSumThreshold - fPotentialLocalWordsWeightSum) / fLocalWordsWeightSumThreshold);
+ fCurrMeanMinDist_LT = fCurrMeanMinDist_LT*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ fCurrMeanMinDist_ST = fCurrMeanMinDist_ST*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ fCurrMeanRawSegmRes_LT = fCurrMeanRawSegmRes_LT*(1.0f - fRollAvgFactor_LT) + fRollAvgFactor_LT;
+ fCurrMeanRawSegmRes_ST = fCurrMeanRawSegmRes_ST*(1.0f - fRollAvgFactor_ST) + fRollAvgFactor_ST;
+ if (bCurrRegionIsFlat || (rand() % nCurrLocalWordUpdateRate) == 0) {
+ size_t nGlobalWordLUTIdx;
+ GlobalWord_3ch* pCurrGlobalWord;
+ for (nGlobalWordLUTIdx = 0; nGlobalWordLUTIdx < m_nCurrGlobalWords; ++nGlobalWordLUTIdx) {
+ pCurrGlobalWord = (GlobalWord_3ch*)m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx];
+ if (L1dist(nCurrIntraDescBITS, pCurrGlobalWord->nDescBITS) <= nCurrTotDescDistThreshold / GWORD_DESC_THRES_BITS_MATCH_FACTOR
+ && cmixdist<3>(anCurrColor, pCurrGlobalWord->oFeature.anColor) <= nCurrTotColorDistThreshold)
+ break;
+ }
+ if (nGlobalWordLUTIdx == m_nCurrGlobalWords)
+ nCurrRegionSegmVal = UCHAR_MAX;
+ else {
+ const float fGlobalWordLocalizedWeight = *(float*)(pCurrGlobalWord->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fPotentialLocalWordsWeightSum + fGlobalWordLocalizedWeight / (bCurrRegionIsFlat ? 2 : 4) < fLocalWordsWeightSumThreshold)
+ nCurrRegionSegmVal = UCHAR_MAX;
+ }
+ }
+ else
+ nCurrRegionSegmVal = UCHAR_MAX;
+ if (fPotentialLocalWordsWeightSum < DEFAULT_LWORD_INIT_WEIGHT) {
+ const size_t nNewLocalWordIdx = m_nCurrLocalWords - 1;
+ LocalWord_3ch* pNewLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nNewLocalWordIdx];
+ for (size_t c = 0; c < 3; ++c) {
+ pNewLocalWord->oFeature.anColor[c] = anCurrColor[c];
+ pNewLocalWord->oFeature.anDesc[c] = anCurrIntraDesc[c];
+ }
+ pNewLocalWord->nOccurrences = nCurrWordOccIncr;
+ pNewLocalWord->nFirstOcc = m_nFrameIndex;
+ pNewLocalWord->nLastOcc = m_nFrameIndex;
+ }
+ }
+ // == neighb updt
+ if ((!nCurrRegionSegmVal && (rand() % nCurrLocalWordUpdateRate) == 0) || bCurrRegionIsROIBorder || m_bUsingMovingCamera) {
+ //if((!nCurrRegionSegmVal && (rand()%(nCurrRegionIllumUpdtVal?(nCurrLocalWordUpdateRate/2+1):nCurrLocalWordUpdateRate))==0) || bCurrRegionIsROIBorder) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ if (bCurrRegionIsFlat || bCurrRegionIsROIBorder || m_bUsingMovingCamera)
+ getRandNeighborPosition_5x5(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP_::PATCH_SIZE / 2, m_oImgSize);
+ else
+ getRandNeighborPosition_3x3(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP_::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (m_oROI.data[nSamplePxIdx]) {
+ const size_t nNeighborLocalDictIdx = m_aPxInfoLUT_PAWCS[nSamplePxIdx].nModelIdx*m_nCurrLocalWords;
+ size_t nNeighborLocalWordIdx = 0;
+ float fNeighborPotentialLocalWordsWeightSum = 0.0f;
+ while (nNeighborLocalWordIdx < m_nCurrLocalWords && fNeighborPotentialLocalWordsWeightSum < fLocalWordsWeightSumThreshold) {
+ LocalWord_3ch* pNeighborLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nNeighborLocalDictIdx + nNeighborLocalWordIdx];
+ const size_t nNeighborTotColorL1Dist = L1dist<3>(anCurrColor, pNeighborLocalWord->oFeature.anColor);
+ const size_t nNeighborColorDistortion = cdist<3>(anCurrColor, pNeighborLocalWord->oFeature.anColor);
+ const size_t nNeighborTotColorMixDist = cmixdist(nNeighborTotColorL1Dist, nNeighborColorDistortion);
+ const size_t nNeighborTotIntraDescDist = hdist<3>(anCurrIntraDesc, pNeighborLocalWord->oFeature.anDesc);
+ const bool bNeighborRegionIsFlat = popcount<3>(pNeighborLocalWord->oFeature.anDesc) < FLAT_REGION_BIT_COUNT * 2;
+ const size_t nNeighborWordOccIncr = bNeighborRegionIsFlat ? nCurrWordOccIncr * 2 : nCurrWordOccIncr;
+ if (nNeighborTotColorMixDist <= nCurrTotColorDistThreshold && nNeighborTotIntraDescDist <= nCurrTotDescDistThreshold) {
+ const float fNeighborLocalWordWeight = GetLocalWordWeight(pNeighborLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ fNeighborPotentialLocalWordsWeightSum += fNeighborLocalWordWeight;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ if (fNeighborLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pNeighborLocalWord->nOccurrences += nNeighborWordOccIncr;
+ }
+ else if (!oCurrFGMask.data[nSamplePxIdx] && bCurrRegionIsFlat && (bBootstrapping || (rand() % nCurrLocalWordUpdateRate) == 0)) {
+ const size_t nSamplePxRGBIdx = nSamplePxIdx * 3;
+ const size_t nSampleDescRGBIdx = nSamplePxRGBIdx * 2;
+ ushort* anNeighborLastIntraDesc = ((ushort*)(m_oLastDescFrame.data + nSampleDescRGBIdx));
+ const size_t nNeighborTotLastIntraDescDist = hdist<3>(anCurrIntraDesc, anNeighborLastIntraDesc);
+ if (nNeighborTotColorMixDist <= nCurrTotColorDistThreshold && nNeighborTotLastIntraDescDist <= nCurrTotDescDistThreshold / 2) {
+ const float fNeighborLocalWordWeight = GetLocalWordWeight(pNeighborLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ fNeighborPotentialLocalWordsWeightSum += fNeighborLocalWordWeight;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ if (fNeighborLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pNeighborLocalWord->nOccurrences += nNeighborWordOccIncr;
+ for (size_t c = 0; c < 3; ++c)
+ pNeighborLocalWord->oFeature.anDesc[c] = anCurrIntraDesc[c];
+ }
+ else {
+ const bool bNeighborLastRegionIsFlat = popcount<3>(anNeighborLastIntraDesc) < FLAT_REGION_BIT_COUNT * 2;
+ if (bNeighborLastRegionIsFlat && bCurrRegionIsFlat &&
+ nNeighborTotLastIntraDescDist + nNeighborTotIntraDescDist <= nCurrTotDescDistThreshold &&
+ nNeighborColorDistortion <= nCurrTotColorDistThreshold / 4) {
+ const float fNeighborLocalWordWeight = GetLocalWordWeight(pNeighborLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ fNeighborPotentialLocalWordsWeightSum += fNeighborLocalWordWeight;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ if (fNeighborLocalWordWeight < DEFAULT_LWORD_MAX_WEIGHT)
+ pNeighborLocalWord->nOccurrences += nNeighborWordOccIncr;
+ for (size_t c = 0; c < 3; ++c)
+ pNeighborLocalWord->oFeature.anColor[c] = anCurrColor[c];
+ }
+ }
+ }
+ ++nNeighborLocalWordIdx;
+ }
+ if (fNeighborPotentialLocalWordsWeightSum < DEFAULT_LWORD_INIT_WEIGHT) {
+ nNeighborLocalWordIdx = m_nCurrLocalWords - 1;
+ LocalWord_3ch* pNeighborLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nNeighborLocalDictIdx + nNeighborLocalWordIdx];
+ for (size_t c = 0; c < 3; ++c) {
+ pNeighborLocalWord->oFeature.anColor[c] = anCurrColor[c];
+ pNeighborLocalWord->oFeature.anDesc[c] = anCurrIntraDesc[c];
+ }
+ pNeighborLocalWord->nOccurrences = nCurrWordOccIncr;
+ pNeighborLocalWord->nFirstOcc = m_nFrameIndex;
+ pNeighborLocalWord->nLastOcc = m_nFrameIndex;
+ }
+ }
+ }
+ if (nCurrRegionIllumUpdtVal)
+ nCurrRegionIllumUpdtVal -= 1;
+ // == feedback adj
+ bCurrRegionIsUnstable = fCurrDistThresholdFactor > UNSTABLE_REG_RDIST_MIN || (fCurrMeanRawSegmRes_LT - fCurrMeanFinalSegmRes_LT) > UNSTABLE_REG_RATIO_MIN || (fCurrMeanRawSegmRes_ST - fCurrMeanFinalSegmRes_ST) > UNSTABLE_REG_RATIO_MIN;
+ if (m_oLastFGMask.data[nPxIter] || (std::min(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST) < UNSTABLE_REG_RATIO_MIN && nCurrRegionSegmVal))
+ fCurrLearningRate = std::min(fCurrLearningRate + FEEDBACK_T_INCR / (std::max(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST)*fCurrDistThresholdVariationFactor), FEEDBACK_T_UPPER);
+ else
+ fCurrLearningRate = std::max(fCurrLearningRate - FEEDBACK_T_DECR*fCurrDistThresholdVariationFactor / std::max(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST), FEEDBACK_T_LOWER);
+ if (std::max(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST) > UNSTABLE_REG_RATIO_MIN && m_oBlinksFrame.data[nPxIter])
+ (fCurrDistThresholdVariationFactor) += bBootstrapping ? FEEDBACK_V_INCR * 2 : FEEDBACK_V_INCR;
+ else
+ fCurrDistThresholdVariationFactor = std::max(fCurrDistThresholdVariationFactor - FEEDBACK_V_DECR*((bBootstrapping || bCurrRegionIsFlat) ? 2 : m_oLastFGMask.data[nPxIter] ? 0.5f : 1), FEEDBACK_V_DECR);
+ if (fCurrDistThresholdFactor < std::pow(1.0f + std::min(fCurrMeanMinDist_LT, fCurrMeanMinDist_ST) * 2, 2))
+ fCurrDistThresholdFactor += FEEDBACK_R_VAR*(fCurrDistThresholdVariationFactor - FEEDBACK_V_DECR);
+ else
+ fCurrDistThresholdFactor = std::max(fCurrDistThresholdFactor - FEEDBACK_R_VAR / fCurrDistThresholdVariationFactor, 1.0f);
+ for (size_t c = 0; c < 3; ++c) {
+ anLastIntraDesc[c] = anCurrIntraDesc[c];
+ anLastColor[c] = anCurrColor[c];
+ }
+ }
+ }
+ const bool bRecalcGlobalWords = !(m_nFrameIndex % (nCurrGlobalWordUpdateRate << 5));
+ const bool bUpdateGlobalWords = !(m_nFrameIndex % (nCurrGlobalWordUpdateRate));
+ cv::Mat oLastFGMask_dilated_inverted_downscaled;
+ if (bUpdateGlobalWords)
+ cv::resize(m_oLastFGMask_dilated_inverted, oLastFGMask_dilated_inverted_downscaled, m_oDownSampledFrameSize_GlobalWordLookup, 0, 0, cv::INTER_NEAREST);
+ for (size_t nGlobalWordIdx = 0; nGlobalWordIdx < m_nCurrGlobalWords; ++nGlobalWordIdx) {
+ if (bRecalcGlobalWords && m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight > 0.0f) {
+ m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight = GetGlobalWordWeight(m_apGlobalWordDict[nGlobalWordIdx]);
+ if (m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight < 1.0f) {
+ m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight = 0.0f;
+ m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap = cv::Scalar(0.0f);
+ }
+ }
+ if (bUpdateGlobalWords && m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight > 0.0f) {
+ cv::accumulateProduct(m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap, m_oTempGlobalWordWeightDiffFactor, m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap, oLastFGMask_dilated_inverted_downscaled);
+ m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight *= 0.9f;
+ cv::blur(m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap, m_apGlobalWordDict[nGlobalWordIdx]->oSpatioOccMap, cv::Size(3, 3), cv::Point(-1, -1), cv::BORDER_REPLICATE);
+ }
+ if (nGlobalWordIdx > 0 && m_apGlobalWordDict[nGlobalWordIdx]->fLatestWeight > m_apGlobalWordDict[nGlobalWordIdx - 1]->fLatestWeight)
+ std::swap(m_apGlobalWordDict[nGlobalWordIdx], m_apGlobalWordDict[nGlobalWordIdx - 1]);
+ }
+ if (bUpdateGlobalWords) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nGlobalWordMapLookupIdx = m_aPxInfoLUT_PAWCS[nPxIter].nGlobalWordMapLookupIdx;
+ float fLastGlobalWordLocalWeight = *(float*)(m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[0]->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ for (size_t nGlobalWordLUTIdx = 1; nGlobalWordLUTIdx < m_nCurrGlobalWords; ++nGlobalWordLUTIdx) {
+ const float fCurrGlobalWordLocalWeight = *(float*)(m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx]->oSpatioOccMap.data + nGlobalWordMapLookupIdx);
+ if (fCurrGlobalWordLocalWeight > fLastGlobalWordLocalWeight)
+ std::swap(m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx], m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT[nGlobalWordLUTIdx - 1]);
+ else
+ fLastGlobalWordLocalWeight = fCurrGlobalWordLocalWeight;
+ }
+ }
+ }
+ cv::bitwise_xor(oCurrFGMask, m_oLastRawFGMask, m_oCurrRawFGBlinkMask);
+ cv::bitwise_or(m_oCurrRawFGBlinkMask, m_oLastRawFGBlinkMask, m_oBlinksFrame);
+ m_oCurrRawFGBlinkMask.copyTo(m_oLastRawFGBlinkMask);
+ oCurrFGMask.copyTo(m_oLastRawFGMask);
+ cv::morphologyEx(oCurrFGMask, m_oFGMask_PreFlood, cv::MORPH_CLOSE, m_oMorphExStructElement);
+ m_oFGMask_PreFlood.copyTo(m_oFGMask_FloodedHoles);
+ cv::floodFill(m_oFGMask_FloodedHoles, cv::Point(0, 0), UCHAR_MAX);
+ cv::bitwise_not(m_oFGMask_FloodedHoles, m_oFGMask_FloodedHoles);
+ cv::erode(m_oFGMask_PreFlood, m_oFGMask_PreFlood, cv::Mat(), cv::Point(-1, -1), 3);
+ cv::bitwise_or(oCurrFGMask, m_oFGMask_FloodedHoles, oCurrFGMask);
+ cv::bitwise_or(oCurrFGMask, m_oFGMask_PreFlood, oCurrFGMask);
+ cv::medianBlur(oCurrFGMask, m_oLastFGMask, m_nMedianBlurKernelSize);
+ cv::dilate(m_oLastFGMask, m_oLastFGMask_dilated, cv::Mat(), cv::Point(-1, -1), 3);
+ cv::bitwise_and(m_oBlinksFrame, m_oLastFGMask_dilated_inverted, m_oBlinksFrame);
+ cv::bitwise_not(m_oLastFGMask_dilated, m_oLastFGMask_dilated_inverted);
+ cv::bitwise_and(m_oBlinksFrame, m_oLastFGMask_dilated_inverted, m_oBlinksFrame);
+ m_oLastFGMask.copyTo(oCurrFGMask);
+ cv::addWeighted(m_oMeanFinalSegmResFrame_LT, (1.0f - fRollAvgFactor_LT), m_oLastFGMask, (1.0 / UCHAR_MAX)*fRollAvgFactor_LT, 0, m_oMeanFinalSegmResFrame_LT, CV_32F);
+ cv::addWeighted(m_oMeanFinalSegmResFrame_ST, (1.0f - fRollAvgFactor_ST), m_oLastFGMask, (1.0 / UCHAR_MAX)*fRollAvgFactor_ST, 0, m_oMeanFinalSegmResFrame_ST, CV_32F);
+ const float fCurrNonFlatRegionRatio = (float)(m_nTotRelevantPxCount - nFlatRegionCount) / m_nTotRelevantPxCount;
+ if (fCurrNonFlatRegionRatio < LBSPDESC_RATIO_MIN && m_fLastNonFlatRegionRatio < LBSPDESC_RATIO_MIN) {
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ if (m_anLBSPThreshold_8bitLUT[t] > cv::saturate_cast<uchar>((m_nLBSPThresholdOffset + t*m_fRelLBSPThreshold) / 4))
+ --m_anLBSPThreshold_8bitLUT[t];
+ }
+ else if (fCurrNonFlatRegionRatio > LBSPDESC_RATIO_MAX && m_fLastNonFlatRegionRatio > LBSPDESC_RATIO_MAX) {
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ if (m_anLBSPThreshold_8bitLUT[t] < cv::saturate_cast<uchar>(m_nLBSPThresholdOffset + UCHAR_MAX*m_fRelLBSPThreshold))
+ ++m_anLBSPThreshold_8bitLUT[t];
+ }
+ m_fLastNonFlatRegionRatio = fCurrNonFlatRegionRatio;
+ cv::resize(oInputImg, m_oDownSampledFrame_MotionAnalysis, m_oDownSampledFrameSize_MotionAnalysis, 0, 0, cv::INTER_AREA);
+ cv::accumulateWeighted(m_oDownSampledFrame_MotionAnalysis, m_oMeanDownSampledLastDistFrame_LT, fRollAvgFactor_LT);
+ cv::accumulateWeighted(m_oDownSampledFrame_MotionAnalysis, m_oMeanDownSampledLastDistFrame_ST, fRollAvgFactor_ST);
+ const float fCurrMeanL1DistRatio = L1dist((float*)m_oMeanDownSampledLastDistFrame_LT.data, (float*)m_oMeanDownSampledLastDistFrame_ST.data, m_oMeanDownSampledLastDistFrame_LT.total(), m_nImgChannels, m_oDownSampledROI_MotionAnalysis.data) / m_nDownSampledROIPxCount;
+ if (!m_bAutoModelResetEnabled && fCurrMeanL1DistRatio >= FRAMELEVEL_MIN_L1DIST_THRES * 2)
+ m_bAutoModelResetEnabled = true;
+ if (m_bAutoModelResetEnabled || m_bUsingMovingCamera) {
+ if ((m_nFrameIndex%DEFAULT_BOOTSTRAP_WIN_SIZE) == 0) {
+ cv::Mat oCurrBackgroundImg, oDownSampledBackgroundImg;
+ getBackgroundImage(oCurrBackgroundImg);
+ cv::resize(oCurrBackgroundImg, oDownSampledBackgroundImg, m_oDownSampledFrameSize_MotionAnalysis, 0, 0, cv::INTER_AREA);
+ cv::Mat oDownSampledBackgroundImg_32F; oDownSampledBackgroundImg.convertTo(oDownSampledBackgroundImg_32F, CV_32F);
+ const float fCurrModelL1DistRatio = L1dist((float*)m_oMeanDownSampledLastDistFrame_LT.data, (float*)oDownSampledBackgroundImg_32F.data, m_oMeanDownSampledLastDistFrame_LT.total(), m_nImgChannels, cv::Mat(m_oDownSampledROI_MotionAnalysis == UCHAR_MAX).data) / m_nDownSampledROIPxCount;
+ const float fCurrModelCDistRatio = cdist((float*)m_oMeanDownSampledLastDistFrame_LT.data, (float*)oDownSampledBackgroundImg_32F.data, m_oMeanDownSampledLastDistFrame_LT.total(), m_nImgChannels, cv::Mat(m_oDownSampledROI_MotionAnalysis == UCHAR_MAX).data) / m_nDownSampledROIPxCount;
+ if (m_bUsingMovingCamera && fCurrModelL1DistRatio < FRAMELEVEL_MIN_L1DIST_THRES / 4 && fCurrModelCDistRatio < FRAMELEVEL_MIN_CDIST_THRES / 4) {
+ m_nLocalWordWeightOffset = DEFAULT_LWORD_WEIGHT_OFFSET;
+ m_bUsingMovingCamera = false;
+ refreshModel(1, 1, true);
+ }
+ else if (bBootstrapping && !m_bUsingMovingCamera && (fCurrModelL1DistRatio >= FRAMELEVEL_MIN_L1DIST_THRES || fCurrModelCDistRatio >= FRAMELEVEL_MIN_CDIST_THRES)) {
+ m_nLocalWordWeightOffset = 5;
+ m_bUsingMovingCamera = true;
+ refreshModel(1, 1, true);
+ }
+ }
+ if (m_nFramesSinceLastReset > DEFAULT_BOOTSTRAP_WIN_SIZE * 2)
+ m_bAutoModelResetEnabled = false;
+ else if (fCurrMeanL1DistRatio >= FRAMELEVEL_MIN_L1DIST_THRES && m_nModelResetCooldown == 0) {
+ m_nFramesSinceLastReset = 0;
+ refreshModel(m_nLocalWordWeightOffset / 8, 0, true);
+ m_nModelResetCooldown = nCurrSamplesForMovingAvg_ST;
+ m_oUpdateRateFrame = cv::Scalar(1.0f);
+ }
+ else if (!bBootstrapping)
+ ++m_nFramesSinceLastReset;
+ }
+ if (m_nModelResetCooldown > 0)
+ --m_nModelResetCooldown;
+}
+
+void BackgroundSubtractorPAWCS::getBackgroundImage(cv::OutputArray backgroundImage) const { // @@@ add option to reconstruct from gwords?
+ CV_Assert(m_bInitialized);
+ cv::Mat oAvgBGImg = cv::Mat::zeros(m_oImgSize, CV_32FC((int)m_nImgChannels));
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nLocalDictIdx = nModelIter*m_nCurrLocalWords;
+ const int nCurrImgCoord_X = m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT_PAWCS[nPxIter].nImgCoord_Y;
+ if (m_nImgChannels == 1) {
+ float fTotWeight = 0.0f;
+ float fTotColor = 0.0f;
+ for (size_t nLocalWordIdx = 0; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ LocalWord_1ch* pCurrLocalWord = (LocalWord_1ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ float fCurrWeight = GetLocalWordWeight(pCurrLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ fTotColor += (float)pCurrLocalWord->oFeature.anColor[0] * fCurrWeight;
+ fTotWeight += fCurrWeight;
+ }
+ oAvgBGImg.at<float>(nCurrImgCoord_Y, nCurrImgCoord_X) = fTotColor / fTotWeight;
+ }
+ else { //m_nImgChannels==3
+ float fTotWeight = 0.0f;
+ float fTotColor[3] = { 0.0f,0.0f,0.0f };
+ for (size_t nLocalWordIdx = 0; nLocalWordIdx < m_nCurrLocalWords; ++nLocalWordIdx) {
+ LocalWord_3ch* pCurrLocalWord = (LocalWord_3ch*)m_apLocalWordDict[nLocalDictIdx + nLocalWordIdx];
+ float fCurrWeight = GetLocalWordWeight(pCurrLocalWord, m_nFrameIndex, m_nLocalWordWeightOffset);
+ for (size_t c = 0; c < 3; ++c)
+ fTotColor[c] += (float)pCurrLocalWord->oFeature.anColor[c] * fCurrWeight;
+ fTotWeight += fCurrWeight;
+ }
+ oAvgBGImg.at<cv::Vec3f>(nCurrImgCoord_Y, nCurrImgCoord_X) = cv::Vec3f(fTotColor[0] / fTotWeight, fTotColor[1] / fTotWeight, fTotColor[2] / fTotWeight);
+ }
+ }
+ oAvgBGImg.convertTo(backgroundImage, CV_8U);
+}
+
+void BackgroundSubtractorPAWCS::getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const {
+ CV_Assert(LBSP_::DESC_SIZE == 2);
+ CV_Assert(m_bInitialized);
+ cv::Mat oAvgBGDesc = cv::Mat::zeros(m_oImgSize, CV_32FC((int)m_nImgChannels));
+ // @@@@@@ TO BE REWRITTEN FOR WORD-BASED RECONSTRUCTION
+ /*for(size_t n=0; n<m_voBGDescSamples.size(); ++n) {
+ for(int y=0; y<m_oImgSize.height; ++y) {
+ for(int x=0; x<m_oImgSize.width; ++x) {
+ const size_t nDescIter = m_voBGDescSamples[n].step.p[0]*y + m_voBGDescSamples[n].step.p[1]*x;
+ const size_t nFloatIter = nDescIter*2;
+ float* oAvgBgDescPtr = (float*)(oAvgBGDesc.data+nFloatIter);
+ const ushort* const oBGDescPtr = (ushort*)(m_voBGDescSamples[n].data+nDescIter);
+ for(size_t c=0; c<m_nImgChannels; ++c)
+ oAvgBgDescPtr[c] += ((float)oBGDescPtr[c])/m_voBGDescSamples.size();
+ }
+ }
+ }*/
+ oAvgBGDesc.convertTo(backgroundDescImage, CV_16U);
+}
+
+void BackgroundSubtractorPAWCS::CleanupDictionaries() {
+ if (m_aLocalWordList_1ch) {
+ delete[] m_aLocalWordList_1ch;
+ m_aLocalWordList_1ch = nullptr;
+ m_pLocalWordListIter_1ch = nullptr;
+ }
+ else if (m_aLocalWordList_3ch) {
+ delete[] m_aLocalWordList_3ch;
+ m_aLocalWordList_3ch = nullptr;
+ m_pLocalWordListIter_3ch = nullptr;
+ }
+ if (m_apLocalWordDict) {
+ delete[] m_apLocalWordDict;
+ m_apLocalWordDict = nullptr;
+ }
+ if (m_aGlobalWordList_1ch) {
+ delete[] m_aGlobalWordList_1ch;
+ m_aGlobalWordList_1ch = nullptr;
+ m_pGlobalWordListIter_1ch = nullptr;
+ }
+ else if (m_aGlobalWordList_3ch) {
+ delete[] m_aGlobalWordList_3ch;
+ m_aGlobalWordList_3ch = nullptr;
+ m_pGlobalWordListIter_3ch = nullptr;
+ }
+ if (m_apGlobalWordDict) {
+ delete[] m_apGlobalWordDict;
+ m_apGlobalWordDict = nullptr;
+ }
+ if (m_aPxInfoLUT_PAWCS) {
+ for (size_t nPxIter = 0; nPxIter < m_nTotPxCount; ++nPxIter)
+ delete[] m_aPxInfoLUT_PAWCS[nPxIter].apGlobalDictSortLUT;
+ delete[] m_aPxInfoLUT_PAWCS;
+ m_aPxInfoLUT = nullptr;
+ m_aPxInfoLUT_PAWCS = nullptr;
+ }
+ if (m_aPxIdxLUT) {
+ delete[] m_aPxIdxLUT;
+ m_aPxIdxLUT = nullptr;
+ }
+}
+
+float BackgroundSubtractorPAWCS::GetLocalWordWeight(const LocalWordBase* w, size_t nCurrFrame, size_t nOffset) {
+ return (float)(w->nOccurrences) / ((w->nLastOcc - w->nFirstOcc) + (nCurrFrame - w->nLastOcc) * 2 + nOffset);
+}
+
+float BackgroundSubtractorPAWCS::GetGlobalWordWeight(const GlobalWordBase* w) {
+ return (float)cv::sum(w->oSpatioOccMap).val[0];
+}
diff --git a/package_bgs/LBSP/BackgroundSubtractorPAWCS.h b/package_bgs/LBSP/BackgroundSubtractorPAWCS.h
new file mode 100644
index 0000000..cafa48c
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorPAWCS.h
@@ -0,0 +1,169 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "BackgroundSubtractorLBSP_.h"
+
+//! defines the default value for BackgroundSubtractorLBSP_::m_fRelLBSPThreshold
+#define BGSPAWCS_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD (0.333f)
+//! defines the default value for BackgroundSubtractorPAWCS::m_nDescDistThresholdOffset
+#define BGSPAWCS_DEFAULT_DESC_DIST_THRESHOLD_OFFSET (2)
+//! defines the default value for BackgroundSubtractorPAWCS::m_nMinColorDistThreshold
+#define BGSPAWCS_DEFAULT_MIN_COLOR_DIST_THRESHOLD (20)
+//! defines the default value for BackgroundSubtractorPAWCS::m_nMaxLocalWords and m_nMaxGlobalWords
+#define BGSPAWCS_DEFAULT_MAX_NB_WORDS (50)
+//! defines the default value for BackgroundSubtractorPAWCS::m_nSamplesForMovingAvgs
+#define BGSPAWCS_DEFAULT_N_SAMPLES_FOR_MV_AVGS (100)
+
+/*!
+ Pixel-based Adaptive Word Consensus Segmenter (PAWCS) change detection algorithm.
+
+ Note: both grayscale and RGB/BGR images may be used with this extractor (parameters are adjusted automatically).
+ For optimal grayscale results, use CV_8UC1 frames instead of CV_8UC3.
+
+ For more details on the different parameters or on the algorithm itself, see P.-L. St-Charles et al.,
+ "A Self-Adjusting Approach to Change Detection Based on Background Word Consensus", in WACV 2015.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class BackgroundSubtractorPAWCS : public BackgroundSubtractorLBSP_ {
+public:
+ //! full constructor
+ BackgroundSubtractorPAWCS(float fRelLBSPThreshold = BGSPAWCS_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD,
+ size_t nDescDistThresholdOffset = BGSPAWCS_DEFAULT_DESC_DIST_THRESHOLD_OFFSET,
+ size_t nMinColorDistThreshold = BGSPAWCS_DEFAULT_MIN_COLOR_DIST_THRESHOLD,
+ size_t nMaxNbWords = BGSPAWCS_DEFAULT_MAX_NB_WORDS,
+ size_t nSamplesForMovingAvgs = BGSPAWCS_DEFAULT_N_SAMPLES_FOR_MV_AVGS);
+ //! default destructor
+ virtual ~BackgroundSubtractorPAWCS();
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI);
+ //! refreshes all local (+ global) dictionaries based on the last analyzed frame
+ virtual void refreshModel(size_t nBaseOccCount, float fOccDecrFrac, bool bForceFGUpdate = false);
+ //! primary model update function; the learning param is used to override the internal learning speed (ignored when <= 0)
+ virtual void apply(cv::InputArray image, cv::OutputArray fgmask, double learningRateOverride = 0);
+ //! returns a copy of the latest reconstructed background image
+ virtual void getBackgroundImage(cv::OutputArray backgroundImage) const;
+ //! returns a copy of the latest reconstructed background descriptors image
+ virtual void getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const;
+
+protected:
+ template<size_t nChannels>
+ struct ColorLBSPFeature {
+ uchar anColor[nChannels];
+ ushort anDesc[nChannels];
+ };
+ struct LocalWordBase {
+ size_t nFirstOcc;
+ size_t nLastOcc;
+ size_t nOccurrences;
+ };
+ template<typename T>
+ struct LocalWord : LocalWordBase {
+ T oFeature;
+ };
+ struct GlobalWordBase {
+ float fLatestWeight;
+ cv::Mat oSpatioOccMap;
+ uchar nDescBITS;
+ };
+ template<typename T>
+ struct GlobalWord : GlobalWordBase {
+ T oFeature;
+ };
+ typedef LocalWord<ColorLBSPFeature<1>> LocalWord_1ch;
+ typedef LocalWord<ColorLBSPFeature<3>> LocalWord_3ch;
+ typedef GlobalWord<ColorLBSPFeature<1>> GlobalWord_1ch;
+ typedef GlobalWord<ColorLBSPFeature<3>> GlobalWord_3ch;
+ struct PxInfo_PAWCS : PxInfoBase {
+ size_t nGlobalWordMapLookupIdx;
+ GlobalWordBase** apGlobalDictSortLUT;
+ };
+ //! absolute minimal color distance threshold ('R' or 'radius' in the original ViBe paper, used as the default/initial 'R(x)' value here)
+ const size_t m_nMinColorDistThreshold;
+ //! absolute descriptor distance threshold offset
+ const size_t m_nDescDistThresholdOffset;
+ //! max/curr number of local words used to build background submodels (for a single pixel, similar to 'N' in ViBe/PBAS, may vary based on img/channel size)
+ size_t m_nMaxLocalWords, m_nCurrLocalWords;
+ //! max/curr number of global words used to build the global background model (may vary based on img/channel size)
+ size_t m_nMaxGlobalWords, m_nCurrGlobalWords;
+ //! number of samples to use to compute the learning rate of moving averages
+ const size_t m_nSamplesForMovingAvgs;
+ //! last calculated non-flat region ratio
+ float m_fLastNonFlatRegionRatio;
+ //! current kernel size for median blur post-proc filtering
+ int m_nMedianBlurKernelSize;
+ //! specifies the downsampled frame size used for cam motion analysis & gword lookup maps
+ cv::Size m_oDownSampledFrameSize_MotionAnalysis, m_oDownSampledFrameSize_GlobalWordLookup;
+ //! downsampled version of the ROI used for cam motion analysis
+ cv::Mat m_oDownSampledROI_MotionAnalysis;
+ //! total pixel count for the downsampled ROIs
+ size_t m_nDownSampledROIPxCount;
+ //! current local word weight offset
+ size_t m_nLocalWordWeightOffset;
+
+ //! word lists & dictionaries
+ LocalWordBase** m_apLocalWordDict;
+ LocalWord_1ch* m_aLocalWordList_1ch, *m_pLocalWordListIter_1ch;
+ LocalWord_3ch* m_aLocalWordList_3ch, *m_pLocalWordListIter_3ch;
+ GlobalWordBase** m_apGlobalWordDict;
+ GlobalWord_1ch* m_aGlobalWordList_1ch, *m_pGlobalWordListIter_1ch;
+ GlobalWord_3ch* m_aGlobalWordList_3ch, *m_pGlobalWordListIter_3ch;
+ PxInfo_PAWCS* m_aPxInfoLUT_PAWCS;
+
+ //! a lookup map used to keep track of regions where illumination recently changed
+ cv::Mat m_oIllumUpdtRegionMask;
+ //! per-pixel update rates ('T(x)' in PBAS, which contains pixel-level 'sigmas', as referred to in ViBe)
+ cv::Mat m_oUpdateRateFrame;
+ //! per-pixel distance thresholds (equivalent to 'R(x)' in PBAS, but used as a relative value to determine both intensity and descriptor variation thresholds)
+ cv::Mat m_oDistThresholdFrame;
+ //! per-pixel distance threshold variation modulators ('v(x)', relative value used to modulate 'R(x)' and 'T(x)' variations)
+ cv::Mat m_oDistThresholdVariationFrame;
+ //! per-pixel mean minimal distances from the model ('D_min(x)' in PBAS, used to control variation magnitude and direction of 'T(x)' and 'R(x)')
+ cv::Mat m_oMeanMinDistFrame_LT, m_oMeanMinDistFrame_ST;
+ //! per-pixel mean downsampled distances between consecutive frames (used to analyze camera movement and force global model resets automatically)
+ cv::Mat m_oMeanDownSampledLastDistFrame_LT, m_oMeanDownSampledLastDistFrame_ST;
+ //! per-pixel mean raw segmentation results (used to detect unstable segmentation regions)
+ cv::Mat m_oMeanRawSegmResFrame_LT, m_oMeanRawSegmResFrame_ST;
+ //! per-pixel mean raw segmentation results (used to detect unstable segmentation regions)
+ cv::Mat m_oMeanFinalSegmResFrame_LT, m_oMeanFinalSegmResFrame_ST;
+ //! a lookup map used to keep track of unstable regions (based on segm. noise & local dist. thresholds)
+ cv::Mat m_oUnstableRegionMask;
+ //! per-pixel blink detection map ('Z(x)')
+ cv::Mat m_oBlinksFrame;
+ //! pre-allocated matrix used to downsample the input frame when needed
+ cv::Mat m_oDownSampledFrame_MotionAnalysis;
+ //! the foreground mask generated by the method at [t-1] (without post-proc, used for blinking px detection)
+ cv::Mat m_oLastRawFGMask;
+
+ //! pre-allocated CV_8UC1 matrices used to speed up morph ops
+ cv::Mat m_oFGMask_PreFlood;
+ cv::Mat m_oFGMask_FloodedHoles;
+ cv::Mat m_oLastFGMask_dilated;
+ cv::Mat m_oLastFGMask_dilated_inverted;
+ cv::Mat m_oCurrRawFGBlinkMask;
+ cv::Mat m_oLastRawFGBlinkMask;
+ cv::Mat m_oTempGlobalWordWeightDiffFactor;
+ cv::Mat m_oMorphExStructElement;
+
+ //! internal cleanup function for the dictionary structures
+ void CleanupDictionaries();
+ //! internal weight lookup function for local words
+ static float GetLocalWordWeight(const LocalWordBase* w, size_t nCurrFrame, size_t nOffset);
+ //! internal weight lookup function for global words
+ static float GetGlobalWordWeight(const GlobalWordBase* w);
+};
diff --git a/package_bgs/LBSP/BackgroundSubtractorSuBSENSE.cpp b/package_bgs/LBSP/BackgroundSubtractorSuBSENSE.cpp
new file mode 100644
index 0000000..3dcc1b8
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorSuBSENSE.cpp
@@ -0,0 +1,753 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "BackgroundSubtractorSuBSENSE.h"
+#include "DistanceUtils.h"
+#include "RandUtils.h"
+#include <iostream>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <iomanip>
+
+/*
+ *
+ * Intrinsic parameters for our method are defined here; tuning these for better
+ * performance should not be required in most cases -- although improvements in
+ * very specific scenarios are always possible.
+ *
+ */
+ //! defines the threshold value(s) used to detect long-term ghosting and trigger the fast edge-based absorption heuristic
+#define GHOSTDET_D_MAX (0.010f) // defines 'negligible' change here
+#define GHOSTDET_S_MIN (0.995f) // defines the required minimum local foreground saturation value
+//! parameter used to scale dynamic distance threshold adjustments ('R(x)')
+#define FEEDBACK_R_VAR (0.01f)
+//! parameters used to adjust the variation step size of 'v(x)'
+#define FEEDBACK_V_INCR (1.000f)
+#define FEEDBACK_V_DECR (0.100f)
+//! parameters used to scale dynamic learning rate adjustments ('T(x)')
+#define FEEDBACK_T_DECR (0.2500f)
+#define FEEDBACK_T_INCR (0.5000f)
+#define FEEDBACK_T_LOWER (2.0000f)
+#define FEEDBACK_T_UPPER (256.00f)
+//! parameters used to define 'unstable' regions, based on segm noise/bg dynamics and local dist threshold values
+#define UNSTABLE_REG_RATIO_MIN (0.100f)
+#define UNSTABLE_REG_RDIST_MIN (3.000f)
+//! parameters used to scale the relative LBSP intensity threshold used for internal comparisons
+#define LBSPDESC_NONZERO_RATIO_MIN (0.100f)
+#define LBSPDESC_NONZERO_RATIO_MAX (0.500f)
+//! parameters used to define model reset/learning rate boosts in our frame-level component
+#define FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD (m_nMinColorDistThreshold/2)
+#define FRAMELEVEL_ANALYSIS_DOWNSAMPLE_RATIO (8)
+
+// local define used to display debug information
+#define DISPLAY_SUBSENSE_DEBUG_INFO 0
+// local define used to specify the default frame size (320x240 = QVGA)
+#define DEFAULT_FRAME_SIZE cv::Size(320,240)
+// local define used to specify the color dist threshold offset used for unstable regions
+#define STAB_COLOR_DIST_OFFSET (m_nMinColorDistThreshold/5)
+// local define used to specify the desc dist threshold offset used for unstable regions
+#define UNSTAB_DESC_DIST_OFFSET (m_nDescDistThresholdOffset)
+
+static const size_t s_nColorMaxDataRange_1ch = UCHAR_MAX;
+static const size_t s_nDescMaxDataRange_1ch = LBSP::DESC_SIZE * 8;
+static const size_t s_nColorMaxDataRange_3ch = s_nColorMaxDataRange_1ch * 3;
+static const size_t s_nDescMaxDataRange_3ch = s_nDescMaxDataRange_1ch * 3;
+
+BackgroundSubtractorSuBSENSE::BackgroundSubtractorSuBSENSE(float fRelLBSPThreshold
+ , size_t nDescDistThresholdOffset
+ , size_t nMinColorDistThreshold
+ , size_t nBGSamples
+ , size_t nRequiredBGSamples
+ , size_t nSamplesForMovingAvgs)
+ : BackgroundSubtractorLBSP(fRelLBSPThreshold)
+ , m_nMinColorDistThreshold(nMinColorDistThreshold)
+ , m_nDescDistThresholdOffset(nDescDistThresholdOffset)
+ , m_nBGSamples(nBGSamples)
+ , m_nRequiredBGSamples(nRequiredBGSamples)
+ , m_nSamplesForMovingAvgs(nSamplesForMovingAvgs)
+ , m_fLastNonZeroDescRatio(0.0f)
+ , m_bLearningRateScalingEnabled(true)
+ , m_fCurrLearningRateLowerCap(FEEDBACK_T_LOWER)
+ , m_fCurrLearningRateUpperCap(FEEDBACK_T_UPPER)
+ , m_nMedianBlurKernelSize(m_nDefaultMedianBlurKernelSize)
+ , m_bUse3x3Spread(true) {
+ CV_Assert(m_nBGSamples > 0 && m_nRequiredBGSamples <= m_nBGSamples);
+ CV_Assert(m_nMinColorDistThreshold >= STAB_COLOR_DIST_OFFSET);
+}
+
+BackgroundSubtractorSuBSENSE::~BackgroundSubtractorSuBSENSE() {
+ if (m_aPxIdxLUT)
+ delete[] m_aPxIdxLUT;
+ if (m_aPxInfoLUT)
+ delete[] m_aPxInfoLUT;
+}
+
+void BackgroundSubtractorSuBSENSE::initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) {
+ // == init
+ CV_Assert(!oInitImg.empty() && oInitImg.cols > 0 && oInitImg.rows > 0);
+ CV_Assert(oInitImg.isContinuous());
+ CV_Assert(oInitImg.type() == CV_8UC3 || oInitImg.type() == CV_8UC1);
+ if (oInitImg.type() == CV_8UC3) {
+ std::vector<cv::Mat> voInitImgChannels;
+ cv::split(oInitImg, voInitImgChannels);
+ if (!cv::countNonZero((voInitImgChannels[0] != voInitImgChannels[1]) | (voInitImgChannels[2] != voInitImgChannels[1])))
+ std::cout << std::endl << "\tBackgroundSubtractorSuBSENSE : Warning, grayscale images should always be passed in CV_8UC1 format for optimal performance." << std::endl;
+ }
+ cv::Mat oNewBGROI;
+ if (oROI.empty() && (m_oROI.empty() || oROI.size() != oInitImg.size())) {
+ oNewBGROI.create(oInitImg.size(), CV_8UC1);
+ oNewBGROI = cv::Scalar_<uchar>(UCHAR_MAX);
+ }
+ else if (oROI.empty())
+ oNewBGROI = m_oROI;
+ else {
+ CV_Assert(oROI.size() == oInitImg.size() && oROI.type() == CV_8UC1);
+ CV_Assert(cv::countNonZero((oROI < UCHAR_MAX)&(oROI > 0)) == 0);
+ oNewBGROI = oROI.clone();
+ cv::Mat oTempROI;
+ cv::dilate(oNewBGROI, oTempROI, cv::Mat(), cv::Point(-1, -1), LBSP::PATCH_SIZE / 2);
+ cv::bitwise_or(oNewBGROI, oTempROI / 2, oNewBGROI);
+ }
+ const size_t nOrigROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
+ CV_Assert(nOrigROIPxCount > 0);
+ LBSP::validateROI(oNewBGROI);
+ const size_t nFinalROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
+ CV_Assert(nFinalROIPxCount > 0);
+ m_oROI = oNewBGROI;
+ m_oImgSize = oInitImg.size();
+ m_nImgType = oInitImg.type();
+ m_nImgChannels = oInitImg.channels();
+ m_nTotPxCount = m_oImgSize.area();
+ m_nTotRelevantPxCount = nFinalROIPxCount;
+ m_nFrameIndex = 0;
+ m_nFramesSinceLastReset = 0;
+ m_nModelResetCooldown = 0;
+ m_fLastNonZeroDescRatio = 0.0f;
+ const int nTotImgPixels = m_oImgSize.height*m_oImgSize.width;
+ if (nOrigROIPxCount >= m_nTotPxCount / 2 && (int)m_nTotPxCount >= DEFAULT_FRAME_SIZE.area()) {
+ m_bLearningRateScalingEnabled = true;
+ m_bAutoModelResetEnabled = true;
+ m_bUse3x3Spread = !(nTotImgPixels > DEFAULT_FRAME_SIZE.area() * 2);
+ const int nRawMedianBlurKernelSize = std::min((int)floor((float)nTotImgPixels / DEFAULT_FRAME_SIZE.area() + 0.5f) + m_nDefaultMedianBlurKernelSize, 14);
+ m_nMedianBlurKernelSize = (nRawMedianBlurKernelSize % 2) ? nRawMedianBlurKernelSize : nRawMedianBlurKernelSize - 1;
+ m_fCurrLearningRateLowerCap = FEEDBACK_T_LOWER;
+ m_fCurrLearningRateUpperCap = FEEDBACK_T_UPPER;
+ }
+ else {
+ m_bLearningRateScalingEnabled = false;
+ m_bAutoModelResetEnabled = false;
+ m_bUse3x3Spread = true;
+ m_nMedianBlurKernelSize = m_nDefaultMedianBlurKernelSize;
+ m_fCurrLearningRateLowerCap = FEEDBACK_T_LOWER * 2;
+ m_fCurrLearningRateUpperCap = FEEDBACK_T_UPPER * 2;
+ }
+ m_oUpdateRateFrame.create(m_oImgSize, CV_32FC1);
+ m_oUpdateRateFrame = cv::Scalar(m_fCurrLearningRateLowerCap);
+ m_oDistThresholdFrame.create(m_oImgSize, CV_32FC1);
+ m_oDistThresholdFrame = cv::Scalar(1.0f);
+ m_oVariationModulatorFrame.create(m_oImgSize, CV_32FC1);
+ m_oVariationModulatorFrame = cv::Scalar(10.0f); // should always be >= FEEDBACK_V_DECR
+ m_oMeanLastDistFrame.create(m_oImgSize, CV_32FC1);
+ m_oMeanLastDistFrame = cv::Scalar(0.0f);
+ m_oMeanMinDistFrame_LT.create(m_oImgSize, CV_32FC1);
+ m_oMeanMinDistFrame_LT = cv::Scalar(0.0f);
+ m_oMeanMinDistFrame_ST.create(m_oImgSize, CV_32FC1);
+ m_oMeanMinDistFrame_ST = cv::Scalar(0.0f);
+ m_oDownSampledFrameSize = cv::Size(m_oImgSize.width / FRAMELEVEL_ANALYSIS_DOWNSAMPLE_RATIO, m_oImgSize.height / FRAMELEVEL_ANALYSIS_DOWNSAMPLE_RATIO);
+ m_oMeanDownSampledLastDistFrame_LT.create(m_oDownSampledFrameSize, CV_32FC((int)m_nImgChannels));
+ m_oMeanDownSampledLastDistFrame_LT = cv::Scalar(0.0f);
+ m_oMeanDownSampledLastDistFrame_ST.create(m_oDownSampledFrameSize, CV_32FC((int)m_nImgChannels));
+ m_oMeanDownSampledLastDistFrame_ST = cv::Scalar(0.0f);
+ m_oMeanRawSegmResFrame_LT.create(m_oImgSize, CV_32FC1);
+ m_oMeanRawSegmResFrame_LT = cv::Scalar(0.0f);
+ m_oMeanRawSegmResFrame_ST.create(m_oImgSize, CV_32FC1);
+ m_oMeanRawSegmResFrame_ST = cv::Scalar(0.0f);
+ m_oMeanFinalSegmResFrame_LT.create(m_oImgSize, CV_32FC1);
+ m_oMeanFinalSegmResFrame_LT = cv::Scalar(0.0f);
+ m_oMeanFinalSegmResFrame_ST.create(m_oImgSize, CV_32FC1);
+ m_oMeanFinalSegmResFrame_ST = cv::Scalar(0.0f);
+ m_oUnstableRegionMask.create(m_oImgSize, CV_8UC1);
+ m_oUnstableRegionMask = cv::Scalar_<uchar>(0);
+ m_oBlinksFrame.create(m_oImgSize, CV_8UC1);
+ m_oBlinksFrame = cv::Scalar_<uchar>(0);
+ m_oDownSampledFrame_MotionAnalysis.create(m_oDownSampledFrameSize, CV_8UC((int)m_nImgChannels));
+ m_oDownSampledFrame_MotionAnalysis = cv::Scalar_<uchar>::all(0);
+ m_oLastColorFrame.create(m_oImgSize, CV_8UC((int)m_nImgChannels));
+ m_oLastColorFrame = cv::Scalar_<uchar>::all(0);
+ m_oLastDescFrame.create(m_oImgSize, CV_16UC((int)m_nImgChannels));
+ m_oLastDescFrame = cv::Scalar_<ushort>::all(0);
+ m_oLastRawFGMask.create(m_oImgSize, CV_8UC1);
+ m_oLastRawFGMask = cv::Scalar_<uchar>(0);
+ m_oLastFGMask.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask = cv::Scalar_<uchar>(0);
+ m_oLastFGMask_dilated.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask_dilated = cv::Scalar_<uchar>(0);
+ m_oLastFGMask_dilated_inverted.create(m_oImgSize, CV_8UC1);
+ m_oLastFGMask_dilated_inverted = cv::Scalar_<uchar>(0);
+ m_oFGMask_FloodedHoles.create(m_oImgSize, CV_8UC1);
+ m_oFGMask_FloodedHoles = cv::Scalar_<uchar>(0);
+ m_oFGMask_PreFlood.create(m_oImgSize, CV_8UC1);
+ m_oFGMask_PreFlood = cv::Scalar_<uchar>(0);
+ m_oCurrRawFGBlinkMask.create(m_oImgSize, CV_8UC1);
+ m_oCurrRawFGBlinkMask = cv::Scalar_<uchar>(0);
+ m_oLastRawFGBlinkMask.create(m_oImgSize, CV_8UC1);
+ m_oLastRawFGBlinkMask = cv::Scalar_<uchar>(0);
+ m_voBGColorSamples.resize(m_nBGSamples);
+ m_voBGDescSamples.resize(m_nBGSamples);
+ for (size_t s = 0; s < m_nBGSamples; ++s) {
+ m_voBGColorSamples[s].create(m_oImgSize, CV_8UC((int)m_nImgChannels));
+ m_voBGColorSamples[s] = cv::Scalar_<uchar>::all(0);
+ m_voBGDescSamples[s].create(m_oImgSize, CV_16UC((int)m_nImgChannels));
+ m_voBGDescSamples[s] = cv::Scalar_<ushort>::all(0);
+ }
+ if (m_aPxIdxLUT)
+ delete[] m_aPxIdxLUT;
+ if (m_aPxInfoLUT)
+ delete[] m_aPxInfoLUT;
+ m_aPxIdxLUT = new size_t[m_nTotRelevantPxCount];
+ m_aPxInfoLUT = new PxInfoBase[m_nTotPxCount];
+ if (m_nImgChannels == 1) {
+ CV_Assert(m_oLastColorFrame.step.p[0] == (size_t)m_oImgSize.width && m_oLastColorFrame.step.p[1] == 1);
+ CV_Assert(m_oLastDescFrame.step.p[0] == m_oLastColorFrame.step.p[0] * 2 && m_oLastDescFrame.step.p[1] == m_oLastColorFrame.step.p[1] * 2);
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>((m_nLBSPThresholdOffset + t*m_fRelLBSPThreshold) / 3);
+ for (size_t nPxIter = 0, nModelIter = 0; nPxIter < m_nTotPxCount; ++nPxIter) {
+ if (m_oROI.data[nPxIter]) {
+ m_aPxIdxLUT[nModelIter] = nPxIter;
+ m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter / m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
+ m_oLastColorFrame.data[nPxIter] = oInitImg.data[nPxIter];
+ const size_t nDescIter = nPxIter * 2;
+ LBSP::computeGrayscaleDescriptor(oInitImg, oInitImg.data[nPxIter], m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxIter]], *((ushort*)(m_oLastDescFrame.data + nDescIter)));
+ ++nModelIter;
+ }
+ }
+ }
+ else { //m_nImgChannels==3
+ CV_Assert(m_oLastColorFrame.step.p[0] == (size_t)m_oImgSize.width * 3 && m_oLastColorFrame.step.p[1] == 3);
+ CV_Assert(m_oLastDescFrame.step.p[0] == m_oLastColorFrame.step.p[0] * 2 && m_oLastDescFrame.step.p[1] == m_oLastColorFrame.step.p[1] * 2);
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>(m_nLBSPThresholdOffset + t*m_fRelLBSPThreshold);
+ for (size_t nPxIter = 0, nModelIter = 0; nPxIter < m_nTotPxCount; ++nPxIter) {
+ if (m_oROI.data[nPxIter]) {
+ m_aPxIdxLUT[nModelIter] = nPxIter;
+ m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter / m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
+ m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
+ const size_t nPxRGBIter = nPxIter * 3;
+ const size_t nDescRGBIter = nPxRGBIter * 2;
+ for (size_t c = 0; c < 3; ++c) {
+ m_oLastColorFrame.data[nPxRGBIter + c] = oInitImg.data[nPxRGBIter + c];
+ LBSP::computeSingleRGBDescriptor(oInitImg, oInitImg.data[nPxRGBIter + c], m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, c, m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxRGBIter + c]], ((ushort*)(m_oLastDescFrame.data + nDescRGBIter))[c]);
+ }
+ ++nModelIter;
+ }
+ }
+ }
+ m_bInitialized = true;
+ refreshModel(1.0f);
+}
+
+void BackgroundSubtractorSuBSENSE::refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate) {
+ // == refresh
+ CV_Assert(m_bInitialized);
+ CV_Assert(fSamplesRefreshFrac > 0.0f && fSamplesRefreshFrac <= 1.0f);
+ const size_t nModelsToRefresh = fSamplesRefreshFrac < 1.0f ? (size_t)(fSamplesRefreshFrac*m_nBGSamples) : m_nBGSamples;
+ const size_t nRefreshStartPos = fSamplesRefreshFrac < 1.0f ? rand() % m_nBGSamples : 0;
+ if (m_nImgChannels == 1) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if (bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
+ for (size_t nCurrModelIdx = nRefreshStartPos; nCurrModelIdx < nRefreshStartPos + nModelsToRefresh; ++nCurrModelIdx) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandSamplePosition(nSampleImgCoord_X, nSampleImgCoord_Y, m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
+ const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
+ m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter] = m_oLastColorFrame.data[nSamplePxIdx];
+ *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data + nPxIter * 2)) = *((ushort*)(m_oLastDescFrame.data + nSamplePxIdx * 2));
+ }
+ }
+ }
+ }
+ }
+ else { //m_nImgChannels==3
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ if (bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
+ for (size_t nCurrModelIdx = nRefreshStartPos; nCurrModelIdx < nRefreshStartPos + nModelsToRefresh; ++nCurrModelIdx) {
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ getRandSamplePosition(nSampleImgCoord_X, nSampleImgCoord_Y, m_aPxInfoLUT[nPxIter].nImgCoord_X, m_aPxInfoLUT[nPxIter].nImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ if (bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
+ const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
+ for (size_t c = 0; c < 3; ++c) {
+ m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter * 3 + c] = m_oLastColorFrame.data[nSamplePxIdx * 3 + c];
+ *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data + (nPxIter * 3 + c) * 2)) = *((ushort*)(m_oLastDescFrame.data + (nSamplePxIdx * 3 + c) * 2));
+ }
+ }
+ }
+ }
+ }
+ }
+}
+
+void BackgroundSubtractorSuBSENSE::apply(cv::InputArray _image, cv::OutputArray _fgmask, double learningRateOverride) {
+ // == process
+ CV_Assert(m_bInitialized);
+ cv::Mat oInputImg = _image.getMat();
+ CV_Assert(oInputImg.type() == m_nImgType && oInputImg.size() == m_oImgSize);
+ CV_Assert(oInputImg.isContinuous());
+ _fgmask.create(m_oImgSize, CV_8UC1);
+ cv::Mat oCurrFGMask = _fgmask.getMat();
+ memset(oCurrFGMask.data, 0, oCurrFGMask.cols*oCurrFGMask.rows);
+ size_t nNonZeroDescCount = 0;
+ const float fRollAvgFactor_LT = 1.0f / std::min(++m_nFrameIndex, m_nSamplesForMovingAvgs);
+ const float fRollAvgFactor_ST = 1.0f / std::min(m_nFrameIndex, m_nSamplesForMovingAvgs / 4);
+ if (m_nImgChannels == 1) {
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const size_t nDescIter = nPxIter * 2;
+ const size_t nFloatIter = nPxIter * 4;
+ const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
+ const uchar nCurrColor = oInputImg.data[nPxIter];
+ size_t nMinDescDist = s_nDescMaxDataRange_1ch;
+ size_t nMinSumDist = s_nColorMaxDataRange_1ch;
+ float* pfCurrDistThresholdFactor = (float*)(m_oDistThresholdFrame.data + nFloatIter);
+ float* pfCurrVariationFactor = (float*)(m_oVariationModulatorFrame.data + nFloatIter);
+ float* pfCurrLearningRate = ((float*)(m_oUpdateRateFrame.data + nFloatIter));
+ float* pfCurrMeanLastDist = ((float*)(m_oMeanLastDistFrame.data + nFloatIter));
+ float* pfCurrMeanMinDist_LT = ((float*)(m_oMeanMinDistFrame_LT.data + nFloatIter));
+ float* pfCurrMeanMinDist_ST = ((float*)(m_oMeanMinDistFrame_ST.data + nFloatIter));
+ float* pfCurrMeanRawSegmRes_LT = ((float*)(m_oMeanRawSegmResFrame_LT.data + nFloatIter));
+ float* pfCurrMeanRawSegmRes_ST = ((float*)(m_oMeanRawSegmResFrame_ST.data + nFloatIter));
+ float* pfCurrMeanFinalSegmRes_LT = ((float*)(m_oMeanFinalSegmResFrame_LT.data + nFloatIter));
+ float* pfCurrMeanFinalSegmRes_ST = ((float*)(m_oMeanFinalSegmResFrame_ST.data + nFloatIter));
+ ushort& nLastIntraDesc = *((ushort*)(m_oLastDescFrame.data + nDescIter));
+ uchar& nLastColor = m_oLastColorFrame.data[nPxIter];
+ const size_t nCurrColorDistThreshold = (size_t)(((*pfCurrDistThresholdFactor)*m_nMinColorDistThreshold) - ((!m_oUnstableRegionMask.data[nPxIter])*STAB_COLOR_DIST_OFFSET)) / 2;
+ const size_t nCurrDescDistThreshold = ((size_t)1 << ((size_t)floor(*pfCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (m_oUnstableRegionMask.data[nPxIter] * UNSTAB_DESC_DIST_OFFSET);
+ ushort nCurrInterDesc, nCurrIntraDesc;
+ LBSP::computeGrayscaleDescriptor(oInputImg, nCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[nCurrColor], nCurrIntraDesc);
+ m_oUnstableRegionMask.data[nPxIter] = ((*pfCurrDistThresholdFactor) > UNSTABLE_REG_RDIST_MIN || (*pfCurrMeanRawSegmRes_LT - *pfCurrMeanFinalSegmRes_LT) > UNSTABLE_REG_RATIO_MIN || (*pfCurrMeanRawSegmRes_ST - *pfCurrMeanFinalSegmRes_ST) > UNSTABLE_REG_RATIO_MIN) ? 1 : 0;
+ size_t nGoodSamplesCount = 0, nSampleIdx = 0;
+ while (nGoodSamplesCount < m_nRequiredBGSamples && nSampleIdx < m_nBGSamples) {
+ const uchar& nBGColor = m_voBGColorSamples[nSampleIdx].data[nPxIter];
+ {
+ const size_t nColorDist = L1dist(nCurrColor, nBGColor);
+ if (nColorDist > nCurrColorDistThreshold)
+ goto failedcheck1ch;
+ const ushort& nBGIntraDesc = *((ushort*)(m_voBGDescSamples[nSampleIdx].data + nDescIter));
+ const size_t nIntraDescDist = hdist(nCurrIntraDesc, nBGIntraDesc);
+ LBSP::computeGrayscaleDescriptor(oInputImg, nBGColor, nCurrImgCoord_X, nCurrImgCoord_Y, m_anLBSPThreshold_8bitLUT[nBGColor], nCurrInterDesc);
+ const size_t nInterDescDist = hdist(nCurrInterDesc, nBGIntraDesc);
+ const size_t nDescDist = (nIntraDescDist + nInterDescDist) / 2;
+ if (nDescDist > nCurrDescDistThreshold)
+ goto failedcheck1ch;
+ const size_t nSumDist = std::min((nDescDist / 4)*(s_nColorMaxDataRange_1ch / s_nDescMaxDataRange_1ch) + nColorDist, s_nColorMaxDataRange_1ch);
+ if (nSumDist > nCurrColorDistThreshold)
+ goto failedcheck1ch;
+ if (nMinDescDist > nDescDist)
+ nMinDescDist = nDescDist;
+ if (nMinSumDist > nSumDist)
+ nMinSumDist = nSumDist;
+ nGoodSamplesCount++;
+ }
+ failedcheck1ch:
+ nSampleIdx++;
+ }
+ const float fNormalizedLastDist = ((float)L1dist(nLastColor, nCurrColor) / s_nColorMaxDataRange_1ch + (float)hdist(nLastIntraDesc, nCurrIntraDesc) / s_nDescMaxDataRange_1ch) / 2;
+ *pfCurrMeanLastDist = (*pfCurrMeanLastDist)*(1.0f - fRollAvgFactor_ST) + fNormalizedLastDist*fRollAvgFactor_ST;
+ if (nGoodSamplesCount < m_nRequiredBGSamples) {
+ // == foreground
+ const float fNormalizedMinDist = std::min(1.0f, ((float)nMinSumDist / s_nColorMaxDataRange_1ch + (float)nMinDescDist / s_nDescMaxDataRange_1ch) / 2 + (float)(m_nRequiredBGSamples - nGoodSamplesCount) / m_nRequiredBGSamples);
+ *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f - fRollAvgFactor_LT) + fRollAvgFactor_LT;
+ *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f - fRollAvgFactor_ST) + fRollAvgFactor_ST;
+ oCurrFGMask.data[nPxIter] = UCHAR_MAX;
+ if (m_nModelResetCooldown && (rand() % (size_t)FEEDBACK_T_LOWER) == 0) {
+ const size_t s_rand = rand() % m_nBGSamples;
+ *((ushort*)(m_voBGDescSamples[s_rand].data + nDescIter)) = nCurrIntraDesc;
+ m_voBGColorSamples[s_rand].data[nPxIter] = nCurrColor;
+ }
+ }
+ else {
+ // == background
+ const float fNormalizedMinDist = ((float)nMinSumDist / s_nColorMaxDataRange_1ch + (float)nMinDescDist / s_nDescMaxDataRange_1ch) / 2;
+ *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f - fRollAvgFactor_LT);
+ *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f - fRollAvgFactor_ST);
+ const size_t nLearningRate = learningRateOverride > 0 ? (size_t)ceil(learningRateOverride) : (size_t)ceil(*pfCurrLearningRate);
+ if ((rand() % nLearningRate) == 0) {
+ const size_t s_rand = rand() % m_nBGSamples;
+ *((ushort*)(m_voBGDescSamples[s_rand].data + nDescIter)) = nCurrIntraDesc;
+ m_voBGColorSamples[s_rand].data[nPxIter] = nCurrColor;
+ }
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ const bool bCurrUsing3x3Spread = m_bUse3x3Spread && !m_oUnstableRegionMask.data[nPxIter];
+ if (bCurrUsing3x3Spread)
+ getRandNeighborPosition_3x3(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ else
+ getRandNeighborPosition_5x5(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t n_rand = rand();
+ const size_t idx_rand_uchar = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ const size_t idx_rand_flt32 = idx_rand_uchar * 4;
+ const float fRandMeanLastDist = *((float*)(m_oMeanLastDistFrame.data + idx_rand_flt32));
+ const float fRandMeanRawSegmRes = *((float*)(m_oMeanRawSegmResFrame_ST.data + idx_rand_flt32));
+ if ((n_rand % (bCurrUsing3x3Spread ? nLearningRate : (nLearningRate / 2 + 1))) == 0
+ || (fRandMeanRawSegmRes > GHOSTDET_S_MIN && fRandMeanLastDist < GHOSTDET_D_MAX && (n_rand % ((size_t)m_fCurrLearningRateLowerCap)) == 0)) {
+ const size_t idx_rand_ushrt = idx_rand_uchar * 2;
+ const size_t s_rand = rand() % m_nBGSamples;
+ *((ushort*)(m_voBGDescSamples[s_rand].data + idx_rand_ushrt)) = nCurrIntraDesc;
+ m_voBGColorSamples[s_rand].data[idx_rand_uchar] = nCurrColor;
+ }
+ }
+ if (m_oLastFGMask.data[nPxIter] || (std::min(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST) < UNSTABLE_REG_RATIO_MIN && oCurrFGMask.data[nPxIter])) {
+ if ((*pfCurrLearningRate) < m_fCurrLearningRateUpperCap)
+ *pfCurrLearningRate += FEEDBACK_T_INCR / (std::max(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST)*(*pfCurrVariationFactor));
+ }
+ else if ((*pfCurrLearningRate) > m_fCurrLearningRateLowerCap)
+ *pfCurrLearningRate -= FEEDBACK_T_DECR*(*pfCurrVariationFactor) / std::max(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST);
+ if ((*pfCurrLearningRate) < m_fCurrLearningRateLowerCap)
+ *pfCurrLearningRate = m_fCurrLearningRateLowerCap;
+ else if ((*pfCurrLearningRate) > m_fCurrLearningRateUpperCap)
+ *pfCurrLearningRate = m_fCurrLearningRateUpperCap;
+ if (std::max(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST) > UNSTABLE_REG_RATIO_MIN && m_oBlinksFrame.data[nPxIter])
+ (*pfCurrVariationFactor) += FEEDBACK_V_INCR;
+ else if ((*pfCurrVariationFactor) > FEEDBACK_V_DECR) {
+ (*pfCurrVariationFactor) -= m_oLastFGMask.data[nPxIter] ? FEEDBACK_V_DECR / 4 : m_oUnstableRegionMask.data[nPxIter] ? FEEDBACK_V_DECR / 2 : FEEDBACK_V_DECR;
+ if ((*pfCurrVariationFactor) < FEEDBACK_V_DECR)
+ (*pfCurrVariationFactor) = FEEDBACK_V_DECR;
+ }
+ if ((*pfCurrDistThresholdFactor) < std::pow(1.0f + std::min(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST) * 2, 2))
+ (*pfCurrDistThresholdFactor) += FEEDBACK_R_VAR*(*pfCurrVariationFactor - FEEDBACK_V_DECR);
+ else {
+ (*pfCurrDistThresholdFactor) -= FEEDBACK_R_VAR / (*pfCurrVariationFactor);
+ if ((*pfCurrDistThresholdFactor) < 1.0f)
+ (*pfCurrDistThresholdFactor) = 1.0f;
+ }
+ if (popcount(nCurrIntraDesc) >= 2)
+ ++nNonZeroDescCount;
+ nLastIntraDesc = nCurrIntraDesc;
+ nLastColor = nCurrColor;
+ }
+ }
+ else { //m_nImgChannels==3
+ for (size_t nModelIter = 0; nModelIter < m_nTotRelevantPxCount; ++nModelIter) {
+ const size_t nPxIter = m_aPxIdxLUT[nModelIter];
+ const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
+ const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
+ const size_t nPxIterRGB = nPxIter * 3;
+ const size_t nDescIterRGB = nPxIterRGB * 2;
+ const size_t nFloatIter = nPxIter * 4;
+ const uchar* const anCurrColor = oInputImg.data + nPxIterRGB;
+ size_t nMinTotDescDist = s_nDescMaxDataRange_3ch;
+ size_t nMinTotSumDist = s_nColorMaxDataRange_3ch;
+ float* pfCurrDistThresholdFactor = (float*)(m_oDistThresholdFrame.data + nFloatIter);
+ float* pfCurrVariationFactor = (float*)(m_oVariationModulatorFrame.data + nFloatIter);
+ float* pfCurrLearningRate = ((float*)(m_oUpdateRateFrame.data + nFloatIter));
+ float* pfCurrMeanLastDist = ((float*)(m_oMeanLastDistFrame.data + nFloatIter));
+ float* pfCurrMeanMinDist_LT = ((float*)(m_oMeanMinDistFrame_LT.data + nFloatIter));
+ float* pfCurrMeanMinDist_ST = ((float*)(m_oMeanMinDistFrame_ST.data + nFloatIter));
+ float* pfCurrMeanRawSegmRes_LT = ((float*)(m_oMeanRawSegmResFrame_LT.data + nFloatIter));
+ float* pfCurrMeanRawSegmRes_ST = ((float*)(m_oMeanRawSegmResFrame_ST.data + nFloatIter));
+ float* pfCurrMeanFinalSegmRes_LT = ((float*)(m_oMeanFinalSegmResFrame_LT.data + nFloatIter));
+ float* pfCurrMeanFinalSegmRes_ST = ((float*)(m_oMeanFinalSegmResFrame_ST.data + nFloatIter));
+ ushort* anLastIntraDesc = ((ushort*)(m_oLastDescFrame.data + nDescIterRGB));
+ uchar* anLastColor = m_oLastColorFrame.data + nPxIterRGB;
+ const size_t nCurrColorDistThreshold = (size_t)(((*pfCurrDistThresholdFactor)*m_nMinColorDistThreshold) - ((!m_oUnstableRegionMask.data[nPxIter])*STAB_COLOR_DIST_OFFSET));
+ const size_t nCurrDescDistThreshold = ((size_t)1 << ((size_t)floor(*pfCurrDistThresholdFactor + 0.5f))) + m_nDescDistThresholdOffset + (m_oUnstableRegionMask.data[nPxIter] * UNSTAB_DESC_DIST_OFFSET);
+ const size_t nCurrTotColorDistThreshold = nCurrColorDistThreshold * 3;
+ const size_t nCurrTotDescDistThreshold = nCurrDescDistThreshold * 3;
+ const size_t nCurrSCColorDistThreshold = nCurrTotColorDistThreshold / 2;
+ ushort anCurrInterDesc[3], anCurrIntraDesc[3];
+ const size_t anCurrIntraLBSPThresholds[3] = { m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]] };
+ LBSP::computeRGBDescriptor(oInputImg, anCurrColor, nCurrImgCoord_X, nCurrImgCoord_Y, anCurrIntraLBSPThresholds, anCurrIntraDesc);
+ m_oUnstableRegionMask.data[nPxIter] = ((*pfCurrDistThresholdFactor) > UNSTABLE_REG_RDIST_MIN || (*pfCurrMeanRawSegmRes_LT - *pfCurrMeanFinalSegmRes_LT) > UNSTABLE_REG_RATIO_MIN || (*pfCurrMeanRawSegmRes_ST - *pfCurrMeanFinalSegmRes_ST) > UNSTABLE_REG_RATIO_MIN) ? 1 : 0;
+ size_t nGoodSamplesCount = 0, nSampleIdx = 0;
+ while (nGoodSamplesCount < m_nRequiredBGSamples && nSampleIdx < m_nBGSamples) {
+ const ushort* const anBGIntraDesc = (ushort*)(m_voBGDescSamples[nSampleIdx].data + nDescIterRGB);
+ const uchar* const anBGColor = m_voBGColorSamples[nSampleIdx].data + nPxIterRGB;
+ size_t nTotDescDist = 0;
+ size_t nTotSumDist = 0;
+ for (size_t c = 0; c < 3; ++c) {
+ const size_t nColorDist = L1dist(anCurrColor[c], anBGColor[c]);
+ if (nColorDist > nCurrSCColorDistThreshold)
+ goto failedcheck3ch;
+ const size_t nIntraDescDist = hdist(anCurrIntraDesc[c], anBGIntraDesc[c]);
+ LBSP::computeSingleRGBDescriptor(oInputImg, anBGColor[c], nCurrImgCoord_X, nCurrImgCoord_Y, c, m_anLBSPThreshold_8bitLUT[anBGColor[c]], anCurrInterDesc[c]);
+ const size_t nInterDescDist = hdist(anCurrInterDesc[c], anBGIntraDesc[c]);
+ const size_t nDescDist = (nIntraDescDist + nInterDescDist) / 2;
+ const size_t nSumDist = std::min((nDescDist / 2)*(s_nColorMaxDataRange_1ch / s_nDescMaxDataRange_1ch) + nColorDist, s_nColorMaxDataRange_1ch);
+ if (nSumDist > nCurrSCColorDistThreshold)
+ goto failedcheck3ch;
+ nTotDescDist += nDescDist;
+ nTotSumDist += nSumDist;
+ }
+ if (nTotDescDist > nCurrTotDescDistThreshold || nTotSumDist > nCurrTotColorDistThreshold)
+ goto failedcheck3ch;
+ if (nMinTotDescDist > nTotDescDist)
+ nMinTotDescDist = nTotDescDist;
+ if (nMinTotSumDist > nTotSumDist)
+ nMinTotSumDist = nTotSumDist;
+ nGoodSamplesCount++;
+ failedcheck3ch:
+ nSampleIdx++;
+ }
+ const float fNormalizedLastDist = ((float)L1dist<3>(anLastColor, anCurrColor) / s_nColorMaxDataRange_3ch + (float)hdist<3>(anLastIntraDesc, anCurrIntraDesc) / s_nDescMaxDataRange_3ch) / 2;
+ *pfCurrMeanLastDist = (*pfCurrMeanLastDist)*(1.0f - fRollAvgFactor_ST) + fNormalizedLastDist*fRollAvgFactor_ST;
+ if (nGoodSamplesCount < m_nRequiredBGSamples) {
+ // == foreground
+ const float fNormalizedMinDist = std::min(1.0f, ((float)nMinTotSumDist / s_nColorMaxDataRange_3ch + (float)nMinTotDescDist / s_nDescMaxDataRange_3ch) / 2 + (float)(m_nRequiredBGSamples - nGoodSamplesCount) / m_nRequiredBGSamples);
+ *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f - fRollAvgFactor_LT) + fRollAvgFactor_LT;
+ *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f - fRollAvgFactor_ST) + fRollAvgFactor_ST;
+ oCurrFGMask.data[nPxIter] = UCHAR_MAX;
+ if (m_nModelResetCooldown && (rand() % (size_t)FEEDBACK_T_LOWER) == 0) {
+ const size_t s_rand = rand() % m_nBGSamples;
+ for (size_t c = 0; c < 3; ++c) {
+ *((ushort*)(m_voBGDescSamples[s_rand].data + nDescIterRGB + 2 * c)) = anCurrIntraDesc[c];
+ *(m_voBGColorSamples[s_rand].data + nPxIterRGB + c) = anCurrColor[c];
+ }
+ }
+ }
+ else {
+ // == background
+ const float fNormalizedMinDist = ((float)nMinTotSumDist / s_nColorMaxDataRange_3ch + (float)nMinTotDescDist / s_nDescMaxDataRange_3ch) / 2;
+ *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f - fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
+ *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f - fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
+ *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f - fRollAvgFactor_LT);
+ *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f - fRollAvgFactor_ST);
+ const size_t nLearningRate = learningRateOverride > 0 ? (size_t)ceil(learningRateOverride) : (size_t)ceil(*pfCurrLearningRate);
+ if ((rand() % nLearningRate) == 0) {
+ const size_t s_rand = rand() % m_nBGSamples;
+ for (size_t c = 0; c < 3; ++c) {
+ *((ushort*)(m_voBGDescSamples[s_rand].data + nDescIterRGB + 2 * c)) = anCurrIntraDesc[c];
+ *(m_voBGColorSamples[s_rand].data + nPxIterRGB + c) = anCurrColor[c];
+ }
+ }
+ int nSampleImgCoord_Y, nSampleImgCoord_X;
+ const bool bCurrUsing3x3Spread = m_bUse3x3Spread && !m_oUnstableRegionMask.data[nPxIter];
+ if (bCurrUsing3x3Spread)
+ getRandNeighborPosition_3x3(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ else
+ getRandNeighborPosition_5x5(nSampleImgCoord_X, nSampleImgCoord_Y, nCurrImgCoord_X, nCurrImgCoord_Y, LBSP::PATCH_SIZE / 2, m_oImgSize);
+ const size_t n_rand = rand();
+ const size_t idx_rand_uchar = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
+ const size_t idx_rand_flt32 = idx_rand_uchar * 4;
+ const float fRandMeanLastDist = *((float*)(m_oMeanLastDistFrame.data + idx_rand_flt32));
+ const float fRandMeanRawSegmRes = *((float*)(m_oMeanRawSegmResFrame_ST.data + idx_rand_flt32));
+ if ((n_rand % (bCurrUsing3x3Spread ? nLearningRate : (nLearningRate / 2 + 1))) == 0
+ || (fRandMeanRawSegmRes > GHOSTDET_S_MIN && fRandMeanLastDist < GHOSTDET_D_MAX && (n_rand % ((size_t)m_fCurrLearningRateLowerCap)) == 0)) {
+ const size_t idx_rand_uchar_rgb = idx_rand_uchar * 3;
+ const size_t idx_rand_ushrt_rgb = idx_rand_uchar_rgb * 2;
+ const size_t s_rand = rand() % m_nBGSamples;
+ for (size_t c = 0; c < 3; ++c) {
+ *((ushort*)(m_voBGDescSamples[s_rand].data + idx_rand_ushrt_rgb + 2 * c)) = anCurrIntraDesc[c];
+ *(m_voBGColorSamples[s_rand].data + idx_rand_uchar_rgb + c) = anCurrColor[c];
+ }
+ }
+ }
+ if (m_oLastFGMask.data[nPxIter] || (std::min(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST) < UNSTABLE_REG_RATIO_MIN && oCurrFGMask.data[nPxIter])) {
+ if ((*pfCurrLearningRate) < m_fCurrLearningRateUpperCap)
+ *pfCurrLearningRate += FEEDBACK_T_INCR / (std::max(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST)*(*pfCurrVariationFactor));
+ }
+ else if ((*pfCurrLearningRate) > m_fCurrLearningRateLowerCap)
+ *pfCurrLearningRate -= FEEDBACK_T_DECR*(*pfCurrVariationFactor) / std::max(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST);
+ if ((*pfCurrLearningRate) < m_fCurrLearningRateLowerCap)
+ *pfCurrLearningRate = m_fCurrLearningRateLowerCap;
+ else if ((*pfCurrLearningRate) > m_fCurrLearningRateUpperCap)
+ *pfCurrLearningRate = m_fCurrLearningRateUpperCap;
+ if (std::max(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST) > UNSTABLE_REG_RATIO_MIN && m_oBlinksFrame.data[nPxIter])
+ (*pfCurrVariationFactor) += FEEDBACK_V_INCR;
+ else if ((*pfCurrVariationFactor) > FEEDBACK_V_DECR) {
+ (*pfCurrVariationFactor) -= m_oLastFGMask.data[nPxIter] ? FEEDBACK_V_DECR / 4 : m_oUnstableRegionMask.data[nPxIter] ? FEEDBACK_V_DECR / 2 : FEEDBACK_V_DECR;
+ if ((*pfCurrVariationFactor) < FEEDBACK_V_DECR)
+ (*pfCurrVariationFactor) = FEEDBACK_V_DECR;
+ }
+ if ((*pfCurrDistThresholdFactor) < std::pow(1.0f + std::min(*pfCurrMeanMinDist_LT, *pfCurrMeanMinDist_ST) * 2, 2))
+ (*pfCurrDistThresholdFactor) += FEEDBACK_R_VAR*(*pfCurrVariationFactor - FEEDBACK_V_DECR);
+ else {
+ (*pfCurrDistThresholdFactor) -= FEEDBACK_R_VAR / (*pfCurrVariationFactor);
+ if ((*pfCurrDistThresholdFactor) < 1.0f)
+ (*pfCurrDistThresholdFactor) = 1.0f;
+ }
+ if (popcount<3>(anCurrIntraDesc) >= 4)
+ ++nNonZeroDescCount;
+ for (size_t c = 0; c < 3; ++c) {
+ anLastIntraDesc[c] = anCurrIntraDesc[c];
+ anLastColor[c] = anCurrColor[c];
+ }
+ }
+ }
+#if DISPLAY_SUBSENSE_DEBUG_INFO
+ std::cout << std::endl;
+ cv::Point dbgpt(nDebugCoordX, nDebugCoordY);
+ cv::Mat oMeanMinDistFrameNormalized; m_oMeanMinDistFrame_ST.copyTo(oMeanMinDistFrameNormalized);
+ cv::circle(oMeanMinDistFrameNormalized, dbgpt, 5, cv::Scalar(1.0f));
+ cv::resize(oMeanMinDistFrameNormalized, oMeanMinDistFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("d_min(x)", oMeanMinDistFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " d_min(" << dbgpt << ") = " << m_oMeanMinDistFrame_ST.at<float>(dbgpt) << std::endl;
+ cv::Mat oMeanLastDistFrameNormalized; m_oMeanLastDistFrame.copyTo(oMeanLastDistFrameNormalized);
+ cv::circle(oMeanLastDistFrameNormalized, dbgpt, 5, cv::Scalar(1.0f));
+ cv::resize(oMeanLastDistFrameNormalized, oMeanLastDistFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("d_last(x)", oMeanLastDistFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " d_last(" << dbgpt << ") = " << m_oMeanLastDistFrame.at<float>(dbgpt) << std::endl;
+ cv::Mat oMeanRawSegmResFrameNormalized; m_oMeanRawSegmResFrame_ST.copyTo(oMeanRawSegmResFrameNormalized);
+ cv::circle(oMeanRawSegmResFrameNormalized, dbgpt, 5, cv::Scalar(1.0f));
+ cv::resize(oMeanRawSegmResFrameNormalized, oMeanRawSegmResFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("s_avg(x)", oMeanRawSegmResFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " s_avg(" << dbgpt << ") = " << m_oMeanRawSegmResFrame_ST.at<float>(dbgpt) << std::endl;
+ cv::Mat oMeanFinalSegmResFrameNormalized; m_oMeanFinalSegmResFrame_ST.copyTo(oMeanFinalSegmResFrameNormalized);
+ cv::circle(oMeanFinalSegmResFrameNormalized, dbgpt, 5, cv::Scalar(1.0f));
+ cv::resize(oMeanFinalSegmResFrameNormalized, oMeanFinalSegmResFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("z_avg(x)", oMeanFinalSegmResFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " z_avg(" << dbgpt << ") = " << m_oMeanFinalSegmResFrame_ST.at<float>(dbgpt) << std::endl;
+ cv::Mat oDistThresholdFrameNormalized; m_oDistThresholdFrame.convertTo(oDistThresholdFrameNormalized, CV_32FC1, 0.25f, -0.25f);
+ cv::circle(oDistThresholdFrameNormalized, dbgpt, 5, cv::Scalar(1.0f));
+ cv::resize(oDistThresholdFrameNormalized, oDistThresholdFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("r(x)", oDistThresholdFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " r(" << dbgpt << ") = " << m_oDistThresholdFrame.at<float>(dbgpt) << std::endl;
+ cv::Mat oVariationModulatorFrameNormalized; cv::normalize(m_oVariationModulatorFrame, oVariationModulatorFrameNormalized, 0, 255, cv::NORM_MINMAX, CV_8UC1);
+ cv::circle(oVariationModulatorFrameNormalized, dbgpt, 5, cv::Scalar(255));
+ cv::resize(oVariationModulatorFrameNormalized, oVariationModulatorFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("v(x)", oVariationModulatorFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " v(" << dbgpt << ") = " << m_oVariationModulatorFrame.at<float>(dbgpt) << std::endl;
+ cv::Mat oUpdateRateFrameNormalized; m_oUpdateRateFrame.convertTo(oUpdateRateFrameNormalized, CV_32FC1, 1.0f / FEEDBACK_T_UPPER, -FEEDBACK_T_LOWER / FEEDBACK_T_UPPER);
+ cv::circle(oUpdateRateFrameNormalized, dbgpt, 5, cv::Scalar(1.0f));
+ cv::resize(oUpdateRateFrameNormalized, oUpdateRateFrameNormalized, DEFAULT_FRAME_SIZE);
+ cv::imshow("t(x)", oUpdateRateFrameNormalized);
+ std::cout << std::fixed << std::setprecision(5) << " t(" << dbgpt << ") = " << m_oUpdateRateFrame.at<float>(dbgpt) << std::endl;
+#endif //DISPLAY_SUBSENSE_DEBUG_INFO
+ cv::bitwise_xor(oCurrFGMask, m_oLastRawFGMask, m_oCurrRawFGBlinkMask);
+ cv::bitwise_or(m_oCurrRawFGBlinkMask, m_oLastRawFGBlinkMask, m_oBlinksFrame);
+ m_oCurrRawFGBlinkMask.copyTo(m_oLastRawFGBlinkMask);
+ oCurrFGMask.copyTo(m_oLastRawFGMask);
+ cv::morphologyEx(oCurrFGMask, m_oFGMask_PreFlood, cv::MORPH_CLOSE, cv::Mat());
+ m_oFGMask_PreFlood.copyTo(m_oFGMask_FloodedHoles);
+ cv::floodFill(m_oFGMask_FloodedHoles, cv::Point(0, 0), UCHAR_MAX);
+ cv::bitwise_not(m_oFGMask_FloodedHoles, m_oFGMask_FloodedHoles);
+ cv::erode(m_oFGMask_PreFlood, m_oFGMask_PreFlood, cv::Mat(), cv::Point(-1, -1), 3);
+ cv::bitwise_or(oCurrFGMask, m_oFGMask_FloodedHoles, oCurrFGMask);
+ cv::bitwise_or(oCurrFGMask, m_oFGMask_PreFlood, oCurrFGMask);
+ cv::medianBlur(oCurrFGMask, m_oLastFGMask, m_nMedianBlurKernelSize);
+ cv::dilate(m_oLastFGMask, m_oLastFGMask_dilated, cv::Mat(), cv::Point(-1, -1), 3);
+ cv::bitwise_and(m_oBlinksFrame, m_oLastFGMask_dilated_inverted, m_oBlinksFrame);
+ cv::bitwise_not(m_oLastFGMask_dilated, m_oLastFGMask_dilated_inverted);
+ cv::bitwise_and(m_oBlinksFrame, m_oLastFGMask_dilated_inverted, m_oBlinksFrame);
+ m_oLastFGMask.copyTo(oCurrFGMask);
+ cv::addWeighted(m_oMeanFinalSegmResFrame_LT, (1.0f - fRollAvgFactor_LT), m_oLastFGMask, (1.0 / UCHAR_MAX)*fRollAvgFactor_LT, 0, m_oMeanFinalSegmResFrame_LT, CV_32F);
+ cv::addWeighted(m_oMeanFinalSegmResFrame_ST, (1.0f - fRollAvgFactor_ST), m_oLastFGMask, (1.0 / UCHAR_MAX)*fRollAvgFactor_ST, 0, m_oMeanFinalSegmResFrame_ST, CV_32F);
+ const float fCurrNonZeroDescRatio = (float)nNonZeroDescCount / m_nTotRelevantPxCount;
+ if (fCurrNonZeroDescRatio < LBSPDESC_NONZERO_RATIO_MIN && m_fLastNonZeroDescRatio < LBSPDESC_NONZERO_RATIO_MIN) {
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ if (m_anLBSPThreshold_8bitLUT[t] > cv::saturate_cast<uchar>(m_nLBSPThresholdOffset + ceil(t*m_fRelLBSPThreshold / 4)))
+ --m_anLBSPThreshold_8bitLUT[t];
+ }
+ else if (fCurrNonZeroDescRatio > LBSPDESC_NONZERO_RATIO_MAX && m_fLastNonZeroDescRatio > LBSPDESC_NONZERO_RATIO_MAX) {
+ for (size_t t = 0; t <= UCHAR_MAX; ++t)
+ if (m_anLBSPThreshold_8bitLUT[t] < cv::saturate_cast<uchar>(m_nLBSPThresholdOffset + UCHAR_MAX*m_fRelLBSPThreshold))
+ ++m_anLBSPThreshold_8bitLUT[t];
+ }
+ m_fLastNonZeroDescRatio = fCurrNonZeroDescRatio;
+ if (m_bLearningRateScalingEnabled) {
+ cv::resize(oInputImg, m_oDownSampledFrame_MotionAnalysis, m_oDownSampledFrameSize, 0, 0, cv::INTER_AREA);
+ cv::accumulateWeighted(m_oDownSampledFrame_MotionAnalysis, m_oMeanDownSampledLastDistFrame_LT, fRollAvgFactor_LT);
+ cv::accumulateWeighted(m_oDownSampledFrame_MotionAnalysis, m_oMeanDownSampledLastDistFrame_ST, fRollAvgFactor_ST);
+ size_t nTotColorDiff = 0;
+ for (int i = 0; i < m_oMeanDownSampledLastDistFrame_ST.rows; ++i) {
+ const size_t idx1 = m_oMeanDownSampledLastDistFrame_ST.step.p[0] * i;
+ for (int j = 0; j < m_oMeanDownSampledLastDistFrame_ST.cols; ++j) {
+ const size_t idx2 = idx1 + m_oMeanDownSampledLastDistFrame_ST.step.p[1] * j;
+ nTotColorDiff += (m_nImgChannels == 1) ?
+ (size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data + idx2)) - (*(float*)(m_oMeanDownSampledLastDistFrame_LT.data + idx2))) / 2
+ : //(m_nImgChannels==3)
+ std::max((size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data + idx2)) - (*(float*)(m_oMeanDownSampledLastDistFrame_LT.data + idx2))),
+ std::max((size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data + idx2 + 4)) - (*(float*)(m_oMeanDownSampledLastDistFrame_LT.data + idx2 + 4))),
+ (size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data + idx2 + 8)) - (*(float*)(m_oMeanDownSampledLastDistFrame_LT.data + idx2 + 8)))));
+ }
+ }
+ const float fCurrColorDiffRatio = (float)nTotColorDiff / (m_oMeanDownSampledLastDistFrame_ST.rows*m_oMeanDownSampledLastDistFrame_ST.cols);
+ if (m_bAutoModelResetEnabled) {
+ if (m_nFramesSinceLastReset > 1000)
+ m_bAutoModelResetEnabled = false;
+ else if (fCurrColorDiffRatio >= FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD && m_nModelResetCooldown == 0) {
+ m_nFramesSinceLastReset = 0;
+ refreshModel(0.1f); // reset 10% of the bg model
+ m_nModelResetCooldown = m_nSamplesForMovingAvgs / 4;
+ m_oUpdateRateFrame = cv::Scalar(1.0f);
+ }
+ else
+ ++m_nFramesSinceLastReset;
+ }
+ else if (fCurrColorDiffRatio >= FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD * 2) {
+ m_nFramesSinceLastReset = 0;
+ m_bAutoModelResetEnabled = true;
+ }
+ if (fCurrColorDiffRatio >= FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD / 2) {
+ m_fCurrLearningRateLowerCap = (float)std::max((int)FEEDBACK_T_LOWER >> (int)(fCurrColorDiffRatio / 2), 1);
+ m_fCurrLearningRateUpperCap = (float)std::max((int)FEEDBACK_T_UPPER >> (int)(fCurrColorDiffRatio / 2), 1);
+ }
+ else {
+ m_fCurrLearningRateLowerCap = FEEDBACK_T_LOWER;
+ m_fCurrLearningRateUpperCap = FEEDBACK_T_UPPER;
+ }
+ if (m_nModelResetCooldown > 0)
+ --m_nModelResetCooldown;
+ }
+}
+
+void BackgroundSubtractorSuBSENSE::getBackgroundImage(cv::OutputArray backgroundImage) const {
+ CV_Assert(m_bInitialized);
+ cv::Mat oAvgBGImg = cv::Mat::zeros(m_oImgSize, CV_32FC((int)m_nImgChannels));
+ for (size_t s = 0; s < m_nBGSamples; ++s) {
+ for (int y = 0; y < m_oImgSize.height; ++y) {
+ for (int x = 0; x < m_oImgSize.width; ++x) {
+ const size_t idx_nimg = m_voBGColorSamples[s].step.p[0] * y + m_voBGColorSamples[s].step.p[1] * x;
+ const size_t nFloatIter = idx_nimg * 4;
+ float* oAvgBgImgPtr = (float*)(oAvgBGImg.data + nFloatIter);
+ const uchar* const oBGImgPtr = m_voBGColorSamples[s].data + idx_nimg;
+ for (size_t c = 0; c < m_nImgChannels; ++c)
+ oAvgBgImgPtr[c] += ((float)oBGImgPtr[c]) / m_nBGSamples;
+ }
+ }
+ }
+ oAvgBGImg.convertTo(backgroundImage, CV_8U);
+}
+
+void BackgroundSubtractorSuBSENSE::getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const {
+ CV_Assert(LBSP::DESC_SIZE == 2);
+ CV_Assert(m_bInitialized);
+ cv::Mat oAvgBGDesc = cv::Mat::zeros(m_oImgSize, CV_32FC((int)m_nImgChannels));
+ for (size_t n = 0; n < m_voBGDescSamples.size(); ++n) {
+ for (int y = 0; y < m_oImgSize.height; ++y) {
+ for (int x = 0; x < m_oImgSize.width; ++x) {
+ const size_t idx_ndesc = m_voBGDescSamples[n].step.p[0] * y + m_voBGDescSamples[n].step.p[1] * x;
+ const size_t nFloatIter = idx_ndesc * 2;
+ float* oAvgBgDescPtr = (float*)(oAvgBGDesc.data + nFloatIter);
+ const ushort* const oBGDescPtr = (ushort*)(m_voBGDescSamples[n].data + idx_ndesc);
+ for (size_t c = 0; c < m_nImgChannels; ++c)
+ oAvgBgDescPtr[c] += ((float)oBGDescPtr[c]) / m_voBGDescSamples.size();
+ }
+ }
+ }
+ oAvgBGDesc.convertTo(backgroundDescImage, CV_16U);
+}
diff --git a/package_bgs/LBSP/BackgroundSubtractorSuBSENSE.h b/package_bgs/LBSP/BackgroundSubtractorSuBSENSE.h
new file mode 100644
index 0000000..9950ea4
--- /dev/null
+++ b/package_bgs/LBSP/BackgroundSubtractorSuBSENSE.h
@@ -0,0 +1,129 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "BackgroundSubtractorLBSP.h"
+
+//! defines the default value for BackgroundSubtractorLBSP::m_fRelLBSPThreshold
+#define BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD (0.333f)
+//! defines the default value for BackgroundSubtractorSuBSENSE::m_nDescDistThresholdOffset
+#define BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET (3)
+//! defines the default value for BackgroundSubtractorSuBSENSE::m_nMinColorDistThreshold
+#define BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD (30)
+//! defines the default value for BackgroundSubtractorSuBSENSE::m_nBGSamples
+#define BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES (50)
+//! defines the default value for BackgroundSubtractorSuBSENSE::m_nRequiredBGSamples
+#define BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES (2)
+//! defines the default value for BackgroundSubtractorSuBSENSE::m_nSamplesForMovingAvgs
+#define BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS (100)
+
+/*!
+ Self-Balanced Sensitivity segmenTER (SuBSENSE) change detection algorithm.
+
+ Note: both grayscale and RGB/BGR images may be used with this extractor (parameters are adjusted automatically).
+ For optimal grayscale results, use CV_8UC1 frames instead of CV_8UC3.
+
+ For more details on the different parameters or on the algorithm itself, see P.-L. St-Charles et al.,
+ "Flexible Background Subtraction With Self-Balanced Local Sensitivity", in CVPRW 2014.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class BackgroundSubtractorSuBSENSE : public BackgroundSubtractorLBSP {
+public:
+ //! full constructor
+ BackgroundSubtractorSuBSENSE(float fRelLBSPThreshold = BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD,
+ size_t nDescDistThresholdOffset = BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET,
+ size_t nMinColorDistThreshold = BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD,
+ size_t nBGSamples = BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES,
+ size_t nRequiredBGSamples = BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES,
+ size_t nSamplesForMovingAvgs = BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS);
+ //! default destructor
+ virtual ~BackgroundSubtractorSuBSENSE();
+ //! (re)initiaization method; needs to be called before starting background subtraction
+ virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI);
+ //! refreshes all samples based on the last analyzed frame
+ virtual void refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate = false);
+ //! primary model update function; the learning param is used to override the internal learning thresholds (ignored when <= 0)
+ virtual void apply(cv::InputArray image, cv::OutputArray fgmask, double learningRateOverride = 0);
+ //! returns a copy of the latest reconstructed background image
+ void getBackgroundImage(cv::OutputArray backgroundImage) const;
+ //! returns a copy of the latest reconstructed background descriptors image
+ void getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const;
+
+protected:
+ //! absolute minimal color distance threshold ('R' or 'radius' in the original ViBe paper, used as the default/initial 'R(x)' value here)
+ const size_t m_nMinColorDistThreshold;
+ //! absolute descriptor distance threshold offset
+ const size_t m_nDescDistThresholdOffset;
+ //! number of different samples per pixel/block to be taken from input frames to build the background model (same as 'N' in ViBe/PBAS)
+ const size_t m_nBGSamples;
+ //! number of similar samples needed to consider the current pixel/block as 'background' (same as '#_min' in ViBe/PBAS)
+ const size_t m_nRequiredBGSamples;
+ //! number of samples to use to compute the learning rate of moving averages
+ const size_t m_nSamplesForMovingAvgs;
+ //! last calculated non-zero desc ratio
+ float m_fLastNonZeroDescRatio;
+ //! specifies whether Tmin/Tmax scaling is enabled or not
+ bool m_bLearningRateScalingEnabled;
+ //! current learning rate caps
+ float m_fCurrLearningRateLowerCap, m_fCurrLearningRateUpperCap;
+ //! current kernel size for median blur post-proc filtering
+ int m_nMedianBlurKernelSize;
+ //! specifies the px update spread range
+ bool m_bUse3x3Spread;
+ //! specifies the downsampled frame size used for cam motion analysis
+ cv::Size m_oDownSampledFrameSize;
+
+ //! background model pixel color intensity samples (equivalent to 'B(x)' in PBAS)
+ std::vector<cv::Mat> m_voBGColorSamples;
+ //! background model descriptors samples
+ std::vector<cv::Mat> m_voBGDescSamples;
+
+ //! per-pixel update rates ('T(x)' in PBAS, which contains pixel-level 'sigmas', as referred to in ViBe)
+ cv::Mat m_oUpdateRateFrame;
+ //! per-pixel distance thresholds (equivalent to 'R(x)' in PBAS, but used as a relative value to determine both intensity and descriptor variation thresholds)
+ cv::Mat m_oDistThresholdFrame;
+ //! per-pixel distance variation modulators ('v(x)', relative value used to modulate 'R(x)' and 'T(x)' variations)
+ cv::Mat m_oVariationModulatorFrame;
+ //! per-pixel mean distances between consecutive frames ('D_last(x)', used to detect ghosts and high variation regions in the sequence)
+ cv::Mat m_oMeanLastDistFrame;
+ //! per-pixel mean minimal distances from the model ('D_min(x)' in PBAS, used to control variation magnitude and direction of 'T(x)' and 'R(x)')
+ cv::Mat m_oMeanMinDistFrame_LT, m_oMeanMinDistFrame_ST;
+ //! per-pixel mean downsampled distances between consecutive frames (used to analyze camera movement and control max learning rates globally)
+ cv::Mat m_oMeanDownSampledLastDistFrame_LT, m_oMeanDownSampledLastDistFrame_ST;
+ //! per-pixel mean raw segmentation results (used to detect unstable segmentation regions)
+ cv::Mat m_oMeanRawSegmResFrame_LT, m_oMeanRawSegmResFrame_ST;
+ //! per-pixel mean raw segmentation results (used to detect unstable segmentation regions)
+ cv::Mat m_oMeanFinalSegmResFrame_LT, m_oMeanFinalSegmResFrame_ST;
+ //! a lookup map used to keep track of unstable regions (based on segm. noise & local dist. thresholds)
+ cv::Mat m_oUnstableRegionMask;
+ //! per-pixel blink detection map ('Z(x)')
+ cv::Mat m_oBlinksFrame;
+ //! pre-allocated matrix used to downsample the input frame when needed
+ cv::Mat m_oDownSampledFrame_MotionAnalysis;
+ //! the foreground mask generated by the method at [t-1] (without post-proc, used for blinking px detection)
+ cv::Mat m_oLastRawFGMask;
+
+ //! pre-allocated CV_8UC1 matrices used to speed up morph ops
+ cv::Mat m_oFGMask_PreFlood;
+ cv::Mat m_oFGMask_FloodedHoles;
+ cv::Mat m_oLastFGMask_dilated;
+ cv::Mat m_oLastFGMask_dilated_inverted;
+ cv::Mat m_oCurrRawFGBlinkMask;
+ cv::Mat m_oLastRawFGBlinkMask;
+};
+
diff --git a/package_bgs/LBSP/DistanceUtils.h b/package_bgs/LBSP/DistanceUtils.h
new file mode 100644
index 0000000..9eabca4
--- /dev/null
+++ b/package_bgs/LBSP/DistanceUtils.h
@@ -0,0 +1,332 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <opencv2/core/types_c.h>
+
+//! computes the L1 distance between two integer values
+template<typename T> static inline typename std::enable_if<std::is_integral<T>::value,size_t>::type L1dist(T a, T b) {
+ return (size_t)abs((int)a-b);
+}
+
+//! computes the L1 distance between two float values
+template<typename T> static inline typename std::enable_if<std::is_floating_point<T>::value,float>::type L1dist(T a, T b) {
+ return fabs((float)a-(float)b);
+}
+
+//! computes the L1 distance between two generic arrays
+template<size_t nChannels, typename T> static inline auto L1dist(const T* a, const T* b) -> decltype(L1dist(*a,*b)) {
+ decltype(L1dist(*a,*b)) oResult = 0;
+ for(size_t c=0; c<nChannels; ++c)
+ oResult += L1dist(a[c],b[c]);
+ return oResult;
+}
+
+//! computes the L1 distance between two generic arrays
+template<size_t nChannels, typename T> static inline auto L1dist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) -> decltype(L1dist<nChannels>(a,b)) {
+ decltype(L1dist<nChannels>(a,b)) oResult = 0;
+ size_t nTotElements = nElements*nChannels;
+ if(m) {
+ for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
+ if(m[i])
+ oResult += L1dist<nChannels>(a+n,b+n);
+ }
+ else {
+ for(size_t n=0; n<nTotElements; n+=nChannels)
+ oResult += L1dist<nChannels>(a+n,b+n);
+ }
+ return oResult;
+}
+
+//! computes the L1 distance between two generic arrays
+template<typename T> static inline auto L1dist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) -> decltype(L1dist<3>(a,b,nElements,m)) {
+ CV_Assert(nChannels>0 && nChannels<=4);
+ switch(nChannels) {
+ case 1: return L1dist<1>(a,b,nElements,m);
+ case 2: return L1dist<2>(a,b,nElements,m);
+ case 3: return L1dist<3>(a,b,nElements,m);
+ case 4: return L1dist<4>(a,b,nElements,m);
+ default: return 0;
+ }
+}
+
+//! computes the L1 distance between two opencv vectors
+template<size_t nChannels, typename T> static inline auto L1dist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) -> decltype(L1dist<nChannels,T>((T*)(0),(T*)(0))) {
+ T a_array[nChannels], b_array[nChannels];
+ for(size_t c=0; c<nChannels; ++c) {
+ a_array[c] = a[(int)c];
+ b_array[c] = b[(int)c];
+ }
+ return L1dist<nChannels>(a_array,b_array);
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////////////
+
+//! computes the squared L2 distance between two generic variables
+template<typename T> static inline auto L2sqrdist(T a, T b) -> decltype(L1dist(a,b)) {
+ auto oResult = L1dist(a,b);
+ return oResult*oResult;
+}
+
+//! computes the squared L2 distance between two generic arrays
+template<size_t nChannels, typename T> static inline auto L2sqrdist(const T* a, const T* b) -> decltype(L2sqrdist(*a,*b)) {
+ decltype(L2sqrdist(*a,*b)) oResult = 0;
+ for(size_t c=0; c<nChannels; ++c)
+ oResult += L2sqrdist(a[c],b[c]);
+ return oResult;
+}
+
+//! computes the squared L2 distance between two generic arrays
+template<size_t nChannels, typename T> static inline auto L2sqrdist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) -> decltype(L2sqrdist<nChannels>(a,b)) {
+ decltype(L2sqrdist<nChannels>(a,b)) oResult = 0;
+ size_t nTotElements = nElements*nChannels;
+ if(m) {
+ for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
+ if(m[i])
+ oResult += L2sqrdist<nChannels>(a+n,b+n);
+ }
+ else {
+ for(size_t n=0; n<nTotElements; n+=nChannels)
+ oResult += L2sqrdist<nChannels>(a+n,b+n);
+ }
+ return oResult;
+}
+
+//! computes the squared L2 distance between two generic arrays
+template<typename T> static inline auto L2sqrdist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) -> decltype(L2sqrdist<3>(a,b,nElements,m)) {
+ CV_Assert(nChannels>0 && nChannels<=4);
+ switch(nChannels) {
+ case 1: return L2sqrdist<1>(a,b,nElements,m);
+ case 2: return L2sqrdist<2>(a,b,nElements,m);
+ case 3: return L2sqrdist<3>(a,b,nElements,m);
+ case 4: return L2sqrdist<4>(a,b,nElements,m);
+ default: return 0;
+ }
+}
+
+//! computes the squared L2 distance between two opencv vectors
+template<size_t nChannels, typename T> static inline auto L2sqrdist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) -> decltype(L2sqrdist<nChannels,T>((T*)(0),(T*)(0))) {
+ T a_array[nChannels], b_array[nChannels];
+ for(size_t c=0; c<nChannels; ++c) {
+ a_array[c] = a[(int)c];
+ b_array[c] = b[(int)c];
+ }
+ return L2sqrdist<nChannels>(a_array,b_array);
+}
+
+//! computes the L2 distance between two generic arrays
+template<size_t nChannels, typename T> static inline float L2dist(const T* a, const T* b) {
+ decltype(L2sqrdist(*a,*b)) oResult = 0;
+ for(size_t c=0; c<nChannels; ++c)
+ oResult += L2sqrdist(a[c],b[c]);
+ return sqrt((float)oResult);
+}
+
+//! computes the L2 distance between two generic arrays
+template<size_t nChannels, typename T> static inline float L2dist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) {
+ decltype(L2sqrdist<nChannels>(a,b)) oResult = 0;
+ size_t nTotElements = nElements*nChannels;
+ if(m) {
+ for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
+ if(m[i])
+ oResult += L2sqrdist<nChannels>(a+n,b+n);
+ }
+ else {
+ for(size_t n=0; n<nTotElements; n+=nChannels)
+ oResult += L2sqrdist<nChannels>(a+n,b+n);
+ }
+ return sqrt((float)oResult);
+}
+
+//! computes the squared L2 distance between two generic arrays
+template<typename T> static inline float L2dist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) {
+ CV_Assert(nChannels>0 && nChannels<=4);
+ switch(nChannels) {
+ case 1: return L2dist<1>(a,b,nElements,m);
+ case 2: return L2dist<2>(a,b,nElements,m);
+ case 3: return L2dist<3>(a,b,nElements,m);
+ case 4: return L2dist<4>(a,b,nElements,m);
+ default: return 0;
+ }
+}
+
+//! computes the L2 distance between two opencv vectors
+template<size_t nChannels, typename T> static inline float L2dist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) {
+ T a_array[nChannels], b_array[nChannels];
+ for(size_t c=0; c<nChannels; ++c) {
+ a_array[c] = a[(int)c];
+ b_array[c] = b[(int)c];
+ }
+ return L2dist<nChannels>(a_array,b_array);
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////////////
+
+//! computes the color distortion between two integer arrays
+template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_integral<T>::value,size_t>::type cdist(const T* curr, const T* bg) {
+ static_assert(nChannels>1,"cdist: requires more than one channel");
+ size_t curr_sqr = 0;
+ bool bSkip = true;
+ for(size_t c=0; c<nChannels; ++c) {
+ curr_sqr += curr[c]*curr[c];
+ bSkip = bSkip&(bg[c]<=0);
+ }
+ if(bSkip)
+ return (size_t)sqrt((float)curr_sqr);
+ size_t bg_sqr = 0;
+ size_t mix = 0;
+ for(size_t c=0; c<nChannels; ++c) {
+ bg_sqr += bg[c]*bg[c];
+ mix += curr[c]*bg[c];
+ }
+ return (size_t)sqrt(curr_sqr-((float)(mix*mix)/bg_sqr));
+}
+
+//! computes the color distortion between two float arrays
+template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_floating_point<T>::value,float>::type cdist(const T* curr, const T* bg) {
+ static_assert(nChannels>1,"cdist: requires more than one channel");
+ float curr_sqr = 0;
+ bool bSkip = true;
+ for(size_t c=0; c<nChannels; ++c) {
+ curr_sqr += (float)curr[c]*curr[c];
+ bSkip = bSkip&(bg[c]<=0);
+ }
+ if(bSkip)
+ return sqrt(curr_sqr);
+ float bg_sqr = 0;
+ float mix = 0;
+ for(size_t c=0; c<nChannels; ++c) {
+ bg_sqr += (float)bg[c]*bg[c];
+ mix += (float)curr[c]*bg[c];
+ }
+ return sqrt(curr_sqr-((mix*mix)/bg_sqr));
+}
+
+//! computes the color distortion between two generic arrays
+template<size_t nChannels, typename T> static inline auto cdist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) -> decltype(cdist<nChannels>(a,b)) {
+ decltype(cdist<nChannels>(a,b)) oResult = 0;
+ size_t nTotElements = nElements*nChannels;
+ if(m) {
+ for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
+ if(m[i])
+ oResult += cdist<nChannels>(a+n,b+n);
+ }
+ else {
+ for(size_t n=0; n<nTotElements; n+=nChannels)
+ oResult += cdist<nChannels>(a+n,b+n);
+ }
+ return oResult;
+}
+
+//! computes the color distortion between two generic arrays
+template<typename T> static inline auto cdist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) -> decltype(cdist<3>(a,b,nElements,m)) {
+ CV_Assert(nChannels>1 && nChannels<=4);
+ switch(nChannels) {
+ case 2: return cdist<2>(a,b,nElements,m);
+ case 3: return cdist<3>(a,b,nElements,m);
+ case 4: return cdist<4>(a,b,nElements,m);
+ default: return 0;
+ }
+}
+
+//! computes the color distortion between two opencv vectors
+template<size_t nChannels, typename T> static inline auto cdist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) -> decltype(cdist<nChannels,T>((T*)(0),(T*)(0))) {
+ T a_array[nChannels], b_array[nChannels];
+ for(size_t c=0; c<nChannels; ++c) {
+ a_array[c] = a[(int)c];
+ b_array[c] = b[(int)c];
+ }
+ return cdist<nChannels>(a_array,b_array);
+}
+
+//! computes a color distortion-distance mix using two generic distances
+template<typename T> static inline T cmixdist(T oL1Distance, T oCDistortion) {
+ return (oL1Distance/2+oCDistortion*4);
+}
+
+//! computes a color distoirtion-distance mix using two generic arrays
+template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_integral<T>::value,size_t>::type cmixdist(const T* curr, const T* bg) {
+ return cmixdist(L1dist<nChannels>(curr,bg),cdist<nChannels>(curr,bg));
+}
+
+template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_floating_point<T>::value,float>::type cmixdist(const T* curr, const T* bg) {
+ return cmixdist(L1dist<nChannels>(curr,bg),cdist<nChannels>(curr,bg));
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////////////
+
+//! popcount LUT for 8-bit vectors
+static const uchar popcount_LUT8[256] = {
+ 0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
+ 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+ 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+ 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+ 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+ 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+ 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+ 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+ 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+ 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+ 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+ 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+ 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+ 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+ 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+ 4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8,
+};
+
+//! computes the population count of an N-byte vector using an 8-bit popcount LUT
+template<typename T> static inline size_t popcount(T x) {
+ size_t nBytes = sizeof(T);
+ size_t nResult = 0;
+ for(size_t l=0; l<nBytes; ++l)
+ nResult += popcount_LUT8[(uchar)(x>>l*8)];
+ return nResult;
+}
+
+//! computes the hamming distance between two N-byte vectors using an 8-bit popcount LUT
+template<typename T> static inline size_t hdist(T a, T b) {
+ return popcount(a^b);
+}
+
+//! computes the gradient magnitude distance between two N-byte vectors using an 8-bit popcount LUT
+template<typename T> static inline size_t gdist(T a, T b) {
+ return L1dist(popcount(a),popcount(b));
+}
+
+//! computes the population count of a (nChannels*N)-byte vector using an 8-bit popcount LUT
+template<size_t nChannels, typename T> static inline size_t popcount(const T* x) {
+ size_t nBytes = sizeof(T);
+ size_t nResult = 0;
+ for(size_t c=0; c<nChannels; ++c)
+ for(size_t l=0; l<nBytes; ++l)
+ nResult += popcount_LUT8[(uchar)(*(x+c)>>l*8)];
+ return nResult;
+}
+
+//! computes the hamming distance between two (nChannels*N)-byte vectors using an 8-bit popcount LUT
+template<size_t nChannels, typename T> static inline size_t hdist(const T* a, const T* b) {
+ T xor_array[nChannels];
+ for(size_t c=0; c<nChannels; ++c)
+ xor_array[c] = a[c]^b[c];
+ return popcount<nChannels>(xor_array);
+}
+
+//! computes the gradient magnitude distance between two (nChannels*N)-byte vectors using an 8-bit popcount LUT
+template<size_t nChannels, typename T> static inline size_t gdist(const T* a, const T* b) {
+ return L1dist(popcount<nChannels>(a),popcount<nChannels>(b));
+}
diff --git a/package_bgs/LBSP/LBSP.cpp b/package_bgs/LBSP/LBSP.cpp
new file mode 100644
index 0000000..4ec17b9
--- /dev/null
+++ b/package_bgs/LBSP/LBSP.cpp
@@ -0,0 +1,334 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "LBSP.h"
+
+LBSP::LBSP(size_t nThreshold)
+ : m_bOnlyUsingAbsThreshold(true)
+ , m_fRelThreshold(0) // unused
+ , m_nThreshold(nThreshold)
+ , m_oRefImage() {}
+
+LBSP::LBSP(float fRelThreshold, size_t nThresholdOffset)
+ : m_bOnlyUsingAbsThreshold(false)
+ , m_fRelThreshold(fRelThreshold)
+ , m_nThreshold(nThresholdOffset)
+ , m_oRefImage() {
+ CV_Assert(m_fRelThreshold >= 0);
+}
+
+LBSP::~LBSP() {}
+
+void LBSP::read(const cv::FileNode& /*fn*/) {
+ // ... = fn["..."];
+}
+
+void LBSP::write(cv::FileStorage& /*fs*/) const {
+ //fs << "..." << ...;
+}
+
+void LBSP::setReference(const cv::Mat& img) {
+ CV_DbgAssert(img.empty() || img.type() == CV_8UC1 || img.type() == CV_8UC3);
+ m_oRefImage = img;
+}
+
+int LBSP::descriptorSize() const {
+ return DESC_SIZE;
+}
+
+int LBSP::descriptorType() const {
+ return CV_16U;
+}
+
+bool LBSP::isUsingRelThreshold() const {
+ return !m_bOnlyUsingAbsThreshold;
+}
+
+float LBSP::getRelThreshold() const {
+ return m_fRelThreshold;
+}
+
+size_t LBSP::getAbsThreshold() const {
+ return m_nThreshold;
+}
+
+static inline void lbsp_computeImpl(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ size_t _t) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create((int)nKeyPoints, 1, CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>((int)k);
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create((int)nKeyPoints, 1, CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * k));
+#include "LBSP_16bits_dbcross_3ch1t.i"
+ }
+ }
+}
+
+static inline void lbsp_computeImpl(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ float fThreshold,
+ size_t nThresholdOffset) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(fThreshold >= 0);
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create((int)nKeyPoints, 1, CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>((int)k);
+ const size_t _t = (size_t)(_ref*fThreshold) + nThresholdOffset;
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create((int)nKeyPoints, 1, CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * k));
+ const size_t _t[3] = { (size_t)(_ref[0] * fThreshold) + nThresholdOffset,(size_t)(_ref[1] * fThreshold) + nThresholdOffset,(size_t)(_ref[2] * fThreshold) + nThresholdOffset };
+#include "LBSP_16bits_dbcross_3ch3t.i"
+ }
+ }
+}
+
+static inline void lbsp_computeImpl2(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ size_t _t) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create(oInputImg.size(), CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>(_y, _x);
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create(oInputImg.size(), CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * _y + oDesc.step.p[1] * _x));
+#include "LBSP_16bits_dbcross_3ch1t.i"
+ }
+ }
+}
+
+static inline void lbsp_computeImpl2(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ float fThreshold,
+ size_t nThresholdOffset) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(fThreshold >= 0);
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create(oInputImg.size(), CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>(_y, _x);
+ const size_t _t = (size_t)(_ref*fThreshold) + nThresholdOffset;
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create(oInputImg.size(), CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * _y + oDesc.step.p[1] * _x));
+ const size_t _t[3] = { (size_t)(_ref[0] * fThreshold) + nThresholdOffset,(size_t)(_ref[1] * fThreshold) + nThresholdOffset,(size_t)(_ref[2] * fThreshold) + nThresholdOffset };
+#include "LBSP_16bits_dbcross_3ch3t.i"
+ }
+ }
+}
+
+void LBSP::compute2(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const {
+ CV_Assert(!oImage.empty());
+ cv::KeyPointsFilter::runByImageBorder(voKeypoints, oImage.size(), PATCH_SIZE / 2);
+ cv::KeyPointsFilter::runByKeypointSize(voKeypoints, std::numeric_limits<float>::epsilon());
+ if (voKeypoints.empty()) {
+ oDescriptors.release();
+ return;
+ }
+ if (m_bOnlyUsingAbsThreshold)
+ lbsp_computeImpl2(oImage, m_oRefImage, voKeypoints, oDescriptors, m_nThreshold);
+ else
+ lbsp_computeImpl2(oImage, m_oRefImage, voKeypoints, oDescriptors, m_fRelThreshold, m_nThreshold);
+}
+
+void LBSP::compute2(const std::vector<cv::Mat>& voImageCollection, std::vector<std::vector<cv::KeyPoint> >& vvoPointCollection, std::vector<cv::Mat>& voDescCollection) const {
+ CV_Assert(voImageCollection.size() == vvoPointCollection.size());
+ voDescCollection.resize(voImageCollection.size());
+ for (size_t i = 0; i < voImageCollection.size(); i++)
+ compute2(voImageCollection[i], vvoPointCollection[i], voDescCollection[i]);
+}
+
+void LBSP::computeImpl(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const {
+ CV_Assert(!oImage.empty());
+ cv::KeyPointsFilter::runByImageBorder(voKeypoints, oImage.size(), PATCH_SIZE / 2);
+ cv::KeyPointsFilter::runByKeypointSize(voKeypoints, std::numeric_limits<float>::epsilon());
+ if (voKeypoints.empty()) {
+ oDescriptors.release();
+ return;
+ }
+ if (m_bOnlyUsingAbsThreshold)
+ lbsp_computeImpl(oImage, m_oRefImage, voKeypoints, oDescriptors, m_nThreshold);
+ else
+ lbsp_computeImpl(oImage, m_oRefImage, voKeypoints, oDescriptors, m_fRelThreshold, m_nThreshold);
+}
+
+void LBSP::reshapeDesc(cv::Size oSize, const std::vector<cv::KeyPoint>& voKeypoints, const cv::Mat& oDescriptors, cv::Mat& oOutput) {
+ CV_DbgAssert(!voKeypoints.empty());
+ CV_DbgAssert(!oDescriptors.empty() && oDescriptors.cols == 1);
+ CV_DbgAssert(oSize.width > 0 && oSize.height > 0);
+ CV_DbgAssert(DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(oDescriptors.type() == CV_16UC1 || oDescriptors.type() == CV_16UC3);
+ const size_t nChannels = (size_t)oDescriptors.channels();
+ const size_t nKeyPoints = voKeypoints.size();
+ if (nChannels == 1) {
+ oOutput.create(oSize, CV_16UC1);
+ oOutput = cv::Scalar_<ushort>(0);
+ for (size_t k = 0; k < nKeyPoints; ++k)
+ oOutput.at<ushort>(voKeypoints[k].pt) = oDescriptors.at<ushort>((int)k);
+ }
+ else { //nChannels==3
+ oOutput.create(oSize, CV_16UC3);
+ oOutput = cv::Scalar_<ushort>(0, 0, 0);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ ushort* output_ptr = (ushort*)(oOutput.data + oOutput.step.p[0] * (int)voKeypoints[k].pt.y);
+ const ushort* const desc_ptr = (ushort*)(oDescriptors.data + oDescriptors.step.p[0] * k);
+ const size_t idx = 3 * (int)voKeypoints[k].pt.x;
+ for (size_t n = 0; n < 3; ++n)
+ output_ptr[idx + n] = desc_ptr[n];
+ }
+ }
+}
+
+void LBSP::calcDescImgDiff(const cv::Mat& oDesc1, const cv::Mat& oDesc2, cv::Mat& oOutput, bool bForceMergeChannels) {
+ CV_DbgAssert(oDesc1.size() == oDesc2.size() && oDesc1.type() == oDesc2.type());
+ CV_DbgAssert(DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(oDesc1.type() == CV_16UC1 || oDesc1.type() == CV_16UC3);
+ CV_DbgAssert(CV_MAT_DEPTH(oDesc1.type()) == CV_16U);
+ CV_DbgAssert(DESC_SIZE * 8 <= UCHAR_MAX);
+ CV_DbgAssert(oDesc1.step.p[0] == oDesc2.step.p[0] && oDesc1.step.p[1] == oDesc2.step.p[1]);
+ const float fScaleFactor = (float)UCHAR_MAX / (DESC_SIZE * 8);
+ const size_t nChannels = CV_MAT_CN(oDesc1.type());
+ const size_t _step_row = oDesc1.step.p[0];
+ if (nChannels == 1) {
+ oOutput.create(oDesc1.size(), CV_8UC1);
+ oOutput = cv::Scalar(0);
+ for (int i = 0; i < oDesc1.rows; ++i) {
+ const size_t idx = _step_row*i;
+ const ushort* const desc1_ptr = (ushort*)(oDesc1.data + idx);
+ const ushort* const desc2_ptr = (ushort*)(oDesc2.data + idx);
+ for (int j = 0; j < oDesc1.cols; ++j)
+ oOutput.at<uchar>(i, j) = (uchar)(fScaleFactor*hdist(desc1_ptr[j], desc2_ptr[j]));
+ }
+ }
+ else { //nChannels==3
+ if (bForceMergeChannels)
+ oOutput.create(oDesc1.size(), CV_8UC1);
+ else
+ oOutput.create(oDesc1.size(), CV_8UC3);
+ oOutput = cv::Scalar::all(0);
+ for (int i = 0; i < oDesc1.rows; ++i) {
+ const size_t idx = _step_row*i;
+ const ushort* const desc1_ptr = (ushort*)(oDesc1.data + idx);
+ const ushort* const desc2_ptr = (ushort*)(oDesc2.data + idx);
+ uchar* output_ptr = oOutput.data + oOutput.step.p[0] * i;
+ for (int j = 0; j < oDesc1.cols; ++j) {
+ for (size_t n = 0; n < 3; ++n) {
+ const size_t idx2 = 3 * j + n;
+ if (bForceMergeChannels)
+ output_ptr[j] += (uchar)((fScaleFactor*hdist(desc1_ptr[idx2], desc2_ptr[idx2])) / 3);
+ else
+ output_ptr[idx2] = (uchar)(fScaleFactor*hdist(desc1_ptr[idx2], desc2_ptr[idx2]));
+ }
+ }
+ }
+ }
+}
+
+void LBSP::validateKeyPoints(std::vector<cv::KeyPoint>& voKeypoints, cv::Size oImgSize) {
+ cv::KeyPointsFilter::runByImageBorder(voKeypoints, oImgSize, PATCH_SIZE / 2);
+}
+
+void LBSP::validateROI(cv::Mat& oROI) {
+ CV_Assert(!oROI.empty() && oROI.type() == CV_8UC1);
+ cv::Mat oROI_new(oROI.size(), CV_8UC1, cv::Scalar_<uchar>(0));
+ const size_t nBorderSize = PATCH_SIZE / 2;
+ const cv::Rect nROI_inner(nBorderSize, nBorderSize, oROI.cols - nBorderSize * 2, oROI.rows - nBorderSize * 2);
+ cv::Mat(oROI, nROI_inner).copyTo(cv::Mat(oROI_new, nROI_inner));
+ oROI = oROI_new;
+}
diff --git a/package_bgs/LBSP/LBSP.h b/package_bgs/LBSP/LBSP.h
new file mode 100644
index 0000000..c908eaa
--- /dev/null
+++ b/package_bgs/LBSP/LBSP.h
@@ -0,0 +1,134 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/features2d/features2d.hpp>
+#include "DistanceUtils.h"
+
+/*!
+ Local Binary Similarity Pattern (LBSP) feature extractor
+
+ Note 1: both grayscale and RGB/BGR images may be used with this extractor.
+ Note 2: using LBSP::compute2(...) is logically equivalent to using LBSP::compute(...) followed by LBSP::reshapeDesc(...).
+
+ For more details on the different parameters, see G.-A. Bilodeau et al, "Change Detection in Feature Space Using Local
+ Binary Similarity Patterns", in CRV 2013.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class LBSP : public cv::DescriptorExtractor {
+public:
+ //! constructor 1, threshold = absolute intensity 'similarity' threshold used when computing comparisons
+ LBSP(size_t nThreshold);
+ //! constructor 2, threshold = relative intensity 'similarity' threshold used when computing comparisons
+ LBSP(float fRelThreshold, size_t nThresholdOffset = 0);
+ //! default destructor
+ virtual ~LBSP();
+ //! loads extractor params from the specified file node @@@@ not impl
+ virtual void read(const cv::FileNode&);
+ //! writes extractor params to the specified file storage @@@@ not impl
+ virtual void write(cv::FileStorage&) const;
+ //! sets the 'reference' image to be used for inter-frame comparisons (note: if no image is set or if the image is empty, the algorithm will default back to intra-frame comparisons)
+ virtual void setReference(const cv::Mat&);
+ //! returns the current descriptor size, in bytes
+ virtual int descriptorSize() const;
+ //! returns the current descriptor data type
+ virtual int descriptorType() const;
+ //! returns whether this extractor is using a relative threshold or not
+ virtual bool isUsingRelThreshold() const;
+ //! returns the current relative threshold used for comparisons (-1 = invalid/not used)
+ virtual float getRelThreshold() const;
+ //! returns the current absolute threshold used for comparisons (-1 = invalid/not used)
+ virtual size_t getAbsThreshold() const;
+
+ //! similar to DescriptorExtractor::compute(const cv::Mat& image, ...), but in this case, the descriptors matrix has the same shape as the input matrix (possibly slower, but the result can be displayed)
+ void compute2(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const;
+ //! batch version of LBSP::compute2(const cv::Mat& image, ...), also similar to DescriptorExtractor::compute(const std::vector<cv::Mat>& imageCollection, ...)
+ void compute2(const std::vector<cv::Mat>& voImageCollection, std::vector<std::vector<cv::KeyPoint> >& vvoPointCollection, std::vector<cv::Mat>& voDescCollection) const;
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (1-channel version)
+ inline static void computeGrayscaleDescriptor(const cv::Mat& oInputImg, const uchar _ref, const int _x, const int _y, const size_t _t, ushort& _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC1);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP::PATCH_SIZE / 2 && _y >= (int)LBSP::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (3-channels version)
+ inline static void computeRGBDescriptor(const cv::Mat& oInputImg, const uchar* const _ref, const int _x, const int _y, const size_t* const _t, ushort* _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP::PATCH_SIZE / 2 && _y >= (int)LBSP::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_3ch3t.i"
+ }
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (3-channels version)
+ inline static void computeRGBDescriptor(const cv::Mat& oInputImg, const uchar* const _ref, const int _x, const int _y, const size_t _t, ushort* _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP::PATCH_SIZE / 2 && _y >= (int)LBSP::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_3ch1t.i"
+ }
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (1-channel-RGB version)
+ inline static void computeSingleRGBDescriptor(const cv::Mat& oInputImg, const uchar _ref, const int _x, const int _y, const size_t _c, const size_t _t, ushort& _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC3 && _c < 3);
+ CV_DbgAssert(LBSP::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP::PATCH_SIZE / 2 && _y >= (int)LBSP::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_s3ch.i"
+ }
+
+ //! utility function, used to reshape a descriptors matrix to its input image size via their keypoint locations
+ static void reshapeDesc(cv::Size oSize, const std::vector<cv::KeyPoint>& voKeypoints, const cv::Mat& oDescriptors, cv::Mat& oOutput);
+ //! utility function, used to illustrate the difference between two descriptor images
+ static void calcDescImgDiff(const cv::Mat& oDesc1, const cv::Mat& oDesc2, cv::Mat& oOutput, bool bForceMergeChannels = false);
+ //! utility function, used to filter out bad keypoints that would trigger out of bounds error because they're too close to the image border
+ static void validateKeyPoints(std::vector<cv::KeyPoint>& voKeypoints, cv::Size oImgSize);
+ //! utility function, used to filter out bad pixels in a ROI that would trigger out of bounds error because they're too close to the image border
+ static void validateROI(cv::Mat& oROI);
+ //! utility, specifies the pixel size of the pattern used (width and height)
+ static const size_t PATCH_SIZE = 5;
+ //! utility, specifies the number of bytes per descriptor (should be the same as calling 'descriptorSize()')
+ static const size_t DESC_SIZE = 2;
+
+protected:
+ //! classic 'compute' implementation, based on the regular DescriptorExtractor::computeImpl arguments & expected output
+ virtual void computeImpl(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const;
+
+ const bool m_bOnlyUsingAbsThreshold;
+ const float m_fRelThreshold;
+ const size_t m_nThreshold;
+ cv::Mat m_oRefImage;
+};
diff --git a/package_bgs/LBSP/LBSP_.cpp b/package_bgs/LBSP/LBSP_.cpp
new file mode 100644
index 0000000..ff5c8e8
--- /dev/null
+++ b/package_bgs/LBSP/LBSP_.cpp
@@ -0,0 +1,334 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "LBSP_.h"
+
+LBSP_::LBSP_(size_t nThreshold)
+ : m_bOnlyUsingAbsThreshold(true)
+ , m_fRelThreshold(0) // unused
+ , m_nThreshold(nThreshold)
+ , m_oRefImage() {}
+
+LBSP_::LBSP_(float fRelThreshold, size_t nThresholdOffset)
+ : m_bOnlyUsingAbsThreshold(false)
+ , m_fRelThreshold(fRelThreshold)
+ , m_nThreshold(nThresholdOffset)
+ , m_oRefImage() {
+ CV_Assert(m_fRelThreshold >= 0);
+}
+
+LBSP_::~LBSP_() {}
+
+void LBSP_::read(const cv::FileNode& /*fn*/) {
+ // ... = fn["..."];
+}
+
+void LBSP_::write(cv::FileStorage& /*fs*/) const {
+ //fs << "..." << ...;
+}
+
+void LBSP_::setReference(const cv::Mat& img) {
+ CV_DbgAssert(img.empty() || img.type() == CV_8UC1 || img.type() == CV_8UC3);
+ m_oRefImage = img;
+}
+
+int LBSP_::descriptorSize() const {
+ return DESC_SIZE;
+}
+
+int LBSP_::descriptorType() const {
+ return CV_16U;
+}
+
+bool LBSP_::isUsingRelThreshold() const {
+ return !m_bOnlyUsingAbsThreshold;
+}
+
+float LBSP_::getRelThreshold() const {
+ return m_fRelThreshold;
+}
+
+size_t LBSP_::getAbsThreshold() const {
+ return m_nThreshold;
+}
+
+static inline void LBSP__computeImpl(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ size_t _t) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create((int)nKeyPoints, 1, CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>((int)k);
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create((int)nKeyPoints, 1, CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * k));
+#include "LBSP_16bits_dbcross_3ch1t.i"
+ }
+ }
+}
+
+static inline void LBSP__computeImpl(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ float fThreshold,
+ size_t nThresholdOffset) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(fThreshold >= 0);
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create((int)nKeyPoints, 1, CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>((int)k);
+ const size_t _t = (size_t)(_ref*fThreshold) + nThresholdOffset;
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create((int)nKeyPoints, 1, CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * k));
+ const size_t _t[3] = { (size_t)(_ref[0] * fThreshold) + nThresholdOffset,(size_t)(_ref[1] * fThreshold) + nThresholdOffset,(size_t)(_ref[2] * fThreshold) + nThresholdOffset };
+#include "LBSP_16bits_dbcross_3ch3t.i"
+ }
+ }
+}
+
+static inline void LBSP__computeImpl2(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ size_t _t) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create(oInputImg.size(), CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>(_y, _x);
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create(oInputImg.size(), CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * _y + oDesc.step.p[1] * _x));
+#include "LBSP_16bits_dbcross_3ch1t.i"
+ }
+ }
+}
+
+static inline void LBSP__computeImpl2(const cv::Mat& oInputImg,
+ const cv::Mat& oRefImg,
+ const std::vector<cv::KeyPoint>& voKeyPoints,
+ cv::Mat& oDesc,
+ float fThreshold,
+ size_t nThresholdOffset) {
+ CV_DbgAssert(oRefImg.empty() || (oRefImg.size == oInputImg.size && oRefImg.type() == oInputImg.type()));
+ CV_DbgAssert(oInputImg.type() == CV_8UC1 || oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(fThreshold >= 0);
+ const size_t nChannels = (size_t)oInputImg.channels();
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* _data = oInputImg.data;
+ const uchar* _refdata = oRefImg.empty() ? oInputImg.data : oRefImg.data;
+ const size_t nKeyPoints = voKeyPoints.size();
+ if (nChannels == 1) {
+ oDesc.create(oInputImg.size(), CV_16UC1);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar _ref = _refdata[_step_row*(_y)+_x];
+ ushort& _res = oDesc.at<ushort>(_y, _x);
+ const size_t _t = (size_t)(_ref*fThreshold) + nThresholdOffset;
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+ }
+ else { //nChannels==3
+ oDesc.create(oInputImg.size(), CV_16UC3);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ const int _x = (int)voKeyPoints[k].pt.x;
+ const int _y = (int)voKeyPoints[k].pt.y;
+ const uchar* _ref = _refdata + _step_row*(_y)+3 * (_x);
+ ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0] * _y + oDesc.step.p[1] * _x));
+ const size_t _t[3] = { (size_t)(_ref[0] * fThreshold) + nThresholdOffset,(size_t)(_ref[1] * fThreshold) + nThresholdOffset,(size_t)(_ref[2] * fThreshold) + nThresholdOffset };
+#include "LBSP_16bits_dbcross_3ch3t.i"
+ }
+ }
+}
+
+void LBSP_::compute2(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const {
+ CV_Assert(!oImage.empty());
+ cv::KeyPointsFilter::runByImageBorder(voKeypoints, oImage.size(), PATCH_SIZE / 2);
+ cv::KeyPointsFilter::runByKeypointSize(voKeypoints, std::numeric_limits<float>::epsilon());
+ if (voKeypoints.empty()) {
+ oDescriptors.release();
+ return;
+ }
+ if (m_bOnlyUsingAbsThreshold)
+ LBSP__computeImpl2(oImage, m_oRefImage, voKeypoints, oDescriptors, m_nThreshold);
+ else
+ LBSP__computeImpl2(oImage, m_oRefImage, voKeypoints, oDescriptors, m_fRelThreshold, m_nThreshold);
+}
+
+void LBSP_::compute2(const std::vector<cv::Mat>& voImageCollection, std::vector<std::vector<cv::KeyPoint> >& vvoPointCollection, std::vector<cv::Mat>& voDescCollection) const {
+ CV_Assert(voImageCollection.size() == vvoPointCollection.size());
+ voDescCollection.resize(voImageCollection.size());
+ for (size_t i = 0; i < voImageCollection.size(); i++)
+ compute2(voImageCollection[i], vvoPointCollection[i], voDescCollection[i]);
+}
+
+void LBSP_::computeImpl(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const {
+ CV_Assert(!oImage.empty());
+ cv::KeyPointsFilter::runByImageBorder(voKeypoints, oImage.size(), PATCH_SIZE / 2);
+ cv::KeyPointsFilter::runByKeypointSize(voKeypoints, std::numeric_limits<float>::epsilon());
+ if (voKeypoints.empty()) {
+ oDescriptors.release();
+ return;
+ }
+ if (m_bOnlyUsingAbsThreshold)
+ LBSP__computeImpl(oImage, m_oRefImage, voKeypoints, oDescriptors, m_nThreshold);
+ else
+ LBSP__computeImpl(oImage, m_oRefImage, voKeypoints, oDescriptors, m_fRelThreshold, m_nThreshold);
+}
+
+void LBSP_::reshapeDesc(cv::Size oSize, const std::vector<cv::KeyPoint>& voKeypoints, const cv::Mat& oDescriptors, cv::Mat& oOutput) {
+ CV_DbgAssert(!voKeypoints.empty());
+ CV_DbgAssert(!oDescriptors.empty() && oDescriptors.cols == 1);
+ CV_DbgAssert(oSize.width > 0 && oSize.height > 0);
+ CV_DbgAssert(DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(oDescriptors.type() == CV_16UC1 || oDescriptors.type() == CV_16UC3);
+ const size_t nChannels = (size_t)oDescriptors.channels();
+ const size_t nKeyPoints = voKeypoints.size();
+ if (nChannels == 1) {
+ oOutput.create(oSize, CV_16UC1);
+ oOutput = cv::Scalar_<ushort>(0);
+ for (size_t k = 0; k < nKeyPoints; ++k)
+ oOutput.at<ushort>(voKeypoints[k].pt) = oDescriptors.at<ushort>((int)k);
+ }
+ else { //nChannels==3
+ oOutput.create(oSize, CV_16UC3);
+ oOutput = cv::Scalar_<ushort>(0, 0, 0);
+ for (size_t k = 0; k < nKeyPoints; ++k) {
+ ushort* output_ptr = (ushort*)(oOutput.data + oOutput.step.p[0] * (int)voKeypoints[k].pt.y);
+ const ushort* const desc_ptr = (ushort*)(oDescriptors.data + oDescriptors.step.p[0] * k);
+ const size_t idx = 3 * (int)voKeypoints[k].pt.x;
+ for (size_t n = 0; n < 3; ++n)
+ output_ptr[idx + n] = desc_ptr[n];
+ }
+ }
+}
+
+void LBSP_::calcDescImgDiff(const cv::Mat& oDesc1, const cv::Mat& oDesc2, cv::Mat& oOutput, bool bForceMergeChannels) {
+ CV_DbgAssert(oDesc1.size() == oDesc2.size() && oDesc1.type() == oDesc2.type());
+ CV_DbgAssert(DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(oDesc1.type() == CV_16UC1 || oDesc1.type() == CV_16UC3);
+ CV_DbgAssert(CV_MAT_DEPTH(oDesc1.type()) == CV_16U);
+ CV_DbgAssert(DESC_SIZE * 8 <= UCHAR_MAX);
+ CV_DbgAssert(oDesc1.step.p[0] == oDesc2.step.p[0] && oDesc1.step.p[1] == oDesc2.step.p[1]);
+ const float fScaleFactor = (float)UCHAR_MAX / (DESC_SIZE * 8);
+ const size_t nChannels = CV_MAT_CN(oDesc1.type());
+ const size_t _step_row = oDesc1.step.p[0];
+ if (nChannels == 1) {
+ oOutput.create(oDesc1.size(), CV_8UC1);
+ oOutput = cv::Scalar(0);
+ for (int i = 0; i < oDesc1.rows; ++i) {
+ const size_t idx = _step_row*i;
+ const ushort* const desc1_ptr = (ushort*)(oDesc1.data + idx);
+ const ushort* const desc2_ptr = (ushort*)(oDesc2.data + idx);
+ for (int j = 0; j < oDesc1.cols; ++j)
+ oOutput.at<uchar>(i, j) = (uchar)(fScaleFactor*hdist(desc1_ptr[j], desc2_ptr[j]));
+ }
+ }
+ else { //nChannels==3
+ if (bForceMergeChannels)
+ oOutput.create(oDesc1.size(), CV_8UC1);
+ else
+ oOutput.create(oDesc1.size(), CV_8UC3);
+ oOutput = cv::Scalar::all(0);
+ for (int i = 0; i < oDesc1.rows; ++i) {
+ const size_t idx = _step_row*i;
+ const ushort* const desc1_ptr = (ushort*)(oDesc1.data + idx);
+ const ushort* const desc2_ptr = (ushort*)(oDesc2.data + idx);
+ uchar* output_ptr = oOutput.data + oOutput.step.p[0] * i;
+ for (int j = 0; j < oDesc1.cols; ++j) {
+ for (size_t n = 0; n < 3; ++n) {
+ const size_t idx2 = 3 * j + n;
+ if (bForceMergeChannels)
+ output_ptr[j] += (uchar)((fScaleFactor*hdist(desc1_ptr[idx2], desc2_ptr[idx2])) / 3);
+ else
+ output_ptr[idx2] = (uchar)(fScaleFactor*hdist(desc1_ptr[idx2], desc2_ptr[idx2]));
+ }
+ }
+ }
+ }
+}
+
+void LBSP_::validateKeyPoints(std::vector<cv::KeyPoint>& voKeypoints, cv::Size oImgSize) {
+ cv::KeyPointsFilter::runByImageBorder(voKeypoints, oImgSize, PATCH_SIZE / 2);
+}
+
+void LBSP_::validateROI(cv::Mat& oROI) {
+ CV_Assert(!oROI.empty() && oROI.type() == CV_8UC1);
+ cv::Mat oROI_new(oROI.size(), CV_8UC1, cv::Scalar_<uchar>(0));
+ const size_t nBorderSize = PATCH_SIZE / 2;
+ const cv::Rect nROI_inner(nBorderSize, nBorderSize, oROI.cols - nBorderSize * 2, oROI.rows - nBorderSize * 2);
+ cv::Mat(oROI, nROI_inner).copyTo(cv::Mat(oROI_new, nROI_inner));
+ oROI = oROI_new;
+}
diff --git a/package_bgs/LBSP/LBSP_.h b/package_bgs/LBSP/LBSP_.h
new file mode 100644
index 0000000..819174a
--- /dev/null
+++ b/package_bgs/LBSP/LBSP_.h
@@ -0,0 +1,134 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <opencv2/core/core.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/features2d/features2d.hpp>
+#include "DistanceUtils.h"
+
+/*!
+ Local Binary Similarity Pattern (LBSP) feature extractor
+
+ Note 1: both grayscale and RGB/BGR images may be used with this extractor.
+ Note 2: using LBSP_::compute2(...) is logically equivalent to using LBSP_::compute(...) followed by LBSP_::reshapeDesc(...).
+
+ For more details on the different parameters, see G.-A. Bilodeau et al, "Change Detection in Feature Space Using Local
+ Binary Similarity Patterns", in CRV 2013.
+
+ This algorithm is currently NOT thread-safe.
+ */
+class LBSP_ : public cv::Feature2D {
+public:
+ //! constructor 1, threshold = absolute intensity 'similarity' threshold used when computing comparisons
+ LBSP_(size_t nThreshold);
+ //! constructor 2, threshold = relative intensity 'similarity' threshold used when computing comparisons
+ LBSP_(float fRelThreshold, size_t nThresholdOffset = 0);
+ //! default destructor
+ virtual ~LBSP_();
+ //! loads extractor params from the specified file node @@@@ not impl
+ virtual void read(const cv::FileNode&);
+ //! writes extractor params to the specified file storage @@@@ not impl
+ virtual void write(cv::FileStorage&) const;
+ //! sets the 'reference' image to be used for inter-frame comparisons (note: if no image is set or if the image is empty, the algorithm will default back to intra-frame comparisons)
+ virtual void setReference(const cv::Mat&);
+ //! returns the current descriptor size, in bytes
+ virtual int descriptorSize() const;
+ //! returns the current descriptor data type
+ virtual int descriptorType() const;
+ //! returns whether this extractor is using a relative threshold or not
+ virtual bool isUsingRelThreshold() const;
+ //! returns the current relative threshold used for comparisons (-1 = invalid/not used)
+ virtual float getRelThreshold() const;
+ //! returns the current absolute threshold used for comparisons (-1 = invalid/not used)
+ virtual size_t getAbsThreshold() const;
+
+ //! similar to DescriptorExtractor::compute(const cv::Mat& image, ...), but in this case, the descriptors matrix has the same shape as the input matrix (possibly slower, but the result can be displayed)
+ void compute2(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const;
+ //! batch version of LBSP_::compute2(const cv::Mat& image, ...), also similar to DescriptorExtractor::compute(const std::vector<cv::Mat>& imageCollection, ...)
+ void compute2(const std::vector<cv::Mat>& voImageCollection, std::vector<std::vector<cv::KeyPoint> >& vvoPointCollection, std::vector<cv::Mat>& voDescCollection) const;
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (1-channel version)
+ inline static void computeGrayscaleDescriptor(const cv::Mat& oInputImg, const uchar _ref, const int _x, const int _y, const size_t _t, ushort& _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC1);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP_::PATCH_SIZE / 2 && _y >= (int)LBSP_::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP_::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP_::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_1ch.i"
+ }
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (3-channels version)
+ inline static void computeRGBDescriptor(const cv::Mat& oInputImg, const uchar* const _ref, const int _x, const int _y, const size_t* const _t, ushort* _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP_::PATCH_SIZE / 2 && _y >= (int)LBSP_::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP_::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP_::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_3ch3t.i"
+ }
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (3-channels version)
+ inline static void computeRGBDescriptor(const cv::Mat& oInputImg, const uchar* const _ref, const int _x, const int _y, const size_t _t, ushort* _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP_::PATCH_SIZE / 2 && _y >= (int)LBSP_::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP_::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP_::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_3ch1t.i"
+ }
+
+ //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (1-channel-RGB version)
+ inline static void computeSingleRGBDescriptor(const cv::Mat& oInputImg, const uchar _ref, const int _x, const int _y, const size_t _c, const size_t _t, ushort& _res) {
+ CV_DbgAssert(!oInputImg.empty());
+ CV_DbgAssert(oInputImg.type() == CV_8UC3 && _c < 3);
+ CV_DbgAssert(LBSP_::DESC_SIZE == 2); // @@@ also relies on a constant desc size
+ CV_DbgAssert(_x >= (int)LBSP_::PATCH_SIZE / 2 && _y >= (int)LBSP_::PATCH_SIZE / 2);
+ CV_DbgAssert(_x < oInputImg.cols - (int)LBSP_::PATCH_SIZE / 2 && _y < oInputImg.rows - (int)LBSP_::PATCH_SIZE / 2);
+ const size_t _step_row = oInputImg.step.p[0];
+ const uchar* const _data = oInputImg.data;
+#include "LBSP_16bits_dbcross_s3ch.i"
+ }
+
+ //! utility function, used to reshape a descriptors matrix to its input image size via their keypoint locations
+ static void reshapeDesc(cv::Size oSize, const std::vector<cv::KeyPoint>& voKeypoints, const cv::Mat& oDescriptors, cv::Mat& oOutput);
+ //! utility function, used to illustrate the difference between two descriptor images
+ static void calcDescImgDiff(const cv::Mat& oDesc1, const cv::Mat& oDesc2, cv::Mat& oOutput, bool bForceMergeChannels = false);
+ //! utility function, used to filter out bad keypoints that would trigger out of bounds error because they're too close to the image border
+ static void validateKeyPoints(std::vector<cv::KeyPoint>& voKeypoints, cv::Size oImgSize);
+ //! utility function, used to filter out bad pixels in a ROI that would trigger out of bounds error because they're too close to the image border
+ static void validateROI(cv::Mat& oROI);
+ //! utility, specifies the pixel size of the pattern used (width and height)
+ static const size_t PATCH_SIZE = 5;
+ //! utility, specifies the number of bytes per descriptor (should be the same as calling 'descriptorSize()')
+ static const size_t DESC_SIZE = 2;
+
+protected:
+ //! classic 'compute' implementation, based on the regular DescriptorExtractor::computeImpl arguments & expected output
+ virtual void computeImpl(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const;
+
+ const bool m_bOnlyUsingAbsThreshold;
+ const float m_fRelThreshold;
+ const size_t m_nThreshold;
+ cv::Mat m_oRefImage;
+};
diff --git a/package_bgs/pl/LBSP_16bits_dbcross_1ch.i b/package_bgs/LBSP/LBSP_16bits_dbcross_1ch.i
similarity index 100%
rename from package_bgs/pl/LBSP_16bits_dbcross_1ch.i
rename to package_bgs/LBSP/LBSP_16bits_dbcross_1ch.i
diff --git a/package_bgs/pl/LBSP_16bits_dbcross_3ch1t.i b/package_bgs/LBSP/LBSP_16bits_dbcross_3ch1t.i
similarity index 100%
rename from package_bgs/pl/LBSP_16bits_dbcross_3ch1t.i
rename to package_bgs/LBSP/LBSP_16bits_dbcross_3ch1t.i
diff --git a/package_bgs/pl/LBSP_16bits_dbcross_3ch3t.i b/package_bgs/LBSP/LBSP_16bits_dbcross_3ch3t.i
similarity index 100%
rename from package_bgs/pl/LBSP_16bits_dbcross_3ch3t.i
rename to package_bgs/LBSP/LBSP_16bits_dbcross_3ch3t.i
diff --git a/package_bgs/pl/LBSP_16bits_dbcross_s3ch.i b/package_bgs/LBSP/LBSP_16bits_dbcross_s3ch.i
similarity index 100%
rename from package_bgs/pl/LBSP_16bits_dbcross_s3ch.i
rename to package_bgs/LBSP/LBSP_16bits_dbcross_s3ch.i
diff --git a/package_bgs/LBSP/RandUtils.h b/package_bgs/LBSP/RandUtils.h
new file mode 100644
index 0000000..f676ca0
--- /dev/null
+++ b/package_bgs/LBSP/RandUtils.h
@@ -0,0 +1,112 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+/*// gaussian 3x3 pattern, based on 'floor(fspecial('gaussian', 3, 1)*256)'
+static const int s_nSamplesInitPatternWidth = 3;
+static const int s_nSamplesInitPatternHeight = 3;
+static const int s_nSamplesInitPatternTot = 256;
+static const int s_anSamplesInitPattern[s_nSamplesInitPatternHeight][s_nSamplesInitPatternWidth] = {
+ {19, 32, 19,},
+ {32, 52, 32,},
+ {19, 32, 19,},
+};*/
+
+// gaussian 7x7 pattern, based on 'floor(fspecial('gaussian',7,2)*512)'
+static const int s_nSamplesInitPatternWidth = 7;
+static const int s_nSamplesInitPatternHeight = 7;
+static const int s_nSamplesInitPatternTot = 512;
+static const int s_anSamplesInitPattern[s_nSamplesInitPatternHeight][s_nSamplesInitPatternWidth] = {
+ {2, 4, 6, 7, 6, 4, 2,},
+ {4, 8, 12, 14, 12, 8, 4,},
+ {6, 12, 21, 25, 21, 12, 6,},
+ {7, 14, 25, 28, 25, 14, 7,},
+ {6, 12, 21, 25, 21, 12, 6,},
+ {4, 8, 12, 14, 12, 8, 4,},
+ {2, 4, 6, 7, 6, 4, 2,},
+};
+
+//! returns a random init/sampling position for the specified pixel position; also guards against out-of-bounds values via image/border size check.
+static inline void getRandSamplePosition(int& x_sample, int& y_sample, const int x_orig, const int y_orig, const int border, const cv::Size& imgsize) {
+ int r = 1+rand()%s_nSamplesInitPatternTot;
+ for(x_sample=0; x_sample<s_nSamplesInitPatternWidth; ++x_sample) {
+ for(y_sample=0; y_sample<s_nSamplesInitPatternHeight; ++y_sample) {
+ r -= s_anSamplesInitPattern[y_sample][x_sample];
+ if(r<=0)
+ goto stop;
+ }
+ }
+stop:
+ x_sample += x_orig-s_nSamplesInitPatternWidth/2;
+ y_sample += y_orig-s_nSamplesInitPatternHeight/2;
+ if(x_sample<border)
+ x_sample = border;
+ else if(x_sample>=imgsize.width-border)
+ x_sample = imgsize.width-border-1;
+ if(y_sample<border)
+ y_sample = border;
+ else if(y_sample>=imgsize.height-border)
+ y_sample = imgsize.height-border-1;
+}
+
+// simple 8-connected (3x3) neighbors pattern
+static const int s_anNeighborPatternSize_3x3 = 8;
+static const int s_anNeighborPattern_3x3[8][2] = {
+ {-1, 1}, { 0, 1}, { 1, 1},
+ {-1, 0}, { 1, 0},
+ {-1,-1}, { 0,-1}, { 1,-1},
+};
+
+//! returns a random neighbor position for the specified pixel position; also guards against out-of-bounds values via image/border size check.
+static inline void getRandNeighborPosition_3x3(int& x_neighbor, int& y_neighbor, const int x_orig, const int y_orig, const int border, const cv::Size& imgsize) {
+ int r = rand()%s_anNeighborPatternSize_3x3;
+ x_neighbor = x_orig+s_anNeighborPattern_3x3[r][0];
+ y_neighbor = y_orig+s_anNeighborPattern_3x3[r][1];
+ if(x_neighbor<border)
+ x_neighbor = border;
+ else if(x_neighbor>=imgsize.width-border)
+ x_neighbor = imgsize.width-border-1;
+ if(y_neighbor<border)
+ y_neighbor = border;
+ else if(y_neighbor>=imgsize.height-border)
+ y_neighbor = imgsize.height-border-1;
+}
+
+// 5x5 neighbors pattern
+static const int s_anNeighborPatternSize_5x5 = 24;
+static const int s_anNeighborPattern_5x5[24][2] = {
+ {-2, 2}, {-1, 2}, { 0, 2}, { 1, 2}, { 2, 2},
+ {-2, 1}, {-1, 1}, { 0, 1}, { 1, 1}, { 2, 1},
+ {-2, 0}, {-1, 0}, { 1, 0}, { 2, 0},
+ {-2,-1}, {-1,-1}, { 0,-1}, { 1,-1}, { 2,-1},
+ {-2,-2}, {-1,-2}, { 0,-2}, { 1,-2}, { 2,-2},
+};
+
+//! returns a random neighbor position for the specified pixel position; also guards against out-of-bounds values via image/border size check.
+static inline void getRandNeighborPosition_5x5(int& x_neighbor, int& y_neighbor, const int x_orig, const int y_orig, const int border, const cv::Size& imgsize) {
+ int r = rand()%s_anNeighborPatternSize_5x5;
+ x_neighbor = x_orig+s_anNeighborPattern_5x5[r][0];
+ y_neighbor = y_orig+s_anNeighborPattern_5x5[r][1];
+ if(x_neighbor<border)
+ x_neighbor = border;
+ else if(x_neighbor>=imgsize.width-border)
+ x_neighbor = imgsize.width-border-1;
+ if(y_neighbor<border)
+ y_neighbor = border;
+ else if(y_neighbor>=imgsize.height-border)
+ y_neighbor = imgsize.height-border-1;
+}
diff --git a/package_bgs/lb/LBSimpleGaussian.cpp b/package_bgs/LBSimpleGaussian.cpp
similarity index 61%
rename from package_bgs/lb/LBSimpleGaussian.cpp
rename to package_bgs/LBSimpleGaussian.cpp
index f0ce6fc..9ce071c 100644
--- a/package_bgs/lb/LBSimpleGaussian.cpp
+++ b/package_bgs/LBSimpleGaussian.cpp
@@ -16,9 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "LBSimpleGaussian.h"
-LBSimpleGaussian::LBSimpleGaussian() : firstTime(true), showOutput(true), sensitivity(66), noiseVariance(162), learningRate(18)
+using namespace bgslibrary::algorithms;
+
+LBSimpleGaussian::LBSimpleGaussian() :
+ sensitivity(66), noiseVariance(162), learningRate(18)
{
std::cout << "LBSimpleGaussian()" << std::endl;
+ setup("./config/LBSimpleGaussian.xml");
}
LBSimpleGaussian::~LBSimpleGaussian()
@@ -29,55 +33,47 @@ LBSimpleGaussian::~LBSimpleGaussian()
void LBSimpleGaussian::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- loadConfig();
-
IplImage *frame = new IplImage(img_input);
-
- if(firstTime)
- {
- saveConfig();
+ if (firstTime)
+ {
int w = cvGetSize(frame).width;
int h = cvGetSize(frame).height;
- m_pBGModel = new BGModelGauss(w,h);
+ m_pBGModel = new BGModelGauss(w, h);
m_pBGModel->InitModel(frame);
}
-
- m_pBGModel->setBGModelParameter(0,sensitivity);
- m_pBGModel->setBGModelParameter(1,noiseVariance);
- m_pBGModel->setBGModelParameter(2,learningRate);
+
+ m_pBGModel->setBGModelParameter(0, sensitivity);
+ m_pBGModel->setBGModelParameter(1, noiseVariance);
+ m_pBGModel->setBGModelParameter(2, learningRate);
m_pBGModel->UpdateModel(frame);
- img_foreground = cv::Mat(m_pBGModel->GetFG());
- img_background = cv::Mat(m_pBGModel->GetBG());
-
- if(showOutput)
+ img_foreground = cv::cvarrToMat(m_pBGModel->GetFG());
+ img_background = cv::cvarrToMat(m_pBGModel->GetBG());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
cv::imshow("SG Mask", img_foreground);
cv::imshow("SG Model", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
-
+
delete frame;
-
+
firstTime = false;
}
-//void LBSimpleGaussian::finish(void)
-//{
-// delete m_pBGModel;
-//}
-
void LBSimpleGaussian::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBSimpleGaussian.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "sensitivity", sensitivity);
cvWriteInt(fs, "noiseVariance", noiseVariance);
@@ -89,12 +85,12 @@ void LBSimpleGaussian::saveConfig()
void LBSimpleGaussian::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/LBSimpleGaussian.xml", 0, CV_STORAGE_READ);
-
- sensitivity = cvReadIntByName(fs, 0, "sensitivity", 66);
- noiseVariance = cvReadIntByName(fs, 0, "noiseVariance", 162);
- learningRate = cvReadIntByName(fs, 0, "learningRate", 18);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ sensitivity = cvReadIntByName(fs, nullptr, "sensitivity", 66);
+ noiseVariance = cvReadIntByName(fs, nullptr, "noiseVariance", 162);
+ learningRate = cvReadIntByName(fs, nullptr, "learningRate", 18);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/LBSimpleGaussian.h b/package_bgs/LBSimpleGaussian.h
similarity index 57%
rename from package_bgs/lb/LBSimpleGaussian.h
rename to package_bgs/LBSimpleGaussian.h
index bfefd3e..5c82923 100644
--- a/package_bgs/lb/LBSimpleGaussian.h
+++ b/package_bgs/LBSimpleGaussian.h
@@ -16,39 +16,33 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "BGModelGauss.h"
-
-#include "../IBGS.h"
+#include "IBGS.h"
+#include "lb/BGModelGauss.h"
using namespace lb_library;
using namespace lb_library::SimpleGaussian;
-class LBSimpleGaussian : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- bool showOutput;
-
- BGModel* m_pBGModel;
- int sensitivity;
- int noiseVariance;
- int learningRate;
-
- cv::Mat img_foreground;
- cv::Mat img_background;
-
-public:
- LBSimpleGaussian();
- ~LBSimpleGaussian();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
- //void finish(void);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
+ namespace algorithms
+ {
+ class LBSimpleGaussian : public IBGS
+ {
+ private:
+ BGModel* m_pBGModel;
+ int sensitivity;
+ int noiseVariance;
+ int learningRate;
+
+ public:
+ LBSimpleGaussian();
+ ~LBSimpleGaussian();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/LOBSTER.cpp b/package_bgs/LOBSTER.cpp
new file mode 100644
index 0000000..dc48a63
--- /dev/null
+++ b/package_bgs/LOBSTER.cpp
@@ -0,0 +1,98 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "LOBSTER.h"
+
+using namespace bgslibrary::algorithms;
+
+LOBSTER::LOBSTER() :
+ pLOBSTER(nullptr),
+ fRelLBSPThreshold(BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD),
+ nLBSPThresholdOffset(BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD),
+ nDescDistThreshold(BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD),
+ nColorDistThreshold(BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD),
+ nBGSamples(BGSLOBSTER_DEFAULT_NB_BG_SAMPLES),
+ nRequiredBGSamples(BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES)
+{
+ std::cout << "LOBSTER()" << std::endl;
+ setup("./config/LOBSTER.xml");
+}
+
+LOBSTER::~LOBSTER()
+{
+ if (pLOBSTER)
+ delete pLOBSTER;
+ std::cout << "~LOBSTER()" << std::endl;
+}
+
+void LOBSTER::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (firstTime)
+ {
+ pLOBSTER = new BackgroundSubtractorLOBSTER(
+ fRelLBSPThreshold, nLBSPThresholdOffset, nDescDistThreshold,
+ nColorDistThreshold, nBGSamples, nRequiredBGSamples);
+
+ pLOBSTER->initialize(img_input, cv::Mat(img_input.size(), CV_8UC1, cv::Scalar_<uchar>(255)));
+ firstTime = false;
+ }
+
+ pLOBSTER->apply(img_input, img_foreground);
+ pLOBSTER->getBackgroundImage(img_background);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ imshow("LOBSTER FG", img_foreground);
+ imshow("LOBSTER BG", img_background);
+ }
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+}
+
+void LOBSTER::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteReal(fs, "fRelLBSPThreshold", fRelLBSPThreshold);
+ cvWriteInt(fs, "nLBSPThresholdOffset", nLBSPThresholdOffset);
+ cvWriteInt(fs, "nDescDistThreshold", nDescDistThreshold);
+ cvWriteInt(fs, "nColorDistThreshold", nColorDistThreshold);
+ cvWriteInt(fs, "nBGSamples", nBGSamples);
+ cvWriteInt(fs, "nRequiredBGSamples", nRequiredBGSamples);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void LOBSTER::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ fRelLBSPThreshold = cvReadRealByName(fs, nullptr, "fRelLBSPThreshold", BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD);
+ nLBSPThresholdOffset = cvReadIntByName(fs, nullptr, "nLBSPThresholdOffset", BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD);
+ nDescDistThreshold = cvReadIntByName(fs, nullptr, "nDescDistThreshold", BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD);
+ nColorDistThreshold = cvReadIntByName(fs, nullptr, "nColorDistThreshold", BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD);
+ nBGSamples = cvReadIntByName(fs, nullptr, "nBGSamples", BGSLOBSTER_DEFAULT_NB_BG_SAMPLES);
+ nRequiredBGSamples = cvReadIntByName(fs, nullptr, "nRequiredBGSamples", BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/LOBSTER.h b/package_bgs/LOBSTER.h
new file mode 100644
index 0000000..41ba882
--- /dev/null
+++ b/package_bgs/LOBSTER.h
@@ -0,0 +1,49 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "LBSP/BackgroundSubtractorLOBSTER.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class LOBSTER : public IBGS
+ {
+ private:
+ BackgroundSubtractorLOBSTER* pLOBSTER;
+
+ float fRelLBSPThreshold;
+ size_t nLBSPThresholdOffset;
+ size_t nDescDistThreshold;
+ size_t nColorDistThreshold;
+ size_t nBGSamples;
+ size_t nRequiredBGSamples;
+
+ public:
+ LOBSTER();
+ ~LOBSTER();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/MixtureOfGaussianV1BGS.cpp b/package_bgs/MixtureOfGaussianV1.cpp
similarity index 53%
rename from package_bgs/MixtureOfGaussianV1BGS.cpp
rename to package_bgs/MixtureOfGaussianV1.cpp
index 51d41eb..e56609a 100644
--- a/package_bgs/MixtureOfGaussianV1BGS.cpp
+++ b/package_bgs/MixtureOfGaussianV1.cpp
@@ -14,27 +14,27 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "MixtureOfGaussianV1BGS.h"
+#include "MixtureOfGaussianV1.h"
-MixtureOfGaussianV1BGS::MixtureOfGaussianV1BGS() : firstTime(true), alpha(0.05), enableThreshold(true), threshold(15), showOutput(true)
+#if CV_MAJOR_VERSION == 2
+
+using namespace bgslibrary::algorithms;
+
+MixtureOfGaussianV1::MixtureOfGaussianV1() :
+ alpha(0.05), enableThreshold(true), threshold(15)
{
- std::cout << "MixtureOfGaussianV1BGS()" << std::endl;
+ std::cout << "MixtureOfGaussianV1()" << std::endl;
+ setup("./config/MixtureOfGaussianV1.xml");
}
-MixtureOfGaussianV1BGS::~MixtureOfGaussianV1BGS()
+MixtureOfGaussianV1::~MixtureOfGaussianV1()
{
- std::cout << "~MixtureOfGaussianV1BGS()" << std::endl;
+ std::cout << "~MixtureOfGaussianV1()" << std::endl;
}
-void MixtureOfGaussianV1BGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void MixtureOfGaussianV1::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
//------------------------------------------------------------------
// BackgroundSubtractorMOG
@@ -43,26 +43,30 @@ void MixtureOfGaussianV1BGS::process(const cv::Mat &img_input, cv::Mat &img_outp
// Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm.
//
// The class implements the algorithm described in:
- // P. KadewTraKuPong and R. Bowden,
- // An improved adaptive background mixture model for real-time tracking with shadow detection,
+ // P. KadewTraKuPong and R. Bowden,
+ // An improved adaptive background mixture model for real-time tracking with shadow detection,
// Proc. 2nd European Workshp on Advanced Video-Based Surveillance Systems, 2001
//------------------------------------------------------------------
mog(img_input, img_foreground, alpha);
- cv::Mat img_background;
mog.getBackgroundImage(img_background);
- if(enableThreshold)
+ if (enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
- if(showOutput)
+ if (img_foreground.empty())
+ img_foreground = cv::Mat::zeros(img_input.size(), img_input.type());
+
+ if (img_background.empty())
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
- if (!img_foreground.empty())
- cv::imshow("GMM FG (KadewTraKuPong&Bowden)", img_foreground);
-
- if (!img_background.empty())
- cv::imshow("GMM BG (KadewTraKuPong&Bowden)", img_background);
+ cv::imshow("GMM FG (KadewTraKuPong&Bowden)", img_foreground);
+ cv::imshow("GMM BG (KadewTraKuPong&Bowden)", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -70,9 +74,9 @@ void MixtureOfGaussianV1BGS::process(const cv::Mat &img_input, cv::Mat &img_outp
firstTime = false;
}
-void MixtureOfGaussianV1BGS::saveConfig()
+void MixtureOfGaussianV1::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MixtureOfGaussianV1BGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "alpha", alpha);
cvWriteInt(fs, "enableThreshold", enableThreshold);
@@ -82,14 +86,15 @@ void MixtureOfGaussianV1BGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void MixtureOfGaussianV1BGS::loadConfig()
+void MixtureOfGaussianV1::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MixtureOfGaussianV1BGS.xml", 0, CV_STORAGE_READ);
-
- alpha = cvReadRealByName(fs, 0, "alpha", 0.05);
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.05);
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
+#endif
diff --git a/package_bgs/MixtureOfGaussianV1BGS.h b/package_bgs/MixtureOfGaussianV1.h
similarity index 59%
rename from package_bgs/MixtureOfGaussianV1BGS.h
rename to package_bgs/MixtureOfGaussianV1.h
index f735a13..e18dbdb 100644
--- a/package_bgs/MixtureOfGaussianV1BGS.h
+++ b/package_bgs/MixtureOfGaussianV1.h
@@ -16,32 +16,38 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
+#include "opencv2/core/version.hpp"
+#if CV_MAJOR_VERSION == 2
+
#include <iostream>
#include <opencv2/opencv.hpp>
-
#include <opencv2/video/background_segm.hpp>
#include "IBGS.h"
-class MixtureOfGaussianV1BGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::BackgroundSubtractorMOG mog;
- cv::Mat img_foreground;
- double alpha;
- bool enableThreshold;
- int threshold;
- bool showOutput;
-
-public:
- MixtureOfGaussianV1BGS();
- ~MixtureOfGaussianV1BGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class MixtureOfGaussianV1 : public IBGS
+ {
+ private:
+ cv::BackgroundSubtractorMOG mog;
+ double alpha;
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ MixtureOfGaussianV1();
+ ~MixtureOfGaussianV1();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
+
+#endif
diff --git a/package_bgs/MixtureOfGaussianV2BGS.cpp b/package_bgs/MixtureOfGaussianV2.cpp
similarity index 60%
rename from package_bgs/MixtureOfGaussianV2BGS.cpp
rename to package_bgs/MixtureOfGaussianV2.cpp
index 5ce33a3..085b1a9 100644
--- a/package_bgs/MixtureOfGaussianV2BGS.cpp
+++ b/package_bgs/MixtureOfGaussianV2.cpp
@@ -14,27 +14,31 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "MixtureOfGaussianV2BGS.h"
+#include "MixtureOfGaussianV2.h"
-MixtureOfGaussianV2BGS::MixtureOfGaussianV2BGS() : firstTime(true), alpha(0.05), enableThreshold(true), threshold(15), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+MixtureOfGaussianV2::MixtureOfGaussianV2() :
+ alpha(0.05), enableThreshold(true), threshold(15)
{
- std::cout << "MixtureOfGaussianV2BGS()" << std::endl;
+ std::cout << "MixtureOfGaussianV2()" << std::endl;
+ setup("./config/MixtureOfGaussianV2.xml");
}
-MixtureOfGaussianV2BGS::~MixtureOfGaussianV2BGS()
+MixtureOfGaussianV2::~MixtureOfGaussianV2()
{
- std::cout << "~MixtureOfGaussianV2BGS()" << std::endl;
+ std::cout << "~MixtureOfGaussianV2()" << std::endl;
}
-void MixtureOfGaussianV2BGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void MixtureOfGaussianV2::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
+ init(img_input, img_output, img_bgmodel);
- if(firstTime)
- saveConfig();
+ if (firstTime) {
+#if CV_MAJOR_VERSION == 3
+ mog = cv::createBackgroundSubtractorMOG2();
+#endif
+ }
//------------------------------------------------------------------
// BackgroundSubtractorMOG2
@@ -43,29 +47,34 @@ void MixtureOfGaussianV2BGS::process(const cv::Mat &img_input, cv::Mat &img_outp
// Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm.
//
// The class implements the Gaussian mixture model background subtraction described in:
- // (1) Z.Zivkovic, Improved adaptive Gausian mixture model for background subtraction, International Conference Pattern Recognition, UK, August, 2004,
+ // (1) Z.Zivkovic, Improved adaptive Gausian mixture model for background subtraction, International Conference Pattern Recognition, UK, August, 2004,
// The code is very fast and performs also shadow detection. Number of Gausssian components is adapted per pixel.
//
- // (2) Z.Zivkovic, F. van der Heijden, Efficient Adaptive Density Estimation per Image Pixel for the Task of Background Subtraction,
- // Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
- // The algorithm similar to the standard Stauffer&Grimson algorithm with additional selection of the number of the Gaussian components based on:
- // Z.Zivkovic, F.van der Heijden, Recursive unsupervised learning of finite mixture models, IEEE Trans. on Pattern Analysis and Machine Intelligence,
+ // (2) Z.Zivkovic, F. van der Heijden, Efficient Adaptive Density Estimation per Image Pixel for the Task of Background Subtraction,
+ // Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
+ // The algorithm similar to the standard Stauffer&Grimson algorithm with additional selection of the number of the Gaussian components based on:
+ // Z.Zivkovic, F.van der Heijden, Recursive unsupervised learning of finite mixture models, IEEE Trans. on Pattern Analysis and Machine Intelligence,
// vol.26, no.5, pages 651-656, 2004.
//------------------------------------------------------------------
+#if CV_MAJOR_VERSION == 2
mog(img_input, img_foreground, alpha);
-
- cv::Mat img_background;
mog.getBackgroundImage(img_background);
+#elif CV_MAJOR_VERSION == 3
+ mog->apply(img_input, img_foreground, alpha);
+ mog->getBackgroundImage(img_background);
+#endif
- if(enableThreshold)
+ if (enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
- cv::imshow("GMM (Zivkovic&Heijden)", img_foreground);
- cv::imshow("GMM BKG (Zivkovic&Heijden)", img_background);
+ cv::imshow("GMM FG (Zivkovic&Heijden)", img_foreground);
+ cv::imshow("GMM BG (Zivkovic&Heijden)", img_background);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -73,9 +82,9 @@ void MixtureOfGaussianV2BGS::process(const cv::Mat &img_input, cv::Mat &img_outp
firstTime = false;
}
-void MixtureOfGaussianV2BGS::saveConfig()
+void MixtureOfGaussianV2::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MixtureOfGaussianV2BGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "alpha", alpha);
cvWriteInt(fs, "enableThreshold", enableThreshold);
@@ -85,14 +94,14 @@ void MixtureOfGaussianV2BGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void MixtureOfGaussianV2BGS::loadConfig()
+void MixtureOfGaussianV2::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MixtureOfGaussianV2BGS.xml", 0, CV_STORAGE_READ);
-
- alpha = cvReadRealByName(fs, 0, "alpha", 0.05);
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.05);
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/MixtureOfGaussianV2BGS.h b/package_bgs/MixtureOfGaussianV2.h
similarity index 57%
rename from package_bgs/MixtureOfGaussianV2BGS.h
rename to package_bgs/MixtureOfGaussianV2.h
index a14ff0b..edc8add 100644
--- a/package_bgs/MixtureOfGaussianV2BGS.h
+++ b/package_bgs/MixtureOfGaussianV2.h
@@ -18,30 +18,35 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <iostream>
#include <opencv2/opencv.hpp>
-
#include <opencv2/video/background_segm.hpp>
#include "IBGS.h"
-class MixtureOfGaussianV2BGS : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- cv::BackgroundSubtractorMOG2 mog;
- cv::Mat img_foreground;
- double alpha;
- bool enableThreshold;
- int threshold;
- bool showOutput;
-
-public:
- MixtureOfGaussianV2BGS();
- ~MixtureOfGaussianV2BGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class MixtureOfGaussianV2 : public IBGS
+ {
+ private:
+#if CV_MAJOR_VERSION == 2
+ cv::BackgroundSubtractorMOG2 mog;
+#elif CV_MAJOR_VERSION == 3
+ cv::Ptr<cv::BackgroundSubtractorMOG2> mog;
+#endif
+ double alpha;
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ MixtureOfGaussianV2();
+ ~MixtureOfGaussianV2();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/sjn/SJN_MultiCueBGS.cpp b/package_bgs/MultiCue.cpp
similarity index 83%
rename from package_bgs/sjn/SJN_MultiCueBGS.cpp
rename to package_bgs/MultiCue.cpp
index 83db6ec..7717842 100644
--- a/package_bgs/sjn/SJN_MultiCueBGS.cpp
+++ b/package_bgs/MultiCue.cpp
@@ -21,12 +21,16 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// - Code by: SeungJon Noh //
//------------------------------------------------------------------------------------------------------------------------------------//
//#include "StdAfx.h"
-#include "SJN_MultiCueBGS.h"
-SJN_MultiCueBGS::SJN_MultiCueBGS() : firstTime(true), showOutput(true)
+#include "MultiCue.h"
+
+using namespace bgslibrary::algorithms::libMultiCue;
+using namespace bgslibrary::algorithms;
+
+MultiCue::MultiCue()
{
//----------------------------------
// User adjustable parameters
- //----------------------------------
+ //----------------------------------
g_iTrainingPeriod = 20; //the training period (The parameter t in the paper)
g_iT_ModelThreshold = 1; //the threshold for texture-model based BGS. (The parameter tau_T in the paper)
g_iC_ModelThreshold = 10; //the threshold for appearance based verification. (The parameter tau_A in the paper)
@@ -37,15 +41,15 @@ SJN_MultiCueBGS::SJN_MultiCueBGS() : firstTime(true), showOutput(true)
g_nColorTrainVolRange = 20; //the codebook size factor for color models. (The parameter eta_1 in the paper)
g_bAbsorptionEnable = TRUE; //If TRUE, cache-book is also modeled for ghost region removal.
- g_iAbsortionPeriod = 200; //the period to absorb static ghost regions
+ g_iAbsortionPeriod = 200; //the period to absorb static ghost regions
g_iRWidth = 160, g_iRHeight = 120; //Frames are precessed after reduced in this size .
//------------------------------------
// For codebook maintenance
//------------------------------------
- g_iBackClearPeriod = 300; //the period to clear background models
- g_iCacheClearPeriod = 30; //the period to clear cache-book models
+ g_iBackClearPeriod = 300; //the period to clear background models
+ g_iCacheClearPeriod = 30; //the period to clear cache-book models
//------------------------------------
// Initialization of other parameters
@@ -57,38 +61,37 @@ SJN_MultiCueBGS::SJN_MultiCueBGS() : firstTime(true), showOutput(true)
g_bForegroundMapEnable = FALSE; //TRUE only when BGS is successful
g_bModelMemAllocated = FALSE; //To handle memory..
g_bNonModelMemAllocated = FALSE; //To handle memory..
+
+ std::cout << "MultiCue()" << std::endl;
+ setup("./config/MultiCue.xml");
}
-SJN_MultiCueBGS::~SJN_MultiCueBGS(void){
+MultiCue::~MultiCue(void)
+{
Destroy();
+ std::cout << "~MultiCue()" << std::endl;
}
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the main function to background modeling and subtraction // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel){
-
- if (img_input.empty())
- return;
-
- loadConfig();
-
- if (firstTime)
- saveConfig();
+void MultiCue::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
//--STep1: Background Modeling--//
//IplImage* frame = &IplImage(img_input);
IplImage* frame = new IplImage(img_input);
IplImage* result_image = cvCreateImage(cvGetSize(frame), IPL_DEPTH_8U, 3);
cvSetZero(result_image);
-
- if (g_iFrameCount <= g_iTrainingPeriod){
+ if (g_iFrameCount <= g_iTrainingPeriod)
+ {
BackgroundModeling_Par(frame);
g_iFrameCount++;
}
-
//--Step2: Background Subtraction--//
- else{
+ else
+ {
g_bForegroundMapEnable = FALSE;
ForegroundExtraction(frame);
@@ -99,33 +102,35 @@ void SJN_MultiCueBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv:
}
delete frame;
- cv::Mat temp(result_image, TRUE);
- temp.copyTo(img_output);
-
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+ img_foreground = cv::cvarrToMat(result_image, TRUE);
cvReleaseImage(&result_image);
+#ifndef MEX_COMPILE_FLAG
if (showOutput)
- {
- cv::imshow("MultiCueBGS FG", img_output);
- }
+ cv::imshow("MultiCue FG", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
firstTime = false;
}
-void SJN_MultiCueBGS::saveConfig()
+void MultiCue::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MultiCueBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
}
-void SJN_MultiCueBGS::loadConfig()
+void MultiCue::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MultiCueBGS.xml", 0, CV_STORAGE_READ);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
@@ -133,7 +138,7 @@ void SJN_MultiCueBGS::loadConfig()
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the system initialization function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::Initialize(IplImage* frame)
+void MultiCue::Initialize(IplImage* frame)
{
int i, j;
@@ -148,15 +153,15 @@ void SJN_MultiCueBGS::Initialize(IplImage* frame)
g_ResizedFrame = cvCreateImage(cvSize(g_iRWidth, g_iRHeight), IPL_DEPTH_8U, 3);
g_aGaussFilteredFrame = (uchar***)malloc(sizeof(uchar**)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_aGaussFilteredFrame[i] = (uchar**)malloc(sizeof(uchar*)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++) g_aGaussFilteredFrame[i][j] = (uchar*)malloc(sizeof(uchar)* 3);
+ for (j = 0; j < g_iRWidth; j++) g_aGaussFilteredFrame[i][j] = (uchar*)malloc(sizeof(uchar) * 3);
}
g_aXYZFrame = (uchar***)malloc(sizeof(uchar**)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_aXYZFrame[i] = (uchar**)malloc(sizeof(uchar*)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++) g_aXYZFrame[i][j] = (uchar*)malloc(sizeof(uchar)* 3);
+ for (j = 0; j < g_iRWidth; j++) g_aXYZFrame[i][j] = (uchar*)malloc(sizeof(uchar) * 3);
}
g_aLandmarkArray = (uchar**)malloc(sizeof(uchar*)*g_iRHeight);
@@ -203,30 +208,30 @@ void SJN_MultiCueBGS::Initialize(IplImage* frame)
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function to release allocated memories //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::Destroy()
+void MultiCue::Destroy()
{
if (g_bModelMemAllocated == FALSE && g_bNonModelMemAllocated == FALSE) return;
short nNeighborNum = g_nNeighborNum;
- if (g_bModelMemAllocated == TRUE){
+ if (g_bModelMemAllocated == TRUE) {
T_ReleaseTextureModelRelatedMemory();
C_ReleaseColorModelRelatedMemory();
g_bModelMemAllocated = FALSE;
}
- if (g_bNonModelMemAllocated == TRUE){
+ if (g_bNonModelMemAllocated == TRUE) {
cvReleaseImage(&g_ResizedFrame);
- for (int i = 0; i < g_iRHeight; i++){
+ for (int i = 0; i < g_iRHeight; i++) {
for (int j = 0; j < g_iRWidth; j++) free(g_aGaussFilteredFrame[i][j]);
free(g_aGaussFilteredFrame[i]);
}
free(g_aGaussFilteredFrame);
- for (int i = 0; i < g_iRHeight; i++){
+ for (int i = 0; i < g_iRHeight; i++) {
for (int j = 0; j < g_iRWidth; j++) free(g_aXYZFrame[i][j]);
free(g_aXYZFrame[i]);
}
@@ -256,7 +261,7 @@ void SJN_MultiCueBGS::Destroy()
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the preprocessing function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::PreProcessing(IplImage* frame){
+void MultiCue::PreProcessing(IplImage* frame) {
//image resize
ReduceImageSize(frame, g_ResizedFrame);
@@ -271,7 +276,7 @@ void SJN_MultiCueBGS::PreProcessing(IplImage* frame){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the background modeling function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::BackgroundModeling_Par(IplImage* frame){
+void MultiCue::BackgroundModeling_Par(IplImage* frame) {
//initialization
if (g_iFrameCount == 0) Initialize(frame);
@@ -285,8 +290,8 @@ void SJN_MultiCueBGS::BackgroundModeling_Par(IplImage* frame){
float fLearningRate = g_fLearningRate * 4;
//Step2: background modeling
- for (int i = iH_Start; i < iH_end; i++){
- for (int j = iW_Start; j < iW_end; j++){
+ for (int i = iH_Start; i < iH_end; i++) {
+ for (int j = iW_Start; j < iW_end; j++) {
point center;
center.m_nX = j;
center.m_nY = i;
@@ -297,9 +302,9 @@ void SJN_MultiCueBGS::BackgroundModeling_Par(IplImage* frame){
}
//Step3: Clear non-essential codewords
- if (g_iFrameCount == g_iTrainingPeriod){
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ if (g_iFrameCount == g_iTrainingPeriod) {
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
T_ClearNonEssentialEntries(g_iTrainingPeriod, g_TextureModel[i][j]);
C_ClearNonEssentialEntries(g_iTrainingPeriod, g_ColorModel[i][j]);
@@ -312,7 +317,7 @@ void SJN_MultiCueBGS::BackgroundModeling_Par(IplImage* frame){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the background subtraction function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::ForegroundExtraction(IplImage* frame){
+void MultiCue::ForegroundExtraction(IplImage* frame) {
//Step1:pre-processing
PreProcessing(frame);
@@ -332,9 +337,9 @@ void SJN_MultiCueBGS::ForegroundExtraction(IplImage* frame){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the post-processing function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::PostProcessing(IplImage* frame){
+void MultiCue::PostProcessing(IplImage* frame) {
- //Step1: morphological operation
+ //Step1: morphological operation
MorphologicalOpearions(g_aLandmarkArray, g_aResizedForeMap, 0.5, 5, g_iRWidth, g_iRHeight);
g_bForegroundMapEnable = TRUE;
@@ -361,20 +366,20 @@ void SJN_MultiCueBGS::PostProcessing(IplImage* frame){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the background-model update function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::UpdateModel_Par(){
+void MultiCue::UpdateModel_Par() {
short nNeighborNum = g_nNeighborNum;
//Step1: update map construction
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
g_aUpdateMap[i][j] = TRUE;
}
}
- for (int k = 0; k < g_BoundBoxInfo->m_iBoundBoxNum; k++){
- if (g_BoundBoxInfo->m_ValidBox[k] == TRUE){
- for (int i = g_BoundBoxInfo->m_aRUpper[k]; i <= g_BoundBoxInfo->m_aRBottom[k]; i++){
- for (int j = g_BoundBoxInfo->m_aRLeft[k]; j <= g_BoundBoxInfo->m_aRRight[k]; j++){
+ for (int k = 0; k < g_BoundBoxInfo->m_iBoundBoxNum; k++) {
+ if (g_BoundBoxInfo->m_ValidBox[k] == TRUE) {
+ for (int i = g_BoundBoxInfo->m_aRUpper[k]; i <= g_BoundBoxInfo->m_aRBottom[k]; i++) {
+ for (int j = g_BoundBoxInfo->m_aRLeft[k]; j <= g_BoundBoxInfo->m_aRRight[k]; j++) {
g_aUpdateMap[i][j] = FALSE;
}
}
@@ -387,16 +392,16 @@ void SJN_MultiCueBGS::UpdateModel_Par(){
float fLearningRate = (float)g_fLearningRate;
- for (int i = iH_Start; i < iH_End; i++){
- for (int j = iW_Start; j < iW_End; j++){
+ for (int i = iH_Start; i < iH_End; i++) {
+ for (int j = iW_Start; j < iW_End; j++) {
point center;
center.m_nX = j;
center.m_nY = i;
- if (g_aUpdateMap[i][j] == TRUE){
- //model update
+ if (g_aUpdateMap[i][j] == TRUE) {
+ //model update
T_ModelConstruction(g_nTextureTrainVolRange, fLearningRate, g_aXYZFrame, center, g_aNeighborDirection[i][j], g_TextureModel[i][j]);
C_CodebookConstruction(g_aXYZFrame[i][j], j, i, g_nColorTrainVolRange, fLearningRate, g_ColorModel[i][j]);
@@ -406,7 +411,7 @@ void SJN_MultiCueBGS::UpdateModel_Par(){
}
else {
- if (g_bAbsorptionEnable == TRUE){
+ if (g_bAbsorptionEnable == TRUE) {
//model update
T_ModelConstruction(g_nTextureTrainVolRange, fLearningRate, g_aXYZFrame, center, g_aNeighborDirection[i][j], g_TCacheBook[i][j]);
C_CodebookConstruction(g_aXYZFrame[i][j], j, i, g_nColorTrainVolRange, fLearningRate, g_CCacheBook[i][j]);
@@ -419,7 +424,7 @@ void SJN_MultiCueBGS::UpdateModel_Par(){
}
//clearing non-essential codewords for cache-books
- if (g_bAbsorptionEnable == TRUE){
+ if (g_bAbsorptionEnable == TRUE) {
T_ClearNonEssentialEntriesForCachebook(g_aLandmarkArray[i][j], g_aTReferredIndex[i][j], 10, g_TCacheBook[i][j]);
C_ClearNonEssentialEntriesForCachebook(g_aLandmarkArray[i][j], g_aCReferredIndex[i][j], 10, g_CCacheBook[i][j]);
}
@@ -431,16 +436,16 @@ void SJN_MultiCueBGS::UpdateModel_Par(){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the color based verification function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::CreateLandmarkArray_Par(float fConfThre, short nTrainVolRange, float**aConfMap, int iNehborNum, uchar*** aXYZ,
- point*** aNeiDir, TextureModel**** TModel, ColorModel*** CModel, uchar**aLandmarkArr){
+void MultiCue::CreateLandmarkArray_Par(float fConfThre, short nTrainVolRange, float**aConfMap, int iNehborNum, uchar*** aXYZ,
+ point*** aNeiDir, TextureModel**** TModel, ColorModel*** CModel, uchar**aLandmarkArr) {
int iBound_w = g_iRWidth - g_nRadius;
int iBound_h = g_iRHeight - g_nRadius;
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
- if (i < g_nRadius || i >= iBound_h || j<g_nRadius || j >= iBound_w) {
+ if (i < g_nRadius || i >= iBound_h || j < g_nRadius || j >= iBound_w) {
aLandmarkArr[i][j] = 0;
continue;
}
@@ -448,14 +453,14 @@ void SJN_MultiCueBGS::CreateLandmarkArray_Par(float fConfThre, short nTrainVolRa
double tmp = aConfMap[i][j];
if (tmp > fConfThre) aLandmarkArr[i][j] = 255;
- else{
+ else {
aLandmarkArr[i][j] = 0;
//Calculating texture amount in the background
double dBackAmt, dCnt;
dBackAmt = dCnt = 0;
- for (int m = 0; m < iNehborNum; m++){
- for (int n = 0; n < TModel[i][j][m]->m_iNumEntries; n++){
+ for (int m = 0; m < iNehborNum; m++) {
+ for (int n = 0; n < TModel[i][j][m]->m_iNumEntries; n++) {
dBackAmt += TModel[i][j][m]->m_Codewords[n]->m_fMean;
dCnt++;
}
@@ -464,7 +469,7 @@ void SJN_MultiCueBGS::CreateLandmarkArray_Par(float fConfThre, short nTrainVolRa
//Calculating texture amount in the input image
double dTemp, dInputAmt = 0;
- for (int m = 0; m < iNehborNum; m++){
+ for (int m = 0; m < iNehborNum; m++) {
dTemp = aXYZ[i][j][2] - aXYZ[aNeiDir[i][j][m].m_nY][aNeiDir[i][j][m].m_nX][2];
if (dTemp >= 0) dInputAmt += dTemp;
@@ -473,13 +478,13 @@ void SJN_MultiCueBGS::CreateLandmarkArray_Par(float fConfThre, short nTrainVolRa
}
//If there are only few textures in both background and input image
- if (dBackAmt < 50 && dInputAmt < 50){
+ if (dBackAmt < 50 && dInputAmt < 50) {
//Conduct color codebook matching
BOOL bMatched = FALSE;
- for (int m = 0; m < CModel[i][j]->m_iNumEntries; m++){
+ for (int m = 0; m < CModel[i][j]->m_iNumEntries; m++) {
int iMatchedCount = 0;
- for (int n = 0; n < 3; n++){
+ for (int n = 0; n < 3; n++) {
double dLowThre = CModel[i][j]->m_Codewords[m]->m_dMean[n] - nTrainVolRange - 10;
double dHighThre = CModel[i][j]->m_Codewords[m]->m_dMean[n] + nTrainVolRange + 10;
@@ -505,13 +510,13 @@ void SJN_MultiCueBGS::CreateLandmarkArray_Par(float fConfThre, short nTrainVolRa
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the Gaussian filtering function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::GaussianFiltering(IplImage* frame, uchar*** aFilteredFrame){
+void MultiCue::GaussianFiltering(IplImage* frame, uchar*** aFilteredFrame) {
double dSigma = 0.7;
- if (dSigma == 0){
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ if (dSigma == 0) {
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
aFilteredFrame[i][j][0] = frame->imageData[i*frame->widthStep + j * 3];
aFilteredFrame[i][j][1] = frame->imageData[i*frame->widthStep + j * 3 + 1];
aFilteredFrame[i][j][2] = frame->imageData[i*frame->widthStep + j * 3 + 2];
@@ -520,16 +525,16 @@ void SJN_MultiCueBGS::GaussianFiltering(IplImage* frame, uchar*** aFilteredFrame
}
else
{
- cv::Mat temp_img(frame, TRUE);
+ cv::Mat temp_img = cv::cvarrToMat(frame, TRUE);
cv::GaussianBlur(temp_img, temp_img, cv::Size(7, 7), dSigma);
//Store results into aFilteredFrame[][][]
//IplImage* img = &IplImage(temp_img);
IplImage* img = new IplImage(temp_img);
- int iWidthStep = img->widthStep;
+ //int iWidthStep = img->widthStep;
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
aFilteredFrame[i][j][0] = img->imageData[i*img->widthStep + j * 3];
aFilteredFrame[i][j][1] = img->imageData[i*img->widthStep + j * 3 + 1];
aFilteredFrame[i][j][2] = img->imageData[i*img->widthStep + j * 3 + 2];
@@ -542,7 +547,7 @@ void SJN_MultiCueBGS::GaussianFiltering(IplImage* frame, uchar*** aFilteredFrame
//------------------------------------------------------------------------------------------------------------------------------------//
// the image resize function //
//------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::ReduceImageSize(IplImage* SrcImage, IplImage* DstImage){
+void MultiCue::ReduceImageSize(IplImage* SrcImage, IplImage* DstImage) {
int iChannel = 3;
@@ -550,8 +555,8 @@ void SJN_MultiCueBGS::ReduceImageSize(IplImage* SrcImage, IplImage* DstImage){
double dResizeFactor_h = (double)g_iHeight / (double)g_iRHeight;
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
int iSrcY = (int)(i*dResizeFactor_h);
int iSrcX = (int)(j*dResizeFactor_w);
@@ -565,18 +570,18 @@ void SJN_MultiCueBGS::ReduceImageSize(IplImage* SrcImage, IplImage* DstImage){
//------------------------------------------------------------------------------------------------------------------------------------//
// the color space conversion function //
//------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::BGR2HSVxyz_Par(uchar*** aBGR, uchar*** aXYZ){
+void MultiCue::BGR2HSVxyz_Par(uchar*** aBGR, uchar*** aXYZ) {
double dH_ratio = (2 * PI) / 360;
- for (int i = 0; i < g_iRHeight; i++){
+ for (int i = 0; i < g_iRHeight; i++) {
double dR, dG, dB;
double dMax, dMin;
double dH, dS, dV;
- for (int j = 0; j < g_iRWidth; j++){
+ for (int j = 0; j < g_iRWidth; j++) {
dB = (double)(aBGR[i][j][0]) / 255;
dG = (double)(aBGR[i][j][1]) / 255;
@@ -593,13 +598,13 @@ void SJN_MultiCueBGS::BGR2HSVxyz_Par(uchar*** aBGR, uchar*** aXYZ){
//Get S, H
if (dV == 0) dS = dH = 0;
- else{
+ else {
//S value
dS = (dMax - dMin) / dMax;
if (dS == 0) dH = 0;
- else{
+ else {
//H value
if (dMax == dR) {
dH = 60 * (dG - dB) / dS;
@@ -622,7 +627,7 @@ void SJN_MultiCueBGS::BGR2HSVxyz_Par(uchar*** aBGR, uchar*** aXYZ){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function to get enlarged confidence map //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::GetEnlargedMap(float** aOriginMap, float** aEnlargedMap){
+void MultiCue::GetEnlargedMap(float** aOriginMap, float** aEnlargedMap) {
int i, j;
short nSrcX;
@@ -639,8 +644,8 @@ void SJN_MultiCueBGS::GetEnlargedMap(float** aOriginMap, float** aEnlargedMap){
double dScaleFactor_w = ((double)g_iWidth) / ((double)g_iRWidth);
double dScaleFactor_h = ((double)g_iHeight) / ((double)g_iRHeight);
- for (i = 0; i < g_iHeight; i++){
- for (j = 0; j < g_iWidth; j++){
+ for (i = 0; i < g_iHeight; i++) {
+ for (j = 0; j < g_iWidth; j++) {
//backward mapping
nSrcY = (int)(i / dScaleFactor_h);
nSrcX = (int)(j / dScaleFactor_w);
@@ -668,7 +673,7 @@ void SJN_MultiCueBGS::GetEnlargedMap(float** aOriginMap, float** aEnlargedMap){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the morphological operation function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::MorphologicalOpearions(uchar** aInput, uchar** aOutput, double dThresholdRatio, int iMaskSize, int iWidth, int iHeight){
+void MultiCue::MorphologicalOpearions(uchar** aInput, uchar** aOutput, double dThresholdRatio, int iMaskSize, int iWidth, int iHeight) {
int iOffset = (int)(iMaskSize / 2);
@@ -676,28 +681,28 @@ void SJN_MultiCueBGS::MorphologicalOpearions(uchar** aInput, uchar** aOutput, do
int iBound_h = iHeight - iOffset;
uchar** aTemp = (uchar**)malloc(sizeof(uchar*)*iHeight);
- for (int i = 0; i < iHeight; i++){
+ for (int i = 0; i < iHeight; i++) {
aTemp[i] = (uchar*)malloc(sizeof(uchar)*iWidth);
}
- for (int i = 0; i < iHeight; i++){
- for (int j = 0; j < iWidth; j++){
+ for (int i = 0; i < iHeight; i++) {
+ for (int j = 0; j < iWidth; j++) {
aTemp[i][j] = aInput[i][j];
}
}
int iThreshold = (int)(iMaskSize*iMaskSize*dThresholdRatio);
- for (int i = 0; i < iHeight; i++){
- for (int j = 0; j < iWidth; j++){
+ for (int i = 0; i < iHeight; i++) {
+ for (int j = 0; j < iWidth; j++) {
- if (i < iOffset || i >= iBound_h || j < iOffset || j >= iBound_w){
+ if (i < iOffset || i >= iBound_h || j < iOffset || j >= iBound_w) {
aOutput[i][j] = 0;
continue;
}
int iCnt = 0;
- for (int m = -iOffset; m <= iOffset; m++){
- for (int n = -iOffset; n <= iOffset; n++){
+ for (int m = -iOffset; m <= iOffset; m++) {
+ for (int n = -iOffset; n <= iOffset; n++) {
if (aTemp[i + m][j + n] == 255) iCnt++;
}
}
@@ -708,7 +713,7 @@ void SJN_MultiCueBGS::MorphologicalOpearions(uchar** aInput, uchar** aOutput, do
}
- for (int i = 0; i < iHeight; i++){
+ for (int i = 0; i < iHeight; i++) {
free(aTemp[i]);
}
free(aTemp);
@@ -717,7 +722,7 @@ void SJN_MultiCueBGS::MorphologicalOpearions(uchar** aInput, uchar** aOutput, do
//-----------------------------------------------------------------------------------------------------------------------------------------//
// 2-raster scan pass based labeling function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLabelTable){
+void MultiCue::Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLabelTable) {
int x, y, i; // pass 1,2
int cnt = 0; // pass 1
int label = 0; // pass 2
@@ -730,45 +735,45 @@ void SJN_MultiCueBGS::Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLa
int* aTable1 = (int*)malloc(iSize / 2 * sizeof(int));
int* aTable2 = (int*)malloc(iSize / 2 * sizeof(int));
- memset(aPass1, 0, (iSize)* sizeof(int));
- for (y = 1; y < (g_iRHeight); y++){
- for (x = 1; x < (g_iRWidth); x++){
+ memset(aPass1, 0, (iSize) * sizeof(int));
+ for (y = 1; y < (g_iRHeight); y++) {
+ for (x = 1; x < (g_iRWidth); x++) {
aLabelTable[y][x] = 0;
}
}
- for (i = 0; i < iTableSize; i++){
+ for (i = 0; i < iTableSize; i++) {
aTable1[i] = i;
}
memset(aTable2, 0, iTableSize * sizeof(int));
// pass 1
- for (y = 1; y < (g_iRHeight); y++){
- for (x = 1; x < (g_iRWidth); x++){
+ for (y = 1; y < (g_iRHeight); y++) {
+ for (x = 1; x < (g_iRWidth); x++) {
- if (aBinaryArray[y][x] == 255){ // fore ground??
+ if (aBinaryArray[y][x] == 255) { // fore ground??
int up, le;
up = aPass1[(y - 1)*(g_iRWidth)+(x)]; // up index
le = aPass1[(y)*(g_iRWidth)+(x - 1)]; // left index
// case
- if (up == 0 && le == 0){
+ if (up == 0 && le == 0) {
++cnt;
aPass1[y * g_iRWidth + x] = cnt;
}
- else if (up != 0 && le != 0){
- if (up > le){
+ else if (up != 0 && le != 0) {
+ if (up > le) {
aPass1[y *g_iRWidth + x] = le;
aTable1[up] = aTable1[le]; // update table1 table1
}
- else{
+ else {
aPass1[y * g_iRWidth + x] = up;
aTable1[le] = aTable1[up]; // update table1 table1
}
}
- else{
+ else {
aPass1[y * g_iRWidth + x] = up + le;
}
@@ -778,13 +783,13 @@ void SJN_MultiCueBGS::Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLa
}
// pass 2
- for (y = 1; y < (g_iRHeight); y++){
- for (x = 1; x < (g_iRWidth); x++){
+ for (y = 1; y < (g_iRHeight); y++) {
+ for (x = 1; x < (g_iRWidth); x++) {
- if (aPass1[y * g_iRWidth + x]){
+ if (aPass1[y * g_iRWidth + x]) {
int v = aTable1[aPass1[y * g_iRWidth + x]];
- if (aTable2[v] == 0){
+ if (aTable2[v] == 0) {
++label;
aTable2[v] = label;
}
@@ -804,12 +809,12 @@ void SJN_MultiCueBGS::Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLa
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function to set bounding boxes for each candidate foreground regions // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::SetBoundingBox(int iLabelCount, int** aLabelTable){
+void MultiCue::SetBoundingBox(int iLabelCount, int** aLabelTable) {
int iBoundBoxIndex;
g_BoundBoxInfo->m_iBoundBoxNum = iLabelCount;
- for (int i = 0; i < g_BoundBoxInfo->m_iBoundBoxNum; i++){
+ for (int i = 0; i < g_BoundBoxInfo->m_iBoundBoxNum; i++) {
g_BoundBoxInfo->m_aRLeft[i] = 9999; //left
g_BoundBoxInfo->m_aRUpper[i] = 9999; //top
g_BoundBoxInfo->m_aRRight[i] = 0; //right
@@ -817,8 +822,8 @@ void SJN_MultiCueBGS::SetBoundingBox(int iLabelCount, int** aLabelTable){
}
//Step1: Set tight bounding boxes
- for (int i = 1; i<g_iRHeight; i++){
- for (int j = 1; j<g_iRWidth; j++){
+ for (int i = 1; i < g_iRHeight; i++) {
+ for (int j = 1; j < g_iRWidth; j++) {
if ((aLabelTable[i][j] == 0)) continue;
@@ -835,7 +840,7 @@ void SJN_MultiCueBGS::SetBoundingBox(int iLabelCount, int** aLabelTable){
//Step2: Add margins.
int iBoundary_w = (int)(g_iRWidth / 80), iBoundary_h = (int)(g_iRHeight / 60);
- for (int i = 0; i < g_BoundBoxInfo->m_iBoundBoxNum; i++){
+ for (int i = 0; i < g_BoundBoxInfo->m_iBoundBoxNum; i++) {
g_BoundBoxInfo->m_aRLeft[i] -= iBoundary_w;
if (g_BoundBoxInfo->m_aRLeft[i] < g_nRadius) g_BoundBoxInfo->m_aRLeft[i] = g_nRadius; //left
@@ -853,7 +858,7 @@ void SJN_MultiCueBGS::SetBoundingBox(int iLabelCount, int** aLabelTable){
double dH_ratio = (double)g_iHeight / (double)g_iRHeight;
double dW_ratio = (double)g_iWidth / (double)g_iRWidth;
- for (int i = 0; i < g_BoundBoxInfo->m_iBoundBoxNum; i++){
+ for (int i = 0; i < g_BoundBoxInfo->m_iBoundBoxNum; i++) {
g_BoundBoxInfo->m_aLeft[i] = (int)(g_BoundBoxInfo->m_aRLeft[i] * dW_ratio);
g_BoundBoxInfo->m_aUpper[i] = (int)(g_BoundBoxInfo->m_aRUpper[i] * dH_ratio);
g_BoundBoxInfo->m_aRight[i] = (int)(g_BoundBoxInfo->m_aRRight[i] * dW_ratio);
@@ -865,7 +870,7 @@ void SJN_MultiCueBGS::SetBoundingBox(int iLabelCount, int** aLabelTable){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the box verification function // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::BoundBoxVerification(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo){
+void MultiCue::BoundBoxVerification(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo) {
//Step1: Verification by the bounding box size
EvaluateBoxSize(BoundBoxInfo);
@@ -875,7 +880,7 @@ void SJN_MultiCueBGS::BoundBoxVerification(IplImage* frame, uchar** aResForeMap,
//Step3: Counting the # of valid box
g_iForegroundNum = 0;
- for (int i = 0; i < BoundBoxInfo->m_iBoundBoxNum; i++){
+ for (int i = 0; i < BoundBoxInfo->m_iBoundBoxNum; i++) {
if (BoundBoxInfo->m_ValidBox[i] == TRUE) g_iForegroundNum++;
}
}
@@ -883,7 +888,7 @@ void SJN_MultiCueBGS::BoundBoxVerification(IplImage* frame, uchar** aResForeMap,
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the size based verification // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::EvaluateBoxSize(BoundingBoxInfo* BoundBoxInfo){
+void MultiCue::EvaluateBoxSize(BoundingBoxInfo* BoundBoxInfo) {
//Set thresholds
int iLowThreshold_w, iHighThreshold_w;
@@ -897,7 +902,7 @@ void SJN_MultiCueBGS::EvaluateBoxSize(BoundingBoxInfo* BoundBoxInfo){
int iBoxWidth, iBoxHeight;
//Perform verification.
- for (int i = 0; i < BoundBoxInfo->m_iBoundBoxNum; i++){
+ for (int i = 0; i < BoundBoxInfo->m_iBoundBoxNum; i++) {
iBoxWidth = BoundBoxInfo->m_aRRight[i] - BoundBoxInfo->m_aRLeft[i];
iBoxHeight = BoundBoxInfo->m_aRBottom[i] - BoundBoxInfo->m_aRUpper[i];
@@ -912,7 +917,7 @@ void SJN_MultiCueBGS::EvaluateBoxSize(BoundingBoxInfo* BoundBoxInfo){
//------------------------------------------------------------------------------------------------------------------------------------//
// overlapped region removal //
//------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo){
+void MultiCue::EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo) {
BOOL *aValidBoxFlag = new BOOL[SrcBoxInfo->m_iBoundBoxNum];
for (int i = 0; i < SrcBoxInfo->m_iBoundBoxNum; i++) aValidBoxFlag[i] = TRUE;
@@ -924,7 +929,7 @@ void SJN_MultiCueBGS::EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo){
int iThreshold, iCount, iSmall_Idx, iLarge_Idx;
double dThreRatio = 0.7;
- for (int i = 0; i < SrcBoxInfo->m_iBoundBoxNum; i++){
+ for (int i = 0; i < SrcBoxInfo->m_iBoundBoxNum; i++) {
if (SrcBoxInfo->m_ValidBox[i] == FALSE) {
aValidBoxFlag[i] = FALSE;
@@ -933,7 +938,7 @@ void SJN_MultiCueBGS::EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo){
size1 = (aRight[i] - aLeft[i]) * (aBottom[i] - aTop[i]);
- for (int j = i; j < SrcBoxInfo->m_iBoundBoxNum; j++){
+ for (int j = i; j < SrcBoxInfo->m_iBoundBoxNum; j++) {
if ((i == j) || (SrcBoxInfo->m_ValidBox[j] == FALSE)) continue;
//Setting threshold for checking overlapped region size
@@ -950,8 +955,8 @@ void SJN_MultiCueBGS::EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo){
//Calculating overlapped region size
iCount = 0;
- for (int m = aLeft[iSmall_Idx]; m < aRight[iSmall_Idx]; m++){
- for (int n = aTop[iSmall_Idx]; n<aBottom[iSmall_Idx]; n++){
+ for (int m = aLeft[iSmall_Idx]; m < aRight[iSmall_Idx]; m++) {
+ for (int n = aTop[iSmall_Idx]; n < aBottom[iSmall_Idx]; n++) {
if (aLeft[iLarge_Idx] <= m && m <= aRight[iLarge_Idx] && aTop[iLarge_Idx] <= n && n <= aBottom[iLarge_Idx]) iCount++;
}
}
@@ -968,20 +973,20 @@ void SJN_MultiCueBGS::EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// appearance based verification // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo){
+void MultiCue::EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo) {
double dThreshold = 10;
BOOL** aUpdateMap = (BOOL**)malloc(sizeof(BOOL*)*g_iRHeight);
- for (int i = 0; i < g_iRHeight; i++){
+ for (int i = 0; i < g_iRHeight; i++) {
aUpdateMap[i] = (BOOL*)malloc(sizeof(BOOL)*g_iRWidth);
for (int j = 0; j < g_iRWidth; j++) aUpdateMap[i][j] = FALSE;
}
//Step1: Conduct fore-region evaluation to identify ghost regions
- for (int i = 0; i < BoundBoxInfo->m_iBoundBoxNum; i++){
- if (BoundBoxInfo->m_ValidBox[i] == TRUE){
+ for (int i = 0; i < BoundBoxInfo->m_iBoundBoxNum; i++) {
+ if (BoundBoxInfo->m_ValidBox[i] == TRUE) {
int iWin_w = BoundBoxInfo->m_aRRight[i] - BoundBoxInfo->m_aRLeft[i];
int iWin_h = BoundBoxInfo->m_aRBottom[i] - BoundBoxInfo->m_aRUpper[i];
@@ -999,8 +1004,8 @@ void SJN_MultiCueBGS::EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap,
//Generating edge image from aResForeMap
IplImage* edge_fore = cvCreateImage(cvSize(iWin_w, iWin_h), IPL_DEPTH_8U, 1);
- for (int m = BoundBoxInfo->m_aRUpper[i]; m < BoundBoxInfo->m_aRBottom[i]; m++){
- for (int n = BoundBoxInfo->m_aRLeft[i]; n<BoundBoxInfo->m_aRRight[i]; n++){
+ for (int m = BoundBoxInfo->m_aRUpper[i]; m < BoundBoxInfo->m_aRBottom[i]; m++) {
+ for (int n = BoundBoxInfo->m_aRLeft[i]; n < BoundBoxInfo->m_aRRight[i]; n++) {
edge_fore->imageData[(m - BoundBoxInfo->m_aRUpper[i])*edge_fore->widthStep + (n - BoundBoxInfo->m_aRLeft[i])] = (char)aResForeMap[m][n];
}
}
@@ -1011,8 +1016,8 @@ void SJN_MultiCueBGS::EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap,
//Recording evaluation result
if (distance > dThreshold) {
- for (int m = BoundBoxInfo->m_aRUpper[i]; m < BoundBoxInfo->m_aRBottom[i]; m++){
- for (int n = BoundBoxInfo->m_aRLeft[i]; n < BoundBoxInfo->m_aRRight[i]; n++){
+ for (int m = BoundBoxInfo->m_aRUpper[i]; m < BoundBoxInfo->m_aRBottom[i]; m++) {
+ for (int n = BoundBoxInfo->m_aRLeft[i]; n < BoundBoxInfo->m_aRRight[i]; n++) {
aUpdateMap[m][n] = TRUE;
}
}
@@ -1029,9 +1034,9 @@ void SJN_MultiCueBGS::EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap,
//Step2: Adding information fo ghost region pixels to background model
float fLearningRate = g_fLearningRate;
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
- if (aUpdateMap[i][j] == TRUE){
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
+ if (aUpdateMap[i][j] == TRUE) {
point center;
center.m_nX = j; center.m_nY = i;
@@ -1053,16 +1058,16 @@ void SJN_MultiCueBGS::EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap,
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function to calculate partial undirected Hausdorff distance(forward distance) // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-double SJN_MultiCueBGS::CalculateHausdorffDist(IplImage* input_image, IplImage* model_image){
+double MultiCue::CalculateHausdorffDist(IplImage* input_image, IplImage* model_image) {
//Step1: Generating imag vectors
//For reduce errors, points at the image boundary are excluded
- vector<point> vInput, vModel;
+ std::vector<point> vInput, vModel;
point temp;
- //input image --> input vector
- for (int i = 0; i < input_image->height; i++){
- for (int j = 0; j < input_image->width; j++){
+ //input image --> input vector
+ for (int i = 0; i < input_image->height; i++) {
+ for (int j = 0; j < input_image->width; j++) {
if ((uchar)input_image->imageData[i*input_image->widthStep + j] == 0) continue;
@@ -1071,8 +1076,8 @@ double SJN_MultiCueBGS::CalculateHausdorffDist(IplImage* input_image, IplImage*
}
}
//model image --> model vector
- for (int i = 0; i < model_image->height; i++){
- for (int j = 0; j < model_image->width; j++){
+ for (int i = 0; i < model_image->height; i++) {
+ for (int j = 0; j < model_image->width; j++) {
if ((uchar)model_image->imageData[i*model_image->widthStep + j] == 0) continue;
temp.m_nX = j; temp.m_nY = i;
@@ -1086,12 +1091,12 @@ double SJN_MultiCueBGS::CalculateHausdorffDist(IplImage* input_image, IplImage*
//Step2: Calculating forward distance h(Model,Image)
double dDist, temp1, temp2, dMinDist;
- vector<double> vTempDist;
+ std::vector<double> vTempDist;
- for (auto iter_m = vModel.begin(); iter_m < vModel.end(); iter_m++){
+ for (auto iter_m = vModel.begin(); iter_m < vModel.end(); iter_m++) {
dMinDist = 9999999;
- for (auto iter_i = vInput.begin(); iter_i < vInput.end(); iter_i++){
+ for (auto iter_i = vInput.begin(); iter_i < vInput.end(); iter_i++) {
temp1 = (*iter_m).m_nX - (*iter_i).m_nX;
temp2 = (*iter_m).m_nY - (*iter_i).m_nY;
dDist = temp1*temp1 + temp2*temp2;
@@ -1114,15 +1119,15 @@ double SJN_MultiCueBGS::CalculateHausdorffDist(IplImage* input_image, IplImage*
//-----------------------------------------------------------------------------------------------------------------------------------------//
// function to remove non-valid bounding boxes fore fore-candidates //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::RemovingInvalidForeRegions(uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo){
+void MultiCue::RemovingInvalidForeRegions(uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo) {
int iBoxNum = BoundBoxInfo->m_iBoundBoxNum;
- for (int k = 0; k < iBoxNum; k++){
+ for (int k = 0; k < iBoxNum; k++) {
- if (BoundBoxInfo->m_ValidBox[k] == FALSE){
- for (int i = BoundBoxInfo->m_aRUpper[k]; i < BoundBoxInfo->m_aRBottom[k]; i++){
- for (int j = BoundBoxInfo->m_aRLeft[k]; j < BoundBoxInfo->m_aRRight[k]; j++){
+ if (BoundBoxInfo->m_ValidBox[k] == FALSE) {
+ for (int i = BoundBoxInfo->m_aRUpper[k]; i < BoundBoxInfo->m_aRBottom[k]; i++) {
+ for (int j = BoundBoxInfo->m_aRLeft[k]; j < BoundBoxInfo->m_aRRight[k]; j++) {
if (aResForeMap[i][j] == 255) aResForeMap[i][j] = 0;
}
}
@@ -1134,15 +1139,15 @@ void SJN_MultiCueBGS::RemovingInvalidForeRegions(uchar** aResForeMap, BoundingBo
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function returning a foreground binary-map //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::GetForegroundMap(IplImage* return_image, IplImage* input_frame){
+void MultiCue::GetForegroundMap(IplImage* return_image, IplImage* input_frame) {
if (g_bForegroundMapEnable == FALSE) return;
IplImage* temp_image = cvCreateImage(cvSize(g_iRWidth, g_iRHeight), IPL_DEPTH_8U, 3);
- if (input_frame == NULL){
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ if (input_frame == NULL) {
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
temp_image->imageData[i*temp_image->widthStep + j * 3] = (char)g_aResizedForeMap[i][j];
temp_image->imageData[i*temp_image->widthStep + j * 3 + 1] = (char)g_aResizedForeMap[i][j];
temp_image->imageData[i*temp_image->widthStep + j * 3 + 2] = (char)g_aResizedForeMap[i][j];
@@ -1150,7 +1155,7 @@ void SJN_MultiCueBGS::GetForegroundMap(IplImage* return_image, IplImage* input_f
}
}
- else{
+ else {
cvResize(input_frame, temp_image);
CvScalar MixColor;
@@ -1158,8 +1163,8 @@ void SJN_MultiCueBGS::GetForegroundMap(IplImage* return_image, IplImage* input_f
MixColor.val[1] = 0; //G
MixColor.val[2] = 255; //R
- for (int i = 0; i < g_iRHeight; i++){
- for (int j = 0; j < g_iRWidth; j++){
+ for (int i = 0; i < g_iRHeight; i++) {
+ for (int j = 0; j < g_iRWidth; j++) {
if (g_aResizedForeMap[i][j] == 255) {
@@ -1187,15 +1192,15 @@ void SJN_MultiCueBGS::GetForegroundMap(IplImage* return_image, IplImage* input_f
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the initialization function for the texture-models //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_AllocateTextureModelRelatedMemory(){
+void MultiCue::T_AllocateTextureModelRelatedMemory() {
int i, j, k;
//neighborhood system related
int iMaxNeighborArraySize = 8;
g_aNeighborDirection = (point***)malloc(sizeof(point**)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_aNeighborDirection[i] = (point**)malloc(sizeof(point*)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++){
+ for (j = 0; j < g_iRWidth; j++) {
g_aNeighborDirection[i][j] = (point*)malloc(sizeof(point)*iMaxNeighborArraySize);
}
}
@@ -1204,11 +1209,11 @@ void SJN_MultiCueBGS::T_AllocateTextureModelRelatedMemory(){
//texture-model related
int iElementArraySize = 6;
g_TextureModel = (TextureModel****)malloc(sizeof(TextureModel***)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_TextureModel[i] = (TextureModel***)malloc(sizeof(TextureModel**)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++){
+ for (j = 0; j < g_iRWidth; j++) {
g_TextureModel[i][j] = (TextureModel**)malloc(sizeof(TextureModel*)*g_nNeighborNum);
- for (k = 0; k < g_nNeighborNum; k++){
+ for (k = 0; k < g_nNeighborNum; k++) {
g_TextureModel[i][j][k] = (TextureModel*)malloc(sizeof(TextureModel));
g_TextureModel[i][j][k]->m_Codewords = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*iElementArraySize);
g_TextureModel[i][j][k]->m_iElementArraySize = iElementArraySize;
@@ -1223,16 +1228,16 @@ void SJN_MultiCueBGS::T_AllocateTextureModelRelatedMemory(){
for (i = 0; i < g_iRHeight; i++) g_aTextureConfMap[i] = (float*)malloc(sizeof(float)*g_iRWidth);
//cache-book related
- if (g_bAbsorptionEnable == TRUE){
+ if (g_bAbsorptionEnable == TRUE) {
iElementArraySize = iElementArraySize / 2;
if (iElementArraySize < 3)iElementArraySize = 3;
g_TCacheBook = (TextureModel****)malloc(sizeof(TextureModel***)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_TCacheBook[i] = (TextureModel***)malloc(sizeof(TextureModel**)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++){
+ for (j = 0; j < g_iRWidth; j++) {
g_TCacheBook[i][j] = (TextureModel**)malloc(sizeof(TextureModel*)*g_nNeighborNum);
- for (k = 0; k < g_nNeighborNum; k++){
+ for (k = 0; k < g_nNeighborNum; k++) {
g_TCacheBook[i][j][k] = (TextureModel*)malloc(sizeof(TextureModel));
g_TCacheBook[i][j][k]->m_Codewords = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*iElementArraySize);
g_TCacheBook[i][j][k]->m_iElementArraySize = iElementArraySize;
@@ -1245,13 +1250,13 @@ void SJN_MultiCueBGS::T_AllocateTextureModelRelatedMemory(){
g_aTReferredIndex = (short***)malloc(sizeof(short**)*g_iRHeight);
g_aTContinuousCnt = (short***)malloc(sizeof(short**)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_aTReferredIndex[i] = (short**)malloc(sizeof(short*)*g_iRWidth);
g_aTContinuousCnt[i] = (short**)malloc(sizeof(short*)*g_iRWidth);
for (j = 0; j < g_iRWidth; j++) {
g_aTReferredIndex[i][j] = (short*)malloc(sizeof(short)*g_nNeighborNum);
g_aTContinuousCnt[i][j] = (short*)malloc(sizeof(short)*g_nNeighborNum);
- for (k = 0; k < g_nNeighborNum; k++){
+ for (k = 0; k < g_nNeighborNum; k++) {
g_aTReferredIndex[i][j][k] = -1;
g_aTContinuousCnt[i][j][k] = 0;
}
@@ -1262,13 +1267,13 @@ void SJN_MultiCueBGS::T_AllocateTextureModelRelatedMemory(){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the memory release function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_ReleaseTextureModelRelatedMemory(){
+void MultiCue::T_ReleaseTextureModelRelatedMemory() {
int i, j, k, m;
short nNeighborNum = g_nNeighborNum;
- for (i = 0; i < g_iRHeight; i++){
- for (j = 0; j < g_iRWidth; j++){
- for (k = 0; k < nNeighborNum; k++){
+ for (i = 0; i < g_iRHeight; i++) {
+ for (j = 0; j < g_iRWidth; j++) {
+ for (k = 0; k < nNeighborNum; k++) {
for (m = 0; m < g_TextureModel[i][j][k]->m_iNumEntries; m++) free(g_TextureModel[i][j][k]->m_Codewords[m]);
free(g_TextureModel[i][j][k]->m_Codewords);
free(g_TextureModel[i][j][k]);
@@ -1278,7 +1283,7 @@ void SJN_MultiCueBGS::T_ReleaseTextureModelRelatedMemory(){
}
free(g_TextureModel);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
for (j = 0; j < g_iRWidth; j++) free(g_aNeighborDirection[i][j]);
free(g_aNeighborDirection[i]);
}
@@ -1287,10 +1292,10 @@ void SJN_MultiCueBGS::T_ReleaseTextureModelRelatedMemory(){
for (i = 0; i < g_iRHeight; i++) free(g_aTextureConfMap[i]);
free(g_aTextureConfMap);
- if (g_bAbsorptionEnable == TRUE){
- for (i = 0; i < g_iRHeight; i++){
- for (j = 0; j < g_iRWidth; j++){
- for (k = 0; k < nNeighborNum; k++){
+ if (g_bAbsorptionEnable == TRUE) {
+ for (i = 0; i < g_iRHeight; i++) {
+ for (j = 0; j < g_iRWidth; j++) {
+ for (k = 0; k < nNeighborNum; k++) {
for (m = 0; m < g_TCacheBook[i][j][k]->m_iNumEntries; m++) free(g_TCacheBook[i][j][k]->m_Codewords[m]);
free(g_TCacheBook[i][j][k]->m_Codewords);
free(g_TCacheBook[i][j][k]);
@@ -1300,8 +1305,8 @@ void SJN_MultiCueBGS::T_ReleaseTextureModelRelatedMemory(){
}
free(g_TCacheBook);
- for (i = 0; i < g_iRHeight; i++){
- for (j = 0; j < g_iRWidth; j++){
+ for (i = 0; i < g_iRHeight; i++) {
+ for (j = 0; j < g_iRWidth; j++) {
free(g_aTReferredIndex[i][j]);
free(g_aTContinuousCnt[i][j]);
}
@@ -1317,7 +1322,7 @@ void SJN_MultiCueBGS::T_ReleaseTextureModelRelatedMemory(){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the codebook construction function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningRate, uchar*** aXYZ, point center, point* aNei, TextureModel** aModel){
+void MultiCue::T_ModelConstruction(short nTrainVolRange, float fLearningRate, uchar*** aXYZ, point center, point* aNei, TextureModel** aModel) {
int i, j;
int iMatchedIndex;
@@ -1329,15 +1334,15 @@ void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningR
float fNegLearningRate = 1 - fLearningRate;
- //for all neighboring pairs
- for (i = 0; i < nNeighborNum; i++){
+ //for all neighboring pairs
+ for (i = 0; i < nNeighborNum; i++) {
fDifference = (float)(aXYZ[center.m_nY][center.m_nX][2] - aXYZ[aNei[i].m_nY][aNei[i].m_nX][2]);
//Step1: matching
iMatchedIndex = -1;
- for (j = 0; j < aModel[i]->m_iNumEntries; j++){
- if (aModel[i]->m_Codewords[j]->m_fLowThre <= fDifference && fDifference <= aModel[i]->m_Codewords[j]->m_fHighThre){
+ for (j = 0; j < aModel[i]->m_iNumEntries; j++) {
+ if (aModel[i]->m_Codewords[j]->m_fLowThre <= fDifference && fDifference <= aModel[i]->m_Codewords[j]->m_fHighThre) {
iMatchedIndex = j;
break;
}
@@ -1345,12 +1350,12 @@ void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningR
aModel[i]->m_iTotal++;
//Step2: adding a new element
- if (iMatchedIndex == -1){
+ if (iMatchedIndex == -1) {
//element array
- if (aModel[i]->m_iElementArraySize == aModel[i]->m_iNumEntries){
+ if (aModel[i]->m_iElementArraySize == aModel[i]->m_iNumEntries) {
aModel[i]->m_iElementArraySize += 5;
TextureCodeword **temp = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*aModel[i]->m_iElementArraySize);
- for (j = 0; j < aModel[i]->m_iNumEntries; j++){
+ for (j = 0; j < aModel[i]->m_iNumEntries; j++) {
temp[j] = aModel[i]->m_Codewords[j];
aModel[i]->m_Codewords[j] = NULL;
}
@@ -1370,7 +1375,7 @@ void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningR
}
//Step3: update
- else{
+ else {
fDiffMean = aModel[i]->m_Codewords[iMatchedIndex]->m_fMean;
aModel[i]->m_Codewords[iMatchedIndex]->m_fMean = fLearningRate*fDifference + fNegLearningRate*fDiffMean;
@@ -1381,10 +1386,10 @@ void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningR
}
//cache-book handling
- if (aModel[i]->m_bID == 1){
+ if (aModel[i]->m_bID == 1) {
//1. m_iMNRL update
int negTime;
- for (j = 0; j < aModel[i]->m_iNumEntries; j++){
+ for (j = 0; j < aModel[i]->m_iNumEntries; j++) {
//m_iMNRL update
negTime = aModel[i]->m_iTotal - aModel[i]->m_Codewords[j]->m_iT_last_time + aModel[i]->m_Codewords[j]->m_iT_first_time - 1;
if (aModel[i]->m_Codewords[j]->m_iMNRL < negTime) aModel[i]->m_Codewords[j]->m_iMNRL = negTime;
@@ -1395,18 +1400,18 @@ void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningR
if (g_bAbsorptionEnable == TRUE) g_aTReferredIndex[center.m_nY][center.m_nX][i] = -1;
}
- else{
+ else {
//1. m_iMNRL update
if (iMatchedIndex == -1) aModel[i]->m_Codewords[aModel[i]->m_iNumEntries - 1]->m_iMNRL = 0;
//2. g_aTReferredIndex[center.m_nY][center.m_nX][i] update
- if (iMatchedIndex == -1){
+ if (iMatchedIndex == -1) {
g_aTReferredIndex[center.m_nY][center.m_nX][i] = aModel[i]->m_iNumEntries - 1;
g_aTContinuousCnt[center.m_nY][center.m_nX][i] = 1;
}
- else{
+ else {
if (iMatchedIndex == g_aTReferredIndex[center.m_nY][center.m_nX][i]) g_aTContinuousCnt[center.m_nY][center.m_nX][i]++;
- else{
+ else {
g_aTReferredIndex[center.m_nY][center.m_nX][i] = iMatchedIndex;
g_aTContinuousCnt[center.m_nY][center.m_nX][i] = 1;
}
@@ -1420,7 +1425,7 @@ void SJN_MultiCueBGS::T_ModelConstruction(short nTrainVolRange, float fLearningR
//-----------------------------------------------------------------------------------------------------------------------------------------//
// Clear non-essential codewords of the given codebook // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_ClearNonEssentialEntries(short nClearNum, TextureModel** aModel){
+void MultiCue::T_ClearNonEssentialEntries(short nClearNum, TextureModel** aModel) {
int i, n;
int iStaleThresh = (int)(nClearNum*0.5);
int iKeepCnt;
@@ -1430,7 +1435,7 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntries(short nClearNum, TextureModel**
TextureModel* c;
- for (n = 0; n < nNeighborNum; n++){
+ for (n = 0; n < nNeighborNum; n++) {
c = aModel[n];
if (c->m_iTotal < nClearNum) continue; //(being operated only when c[w][h]->m_iTotal == nClearNum)
@@ -1441,7 +1446,7 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntries(short nClearNum, TextureModel**
iKeepCnt = 0;
//Step2: Find non-essential code-words
- for (i = 0; i<c->m_iNumEntries; i++){
+ for (i = 0; i < c->m_iNumEntries; i++) {
if (c->m_Codewords[i]->m_iMNRL > iStaleThresh) {
aKeep[i] = 0; //removal candidate
}
@@ -1452,20 +1457,20 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntries(short nClearNum, TextureModel**
}
//Step3: Perform removal
- if (iKeepCnt == 0 || iKeepCnt == c->m_iNumEntries){
- for (i = 0; i < c->m_iNumEntries; i++){
+ if (iKeepCnt == 0 || iKeepCnt == c->m_iNumEntries) {
+ for (i = 0; i < c->m_iNumEntries; i++) {
c->m_Codewords[i]->m_iT_first_time = 1;
c->m_Codewords[i]->m_iT_last_time = 1;
c->m_Codewords[i]->m_iMNRL = 0;
}
}
- else{
+ else {
iKeepCnt = 0;
TextureCodeword** temp = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*c->m_iNumEntries);
- for (i = 0; i < c->m_iNumEntries; i++){
- if (aKeep[i] == 1){
+ for (i = 0; i < c->m_iNumEntries; i++) {
+ if (aKeep[i] == 1) {
temp[iKeepCnt] = c->m_Codewords[i];
temp[iKeepCnt]->m_iT_first_time = 1;
temp[iKeepCnt]->m_iT_last_time = 1;
@@ -1491,21 +1496,21 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntries(short nClearNum, TextureModel**
//-----------------------------------------------------------------------------------------------------------------------------------------//
// Clear non-essential codewords of the given codebook (only for the cache-book) //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short* nReferredIdxArr, short nClearNum, TextureModel** pCachebook){
+void MultiCue::T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short* nReferredIdxArr, short nClearNum, TextureModel** pCachebook) {
int i, n;
short nNeighborNum = g_nNeighborNum;
TextureModel* c;
short nReferredIdx;
- for (n = 0; n < nNeighborNum; n++){
+ for (n = 0; n < nNeighborNum; n++) {
c = pCachebook[n];
nReferredIdx = nReferredIdxArr[n];
//pCachebook->m_iTotal < nClearNum? --> MNRL update
if (c->m_iTotal < nClearNum) {
- for (i = 0; i < c->m_iNumEntries; i++){
+ for (i = 0; i < c->m_iNumEntries; i++) {
if (bLandmark == 255 && i == nReferredIdx) c->m_Codewords[i]->m_iMNRL = 0;
else c->m_Codewords[i]->m_iMNRL++;
}
@@ -1514,7 +1519,7 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
}
//Perform clearing
- else{
+ else {
int iStaleThreshold = 5;
int* aKeep;
@@ -1523,8 +1528,8 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
aKeep = (int*)malloc(sizeof(int)*c->m_iNumEntries);
nKeepCnt = 0;
- for (i = 0; i < c->m_iNumEntries; i++){
- if (c->m_Codewords[i]->m_iMNRL < iStaleThreshold){
+ for (i = 0; i < c->m_iNumEntries; i++) {
+ if (c->m_Codewords[i]->m_iMNRL < iStaleThreshold) {
aKeep[i] = 1;
nKeepCnt++;
}
@@ -1537,8 +1542,8 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
TextureCodeword** temp = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*c->m_iElementArraySize);
nKeepCnt = 0;
- for (i = 0; i < c->m_iNumEntries; i++){
- if (aKeep[i] == 1){
+ for (i = 0; i < c->m_iNumEntries; i++) {
+ if (aKeep[i] == 1) {
temp[nKeepCnt] = c->m_Codewords[i];
temp[nKeepCnt]->m_iMNRL = 0;
nKeepCnt++;
@@ -1564,7 +1569,7 @@ void SJN_MultiCueBGS::T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function to generate texture confidence maps //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap, point*** aNeiDirArr, TextureModel**** aModel){
+void MultiCue::T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap, point*** aNeiDirArr, TextureModel**** aModel) {
int iBound_w = g_iRWidth - g_nRadius;
int iBound_h = g_iRHeight - g_nRadius;
@@ -1572,10 +1577,10 @@ void SJN_MultiCueBGS::T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap,
short nNeighborNum = g_nNeighborNum;
float fPadding = 5;
- for (int h = 0; h < g_iRHeight; h++){
- for (int w = 0; w < g_iRWidth; w++){
+ for (int h = 0; h < g_iRHeight; h++) {
+ for (int w = 0; w < g_iRWidth; w++) {
- if (h < g_nRadius || h >= iBound_h || w < g_nRadius || w >= iBound_w){
+ if (h < g_nRadius || h >= iBound_h || w < g_nRadius || w >= iBound_w) {
aTextureMap[h][w] = 0;
continue;
}
@@ -1585,7 +1590,7 @@ void SJN_MultiCueBGS::T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap,
float fDifference;
point nei;
- for (int i = 0; i < nNeighborNum; i++){
+ for (int i = 0; i < nNeighborNum; i++) {
nei.m_nX = aNeiDirArr[h][w][i].m_nX;
nei.m_nY = aNeiDirArr[h][w][i].m_nY;
@@ -1594,8 +1599,8 @@ void SJN_MultiCueBGS::T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap,
if (fDifference < 0) fDiffSum -= fDifference;
else fDiffSum += fDifference;
- for (int j = 0; j < aModel[h][w][i]->m_iNumEntries; j++){
- if (aModel[h][w][i]->m_Codewords[j]->m_fLowThre - fPadding <= fDifference && fDifference <= aModel[h][w][i]->m_Codewords[j]->m_fHighThre + fPadding){
+ for (int j = 0; j < aModel[h][w][i]->m_iNumEntries; j++) {
+ if (aModel[h][w][i]->m_Codewords[j]->m_fLowThre - fPadding <= fDifference && fDifference <= aModel[h][w][i]->m_Codewords[j]->m_fHighThre + fPadding) {
nMatchedCount++;
break;
}
@@ -1609,21 +1614,21 @@ void SJN_MultiCueBGS::T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap,
//-----------------------------------------------------------------------------------------------------------------------------------------//
// Absorbing Ghost Non-background Region Update //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_Absorption(int iAbsorbCnt, point pos, short*** aContinuCnt, short*** aRefferedIndex, TextureModel** pModel, TextureModel** pCache){
+void MultiCue::T_Absorption(int iAbsorbCnt, point pos, short*** aContinuCnt, short*** aRefferedIndex, TextureModel** pModel, TextureModel** pCache) {
int i, j, k;
int iLeavingIndex;
- short g_nRadius = 2;
+ //short g_nRadius = 2;
short nNeighborNum = g_nNeighborNum;
- for (i = 0; i < nNeighborNum; i++){
+ for (i = 0; i < nNeighborNum; i++) {
//set iLeavingIndex
if (aContinuCnt[pos.m_nY][pos.m_nX][i] < iAbsorbCnt) continue;
iLeavingIndex = aRefferedIndex[pos.m_nY][pos.m_nX][i];
//array expansion
- if (pModel[i]->m_iElementArraySize == pModel[i]->m_iNumEntries){
+ if (pModel[i]->m_iElementArraySize == pModel[i]->m_iNumEntries) {
pModel[i]->m_iElementArraySize = pModel[i]->m_iElementArraySize + 5;
TextureCodeword** temp = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*pModel[i]->m_iElementArraySize);
for (j = 0; j < pModel[i]->m_iNumEntries; j++) temp[j] = pModel[i]->m_Codewords[j];
@@ -1643,9 +1648,9 @@ void SJN_MultiCueBGS::T_Absorption(int iAbsorbCnt, point pos, short*** aContinuC
k = 0;
TextureCodeword **temp_Cache = (TextureCodeword**)malloc(sizeof(TextureCodeword*)*pCache[i]->m_iElementArraySize);
- for (j = 0; j < pCache[i]->m_iNumEntries; j++){
+ for (j = 0; j < pCache[i]->m_iNumEntries; j++) {
if (j == iLeavingIndex) continue;
- else{
+ else {
temp_Cache[k] = pCache[i]->m_Codewords[j];
k++;
}
@@ -1659,7 +1664,7 @@ void SJN_MultiCueBGS::T_Absorption(int iAbsorbCnt, point pos, short*** aContinuC
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the function to set neighborhood system //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::T_SetNeighborDirection(point*** aNeighborPos){
+void MultiCue::T_SetNeighborDirection(point*** aNeighborPos) {
int i, j, k;
point* aSearchDirection = (point*)malloc(sizeof(point)*g_nNeighborNum);
@@ -1683,9 +1688,9 @@ void SJN_MultiCueBGS::T_SetNeighborDirection(point*** aNeighborPos){
point temp_pos;
- for (i = 0; i < g_iRHeight; i++){
- for (j = 0; j < g_iRWidth; j++){
- for (k = 0; k < g_nNeighborNum; k++){
+ for (i = 0; i < g_iRHeight; i++) {
+ for (j = 0; j < g_iRWidth; j++) {
+ for (k = 0; k < g_nNeighborNum; k++) {
temp_pos.m_nX = j + aSearchDirection[k].m_nX;
temp_pos.m_nY = i + aSearchDirection[k].m_nY;
@@ -1707,16 +1712,16 @@ void SJN_MultiCueBGS::T_SetNeighborDirection(point*** aNeighborPos){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the color-model initialization function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::C_AllocateColorModelRelatedMemory(){
+void MultiCue::C_AllocateColorModelRelatedMemory() {
int i, j;
int iElementArraySize = 10;
//codebook initialization
g_ColorModel = (ColorModel***)malloc(sizeof(ColorModel**)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_ColorModel[i] = (ColorModel**)malloc(sizeof(ColorModel*)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++){
+ for (j = 0; j < g_iRWidth; j++) {
//initialization of each CodeBookArray.
g_ColorModel[i][j] = (ColorModel*)malloc(sizeof(ColorModel));
g_ColorModel[i][j]->m_Codewords = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*iElementArraySize);
@@ -1728,13 +1733,13 @@ void SJN_MultiCueBGS::C_AllocateColorModelRelatedMemory(){
}
//cache-book initialization
- if (g_bAbsorptionEnable == TRUE){
+ if (g_bAbsorptionEnable == TRUE) {
iElementArraySize = 3;
g_CCacheBook = (ColorModel***)malloc(sizeof(ColorModel**)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_CCacheBook[i] = (ColorModel**)malloc(sizeof(ColorModel*)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++){
+ for (j = 0; j < g_iRWidth; j++) {
//initialization of each CodeBookArray.
g_CCacheBook[i][j] = (ColorModel*)malloc(sizeof(ColorModel));
g_CCacheBook[i][j]->m_Codewords = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*iElementArraySize);
@@ -1747,10 +1752,10 @@ void SJN_MultiCueBGS::C_AllocateColorModelRelatedMemory(){
g_aCReferredIndex = (short**)malloc(sizeof(short*)*g_iRHeight);
g_aCContinuousCnt = (short**)malloc(sizeof(short*)*g_iRHeight);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
g_aCReferredIndex[i] = (short*)malloc(sizeof(short)*g_iRWidth);
g_aCContinuousCnt[i] = (short*)malloc(sizeof(short)*g_iRWidth);
- for (j = 0; j < g_iRWidth; j++){
+ for (j = 0; j < g_iRWidth; j++) {
g_aCReferredIndex[i][j] = -1;
g_aCContinuousCnt[i][j] = 0;
}
@@ -1761,12 +1766,12 @@ void SJN_MultiCueBGS::C_AllocateColorModelRelatedMemory(){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the memory release function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::C_ReleaseColorModelRelatedMemory(){
+void MultiCue::C_ReleaseColorModelRelatedMemory() {
int i, j, k;
- for (i = 0; i < g_iRHeight; i++){
- for (j = 0; j < g_iRWidth; j++){
- for (k = 0; k < g_ColorModel[i][j]->m_iNumEntries; k++){
+ for (i = 0; i < g_iRHeight; i++) {
+ for (j = 0; j < g_iRWidth; j++) {
+ for (k = 0; k < g_ColorModel[i][j]->m_iNumEntries; k++) {
free(g_ColorModel[i][j]->m_Codewords[k]);
}
free(g_ColorModel[i][j]->m_Codewords);
@@ -1776,10 +1781,10 @@ void SJN_MultiCueBGS::C_ReleaseColorModelRelatedMemory(){
}
free(g_ColorModel);
- if (g_bAbsorptionEnable == TRUE){
- for (i = 0; i < g_iRHeight; i++){
- for (j = 0; j < g_iRWidth; j++){
- for (k = 0; k < g_CCacheBook[i][j]->m_iNumEntries; k++){
+ if (g_bAbsorptionEnable == TRUE) {
+ for (i = 0; i < g_iRHeight; i++) {
+ for (j = 0; j < g_iRWidth; j++) {
+ for (k = 0; k < g_CCacheBook[i][j]->m_iNumEntries; k++) {
free(g_CCacheBook[i][j]->m_Codewords[k]);
}
free(g_CCacheBook[i][j]->m_Codewords);
@@ -1789,7 +1794,7 @@ void SJN_MultiCueBGS::C_ReleaseColorModelRelatedMemory(){
}
free(g_CCacheBook);
- for (i = 0; i < g_iRHeight; i++){
+ for (i = 0; i < g_iRHeight; i++) {
free(g_aCReferredIndex[i]);
free(g_aCContinuousCnt[i]);
}
@@ -1801,7 +1806,7 @@ void SJN_MultiCueBGS::C_ReleaseColorModelRelatedMemory(){
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the codebook construction function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, short nTrainVolRange, float fLearningRate, ColorModel* pC){
+void MultiCue::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, short nTrainVolRange, float fLearningRate, ColorModel* pC) {
//Step1: matching
short nMatchedIndex;
@@ -1810,14 +1815,14 @@ void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, sh
nMatchedIndex = -1;
- for (int i = 0; i < pC->m_iNumEntries; i++){
+ for (int i = 0; i < pC->m_iNumEntries; i++) {
//Checking X
- if (pC->m_Codewords[i]->m_dMean[0] - nTrainVolRange <= aP[0] && aP[0] <= pC->m_Codewords[i]->m_dMean[0] + nTrainVolRange){
+ if (pC->m_Codewords[i]->m_dMean[0] - nTrainVolRange <= aP[0] && aP[0] <= pC->m_Codewords[i]->m_dMean[0] + nTrainVolRange) {
//Checking Y
- if (pC->m_Codewords[i]->m_dMean[1] - nTrainVolRange <= aP[1] && aP[1] <= pC->m_Codewords[i]->m_dMean[1] + nTrainVolRange){
+ if (pC->m_Codewords[i]->m_dMean[1] - nTrainVolRange <= aP[1] && aP[1] <= pC->m_Codewords[i]->m_dMean[1] + nTrainVolRange) {
//Checking Z
- if (pC->m_Codewords[i]->m_dMean[2] - nTrainVolRange <= aP[2] && aP[2] <= pC->m_Codewords[i]->m_dMean[2] + nTrainVolRange){
+ if (pC->m_Codewords[i]->m_dMean[2] - nTrainVolRange <= aP[2] && aP[2] <= pC->m_Codewords[i]->m_dMean[2] + nTrainVolRange) {
nMatchedIndex = i;
break;
}
@@ -1828,11 +1833,11 @@ void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, sh
pC->m_iTotal = pC->m_iTotal + 1;
//Step2 : adding a new element
- if (nMatchedIndex == -1){
- if (pC->m_iElementArraySize == pC->m_iNumEntries){
+ if (nMatchedIndex == -1) {
+ if (pC->m_iElementArraySize == pC->m_iNumEntries) {
pC->m_iElementArraySize = pC->m_iElementArraySize + 5;
ColorCodeword **temp = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*pC->m_iElementArraySize);
- for (int j = 0; j < pC->m_iNumEntries; j++){
+ for (int j = 0; j < pC->m_iNumEntries; j++) {
temp[j] = pC->m_Codewords[j];
pC->m_Codewords[j] = NULL;
}
@@ -1853,7 +1858,7 @@ void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, sh
}
//Step3 : update
- else{
+ else {
//m_dMean update
pC->m_Codewords[nMatchedIndex]->m_dMean[0] = (fLearningRate*aP[0]) + fNegLearningRate*pC->m_Codewords[nMatchedIndex]->m_dMean[0];//X
pC->m_Codewords[nMatchedIndex]->m_dMean[1] = (fLearningRate*aP[1]) + fNegLearningRate*pC->m_Codewords[nMatchedIndex]->m_dMean[1];//Y
@@ -1863,10 +1868,10 @@ void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, sh
}
//cache-book handling
- if (pC->m_bID == 1){
+ if (pC->m_bID == 1) {
//1. m_iMNRL update
int iNegTime;
- for (int i = 0; i < pC->m_iNumEntries; i++){
+ for (int i = 0; i < pC->m_iNumEntries; i++) {
//m_iMNRL update
iNegTime = pC->m_iTotal - pC->m_Codewords[i]->m_iT_last_time + pC->m_Codewords[i]->m_iT_first_time - 1;
if (pC->m_Codewords[i]->m_iMNRL < iNegTime) pC->m_Codewords[i]->m_iMNRL = iNegTime;
@@ -1876,18 +1881,18 @@ void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, sh
if (g_bAbsorptionEnable == TRUE) g_aCReferredIndex[iPosY][iPosX] = -1;
}
- else{
+ else {
//1. m_iMNRL update:
if (nMatchedIndex == -1) pC->m_Codewords[pC->m_iNumEntries - 1]->m_iMNRL = 0;
//2. g_aCReferredIndex[iPosY][iPosX] update
- if (nMatchedIndex == -1){
+ if (nMatchedIndex == -1) {
g_aCReferredIndex[iPosY][iPosX] = pC->m_iNumEntries - 1;
g_aCContinuousCnt[iPosY][iPosX] = 1;
}
- else{
+ else {
if (nMatchedIndex == g_aCReferredIndex[iPosY][iPosX]) g_aCContinuousCnt[iPosY][iPosX]++;
- else{
+ else {
g_aCReferredIndex[iPosY][iPosX] = nMatchedIndex;
g_aCContinuousCnt[iPosY][iPosX] = 1;
}
@@ -1898,7 +1903,7 @@ void SJN_MultiCueBGS::C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, sh
//-----------------------------------------------------------------------------------------------------------------------------------------//
// Clear non-essential codewords of the given codebook // //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::C_ClearNonEssentialEntries(short nClearNum, ColorModel* pModel){
+void MultiCue::C_ClearNonEssentialEntries(short nClearNum, ColorModel* pModel) {
int i;
short nStaleThresh = (int)(nClearNum*0.5);
short nKeepCnt;
@@ -1914,7 +1919,7 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntries(short nClearNum, ColorModel* pM
nKeepCnt = 0;
//Step2: Find non-essential codewords
- for (i = 0; i<pC->m_iNumEntries; i++){
+ for (i = 0; i < pC->m_iNumEntries; i++) {
if (pC->m_Codewords[i]->m_iMNRL > nStaleThresh) {
aKeep[i] = 0; //removal
}
@@ -1925,19 +1930,19 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntries(short nClearNum, ColorModel* pM
}
//Step3: Perform removal
- if (nKeepCnt == 0 || nKeepCnt == pC->m_iNumEntries){
- for (i = 0; i < pC->m_iNumEntries; i++){
+ if (nKeepCnt == 0 || nKeepCnt == pC->m_iNumEntries) {
+ for (i = 0; i < pC->m_iNumEntries; i++) {
pC->m_Codewords[i]->m_iT_first_time = 1;
pC->m_Codewords[i]->m_iT_last_time = 1;
pC->m_Codewords[i]->m_iMNRL = 0;
}
}
- else{
+ else {
nKeepCnt = 0;
ColorCodeword** temp = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*pC->m_iNumEntries);
- for (i = 0; i < pC->m_iNumEntries; i++){
- if (aKeep[i] == 1){
+ for (i = 0; i < pC->m_iNumEntries; i++) {
+ if (aKeep[i] == 1) {
temp[nKeepCnt] = pC->m_Codewords[i];
temp[nKeepCnt]->m_iT_first_time = 1;
temp[nKeepCnt]->m_iT_last_time = 1;
@@ -1962,11 +1967,11 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntries(short nClearNum, ColorModel* pM
//-----------------------------------------------------------------------------------------------------------------------------------------//
// Clear non-essential codewords of the given codebook (for cache-book) //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short nReferredIdx, short nClearNum, ColorModel* pCachebook){
+void MultiCue::C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short nReferredIdx, short nClearNum, ColorModel* pCachebook) {
int i;
if (pCachebook->m_iTotal < nClearNum) {
- for (i = 0; i < pCachebook->m_iNumEntries; i++){
+ for (i = 0; i < pCachebook->m_iNumEntries; i++) {
if (bLandmark == 255 && i == nReferredIdx) pCachebook->m_Codewords[i]->m_iMNRL = 0;
else pCachebook->m_Codewords[i]->m_iMNRL++;
}
@@ -1974,7 +1979,7 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
pCachebook->m_iTotal++;
}
- else{
+ else {
int iStaleThreshold = 5;
int* aKeep;
@@ -1983,8 +1988,8 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
aKeep = (int*)malloc(sizeof(int)*pCachebook->m_iNumEntries);
nKeepCnt = 0;
- for (i = 0; i < pCachebook->m_iNumEntries; i++){
- if (pCachebook->m_Codewords[i]->m_iMNRL < iStaleThreshold){
+ for (i = 0; i < pCachebook->m_iNumEntries; i++) {
+ if (pCachebook->m_Codewords[i]->m_iMNRL < iStaleThreshold) {
aKeep[i] = 1;
nKeepCnt++;
}
@@ -1997,8 +2002,8 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
ColorCodeword** temp = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*pCachebook->m_iElementArraySize);
nKeepCnt = 0;
- for (i = 0; i < pCachebook->m_iNumEntries; i++){
- if (aKeep[i] == 1){
+ for (i = 0; i < pCachebook->m_iNumEntries; i++) {
+ if (aKeep[i] == 1) {
temp[nKeepCnt] = pCachebook->m_Codewords[i];
temp[nKeepCnt]->m_iMNRL = 0;
nKeepCnt++;
@@ -2022,7 +2027,7 @@ void SJN_MultiCueBGS::C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, sh
//-----------------------------------------------------------------------------------------------------------------------------------------//
// the ghost-region absorption function //
//-----------------------------------------------------------------------------------------------------------------------------------------//
-void SJN_MultiCueBGS::C_Absorption(int iAbsorbCnt, point pos, short** aContinuCnt, short** aRefferedIndex, ColorModel* pModel, ColorModel* pCache){
+void MultiCue::C_Absorption(int iAbsorbCnt, point pos, short** aContinuCnt, short** aRefferedIndex, ColorModel* pModel, ColorModel* pCache) {
//set iLeavingIndex
if (aContinuCnt[pos.m_nY][pos.m_nX] < iAbsorbCnt) return;
@@ -2030,7 +2035,7 @@ void SJN_MultiCueBGS::C_Absorption(int iAbsorbCnt, point pos, short** aContinuCn
int iLeavingIndex = aRefferedIndex[pos.m_nY][pos.m_nX];
//array expansion
- if (pModel->m_iElementArraySize == pModel->m_iNumEntries){
+ if (pModel->m_iElementArraySize == pModel->m_iNumEntries) {
pModel->m_iElementArraySize = pModel->m_iElementArraySize + 5;
ColorCodeword** temp = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*pModel->m_iElementArraySize);
for (int i = 0; i < pModel->m_iNumEntries; i++) temp[i] = pModel->m_Codewords[i];
@@ -2051,9 +2056,9 @@ void SJN_MultiCueBGS::C_Absorption(int iAbsorbCnt, point pos, short** aContinuCn
int k = 0;
ColorCodeword **pTempCache = (ColorCodeword**)malloc(sizeof(ColorCodeword*)*pCache->m_iElementArraySize);
- for (int i = 0; i < pCache->m_iNumEntries; i++){
+ for (int i = 0; i < pCache->m_iNumEntries; i++) {
if (i == iLeavingIndex) continue;
- else{
+ else {
pTempCache[k] = pCache->m_Codewords[i];
k++;
}
diff --git a/package_bgs/MultiCue.h b/package_bgs/MultiCue.h
new file mode 100644
index 0000000..44524e0
--- /dev/null
+++ b/package_bgs/MultiCue.h
@@ -0,0 +1,254 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#define MIN3(x,y,z) ((y) <= (z) ? ((x) <= (y) ? (x) : (y)) : ((x) <= (z) ? (x) : (z)))
+#define MAX3(x,y,z) ((y) >= (z) ? ((x) >= (y) ? (x) : (y)) : ((x) >= (z) ? (x) : (z)))
+
+#ifndef PI
+#define PI 3.14159
+#endif
+
+typedef int BOOL;
+
+#ifndef FALSE
+#define FALSE 0
+#endif
+
+#ifndef TRUE
+#define TRUE 1
+#endif
+
+#if !defined(__APPLE__)
+#include <malloc.h>
+#endif
+#include "math.h"
+
+#include <vector>
+#include <algorithm>
+#include <opencv2/opencv.hpp>
+
+#include "IBGS.h"
+
+//------------------------------------Structure Lists-------------------------------------//
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ namespace libMultiCue
+ {
+ struct point {
+ short m_nX;
+ short m_nY;
+ };
+
+ struct neighbor_pos {
+ short m_nX;
+ short m_nY;
+ };
+ //1) Bounding Box Structure
+ struct BoundingBoxInfo {
+ int m_iBoundBoxNum; //# of bounding boxes for all foreground and false-positive blobs
+ int m_iArraySize; //the size of the below arrays to store bounding box information
+
+ short *m_aLeft, *m_aRight, *m_aUpper, *m_aBottom; //arrays to store bounding box information for (the original frame size)
+ short *m_aRLeft, *m_aRRight, *m_aRUpper, *m_aRBottom; //arrays to store bounding box information for (the reduced frame size)
+ BOOL* m_ValidBox; //If this value is true, the corresponding bounding box is for a foreground blob.
+ //Else, it is for a false-positive blob
+ };
+
+ //2) Texture Model Structure
+ struct TextureCodeword {
+ int m_iMNRL; //the maximum negative run-length
+ int m_iT_first_time; //the first access time
+ int m_iT_last_time; //the last access time
+
+ float m_fLowThre; //a low threshold for the matching
+ float m_fHighThre; //a high threshold for the matching
+ float m_fMean; //mean of the codeword
+ };
+
+ struct TextureModel {
+ TextureCodeword** m_Codewords; //the texture-codeword Array
+
+ int m_iTotal; //# of learned samples after the last clear process
+ int m_iElementArraySize; //the array size of m_Codewords
+ int m_iNumEntries; //# of codewords
+
+ BOOL m_bID; //id=1 --> background model, id=0 --> cachebook
+ };
+
+ //3) Color Model Structure
+ struct ColorCodeword {
+ int m_iMNRL; //the maximum negative run-length
+ int m_iT_first_time; //the first access time
+ int m_iT_last_time; //the last access time
+
+ double m_dMean[3]; //mean vector of the codeword
+
+ };
+
+ struct ColorModel {
+ ColorCodeword** m_Codewords; //the color-codeword Array
+
+ int m_iTotal; //# of learned samples after the last clear process
+ int m_iElementArraySize; //the array size of m_Codewords
+ int m_iNumEntries; //# of codewords
+
+ BOOL m_bID; //id=1 --> background model, id=0 --> cachebookk
+ };
+ }
+ }
+}
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ using namespace bgslibrary::algorithms::libMultiCue;
+
+ class MultiCue : public IBGS
+ {
+ private:
+ void saveConfig();
+ void loadConfig();
+
+ public:
+ MultiCue();
+ ~MultiCue();
+
+ public:
+ //----------------------------------------------------
+ // APIs and User-Adjustable Parameters
+ //----------------------------------------------------
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel); //the main function to background modeling and subtraction
+
+ void GetForegroundMap(IplImage* return_image, IplImage* input_frame = NULL); //the function returning a foreground binary-map
+ void Destroy(); //the function to release allocated memories
+
+ int g_iTrainingPeriod; //the training period (The parameter t in the paper)
+ int g_iT_ModelThreshold; //the threshold for texture-model based BGS. (The parameter tau_T in the paper)
+ int g_iC_ModelThreshold; //the threshold for appearance based verification. (The parameter tau_A in the paper)
+
+ float g_fLearningRate; //the learning rate for background models. (The parameter alpha in the paper)
+
+ short g_nTextureTrainVolRange; //the codebook size factor for texture models. (The parameter k in the paper)
+ short g_nColorTrainVolRange; //the codebook size factor for color models. (The parameter eta_1 in the paper)
+
+ public:
+ //----------------------------------------------------
+ // Implemented Function Lists
+ //----------------------------------------------------
+
+ //--1) General Functions
+ void Initialize(IplImage* frame);
+
+ void PreProcessing(IplImage* frame);
+ void ReduceImageSize(IplImage* SrcImage, IplImage* DstImage);
+ void GaussianFiltering(IplImage* frame, uchar*** aFilteredFrame);
+ void BGR2HSVxyz_Par(uchar*** aBGR, uchar*** aXYZ);
+
+ void BackgroundModeling_Par(IplImage* frame);
+ void ForegroundExtraction(IplImage* frame);
+ void CreateLandmarkArray_Par(float fConfThre, short nTrainVolRange, float**aConfMap, int iNehborNum, uchar*** aXYZ,
+ point*** aNeiDir, TextureModel**** TModel, ColorModel*** CModel, uchar**aLandmarkArr);
+
+ void PostProcessing(IplImage* frame);
+ void MorphologicalOpearions(uchar** aInput, uchar** aOutput, double dThresholdRatio, int iMaskSize, int iWidth, int iHeight);
+ void Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLabelTable);
+ void SetBoundingBox(int iLabelCount, int** aLabelTable);
+ void BoundBoxVerification(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo);
+ void EvaluateBoxSize(BoundingBoxInfo* BoundBoxInfo);
+ void EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo);
+ void EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo);
+ double CalculateHausdorffDist(IplImage* input_image, IplImage* model_image);
+ void RemovingInvalidForeRegions(uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo);
+
+ void UpdateModel_Par();
+ void GetEnlargedMap(float** aOriginMap, float** aEnlargedMap);
+
+ //--2) Texture Model Related Functions
+ void T_AllocateTextureModelRelatedMemory();
+ void T_ReleaseTextureModelRelatedMemory();
+ void T_SetNeighborDirection(point*** aNeighborPos);
+ void T_ModelConstruction(short nTrainVolRange, float fLearningRate, uchar*** aXYZ, point center, point* aNei, TextureModel** aModel);
+ void T_ClearNonEssentialEntries(short nClearNum, TextureModel** aModel);
+ void T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short* nReferredIdxArr, short nClearNum, TextureModel** pCachebook);
+ void T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap, point*** aNeiDirArr, TextureModel**** aModel);
+ void T_Absorption(int iAbsorbCnt, point pos, short*** aContinuCnt, short*** aRefferedIndex, TextureModel** pModel, TextureModel** pCache);
+
+ //--3) Color Model Related Functions
+ void C_AllocateColorModelRelatedMemory();
+ void C_ReleaseColorModelRelatedMemory();
+ void C_CodebookConstruction(uchar* aP, int iPosX, int iPosY, short nTrainVolRange, float fLearningRate, ColorModel* pC);
+ void C_ClearNonEssentialEntries(short nClearNum, ColorModel* pModel);
+ void C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short nReferredIdx, short nClearNum, ColorModel* pCachebook);
+ void C_Absorption(int iAbsorbCnt, point pos, short** aContinuCnt, short** aRefferedIndex, ColorModel* pModel, ColorModel* pCache);
+ public:
+ //----------------------------------------------------
+ // Implemented Variable Lists
+ //----------------------------------------------------
+
+ //--1) General Variables
+ int g_iFrameCount; //the counter of processed frames
+
+ int g_iBackClearPeriod; //the period to clear background models
+ int g_iCacheClearPeriod; //the period to clear cache-book models
+
+ int g_iAbsortionPeriod; //the period to absorb static ghost regions
+ BOOL g_bAbsorptionEnable; //If True, procedures for ghost region absorption are activated.
+
+ BOOL g_bModelMemAllocated; //To handle memory..
+ BOOL g_bNonModelMemAllocated; //To handle memory..
+
+ float g_fConfidenceThre; //the final decision threshold
+
+ int g_iWidth, g_iHeight; //width and height of input frames
+ int g_iRWidth, g_iRHeight; //width and height of reduced frames (For efficiency, the reduced size of frames are processed)
+ int g_iForegroundNum; //# of detected foreground regions
+ BOOL g_bForegroundMapEnable; //TRUE only when BGS is successful
+
+ IplImage* g_ResizedFrame; //reduced size of frame (For efficiency, the reduced size of frames are processed)
+ uchar*** g_aGaussFilteredFrame;
+ uchar*** g_aXYZFrame;
+ uchar** g_aLandmarkArray; //the landmark map
+ uchar** g_aResizedForeMap; //the resized foreground map
+ uchar** g_aForegroundMap; //the final foreground map
+ BOOL** g_aUpdateMap; //the location map of update candidate pixels
+
+ BoundingBoxInfo* g_BoundBoxInfo; //the array of bounding boxes of each foreground blob
+
+ //--2) Texture Model Related
+ TextureModel**** g_TextureModel; //the texture background model
+ TextureModel**** g_TCacheBook; //the texture cache-book
+ short*** g_aTReferredIndex; //To handle cache-book
+ short*** g_aTContinuousCnt; //To handle cache-book
+ point*** g_aNeighborDirection;
+ float**g_aTextureConfMap; //the texture confidence map
+
+ short g_nNeighborNum; //# of neighborhoods
+ short g_nRadius;
+ short g_nBoundarySize;
+
+ //--3) Texture Model Related
+ ColorModel*** g_ColorModel; //the color background model
+ ColorModel*** g_CCacheBook; //the color cache-book
+ short** g_aCReferredIndex; //To handle cache-book
+ short** g_aCContinuousCnt; //To handle cache-book
+ };
+ }
+}
diff --git a/package_bgs/jmo/MultiLayerBGS.cpp b/package_bgs/MultiLayer.cpp
similarity index 65%
rename from package_bgs/jmo/MultiLayerBGS.cpp
rename to package_bgs/MultiLayer.cpp
index 03e223f..180d88d 100644
--- a/package_bgs/jmo/MultiLayerBGS.cpp
+++ b/package_bgs/MultiLayer.cpp
@@ -14,36 +14,40 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "MultiLayerBGS.h"
+#include "MultiLayer.h"
-MultiLayerBGS::MultiLayerBGS() : firstTime(true), frameNumber(0), showOutput(true),
-saveModel(false), disableDetectMode(true), disableLearning(false), detectAfter(0), bg_model_preload(""), loadDefaultParams(true)
+using namespace bgslibrary::algorithms;
+
+MultiLayer::MultiLayer() :
+ frameNumber(0), saveModel(false), disableDetectMode(true), disableLearning(false),
+ detectAfter(0), bg_model_preload(""), loadDefaultParams(true)
{
- std::cout << "MultiLayerBGS()" << std::endl;
+ std::cout << "MultiLayer()" << std::endl;
+ setup("./config/MultiLayer.xml");
}
-MultiLayerBGS::~MultiLayerBGS()
+MultiLayer::~MultiLayer()
{
finish();
- std::cout << "~MultiLayerBGS()" << std::endl;
+ std::cout << "~MultiLayer()" << std::endl;
}
-void MultiLayerBGS::setStatus(Status _status)
+void MultiLayer::setStatus(Status _status)
{
status = _status;
}
-void MultiLayerBGS::finish(void)
+void MultiLayer::finish()
{
if (bg_model_preload.empty())
{
- bg_model_preload = "./models/MultiLayerBGSModel.yml";
+ bg_model_preload = "./MultiLayerModel.yml";
saveConfig();
}
if (status == MLBGS_LEARN && saveModel == true)
{
- std::cout << "MultiLayerBGS saving background model: " << bg_model_preload << std::endl;
+ std::cout << "MultiLayer saving background model: " << bg_model_preload << std::endl;
BGS->Save(bg_model_preload.c_str());
}
@@ -57,13 +61,9 @@ void MultiLayerBGS::finish(void)
delete BGS;
}
-void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void MultiLayer::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if (img_input.empty())
- return;
-
- loadConfig();
-
+ init(img_input, img_output, img_bgmodel);
CvSize img_size = cvSize(cvCeil((double)img_input.size().width), cvCeil((double)img_input.size().height));
if (firstTime)
@@ -72,10 +72,10 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
status = MLBGS_LEARN;
if (status == MLBGS_LEARN)
- std::cout << "MultiLayerBGS in LEARN mode" << std::endl;
+ std::cout << "MultiLayer in LEARN mode" << std::endl;
if (status == MLBGS_DETECT)
- std::cout << "MultiLayerBGS in DETECT mode" << std::endl;
+ std::cout << "MultiLayer in DETECT mode" << std::endl;
org_img = new IplImage(img_input);
@@ -93,7 +93,7 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
if (bg_model_preload.empty() == false)
{
- std::cout << "MultiLayerBGS loading background model: " << bg_model_preload << std::endl;
+ std::cout << "MultiLayer loading background model: " << bg_model_preload << std::endl;
BGS->Load(bg_model_preload.c_str());
}
@@ -102,14 +102,14 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
BGS->m_disableLearning = disableLearning;
if (disableLearning)
- std::cout << "MultiLayerBGS disabled learning in DETECT mode" << std::endl;
+ std::cout << "MultiLayer disabled learning in DETECT mode" << std::endl;
else
- std::cout << "MultiLayerBGS enabled learning in DETECT mode" << std::endl;
+ std::cout << "MultiLayer enabled learning in DETECT mode" << std::endl;
}
if (loadDefaultParams)
{
- std::cout << "MultiLayerBGS loading default params" << std::endl;
+ std::cout << "MultiLayer loading default params" << std::endl;
max_mode_num = 5;
weight_updating_constant = 5.0;
@@ -127,7 +127,7 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
bilater_filter_sigma_r = 0.1f;
}
else
- std::cout << "MultiLayerBGS loading config params" << std::endl;
+ std::cout << "MultiLayer loading config params" << std::endl;
BGS->m_nMaxLBPModeNum = max_mode_num;
BGS->m_fWeightUpdatingConstant = weight_updating_constant;
@@ -186,9 +186,6 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
}
BGS->SetParameters(max_mode_num, mode_learn_rate_per_second, weight_learn_rate_per_second, init_mode_weight);
-
- saveConfig();
-
delete org_img;
}
@@ -199,7 +196,7 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
if (detectAfter > 0 && detectAfter == frameNumber)
{
- std::cout << "MultiLayerBGS in DETECT mode" << std::endl;
+ std::cout << "MultiLayer in DETECT mode" << std::endl;
status = MLBGS_DETECT;
@@ -212,9 +209,9 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
BGS->m_disableLearning = disableLearning;
if (disableLearning)
- std::cout << "MultiLayerBGS disabled learning in DETECT mode" << std::endl;
+ std::cout << "MultiLayer disabled learning in DETECT mode" << std::endl;
else
- std::cout << "MultiLayerBGS enabled learning in DETECT mode" << std::endl;
+ std::cout << "MultiLayer enabled learning in DETECT mode" << std::endl;
}
IplImage* img = new IplImage(img_input);
@@ -228,15 +225,17 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
BGS->GetForegroundMaskImage(fg_mask_img);
BGS->MergeImages(4, img, bg_img, fg_prob_img3, fg_img, merged_img);
- img_merged = cv::Mat(merged_img);
- img_foreground = cv::Mat(fg_mask_img);
- img_background = cv::Mat(bg_img);
+ img_merged = cv::cvarrToMat(merged_img);
+ img_foreground = cv::cvarrToMat(fg_mask_img);
+ img_background = cv::cvarrToMat(bg_img);
+#ifndef MEX_COMPILE_FLAG
if (showOutput)
{
cv::imshow("MLBGS Layers", img_merged);
cv::imshow("MLBGS FG Mask", img_foreground);
}
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -248,9 +247,9 @@ void MultiLayerBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::M
frameNumber++;
}
-void MultiLayerBGS::saveConfig()
+void MultiLayer::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MultiLayerBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteString(fs, "preloadModel", bg_model_preload.c_str());
cvWriteInt(fs, "saveModel", saveModel);
@@ -289,43 +288,43 @@ void MultiLayerBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void MultiLayerBGS::loadConfig()
+void MultiLayer::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/MultiLayerBGS.xml", 0, CV_STORAGE_READ);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
- bg_model_preload = cvReadStringByName(fs, 0, "preloadModel", "");
- saveModel = cvReadIntByName(fs, 0, "saveModel", false);
- detectAfter = cvReadIntByName(fs, 0, "detectAfter", 0);
- disableDetectMode = cvReadIntByName(fs, 0, "disableDetectMode", true);
- disableLearning = cvReadIntByName(fs, 0, "disableLearningInDetecMode", false);
- loadDefaultParams = cvReadIntByName(fs, 0, "loadDefaultParams", true);
+ bg_model_preload = cvReadStringByName(fs, nullptr, "preloadModel", "");
+ saveModel = cvReadIntByName(fs, nullptr, "saveModel", false);
+ detectAfter = cvReadIntByName(fs, nullptr, "detectAfter", 0);
+ disableDetectMode = cvReadIntByName(fs, nullptr, "disableDetectMode", true);
+ disableLearning = cvReadIntByName(fs, nullptr, "disableLearningInDetecMode", false);
+ loadDefaultParams = cvReadIntByName(fs, nullptr, "loadDefaultParams", true);
- max_mode_num = cvReadIntByName(fs, 0, "max_mode_num", 5);
+ max_mode_num = cvReadIntByName(fs, nullptr, "max_mode_num", 5);
weight_updating_constant = cvReadRealByName(fs, 0, "weight_updating_constant", 5.0);
- texture_weight = cvReadRealByName(fs, 0, "texture_weight", 0.5);
- bg_mode_percent = cvReadRealByName(fs, 0, "bg_mode_percent", 0.6);
- pattern_neig_half_size = cvReadIntByName(fs, 0, "pattern_neig_half_size", 4);
- pattern_neig_gaus_sigma = cvReadRealByName(fs, 0, "pattern_neig_gaus_sigma", 3.0);
- bg_prob_threshold = cvReadRealByName(fs, 0, "bg_prob_threshold", 0.2);
- bg_prob_updating_threshold = cvReadRealByName(fs, 0, "bg_prob_updating_threshold", 0.2);
- robust_LBP_constant = cvReadIntByName(fs, 0, "robust_LBP_constant", 3);
- min_noised_angle = cvReadRealByName(fs, 0, "min_noised_angle", 0.01768);
- shadow_rate = cvReadRealByName(fs, 0, "shadow_rate", 0.6);
- highlight_rate = cvReadRealByName(fs, 0, "highlight_rate", 1.2);
- bilater_filter_sigma_s = cvReadRealByName(fs, 0, "bilater_filter_sigma_s", 3.0);
- bilater_filter_sigma_r = cvReadRealByName(fs, 0, "bilater_filter_sigma_r", 0.1);
-
- frame_duration = cvReadRealByName(fs, 0, "frame_duration", 0.1);
-
- learn_mode_learn_rate_per_second = cvReadRealByName(fs, 0, "learn_mode_learn_rate_per_second", 0.5);
- learn_weight_learn_rate_per_second = cvReadRealByName(fs, 0, "learn_weight_learn_rate_per_second", 0.5);
- learn_init_mode_weight = cvReadRealByName(fs, 0, "learn_init_mode_weight", 0.05);
-
- detect_mode_learn_rate_per_second = cvReadRealByName(fs, 0, "detect_mode_learn_rate_per_second", 0.01);
- detect_weight_learn_rate_per_second = cvReadRealByName(fs, 0, "detect_weight_learn_rate_per_second", 0.01);
- detect_init_mode_weight = cvReadRealByName(fs, 0, "detect_init_mode_weight", 0.001);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ texture_weight = cvReadRealByName(fs, nullptr, "texture_weight", 0.5);
+ bg_mode_percent = cvReadRealByName(fs, nullptr, "bg_mode_percent", 0.6);
+ pattern_neig_half_size = cvReadIntByName(fs, nullptr, "pattern_neig_half_size", 4);
+ pattern_neig_gaus_sigma = cvReadRealByName(fs, nullptr, "pattern_neig_gaus_sigma", 3.0);
+ bg_prob_threshold = cvReadRealByName(fs, nullptr, "bg_prob_threshold", 0.2);
+ bg_prob_updating_threshold = cvReadRealByName(fs, nullptr, "bg_prob_updating_threshold", 0.2);
+ robust_LBP_constant = cvReadIntByName(fs, nullptr, "robust_LBP_constant", 3);
+ min_noised_angle = cvReadRealByName(fs, nullptr, "min_noised_angle", 0.01768);
+ shadow_rate = cvReadRealByName(fs, nullptr, "shadow_rate", 0.6);
+ highlight_rate = cvReadRealByName(fs, nullptr, "highlight_rate", 1.2);
+ bilater_filter_sigma_s = cvReadRealByName(fs, nullptr, "bilater_filter_sigma_s", 3.0);
+ bilater_filter_sigma_r = cvReadRealByName(fs, nullptr, "bilater_filter_sigma_r", 0.1);
+
+ frame_duration = cvReadRealByName(fs, nullptr, "frame_duration", 0.1);
+
+ learn_mode_learn_rate_per_second = cvReadRealByName(fs, nullptr, "learn_mode_learn_rate_per_second", 0.5);
+ learn_weight_learn_rate_per_second = cvReadRealByName(fs, nullptr, "learn_weight_learn_rate_per_second", 0.5);
+ learn_init_mode_weight = cvReadRealByName(fs, nullptr, "learn_init_mode_weight", 0.05);
+
+ detect_mode_learn_rate_per_second = cvReadRealByName(fs, nullptr, "detect_mode_learn_rate_per_second", 0.01);
+ detect_weight_learn_rate_per_second = cvReadRealByName(fs, nullptr, "detect_weight_learn_rate_per_second", 0.01);
+ detect_init_mode_weight = cvReadRealByName(fs, nullptr, "detect_init_mode_weight", 0.001);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/MultiLayer.h b/package_bgs/MultiLayer.h
new file mode 100644
index 0000000..af7e128
--- /dev/null
+++ b/package_bgs/MultiLayer.h
@@ -0,0 +1,99 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "MultiLayer/CMultiLayerBGS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class MultiLayer : public IBGS
+ {
+ public:
+ enum Status
+ {
+ MLBGS_NONE = -1,
+ MLBGS_LEARN = 0,
+ MLBGS_DETECT = 1
+ };
+
+ private:
+ long long frameNumber;
+ cv::Mat img_merged;
+ bool saveModel;
+ bool disableDetectMode;
+ bool disableLearning;
+ int detectAfter;
+ CMultiLayerBGS* BGS;
+ Status status;
+ IplImage* img;
+ IplImage* org_img;
+ IplImage* fg_img;
+ IplImage* bg_img;
+ IplImage* fg_prob_img;
+ IplImage* fg_mask_img;
+ IplImage* fg_prob_img3;
+ IplImage* merged_img;
+ std::string bg_model_preload;
+
+ bool loadDefaultParams;
+
+ int max_mode_num;
+ float weight_updating_constant;
+ float texture_weight;
+ float bg_mode_percent;
+ int pattern_neig_half_size;
+ float pattern_neig_gaus_sigma;
+ float bg_prob_threshold;
+ float bg_prob_updating_threshold;
+ int robust_LBP_constant;
+ float min_noised_angle;
+ float shadow_rate;
+ float highlight_rate;
+ float bilater_filter_sigma_s;
+ float bilater_filter_sigma_r;
+
+ float frame_duration;
+
+ float mode_learn_rate_per_second;
+ float weight_learn_rate_per_second;
+ float init_mode_weight;
+
+ float learn_mode_learn_rate_per_second;
+ float learn_weight_learn_rate_per_second;
+ float learn_init_mode_weight;
+
+ float detect_mode_learn_rate_per_second;
+ float detect_weight_learn_rate_per_second;
+ float detect_init_mode_weight;
+
+ public:
+ MultiLayer();
+ ~MultiLayer();
+
+ void setStatus(Status status);
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void finish();
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/jmo/BGS.h b/package_bgs/MultiLayer/BGS.h
similarity index 98%
rename from package_bgs/jmo/BGS.h
rename to package_bgs/MultiLayer/BGS.h
index c506df2..ad2129b 100644
--- a/package_bgs/jmo/BGS.h
+++ b/package_bgs/MultiLayer/BGS.h
@@ -40,10 +40,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
-#if !defined(_BGS_H_)
-#define _BGS_H_
+#pragma once
-#include <opencv2/opencv.hpp>
+#include "OpenCvLegacyIncludes.h"
// TODO check these defines are not used (or not redundant with real params)
@@ -211,6 +210,3 @@ class IMAGE_BG_MODEL
delete[] pixel_PATTERNs;
}
};
-
-
-#endif // !defined(_BGS_H_)
diff --git a/package_bgs/jmo/BackgroundSubtractionAPI.h b/package_bgs/MultiLayer/BackgroundSubtractionAPI.h
similarity index 89%
rename from package_bgs/jmo/BackgroundSubtractionAPI.h
rename to package_bgs/MultiLayer/BackgroundSubtractionAPI.h
index bb39611..409fa40 100644
--- a/package_bgs/jmo/BackgroundSubtractionAPI.h
+++ b/package_bgs/MultiLayer/BackgroundSubtractionAPI.h
@@ -60,12 +60,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// char image for the output
//
//////////////////////////////////////////////////////////////////////
+#pragma once
-
-#if !defined(_BACKGROUND_SUBTRACTION_API_H_)
-#define _BACKGROUND_SUBTRACTION_API_H_
-
-#include <opencv2/opencv.hpp>
+#include "OpenCvLegacyIncludes.h"
class CBackgroundSubtractionAPI
{
@@ -79,14 +76,14 @@ public:
void Init(int width, int height);
//-------------------------------------------------------------
- // PROVIDE A MASK TO DEFINE THE SET OF POINTS WHERE BACKGROUND
+ // PROVIDE A MASK TO DEFINE THE SET OF POINTS WHERE BACKGROUND
// SUBTRACTION DOES NOT NEED TO BE PERFORMED
- //
- // mode is useful to specify if the points to remove from
+ //
+ // mode is useful to specify if the points to remove from
// processing are in addition to the ones potentially
// removed according to the configuration file,
- // or if they are the only ones to be removed
- //
+ // or if they are the only ones to be removed
+ //
// mode=0 : provided points need to be removed
// in addition to those already removed
// mode=1 : the provided points are the only one to remove
@@ -96,12 +93,12 @@ public:
void SetValidPointMask(IplImage* maskImage, int mode);
//-------------------------------------------------------------
- //
+ //
// set the frame rate, to adjust the update parameters
// to the actual frame rate.
// Can be called only once at initialisation,
// but in online cases, can be used to indicate
- // the time interval during the last processed frame
+ // the time interval during the last processed frame
//
// frameDuration is in millisecond
void SetFrameRate(float frameDuration);
@@ -113,31 +110,31 @@ public:
// Here assumes that the input image will contain RGB images.
// The memory of this image is handled by the caller.
//
- // The return value indicate whether the actual Background
+ // The return value indicate whether the actual Background
// Subtraction algorithm handles RGB images (1) or not (0).
- //
+ //
int SetRGBInputImage(IplImage * inputImage);
//-------------------------------------------------------------
// PROVIDE A POINTER TO THE RESULT IMAGE
// INDICATE WHERE THE BACKGROUND RESULT NEED TO BE STORED
- //
+ //
// The return value is 1 if correct image format is provided,
// otherwise the return value is 0.
// e.g. fg_mask_img = cvCreateImage(imgSize, IPL_DEPTH_8U, 1);
int SetForegroundMaskImage(IplImage *fg_mask_img);
- // The return value is 1 if the function is implemented
+ // The return value is 1 if the function is implemented
// with correct format, otherwise the return value is 0
// e.g. fg_prob_img = cvCreateImage(imgSize, IPL_DEPTH_32F, 1);
int SetForegroundProbImage(IplImage *fg_prob_img);
//-------------------------------------------------------------
- // This function should be called each time a new image is
+ // This function should be called each time a new image is
// available in the input image.
- //
+ //
// The return value is 1 if everything goes well,
- // otherwise the return value is 0.
+ // otherwise the return value is 0.
//
int Process();
@@ -150,9 +147,7 @@ public:
//-------------------------------------------------------------
// this function should load the parameters necessary
- // for the processing of the background subtraction or
+ // for the processing of the background subtraction or
// load background model information
void Load(char *bg_model_fn);
};
-
-#endif // !defined(_BACKGROUND_SUBTRACTION_API_H_)
diff --git a/package_bgs/jmo/BlobExtraction.cpp b/package_bgs/MultiLayer/BlobExtraction.cpp
similarity index 91%
rename from package_bgs/jmo/BlobExtraction.cpp
rename to package_bgs/MultiLayer/BlobExtraction.cpp
index 81857eb..7aecd65 100644
--- a/package_bgs/jmo/BlobExtraction.cpp
+++ b/package_bgs/MultiLayer/BlobExtraction.cpp
@@ -55,47 +55,47 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
//! Indica si la connectivitat es a 8 (si es desactiva es a 4)
#define B_CONNECTIVITAT_8
-//! si la imatge �s c�clica verticalment (els blobs que toquen
+//! si la imatge és cÃclica verticalment (els blobs que toquen
//! les vores superior i inferior no es consideren externs)
#define IMATGE_CICLICA_VERTICAL 1
-//! si la imatge �s c�clica horitzontalment (els blobs que toquen
+//! si la imatge és cÃclica horitzontalment (els blobs que toquen
//! les vores dreta i esquerra no es consideren externs)
#define IMATGE_CICLICA_HORITZONTAL 0
#define PERIMETRE_DIAGONAL (1.41421356237310 - 2)
#define SQRT2 1.41421356237310
-// color dels p�xels de la m�scara per ser exteriors
+// color dels pÃxels de la mà scara per ser exteriors
#define PIXEL_EXTERIOR 0
#include "BlobResult.h"
#include "BlobExtraction.h"
-#include <opencv2/legacy/compat.hpp>
+#include "OpenCvLegacyIncludes.h"
namespace Blob
{
/**
- - FUNCI�: BlobAnalysis
- - FUNCIONALITAT: Extreu els blobs d'una imatge d'un sol canal
- - PAR�METRES:
- - inputImage: Imatge d'entrada. Ha de ser d'un sol canal
- - threshold: Nivell de gris per considerar un pixel blanc o negre
- - maskImage: Imatge de m�scara fora de la cual no es calculen els blobs. A m�s,
- els blobs que toquen els pixels de la m�scara a 0, s�n considerats
- externs
- - borderColor: Color del marc de la imatge (0=black or 1=white)
- - findmoments: calcula els moments dels blobs o no
- - RegionData: on es desar� el resultat
- - RESULTAT:
- - retorna true si tot ha anat b�, false si no. Deixa el resultat a blobs.
- - RESTRICCIONS:
- - La imatge d'entrada ha de ser d'un sol canal
- - AUTOR: dgrossman@cdr.stanford.edu
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- - fpinyol@cvc.uab.es, rborras@cvc.uab.es: adaptaci� a les OpenCV
- */
+ - FUNCIÓ: BlobAnalysis
+ - FUNCIONALITAT: Extreu els blobs d'una imatge d'un sol canal
+ - PARÀMETRES:
+ - inputImage: Imatge d'entrada. Ha de ser d'un sol canal
+ - threshold: Nivell de gris per considerar un pixel blanc o negre
+ - maskImage: Imatge de mà scara fora de la cual no es calculen els blobs. A més,
+ els blobs que toquen els pixels de la mà scara a 0, són considerats
+ externs
+ - borderColor: Color del marc de la imatge (0=black or 1=white)
+ - findmoments: calcula els moments dels blobs o no
+ - RegionData: on es desarà el resultat
+ - RESULTAT:
+ - retorna true si tot ha anat bé, false si no. Deixa el resultat a blobs.
+ - RESTRICCIONS:
+ - La imatge d'entrada ha de ser d'un sol canal
+ - AUTOR: dgrossman@cdr.stanford.edu
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ - fpinyol@cvc.uab.es, rborras@cvc.uab.es: adaptació a les OpenCV
+ */
bool BlobAnalysis(IplImage* inputImage,
uchar threshold,
IplImage* maskImage,
@@ -151,13 +151,13 @@ namespace Blob
if (!CV_IS_IMAGE(inputImage) || !CV_IS_IMAGE(maskImage))
return false;
- // comprova que la m�scara tingui les mateixes dimensions que la imatge
+ // comprova que la mà scara tingui les mateixes dimensions que la imatge
if (inputImage->width != maskImage->width || inputImage->height != maskImage->height)
{
return false;
}
- // comprova que la m�scara sigui una imatge d'un sol canal (grayscale)
+ // comprova que la mà scara sigui una imatge d'un sol canal (grayscale)
if (maskImage->nChannels != 1)
{
return false;
@@ -167,16 +167,16 @@ namespace Blob
// Initialize Transition array
Transition = new int[(Rows + 2)*(Cols + 2)];
- memset(Transition, 0, (Rows + 2) * (Cols + 2)*sizeof(int));
+ memset(Transition, 0, (Rows + 2) * (Cols + 2) * sizeof(int));
Transition[0] = Transition[(Rows + 1) * (Cols + 2)] = Cols + 2;
// Start at the beginning of the image (startCol, startRow)
pImage = inputImage->imageData + startCol - 1 + startRow * inputImage->widthStep;
/*
- Paral�lelitzaci� del c�lcul de la matriu de transicions
- Fem que cada iteraci� del for el faci un thread o l'altre ( tenim 2 possibles threads )
- */
+ Paral·lelització del cà lcul de la matriu de transicions
+ Fem que cada iteració del for el faci un thread o l'altre ( tenim 2 possibles threads )
+ */
if (maskImage == NULL)
{
imatgePerimetreExtern = NULL;
@@ -184,7 +184,7 @@ namespace Blob
//Fill Transition array
for (iRow = 1; iRow < Rows + 1; iRow++) // Choose a row of Bordered image
{
- TransitionOffset = iRow*(Cols + 2); //per a que sigui paral�litzable
+ TransitionOffset = iRow*(Cols + 2); //per a que sigui paral·litzable
iTran = 0; // Index into Transition array
Tran = 0; // No transitions at row start
LastCell = borderColor;
@@ -218,12 +218,12 @@ namespace Blob
}
else
{
- //maskImage not NULL: Cal rec�rrer la m�scara tamb� per calcular la matriu de transicions
+ //maskImage not NULL: Cal recòrrer la mà scara també per calcular la matriu de transicions
char perimeter;
char *pPerimetre;
- // creem la imatge que contindr� el perimetre extern de cada pixel
+ // creem la imatge que contindrà el perimetre extern de cada pixel
imatgePerimetreExtern = cvCreateImage(cvSize(maskImage->width, maskImage->height), IPL_DEPTH_8U, 1);
cvSetZero(imatgePerimetreExtern);
@@ -255,9 +255,9 @@ namespace Blob
}
/*////////////////////////////////////////////////////////////////////////
- Calcul de la imatge amb els pixels externs
- ////////////////////////////////////////////////////////////////////////*/
- // pels pixels externs no cal calcular res pq no hi accedir-hem
+ Calcul de la imatge amb els pixels externs
+ ////////////////////////////////////////////////////////////////////////*/
+ // pels pixels externs no cal calcular res pq no hi accedir-hem
if ((iCol > 0) && (iCol < Cols))
{
if (*pMask == PIXEL_EXTERIOR)
@@ -277,7 +277,7 @@ namespace Blob
// pixels a l'est i oest de l'actual
if (iRow < imatgePerimetreExtern->height)
{
- if ((iCol>0) && (*(pMask - 1) == PIXEL_EXTERIOR)) perimeter++;
+ if ((iCol > 0) && (*(pMask - 1) == PIXEL_EXTERIOR)) perimeter++;
if ((iCol < imatgePerimetreExtern->width - 1) && (*(pMask + 1) == PIXEL_EXTERIOR)) perimeter++;
}
@@ -323,7 +323,7 @@ namespace Blob
// Last |xxx |xxxxoo |xxxxxxx|xxxxxxx|ooxxxxx|ooxxx |ooxxxxx| xxx|
// This | yyy| yyy| yyyy | yyyyy|yyyyyyy|yyyyyyy|yyyy |yyyy |
// Here o is optional
- //
+ //
// Here are the primitive tests to distinguish these 6 cases:
// A) Last end < This start - 1 OR NOT Note: -1
// B) This end < Last start OR NOT
@@ -409,7 +409,7 @@ namespace Blob
uchar imagevalue;
bool CandidatExterior = false;
- // apuntadors als blobs de la regi� actual i last
+ // apuntadors als blobs de la regió actual i last
CBlob *regionDataThisRegion, *regionDataLastRegion;
LastRegion = new int[Cols + 2];
@@ -431,7 +431,7 @@ namespace Blob
ThisIndexCount = 1;
ThisRegion[0] = 0; // Border region
- // beginning of the image
+ // beginning of the image
// en cada linia, pimage apunta al primer pixel de la fila
pImage = inputImage->imageData - 1 + startCol + startRow * inputImage->widthStep;
//the mask should be the same size as image Roi, so don't take into account the offset
@@ -457,9 +457,9 @@ namespace Blob
{
int Index = ThisOffset + j;
int TranVal = Transition[Index];
- if (TranVal > 0) ThisIndexCount = j + 1; // stop at highest
+ if (TranVal > 0) ThisIndexCount = j + 1; // stop at highest
- if (ThisRegion[j] == -1) { EndLast = 1; }
+ if (ThisRegion[j] == -1) { EndLast = 1; }
if (TranVal < 0) { EndThis = 1; }
if (EndLast > 0 && EndThis > 0) { break; }
@@ -505,7 +505,7 @@ namespace Blob
#endif
#if !IMATGE_CICLICA_HORITZONTAL
ThisStart <= 1 || ThisEnd >= Cols ||
-#endif
+#endif
GetExternPerimeter(ThisStart, ThisEnd, ThisRow, inputImage->width, inputImage->height, imatgePerimetreExtern)
)
{
@@ -601,7 +601,7 @@ namespace Blob
//afegim la cantonada a ThisRegion
if (ThisRegionNum != -1)
{
- // afegim dos vertexs si s�n diferents, nom�s
+ // afegim dos vertexs si són diferents, només
if (ThisStart - 1 != ThisEnd)
{
actualedge.x = ThisStart - 1;
@@ -615,7 +615,7 @@ namespace Blob
//afegim la cantonada a ThisRegion
if (LastRegionNum != -1 && LastRegionNum != ThisRegionNum)
{
- // afegim dos vertexs si s�n diferents, nom�s
+ // afegim dos vertexs si són diferents, només
if (ThisStart - 1 != ThisEnd)
{
actualedge.x = ThisStart - 1;
@@ -662,8 +662,8 @@ namespace Blob
SubsumedRegion = NewSubsume(SubsumedRegion, HighRegionNum);
if (CandidatExterior)
ThisExternPerimeter = GetExternPerimeter(ThisStart, ThisEnd, ThisRow,
- inputImage->width, inputImage->height,
- imatgePerimetreExtern);
+ inputImage->width, inputImage->height,
+ imatgePerimetreExtern);
}
@@ -728,8 +728,8 @@ namespace Blob
SubsumedRegion = NewSubsume(SubsumedRegion, HighRegionNum);
if (CandidatExterior)
ThisExternPerimeter = GetExternPerimeter(ThisStart, ThisEnd, ThisRow,
- inputImage->width, inputImage->height,
- imatgePerimetreExtern);
+ inputImage->width, inputImage->height,
+ imatgePerimetreExtern);
}
@@ -789,8 +789,8 @@ namespace Blob
SubsumedRegion = NewSubsume(SubsumedRegion, HighRegionNum);
if (CandidatExterior)
ThisExternPerimeter = GetExternPerimeter(ThisStart, ThisEnd, ThisRow,
- inputImage->width, inputImage->height,
- imatgePerimetreExtern);
+ inputImage->width, inputImage->height,
+ imatgePerimetreExtern);
}
else if (TestMatch && !TestKnown) // Same color and unknown
@@ -986,8 +986,8 @@ namespace Blob
SubsumedRegion = NewSubsume(SubsumedRegion, HighRegionNum);
if (CandidatExterior)
ThisExternPerimeter = GetExternPerimeter(ThisStart, ThisEnd, ThisRow,
- inputImage->width, inputImage->height,
- imatgePerimetreExtern);
+ inputImage->width, inputImage->height,
+ imatgePerimetreExtern);
}
else if (TestMatch && !TestKnown)
@@ -1077,7 +1077,7 @@ namespace Blob
//|yyyy |
#ifdef B_CONNECTIVITAT_8
- // fusionem blobs
+ // fusionem blobs
if (TestMatch)
{
if (ThisRegionNum > LastRegionNum)
@@ -1159,7 +1159,7 @@ namespace Blob
}
- // compute the mean gray level and its std deviation
+ // compute the mean gray level and its std deviation
if (ThisRow <= Rows)
{
pImageAux = pImage + ThisStart;
@@ -1170,9 +1170,9 @@ namespace Blob
{
if (maskImage != NULL)
{
- // nom�s es t� en compte el valor del p�xel de la
- // imatge que queda dins de la m�scara
- // (de pas, comptem el nombre de p�xels de la m�scara)
+ // només es té en compte el valor del pÃxel de la
+ // imatge que queda dins de la mà scara
+ // (de pas, comptem el nombre de pÃxels de la mà scara)
if (((unsigned char)*pMaskAux) != PIXEL_EXTERIOR)
{
imagevalue = (unsigned char)(*pImageAux);
@@ -1200,7 +1200,7 @@ namespace Blob
// compute the min and max values of X and Y
if (ThisStart - 1 < (int)ThisMinX) ThisMinX = (float)(ThisStart - 1);
if (ThisMinX < (float) 0.0) ThisMinX = (float) 0.0;
- if (ThisEnd >(int) ThisMaxX) ThisMaxX = (float)ThisEnd;
+ if (ThisEnd > (int) ThisMaxX) ThisMaxX = (float)ThisEnd;
if (ThisRow - 1 < ThisMinY) ThisMinY = ThisRow - 1;
if (ThisMinY < (float) 0.0) ThisMinY = (float) 0.0;
@@ -1242,10 +1242,10 @@ namespace Blob
} // end Main loop
if (ErrorFlag != 0) {
- delete[] Transition;
- delete[] ThisRegion;
- delete[] LastRegion;
- return false;
+ delete[] Transition;
+ delete[] ThisRegion;
+ delete[] LastRegion;
+ return false;
}
// ens situem al primer pixel de la seguent fila
pImage = inputImage->imageData - 1 + startCol + (ThisRow + startRow) * inputImage->widthStep;
@@ -1254,19 +1254,19 @@ namespace Blob
pMask = maskImage->imageData - 1 + ThisRow * maskImage->widthStep;
} // end Loop over all rows
- // eliminem l'�rea del marc
- // i tamb� els p�xels de la m�scara
+ // eliminem l'Ã rea del marc
+ // i també els pÃxels de la mà scara
// ATENCIO: PERFER: el fet de restar el nombre_pixels_mascara del
- // blob 0 nom�s ser� cert si la m�scara t� contacte amb el marc.
- // Si no, s'haur� de trobar quin �s el blob que cont� m�s p�xels del
+ // blob 0 només serà cert si la mà scara té contacte amb el marc.
+ // Si no, s'haurà de trobar quin és el blob que conté més pÃxels del
// compte.
RegionData[0]->area -= (Rows + 1 + Cols + 1) * 2 + nombre_pixels_mascara;
- // eliminem el per�metre de m�s:
- // - sense marc: 2m+2n (per�metre extern)
+ // eliminem el perÃmetre de més:
+ // - sense marc: 2m+2n (perÃmetre extern)
// - amb marc: 2(m+2)+2(n+2) = 2m+2n + 8
- // (segurament no �s del tot acurat)
- // (i amb les m�scares encara menys...)
+ // (segurament no és del tot acurat)
+ // (i amb les mà scares encara menys...)
RegionData[0]->perimeter -= 8.0;
// Condense the list
@@ -1306,7 +1306,7 @@ namespace Blob
if (findmoments)
{
iti = RegionData.begin();
- // Normalize summation fields into moments
+ // Normalize summation fields into moments
for (ThisRegionNum = 0; ThisRegionNum <= HighRegionNum; ThisRegionNum++, iti++)
{
blobActual = *iti;
@@ -1340,10 +1340,10 @@ namespace Blob
blobActual->stddev =
sqrt(
(
- blobActual->stddev * blobActual->area -
- blobActual->mean * blobActual->mean
- ) /
- (blobActual->area*(blobActual->area - 1))
+ blobActual->stddev * blobActual->area -
+ blobActual->mean * blobActual->mean
+ ) /
+ (blobActual->area*(blobActual->area - 1))
);
}
else
@@ -1385,16 +1385,16 @@ namespace Blob
}
else
{
- subsumed = (int*)realloc(subsumed, (index_subsume + 1)*sizeof(int));
+ subsumed = (int*)realloc(subsumed, (index_subsume + 1) * sizeof(int));
}
subsumed[index_subsume] = 0;
return subsumed;
}
/**
- Fusiona dos blobs i afegeix el blob les caracter�stiques del blob RegionData[HiNum]
- al blob RegionData[LoNum]. Al final allibera el blob de RegionData[HiNum]
- */
+ Fusiona dos blobs i afegeix el blob les caracterÃstiques del blob RegionData[HiNum]
+ al blob RegionData[LoNum]. Al final allibera el blob de RegionData[HiNum]
+ */
void Subsume(blob_vector &RegionData,
int HighRegionNum,
int* SubsumedRegion,
@@ -1440,28 +1440,28 @@ namespace Blob
// marquem el blob com a lliure
blobHi->etiqueta = -1;
- // Atenci�!!!! abans d'eliminar els edges
+ // Atenció!!!! abans d'eliminar els edges
// s'han de traspassar del blob HiNum al blob LoNum
blobHi->CopyEdges(*blobLo);
blobHi->ClearEdges();
}
/**
- - FUNCI�: GetExternPerimeter
- - FUNCIONALITAT: Retorna el perimetre extern d'una run lenght
- - PAR�METRES:
- - start: columna d'inici del run
- - end: columna final del run
- - row: fila del run
- - maskImage: m�scara pels pixels externs
- - RESULTAT:
- - quantitat de perimetre extern d'un run, suposant que �s un blob
- d'una �nica fila d'al�ada
- - RESTRICCIONS:
- - AUTOR:
- - DATA DE CREACI�: 2006/02/27
- - MODIFICACI�: Data. Autor. Descripci�.
- */
+ - FUNCIÓ: GetExternPerimeter
+ - FUNCIONALITAT: Retorna el perimetre extern d'una run lenght
+ - PARÀMETRES:
+ - start: columna d'inici del run
+ - end: columna final del run
+ - row: fila del run
+ - maskImage: mà scara pels pixels externs
+ - RESULTAT:
+ - quantitat de perimetre extern d'un run, suposant que és un blob
+ d'una única fila d'alçada
+ - RESTRICCIONS:
+ - AUTOR:
+ - DATA DE CREACIÓ: 2006/02/27
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
double GetExternPerimeter(int start, int end, int row, int width, int height, IplImage *imatgePerimetreExtern)
{
double perimeter = 0.0f;
@@ -1474,7 +1474,7 @@ namespace Blob
if (row >= height - 1) perimeter += start - end;
- // comprovem els pixels que toquen a la m�scara (si s'escau)
+ // comprovem els pixels que toquen a la mà scara (si s'escau)
if (imatgePerimetreExtern != NULL)
{
if (row <= 0 || row >= height) return perimeter;
diff --git a/package_bgs/jmo/BlobExtraction.h b/package_bgs/MultiLayer/BlobExtraction.h
similarity index 96%
rename from package_bgs/jmo/BlobExtraction.h
rename to package_bgs/MultiLayer/BlobExtraction.h
index 9f47b02..d8bd1af 100644
--- a/package_bgs/jmo/BlobExtraction.h
+++ b/package_bgs/MultiLayer/BlobExtraction.h
@@ -49,10 +49,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
//* Email: dgrossman@cdr.stanford.edu *//
//* Acknowledgement: the algorithm has been around > 20 yrs *//
//***********************************************************//
-
-
-#if !defined(_CLASSE_BLOBEXTRACTION_INCLUDED)
-#define _CLASSE_BLOBEXTRACTION_INCLUDED
+#pragma once
namespace Blob
{
@@ -71,6 +68,3 @@ namespace Blob
//! Retorna el perimetre extern d'una run lenght
double GetExternPerimeter(int start, int end, int row, int width, int height, IplImage *maskImage);
}
-
-#endif //_CLASSE_BLOBEXTRACTION_INCLUDED
-
diff --git a/package_bgs/jmo/BlobLibraryConfiguration.h b/package_bgs/MultiLayer/BlobLibraryConfiguration.h
similarity index 95%
rename from package_bgs/jmo/BlobLibraryConfiguration.h
rename to package_bgs/MultiLayer/BlobLibraryConfiguration.h
index b864fc7..0ba18fc 100644
--- a/package_bgs/jmo/BlobLibraryConfiguration.h
+++ b/package_bgs/MultiLayer/BlobLibraryConfiguration.h
@@ -43,15 +43,16 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
/************************************************************************
BlobLibraryConfiguration.h
-FUNCIONALITAT: Configuraci� del comportament global de la llibreria
+FUNCIONALITAT: Configuració del comportament global de la llibreria
AUTOR: Inspecta S.L.
-MODIFICACIONS (Modificaci�, Autor, Data):
+MODIFICACIONS (Modificació, Autor, Data):
FUNCTIONALITY: Global configuration of the library
AUTHOR: Inspecta S.L.
MODIFICATIONS (Modification, Author, Date):
**************************************************************************/
+#pragma once
//! Indica si es volen fer servir les MatrixCV o no
//! Use/Not use the MatrixCV class
diff --git a/package_bgs/MultiLayer/BlobResult.cpp b/package_bgs/MultiLayer/BlobResult.cpp
new file mode 100644
index 0000000..1ec60e3
--- /dev/null
+++ b/package_bgs/MultiLayer/BlobResult.cpp
@@ -0,0 +1,847 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/* --- --- ---
+* Copyright (C) 2008--2010 Idiap Research Institute (.....@idiap.ch)
+* All rights reserved.
+*
+* Redistribution and use in source and binary forms, with or without
+* modification, are permitted provided that the following conditions
+* are met:
+* 1. Redistributions of source code must retain the above copyright
+* notice, this list of conditions and the following disclaimer.
+* 2. Redistributions in binary form must reproduce the above copyright
+* notice, this list of conditions and the following disclaimer in the
+* documentation and/or other materials provided with the distribution.
+* 3. The name of the author may not be used to endorse or promote products
+* derived from this software without specific prior written permission.
+*
+* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
+* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
+* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
+* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
+* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
+* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
+* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+/************************************************************************
+BlobResult.cpp
+
+FUNCIONALITAT: Implementació de la classe CBlobResult
+AUTOR: Inspecta S.L.
+MODIFICACIONS (Modificació, Autor, Data):
+
+**************************************************************************/
+
+#include <limits.h>
+#include <stdio.h>
+#include <functional>
+#include <algorithm>
+#include "BlobResult.h"
+#include "BlobExtraction.h"
+
+/**************************************************************************
+Constructors / Destructors
+**************************************************************************/
+
+namespace Blob
+{
+
+ /**
+ - FUNCIÓ: CBlobResult
+ - FUNCIONALITAT: Constructor estandard.
+ - PARÀMETRES:
+ - RESULTAT:
+ - Crea un CBlobResult sense cap blob
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobResult
+ - FUNCTIONALITY: Standard constructor
+ - PARAMETERS:
+ - RESULT:
+ - creates an empty set of blobs
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlobResult::CBlobResult()
+ {
+ m_blobs = blob_vector();
+ }
+
+ /**
+ - FUNCIÓ: CBlobResult
+ - FUNCIONALITAT: Constructor a partir d'una imatge. Inicialitza la seqüència de blobs
+ amb els blobs resultants de l'anà lisi de blobs de la imatge.
+ - PARÀMETRES:
+ - source: imatge d'on s'extreuran els blobs
+ - mask: mà scara a aplicar. Només es calcularan els blobs on la mà scara sigui
+ diferent de 0. Els blobs que toquin a un pixel 0 de la mà scara seran
+ considerats exteriors.
+ - threshold: llindar que s'aplicarà a la imatge source abans de calcular els blobs
+ - findmoments: indica si s'han de calcular els moments de cada blob
+ - RESULTAT:
+ - objecte CBlobResult amb els blobs de la imatge source
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlob
+ - FUNCTIONALITY: Constructor from an image. Fills an object with all the blobs in
+ the image
+ - PARAMETERS:
+ - source: image to extract the blobs from
+ - mask: optional mask to apply. The blobs will be extracted where the mask is
+ not 0. All the neighbouring blobs where the mask is 0 will be extern blobs
+ - threshold: threshold level to apply to the image before computing blobs
+ - findmoments: true to calculate the blob moments (slower)
+ - RESULT:
+ - object with all the blobs in the image. It throws an EXCEPCIO_CALCUL_BLOBS
+ if some error appears in the BlobAnalysis function
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlobResult::CBlobResult(IplImage *source, IplImage *mask, int threshold, bool findmoments)
+ {
+ bool success;
+
+ try
+ {
+ // cridem la funció amb el marc a true=1=blanc (aixà no unirà els blobs externs)
+ success = BlobAnalysis(source, (uchar)threshold, mask, true, findmoments, m_blobs);
+ }
+ catch (...)
+ {
+ success = false;
+ }
+
+ if (!success) throw EXCEPCIO_CALCUL_BLOBS;
+ }
+
+ /**
+ - FUNCIÓ: CBlobResult
+ - FUNCIONALITAT: Constructor de còpia. Inicialitza la seqüència de blobs
+ amb els blobs del parà metre.
+ - PARÀMETRES:
+ - source: objecte que es copiarÃ
+ - RESULTAT:
+ - objecte CBlobResult amb els blobs de l'objecte source
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobResult
+ - FUNCTIONALITY: Copy constructor
+ - PARAMETERS:
+ - source: object to copy
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlobResult::CBlobResult(const CBlobResult &source)
+ {
+ m_blobs = blob_vector(source.GetNumBlobs());
+
+ // creem el nou a partir del passat com a parà metre
+ m_blobs = blob_vector(source.GetNumBlobs());
+ // copiem els blobs de l'origen a l'actual
+ blob_vector::const_iterator pBlobsSrc = source.m_blobs.begin();
+ blob_vector::iterator pBlobsDst = m_blobs.begin();
+
+ while (pBlobsSrc != source.m_blobs.end())
+ {
+ // no podem cridar a l'operador = ja que blob_vector és un
+ // vector de CBlob*. Per tant, creem un blob nou a partir del
+ // blob original
+ *pBlobsDst = new CBlob(**pBlobsSrc);
+ ++pBlobsSrc;
+ ++pBlobsDst;
+ }
+ }
+
+
+
+ /**
+ - FUNCIÓ: ~CBlobResult
+ - FUNCIONALITAT: Destructor estandard.
+ - PARÀMETRES:
+ - RESULTAT:
+ - Allibera la memòria reservada de cadascun dels blobs de la classe
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: ~CBlobResult
+ - FUNCTIONALITY: Destructor
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlobResult::~CBlobResult()
+ {
+ ClearBlobs();
+ }
+
+ /**************************************************************************
+ Operadors / Operators
+ **************************************************************************/
+
+
+ /**
+ - FUNCIÓ: operador =
+ - FUNCIONALITAT: Assigna un objecte source a l'actual
+ - PARÀMETRES:
+ - source: objecte a assignar
+ - RESULTAT:
+ - Substitueix els blobs actuals per els de l'objecte source
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: Assigment operator
+ - FUNCTIONALITY:
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlobResult& CBlobResult::operator=(const CBlobResult& source)
+ {
+ // si ja són el mateix, no cal fer res
+ if (this != &source)
+ {
+ // alliberem el conjunt de blobs antic
+ for (int i = 0; i < GetNumBlobs(); i++)
+ {
+ delete m_blobs[i];
+ }
+ m_blobs.clear();
+ // creem el nou a partir del passat com a parà metre
+ m_blobs = blob_vector(source.GetNumBlobs());
+ // copiem els blobs de l'origen a l'actual
+ blob_vector::const_iterator pBlobsSrc = source.m_blobs.begin();
+ blob_vector::iterator pBlobsDst = m_blobs.begin();
+
+ while (pBlobsSrc != source.m_blobs.end())
+ {
+ // no podem cridar a l'operador = ja que blob_vector és un
+ // vector de CBlob*. Per tant, creem un blob nou a partir del
+ // blob original
+ *pBlobsDst = new CBlob(**pBlobsSrc);
+ ++pBlobsSrc;
+ ++pBlobsDst;
+ }
+ }
+ return *this;
+ }
+
+
+ /**
+ - FUNCIÓ: operador +
+ - FUNCIONALITAT: Concatena els blobs de dos CBlobResult
+ - PARÀMETRES:
+ - source: d'on s'agafaran els blobs afegits a l'actual
+ - RESULTAT:
+ - retorna un nou CBlobResult amb els dos CBlobResult concatenats
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - NOTA: per la implementació, els blobs del parà metre es posen en ordre invers
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: + operator
+ - FUNCTIONALITY: Joins the blobs in source with the current ones
+ - PARAMETERS:
+ - source: object to copy the blobs
+ - RESULT:
+ - object with the actual blobs and the source blobs
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlobResult CBlobResult::operator+(const CBlobResult& source)
+ {
+ //creem el resultat a partir dels blobs actuals
+ CBlobResult resultat(*this);
+
+ // reservem memòria per als nous blobs
+ resultat.m_blobs.resize(resultat.GetNumBlobs() + source.GetNumBlobs());
+
+ // declarem els iterador per recòrrer els blobs d'origen i desti
+ blob_vector::const_iterator pBlobsSrc = source.m_blobs.begin();
+ blob_vector::iterator pBlobsDst = resultat.m_blobs.end();
+
+ // insertem els blobs de l'origen a l'actual
+ while (pBlobsSrc != source.m_blobs.end())
+ {
+ --pBlobsDst;
+ *pBlobsDst = new CBlob(**pBlobsSrc);
+ ++pBlobsSrc;
+ }
+
+ return resultat;
+ }
+
+ /**************************************************************************
+ Operacions / Operations
+ **************************************************************************/
+
+ /**
+ - FUNCIÓ: AddBlob
+ - FUNCIONALITAT: Afegeix un blob al conjunt
+ - PARÀMETRES:
+ - blob: blob a afegir
+ - RESULTAT:
+ - modifica el conjunt de blobs actual
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 2006/03/01
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ void CBlobResult::AddBlob(CBlob *blob)
+ {
+ if (blob != NULL)
+ m_blobs.push_back(new CBlob(blob));
+ }
+
+
+ /**
+ - FUNCIÓ: GetSTLResult
+ - FUNCIONALITAT: Calcula el resultat especificat sobre tots els blobs de la classe
+ - PARÀMETRES:
+ - evaluador: Qualsevol objecte derivat de COperadorBlob
+ - RESULTAT:
+ - Retorna un array de double's STL amb el resultat per cada blob
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: GetResult
+ - FUNCTIONALITY: Computes the function evaluador on all the blobs of the class
+ and returns a vector with the result
+ - PARAMETERS:
+ - evaluador: function to apply to each blob (any object derived from the
+ COperadorBlob class )
+ - RESULT:
+ - vector with all the results in the same order as the blobs
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double_stl_vector CBlobResult::GetSTLResult(funcio_calculBlob *evaluador) const
+ {
+ if (GetNumBlobs() <= 0)
+ {
+ return double_stl_vector();
+ }
+
+ // definim el resultat
+ double_stl_vector result = double_stl_vector(GetNumBlobs());
+ // i iteradors sobre els blobs i el resultat
+ double_stl_vector::iterator itResult = result.begin();
+ blob_vector::const_iterator itBlobs = m_blobs.begin();
+
+ // avaluem la funció en tots els blobs
+ while (itBlobs != m_blobs.end())
+ {
+ *itResult = (*evaluador)(**itBlobs);
+ ++itBlobs;
+ ++itResult;
+ }
+ return result;
+ }
+
+ /**
+ - FUNCIÓ: GetNumber
+ - FUNCIONALITAT: Calcula el resultat especificat sobre un únic blob de la classe
+ - PARÀMETRES:
+ - evaluador: Qualsevol objecte derivat de COperadorBlob
+ - indexblob: número de blob del que volem calcular el resultat.
+ - RESULTAT:
+ - Retorna un double amb el resultat
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: GetNumber
+ - FUNCTIONALITY: Computes the function evaluador on a blob of the class
+ - PARAMETERS:
+ - indexBlob: index of the blob to compute the function
+ - evaluador: function to apply to each blob (any object derived from the
+ COperadorBlob class )
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobResult::GetNumber(int indexBlob, funcio_calculBlob *evaluador) const
+ {
+ if (indexBlob < 0 || indexBlob >= GetNumBlobs())
+ RaiseError(EXCEPTION_BLOB_OUT_OF_BOUNDS);
+ return (*evaluador)(*m_blobs[indexBlob]);
+ }
+
+ /////////////////////////// FILTRAT DE BLOBS ////////////////////////////////////
+
+ /**
+ - FUNCIÓ: Filter
+ - FUNCIONALITAT: Filtra els blobs de la classe i deixa el resultat amb només
+ els blobs que han passat el filtre.
+ El filtrat es basa en especificar condicions sobre un resultat dels blobs
+ i seleccionar (o excloure) aquells blobs que no compleixen una determinada
+ condicio
+ - PARÀMETRES:
+ - dst: variable per deixar els blobs filtrats
+ - filterAction: acció de filtrat. Incloure els blobs trobats (B_INCLUDE),
+ o excloure els blobs trobats (B_EXCLUDE)
+ - evaluador: Funció per evaluar els blobs (qualsevol objecte derivat de COperadorBlob
+ - Condition: tipus de condició que ha de superar la mesura (FilterType)
+ sobre cada blob per a ser considerat.
+ B_EQUAL,B_NOT_EQUAL,B_GREATER,B_LESS,B_GREATER_OR_EQUAL,
+ B_LESS_OR_EQUAL,B_INSIDE,B_OUTSIDE
+ - LowLimit: valor numèric per a la comparació (Condition) de la mesura (FilterType)
+ - HighLimit: valor numèric per a la comparació (Condition) de la mesura (FilterType)
+ (només té sentit per a aquelles condicions que tenen dos valors
+ (B_INSIDE, per exemple).
+ - RESULTAT:
+ - Deixa els blobs resultants del filtrat a destination
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: Filter
+ - FUNCTIONALITY: Get some blobs from the class based on conditions on measures
+ of the blobs.
+ - PARAMETERS:
+ - dst: where to store the selected blobs
+ - filterAction: B_INCLUDE: include the blobs which pass the filter in the result
+ B_EXCLUDE: exclude the blobs which pass the filter in the result
+ - evaluador: Object to evaluate the blob
+ - Condition: How to decide if the result returned by evaluador on each blob
+ is included or not. It can be:
+ B_EQUAL,B_NOT_EQUAL,B_GREATER,B_LESS,B_GREATER_OR_EQUAL,
+ B_LESS_OR_EQUAL,B_INSIDE,B_OUTSIDE
+ - LowLimit: numerical value to evaluate the Condition on evaluador(blob)
+ - HighLimit: numerical value to evaluate the Condition on evaluador(blob).
+ Only useful for B_INSIDE and B_OUTSIDE
+ - RESULT:
+ - It returns on dst the blobs that accomplish (B_INCLUDE) or discards (B_EXCLUDE)
+ the Condition on the result returned by evaluador on each blob
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlobResult::Filter(CBlobResult &dst,
+ int filterAction,
+ funcio_calculBlob *evaluador,
+ int condition,
+ double lowLimit, double highLimit /*=0*/)
+
+ {
+ int i, numBlobs;
+ bool resultavaluacio;
+ double_stl_vector avaluacioBlobs;
+ double_stl_vector::iterator itavaluacioBlobs;
+
+ if (GetNumBlobs() <= 0) return;
+ if (!evaluador) return;
+ //avaluem els blobs amb la funció pertinent
+ avaluacioBlobs = GetSTLResult(evaluador);
+ itavaluacioBlobs = avaluacioBlobs.begin();
+ numBlobs = GetNumBlobs();
+ switch (condition)
+ {
+ case B_EQUAL:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = *itavaluacioBlobs == lowLimit;
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_NOT_EQUAL:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = *itavaluacioBlobs != lowLimit;
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_GREATER:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = *itavaluacioBlobs > lowLimit;
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_LESS:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = *itavaluacioBlobs < lowLimit;
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_GREATER_OR_EQUAL:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = *itavaluacioBlobs >= lowLimit;
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_LESS_OR_EQUAL:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = *itavaluacioBlobs <= lowLimit;
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_INSIDE:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = (*itavaluacioBlobs >= lowLimit) && (*itavaluacioBlobs <= highLimit);
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ case B_OUTSIDE:
+ for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
+ {
+ resultavaluacio = (*itavaluacioBlobs < lowLimit) || (*itavaluacioBlobs > highLimit);
+ if ((resultavaluacio && filterAction == B_INCLUDE) ||
+ (!resultavaluacio && filterAction == B_EXCLUDE))
+ {
+ dst.m_blobs.push_back(new CBlob(GetBlob(i)));
+ }
+ }
+ break;
+ }
+
+
+ // en cas de voler filtrar un CBlobResult i deixar-ho en el mateix CBlobResult
+ // ( operacio inline )
+ if (&dst == this)
+ {
+ // esborrem els primers blobs ( que són els originals )
+ // ja que els tindrem replicats al final si passen el filtre
+ blob_vector::iterator itBlobs = m_blobs.begin();
+ for (int i = 0; i < numBlobs; i++)
+ {
+ delete *itBlobs;
+ ++itBlobs;
+ }
+ m_blobs.erase(m_blobs.begin(), itBlobs);
+ }
+ }
+
+
+ /**
+ - FUNCIÓ: GetBlob
+ - FUNCIONALITAT: Retorna un blob si aquest existeix (index != -1)
+ - PARÀMETRES:
+ - indexblob: index del blob a retornar
+ - RESULTAT:
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /*
+ - FUNCTION: GetBlob
+ - FUNCTIONALITY: Gets the n-th blob (without ordering the blobs)
+ - PARAMETERS:
+ - indexblob: index in the blob array
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlob CBlobResult::GetBlob(int indexblob) const
+ {
+ if (indexblob < 0 || indexblob >= GetNumBlobs())
+ RaiseError(EXCEPTION_BLOB_OUT_OF_BOUNDS);
+
+ return *m_blobs[indexblob];
+ }
+ CBlob *CBlobResult::GetBlob(int indexblob)
+ {
+ if (indexblob < 0 || indexblob >= GetNumBlobs())
+ RaiseError(EXCEPTION_BLOB_OUT_OF_BOUNDS);
+
+ return m_blobs[indexblob];
+ }
+
+ /**
+ - FUNCIÓ: GetNthBlob
+ - FUNCIONALITAT: Retorna l'enèssim blob segons un determinat criteri
+ - PARÀMETRES:
+ - criteri: criteri per ordenar els blobs (objectes derivats de COperadorBlob)
+ - nBlob: index del blob a retornar
+ - dst: on es retorna el resultat
+ - RESULTAT:
+ - retorna el blob nBlob a dst ordenant els blobs de la classe segons el criteri
+ en ordre DESCENDENT. Per exemple, per obtenir el blob major:
+ GetNthBlob( CBlobGetArea(), 0, blobMajor );
+ GetNthBlob( CBlobGetArea(), 1, blobMajor ); (segon blob més gran)
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /*
+ - FUNCTION: GetNthBlob
+ - FUNCTIONALITY: Gets the n-th blob ordering first the blobs with some criteria
+ - PARAMETERS:
+ - criteri: criteria to order the blob array
+ - nBlob: index of the returned blob in the ordered blob array
+ - dst: where to store the result
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlobResult::GetNthBlob(funcio_calculBlob *criteri, int nBlob, CBlob &dst) const
+ {
+ // verifiquem que no estem accedint fora el vector de blobs
+ if (nBlob < 0 || nBlob >= GetNumBlobs())
+ {
+ //RaiseError( EXCEPTION_BLOB_OUT_OF_BOUNDS );
+ dst = CBlob();
+ return;
+ }
+
+ double_stl_vector avaluacioBlobs, avaluacioBlobsOrdenat;
+ double valorEnessim;
+
+ //avaluem els blobs amb la funció pertinent
+ avaluacioBlobs = GetSTLResult(criteri);
+
+ avaluacioBlobsOrdenat = double_stl_vector(GetNumBlobs());
+
+ // obtenim els nBlob primers resultats (en ordre descendent)
+ std::partial_sort_copy(avaluacioBlobs.begin(),
+ avaluacioBlobs.end(),
+ avaluacioBlobsOrdenat.begin(),
+ avaluacioBlobsOrdenat.end(),
+ std::greater<double>());
+
+ valorEnessim = avaluacioBlobsOrdenat[nBlob];
+
+ // busquem el primer blob que té el valor n-ssim
+ double_stl_vector::const_iterator itAvaluacio = avaluacioBlobs.begin();
+
+ bool trobatBlob = false;
+ int indexBlob = 0;
+ while (itAvaluacio != avaluacioBlobs.end() && !trobatBlob)
+ {
+ if (*itAvaluacio == valorEnessim)
+ {
+ trobatBlob = true;
+ dst = CBlob(GetBlob(indexBlob));
+ }
+ ++itAvaluacio;
+ indexBlob++;
+ }
+ }
+
+ /**
+ - FUNCIÓ: ClearBlobs
+ - FUNCIONALITAT: Elimina tots els blobs de l'objecte
+ - PARÀMETRES:
+ - RESULTAT:
+ - Allibera tota la memòria dels blobs
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borràs Navarra
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /*
+ - FUNCTION: ClearBlobs
+ - FUNCTIONALITY: Clears all the blobs from the object and releases all its memory
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlobResult::ClearBlobs()
+ {
+ /*for( int i = 0; i < GetNumBlobs(); i++ )
+ {
+ delete m_blobs[i];
+ }*/
+ blob_vector::iterator itBlobs = m_blobs.begin();
+ while (itBlobs != m_blobs.end())
+ {
+ delete *itBlobs;
+ ++itBlobs;
+ }
+
+ m_blobs.clear();
+ }
+
+ /**
+ - FUNCIÓ: RaiseError
+ - FUNCIONALITAT: Funció per a notificar errors al l'usuari (en debug) i llença
+ les excepcions
+ - PARÀMETRES:
+ - errorCode: codi d'error
+ - RESULTAT:
+ - Ensenya un missatge a l'usuari (en debug) i llença una excepció
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borràs Navarra
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /*
+ - FUNCTION: RaiseError
+ - FUNCTIONALITY: Error handling function
+ - PARAMETERS:
+ - errorCode: reason of the error
+ - RESULT:
+ - in _DEBUG version, shows a message box with the error. In release is silent.
+ In both cases throws an exception with the error.
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlobResult::RaiseError(const int errorCode) const
+ {
+ throw errorCode;
+ }
+
+
+
+ /**************************************************************************
+ Auxiliars / Auxiliary functions
+ **************************************************************************/
+
+
+ /**
+ - FUNCIÓ: PrintBlobs
+ - FUNCIONALITAT: Escriu els parà metres (à rea, perÃmetre, exterior, mitjana)
+ de tots els blobs a un fitxer.
+ - PARÀMETRES:
+ - nom_fitxer: path complet del fitxer amb el resultat
+ - RESULTAT:
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /*
+ - FUNCTION: PrintBlobs
+ - FUNCTIONALITY: Prints some blob features in an ASCII file
+ - PARAMETERS:
+ - nom_fitxer: full path + filename to generate
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlobResult::PrintBlobs(char *nom_fitxer) const
+ {
+ double_stl_vector area, /*perimetre,*/ exterior, mitjana, compacitat, longitud,
+ externPerimeter, perimetreConvex, perimetre;
+ int i;
+ FILE *fitxer_sortida;
+
+ area = GetSTLResult(CBlobGetArea());
+ perimetre = GetSTLResult(CBlobGetPerimeter());
+ exterior = GetSTLResult(CBlobGetExterior());
+ mitjana = GetSTLResult(CBlobGetMean());
+ compacitat = GetSTLResult(CBlobGetCompactness());
+ longitud = GetSTLResult(CBlobGetLength());
+ externPerimeter = GetSTLResult(CBlobGetExternPerimeter());
+ perimetreConvex = GetSTLResult(CBlobGetHullPerimeter());
+
+ fitxer_sortida = fopen(nom_fitxer, "w");
+
+ for (i = 0; i < GetNumBlobs(); i++)
+ {
+ fprintf(fitxer_sortida, "blob %d ->\t a=%7.0f\t p=%8.2f (%8.2f extern)\t pconvex=%8.2f\t ext=%.0f\t m=%7.2f\t c=%3.2f\t l=%8.2f\n",
+ i, area[i], perimetre[i], externPerimeter[i], perimetreConvex[i], exterior[i], mitjana[i], compacitat[i], longitud[i]);
+ }
+ fclose(fitxer_sortida);
+
+ }
+
+}
diff --git a/package_bgs/jmo/BlobResult.h b/package_bgs/MultiLayer/BlobResult.h
similarity index 80%
rename from package_bgs/jmo/BlobResult.h
rename to package_bgs/MultiLayer/BlobResult.h
index b232a97..aa3e37b 100644
--- a/package_bgs/jmo/BlobResult.h
+++ b/package_bgs/MultiLayer/BlobResult.h
@@ -40,29 +40,26 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
-/************************************************************************
- BlobResult.h
+ /************************************************************************
+ BlobResult.h
- FUNCIONALITAT: Definici� de la classe CBlobResult
- AUTOR: Inspecta S.L.
- MODIFICACIONS (Modificaci�, Autor, Data):
+ FUNCIONALITAT: Definició de la classe CBlobResult
+ AUTOR: Inspecta S.L.
+ MODIFICACIONS (Modificació, Autor, Data):
- FUNCTIONALITY: Definition of the CBlobResult class
- AUTHOR: Inspecta S.L.
- MODIFICATIONS (Modification, Author, Date):
+ FUNCTIONALITY: Definition of the CBlobResult class
+ AUTHOR: Inspecta S.L.
+ MODIFICATIONS (Modification, Author, Date):
- **************************************************************************/
+ **************************************************************************/
#pragma once
-#if !defined(_CLASSE_BLOBRESULT_INCLUDED)
-#define _CLASSE_BLOBRESULT_INCLUDED
-
#include "BlobLibraryConfiguration.h"
#include <math.h>
-//#include "cxcore.h"
+ //#include "cxcore.h"
#include <vector>
#include <functional>
-#include <opencv2/core/types_c.h>
+#include "OpenCvLegacyIncludes.h"
#include "blob.h"
typedef std::vector<double> double_stl_vector;
@@ -71,8 +68,8 @@ typedef std::vector<double> double_stl_vector;
Filtres / Filters
**************************************************************************/
-//! accions que es poden fer amb els filtres
-//! Actions performed by a filter (include or exclude blobs)
+ //! accions que es poden fer amb els filtres
+ //! Actions performed by a filter (include or exclude blobs)
#define B_INCLUDE 1L
#define B_EXCLUDE 2L
@@ -92,23 +89,23 @@ typedef std::vector<double> double_stl_vector;
Excepcions / Exceptions
**************************************************************************/
-//! Excepcions llen�ades per les funcions:
+ //! Excepcions llençades per les funcions:
#define EXCEPTION_BLOB_OUT_OF_BOUNDS 1000
#define EXCEPCIO_CALCUL_BLOBS 1001
namespace Blob
{
- //! definici� de que es un vector de blobs
+ //! definició de que es un vector de blobs
typedef std::vector<CBlob*> blob_vector;
/**
- Classe que cont� un conjunt de blobs i permet extreure'n propietats
- o filtrar-los segons determinats criteris.
- Class to calculate the blobs of an image and calculate some properties
- on them. Also, the class provides functions to filter the blobs using
- some criteria.
- */
+ Classe que conté un conjunt de blobs i permet extreure'n propietats
+ o filtrar-los segons determinats criteris.
+ Class to calculate the blobs of an image and calculate some properties
+ on them. Also, the class provides functions to filter the blobs using
+ some criteria.
+ */
class CBlobResult
{
public:
@@ -119,7 +116,7 @@ namespace Blob
//! constructor a partir d'una imatge
//! Image constructor, it creates an object with the blobs of the image
CBlobResult(IplImage *source, IplImage *mask, int threshold, bool findmoments);
- //! constructor de c�pia
+ //! constructor de còpia
//! Copy constructor
CBlobResult(const CBlobResult &source);
//! Destructor
@@ -139,7 +136,7 @@ namespace Blob
#ifdef MATRIXCV_ACTIU
//! Calcula un valor sobre tots els blobs de la classe retornant una MatrixCV
//! Computes some property on all the blobs of the class
- double_vector GetResult( funcio_calculBlob *evaluador ) const;
+ double_vector GetResult(funcio_calculBlob *evaluador) const;
#endif
//! Calcula un valor sobre tots els blobs de la classe retornant un std::vector<double>
//! Computes some property on all the blobs of the class
@@ -149,17 +146,17 @@ namespace Blob
//! Computes some property on one blob of the class
double GetNumber(int indexblob, funcio_calculBlob *evaluador) const;
- //! Retorna aquells blobs que compleixen les condicions del filtre en el destination
+ //! Retorna aquells blobs que compleixen les condicions del filtre en el destination
//! Filters the blobs of the class using some property
void Filter(CBlobResult &dst,
int filterAction, funcio_calculBlob *evaluador,
int condition, double lowLimit, double highLimit = 0);
- //! Retorna l'en�ssim blob segons un determinat criteri
+ //! Retorna l'enèssim blob segons un determinat criteri
//! Sorts the blobs of the class acording to some criteria and returns the n-th blob
void GetNthBlob(funcio_calculBlob *criteri, int nBlob, CBlob &dst) const;
- //! Retorna el blob en�ssim
+ //! Retorna el blob enèssim
//! Gets the n-th blob of the class ( without sorting )
CBlob GetBlob(int indexblob) const;
CBlob *GetBlob(int indexblob);
@@ -185,7 +182,7 @@ namespace Blob
private:
- //! Funci� per gestionar els errors
+ //! Funció per gestionar els errors
//! Function to manage the errors
void RaiseError(const int errorCode) const;
@@ -197,6 +194,3 @@ namespace Blob
};
}
-
-#endif // !defined(_CLASSE_BLOBRESULT_INCLUDED)
-
diff --git a/package_bgs/jmo/CMultiLayerBGS.cpp b/package_bgs/MultiLayer/CMultiLayerBGS.cpp
similarity index 99%
rename from package_bgs/jmo/CMultiLayerBGS.cpp
rename to package_bgs/MultiLayer/CMultiLayerBGS.cpp
index 6daa9b9..4341736 100644
--- a/package_bgs/jmo/CMultiLayerBGS.cpp
+++ b/package_bgs/MultiLayer/CMultiLayerBGS.cpp
@@ -53,7 +53,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <fstream> // file I/O
#include <cmath> // math includes
#include <iostream> // I/O streams
-#include <opencv2/legacy/compat.hpp>
+#include "OpenCvLegacyIncludes.h"
using namespace Blob;
@@ -220,16 +220,16 @@ void CMultiLayerBGS::MergeImages(int num, ...) {
int img_idx = 0;
for (a = 0; a < nRows; a++)
- for (b = 0; b < nCols; b++) {
- if (img_idx >= num)
- break;
+ for (b = 0; b < nCols; b++) {
+ if (img_idx >= num)
+ break;
- imgROIRect = cvRect(b * imgSize.width, a * imgSize.height, imgSize.width, imgSize.height);
+ imgROIRect = cvRect(b * imgSize.width, a * imgSize.height, imgSize.width, imgSize.height);
- cvSetImageROI(ppIplImg[num], imgROIRect);
- cvCopyImage(ppIplImg[img_idx++], ppIplImg[num]);
- cvResetImageROI(ppIplImg[num]);
- }
+ cvSetImageROI(ppIplImg[num], imgROIRect);
+ cvCopy(ppIplImg[img_idx++], ppIplImg[num]);
+ cvResetImageROI(ppIplImg[num]);
+ }
delete[] ppIplImg;
}
@@ -369,7 +369,7 @@ void CMultiLayerBGS::SetBkMaskImage(IplImage *mask_img) {
if (m_pBkMaskImg == NULL) {
m_pBkMaskImg = cvCreateImage(cvGetSize(mask_img), mask_img->depth, mask_img->nChannels);
}
- cvCopyImage(mask_img, m_pBkMaskImg);
+ cvCopy(mask_img, m_pBkMaskImg);
}
void CMultiLayerBGS::BackgroundSubtractionProcess() {
@@ -691,7 +691,7 @@ void CMultiLayerBGS::BackgroundSubtractionProcess() {
removed_modes[a] = false;
if (LBPs[lbp_idxes[a]].bg_layer_num > curLBP->bg_layer_num &&
LBPs[lbp_idxes[a]].weight < LBPs[lbp_idxes[a]].max_weight * 0.9f) { /* remove layers */
- //LBPs[lbp_idxes[a]].bg_layer_num = 0;
+ //LBPs[lbp_idxes[a]].bg_layer_num = 0;
removed_modes[a] = true;
removed_bg_layers = true;
}
@@ -835,7 +835,7 @@ void CMultiLayerBGS::GetBackgroundImage(IplImage *bk_img) {
ODC.SetImageData(bg_img, org_data);
delete[] org_data;
- cvCopyImage(m_pBgImg, bk_img);
+ cvCopy(m_pBgImg, bk_img);
}
void CMultiLayerBGS::GetForegroundImage(IplImage *fg_img, CvScalar bg_color) {
@@ -865,7 +865,7 @@ void CMultiLayerBGS::GetForegroundMaskImage(IplImage *fg_mask_img) {
if (m_pROI && (m_pROI->width <= 0 || m_pROI->height <= 0))
return;
- //cvCopyImage(m_pFgMaskImg, fg_mask_img);
+ //cvCopy(m_pFgMaskImg, fg_mask_img);
if (m_pROI) {
cvSetImageROI(m_pFgMaskImg, *m_pROI);
cvSetImageROI(fg_mask_img, *m_pROI);
@@ -1391,7 +1391,7 @@ void CMultiLayerBGS::GetCurrentLayeredBackgroundImage(int layered_no, IplImage *
}
void CMultiLayerBGS::GetColoredBgMultiLayeredImage(IplImage *bg_multi_layer_img, CvScalar *layer_colors) {
- cvCopyImage(m_pOrgImg, bg_multi_layer_img);
+ cvCopy(m_pOrgImg, bg_multi_layer_img);
COpencvDataConversion<uchar, uchar> ODC;
diff --git a/package_bgs/jmo/CMultiLayerBGS.h b/package_bgs/MultiLayer/CMultiLayerBGS.h
similarity index 96%
rename from package_bgs/jmo/CMultiLayerBGS.h
rename to package_bgs/MultiLayer/CMultiLayerBGS.h
index c8698f6..78a0527 100644
--- a/package_bgs/jmo/CMultiLayerBGS.h
+++ b/package_bgs/MultiLayer/CMultiLayerBGS.h
@@ -43,9 +43,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// BackgroundSubtraction.h: interface for the CBackgroundSubtraction class.
//
//////////////////////////////////////////////////////////////////////
-
-#if !defined(_MULTI_LAYER_BGS_H_)
-#define _MULTI_LAYER_BGS_H_
+#pragma once
/*
Since the used fast cross bilateral filter codes can not be compiled under Windows,
@@ -124,16 +122,16 @@ public:
float weight_updating_learn_rate_per_second, // mode's weight updating learning rate per second
float low_init_mode_weight); // the low initial mode weight
- //-------------------------------------------------------------
- // PROVIDE A POINTER TO THE INPUT IMAGE
- // -> INDICATE WHERE THE NEW IMAGE TO PROCESS IS STORED
- //
- // Here assumes that the input image will contain RGB images.
- // The memory of this image is handled by the caller.
- //
- // The return value indicate whether the actual Background
- // Subtraction algorithm handles RGB images (1) or not (0).
- //
+//-------------------------------------------------------------
+// PROVIDE A POINTER TO THE INPUT IMAGE
+// -> INDICATE WHERE THE NEW IMAGE TO PROCESS IS STORED
+//
+// Here assumes that the input image will contain RGB images.
+// The memory of this image is handled by the caller.
+//
+// The return value indicate whether the actual Background
+// Subtraction algorithm handles RGB images (1) or not (0).
+//
int SetRGBInputImage(IplImage * inputImage, CvRect *roi = NULL);
//-------------------------------------------------------------
@@ -308,6 +306,3 @@ public:
CMultiLayerBGS();
virtual ~CMultiLayerBGS();
};
-
-#endif // !defined(_MULTI_LAYER_BGS_H_)
-
diff --git a/package_bgs/jmo/LocalBinaryPattern.cpp b/package_bgs/MultiLayer/LocalBinaryPattern.cpp
similarity index 95%
rename from package_bgs/jmo/LocalBinaryPattern.cpp
rename to package_bgs/MultiLayer/LocalBinaryPattern.cpp
index 6967cf4..060b9ea 100644
--- a/package_bgs/jmo/LocalBinaryPattern.cpp
+++ b/package_bgs/MultiLayer/LocalBinaryPattern.cpp
@@ -105,13 +105,13 @@ void CLocalBinaryPattern::Initialization(IplImage **first_imgs, int imgs_num, in
m_nMaxShift.y = 0;
int shift_idx = 0;
for (a = 0; a < m_nLBPLevelNum; a++)
- for (b = 0; b < m_pNeigPointsNums[a]; b++) {
- // compute the offset of neig point
- CalNeigPixelOffset(m_pRadiuses[a], m_pNeigPointsNums[a], b, m_pXYShifts[shift_idx].x, m_pXYShifts[shift_idx].y);
- m_nMaxShift.x = MAX(m_nMaxShift.x, m_pXYShifts[shift_idx].x);
- m_nMaxShift.y = MAX(m_nMaxShift.y, m_pXYShifts[shift_idx].y);
- shift_idx++;
- }
+ for (b = 0; b < m_pNeigPointsNums[a]; b++) {
+ // compute the offset of neig point
+ CalNeigPixelOffset(m_pRadiuses[a], m_pNeigPointsNums[a], b, m_pXYShifts[shift_idx].x, m_pXYShifts[shift_idx].y);
+ m_nMaxShift.x = MAX(m_nMaxShift.x, m_pXYShifts[shift_idx].x);
+ m_nMaxShift.y = MAX(m_nMaxShift.y, m_pXYShifts[shift_idx].y);
+ shift_idx++;
+ }
m_fRobustWhiteNoise = robust_white_noise;
}
@@ -155,7 +155,7 @@ void CLocalBinaryPattern::ComputeLBP(PixelLBPStruct *PLBP, CvRect *roi)
if (roi) {
int x, y;
- for (y = 0; y < roi->height; y++) {
+ for (y = 0; y < roi->height; y++) {
_PLBP = PLBP + (y + roi->y)*m_cvImgSize.width + roi->x;
for (x = 0; x < roi->width; x++) {
cur_pattern = (*_PLBP++).cur_pattern;
diff --git a/package_bgs/jmo/LocalBinaryPattern.h b/package_bgs/MultiLayer/LocalBinaryPattern.h
similarity index 96%
rename from package_bgs/jmo/LocalBinaryPattern.h
rename to package_bgs/MultiLayer/LocalBinaryPattern.h
index 987a2c2..40d4379 100644
--- a/package_bgs/jmo/LocalBinaryPattern.h
+++ b/package_bgs/MultiLayer/LocalBinaryPattern.h
@@ -43,11 +43,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// LocalBinaryPattern.h: interface for the CLocalBinaryPattern class.
//
//////////////////////////////////////////////////////////////////////
+#pragma once
-#if !defined(_LOCAL_BINARY_PATTERN_H_)
-#define _LOCAL_BINARY_PATTERN_H_
-
-#include <opencv2/opencv.hpp>
+#include "OpenCvLegacyIncludes.h"
#include "BGS.h"
@@ -98,6 +96,3 @@ private:
IplImage* m_pShiftedImg;
};
-
-#endif // !defined(_LOCAL_BINARY_PATTERN_H_)
-
diff --git a/package_bgs/jmo/OpenCvDataConversion.h b/package_bgs/MultiLayer/OpenCvDataConversion.h
similarity index 97%
rename from package_bgs/jmo/OpenCvDataConversion.h
rename to package_bgs/MultiLayer/OpenCvDataConversion.h
index a47563e..18371b3 100644
--- a/package_bgs/jmo/OpenCvDataConversion.h
+++ b/package_bgs/MultiLayer/OpenCvDataConversion.h
@@ -43,11 +43,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// OpencvDataConversion.h: interface for the COpencvDataConversion class.
//
//////////////////////////////////////////////////////////////////////
+#pragma once
-#if !defined(_OPENCV_DATA_CONVERSION_H_)
-#define _OPENCV_DATA_CONVERSION_H_
-
-#include <opencv2/opencv.hpp>
+#include "OpenCvLegacyIncludes.h"
#include <stdio.h>
template <class TI, class TM> /* class TI - the type of image data, class TM - the type of matrix data */
@@ -219,6 +217,3 @@ public:
COpencvDataConversion() {};
virtual ~COpencvDataConversion() {};
};
-
-#endif // !defined(_OPENCV_DATA_CONVERSION_H_)
-
diff --git a/package_bgs/MultiLayer/OpenCvLegacyIncludes.h b/package_bgs/MultiLayer/OpenCvLegacyIncludes.h
new file mode 100644
index 0000000..9d30c0e
--- /dev/null
+++ b/package_bgs/MultiLayer/OpenCvLegacyIncludes.h
@@ -0,0 +1,50 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/* --- --- ---
+* Copyright (C) 2008--2010 Idiap Research Institute (.....@idiap.ch)
+* All rights reserved.
+*
+* Redistribution and use in source and binary forms, with or without
+* modification, are permitted provided that the following conditions
+* are met:
+* 1. Redistributions of source code must retain the above copyright
+* notice, this list of conditions and the following disclaimer.
+* 2. Redistributions in binary form must reproduce the above copyright
+* notice, this list of conditions and the following disclaimer in the
+* documentation and/or other materials provided with the distribution.
+* 3. The name of the author may not be used to endorse or promote products
+* derived from this software without specific prior written permission.
+*
+* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
+* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
+* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
+* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
+* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
+* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
+* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+// OpenCvLegacyIncludes.h: necessary includes to compile with OpenCV 3.
+//
+//////////////////////////////////////////////////////////////////////
+#pragma once
+
+#include "opencv2/core/core_c.h"
+#include "opencv2/core/types_c.h"
+#include "opencv2/imgproc/imgproc_c.h"
diff --git a/package_bgs/MultiLayer/blob.cpp b/package_bgs/MultiLayer/blob.cpp
new file mode 100644
index 0000000..5e0fa45
--- /dev/null
+++ b/package_bgs/MultiLayer/blob.cpp
@@ -0,0 +1,1148 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/* --- --- ---
+* Copyright (C) 2008--2010 Idiap Research Institute (.....@idiap.ch)
+* All rights reserved.
+*
+* Redistribution and use in source and binary forms, with or without
+* modification, are permitted provided that the following conditions
+* are met:
+* 1. Redistributions of source code must retain the above copyright
+* notice, this list of conditions and the following disclaimer.
+* 2. Redistributions in binary form must reproduce the above copyright
+* notice, this list of conditions and the following disclaimer in the
+* documentation and/or other materials provided with the distribution.
+* 3. The name of the author may not be used to endorse or promote products
+* derived from this software without specific prior written permission.
+*
+* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
+* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
+* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
+* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
+* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
+* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
+* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+/************************************************************************
+Blob.cpp
+
+- FUNCIONALITAT: Implementació de la classe CBlob
+- AUTOR: Inspecta S.L.
+MODIFICACIONS (Modificació, Autor, Data):
+
+
+FUNCTIONALITY: Implementation of the CBlob class and some helper classes to perform
+some calculations on it
+AUTHOR: Inspecta S.L.
+MODIFICATIONS (Modification, Author, Date):
+
+**************************************************************************/
+
+
+#include <limits.h>
+#include "blob.h"
+
+namespace Blob
+{
+
+ /**
+ - FUNCIÓ: CBlob
+ - FUNCIONALITAT: Constructor està ndard
+ - PARÀMETRES:
+ - RESULTAT:
+ - inicialització de totes les variables internes i de l'storage i la sequencia
+ per a les cantonades del blob
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlob
+ - FUNCTIONALITY: Standard constructor
+ - PARAMETERS:
+ - RESULT:
+ - memory allocation for the blob edges and initialization of member variables
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlob::CBlob()
+ {
+ etiqueta = -1; // Flag indicates null region
+ exterior = 0;
+ area = 0.0f;
+ perimeter = 0.0f;
+ parent = -1;
+ minx = LONG_MAX;
+ maxx = 0;
+ miny = LONG_MAX;
+ maxy = 0;
+ sumx = 0;
+ sumy = 0;
+ sumxx = 0;
+ sumyy = 0;
+ sumxy = 0;
+ mean = 0;
+ stddev = 0;
+ externPerimeter = 0;
+
+ m_storage = cvCreateMemStorage(0);
+ edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
+ sizeof(CvContour),
+ sizeof(CvPoint), m_storage);
+ }
+
+ /**
+ - FUNCIÓ: CBlob
+ - FUNCIONALITAT: Constructor de còpia
+ - PARÀMETRES:
+ - RESULTAT:
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlob
+ - FUNCTIONALITY: Copy constructor
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlob::CBlob(const CBlob &src)
+ {
+ // copiem les propietats del blob origen a l'actual
+ etiqueta = src.etiqueta;
+ exterior = src.exterior;
+ area = src.Area();
+ perimeter = src.Perimeter();
+ parent = src.parent;
+ minx = src.minx;
+ maxx = src.maxx;
+ miny = src.miny;
+ maxy = src.maxy;
+ sumx = src.sumx;
+ sumy = src.sumy;
+ sumxx = src.sumxx;
+ sumyy = src.sumyy;
+ sumxy = src.sumxy;
+ mean = src.mean;
+ stddev = src.stddev;
+ externPerimeter = src.externPerimeter;
+
+ // copiem els edges del blob origen a l'actual
+ CvSeqReader reader;
+ CvSeqWriter writer;
+ CvPoint edgeactual;
+
+ // creem una sequencia buida per als edges
+ m_storage = cvCreateMemStorage(0);
+ edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
+ sizeof(CvContour),
+ sizeof(CvPoint), m_storage);
+
+ cvStartReadSeq(src.Edges(), &reader);
+ cvStartAppendToSeq(edges, &writer);
+
+ for (int i = 0; i < src.Edges()->total; i++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ CV_WRITE_SEQ_ELEM(edgeactual, writer);
+ }
+
+ cvEndWriteSeq(&writer);
+ }
+ CBlob::CBlob(const CBlob *src)
+ {
+ // copiem les propietats del blob origen a l'actual
+ etiqueta = src->etiqueta;
+ exterior = src->exterior;
+ area = src->Area();
+ perimeter = src->Perimeter();
+ parent = src->parent;
+ minx = src->minx;
+ maxx = src->maxx;
+ miny = src->miny;
+ maxy = src->maxy;
+ sumx = src->sumx;
+ sumy = src->sumy;
+ sumxx = src->sumxx;
+ sumyy = src->sumyy;
+ sumxy = src->sumxy;
+ mean = src->mean;
+ stddev = src->stddev;
+ externPerimeter = src->externPerimeter;
+
+ // copiem els edges del blob origen a l'actual
+ CvSeqReader reader;
+ CvSeqWriter writer;
+ CvPoint edgeactual;
+
+ // creem una sequencia buida per als edges
+ m_storage = cvCreateMemStorage(0);
+ edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
+ sizeof(CvContour),
+ sizeof(CvPoint), m_storage);
+
+ cvStartReadSeq(src->Edges(), &reader);
+ cvStartAppendToSeq(edges, &writer);
+
+ for (int i = 0; i < src->Edges()->total; i++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ CV_WRITE_SEQ_ELEM(edgeactual, writer);
+ }
+
+ cvEndWriteSeq(&writer);
+ }
+
+ /**
+ - FUNCIÓ: ~CBlob
+ - FUNCIONALITAT: Destructor està ndard
+ - PARÀMETRES:
+ - RESULTAT:
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlob
+ - FUNCTIONALITY: Standard destructor
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlob::~CBlob()
+ {
+ // Eliminar vèrtexs del blob
+ cvClearSeq(edges);
+ // i la zona de memòria on són
+ cvReleaseMemStorage(&m_storage);
+ }
+
+ /**
+ - FUNCIÓ: operator=
+ - FUNCIONALITAT: Operador d'assignació
+ - PARÀMETRES:
+ - src: blob a assignar a l'actual
+ - RESULTAT:
+ - Substitueix el blob actual per el src
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: Assigment operator
+ - FUNCTIONALITY: Assigns a blob to the current
+ - PARAMETERS:
+ - src: blob to assign
+ - RESULT:
+ - the current blob is replaced by the src blob
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CBlob& CBlob::operator=(const CBlob &src)
+ {
+ // si ja són el mateix, no cal fer res
+ if (this != &src)
+ {
+ // Eliminar vèrtexs del blob
+ cvClearSeq(edges);
+ // i la zona de memòria on són
+ cvReleaseMemStorage(&m_storage);
+
+ // creem una sequencia buida per als edges
+ m_storage = cvCreateMemStorage(0);
+ edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
+ sizeof(CvContour),
+ sizeof(CvPoint), m_storage);
+
+ // copiem les propietats del blob origen a l'actual
+ etiqueta = src.etiqueta;
+ exterior = src.exterior;
+ area = src.Area();
+ perimeter = src.Perimeter();
+ parent = src.parent;
+ minx = src.minx;
+ maxx = src.maxx;
+ miny = src.miny;
+ maxy = src.maxy;
+ sumx = src.sumx;
+ sumy = src.sumy;
+ sumxx = src.sumxx;
+ sumyy = src.sumyy;
+ sumxy = src.sumxy;
+ mean = src.mean;
+ stddev = src.stddev;
+ externPerimeter = src.externPerimeter;
+
+ // copiem els edges del blob origen a l'actual
+ CvSeqReader reader;
+ CvSeqWriter writer;
+ CvPoint edgeactual;
+
+ cvStartReadSeq(src.Edges(), &reader);
+ cvStartAppendToSeq(edges, &writer);
+
+ for (int i = 0; i < src.Edges()->total; i++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ CV_WRITE_SEQ_ELEM(edgeactual, writer);
+ }
+
+ cvEndWriteSeq(&writer);
+ }
+ return *this;
+ }
+
+ /**
+ - FUNCIÓ: FillBlob
+ - FUNCIONALITAT: Pinta l'interior d'un blob amb el color especificat
+ - PARÀMETRES:
+ - imatge: imatge on es vol pintar el el blob
+ - color: color amb que es vol pintar el blob
+ - RESULTAT:
+ - retorna la imatge d'entrada amb el blob pintat
+ - RESTRICCIONS:
+ - AUTOR:
+ - Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: FillBlob
+ - FUNCTIONALITY:
+ - Fills the blob with a specified colour
+ - PARAMETERS:
+ - imatge: where to paint
+ - color: colour to paint the blob
+ - RESULT:
+ - modifies input image and returns the seed point used to fill the blob
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlob::FillBlob(IplImage *imatge, CvScalar color, int offsetX /*=0*/, int offsetY /*=0*/) const
+ {
+
+ //verifiquem que existeixi el blob i que tingui cantonades
+ if (edges == NULL || edges->total == 0) return;
+
+ CvPoint edgeactual, pt1, pt2;
+ CvSeqReader reader;
+ vectorPunts vectorEdges = vectorPunts(edges->total);
+ vectorPunts::iterator itEdges, itEdgesSeguent;
+ bool dinsBlob;
+ int yActual;
+
+ // passem els punts del blob a un vector de punts de les STL
+ cvStartReadSeq(edges, &reader);
+ itEdges = vectorEdges.begin();
+ while (itEdges != vectorEdges.end())
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ *itEdges = edgeactual;
+ ++itEdges;
+ }
+ // ordenem el vector per les Y's i les X's d'esquerra a dreta
+ std::sort(vectorEdges.begin(), vectorEdges.end(), comparaCvPoint());
+
+ // recorrem el vector ordenat i fem linies entre punts consecutius
+ itEdges = vectorEdges.begin();
+ itEdgesSeguent = vectorEdges.begin() + 1;
+ dinsBlob = true;
+ while (itEdges != (vectorEdges.end() - 1))
+ {
+ yActual = (*itEdges).y;
+
+ if (((*itEdges).x != (*itEdgesSeguent).x) &&
+ ((*itEdgesSeguent).y == yActual)
+ )
+ {
+ if (dinsBlob)
+ {
+ pt1 = *itEdges;
+ pt1.x += offsetX;
+ pt1.y += offsetY;
+
+ pt2 = *itEdgesSeguent;
+ pt2.x += offsetX;
+ pt2.y += offsetY;
+
+ cvLine(imatge, pt1, pt2, color);
+ }
+ dinsBlob = !dinsBlob;
+ }
+ ++itEdges;
+ ++itEdgesSeguent;
+ if ((*itEdges).y != yActual) dinsBlob = true;
+ }
+ vectorEdges.clear();
+ }
+
+ /**
+ - FUNCIÓ: CopyEdges
+ - FUNCIONALITAT: Afegeix els vèrtexs del blob al blob destination
+ - PARÀMETRES:
+ - destination: blob al que volem afegir els vèrtexs
+ - RESULTAT:
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CopyEdges
+ - FUNCTIONALITY: Adds the blob edges to destination
+ - PARAMETERS:
+ - destination: where to add the edges
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlob::CopyEdges(CBlob &destination) const
+ {
+ CvSeqReader reader;
+ CvSeqWriter writer;
+ CvPoint edgeactual;
+
+ cvStartReadSeq(edges, &reader);
+ cvStartAppendToSeq(destination.Edges(), &writer);
+
+ for (int i = 0; i < edges->total; i++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ CV_WRITE_SEQ_ELEM(edgeactual, writer);
+ }
+
+ cvEndWriteSeq(&writer);
+ }
+
+ /**
+ - FUNCIÓ: ClearEdges
+ - FUNCIONALITAT: Elimina els vèrtexs del blob
+ - PARÀMETRES:
+ - RESULTAT:
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: ClearEdges
+ - FUNCTIONALITY: Delete current blob edges
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ void CBlob::ClearEdges()
+ {
+ // Eliminar vèrtexs del blob eliminat
+ cvClearSeq(edges);
+ }
+
+ /**
+ - FUNCIÓ: GetConvexHull
+ - FUNCIONALITAT: Retorna el poligon convex del blob
+ - PARÀMETRES:
+ - dst: sequencia on desarem el resultat (no ha d'estar inicialitzada)
+ - RESULTAT:
+ - true si tot ha anat bé
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: GetConvexHull
+ - FUNCTIONALITY: Calculates the convex hull polygon of the blob
+ - PARAMETERS:
+ - dst: where to store the result
+ - RESULT:
+ - true if no error ocurred
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ bool CBlob::GetConvexHull(CvSeq **dst) const
+ {
+ if (edges != NULL && edges->total > 0)
+ {
+ *dst = cvConvexHull2(edges, 0, CV_CLOCKWISE, 0);
+ return true;
+ }
+ return false;
+ }
+
+ /**
+ - FUNCIÓ: GetEllipse
+ - FUNCIONALITAT: Retorna l'ellipse que s'ajusta millor a les cantonades del blob
+ - PARÀMETRES:
+ - RESULTAT:
+ - estructura amb l'ellipse
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 25-05-2005.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: GetEllipse
+ - FUNCTIONALITY: Calculates the ellipse that best fits the edges of the blob
+ - PARAMETERS:
+ - RESULT:
+ - CvBox2D struct with the calculated ellipse
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ CvBox2D CBlob::GetEllipse() const
+ {
+ CvBox2D elipse;
+ // necessitem 6 punts per calcular l'elipse
+ if (edges != NULL && edges->total > 6)
+ {
+ elipse = cvFitEllipse2(edges);
+ }
+ else
+ {
+ elipse.center.x = 0.0;
+ elipse.center.y = 0.0;
+ elipse.size.width = 0.0;
+ elipse.size.height = 0.0;
+ elipse.angle = 0.0;
+ }
+ return elipse;
+ }
+
+
+
+ /***************************************************************************
+ Implementació de les classes per al cà lcul de caracterÃstiques sobre el blob
+
+ Implementation of the helper classes to perform operations on blobs
+ **************************************************************************/
+
+ /**
+ - FUNCIÓ: Moment
+ - FUNCIONALITAT: Calcula el moment pq del blob
+ - RESULTAT:
+ - retorna el moment pq especificat o 0 si el moment no està implementat
+ - RESTRICCIONS:
+ - Implementats els moments pq: 00, 01, 10, 20, 02
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: Moment
+ - FUNCTIONALITY: Calculates the pq moment of the blob
+ - PARAMETERS:
+ - RESULT:
+ - returns the pq moment or 0 if the moment it is not implemented
+ - RESTRICTIONS:
+ - Currently, only implemented the 00, 01, 10, 20, 02 pq moments
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 20-07-2004.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetMoment::operator()(const CBlob &blob) const
+ {
+ //Moment 00
+ if ((m_p == 0) && (m_q == 0))
+ return blob.Area();
+
+ //Moment 10
+ if ((m_p == 1) && (m_q == 0))
+ return blob.SumX();
+
+ //Moment 01
+ if ((m_p == 0) && (m_q == 1))
+ return blob.SumY();
+
+ //Moment 20
+ if ((m_p == 2) && (m_q == 0))
+ return blob.SumXX();
+
+ //Moment 02
+ if ((m_p == 0) && (m_q == 2))
+ return blob.SumYY();
+
+ return 0;
+ }
+
+ /**
+ - FUNCIÓ: HullPerimeter
+ - FUNCIONALITAT: Calcula la longitud del perimetre convex del blob.
+ Fa servir la funció d'OpenCV cvConvexHull2 per a
+ calcular el perimetre convex.
+
+ - PARÀMETRES:
+ - RESULTAT:
+ - retorna la longitud del perÃmetre convex del blob. Si el blob no té coordenades
+ associades retorna el perÃmetre normal del blob.
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobGetHullPerimeter
+ - FUNCTIONALITY: Calculates the convex hull perimeter of the blob
+ - PARAMETERS:
+ - RESULT:
+ - returns the convex hull perimeter of the blob or the perimeter if the
+ blob edges could not be retrieved
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetHullPerimeter::operator()(const CBlob &blob) const
+ {
+ if (blob.Edges() != NULL && blob.Edges()->total > 0)
+ {
+ CvSeq *hull = cvConvexHull2(blob.Edges(), 0, CV_CLOCKWISE, 1);
+ return fabs(cvArcLength(hull, CV_WHOLE_SEQ, 1));
+ }
+ return blob.Perimeter();
+ }
+
+ double CBlobGetHullArea::operator()(const CBlob &blob) const
+ {
+ if (blob.Edges() != NULL && blob.Edges()->total > 0)
+ {
+ CvSeq *hull = cvConvexHull2(blob.Edges(), 0, CV_CLOCKWISE, 1);
+ return fabs(cvContourArea(hull));
+ }
+ return blob.Perimeter();
+ }
+
+ /**
+ - FUNCIÓ: MinX_at_MinY
+ - FUNCIONALITAT: Calcula el valor MinX a MinY.
+ - PARÀMETRES:
+ - blob: blob del que volem calcular el valor
+ - RESULTAT:
+ - retorna la X minima en la Y minima.
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobGetMinXatMinY
+ - FUNCTIONALITY: Calculates the minimum X on the minimum Y
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetMinXatMinY::operator()(const CBlob &blob) const
+ {
+ double MinX_at_MinY = LONG_MAX;
+
+ CvSeqReader reader;
+ CvPoint edgeactual;
+
+ cvStartReadSeq(blob.Edges(), &reader);
+
+ for (int j = 0; j < blob.Edges()->total; j++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ if ((edgeactual.y == blob.MinY()) && (edgeactual.x < MinX_at_MinY))
+ {
+ MinX_at_MinY = edgeactual.x;
+ }
+ }
+
+ return MinX_at_MinY;
+ }
+
+ /**
+ - FUNCIÓ: MinY_at_MaxX
+ - FUNCIONALITAT: Calcula el valor MinX a MaxX.
+ - PARÀMETRES:
+ - blob: blob del que volem calcular el valor
+ - RESULTAT:
+ - retorna la Y minima en la X maxima.
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobGetMinXatMinY
+ - FUNCTIONALITY: Calculates the minimum Y on the maximum X
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetMinYatMaxX::operator()(const CBlob &blob) const
+ {
+ double MinY_at_MaxX = LONG_MAX;
+
+ CvSeqReader reader;
+ CvPoint edgeactual;
+
+ cvStartReadSeq(blob.Edges(), &reader);
+
+ for (int j = 0; j < blob.Edges()->total; j++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ if ((edgeactual.x == blob.MaxX()) && (edgeactual.y < MinY_at_MaxX))
+ {
+ MinY_at_MaxX = edgeactual.y;
+ }
+ }
+
+ return MinY_at_MaxX;
+ }
+
+ /**
+ - FUNCIÓ: MaxX_at_MaxY
+ - FUNCIONALITAT: Calcula el valor MaxX a MaxY.
+ - PARÀMETRES:
+ - blob: blob del que volem calcular el valor
+ - RESULTAT:
+ - retorna la X maxima en la Y maxima.
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobGetMaxXatMaxY
+ - FUNCTIONALITY: Calculates the maximum X on the maximum Y
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetMaxXatMaxY::operator()(const CBlob &blob) const
+ {
+ double MaxX_at_MaxY = LONG_MIN;
+
+ CvSeqReader reader;
+ CvPoint edgeactual;
+
+ cvStartReadSeq(blob.Edges(), &reader);
+
+ for (int j = 0; j < blob.Edges()->total; j++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ if ((edgeactual.y == blob.MaxY()) && (edgeactual.x > MaxX_at_MaxY))
+ {
+ MaxX_at_MaxY = edgeactual.x;
+ }
+ }
+
+ return MaxX_at_MaxY;
+ }
+
+ /**
+ - FUNCIÓ: MaxY_at_MinX
+ - FUNCIONALITAT: Calcula el valor MaxY a MinX.
+ - PARÀMETRES:
+ - blob: blob del que volem calcular el valor
+ - RESULTAT:
+ - retorna la Y maxima en la X minima.
+ - RESTRICCIONS:
+ - AUTOR: Ricard Borrà s
+ - DATA DE CREACIÓ: 20-07-2004.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: CBlobGetMaxYatMinX
+ - FUNCTIONALITY: Calculates the maximum Y on the minimum X
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetMaxYatMinX::operator()(const CBlob &blob) const
+ {
+ double MaxY_at_MinX = LONG_MIN;
+
+ CvSeqReader reader;
+ CvPoint edgeactual;
+
+ cvStartReadSeq(blob.Edges(), &reader);
+
+ for (int j = 0; j < blob.Edges()->total; j++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ if ((edgeactual.x == blob.MinY()) && (edgeactual.y > MaxY_at_MinX))
+ {
+ MaxY_at_MinX = edgeactual.y;
+ }
+ }
+
+ return MaxY_at_MinX;
+ }
+
+ /**
+ Retorna l'elongació del blob (longitud/amplada)
+ */
+ /**
+ - FUNCTION: CBlobGetElongation
+ - FUNCTIONALITY: Calculates the elongation of the blob ( length/breadth )
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - See below to see how the lenght and the breadth are aproximated
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetElongation::operator()(const CBlob &blob) const
+ {
+ double ampladaC, longitudC, amplada, longitud;
+
+ ampladaC = (double)(blob.Perimeter() + sqrt(pow(blob.Perimeter(), 2) - 16 * blob.Area())) / 4;
+ if (ampladaC <= 0.0) return 0;
+ longitudC = (double)blob.Area() / ampladaC;
+
+ longitud = MAX(longitudC, ampladaC);
+ amplada = MIN(longitudC, ampladaC);
+
+ return (double)longitud / amplada;
+ }
+
+ /**
+ Retorna la compacitat del blob
+ */
+ /**
+ - FUNCTION: CBlobGetCompactness
+ - FUNCTIONALITY: Calculates the compactness of the blob
+ ( maximum for circle shaped blobs, minimum for the rest)
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetCompactness::operator()(const CBlob &blob) const
+ {
+ if (blob.Area() != 0.0)
+ return (double)pow(blob.Perimeter(), 2) / (4 * CV_PI*blob.Area());
+ else
+ return 0.0;
+ }
+
+ /**
+ Retorna la rugositat del blob
+ */
+ /**
+ - FUNCTION: CBlobGetRoughness
+ - FUNCTIONALITY: Calculates the roughness of the blob
+ ( ratio between perimeter and convex hull perimeter)
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetRoughness::operator()(const CBlob &blob) const
+ {
+ CBlobGetHullPerimeter getHullPerimeter = CBlobGetHullPerimeter();
+
+ double hullPerimeter = getHullPerimeter(blob);
+
+ if (hullPerimeter != 0.0)
+ return blob.Perimeter() / hullPerimeter;//HullPerimeter();
+
+ return 0.0;
+ }
+
+ /**
+ Retorna la longitud del blob
+ */
+ /**
+ - FUNCTION: CBlobGetLength
+ - FUNCTIONALITY: Calculates the lenght of the blob (the biggest axis of the blob)
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - The lenght is an aproximation to the real lenght
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetLength::operator()(const CBlob &blob) const
+ {
+ double ampladaC, longitudC;
+ double tmp;
+
+ tmp = blob.Perimeter()*blob.Perimeter() - 16 * blob.Area();
+
+ if (tmp > 0.0)
+ ampladaC = (double)(blob.Perimeter() + sqrt(tmp)) / 4;
+ // error intrÃnsec en els cà lculs de l'à rea i el perÃmetre
+ else
+ ampladaC = (double)(blob.Perimeter()) / 4;
+
+ if (ampladaC <= 0.0) return 0;
+ longitudC = (double)blob.Area() / ampladaC;
+
+ return MAX(longitudC, ampladaC);
+ }
+
+ /**
+ Retorna l'amplada del blob
+ */
+ /**
+ - FUNCTION: CBlobGetBreadth
+ - FUNCTIONALITY: Calculates the breadth of the blob (the smallest axis of the blob)
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - The breadth is an aproximation to the real breadth
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetBreadth::operator()(const CBlob &blob) const
+ {
+ double ampladaC, longitudC;
+ double tmp;
+
+ tmp = blob.Perimeter()*blob.Perimeter() - 16 * blob.Area();
+
+ if (tmp > 0.0)
+ ampladaC = (double)(blob.Perimeter() + sqrt(tmp)) / 4;
+ // error intrÃnsec en els cà lculs de l'à rea i el perÃmetre
+ else
+ ampladaC = (double)(blob.Perimeter()) / 4;
+
+ if (ampladaC <= 0.0) return 0;
+ longitudC = (double)blob.Area() / ampladaC;
+
+ return MIN(longitudC, ampladaC);
+ }
+
+ /**
+ Calcula la distà ncia entre un punt i el centre del blob
+ */
+ /**
+ - FUNCTION: CBlobGetDistanceFromPoint
+ - FUNCTIONALITY: Calculates the euclidean distance between the blob center and
+ the point specified in the constructor
+ - PARAMETERS:
+ - RESULT:
+ - RESTRICTIONS:
+ - AUTHOR: Ricard Borrà s
+ - CREATION DATE: 25-05-2005.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetDistanceFromPoint::operator()(const CBlob &blob) const
+ {
+ double xmitjana, ymitjana;
+ CBlobGetXCenter getXCenter;
+ CBlobGetYCenter getYCenter;
+
+ xmitjana = m_x - getXCenter(blob);
+ ymitjana = m_y - getYCenter(blob);
+
+ return sqrt((xmitjana*xmitjana) + (ymitjana*ymitjana));
+ }
+
+ /**
+ - FUNCIÓ: BlobGetXYInside
+ - FUNCIONALITAT: Calcula si un punt cau dins de la capsa rectangular
+ del blob
+ - RESULTAT:
+ - retorna 1 si hi està ; 0 si no
+ - RESTRICCIONS:
+ - AUTOR: Francesc Pinyol Margalef
+ - DATA DE CREACIÓ: 16-01-2006.
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ /**
+ - FUNCTION: BlobGetXYInside
+ - FUNCTIONALITY: Calculates whether a point is inside the
+ rectangular bounding box of a blob
+ - PARAMETERS:
+ - RESULT:
+ - returns 1 if it is inside; o if not
+ - RESTRICTIONS:
+ - AUTHOR: Francesc Pinyol Margalef
+ - CREATION DATE: 16-01-2006.
+ - MODIFICATION: Date. Author. Description.
+ */
+ double CBlobGetXYInside::operator()(const CBlob &blob) const
+ {
+ if (blob.Edges() == NULL || blob.Edges()->total == 0) return 0.0;
+
+ // passem els punts del blob a un vector de punts de les STL
+ CvSeqReader reader;
+ CBlob::vectorPunts vectorEdges;
+ CBlob::vectorPunts::iterator itEdges, itEdgesSeguent;
+ CvPoint edgeactual;
+ bool dinsBlob;
+
+ // agafem tots els punts amb la mateixa y que l'actual
+ cvStartReadSeq(blob.Edges(), &reader);
+
+ for (int i = 0; i < blob.Edges()->total; i++)
+ {
+ CV_READ_SEQ_ELEM(edgeactual, reader);
+ if (edgeactual.y == m_p.y)
+ vectorEdges.push_back(edgeactual);
+ }
+
+ if (vectorEdges.empty()) return 0.0;
+
+ // ordenem el vector per les Y's i les X's d'esquerra a dreta
+ std::sort(vectorEdges.begin(), vectorEdges.end(), CBlob::comparaCvPoint());
+
+ // recorrem el punts del blob de la mateixa fila que el punt d'entrada
+ // i mirem si la X del punt d'entrada està entre dos coordenades "plenes"
+ // del blob
+ itEdges = vectorEdges.begin();
+ itEdgesSeguent = vectorEdges.begin() + 1;
+ dinsBlob = true;
+
+ while (itEdges != (vectorEdges.end() - 1))
+ {
+ if ((*itEdges).x <= m_p.x && (*itEdgesSeguent).x >= m_p.x && dinsBlob)
+ {
+ vectorEdges.clear();
+ return 1.0;
+ }
+
+ ++itEdges;
+ ++itEdgesSeguent;
+ dinsBlob = !dinsBlob;
+ }
+
+ vectorEdges.clear();
+ return 0.0;
+ }
+
+#ifdef BLOB_OBJECT_FACTORY
+
+ /**
+ - FUNCIÓ: RegistraTotsOperadors
+ - FUNCIONALITAT: Registrar tots els operadors definits a blob.h
+ - PARÀMETRES:
+ - fabricaOperadorsBlob: fà brica on es registraran els operadors
+ - RESULTAT:
+ - Modifica l'objecte fabricaOperadorsBlob
+ - RESTRICCIONS:
+ - Només es registraran els operadors de blob.h. Si se'n volen afegir, cal afegir-los amb
+ el mètode Register de la fà brica.
+ - AUTOR: rborras
+ - DATA DE CREACIÓ: 2006/05/18
+ - MODIFICACIÓ: Data. Autor. Descripció.
+ */
+ void RegistraTotsOperadors(t_OperadorBlobFactory &fabricaOperadorsBlob)
+ {
+ // blob shape
+ fabricaOperadorsBlob.Register(CBlobGetArea().GetNom(), Type2Type<CBlobGetArea>());
+ fabricaOperadorsBlob.Register(CBlobGetBreadth().GetNom(), Type2Type<CBlobGetBreadth>());
+ fabricaOperadorsBlob.Register(CBlobGetCompactness().GetNom(), Type2Type<CBlobGetCompactness>());
+ fabricaOperadorsBlob.Register(CBlobGetElongation().GetNom(), Type2Type<CBlobGetElongation>());
+ fabricaOperadorsBlob.Register(CBlobGetExterior().GetNom(), Type2Type<CBlobGetExterior>());
+ fabricaOperadorsBlob.Register(CBlobGetLength().GetNom(), Type2Type<CBlobGetLength>());
+ fabricaOperadorsBlob.Register(CBlobGetPerimeter().GetNom(), Type2Type<CBlobGetPerimeter>());
+ fabricaOperadorsBlob.Register(CBlobGetRoughness().GetNom(), Type2Type<CBlobGetRoughness>());
+
+ // extern pixels
+ fabricaOperadorsBlob.Register(CBlobGetExternPerimeterRatio().GetNom(), Type2Type<CBlobGetExternPerimeterRatio>());
+ fabricaOperadorsBlob.Register(CBlobGetExternHullPerimeterRatio().GetNom(), Type2Type<CBlobGetExternHullPerimeterRatio>());
+ fabricaOperadorsBlob.Register(CBlobGetExternPerimeter().GetNom(), Type2Type<CBlobGetExternPerimeter>());
+
+
+ // hull
+ fabricaOperadorsBlob.Register(CBlobGetHullPerimeter().GetNom(), Type2Type<CBlobGetHullPerimeter>());
+ fabricaOperadorsBlob.Register(CBlobGetHullArea().GetNom(), Type2Type<CBlobGetHullArea>());
+
+
+ // elipse info
+ fabricaOperadorsBlob.Register(CBlobGetMajorAxisLength().GetNom(), Type2Type<CBlobGetMajorAxisLength>());
+ fabricaOperadorsBlob.Register(CBlobGetMinorAxisLength().GetNom(), Type2Type<CBlobGetMinorAxisLength>());
+ fabricaOperadorsBlob.Register(CBlobGetAxisRatio().GetNom(), Type2Type<CBlobGetAxisRatio>());
+ fabricaOperadorsBlob.Register(CBlobGetOrientation().GetNom(), Type2Type<CBlobGetOrientation>());
+ fabricaOperadorsBlob.Register(CBlobGetOrientationCos().GetNom(), Type2Type<CBlobGetOrientationCos>());
+ fabricaOperadorsBlob.Register(CBlobGetAreaElipseRatio().GetNom(), Type2Type<CBlobGetAreaElipseRatio>());
+
+ // min an max
+ fabricaOperadorsBlob.Register(CBlobGetMaxX().GetNom(), Type2Type<CBlobGetMaxX>());
+ fabricaOperadorsBlob.Register(CBlobGetMaxY().GetNom(), Type2Type<CBlobGetMaxY>());
+ fabricaOperadorsBlob.Register(CBlobGetMinX().GetNom(), Type2Type<CBlobGetMinX>());
+ fabricaOperadorsBlob.Register(CBlobGetMinY().GetNom(), Type2Type<CBlobGetMinY>());
+
+ fabricaOperadorsBlob.Register(CBlobGetMaxXatMaxY().GetNom(), Type2Type<CBlobGetMaxXatMaxY>());
+ fabricaOperadorsBlob.Register(CBlobGetMaxYatMinX().GetNom(), Type2Type<CBlobGetMaxYatMinX>());
+ fabricaOperadorsBlob.Register(CBlobGetMinXatMinY().GetNom(), Type2Type<CBlobGetMinXatMinY>());
+ fabricaOperadorsBlob.Register(CBlobGetMinYatMaxX().GetNom(), Type2Type<CBlobGetMinYatMaxX>());
+
+ // grey level stats
+ fabricaOperadorsBlob.Register(CBlobGetMean().GetNom(), Type2Type<CBlobGetMean>());
+ fabricaOperadorsBlob.Register(CBlobGetStdDev().GetNom(), Type2Type<CBlobGetStdDev>());
+
+ // coordinate info
+ fabricaOperadorsBlob.Register(CBlobGetXYInside().GetNom(), Type2Type<CBlobGetXYInside>());
+ fabricaOperadorsBlob.Register(CBlobGetDiffY().GetNom(), Type2Type<CBlobGetDiffY>());
+ fabricaOperadorsBlob.Register(CBlobGetDiffX().GetNom(), Type2Type<CBlobGetDiffX>());
+ fabricaOperadorsBlob.Register(CBlobGetXCenter().GetNom(), Type2Type<CBlobGetXCenter>());
+ fabricaOperadorsBlob.Register(CBlobGetYCenter().GetNom(), Type2Type<CBlobGetYCenter>());
+ fabricaOperadorsBlob.Register(CBlobGetDistanceFromPoint().GetNom(), Type2Type<CBlobGetDistanceFromPoint>());
+
+ // moments
+ fabricaOperadorsBlob.Register(CBlobGetMoment().GetNom(), Type2Type<CBlobGetMoment>());
+
+ }
+
+#endif
+
+}
+
diff --git a/package_bgs/jmo/blob.h b/package_bgs/MultiLayer/blob.h
similarity index 87%
rename from package_bgs/jmo/blob.h
rename to package_bgs/MultiLayer/blob.h
index 67bdf11..b7d5fe1 100644
--- a/package_bgs/jmo/blob.h
+++ b/package_bgs/MultiLayer/blob.h
@@ -43,9 +43,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
/************************************************************************
Blob.h
-FUNCIONALITAT: Definici� de la classe CBlob
+FUNCIONALITAT: Definició de la classe CBlob
AUTOR: Inspecta S.L.
-MODIFICACIONS (Modificaci�, Autor, Data):
+MODIFICACIONS (Modificació, Autor, Data):
FUNCTIONALITY: Definition of the CBlob class and some helper classes to perform
some calculations on it
@@ -53,51 +53,46 @@ AUTHOR: Inspecta S.L.
MODIFICATIONS (Modification, Author, Date):
**************************************************************************/
-
-//! Disable warnings referred to 255 character truncation for the std:map
-//#pragma warning( disable : 4786 )
-
-#ifndef CBLOB_INSPECTA_INCLUDED
-#define CBLOB_INSPECTA_INCLUDED
+#pragma once
//#include "cxcore.h"
#include "BlobLibraryConfiguration.h"
#include <functional>
#include <vector>
#include <algorithm>
-#include <opencv2/core/types_c.h>
-//! Factor de conversi� de graus a radians
+#include "OpenCvLegacyIncludes.h"
+//! Factor de conversió de graus a radians
#define DEGREE2RAD (CV_PI / 180.0)
namespace Blob
{
/**
- Classe que representa un blob, ent�s com un conjunt de pixels del
- mateix color contigus en una imatge binaritzada.
+ Classe que representa un blob, entés com un conjunt de pixels del
+ mateix color contigus en una imatge binaritzada.
- Class to represent a blob, a group of connected pixels in a binary image
- */
+ Class to represent a blob, a group of connected pixels in a binary image
+ */
class CBlob
{
public:
- //! Constructor est�ndard
+ //! Constructor està ndard
//! Standard constructor
CBlob();
- //! Constructor de c�pia
+ //! Constructor de còpia
//! Copy constructor
CBlob(const CBlob &src);
CBlob(const CBlob *src);
- //! Destructor est�ndard
+ //! Destructor està ndard
//! Standard Destructor
~CBlob();
- //! Operador d'assignaci�
+ //! Operador d'assignació
//! Assigment operator
CBlob& operator=(const CBlob &src);
- //! Indica si el blob est� buit ( no t� cap info associada )
+ //! Indica si el blob està buit ( no té cap info associada )
//! Shows if the blob has associated information
bool IsEmpty() const
{
@@ -107,13 +102,13 @@ namespace Blob
//! Neteja les cantonades del blob
//! Clears the edges of the blob
void ClearEdges();
- //! Copia les cantonades del blob a un altre (les afegeix al dest�)
+ //! Copia les cantonades del blob a un altre (les afegeix al destÃ)
//! Adds the blob edges to another blob
void CopyEdges(CBlob &destination) const;
//! Retorna el poligon convex del blob
//! Calculates the convex hull of the blob
bool GetConvexHull(CvSeq **dst) const;
- //! Calcula l'elipse que s'adapta als v�rtexs del blob
+ //! Calcula l'elipse que s'adapta als vèrtexs del blob
//! Fits an ellipse to the blob edges
CvBox2D GetEllipse() const;
@@ -124,8 +119,8 @@ namespace Blob
//! Funcions GET sobre els valors dels blobs
//! Get functions
- inline int Label() const { return etiqueta; }
- inline int Parent() const { return parent; }
+ inline int Label() const { return etiqueta; }
+ inline int Parent() const { return parent; }
inline double Area() const { return area; }
inline double Perimeter() const { return perimeter; }
inline double ExternPerimeter() const { return externPerimeter; }
@@ -176,14 +171,14 @@ namespace Blob
//! mitjana
//! mean of the grey scale values of the blob pixels
double mean;
- //! desviaci� standard
+ //! desviació standard
//! standard deviation of the grey scale values of the blob pixels
double stddev;
- //! �rea de mem�ria on es desaran els punts de contorn del blob
+ //! à rea de memòria on es desaran els punts de contorn del blob
//! storage which contains the edges of the blob
CvMemStorage *m_storage;
- //! Sequ�ncia de punts del contorn del blob
+ //! Sequència de punts del contorn del blob
//! Sequence with the edges of the blob
CvSeq *edges;
@@ -194,7 +189,7 @@ namespace Blob
//! Helper class to compare two CvPoints (for sorting in FillBlob)
struct comparaCvPoint : public std::binary_function<CvPoint, CvPoint, bool>
{
- //! Definim que un punt �s menor com m�s amunt a la dreta estigui
+ //! Definim que un punt és menor com més amunt a la dreta estigui
bool operator()(CvPoint a, CvPoint b)
{
if (a.y == b.y)
@@ -208,22 +203,22 @@ namespace Blob
/**************************************************************************
- Definici� de les classes per a fer operacions sobre els blobs
+ Definició de les classes per a fer operacions sobre els blobs
- Helper classes to perform operations on blobs
- **************************************************************************/
+ Helper classes to perform operations on blobs
+ **************************************************************************/
- //! Classe d'on derivarem totes les operacions sobre els blobs
- //! Interface to derive all blob operations
+ //! Classe d'on derivarem totes les operacions sobre els blobs
+ //! Interface to derive all blob operations
class COperadorBlob
{
public:
- virtual ~COperadorBlob(){};
+ virtual ~COperadorBlob() {};
- //! Aplica l'operaci� al blob
+ //! Aplica l'operació al blob
virtual double operator()(const CBlob &blob) const = 0;
- //! Obt� el nom de l'operador
+ //! Obté el nom de l'operador
virtual const char *GetNom() const = 0;
operator COperadorBlob*() const
@@ -236,8 +231,8 @@ namespace Blob
#ifdef BLOB_OBJECT_FACTORY
/**
- Funci� per comparar dos identificadors dins de la f�brica de COperadorBlobs
- */
+ Funció per comparar dos identificadors dins de la fà brica de COperadorBlobs
+ */
struct functorComparacioIdOperador
{
bool operator()(const char* s1, const char* s2) const
@@ -249,12 +244,12 @@ namespace Blob
//! Definition of Object factory type for COperadorBlob objects
typedef ObjectFactory<COperadorBlob, const char *, functorComparacioIdOperador > t_OperadorBlobFactory;
- //! Funci� global per a registrar tots els operadors definits a blob.h
- void RegistraTotsOperadors( t_OperadorBlobFactory &fabricaOperadorsBlob );
+ //! Funció global per a registrar tots els operadors definits a blob.h
+ void RegistraTotsOperadors(t_OperadorBlobFactory &fabricaOperadorsBlob);
#endif
- //! Classe per calcular l'�rea d'un blob
+ //! Classe per calcular l'Ã rea d'un blob
//! Class to get the area of a blob
class CBlobGetArea : public COperadorBlob
{
@@ -284,7 +279,7 @@ namespace Blob
}
};
- //! Classe que diu si un blob �s extern o no
+ //! Classe que diu si un blob és extern o no
//! Class to get the extern flag of a blob
class CBlobGetExterior : public COperadorBlob
{
@@ -314,7 +309,7 @@ namespace Blob
}
};
- //! Classe per calcular la desviaci� est�ndard dels nivells de gris d'un blob
+ //! Classe per calcular la desviació està ndard dels nivells de gris d'un blob
//! Class to get the standard deviation of the grey level values of a blob
class CBlobGetStdDev : public COperadorBlob
{
@@ -365,7 +360,7 @@ namespace Blob
}
};
- //! Classe per calcular la difer�ncia en X del blob
+ //! Classe per calcular la diferència en X del blob
class CBlobGetDiffX : public COperadorBlob
{
public:
@@ -379,7 +374,7 @@ namespace Blob
}
};
- //! Classe per calcular la difer�ncia en X del blob
+ //! Classe per calcular la diferència en X del blob
class CBlobGetDiffY : public COperadorBlob
{
public:
@@ -398,7 +393,7 @@ namespace Blob
class CBlobGetMoment : public COperadorBlob
{
public:
- //! Constructor est�ndard
+ //! Constructor està ndard
//! Standard constructor (gets the 00 moment)
CBlobGetMoment()
{
@@ -434,7 +429,7 @@ namespace Blob
}
};
- //! Classe per calcular l'�rea del poligon convex d'un blob
+ //! Classe per calcular l'Ã rea del poligon convex d'un blob
//! Class to calculate the convex hull area of a blob
class CBlobGetHullArea : public COperadorBlob
{
@@ -494,7 +489,7 @@ namespace Blob
}
};
- //! Classe per a calcular la x m�nima
+ //! Classe per a calcular la x mÃnima
//! Class to get the minimum x
class CBlobGetMinX : public COperadorBlob
{
@@ -509,7 +504,7 @@ namespace Blob
}
};
- //! Classe per a calcular la x m�xima
+ //! Classe per a calcular la x mà xima
//! Class to get the maximum x
class CBlobGetMaxX : public COperadorBlob
{
@@ -524,7 +519,7 @@ namespace Blob
}
};
- //! Classe per a calcular la y m�nima
+ //! Classe per a calcular la y mÃnima
//! Class to get the minimum y
class CBlobGetMinY : public COperadorBlob
{
@@ -539,7 +534,7 @@ namespace Blob
}
};
- //! Classe per a calcular la y m�xima
+ //! Classe per a calcular la y mà xima
//! Class to get the maximum y
class CBlobGetMaxY : public COperadorBlob
{
@@ -579,7 +574,7 @@ namespace Blob
}
};
- //! Classe per calcular la dist�ncia entre el centre del blob i un punt donat
+ //! Classe per calcular la distà ncia entre el centre del blob i un punt donat
//! Class to calculate the euclidean distance between the center of a blob and a given point
class CBlobGetDistanceFromPoint : public COperadorBlob
{
@@ -603,7 +598,7 @@ namespace Blob
}
private:
- // coordenades del punt on volem calcular la dist�ncia
+ // coordenades del punt on volem calcular la distà ncia
double m_x, m_y;
};
@@ -623,8 +618,8 @@ namespace Blob
};
//! Classe per calcular el ratio entre el perimetre i nombre pixels externs
- //! valors propers a 0 indiquen que la majoria del blob �s intern
- //! valors propers a 1 indiquen que la majoria del blob �s extern
+ //! valors propers a 0 indiquen que la majoria del blob és intern
+ //! valors propers a 1 indiquen que la majoria del blob és extern
//! Class to calculate the ratio between the perimeter and the number of extern pixels
class CBlobGetExternPerimeterRatio : public COperadorBlob
{
@@ -643,8 +638,8 @@ namespace Blob
};
//! Classe per calcular el ratio entre el perimetre convex i nombre pixels externs
- //! valors propers a 0 indiquen que la majoria del blob �s intern
- //! valors propers a 1 indiquen que la majoria del blob �s extern
+ //! valors propers a 0 indiquen que la majoria del blob és intern
+ //! valors propers a 1 indiquen que la majoria del blob és extern
//! Class to calculate the ratio between the perimeter and the number of extern pixels
class CBlobGetExternHullPerimeterRatio : public COperadorBlob
{
@@ -713,7 +708,7 @@ namespace Blob
};
//! Classe per calcular el ratio entre l'area de la elipse i la de la taca
- //! Class
+ //! Class
class CBlobGetAreaElipseRatio : public COperadorBlob
{
public:
@@ -755,7 +750,7 @@ namespace Blob
}
};
- //! Classe per calcular l'orientaci� de l'ellipse del blob en radians
+ //! Classe per calcular l'orientació de l'ellipse del blob en radians
//! Class to calculate the orientation of the ellipse that fits the blob edges in radians
class CBlobGetOrientation : public COperadorBlob
{
@@ -776,7 +771,7 @@ namespace Blob
}
};
- //! Classe per calcular el cosinus de l'orientaci� de l'ellipse del blob
+ //! Classe per calcular el cosinus de l'orientació de l'ellipse del blob
//! Class to calculate the cosinus of the orientation of the ellipse that fits the blob edges
class CBlobGetOrientationCos : public COperadorBlob
{
@@ -793,7 +788,7 @@ namespace Blob
};
- //! Classe per calcular el ratio entre l'eix major i menor de la el�lipse
+ //! Classe per calcular el ratio entre l'eix major i menor de la el·lipse
//! Class to calculate the ratio between both axes of the ellipse
class CBlobGetAxisRatio : public COperadorBlob
{
@@ -816,7 +811,7 @@ namespace Blob
class CBlobGetXYInside : public COperadorBlob
{
public:
- //! Constructor est�ndard
+ //! Constructor està ndard
//! Standard constructor
CBlobGetXYInside()
{
@@ -841,6 +836,3 @@ namespace Blob
};
}
-
-#endif //CBLOB_INSPECTA_INCLUDED
-
diff --git a/package_bgs/PAWCS.cpp b/package_bgs/PAWCS.cpp
new file mode 100644
index 0000000..908b3ae
--- /dev/null
+++ b/package_bgs/PAWCS.cpp
@@ -0,0 +1,93 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "PAWCS.h"
+
+using namespace bgslibrary::algorithms;
+
+PAWCS::PAWCS() : pPAWCS(nullptr),
+fRelLBSPThreshold(BGSPAWCS_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD),
+nDescDistThresholdOffset(BGSPAWCS_DEFAULT_DESC_DIST_THRESHOLD_OFFSET),
+nMinColorDistThreshold(BGSPAWCS_DEFAULT_MIN_COLOR_DIST_THRESHOLD),
+nMaxNbWords(BGSPAWCS_DEFAULT_MAX_NB_WORDS),
+nSamplesForMovingAvgs(BGSPAWCS_DEFAULT_N_SAMPLES_FOR_MV_AVGS)
+{
+ std::cout << "PAWCS()" << std::endl;
+ setup("./config/PAWCS.xml");
+}
+PAWCS::~PAWCS()
+{
+ if (pPAWCS)
+ delete pPAWCS;
+ std::cout << "~PAWCS()" << std::endl;
+}
+
+void PAWCS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (firstTime)
+ {
+ pPAWCS = new BackgroundSubtractorPAWCS(
+ fRelLBSPThreshold, nDescDistThresholdOffset, nMinColorDistThreshold,
+ nMaxNbWords, nSamplesForMovingAvgs);
+
+ pPAWCS->initialize(img_input, cv::Mat(img_input.size(), CV_8UC1, cv::Scalar_<uchar>(255)));
+ firstTime = false;
+ }
+
+ pPAWCS->apply(img_input, img_foreground);
+ pPAWCS->getBackgroundImage(img_background);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ imshow("PAWCS FG", img_foreground);
+ imshow("PAWCS BG", img_background);
+ }
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+}
+
+void PAWCS::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteReal(fs, "fRelLBSPThreshold", fRelLBSPThreshold);
+ cvWriteInt(fs, "nDescDistThresholdOffset", nDescDistThresholdOffset);
+ cvWriteInt(fs, "nMinColorDistThreshold", nMinColorDistThreshold);
+ cvWriteInt(fs, "nMaxNbWords", nMaxNbWords);
+ cvWriteInt(fs, "nSamplesForMovingAvgs", nSamplesForMovingAvgs);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void PAWCS::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ fRelLBSPThreshold = cvReadRealByName(fs, nullptr, "fRelLBSPThreshold", BGSPAWCS_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD);
+ nDescDistThresholdOffset = cvReadIntByName(fs, nullptr, "nDescDistThresholdOffset", BGSPAWCS_DEFAULT_DESC_DIST_THRESHOLD_OFFSET);
+ nMinColorDistThreshold = cvReadIntByName(fs, nullptr, "nMinColorDistThreshold", BGSPAWCS_DEFAULT_MIN_COLOR_DIST_THRESHOLD);
+ nMaxNbWords = cvReadIntByName(fs, nullptr, "nMaxNbWords", BGSPAWCS_DEFAULT_MAX_NB_WORDS);
+ nSamplesForMovingAvgs = cvReadIntByName(fs, nullptr, "nSamplesForMovingAvgs", BGSPAWCS_DEFAULT_N_SAMPLES_FOR_MV_AVGS);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/PAWCS.h b/package_bgs/PAWCS.h
new file mode 100644
index 0000000..173bcf6
--- /dev/null
+++ b/package_bgs/PAWCS.h
@@ -0,0 +1,48 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "LBSP/BackgroundSubtractorPAWCS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class PAWCS : public IBGS
+ {
+ private:
+ BackgroundSubtractorPAWCS* pPAWCS;
+
+ float fRelLBSPThreshold;
+ size_t nDescDistThresholdOffset;
+ size_t nMinColorDistThreshold;
+ size_t nMaxNbWords;
+ size_t nSamplesForMovingAvgs;
+
+ public:
+ PAWCS();
+ ~PAWCS();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/PBAS/PBAS.cpp b/package_bgs/PBAS/PBAS.cpp
new file mode 100644
index 0000000..bc3ad40
--- /dev/null
+++ b/package_bgs/PBAS/PBAS.cpp
@@ -0,0 +1,585 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "PBAS.h"
+
+PBAS::PBAS(void) : N(20), R_lower(18), Raute_min(2), T_lower(2), T_upper(200), R_scale(5), R_incdec(0.05), T_dec(0.05), T_inc(1)
+{
+ std::cout << "PBAS()" << std::endl;
+
+ //feature vector
+ alpha = 7.0;
+ beta = 1.0;
+ formerMeanNorm = 0;
+ width = 0;
+
+ //result image
+ foregroundValue = 255;
+ backgroundValue = 0;
+
+ //length of random array
+ countOfRandomNumb = 1000;
+
+ //the T(x_i) value needs initiation
+ T_init = R_lower;
+
+ //check if something is moving in the picture
+ isMove = false;
+
+ //for init, count number of runs
+ runs = 0;
+ newInitialization();
+}
+
+void PBAS::newInitialization()
+{
+ if (!randomN.empty())
+ randomN.clear();
+
+ if (!randomX.empty())
+ randomX.clear();
+
+ if (!randomY.empty())
+ randomY.clear();
+
+ if (!randomMinDist.empty())
+ randomMinDist.clear();
+
+ if (!randomT.empty())
+ randomT.clear();
+
+ if (!randomTN.empty())
+ randomTN.clear();
+
+ for (int l = 0; l < countOfRandomNumb; l++)
+ {
+ randomN.push_back((int)randomGenerator.uniform((int)0, (int)N));
+ randomX.push_back((int)randomGenerator.uniform(-1, +2));
+ randomY.push_back((int)randomGenerator.uniform(-1, +2));
+ randomMinDist.push_back((int)randomGenerator.uniform((int)0, (int)N));
+ randomT.push_back((int)randomGenerator.uniform((int)0, (int)T_upper));
+ randomTN.push_back((int)randomGenerator.uniform((int)0, (int)T_upper));
+ }
+}
+
+PBAS::~PBAS(void)
+{
+ std::cout << "~PBAS()" << std::endl;
+
+ randomN.clear();
+ randomX.clear();
+ randomY.clear();
+ randomMinDist.clear();
+ randomT.clear();
+ randomTN.clear();
+
+ for (int k = 0; k < backgroundModel.size(); ++k)
+ {
+ if (chans == 1)
+ {
+ backgroundModel.at(k).at(0).release();
+ backgroundModel.at(k).at(1).release();
+ }
+ else
+ {
+ backgroundModel.at(k).at(0).release();
+ backgroundModel.at(k).at(1).release();
+ backgroundModel.at(k).at(2).release();
+
+ backgroundModel.at(k).at(3).release();
+ backgroundModel.at(k).at(4).release();
+ backgroundModel.at(k).at(5).release();
+ }
+ }
+
+ backgroundModel.clear();
+ meanMinDist.release();
+
+ actualR.release();
+ actualT.release();
+
+ sobelX.release();
+ sobelY.release();
+}
+
+bool PBAS::process(cv::Mat* input, cv::Mat* output)
+{
+ if (width != input->cols)
+ {
+ width = input->cols;
+ chans = input->channels();
+ height = input->rows;
+
+ if (input->rows < 1 || input->cols < 1)
+ {
+ std::cout << "Error: Occurrence of to small (or empty?) image size in PBAS. STOPPING " << std::endl;
+ return false;
+ }
+ }
+
+ //iniate the background model
+ init(input);
+
+ resultMap = new cv::Mat(input->rows, input->cols, CV_8UC1);
+
+ //calculate features
+ calculateFeatures(¤tFeatures, input);
+
+ //set sumMagnitude to zero at beginning and then sum up in the loop
+ sumMagnitude = 0;
+ long glCounterFore = 0;
+ isMove = false;
+
+ //Here starts the whole processing of each pixel of the image
+ // for each pixel
+ for (int j = 0; j < resultMap->rows; ++j)
+ {
+ resultMap_Pt = resultMap->ptr<uchar>(j);
+ currentFeaturesM_Pt.clear();
+ currentFeaturesC_Pt.clear();
+ std::vector<float*> fT;
+ std::vector<uchar*> uT;
+ B_Mag_Pts.clear();
+ B_Col_Pts.clear();
+
+ for (int z = 0; z < chans; ++z)
+ {
+ currentFeaturesM_Pt.push_back(currentFeatures.at(z).ptr<float>(j));
+ currentFeaturesC_Pt.push_back(currentFeatures.at(z + chans).ptr<uchar>(j));
+
+ B_Mag_Pts.push_back(fT);
+
+ B_Col_Pts.push_back(uT);
+ }
+
+ meanMinDist_Pt = meanMinDist.ptr<float>(j);
+ actualR_Pt = actualR.ptr<float>(j);
+ actualT_Pt = actualT.ptr<float>(j);
+
+ for (int k = 0; k < runs; ++k)
+ {
+ for (int z = 0; z < chans; ++z)
+ {
+ B_Mag_Pts.at(z).push_back(backgroundModel.at(k).at(z).ptr<float>(j));
+ B_Col_Pts.at(z).push_back(backgroundModel.at(k).at(z + chans).ptr<uchar>(j));
+ }
+ }
+
+ for (int i = 0; i < resultMap->cols; ++i)
+ {
+ //Compare each pixel to in the worst runtime-case each background model
+ int count = 0;
+ int index = 0;
+
+ double norm = 0.0;
+ double dist = 0.0;
+ double minDist = 1000.0;
+ int entry = randomGenerator.uniform(3, countOfRandomNumb - 4);
+
+ do
+ {
+ if (chans == 3)
+ {
+ norm = sqrt(
+ (((double)B_Mag_Pts.at(0).at(index)[i] - ((double)*currentFeaturesM_Pt.at(0)))*((double)B_Mag_Pts.at(0).at(index)[i] - ((double)*currentFeaturesM_Pt.at(0)))) +
+ (((double)B_Mag_Pts.at(1).at(index)[i] - ((double)*currentFeaturesM_Pt.at(1)))*((double)B_Mag_Pts.at(1).at(index)[i] - ((double)*currentFeaturesM_Pt.at(1)))) +
+ (((double)B_Mag_Pts.at(2).at(index)[i] - ((double)*currentFeaturesM_Pt.at(2)))*((double)B_Mag_Pts.at(2).at(index)[i] - ((double)*currentFeaturesM_Pt.at(2))))
+ );
+
+ dist = sqrt(
+ (((double)B_Col_Pts.at(0).at(index)[i] - ((double)*currentFeaturesC_Pt.at(0)))*((double)B_Col_Pts.at(0).at(index)[i] - ((double)*currentFeaturesC_Pt.at(0)))) +
+ (((double)B_Col_Pts.at(1).at(index)[i] - ((double)*currentFeaturesC_Pt.at(1)))*((double)B_Col_Pts.at(1).at(index)[i] - ((double)*currentFeaturesC_Pt.at(1)))) +
+ (((double)B_Col_Pts.at(2).at(index)[i] - ((double)*currentFeaturesC_Pt.at(2)))*((double)B_Col_Pts.at(2).at(index)[i] - ((double)*currentFeaturesC_Pt.at(2))))
+ );
+ }
+ else
+ {
+ norm = abs((((double)B_Mag_Pts.at(0).at(index)[i] -
+ ((double)*currentFeaturesM_Pt.at(0)))*((double)B_Mag_Pts.at(0).at(index)[i] - ((double)*currentFeaturesM_Pt.at(0)))));
+
+ dist = abs((((double)B_Col_Pts.at(0).at(index)[i] -
+ ((double)*currentFeaturesC_Pt.at(0)))*((double)B_Col_Pts.at(0).at(index)[i] - ((double)*currentFeaturesC_Pt.at(0))))
+ );
+ }
+ dist = ((double)alpha*(norm / formerMeanMag) + beta*dist);
+
+ if ((dist < *actualR_Pt))
+ {
+ ++count;
+ if (minDist > dist)
+ minDist = dist;
+ }
+ else
+ {
+ sumMagnitude += (double)(norm);
+ ++glCounterFore;
+ }
+ ++index;
+ } while ((count < Raute_min) && (index < runs));
+
+
+ //#############################################
+ //update backgroundmodel
+ // is BACKGROUND
+ if (count >= Raute_min)
+ {
+ *resultMap_Pt = 0;
+ double ratio = std::ceil((double)T_upper / (double)(*actualT_Pt));
+ //in the first run every distance is zero, because there is no background model
+ //in the secont run, we have already one image as background model, hence a
+ // reasonable minDist could be found -> because of the partly 1/run changing in the running average, we set in the first try meanMinDist to the actual minDist value
+ if (runs < N && runs > 2)
+ {
+ *meanMinDist_Pt = ((((float)(runs - 1)) * (*meanMinDist_Pt)) + (float)minDist) / ((float)runs);
+ }
+ else if (runs < N && runs == 2)
+ {
+ *meanMinDist_Pt = (float)minDist;
+ }
+
+ //1. update model
+ if (runs == N)
+ {
+ //Update current pixel
+ //check if random numer is smaller than ratio
+ if (randomT.at(entry) < ratio)
+ {
+ // replace randomly chosen sample
+ int rand = randomN.at(entry + 1); //randomGenerator.uniform((int)0,(int)N-1);
+ for (int z = 0; z < chans; ++z)
+ {
+ B_Mag_Pts.at(z).at(rand)[i] = (float)*currentFeaturesM_Pt.at(z);
+ B_Col_Pts.at(z).at(rand)[i] = (uchar)*currentFeaturesC_Pt.at(z);
+
+ }
+
+ *meanMinDist_Pt = ((((float)(N - 1)) * (*meanMinDist_Pt)) + (float)minDist) / ((float)N);
+ }
+
+ //Update neighboring pixel model
+ if (randomTN.at(entry) < ratio)
+ {
+ //choose neighboring pixel randomly
+ int xNeigh = randomX.at(entry) + i;
+ int yNeigh = randomY.at(entry) + j;
+ checkValid(&xNeigh, &yNeigh);
+
+ // replace randomly chosen sample
+ int rand = randomN.at(entry - 1);
+ for (int z = 0; z < chans; ++z)
+ {
+ (backgroundModel.at(rand)).at(z).at<float>(yNeigh, xNeigh) = currentFeatures.at(z).at<float>(yNeigh, xNeigh);
+ (backgroundModel.at(rand)).at(z + chans).at<uchar>(yNeigh, xNeigh) = currentFeatures.at(z + chans).at<uchar>(yNeigh, xNeigh);
+ }
+ }
+ }
+ }
+ else
+ {
+ // store pixel as foreground
+ *resultMap_Pt = 255;
+
+ //there is some movement
+ isMove = true;
+ }
+
+ //#######################//#######################//#######################//#######################
+ //control loops
+ //#######################//#######################//#######################//#######################
+ //update R
+ decisionThresholdRegulator(actualR_Pt, meanMinDist_Pt);
+
+ //update T
+ learningRateRegulator(actualT_Pt, meanMinDist_Pt, resultMap_Pt);
+
+ //#######################//#######################//#######################//#######################
+ //#######################//#######################//#######################//#######################
+
+ //jump to next pixel
+ ++resultMap_Pt;
+ for (int z = 0; z < chans; ++z)
+ {
+ ++currentFeaturesM_Pt.at(z);
+ ++currentFeaturesC_Pt.at(z);
+ }
+
+ ++meanMinDist_Pt;
+ ++actualR_Pt;
+ ++actualT_Pt;
+ }
+ }
+
+ resultMap->copyTo(*output);
+
+ //if there is no foreground -> no magnitudes fount
+ //-> initiate some low value to prevent diving through zero
+ double meanMag = sumMagnitude / (double)(glCounterFore + 1); //height*width);
+
+ if (meanMag > 20)
+ formerMeanMag = meanMag;
+ else
+ formerMeanMag = 20;
+
+ delete resultMap;
+
+ for (int z = 0; z < chans; ++z)
+ {
+ currentFeatures.at(z + chans).release();
+ currentFeatures.at(z).release();
+ }
+
+ return true;
+}
+
+void PBAS::decisionThresholdRegulator(float* pt, float* meanDist)
+{
+ //update R
+ double tempR = *pt;
+ double newThresh = (*meanDist)*R_scale;
+
+ if (tempR < newThresh)
+ {
+ tempR += tempR * R_incdec;
+ }
+ else
+ {
+ tempR -= tempR * R_incdec;
+ }
+
+ if (tempR >= R_lower)
+ *pt = (float)tempR;
+ else
+ *pt = (float)R_lower;
+}
+
+void PBAS::learningRateRegulator(float* pt, float* meanDist, uchar* isFore)
+{
+ //time update
+ double tempT = *pt;
+
+ if ((int)*isFore < 128)
+ {
+ tempT -= T_inc / (*meanDist + 1.0);
+ }
+ else
+ {
+ tempT += T_dec / (*meanDist + 1.0);
+ }
+
+ if (tempT > T_lower && tempT < T_upper)
+ *pt = (float)tempT;
+}
+
+void PBAS::checkValid(int *x, int *y)
+{
+ if (*x < 0)
+ {
+ *x = 0;
+ }
+ else if (*x >= width)
+ {
+ *x = width - 1;
+ }
+
+ if (*y < 0)
+ {
+ *y = 0;
+ }
+ else if (*y >= height)
+ {
+ *y = height - 1;
+ }
+}
+
+void PBAS::init(cv::Mat* input)
+{
+ if (runs < N)
+ {
+ std::vector<cv::Mat> init;
+ calculateFeatures(&init, input);
+ backgroundModel.push_back(init);
+
+ if (chans == 1)
+ {
+ init.at(0).release();
+ init.at(1).release();
+ }
+ else
+ {
+ init.at(0).release();
+ init.at(1).release();
+ init.at(2).release();
+ init.at(3).release();
+ init.at(4).release();
+ init.at(5).release();
+ }
+
+ init.clear();
+
+ if (runs == 0)
+ {
+ meanMinDist.create(input->size(), CV_32FC1);
+ meanMinDist.zeros(input->rows, input->cols, CV_32FC1);
+
+ actualR.create(input->rows, input->cols, CV_32FC1);
+ actualT.create(input->rows, input->cols, CV_32FC1);
+
+ float* ptRs, *ptTs; //, *ptM;
+ for (int rows = 0; rows < actualR.rows; ++rows)
+ {
+ ptRs = actualR.ptr<float>(rows);
+ ptTs = actualT.ptr<float>(rows);
+
+ for (int cols = 0; cols < actualR.cols; ++cols)
+ {
+ ptRs[cols] = (float)R_lower;
+ ptTs[cols] = (float)T_init;
+ }
+ }
+ }
+
+ ++runs;
+ }
+}
+
+void PBAS::calculateFeatures(std::vector<cv::Mat>* feature, cv::Mat* inputImage)
+{
+ if (!feature->empty())
+ feature->clear();
+
+ cv::Mat mag[3], dir;
+
+ if (inputImage->channels() == 3)
+ {
+ std::vector<cv::Mat> rgbChannels(3);
+ cv::split(*inputImage, rgbChannels);
+
+ for (int l = 0; l < 3; ++l)
+ {
+ cv::Sobel(rgbChannels.at(l), sobelX, CV_32F, 1, 0, 3, 1, 0.0);
+ cv::Sobel(rgbChannels.at(l), sobelY, CV_32F, 0, 1, 3, 1, 0.0);
+
+ // Compute the L2 norm and direction of the gradient
+ cv::cartToPolar(sobelX, sobelY, mag[l], dir, true);
+ feature->push_back(mag[l]);
+ sobelX.release();
+ sobelY.release();
+ }
+
+ feature->push_back(rgbChannels.at(0));
+ feature->push_back(rgbChannels.at(1));
+ feature->push_back(rgbChannels.at(2));
+ rgbChannels.at(0).release();
+ rgbChannels.at(1).release();
+ rgbChannels.at(2).release();
+ }
+ else
+ {
+ cv::Sobel(*inputImage, sobelX, CV_32F, 1, 0, 3, 1, 0.0);
+ cv::Sobel(*inputImage, sobelY, CV_32F, 0, 1, 3, 1, 0.0);
+
+ // Compute the L2 norm and direction of the gradient
+ cv::cartToPolar(sobelX, sobelY, mag[0], dir, true);
+ feature->push_back(mag[0]);
+
+ cv::Mat temp;
+ inputImage->copyTo(temp);
+ feature->push_back(temp);
+ temp.release();
+ }
+
+ mag[0].release();
+ mag[1].release();
+ mag[2].release();
+ dir.release();
+}
+
+void PBAS::setN(int temp)
+{
+ N = temp;
+ newInitialization();
+}
+
+void PBAS::setRaute_min(int temp)
+{
+ Raute_min = temp;
+}
+
+void PBAS::setR_lower(double temp)
+{
+ R_lower = temp;
+}
+
+void PBAS::setR_incdec(double temp)
+{
+ R_incdec = temp;
+}
+
+void PBAS::setR_scale(double temp)
+{
+ R_scale = temp;
+}
+
+void PBAS::setT_init(double temp)
+{
+ T_init = temp;
+}
+
+void PBAS::setT_lower(double temp)
+{
+ T_lower = temp;
+}
+
+void PBAS::setT_upper(double temp)
+{
+ T_upper = temp;
+ newInitialization();
+}
+
+void PBAS::setT_dec(double temp)
+{
+ T_dec = temp;
+}
+
+void PBAS::setT_inc(double temp)
+{
+ T_inc = temp;
+}
+
+void PBAS::setAlpha(double temp)
+{
+ alpha = temp;
+}
+
+void PBAS::setBeta(double temp)
+{
+ beta = temp;
+}
+
+bool PBAS::isMovement()
+{
+ return isMove;
+}
+
+//cv::Mat* PBAS::getR1_xi()
+//{
+// return &actualR;
+//}
+//
+//cv::Mat* PBAS::getT_xi()
+//{
+// return &actualT;
+//}
diff --git a/package_bgs/PBAS/PBAS.h b/package_bgs/PBAS/PBAS.h
new file mode 100644
index 0000000..9014a28
--- /dev/null
+++ b/package_bgs/PBAS/PBAS.h
@@ -0,0 +1,207 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+//Implementation of the PBAS from:
+//
+//M. Hofmann, P. Tiefenbacher, G. Rigoll
+//"Background Segmentation with Feedback: The Pixel-Based Adaptive Segmenter",
+//in proc of IEEE Workshop on Change Detection, 2012
+//
+//Note: some changes, to improve the speed and memory requirements, were achieved in comparison to the
+//described PBAS algorithm in the paper above.
+//
+//Example usage:
+// //Somewhere during initalization:
+// #include "PBAS.h"
+// #include <opencv2/opencv.hpp>
+// PBAS pbas;
+//
+// //you might want to change some parameters of the PBAS here...
+// ....
+//
+// //repeat for each frame
+// //make gaussian blur for reducing image noise
+//cv::Mat bluredImage;
+//cv::Mat pbastResult;
+//cv::GaussianBlur(singleFrame, bluredImage, cv::Size(5,5), 1.5);
+//
+// //process image and receive segmentation in pbasResult
+//pbas.process(&bluredImage, &pbasResult);
+//
+// //make medianBlur on the result to reduce "salt and pepper noise"
+// //of the per pixel wise segmentation
+//cv::medianBlur(pbasResult, pbasResult, 5);
+//
+//
+//
+//Author: P.Tiefenbacher, https://sites.google.com/site/pbassegmenter/
+//Technische Universität München, Germany
+//Date: 22-May-2012, Version:0.1
+///////////
+#pragma once
+
+#include <iostream>
+#include <opencv2/opencv.hpp>
+//#include <highgui.h>
+
+class PBAS
+{
+public:
+ PBAS(void);
+ ~PBAS(void);
+ bool process(cv::Mat* input, cv::Mat* output);
+
+ void setN(int);
+ void setRaute_min(int);
+ void setR_lower(double);
+ void setR_incdec(double);
+ void setR_scale(double);
+ void setT_init(double);
+ void setT_lower(double);
+ void setT_upper(double);
+ void setT_dec(double);
+ void setT_inc(double);
+ void setAlpha(double);
+ void setBeta(double);
+
+ bool isMovement();
+
+
+private:
+ void calculateFeatures(std::vector<cv::Mat>* feature, cv::Mat* inputImage);
+ void checkValid(int *x, int *y);
+ void decisionThresholdRegulator(float* pt, float* meanDistArr);
+ void learningRateRegulator(float* pt, float* meanDist, uchar* isFore);
+ void init(cv::Mat*);
+ void newInitialization();
+
+ cv::Mat meanMinDist;
+ float* meanMinDist_Pt;
+
+
+
+ int width, height;
+ int chans;
+
+ //balance of feature pixel value to conture value
+ double alpha, beta;
+ //##################################################################################
+
+ double formerMeanNorm;
+
+ //define value of foreground/background pixels
+ int foregroundValue, backgroundValue;
+
+ //##################################################################################
+ //random number parameters
+
+ //random number generator
+ cv::RNG randomGenerator;
+
+ //length of random array initialization
+ long countOfRandomNumb;
+
+ //pre - initialize the randomNumbers for better performance
+ std::vector<int> randomN, randomMinDist, randomX, randomY, randomT, randomTN;
+
+ //###################################################################################
+
+ //check if something is moving
+ bool isMove;
+
+ //for init, count number of runs
+ int runs;
+
+
+ cv::Mat* resultMap;
+ std::vector<cv::Mat> currentFeatures;
+
+ std::vector<float*> currentFeaturesM_Pt;
+ std::vector<uchar*> currentFeaturesC_Pt;
+ uchar* resultMap_Pt;
+
+ std::vector<std::vector<float*>>B_Mag_Pts;
+ std::vector<std::vector<uchar*>>B_Col_Pts;
+
+ double sumMagnitude;
+ double formerMeanMag;
+ float formerDistanceBack;
+
+ //####################################################################################
+ //N - Number: Defining the size of the background-history-model
+ // number of samples per pixel
+ //size of background history B(x_i)
+ int N;
+ // background model
+ std::vector<std::vector<cv::Mat>> backgroundModel;
+ //####################################################################################
+ //####################################################################################
+ //R-Threshhold - Variables
+ //minimal Threshold for foreground and initial value of R(x_i)
+ // radius of the sphere -> lower border boundary
+ double R_lower;
+
+ //factor which defines new threshold of R(x_i) together with meanMinDist(x_i)
+ // scale for the sphere threshhold to define pixel-based Thresholds
+ double R_scale;
+
+ //decreasing / increasing factor of R(x_i)
+ // increasing/decreasing factor for the r-Threshold based on the result of rTreshScale * meanMinDistBackground
+ double R_incdec;
+
+ cv::Mat actualR;
+ float* actualR_Pt; //new pixel-based r-threshhold -> pointer to arrays
+ //#####################################################################################
+ //####################################################################################
+ //counter for minimal distance to background
+ // Defining the number of background-model-images, which have a lowerDIstance to the current Image than defined by the R-Thresholds, that are necessary
+ // to decide that this pixel is background
+ int Raute_min;
+ //#####################################################################################
+ //####################################################################################
+ //initial value of inverse update factor T(x_i)
+ // Initialize the background-model update rate
+ double T_init;
+
+ //increasing Factor of the update rate 1/T(x_i)
+ // scale that defines the increasing of the update rate of the background model, if the current pixel is background
+ //--> more frequently updates if pixel is background because, there shouln't be any change
+ double T_inc;
+
+ //upper boundary of T(x_i)
+ // defining an upper value, that nrSubsampling can achieve, thus it doesn't reach to an infinite value, where actually no update is possible
+ // at all
+ double T_upper;
+
+ //lower boundary of T(x_i)
+ // defining a minimum value for nrSubsampling --> base value 2.0
+ double T_lower;
+
+ //decreasing factor of the update rate 1/T(x_i)
+ // opposite scale to increasingRateScale, for decreasing the update rate of the background model, if the current pixel is foreground
+ //--> Thesis: Our Foreground is a real moving object -> thus the background-model is good, so don't update it
+ double T_dec;
+
+ //holds update rate of current pixel
+ cv::Mat actualT;
+ float* actualT_Pt;
+
+ //#####################################################################################
+
+
+ cv::Mat sobelX, sobelY;
+};
+
diff --git a/package_bgs/PixelBasedAdaptiveSegmenter.cpp b/package_bgs/PixelBasedAdaptiveSegmenter.cpp
new file mode 100644
index 0000000..8a3de97
--- /dev/null
+++ b/package_bgs/PixelBasedAdaptiveSegmenter.cpp
@@ -0,0 +1,126 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "PixelBasedAdaptiveSegmenter.h"
+
+using namespace bgslibrary::algorithms;
+
+PixelBasedAdaptiveSegmenter::PixelBasedAdaptiveSegmenter() :
+ enableInputBlur(true), enableOutputBlur(true),
+ alpha(7.0), beta(1.0), N(20), Raute_min(2), R_incdec(0.05), R_lower(18),
+ R_scale(5), T_dec(0.05), T_inc(1), T_init(18), T_lower(2), T_upper(200)
+{
+ std::cout << "PixelBasedAdaptiveSegmenter()" << std::endl;
+ setup("./config/PixelBasedAdaptiveSegmenter.xml");
+}
+
+PixelBasedAdaptiveSegmenter::~PixelBasedAdaptiveSegmenter()
+{
+ std::cout << "~PixelBasedAdaptiveSegmenter()" << std::endl;
+}
+
+void PixelBasedAdaptiveSegmenter::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (firstTime)
+ {
+ pbas.setAlpha(alpha);
+ pbas.setBeta(beta);
+ pbas.setN(N);
+ pbas.setRaute_min(Raute_min);
+ pbas.setR_incdec(R_incdec);
+ pbas.setR_lower(R_lower);
+ pbas.setR_scale(R_scale);
+ pbas.setT_dec(T_dec);
+ pbas.setT_inc(T_inc);
+ pbas.setT_init(T_init);
+ pbas.setT_lower(T_lower);
+ pbas.setT_upper(T_upper);
+ }
+
+ cv::Mat img_input_new;
+ if (enableInputBlur)
+ cv::GaussianBlur(img_input, img_input_new, cv::Size(5, 5), 1.5);
+ else
+ img_input.copyTo(img_input_new);
+
+ pbas.process(&img_input_new, &img_foreground);
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+ if (enableOutputBlur)
+ cv::medianBlur(img_foreground, img_foreground, 5);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("PBAS", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+
+ firstTime = false;
+}
+
+void PixelBasedAdaptiveSegmenter::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "enableInputBlur", enableInputBlur);
+ cvWriteInt(fs, "enableOutputBlur", enableOutputBlur);
+
+ cvWriteReal(fs, "alpha", alpha);
+ cvWriteReal(fs, "beta", beta);
+ cvWriteInt(fs, "N", N);
+ cvWriteInt(fs, "Raute_min", Raute_min);
+ cvWriteReal(fs, "R_incdec", R_incdec);
+ cvWriteInt(fs, "R_lower", R_lower);
+ cvWriteInt(fs, "R_scale", R_scale);
+ cvWriteReal(fs, "T_dec", T_dec);
+ cvWriteInt(fs, "T_inc", T_inc);
+ cvWriteInt(fs, "T_init", T_init);
+ cvWriteInt(fs, "T_lower", T_lower);
+ cvWriteInt(fs, "T_upper", T_upper);
+
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void PixelBasedAdaptiveSegmenter::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ enableInputBlur = cvReadIntByName(fs, nullptr, "enableInputBlur", true);
+ enableOutputBlur = cvReadIntByName(fs, nullptr, "enableOutputBlur", true);
+
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 7.0);
+ beta = cvReadRealByName(fs, nullptr, "beta", 1.0);
+ N = cvReadIntByName(fs, nullptr, "N", 20);
+ Raute_min = cvReadIntByName(fs, nullptr, "Raute_min", 2);
+ R_incdec = cvReadRealByName(fs, nullptr, "R_incdec", 0.05);
+ R_lower = cvReadIntByName(fs, nullptr, "R_lower", 18);
+ R_scale = cvReadIntByName(fs, nullptr, "R_scale", 5);
+ T_dec = cvReadRealByName(fs, nullptr, "T_dec", 0.05);
+ T_inc = cvReadIntByName(fs, nullptr, "T_inc", 1);
+ T_init = cvReadIntByName(fs, nullptr, "T_init", 18);
+ T_lower = cvReadIntByName(fs, nullptr, "T_lower", 2);
+ T_upper = cvReadIntByName(fs, nullptr, "T_upper", 200);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/PixelBasedAdaptiveSegmenter.h b/package_bgs/PixelBasedAdaptiveSegmenter.h
new file mode 100644
index 0000000..36dd0ad
--- /dev/null
+++ b/package_bgs/PixelBasedAdaptiveSegmenter.h
@@ -0,0 +1,58 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "PBAS/PBAS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class PixelBasedAdaptiveSegmenter : public IBGS
+ {
+ private:
+ PBAS pbas;
+
+ bool enableInputBlur;
+ bool enableOutputBlur;
+
+ float alpha;
+ float beta;
+ int N;
+ int Raute_min;
+ float R_incdec;
+ int R_lower;
+ int R_scale;
+ float T_dec;
+ int T_inc;
+ int T_init;
+ int T_lower;
+ int T_upper;
+
+ public:
+ PixelBasedAdaptiveSegmenter();
+ ~PixelBasedAdaptiveSegmenter();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/SigmaDelta.cpp b/package_bgs/SigmaDelta.cpp
new file mode 100644
index 0000000..d305226
--- /dev/null
+++ b/package_bgs/SigmaDelta.cpp
@@ -0,0 +1,101 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "SigmaDelta.h"
+
+using namespace bgslibrary::algorithms;
+
+SigmaDelta::SigmaDelta() :
+ ampFactor(1), minVar(15), maxVar(255), algorithm(sdLaMa091New())
+{
+ applyParams();
+ std::cout << "SigmaDelta()" << std::endl;
+ setup("./config/SigmaDelta.xml");
+}
+
+SigmaDelta::~SigmaDelta()
+{
+ sdLaMa091Free(algorithm);
+ std::cout << "~SigmaDelta()" << std::endl;
+}
+
+void SigmaDelta::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (firstTime)
+ {
+ sdLaMa091AllocInit_8u_C3R(algorithm, img_input.data, img_input.cols, img_input.rows, img_input.step);
+ img_foreground = cv::Mat(img_input.size(), CV_8UC1);
+ img_background = cv::Mat(img_input.size(), CV_8UC3);
+ firstTime = false;
+ }
+ else
+ {
+ cv::Mat img_output_tmp(img_input.rows, img_input.cols, CV_8UC3);
+ sdLaMa091Update_8u_C3R(algorithm, img_input.data, img_output_tmp.data);
+
+ unsigned char* tmpBuffer = (unsigned char*)img_output_tmp.data;
+ unsigned char* outBuffer = (unsigned char*)img_foreground.data;
+
+ for (size_t i = 0; i < img_foreground.total(); ++i) {
+ *outBuffer = *tmpBuffer;
+ ++outBuffer;
+ tmpBuffer += img_output_tmp.channels();
+ }
+ }
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("Sigma-Delta", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+}
+
+void SigmaDelta::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "ampFactor", ampFactor);
+ cvWriteInt(fs, "minVar", minVar);
+ cvWriteInt(fs, "maxVar", maxVar);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void SigmaDelta::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ ampFactor = cvReadIntByName(fs, nullptr, "ampFactor", 1);
+ minVar = cvReadIntByName(fs, nullptr, "minVar", 15);
+ maxVar = cvReadIntByName(fs, nullptr, "maxVar", 255);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ applyParams();
+
+ cvReleaseFileStorage(&fs);
+}
+
+void SigmaDelta::applyParams()
+{
+ sdLaMa091SetAmplificationFactor(algorithm, ampFactor);
+ sdLaMa091SetMinimalVariance(algorithm, minVar);
+ sdLaMa091SetMaximalVariance(algorithm, maxVar);
+}
diff --git a/package_bgs/SigmaDelta.h b/package_bgs/SigmaDelta.h
new file mode 100644
index 0000000..c7b1a2c
--- /dev/null
+++ b/package_bgs/SigmaDelta.h
@@ -0,0 +1,49 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+
+//extern "C" {
+#include "SigmaDelta/sdLaMa091.h"
+//}
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class SigmaDelta : public IBGS
+ {
+ private:
+ unsigned int ampFactor;
+ unsigned int minVar;
+ unsigned int maxVar;
+ sdLaMa091_t* algorithm;
+
+ public:
+ SigmaDelta();
+ ~SigmaDelta();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ void applyParams();
+ };
+ }
+}
diff --git a/package_bgs/bl/sdLaMa091.cpp b/package_bgs/SigmaDelta/sdLaMa091.cpp
similarity index 97%
rename from package_bgs/bl/sdLaMa091.cpp
rename to package_bgs/SigmaDelta/sdLaMa091.cpp
index 7071438..286556b 100644
--- a/package_bgs/bl/sdLaMa091.cpp
+++ b/package_bgs/SigmaDelta/sdLaMa091.cpp
@@ -84,7 +84,7 @@ static inline uint8_t max(uint8_t a, uint8_t b) {
}
sdLaMa091_t* sdLaMa091New(void) {
- sdLaMa091_t* sdLaMa091 = (sdLaMa091_t*) malloc(sizeof(*sdLaMa091));
+ sdLaMa091_t* sdLaMa091 = (sdLaMa091_t*)malloc(sizeof(*sdLaMa091));
#ifdef DEFENSIVE_ALLOC
if (sdLaMa091 == NULL) {
@@ -151,7 +151,7 @@ int32_t sdLaMa091AllocInit_8u_C1R(sdLaMa091_t* sdLaMa091,
sdLaMa091->numBytes = stride * height;
sdLaMa091->unusedBytes = stride - sdLaMa091->width;
- sdLaMa091->Mt = (uint8_t*) malloc(sdLaMa091->numBytes);
+ sdLaMa091->Mt = (uint8_t*)malloc(sdLaMa091->numBytes);
#ifdef DEFENSIVE_ALLOC
if (sdLaMa091->Mt == NULL) {
outputError("Cannot allocate sdLaMa091->Mt table");
@@ -160,7 +160,7 @@ int32_t sdLaMa091AllocInit_8u_C1R(sdLaMa091_t* sdLaMa091,
#endif
memcpy(sdLaMa091->Mt, image_data, sdLaMa091->numBytes);
- sdLaMa091->Ot = (uint8_t*) malloc(sdLaMa091->numBytes);
+ sdLaMa091->Ot = (uint8_t*)malloc(sdLaMa091->numBytes);
#ifdef DEFENSIVE_ALLOC
if (sdLaMa091->Ot == NULL) {
outputError("Cannot allocate sdLaMa091->Ot table");
@@ -170,16 +170,16 @@ int32_t sdLaMa091AllocInit_8u_C1R(sdLaMa091_t* sdLaMa091,
uint8_t* workOt = sdLaMa091->Ot;
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->width; ++j, ++workOt)
*workOt = 0;
-
+
if (sdLaMa091->unusedBytes > 0)
workOt += sdLaMa091->unusedBytes;
}
- sdLaMa091->Vt = (uint8_t*) malloc(sdLaMa091->numBytes);
+ sdLaMa091->Vt = (uint8_t*)malloc(sdLaMa091->numBytes);
#ifdef DEFENSIVE_ALLOC
if (sdLaMa091->Vt == NULL) {
outputError("Cannot allocate sdLaMa091->Vt table");
@@ -188,13 +188,13 @@ int32_t sdLaMa091AllocInit_8u_C1R(sdLaMa091_t* sdLaMa091,
#endif
uint8_t* workVt = sdLaMa091->Vt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->width; ++j, ++workVt)
*workVt = sdLaMa091->Vmin;
-
+
if (sdLaMa091->unusedBytes > 0)
workVt += sdLaMa091->unusedBytes;
}
@@ -375,13 +375,13 @@ int32_t sdLaMa091Update_8u_C1R(sdLaMa091_t* sdLaMa091,
}
#endif
-
+
const uint8_t* workImage = image_data;
uint8_t* workMt = sdLaMa091->Mt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->width; ++j, ++workImage, ++workMt) {
if (*workMt < *workImage)
++(*workMt);
@@ -389,7 +389,7 @@ int32_t sdLaMa091Update_8u_C1R(sdLaMa091_t* sdLaMa091,
--(*workMt);
}
-
+
if (sdLaMa091->unusedBytes > 0) {
workImage += sdLaMa091->unusedBytes;
workMt += sdLaMa091->unusedBytes;
@@ -400,14 +400,14 @@ int32_t sdLaMa091Update_8u_C1R(sdLaMa091_t* sdLaMa091,
workMt = sdLaMa091->Mt;
uint8_t* workOt = sdLaMa091->Ot;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->width; ++j, ++workImage, ++workMt,
++workOt)
*workOt = absVal(*workMt - *workImage);
-
+
if (sdLaMa091->unusedBytes > 0) {
workImage += sdLaMa091->unusedBytes;
workMt += sdLaMa091->unusedBytes;
@@ -415,13 +415,13 @@ int32_t sdLaMa091Update_8u_C1R(sdLaMa091_t* sdLaMa091,
}
}
-
+
workOt = sdLaMa091->Ot;
uint8_t* workVt = sdLaMa091->Vt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->width; ++j, ++workOt, ++workVt) {
uint32_t ampOt = sdLaMa091->N * *workOt;
@@ -433,30 +433,30 @@ int32_t sdLaMa091Update_8u_C1R(sdLaMa091_t* sdLaMa091,
*workVt = max(min(*workVt, sdLaMa091->Vmax), sdLaMa091->Vmin);
}
-
+
if (sdLaMa091->unusedBytes > 0) {
workOt += sdLaMa091->unusedBytes;
workVt += sdLaMa091->unusedBytes;
}
}
-
+
workOt = sdLaMa091->Ot;
workVt = sdLaMa091->Vt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->width; ++j, ++segmentation_map,
++workOt, ++workVt) {
-
+
if (*workOt < *workVt)
*segmentation_map = BACKGROUND;
else
*segmentation_map = FOREGROUND;
}
-
+
if (sdLaMa091->unusedBytes > 0) {
segmentation_map += sdLaMa091->unusedBytes;
workOt += sdLaMa091->unusedBytes;
@@ -525,13 +525,13 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
}
#endif
-
+
const uint8_t* workImage = image_data;
uint8_t* workMt = sdLaMa091->Mt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->rgbWidth; ++j, ++workImage, ++workMt) {
if (*workMt < *workImage)
++(*workMt);
@@ -539,26 +539,26 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
--(*workMt);
}
-
+
if (sdLaMa091->rgbUnusedBytes > 0) {
workImage += sdLaMa091->rgbUnusedBytes;
workMt += sdLaMa091->rgbUnusedBytes;
}
}
-
+
workImage = image_data;
workMt = sdLaMa091->Mt;
uint8_t* workOt = sdLaMa091->Ot;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->rgbWidth; ++j, ++workImage, ++workMt,
++workOt)
*workOt = absVal(*workMt - *workImage);
-
+
if (sdLaMa091->rgbUnusedBytes > 0) {
workImage += sdLaMa091->rgbUnusedBytes;
workMt += sdLaMa091->rgbUnusedBytes;
@@ -569,9 +569,9 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
workOt = sdLaMa091->Ot;
uint8_t* workVt = sdLaMa091->Vt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
for (uint32_t j = 0; j < sdLaMa091->rgbWidth; ++j, ++workOt, ++workVt) {
uint32_t ampOt = sdLaMa091->N * *workOt;
@@ -583,7 +583,7 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
*workVt = max(min(*workVt, sdLaMa091->Vmax), sdLaMa091->Vmin);
}
-
+
if (sdLaMa091->rgbUnusedBytes > 0) {
workOt += sdLaMa091->rgbUnusedBytes;
workVt += sdLaMa091->rgbUnusedBytes;
@@ -593,19 +593,19 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
workOt = sdLaMa091->Ot;
workVt = sdLaMa091->Vt;
-
+
for (uint32_t i = 0; i < sdLaMa091->numBytes; i += sdLaMa091->stride) {
-
+
uint32_t numColor = 0;
-
+
bool isForeground = false;
-
+
for (uint32_t j = 0; j < sdLaMa091->rgbWidth; ++j, ++workOt, ++workVt) {
if (*workOt >= *workVt)
isForeground = true;
-
+
if (numColor == BLUE) {
if (isForeground) {
*segmentation_map = FOREGROUND;
@@ -626,7 +626,7 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
numColor = (numColor + 1) % CHANNELS;
}
-
+
if (sdLaMa091->rgbUnusedBytes > 0) {
segmentation_map += sdLaMa091->rgbUnusedBytes;
workOt += sdLaMa091->rgbUnusedBytes;
diff --git a/package_bgs/bl/sdLaMa091.h b/package_bgs/SigmaDelta/sdLaMa091.h
similarity index 96%
rename from package_bgs/bl/sdLaMa091.h
rename to package_bgs/SigmaDelta/sdLaMa091.h
index bec93fb..cf9e777 100644
--- a/package_bgs/bl/sdLaMa091.h
+++ b/package_bgs/SigmaDelta/sdLaMa091.h
@@ -14,11 +14,9 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#ifndef SD_LA_MA_091_H_
-#define SD_LA_MA_091_H_
+#pragma once
#include <errno.h>
-#include "stdbool.h"
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
@@ -68,5 +66,3 @@ int32_t sdLaMa091Update_8u_C3R(sdLaMa091_t* sdLaMa091,
uint8_t* segmentation_map);
int32_t sdLaMa091Free(sdLaMa091_t* sdLaMa091);
-
-#endif
diff --git a/package_bgs/StaticFrameDifferenceBGS.cpp b/package_bgs/StaticFrameDifference.cpp
similarity index 53%
rename from package_bgs/StaticFrameDifferenceBGS.cpp
rename to package_bgs/StaticFrameDifference.cpp
index 3463c45..2faa40c 100644
--- a/package_bgs/StaticFrameDifferenceBGS.cpp
+++ b/package_bgs/StaticFrameDifference.cpp
@@ -14,41 +14,41 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "StaticFrameDifferenceBGS.h"
+#include "StaticFrameDifference.h"
-StaticFrameDifferenceBGS::StaticFrameDifferenceBGS() : firstTime(true), enableThreshold(true), threshold(15), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+StaticFrameDifference::StaticFrameDifference() :
+ enableThreshold(true), threshold(15)
{
- std::cout << "StaticFrameDifferenceBGS()" << std::endl;
+ std::cout << "StaticFrameDifference()" << std::endl;
+ setup("./config/StaticFrameDifference.xml");
}
-StaticFrameDifferenceBGS::~StaticFrameDifferenceBGS()
+StaticFrameDifference::~StaticFrameDifference()
{
- std::cout << "~StaticFrameDifferenceBGS()" << std::endl;
+ std::cout << "~StaticFrameDifference()" << std::endl;
}
-void StaticFrameDifferenceBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void StaticFrameDifference::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
+ init(img_input, img_output, img_bgmodel);
- if(img_background.empty())
+ if (img_background.empty())
img_input.copyTo(img_background);
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
cv::absdiff(img_input, img_background, img_foreground);
- if(img_foreground.channels() == 3)
+ if (img_foreground.channels() == 3)
cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
- if(enableThreshold)
+ if (enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
cv::imshow("Static Frame Difference", img_foreground);
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -56,9 +56,9 @@ void StaticFrameDifferenceBGS::process(const cv::Mat &img_input, cv::Mat &img_ou
firstTime = false;
}
-void StaticFrameDifferenceBGS::saveConfig()
+void StaticFrameDifference::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/StaticFrameDifferenceBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "enableThreshold", enableThreshold);
cvWriteInt(fs, "threshold", threshold);
@@ -67,13 +67,13 @@ void StaticFrameDifferenceBGS::saveConfig()
cvReleaseFileStorage(&fs);
}
-void StaticFrameDifferenceBGS::loadConfig()
+void StaticFrameDifference::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/StaticFrameDifferenceBGS.xml", 0, CV_STORAGE_READ);
-
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/StaticFrameDifference.h b/package_bgs/StaticFrameDifference.h
new file mode 100644
index 0000000..8c8474c
--- /dev/null
+++ b/package_bgs/StaticFrameDifference.h
@@ -0,0 +1,42 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class StaticFrameDifference : public IBGS
+ {
+ private:
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ StaticFrameDifference();
+ ~StaticFrameDifference();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/SuBSENSE.cpp b/package_bgs/SuBSENSE.cpp
new file mode 100644
index 0000000..c8a0e5d
--- /dev/null
+++ b/package_bgs/SuBSENSE.cpp
@@ -0,0 +1,96 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "SuBSENSE.h"
+
+using namespace bgslibrary::algorithms;
+
+SuBSENSE::SuBSENSE() :
+ pSubsense(0),
+ fRelLBSPThreshold(BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD),
+ nDescDistThresholdOffset(BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET),
+ nMinColorDistThreshold(BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD),
+ nBGSamples(BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES),
+ nRequiredBGSamples(BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES),
+ nSamplesForMovingAvgs(BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS)
+{
+ std::cout << "SuBSENSE()" << std::endl;
+}
+
+SuBSENSE::~SuBSENSE() {
+ if (pSubsense)
+ delete pSubsense;
+ std::cout << "~SuBSENSE()" << std::endl;
+}
+
+void SuBSENSE::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (firstTime)
+ {
+ pSubsense = new BackgroundSubtractorSuBSENSE(
+ fRelLBSPThreshold, nDescDistThresholdOffset, nMinColorDistThreshold,
+ nBGSamples, nRequiredBGSamples, nSamplesForMovingAvgs);
+
+ pSubsense->initialize(img_input, cv::Mat(img_input.size(), CV_8UC1, cv::Scalar_<uchar>(255)));
+ firstTime = false;
+ }
+
+ pSubsense->apply(img_input, img_foreground);
+ pSubsense->getBackgroundImage(img_background);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
+ imshow("SuBSENSE FG", img_foreground);
+ imshow("SuBSENSE BG", img_background);
+ }
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
+}
+
+void SuBSENSE::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteReal(fs, "fRelLBSPThreshold", fRelLBSPThreshold);
+ cvWriteInt(fs, "nDescDistThresholdOffset", nDescDistThresholdOffset);
+ cvWriteInt(fs, "nMinColorDistThreshold", nMinColorDistThreshold);
+ cvWriteInt(fs, "nBGSamples", nBGSamples);
+ cvWriteInt(fs, "nRequiredBGSamples", nRequiredBGSamples);
+ cvWriteInt(fs, "nSamplesForMovingAvgs", nSamplesForMovingAvgs);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void SuBSENSE::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ fRelLBSPThreshold = cvReadRealByName(fs, nullptr, "fRelLBSPThreshold", BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD);
+ nDescDistThresholdOffset = cvReadIntByName(fs, nullptr, "nDescDistThresholdOffset", BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET);
+ nMinColorDistThreshold = cvReadIntByName(fs, nullptr, "nMinColorDistThreshold", BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD);
+ nBGSamples = cvReadIntByName(fs, nullptr, "nBGSamples", BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES);
+ nRequiredBGSamples = cvReadIntByName(fs, nullptr, "nRequiredBGSamples", BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES);
+ nSamplesForMovingAvgs = cvReadIntByName(fs, nullptr, "nSamplesForMovingAvgs", BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/SuBSENSE.h b/package_bgs/SuBSENSE.h
new file mode 100644
index 0000000..9ac9aa6
--- /dev/null
+++ b/package_bgs/SuBSENSE.h
@@ -0,0 +1,49 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "LBSP/BackgroundSubtractorSuBSENSE.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class SuBSENSE : public IBGS
+ {
+ private:
+ BackgroundSubtractorSuBSENSE* pSubsense;
+
+ float fRelLBSPThreshold;
+ size_t nDescDistThresholdOffset;
+ size_t nMinColorDistThreshold;
+ size_t nBGSamples;
+ size_t nRequiredBGSamples;
+ size_t nSamplesForMovingAvgs;
+
+ public:
+ SuBSENSE();
+ ~SuBSENSE();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/T2F/FuzzyUtils.cpp b/package_bgs/T2F/FuzzyUtils.cpp
new file mode 100644
index 0000000..a151136
--- /dev/null
+++ b/package_bgs/T2F/FuzzyUtils.cpp
@@ -0,0 +1,512 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "FuzzyUtils.h"
+
+FuzzyUtils::FuzzyUtils(void) {}
+
+FuzzyUtils::~FuzzyUtils(void) {}
+
+void FuzzyUtils::LBP(IplImage* InputImage, IplImage* LBPimage)
+{
+ PixelUtils p;
+
+ float* neighberPixel = (float*)malloc(9 * sizeof(float));
+ float* BinaryValue = (float*)malloc(9 * sizeof(float));
+ float* CarreExp = (float*)malloc(9 * sizeof(float));
+ float* valLBP = (float*)malloc(1 * sizeof(float));
+
+ *valLBP = 0;
+
+ int x = 0, y = 0;
+
+ // on implemente les 8 valeurs puissance de 2 qui correspondent aux 8 elem. d'image voisins au elem. d'image central
+ *(CarreExp + 0) = 1.0;
+ *(CarreExp + 1) = 2.0;
+ *(CarreExp + 2) = 4.0;
+ *(CarreExp + 3) = 8.0;
+ *(CarreExp + 4) = 0.0;
+ *(CarreExp + 5) = 16.0;
+ *(CarreExp + 6) = 32.0;
+ *(CarreExp + 7) = 64.0;
+ *(CarreExp + 8) = 128.0;
+
+ //le calcule de LBP
+ //pour les 4 coins
+ /* 1.*/
+ if (x == 0 && y == 0)
+ {
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 4, 0);
+ *valLBP = *valLBP + ((*(BinaryValue + 1))*(*(CarreExp + 1)) + (*(BinaryValue + 2))*(*(CarreExp + 2)) + (*(BinaryValue + 3))*(*(CarreExp + 3))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+
+ /* 2.*/
+ if (x == 0 && y == InputImage->width)
+ {
+ *valLBP = 0;
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 4, 1);
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp)) + (*(BinaryValue + 2))*(*(CarreExp + 2)) + (*(BinaryValue + 3))*(*(CarreExp + 3))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+
+ /* 3.*/
+ if (x == InputImage->height && y == 0)
+ {
+ *valLBP = 0;
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 4, 2);
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp)) + (*(BinaryValue + 1))*(*(CarreExp + 1)) + (*(BinaryValue + 3))*(*(CarreExp + 3))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+
+ /* 4.*/
+ if (x == InputImage->height && y == InputImage->width)
+ {
+ *valLBP = 0;
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 4, 3);
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp)) + (*(BinaryValue + 1))*(*(CarreExp + 1)) + (*(BinaryValue + 2))*(*(CarreExp + 2))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+
+ //le calcul de LBP pour la première ligne : L(0)
+ if (x == 0 && (y != 0 && y != InputImage->width))
+ {
+ for (int y = 1; y < InputImage->width - 1; y++)
+ {
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 6, 4);
+ *valLBP = 0;
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp)) + (*(BinaryValue + 1))*(*(CarreExp + 1)) + (*(BinaryValue + 2))*(*(CarreExp + 2)) + (*(BinaryValue + 3))*(*(CarreExp + 3)) + (*(BinaryValue + 5))*(*(CarreExp + 5))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+ }
+
+ //le calcul de LBP pour la dernière colonne : C(w)
+ if ((x != 0 && x != InputImage->height) && y == InputImage->width)
+ {
+ for (int x = 1; x < InputImage->height - 1; x++)
+ {
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 6, 4);
+ *valLBP = 0;
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp)) + (*(BinaryValue + 1))*(*(CarreExp + 1)) + (*(BinaryValue + 2))*(*(CarreExp + 2)) + (*(BinaryValue + 3))*(*(CarreExp + 3)) + (*(BinaryValue + 5))*(*(CarreExp + 5))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+ }
+
+ //le calcul de LBP pour la dernière ligne : L(h)
+ if (x == InputImage->height && (y != 0 && y != InputImage->width))
+ {
+ for (int y = 1; y < InputImage->width - 1; y++)
+ {
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 6, 1);
+ *valLBP = 0;
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp)) + (*(BinaryValue + 2))*(*(CarreExp + 2)) + (*(BinaryValue + 3))*(*(CarreExp + 3)) + (*(BinaryValue + 4))*(*(CarreExp + 4)) + (*(BinaryValue + 5))*(*(CarreExp + 5))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+ }
+
+ //le calcul de LBP pour la première colonne : C(0)
+ if ((x != 0 && x != InputImage->height) && y == 0)
+ {
+ for (int x = 1; x < InputImage->height - 1; x++)
+ {
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 6, 2);
+ *valLBP = 0;
+ *valLBP = *valLBP + ((*(BinaryValue))*(*(CarreExp + 5)) + (*(BinaryValue + 1))*(*(CarreExp + 6)) + (*(BinaryValue + 3))*(*(CarreExp + 3)) + (*(BinaryValue + 4))*(*(CarreExp)) + (*(BinaryValue + 5))*(*(CarreExp + 1))) / 255.0;
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+ }
+
+ //pour le reste des elements d'image
+ for (int y = 1; y < InputImage->height - 1; y++)
+ {
+ for (int x = 1; x < InputImage->width - 1; x++)
+ {
+ p.getNeighberhoodGrayPixel(InputImage, x, y, neighberPixel);
+ getBinValue(neighberPixel, BinaryValue, 9, 4);
+ //le calcul de la valeur du LBP pour chaque elem. d'im.
+ *valLBP = 0;
+ for (int l = 0; l < 9; l++)
+ *valLBP = *valLBP + ((*(BinaryValue + l)) * (*(CarreExp + l))) / 255.0;
+ //printf("\nvalLBP(%d,%d)=%f",x,y,*valLBP);
+ p.PutGrayPixel(LBPimage, x, y, *valLBP);
+ }
+ }
+
+ free(neighberPixel);
+ free(BinaryValue);
+ free(CarreExp);
+ free(valLBP);
+}
+
+void FuzzyUtils::getBinValue(float* neighberGrayPixel, float* BinaryValue, int m, int n)
+{
+ // la comparaison entre la valeur d'elem d'image central et les valeurs des elem. d'im. voisins
+ // m = le numero des elements (4, 6 ou 9);
+ // n = la position de l'element central;
+
+ int h = 0;
+ for (int k = 0; k < m; k++)
+ {
+ if (*(neighberGrayPixel + k) >= *(neighberGrayPixel + n))
+ {
+ *(BinaryValue + h) = 1;
+ h++;
+ }
+ else
+ {
+ *(BinaryValue + h) = 0;
+ h++;
+ }
+ }
+}
+
+void FuzzyUtils::SimilarityDegreesImage(IplImage* CurrentImage, IplImage* BGImage, IplImage* DeltaImage, int n, int color_space)
+{
+ PixelUtils p;
+ int i, j;
+
+ if (n == 1)
+ {
+ float* CurrentGrayPixel = (float*)malloc(1 * (sizeof(float)));
+ float* BGGrayPixel = (float*)malloc(1 * (sizeof(float)));
+ float* DeltaGrayPixel = (float*)malloc(1 * (sizeof(float)));
+
+ for (i = 0; i < CurrentImage->width; i++)
+ {
+ for (j = 0; j < CurrentImage->height; j++)
+ {
+ p.GetGrayPixel(CurrentImage, i, j, CurrentGrayPixel);
+ p.GetGrayPixel(BGImage, i, j, BGGrayPixel);
+ RatioPixels(CurrentGrayPixel, BGGrayPixel, DeltaGrayPixel, 1);
+ p.PutGrayPixel(DeltaImage, i, j, *DeltaGrayPixel);
+ }
+ }
+
+ free(CurrentGrayPixel);
+ free(BGGrayPixel);
+ free(DeltaGrayPixel);
+ }
+
+ if (n != 1)
+ {
+ IplImage* ConvertedCurrentImage = cvCreateImage(cvSize(CurrentImage->width, CurrentImage->height), IPL_DEPTH_32F, 3);
+ IplImage* ConvertedBGImage = cvCreateImage(cvSize(CurrentImage->width, CurrentImage->height), IPL_DEPTH_32F, 3);
+
+ float* ConvertedCurrentPixel = (float*)malloc(3 * (sizeof(float)));
+ float* ConvertedBGPixel = (float*)malloc(3 * (sizeof(float)));
+ float* DeltaConvertedPixel = (float*)malloc(3 * (sizeof(float)));
+
+ p.ColorConversion(CurrentImage, ConvertedCurrentImage, color_space);
+ p.ColorConversion(BGImage, ConvertedBGImage, color_space);
+
+ for (i = 0; i < CurrentImage->width; i++)
+ {
+ for (j = 0; j < CurrentImage->height; j++)
+ {
+ p.GetPixel(ConvertedCurrentImage, i, j, ConvertedCurrentPixel);
+ p.GetPixel(ConvertedBGImage, i, j, ConvertedBGPixel);
+ RatioPixels(ConvertedCurrentPixel, ConvertedBGPixel, DeltaConvertedPixel, 3);
+ p.PutPixel(DeltaImage, i, j, DeltaConvertedPixel);
+ }
+ }
+
+ free(ConvertedCurrentPixel);
+ free(ConvertedBGPixel);
+ free(DeltaConvertedPixel);
+
+ cvReleaseImage(&ConvertedCurrentImage);
+ cvReleaseImage(&ConvertedBGImage);
+ }
+}
+
+void FuzzyUtils::RatioPixels(float* CurrentPixel, float* BGPixel, float* DeltaPixel, int n)
+{
+ if (n == 1)
+ {
+ if (*CurrentPixel < *BGPixel)
+ *DeltaPixel = *CurrentPixel / *BGPixel;
+
+ if (*CurrentPixel > *BGPixel)
+ *DeltaPixel = *BGPixel / *CurrentPixel;
+
+ if (*CurrentPixel == *BGPixel)
+ *DeltaPixel = 1.0;
+ }
+
+ if (n == 3)
+ for (int i = 0; i < 3; i++)
+ {
+ if (*(CurrentPixel + i) < *(BGPixel + i))
+ *(DeltaPixel + i) = *(CurrentPixel + i) / *(BGPixel + i);
+
+ if (*(CurrentPixel + i) > *(BGPixel + i))
+ *(DeltaPixel + i) = *(BGPixel + i) / *(CurrentPixel + i);
+
+ if (*(CurrentPixel + i) == *(BGPixel + i))
+ *(DeltaPixel + i) = 1.0;
+ }
+}
+
+void FuzzyUtils::getFuzzyIntegralSugeno(IplImage* H, IplImage* Delta, int n, float *MeasureG, IplImage* OutputImage)
+{
+ // MeasureG : est un vecteur contenant 3 mesure g (g1,g2,g3) tel que : g1+g2+g3=1
+ // n : =2 cad aggreger les 2 images "H" et "Delta"
+ // =1 cad aggreger uniquement les valeurs des composantes couleurs de l'image "Delta"
+
+ PixelUtils p;
+
+ float* HTexturePixel = (float*)malloc(1 * sizeof(float));
+ float* DeltaOhtaPixel = (float*)malloc(3 * (sizeof(float)));
+ int *Indice = (int*)malloc(3 * (sizeof(int)));
+ float *HI = (float*)malloc(3 * (sizeof(float)));
+ float *Integral = (float*)malloc(3 * (sizeof(float)));
+ float* X = (float*)malloc(1 * sizeof(float));
+ float* XiXj = (float*)malloc(1 * sizeof(float));
+ float IntegralFlou;
+
+ *Indice = 0;
+ *(Indice + 1) = 1;
+ *(Indice + 2) = 2;
+ *X = 1.0;
+
+ for (int i = 0; i < H->width; i++)
+ {
+ for (int j = 0; j < H->height; j++)
+ {
+ p.GetGrayPixel(H, i, j, HTexturePixel);
+ p.GetPixel(Delta, i, j, DeltaOhtaPixel);
+
+ *(HI + 0) = *(HTexturePixel + 0);
+ *(HI + 1) = *(DeltaOhtaPixel + 0);
+ *(HI + 2) = *(DeltaOhtaPixel + 1);
+
+ Trier(HI, 3, Indice);
+
+ *XiXj = *(MeasureG + (*(Indice + 1))) + (*(MeasureG + (*(Indice + 2))));
+
+ *(Integral + 0) = min((HI + (*(Indice + 0))), X);
+ *(Integral + 1) = min((HI + (*(Indice + 1))), XiXj);
+ *(Integral + 2) = min((HI + (*(Indice + 2))), ((MeasureG + (*(Indice + 2)))));
+
+ IntegralFlou = max(Integral, 3);
+ p.PutGrayPixel(OutputImage, i, j, IntegralFlou);
+ }
+ }
+
+ free(HTexturePixel);
+ free(DeltaOhtaPixel);
+ free(Indice);
+ free(HI);
+ free(X);
+ free(XiXj);
+ free(Integral);
+}
+
+void FuzzyUtils::getFuzzyIntegralChoquet(IplImage* H, IplImage* Delta, int n, float *MeasureG, IplImage* OutputImage)
+{
+ // MeasureG : est un vecteur contenant 3 mesure g (g1,g2,g3) tel que : g1+g2+g3=1
+ // n : =2 cad aggreger les 2 images "H" et "Delta"
+ // =1 cad aggreger uniquement les valeurs des composantes couleurs de l'image "Delta"
+
+ PixelUtils p;
+
+ float* HTexturePixel = (float*)malloc(1 * sizeof(float));
+ float* DeltaOhtaPixel = (float*)malloc(3 * (sizeof(float)));
+ int *Indice = (int*)malloc(3 * (sizeof(int)));
+ float *HI = (float*)malloc(3 * (sizeof(float)));
+ float *Integral = (float*)malloc(3 * (sizeof(float)));
+ float* X = (float*)malloc(1 * sizeof(float));
+ float* XiXj = (float*)malloc(1 * sizeof(float));
+ float IntegralFlou;
+
+ *Indice = 0;
+ *(Indice + 1) = 1;
+ *(Indice + 2) = 2;
+ *X = 1.0;
+
+ for (int i = 0; i < Delta->width; i++)
+ {
+ for (int j = 0; j < Delta->height; j++)
+ {
+ if (n == 2)
+ {
+ p.GetGrayPixel(H, i, j, HTexturePixel);
+ p.GetPixel(Delta, i, j, DeltaOhtaPixel);
+
+ *(HI + 0) = *(HTexturePixel + 0);
+ *(HI + 1) = *(DeltaOhtaPixel + 0);
+ *(HI + 2) = *(DeltaOhtaPixel + 1);
+ }
+
+ if (n == 1)
+ {
+ //remplir HI par les valeurs des 3 composantes couleurs uniquement
+ p.GetPixel(Delta, i, j, DeltaOhtaPixel);
+
+ *(HI + 0) = *(DeltaOhtaPixel + 0);
+ //*(HI+0) = *(DeltaOhtaPixel+2);
+ *(HI + 1) = *(DeltaOhtaPixel + 1);
+ *(HI + 2) = *(DeltaOhtaPixel + 2);
+ }
+
+ Trier(HI, 3, Indice);
+ *XiXj = *(MeasureG + (*(Indice + 1))) + (*(MeasureG + (*(Indice + 2))));
+
+ *(Integral + 0) = *(HI + (*(Indice + 0)))* (*X - *XiXj);
+ *(Integral + 1) = *(HI + (*(Indice + 1)))* (*XiXj - *(MeasureG + (*(Indice + 2))));
+ *(Integral + 2) = *(HI + (*(Indice + 2)))* (*(MeasureG + (*(Indice + 2))));
+
+ IntegralFlou = *(Integral + 0) + *(Integral + 1) + *(Integral + 2);
+ p.PutGrayPixel(OutputImage, i, j, IntegralFlou);
+ }
+ }
+
+ free(HTexturePixel);
+ free(DeltaOhtaPixel);
+ free(Indice);
+ free(HI);
+ free(X);
+ free(XiXj);
+ free(Integral);
+}
+
+void FuzzyUtils::FuzzyMeasureG(float g1, float g2, float g3, float *G)
+{
+ *(G + 0) = g1;
+ *(G + 1) = g2;
+ *(G + 2) = g3;
+}
+
+void FuzzyUtils::Trier(float* g, int n, int* index)
+{
+ // Cette fonction trie un vecteur g par ordre croissant et
+ // sort egalement l'indice des elements selon le trie dans le vecteur "index" supposé initialisé par des valeurs de 1 a n
+
+ float t;
+ int r, a, b;
+
+ for (a = 1; a <= n; a++)
+ {
+ for (b = n - 1; b >= a; b--)
+ if (*(g + b - 1) < (*(g + b)))
+ {
+ // ordre croissant des élements
+ t = *(g + b - 1);
+ *(g + b - 1) = *(g + b);
+ *(g + b) = t;
+
+ // ordre des indices des élements du vecteur g
+ r = *(index + b - 1);
+ *(index + b - 1) = *(index + b);
+ *(index + b) = r;
+ }
+ }
+}
+
+float FuzzyUtils::min(float *a, float *b)
+{
+ float min = 0;
+
+ if (*a >= (*b))
+ min = *b;
+ else
+ min = *a;
+
+ return min;
+}
+
+float FuzzyUtils::max(float* g, int n)
+{
+ float max = 0;
+
+ for (int i = 0; i < n; i++)
+ {
+ if (*(g + i) >= max)
+ max = *(g + i);
+ }
+
+ return max;
+}
+
+void FuzzyUtils::gDeDeux(float* a, float* b, float* lambda)
+{
+ float* c = (float*)malloc(1 * sizeof(float));
+ *c = *a + (*b) + (*lambda) * (*a) * (*b);
+}
+
+void FuzzyUtils::getLambda(float* g)
+{
+ float a, b;
+ float* lambda = (float*)malloc(1 * sizeof(float));
+
+ a = (*(g + 0) * (*(g + 1)) + (*(g + 1)) * (*(g + 2)) + (*(g + 0)) * (*(g + 2)));
+ *lambda = -(*(g + 0) * (*(g + 1)) + (*(g + 1)) * (*(g + 2)) + (*(g + 0)) * (*(g + 2))) / (*(g + 0) * (*(g + 1)) * (*(g + 2)));
+ b = (*(g + 0) * (*(g + 1)) * (*(g + 2)));
+
+ //printf("\na:%f",a);
+ //printf("\nb:%f",b);
+ //printf("\nlambda:%f", *lambda);
+
+ free(lambda);
+}
+
+void FuzzyUtils::AdaptativeSelectiveBackgroundModelUpdate(IplImage* CurrentImage, IplImage* BGImage, IplImage* OutputImage, IplImage* Integral, float seuil, float alpha)
+{
+ PixelUtils p;
+
+ float beta = 0.0;
+ float* CurentImagePixel = (float*)malloc(3 * sizeof(float));
+ float* BGImagePixel = (float*)malloc(3 * sizeof(float));
+ float* OutputImagePixel = (float*)malloc(3 * sizeof(float));
+ float* IntegralImagePixel = (float*)malloc(1 * sizeof(float));
+ float *Maximum = (float*)malloc(1 * sizeof(float));
+ float *Minimum = (float*)malloc(1 * sizeof(float));
+
+ p.ForegroundMaximum(Integral, Maximum, 1);
+ p.ForegroundMinimum(Integral, Minimum, 1);
+
+ for (int i = 0; i < CurrentImage->width; i++)
+ {
+ for (int j = 0; j < CurrentImage->height; j++)
+ {
+ p.GetPixel(CurrentImage, i, j, CurentImagePixel);
+ p.GetPixel(BGImage, i, j, BGImagePixel);
+ p.GetGrayPixel(Integral, i, j, IntegralImagePixel);
+
+ beta = 1 - ((*IntegralImagePixel) - ((*Minimum / (*Minimum - *Maximum)) * (*IntegralImagePixel) - (*Minimum * (*Maximum) / (*Minimum - *Maximum))));
+
+ for (int k = 0; k < 3; k++)
+ *(OutputImagePixel + k) = beta * (*(BGImagePixel + k)) + (1 - beta) * (alpha * (*(CurentImagePixel + k)) + (1 - alpha) * (*(BGImagePixel + k)));
+
+ p.PutPixel(OutputImage, i, j, OutputImagePixel);
+ }
+ }
+
+ free(CurentImagePixel);
+ free(BGImagePixel);
+ free(OutputImagePixel);
+ free(IntegralImagePixel);
+ free(Maximum);
+ free(Minimum);
+}
diff --git a/package_bgs/tb/FuzzyUtils.h b/package_bgs/T2F/FuzzyUtils.h
similarity index 86%
rename from package_bgs/tb/FuzzyUtils.h
rename to package_bgs/T2F/FuzzyUtils.h
index 43fc9ad..9a53a83 100644
--- a/package_bgs/tb/FuzzyUtils.h
+++ b/package_bgs/T2F/FuzzyUtils.h
@@ -15,19 +15,8 @@ You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-/*
-Code provided by Thierry BOUWMANS
-
-Maitre de Conf�rences
-Laboratoire MIA
-Universit� de La Rochelle
-17000 La Rochelle
-France
-tbouwman@univ-lr.fr
-http://sites.google.com/site/thierrybouwmans/
-*/
-#include "PixelUtils.h"
+#include "../../package_analysis/PixelUtils.h"
class FuzzyUtils
{
@@ -44,7 +33,7 @@ public:
void getFuzzyIntegralSugeno(IplImage* H, IplImage* Delta, int n, float *MeasureG, IplImage* OutputImage);
void getFuzzyIntegralChoquet(IplImage* H, IplImage* Delta, int n, float *MeasureG, IplImage* OutputImage);
void FuzzyMeasureG(float g1, float g2, float g3, float *G);
- void Trier(float* g, int n, int* index);
+ void Trier(float* g, int n, int* index);
float min(float *a, float *b);
float max(float *g, int n);
void gDeDeux(float* a, float* b, float* lambda);
diff --git a/package_bgs/tb/MRF.cpp b/package_bgs/T2F/MRF.cpp
similarity index 58%
rename from package_bgs/tb/MRF.cpp
rename to package_bgs/T2F/MRF.cpp
index cfde8af..291a846 100644
--- a/package_bgs/tb/MRF.cpp
+++ b/package_bgs/T2F/MRF.cpp
@@ -58,68 +58,68 @@ MRF_TC::MRF_TC()
MRF_TC::~MRF_TC()
{
- delete []classes;
- delete []old_labeling;
- delete []in_image_data;
- delete []local_evidence;
+ delete[]classes;
+ delete[]old_labeling;
+ delete[]in_image_data;
+ delete[]local_evidence;
}
double MRF_TC::TimeEnergy2(int i, int j, int label)
{
double energy = 0.0;
-
- if(old_labeling[i][j] == (label*255))
+
+ if (old_labeling[i][j] == (label * 255))
energy -= beta_time;
else
energy += beta_time;
- if(i != height-1) // south
+ if (i != height - 1) // south
{
- if(label*255 == old_labeling[i+1][j])
+ if (label * 255 == old_labeling[i + 1][j])
energy -= beta_time;
else
energy += beta_time;
- if((j != width-1) && (label*255 == old_labeling[i+1][j+1]))
+ if ((j != width - 1) && (label * 255 == old_labeling[i + 1][j + 1]))
energy -= beta_time;
else
energy += beta_time;
-
- if((j != 0) && (label*255 == old_labeling[i+1][j-1]))
+
+ if ((j != 0) && (label * 255 == old_labeling[i + 1][j - 1]))
energy -= beta_time;
else
energy += beta_time;
}
- if(j != width-1) // east
+ if (j != width - 1) // east
{
- if(label*255 == old_labeling[i][j+1])
+ if (label * 255 == old_labeling[i][j + 1])
energy -= beta_time;
else
energy += beta_time;
}
- if(i != 0) // nord
+ if (i != 0) // nord
{
- if(label*255 == old_labeling[i-1][j])
+ if (label * 255 == old_labeling[i - 1][j])
energy -= beta_time;
else
energy += beta_time;
- if((j != width-1) && (label*255 == old_labeling[i-1][j+1]))
+ if ((j != width - 1) && (label * 255 == old_labeling[i - 1][j + 1]))
energy -= beta_time;
else
energy += beta_time;
-
- if((j != 0) && (label*255 == old_labeling[i-1][j-1]))
+
+ if ((j != 0) && (label * 255 == old_labeling[i - 1][j - 1]))
energy -= beta_time;
else
energy += beta_time;
}
- if(j != 0) // west
+ if (j != 0) // west
{
- if(label*255 == old_labeling[i][j-1])
+ if (label * 255 == old_labeling[i][j - 1])
energy -= beta_time;
else
energy += beta_time;
@@ -132,53 +132,53 @@ double MRF_TC::Doubleton2(int i, int j, int label)
{
double energy = 0.0;
- if(i != height-1) // south
+ if (i != height - 1) // south
{
- if(label == classes[i+1][j])
+ if (label == classes[i + 1][j])
energy -= beta;
else
energy += beta;
- if((j != width-1) && (label == classes[i+1][j+1]))
+ if ((j != width - 1) && (label == classes[i + 1][j + 1]))
energy -= beta;
else
energy += beta;
-
- if((j != 0) && (label == classes[i+1][j-1]))
+
+ if ((j != 0) && (label == classes[i + 1][j - 1]))
energy -= beta;
else
energy += beta;
}
- if(j != width-1) // east
+ if (j != width - 1) // east
{
- if(label == classes[i][j+1])
+ if (label == classes[i][j + 1])
energy -= beta;
else
energy += beta;
}
- if(i != 0) // nord
+ if (i != 0) // nord
{
- if(label == classes[i-1][j])
+ if (label == classes[i - 1][j])
energy -= beta;
else
energy += beta;
- if((j != width-1) && (label == classes[i-1][j+1]))
+ if ((j != width - 1) && (label == classes[i - 1][j + 1]))
energy -= beta;
else
energy += beta;
- if((j != 0) && (label == classes[i-1][j-1]))
+ if ((j != 0) && (label == classes[i - 1][j - 1]))
energy -= beta;
else
energy += beta;
}
- if(j != 0) // west
+ if (j != 0) // west
{
- if(label == classes[i][j-1])
+ if (label == classes[i][j - 1])
energy -= beta;
else
energy += beta;
@@ -196,17 +196,17 @@ void MRF_TC::OnIterationOver2(void)
void MRF_TC::Build_Classes_OldLabeling_InImage_LocalEnergy()
{
int i;
- classes = new int* [height];
+ classes = new int*[height];
old_labeling = new int *[height];
- in_image_data = new int* [height];
- local_evidence = new float* [height];
+ in_image_data = new int*[height];
+ local_evidence = new float*[height];
- for(i = 0; i < height; ++i)
+ for (i = 0; i < height; ++i)
{
classes[i] = new int[width];
old_labeling[i] = new int[width];
in_image_data[i] = new int[width];
- local_evidence[i] = new float[width*2];
+ local_evidence[i] = new float[width * 2];
}
}
@@ -215,19 +215,19 @@ void MRF_TC::InitEvidence2(GMM *gmm, HMM *hmm, IplImage *labeling)
int i, j;
background = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 3);
- cvCopy(background2,background.Ptr());
+ cvCopy(background2, background.Ptr());
unsigned char *in_data = (unsigned char *)(in_image->imageData);
unsigned char *labeling_data = (unsigned char *)(labeling->imageData);
- for(i = 0; i < height; ++i)
+ for (i = 0; i < height; ++i)
{
- for(j = 0; j < width; ++j)
+ for (j = 0; j < width; ++j)
{
- in_image_data[i][j] = in_data[(i*in_image->widthStep)+j];
- old_labeling[i][j] = labeling_data[i*width+j];
-
- if(in_image_data[i][j] == 255)
+ in_image_data[i][j] = in_data[(i*in_image->widthStep) + j];
+ old_labeling[i][j] = labeling_data[i*width + j];
+
+ if (in_image_data[i][j] == 255)
classes[i][j] = 1;
else
classes[i][j] = 0;
@@ -241,29 +241,29 @@ void MRF_TC::InitEvidence2(GMM *gmm, HMM *hmm, IplImage *labeling)
float pixel;
int modes = 3;
- float mu;
+ float mu;
- for(i = 0; i < height; ++i)
+ for (i = 0; i < height; ++i)
{
- for(j = 0; j < width; ++j)
+ for (j = 0; j < width; ++j)
{
- variance = gmm[(i*width+j) * modes+0].variance;
- muR = gmm[(i*width+j) * modes+0].muR;
- muG = gmm[(i*width+j) * modes+0].muG;
- muB = gmm[(i*width+j) * modes+0].muB;
+ variance = gmm[(i*width + j) * modes + 0].variance;
+ muR = gmm[(i*width + j) * modes + 0].muR;
+ muG = gmm[(i*width + j) * modes + 0].muG;
+ muB = gmm[(i*width + j) * modes + 0].muB;
- mu = (muR + muG + muB)/3;
+ mu = (muR + muG + muB) / 3;
- pixel = (background(i,j,0) + background(i,j,1) + background(i,j,2))/3;
+ pixel = (background(i, j, 0) + background(i, j, 1) + background(i, j, 2)) / 3;
- if(variance == 0) variance = 1;
+ if (variance == 0) variance = 1;
- local_evidence[i][j*2+0] = pow((pixel-mu),2)/2/variance;
+ local_evidence[i][j * 2 + 0] = pow((pixel - mu), 2) / 2 / variance;
- if(pixel >= mu)
- local_evidence[i][j*2+1] = pow((pixel - mu - 2.5*sqrt(variance)),2)/2/variance;
+ if (pixel >= mu)
+ local_evidence[i][j * 2 + 1] = pow((pixel - mu - 2.5*sqrt(variance)), 2) / 2 / variance;
else
- local_evidence[i][j*2+1] = pow((pixel - mu + 2.5*sqrt(variance)),2)/2/variance;
+ local_evidence[i][j * 2 + 1] = pow((pixel - mu + 2.5*sqrt(variance)), 2) / 2 / variance;
}
}
}
@@ -274,12 +274,12 @@ void MRF_TC::CreateOutput2()
int i, j;
unsigned char *out_data;
- out_data = (unsigned char *) out_image->imageData;
+ out_data = (unsigned char *)out_image->imageData;
// create output image
for (i = 0; i < height; ++i)
- for(j = 0; j < width; ++j)
- out_data[(i*width) + j] = (unsigned char)((classes[i][j])*255);
+ for (j = 0; j < width; ++j)
+ out_data[(i*width) + j] = (unsigned char)((classes[i][j]) * 255);
}
//calculate the whole energy
@@ -288,12 +288,12 @@ double MRF_TC::CalculateEnergy2()
double sum = 0.0;
int i, j, k;
// !FAIL!
- for(i = 0; i < height; ++i)
+ for (i = 0; i < height; ++i)
{
- for(j = 0; j < width; ++j)
+ for (j = 0; j < width; ++j)
{
k = classes[i][j];
- sum = sum + local_evidence[i][j*2+k] + Doubleton2(i,j,k) + TimeEnergy2(i, j, k);//min the value
+ sum = sum + local_evidence[i][j * 2 + k] + Doubleton2(i, j, k) + TimeEnergy2(i, j, k);//min the value
}
}
//sum = 0.1;
@@ -303,7 +303,7 @@ double MRF_TC::CalculateEnergy2()
// local energy
double MRF_TC::LocalEnergy2(int i, int j, int label)
{
- return local_evidence[i][j*2+label] + Doubleton2(i,j,label) + TimeEnergy2(i,j,label);
+ return local_evidence[i][j * 2 + label] + Doubleton2(i, j, label) + TimeEnergy2(i, j, label);
}
void MRF_TC::ICM2()
@@ -317,22 +317,22 @@ void MRF_TC::ICM2()
do
{
- for(i = 0; i < height; ++i)
- for(j = 0; j < width; ++j)
+ for (i = 0; i < height; ++i)
+ for (j = 0; j < width; ++j)
{
- localenergy0 = LocalEnergy2(i,j,0);
- localenergy1 = LocalEnergy2(i,j,1);
-
- if(localenergy0 < localenergy1)
+ localenergy0 = LocalEnergy2(i, j, 0);
+ localenergy1 = LocalEnergy2(i, j, 1);
+
+ if (localenergy0 < localenergy1)
classes[i][j] = 0;
else
classes[i][j] = 1;
}
- //E = CalculateEnergy2();
- //summa_deltaE = fabs(E_old-E);
- //E_old = E;
- ++K;
- OnIterationOver2();
- }while(K < 2);
+ //E = CalculateEnergy2();
+ //summa_deltaE = fabs(E_old-E);
+ //E_old = E;
+ ++K;
+ OnIterationOver2();
+ } while (K < 2);
}
diff --git a/package_bgs/tb/MRF.h b/package_bgs/T2F/MRF.h
similarity index 95%
rename from package_bgs/tb/MRF.h
rename to package_bgs/T2F/MRF.h
index c745899..1276a30 100644
--- a/package_bgs/tb/MRF.h
+++ b/package_bgs/T2F/MRF.h
@@ -14,8 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#ifndef MRF_H
-#define MRF_H
+#pragma once
#include "T2FMRF.h"
@@ -53,7 +52,7 @@ namespace Algorithms
//////////////////////////////////////////////////////////////////////////
// alpha value for MMD
- double alpha;
+ double alpha;
//////////////////////////////////////////////////////////////////////////
//current global energy
@@ -64,7 +63,7 @@ namespace Algorithms
int K;
//////////////////////////////////////////////////////////////////////////
- //labeling image
+ //labeling image
int **classes;
//input image
int **in_image_data;
@@ -75,7 +74,7 @@ namespace Algorithms
/************************************************************************/
/* the Markov Random Field with time constraints for T2FGMM */
/************************************************************************/
- class MRF_TC: public MRF
+ class MRF_TC : public MRF
{
private:
double beta_time;
@@ -103,5 +102,3 @@ namespace Algorithms
};
}
}
-
-#endif
diff --git a/package_bgs/tb/T2FGMM.cpp b/package_bgs/T2F/T2FGMM.cpp
similarity index 69%
rename from package_bgs/tb/T2FGMM.cpp
rename to package_bgs/T2F/T2FGMM.cpp
index a49407b..6ff9997 100644
--- a/package_bgs/tb/T2FGMM.cpp
+++ b/package_bgs/T2F/T2FGMM.cpp
@@ -17,8 +17,8 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
/****************************************************************************
*
* T2FGMM.cpp
-*
-* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
+*
+* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
* "Modeling of Dynamic Backgrounds by Type-2 Fuzzy Gaussians Mixture Models"
* Author: Fida El Baf, Thierry Bouwmans, September 2008.
@@ -33,9 +33,9 @@ int compareT2FGMM(const void* _gmm1, const void* _gmm2)
GMM gmm1 = *(GMM*)_gmm1;
GMM gmm2 = *(GMM*)_gmm2;
- if(gmm1.significants < gmm2.significants)
+ if (gmm1.significants < gmm2.significants)
return 1;
- else if(gmm1.significants == gmm2.significants)
+ else if (gmm1.significants == gmm2.significants)
return 0;
else
return -1;
@@ -53,10 +53,10 @@ T2FGMM::~T2FGMM()
void T2FGMM::Initalize(const BgsParams& param)
{
- m_params = (T2FGMMParams&) param;
+ m_params = (T2FGMMParams&)param;
// Tbf - the threshold
- m_bg_threshold = 0.75f; // 1-cf from the paper
+ m_bg_threshold = 0.75f; // 1-cf from the paper
// Tgenerate - the threshold
m_variance = 36.0f; // sigma for the new mode
@@ -71,11 +71,11 @@ void T2FGMM::Initalize(const BgsParams& param)
// Factor control for the T2FGMM-UM [0,3]
//km = (float) 1.5;
- km = (float) m_params.KM();
+ km = (float)m_params.KM();
// Factor control for the T2FGMM-UV [0.3,1]
//kv = (float) 0.6;
- kv = (float) m_params.KV();
+ kv = (float)m_params.KV();
}
RgbImage* T2FGMM::Background()
@@ -87,7 +87,7 @@ void T2FGMM::InitModel(const RgbImage& data)
{
m_modes_per_pixel.Clear();
- for(unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
+ for (unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
{
m_modes[i].weight = 0;
m_modes[i].variance = 0;
@@ -98,13 +98,13 @@ void T2FGMM::InitModel(const RgbImage& data)
}
}
-void T2FGMM::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void T2FGMM::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
// it doesn't make sense to have conditional updates in the GMM framework
}
-void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes,
- unsigned char& low_threshold, unsigned char& high_threshold)
+void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes,
+ unsigned char& low_threshold, unsigned char& high_threshold)
{
// calculate distances to the modes (+ sort???)
// here we need to go in descending order!!!
@@ -119,19 +119,19 @@ void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char&
// calculate number of Gaussians to include in the background model
int backgroundGaussians = 0;
double sum = 0.0;
- for(int i = 0; i < numModes; ++i)
+ for (int i = 0; i < numModes; ++i)
{
- if(sum < m_bg_threshold)
+ if (sum < m_bg_threshold)
{
backgroundGaussians++;
- sum += m_modes[posPixel+i].weight;
+ sum += m_modes[posPixel + i].weight;
}
else
break;
}
// update all distributions and check for match with current pixel
- for(int iModes = 0; iModes < numModes; iModes++)
+ for (int iModes = 0; iModes < numModes; iModes++)
{
pos = posPixel + iModes;
float weight = m_modes[pos].weight;
@@ -159,45 +159,45 @@ void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char&
float HB;
// T2FGMM-UM
- if(m_params.Type() == TYPE_T2FGMM_UM)
+ if (m_params.Type() == TYPE_T2FGMM_UM)
{
- if((pixel(0)<muR-km*var)|| (pixel(0)>muR+km*var))
- HR=2*km*dR/var;
+ if ((pixel(0) < muR - km*var) || (pixel(0) > muR + km*var))
+ HR = 2 * km*dR / var;
else
- HR=dR*dR/(2*var*var)+km*dR/var+km*km/2;
+ HR = dR*dR / (2 * var*var) + km*dR / var + km*km / 2;
- if((pixel(1)<muG-km*var)|| (pixel(1)>muG+km*var))
- HG=2*km*dG/var;
+ if ((pixel(1) < muG - km*var) || (pixel(1) > muG + km*var))
+ HG = 2 * km*dG / var;
else
- HG=dG*dG/(2*var*var)+km*dG/var+km*km/2;
+ HG = dG*dG / (2 * var*var) + km*dG / var + km*km / 2;
- if((pixel(2)<muB-km*var)|| (pixel(2)>muB+km*var))
- HB=2*km*dB/var;
+ if ((pixel(2) < muB - km*var) || (pixel(2) > muB + km*var))
+ HB = 2 * km*dB / var;
else
- HB=dB*dB/(2*var*var)+km*dB/var+km*km/2;
+ HB = dB*dB / (2 * var*var) + km*dB / var + km*km / 2;
}
// T2FGMM-UV
- if(m_params.Type() == TYPE_T2FGMM_UV)
+ if (m_params.Type() == TYPE_T2FGMM_UV)
{
- HR = (1/(kv*kv)-kv*kv) * (pixel(0)-muR) * (pixel(0)-muR)/(2*var);
- HG = (1/(kv*kv)-kv*kv) * (pixel(1)-muG) * (pixel(1)-muG)/(2*var);
- HB = (1/(kv*kv)-kv*kv) * (pixel(2)-muB) * (pixel(2)-muB)/(2*var);
+ HR = (1 / (kv*kv) - kv*kv) * (pixel(0) - muR) * (pixel(0) - muR) / (2 * var);
+ HG = (1 / (kv*kv) - kv*kv) * (pixel(1) - muG) * (pixel(1) - muG) / (2 * var);
+ HB = (1 / (kv*kv) - kv*kv) * (pixel(2) - muB) * (pixel(2) - muB) / (2 * var);
}
-
+
// calculate the squared distance
float dist = (HR*HR + HG*HG + HB*HB);
- if(dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
+ if (dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
bBackgroundHigh = true;
// a match occurs when the pixel is within sqrt(fTg) standard deviations of the distribution
- if(dist < m_params.LowThreshold()*var)
+ if (dist < m_params.LowThreshold()*var)
{
bFitsPDF = true;
// check if this Gaussian is part of the background model
- if(iModes < backgroundGaussians)
+ if (iModes < backgroundGaussians)
bBackgroundLow = true;
//update distribution
@@ -209,16 +209,16 @@ void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char&
m_modes[pos].muB = muB - k*(dB);
//limit the variance
- float sigmanew = var + k*(dist-var);
- m_modes[pos].variance = sigmanew < 4 ? 4 : sigmanew > 5*m_variance ? 5*m_variance : sigmanew;
+ float sigmanew = var + k*(dist - var);
+ m_modes[pos].variance = sigmanew < 4 ? 4 : sigmanew > 5 * m_variance ? 5 * m_variance : sigmanew;
m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
}
else
{
weight = fOneMinAlpha*weight;
- if(weight < 0.0)
+ if (weight < 0.0)
{
- weight=0.0;
+ weight = 0.0;
numModes--;
}
@@ -229,9 +229,9 @@ void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char&
else
{
weight = fOneMinAlpha*weight;
- if(weight < 0.0)
+ if (weight < 0.0)
{
- weight=0.0;
+ weight = 0.0;
numModes--;
}
m_modes[pos].weight = weight;
@@ -243,25 +243,25 @@ void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char&
// renormalize weights so they add to one
double invTotalWeight = 1.0 / totalWeight;
- for(int iLocal = 0; iLocal < numModes; iLocal++)
+ for (int iLocal = 0; iLocal < numModes; iLocal++)
{
m_modes[posPixel + iLocal].weight *= (float)invTotalWeight;
- m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight
+ m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight
/ sqrt(m_modes[posPixel + iLocal].variance);
}
- // Sort significance values so they are in desending order.
- qsort(&m_modes[posPixel], numModes, sizeof(GMM), compareT2FGMM);
+ // Sort significance values so they are in desending order.
+ qsort(&m_modes[posPixel], numModes, sizeof(GMM), compareT2FGMM);
// make new mode if needed and exit
- if(!bFitsPDF)
+ if (!bFitsPDF)
{
- if(numModes < m_params.MaxModes())
+ if (numModes < m_params.MaxModes())
numModes++;
//else
- // the weakest mode will be replaced
-
- pos = posPixel + numModes-1;
+ // the weakest mode will be replaced
+
+ pos = posPixel + numModes - 1;
m_modes[pos].muR = pixel.ch[0];
m_modes[pos].muG = pixel.ch[1];
@@ -277,26 +277,26 @@ void T2FGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char&
//renormalize weights
int iLocal;
float sum = 0.0;
- for(iLocal = 0; iLocal < numModes; iLocal++)
- sum += m_modes[posPixel+ iLocal].weight;
-
- double invSum = 1.0/sum;
- for(iLocal = 0; iLocal < numModes; iLocal++)
+ for (iLocal = 0; iLocal < numModes; iLocal++)
+ sum += m_modes[posPixel + iLocal].weight;
+
+ double invSum = 1.0 / sum;
+ for (iLocal = 0; iLocal < numModes; iLocal++)
{
m_modes[posPixel + iLocal].weight *= (float)invSum;
m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight / sqrt(m_modes[posPixel + iLocal].variance);
}
}
- // Sort significance values so they are in desending order.
+ // Sort significance values so they are in desending order.
qsort(&(m_modes[posPixel]), numModes, sizeof(GMM), compareT2FGMM);
- if(bBackgroundLow)
+ if (bBackgroundLow)
low_threshold = BACKGROUND;
else
low_threshold = FOREGROUND;
-
- if(bBackgroundHigh)
+
+ if (bBackgroundHigh)
high_threshold = BACKGROUND;
else
high_threshold = FOREGROUND;
@@ -316,21 +316,21 @@ void T2FGMM::Subtract(int frame_num, const RgbImage& data, BwImage& low_threshol
long posPixel;
// update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
{
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
// update model + background subtract
posPixel = (r*m_params.Width() + c) * m_params.MaxModes();
- SubtractPixel(posPixel, data(r,c), m_modes_per_pixel(r,c), low_threshold, high_threshold);
+ SubtractPixel(posPixel, data(r, c), m_modes_per_pixel(r, c), low_threshold, high_threshold);
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
- m_background(r,c,0) = (unsigned char) m_modes[posPixel].muR;
- m_background(r,c,1) = (unsigned char) m_modes[posPixel].muG;
- m_background(r,c,2) = (unsigned char) m_modes[posPixel].muB;
+ m_background(r, c, 0) = (unsigned char)m_modes[posPixel].muR;
+ m_background(r, c, 1) = (unsigned char)m_modes[posPixel].muG;
+ m_background(r, c, 2) = (unsigned char)m_modes[posPixel].muB;
}
}
}
diff --git a/package_bgs/tb/T2FGMM.h b/package_bgs/T2F/T2FGMM.h
similarity index 92%
rename from package_bgs/tb/T2FGMM.h
rename to package_bgs/T2F/T2FGMM.h
index 7d966db..203c350 100644
--- a/package_bgs/tb/T2FGMM.h
+++ b/package_bgs/T2F/T2FGMM.h
@@ -18,18 +18,16 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* T2FGMM.h
*
-* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
+* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
* "Modeling of Dynamic Backgrounds by Type-2 Fuzzy Gaussians Mixture Models"
* Author: Fida El Baf, Thierry Bouwmans, September 2008
*
* This code is based on code by Z. Zivkovic's written for his enhanced GMM
-* background subtraction algorithm:
+* background subtraction algorithm:
*
* Zivkovic's code can be obtained at: www.zoranz.net
******************************************************************************/
-
-#ifndef T2F_GMM_
-#define T2F_GMM_
+#pragma once
#include "../dp/Bgs.h"
#include "../dp/GrimsonGMM.h"
@@ -55,9 +53,9 @@ namespace Algorithms
float &KV() { return m_kv; }
private:
- // Threshold on the squared dist. to decide when a sample is close to an existing
- // components. If it is not close to any a new component will be generated.
- // Smaller threshold values lead to more generated components and higher threshold values
+ // Threshold on the squared dist. to decide when a sample is close to an existing
+ // components. If it is not close to any a new component will be generated.
+ // Smaller threshold values lead to more generated components and higher threshold values
// lead to a small number of components but they can grow too large.
//
// It is usual easiest to think of these thresholds as being the number of variances away
@@ -66,7 +64,7 @@ namespace Algorithms
float m_high_threshold;
// alpha - speed of update - if the time interval you want to average over is T
- // set alpha=1/T.
+ // set alpha=1/T.
float m_alpha;
// Maximum number of modes (Gaussian components) that will be used per pixel
@@ -92,12 +90,12 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data, BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Subtract(int frame_num, const RgbImage& data, BwImage& low_threshold_mask, BwImage& high_threshold_mask);
void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background();
- private:
+ private:
void SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes, unsigned char& lowThreshold, unsigned char& highThreshold);
// User adjustable parameters
@@ -109,8 +107,8 @@ namespace Algorithms
// it is considered foreground
float m_bg_threshold; //1-cf from the paper
- // Initial variance for the newly generated components.
- // It will will influence the speed of adaptation. A good guess should be made.
+ // Initial variance for the newly generated components.
+ // It will will influence the speed of adaptation. A good guess should be made.
// A simple way is to estimate the typical standard deviation from the images.
float m_variance;
@@ -131,5 +129,3 @@ namespace Algorithms
};
}
}
-
-#endif
diff --git a/package_bgs/tb/T2FMRF.cpp b/package_bgs/T2F/T2FMRF.cpp
similarity index 70%
rename from package_bgs/tb/T2FMRF.cpp
rename to package_bgs/T2F/T2FMRF.cpp
index 372f564..e722d02 100644
--- a/package_bgs/tb/T2FMRF.cpp
+++ b/package_bgs/T2F/T2FMRF.cpp
@@ -18,12 +18,12 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* T2FMRF.cpp
*
-* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
+* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
* "Modeling of Dynamic Backgrounds by Type-2 Fuzzy Gaussians Mixture Models"
* Author: Fida El Baf, Thierry Bouwmans, September 2008
*
* This code is based on code by Z. Zivkovic's written for his enhanced GMM
-* background subtraction algorithm:
+* background subtraction algorithm:
*
* Zivkovic's code can be obtained at: www.zoranz.net
******************************************************************************/
@@ -37,9 +37,9 @@ int compareT2FMRF(const void* _gmm1, const void* _gmm2)
GMM gmm1 = *(GMM*)_gmm1;
GMM gmm2 = *(GMM*)_gmm2;
- if(gmm1.significants < gmm2.significants)
+ if (gmm1.significants < gmm2.significants)
return 1;
- else if(gmm1.significants == gmm2.significants)
+ else if (gmm1.significants == gmm2.significants)
return 0;
else
return -1;
@@ -66,10 +66,10 @@ T2FMRF::~T2FMRF()
void T2FMRF::Initalize(const BgsParams& param)
{
- m_params = (T2FMRFParams&) param;
+ m_params = (T2FMRFParams&)param;
// Tbf - the threshold
- m_bg_threshold = 0.75f; // 1-cf from the paper
+ m_bg_threshold = 0.75f; // 1-cf from the paper
// Tgenerate - the threshold
m_variance = 36.0f; // sigma for the new mode
@@ -87,11 +87,11 @@ void T2FMRF::Initalize(const BgsParams& param)
// Factor control for the T2FGMM-UM [0,3]
// km = (float) 2; //1.5;
- km = (float) m_params.KM();
+ km = (float)m_params.KM();
// Factor control for the T2FGMM-UV [0.3,1]
// kv = (float) 0.9; //0.6;
- kv = (float) m_params.KV();
+ kv = (float)m_params.KV();
}
RgbImage* T2FMRF::Background()
@@ -103,7 +103,7 @@ void T2FMRF::InitModel(const RgbImage& data)
{
m_modes_per_pixel.Clear();
- for(unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
+ for (unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
{
m_modes[i].weight = 0;
m_modes[i].variance = 0;
@@ -124,13 +124,13 @@ void T2FMRF::InitModel(const RgbImage& data)
}
}
-void T2FMRF::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void T2FMRF::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
// it doesn't make sense to have conditional updates in the GMM framework
}
-void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel, unsigned char& numModes,
- unsigned char& low_threshold, unsigned char& high_threshold)
+void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel, unsigned char& numModes,
+ unsigned char& low_threshold, unsigned char& high_threshold)
{
// calculate distances to the modes (+ sort???)
// here we need to go in descending order!!!
@@ -144,7 +144,7 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
float Ab2f = m_state[posPixel].Ab2f;
float Af2b = m_state[posPixel].Af2b;
float Af2f = m_state[posPixel].Af2f;
- float T = m_state[posPixel].T;
+ //float T = m_state[posPixel].T;
float fOneMinAlpha = 1 - m_params.Alpha();
float totalWeight = 0.0f;
@@ -152,12 +152,12 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
// calculate number of Gaussians to include in the background model
int backgroundGaussians = 0;
double sum = 0.0;
- for(int i = 0; i < numModes; ++i)
+ for (int i = 0; i < numModes; ++i)
{
- if(sum < m_bg_threshold)
+ if (sum < m_bg_threshold)
{
backgroundGaussians++;
- sum += m_modes[posGMode+i].weight;
+ sum += m_modes[posGMode + i].weight;
}
else
break;
@@ -192,57 +192,57 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
float HB;
// T2FMRF-UM
- if(m_params.Type() == TYPE_T2FMRF_UM)
+ if (m_params.Type() == TYPE_T2FMRF_UM)
{
- if((pixel(0) < muR-km*var) || (pixel(0) > muR+km*var))
- HR = 2*km*dR/var;
+ if ((pixel(0) < muR - km*var) || (pixel(0) > muR + km*var))
+ HR = 2 * km*dR / var;
else
- HR = dR*dR/(2*var*var)+km*dR/var+km*km/2;
+ HR = dR*dR / (2 * var*var) + km*dR / var + km*km / 2;
- if((pixel(1) < muG-km*var) || (pixel(1) > muG+km*var))
- HG = 2*km*dG/var;
+ if ((pixel(1) < muG - km*var) || (pixel(1) > muG + km*var))
+ HG = 2 * km*dG / var;
else
- HG = dG*dG/(2*var*var)+km*dG/var+km*km/2;
+ HG = dG*dG / (2 * var*var) + km*dG / var + km*km / 2;
- if((pixel(2) < muB-km*var) || (pixel(2) > muB+km*var))
- HB = 2*km*dB/var;
+ if ((pixel(2) < muB - km*var) || (pixel(2) > muB + km*var))
+ HB = 2 * km*dB / var;
else
- HB = dB*dB/(2*var*var)+km*dB/var+km*km/2;
+ HB = dB*dB / (2 * var*var) + km*dB / var + km*km / 2;
}
// T2FGMM-UV
- if(m_params.Type() == TYPE_T2FMRF_UV)
+ if (m_params.Type() == TYPE_T2FMRF_UV)
{
- HR = (1/(kv*kv)-kv*kv) * (pixel(0)-muR) * (pixel(0)-muR)/(2*var);
- HG = (1/(kv*kv)-kv*kv) * (pixel(1)-muG) * (pixel(1)-muG)/(2*var);
- HB = (1/(kv*kv)-kv*kv) * (pixel(2)-muB) * (pixel(2)-muB)/(2*var);
+ HR = (1 / (kv*kv) - kv*kv) * (pixel(0) - muR) * (pixel(0) - muR) / (2 * var);
+ HG = (1 / (kv*kv) - kv*kv) * (pixel(1) - muG) * (pixel(1) - muG) / (2 * var);
+ HB = (1 / (kv*kv) - kv*kv) * (pixel(2) - muB) * (pixel(2) - muB) / (2 * var);
}
float ro;
if (CurrentState == background)
{
- if (Ab2b!=0) ro = (Ab2f/Ab2b);
+ if (Ab2b != 0) ro = (Ab2f / Ab2b);
else ro = 10;
}
else
{
- if(Af2b!=0) ro = (Af2f/Af2b);
+ if (Af2b != 0) ro = (Af2f / Af2b);
else ro = 10;
}
-
+
// calculate the squared distance
float dist = (HR*HR + HG*HG + HB*HB);
- if(dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
+ if (dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
bBackgroundHigh = true;
// a match occurs when the pixel is within sqrt(fTg) standard deviations of the distribution
- if(dist < m_params.LowThreshold()*var)
+ if (dist < m_params.LowThreshold()*var)
{
bFitsPDF = true;
// check if this Gaussian is part of the background model
- if(iModes < backgroundGaussians)
+ if (iModes < backgroundGaussians)
bBackgroundLow = true;
//update distribution
@@ -254,8 +254,8 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
m_modes[pos].muB = muB - k*(dB);
//limit the variance
- float sigmanew = var + k*(dist-var);
- m_modes[pos].variance = sigmanew < 4 ? 4 : sigmanew > 5*m_variance ? 5*m_variance : sigmanew;
+ float sigmanew = var + k*(dist - var);
+ m_modes[pos].variance = sigmanew < 4 ? 4 : sigmanew > 5 * m_variance ? 5 * m_variance : sigmanew;
m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
}
else
@@ -263,7 +263,7 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
weight = fOneMinAlpha*weight;
if (weight < 0.0)
{
- weight=0.0;
+ weight = 0.0;
numModes--;
}
@@ -276,7 +276,7 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
weight = fOneMinAlpha*weight;
if (weight < 0.0)
{
- weight=0.0;
+ weight = 0.0;
numModes--;
}
m_modes[pos].weight = weight;
@@ -294,18 +294,18 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
m_modes[posGMode + iLocal].significants = m_modes[posGMode + iLocal].weight / sqrt(m_modes[posGMode + iLocal].variance);
}
- // Sort significance values so they are in desending order.
- qsort(&m_modes[posGMode], numModes, sizeof(GMM), compareT2FMRF);
+ // Sort significance values so they are in desending order.
+ qsort(&m_modes[posGMode], numModes, sizeof(GMM), compareT2FMRF);
// make new mode if needed and exit
- if(!bFitsPDF)
+ if (!bFitsPDF)
{
- if(numModes < m_params.MaxModes())
+ if (numModes < m_params.MaxModes())
numModes++;
//else
- // the weakest mode will be replaced
-
- pos = posGMode + numModes-1;
+ // the weakest mode will be replaced
+
+ pos = posGMode + numModes - 1;
m_modes[pos].muR = pixel.ch[0];
m_modes[pos].muG = pixel.ch[1];
@@ -313,7 +313,7 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
m_modes[pos].variance = m_variance;
m_modes[pos].significants = 0; // will be set below
- if(numModes == 1)
+ if (numModes == 1)
m_modes[pos].weight = 1;
else
m_modes[pos].weight = m_params.Alpha();
@@ -321,33 +321,33 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
//renormalize weights
int iLocal;
float sum = 0.0;
- for(iLocal = 0; iLocal < numModes; iLocal++)
- sum += m_modes[posGMode+ iLocal].weight;
-
- double invSum = 1.0/sum;
- for(iLocal = 0; iLocal < numModes; iLocal++)
+ for (iLocal = 0; iLocal < numModes; iLocal++)
+ sum += m_modes[posGMode + iLocal].weight;
+
+ double invSum = 1.0 / sum;
+ for (iLocal = 0; iLocal < numModes; iLocal++)
{
m_modes[posGMode + iLocal].weight *= (float)invSum;
m_modes[posGMode + iLocal].significants = m_modes[posPixel + iLocal].weight / sqrt(m_modes[posGMode + iLocal].variance);
}
}
- // Sort significance values so they are in desending order.
+ // Sort significance values so they are in desending order.
qsort(&(m_modes[posGMode]), numModes, sizeof(GMM), compareT2FMRF);
- if(bBackgroundLow)
+ if (bBackgroundLow)
{
low_threshold = BACKGROUND;
m_state[posPixel].State = background;
- if(CurrentState == background)
+ if (CurrentState == background)
{
float b2b = fOneMinAlpha*Ab2b + m_params.Alpha();
float b2f = fOneMinAlpha*Ab2f;
float b = b2b + b2f;
- m_state[posPixel].Ab2b = b2b/b;
- m_state[posPixel].Ab2f = b2f/b;
+ m_state[posPixel].Ab2b = b2b / b;
+ m_state[posPixel].Ab2f = b2f / b;
m_state[posPixel].T = m_state[posPixel].Ab2b;
}
else
@@ -356,8 +356,8 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
float f2f = fOneMinAlpha*Af2f;
float f = f2b + f2f;
- m_state[posPixel].Af2b = f2b/f;
- m_state[posPixel].Af2f = f2f/f;
+ m_state[posPixel].Af2b = f2b / f;
+ m_state[posPixel].Af2f = f2f / f;
m_state[posPixel].T = m_state[posPixel].Af2b;
}
}
@@ -366,14 +366,14 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
low_threshold = FOREGROUND;
m_state[posPixel].State = foreground;
- if(CurrentState == background)
+ if (CurrentState == background)
{
float b2b = fOneMinAlpha*Ab2b;
float b2f = fOneMinAlpha*Ab2f + m_params.Alpha();
float b = b2b + b2f;
- m_state[posPixel].Ab2b = b2b/b;
- m_state[posPixel].Ab2f = b2f/b;
+ m_state[posPixel].Ab2b = b2b / b;
+ m_state[posPixel].Ab2f = b2f / b;
m_state[posPixel].T = m_state[posPixel].Ab2b;
}
else
@@ -382,13 +382,13 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
float f2f = fOneMinAlpha*Af2f + m_params.Alpha();
float f = f2b + f2f;
- m_state[posPixel].Af2b = f2b/f;
- m_state[posPixel].Af2f = f2f/f;
+ m_state[posPixel].Af2b = f2b / f;
+ m_state[posPixel].Af2f = f2f / f;
m_state[posPixel].T = m_state[posPixel].Af2b;
}
}
- if(bBackgroundHigh)
+ if (bBackgroundHigh)
high_threshold = BACKGROUND;
else
high_threshold = FOREGROUND;
@@ -402,30 +402,30 @@ void T2FMRF::SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel,
// (the memory should already be reserved)
// values: 255-foreground, 125-shadow, 0-background
///////////////////////////////////////////////////////////////////////////////
-void T2FMRF::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void T2FMRF::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
unsigned char low_threshold, high_threshold;
long posPixel;
long posGMode;
// update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
{
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
// update model + background subtract
posPixel = r*m_params.Width() + c;
posGMode = (r*m_params.Width() + c) * m_params.MaxModes();
- SubtractPixel(posPixel, posGMode, data(r,c), m_modes_per_pixel(r,c), low_threshold, high_threshold);
+ SubtractPixel(posPixel, posGMode, data(r, c), m_modes_per_pixel(r, c), low_threshold, high_threshold);
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
- m_background(r,c,0) = (unsigned char) m_modes[posGMode].muR;
- m_background(r,c,1) = (unsigned char) m_modes[posGMode].muG;
- m_background(r,c,2) = (unsigned char) m_modes[posGMode].muB;
+ m_background(r, c, 0) = (unsigned char)m_modes[posGMode].muR;
+ m_background(r, c, 1) = (unsigned char)m_modes[posGMode].muG;
+ m_background(r, c, 2) = (unsigned char)m_modes[posGMode].muB;
}
}
}
diff --git a/package_bgs/tb/T2FMRF.h b/package_bgs/T2F/T2FMRF.h
similarity index 91%
rename from package_bgs/tb/T2FMRF.h
rename to package_bgs/T2F/T2FMRF.h
index 00e464c..1015426 100644
--- a/package_bgs/tb/T2FMRF.h
+++ b/package_bgs/T2F/T2FMRF.h
@@ -18,18 +18,16 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* T2FMRF.h
*
-* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
+* Purpose: Implementation of the T2 Fuzzy Gaussian Mixture Models (T2GMMs)
* "Modeling of Dynamic Backgrounds by Type-2 Fuzzy Gaussians Mixture Models"
* Author: Fida El Baf, Thierry Bouwmans, September 2008
*
* This code is based on code by Z. Zivkovic's written for his enhanced GMM
-* background subtraction algorithm:
+* background subtraction algorithm:
*
* Zivkovic's code can be obtained at: www.zoranz.net
******************************************************************************/
-
-#ifndef T2F_MRF_
-#define T2F_MRF_
+#pragma once
#include "../dp/Bgs.h"
#include "../dp/GrimsonGMM.h"
@@ -41,9 +39,9 @@ namespace Algorithms
const int TYPE_T2FMRF_UM = 0;
const int TYPE_T2FMRF_UV = 1;
- enum HiddenState {background, foreground};
+ enum HiddenState { background, foreground };
- typedef struct HMMState
+ typedef struct HMMState
{
float T;
//Hidden State
@@ -80,9 +78,9 @@ namespace Algorithms
float &KV() { return m_kv; }
private:
- // Threshold on the squared dist. to decide when a sample is close to an existing
- // components. If it is not close to any a new component will be generated.
- // Smaller threshold values lead to more generated components and higher threshold values
+ // Threshold on the squared dist. to decide when a sample is close to an existing
+ // components. If it is not close to any a new component will be generated.
+ // Smaller threshold values lead to more generated components and higher threshold values
// lead to a small number of components but they can grow too large.
//
// It is usual easiest to think of these thresholds as being the number of variances away
@@ -91,7 +89,7 @@ namespace Algorithms
float m_high_threshold;
// alpha - speed of update - if the time interval you want to average over is T
- // set alpha=1/T.
+ // set alpha=1/T.
float m_alpha;
// Maximum number of modes (Gaussian components) that will be used per pixel
@@ -116,7 +114,7 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data, BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Subtract(int frame_num, const RgbImage& data, BwImage& low_threshold_mask, BwImage& high_threshold_mask);
void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background();
@@ -124,7 +122,7 @@ namespace Algorithms
GMM *gmm(void);
HMM *hmm(void);
- private:
+ private:
void SubtractPixel(long posPixel, long posGMode, const RgbPixel& pixel, unsigned char& numModes, unsigned char& lowThreshold, unsigned char& highThreshold);
// User adjustable parameters
@@ -136,8 +134,8 @@ namespace Algorithms
// it is considered foreground
float m_bg_threshold; //1-cf from the paper
- // Initial variance for the newly generated components.
- // It will will influence the speed of adaptation. A good guess should be made.
+ // Initial variance for the newly generated components.
+ // It will will influence the speed of adaptation. A good guess should be made.
// A simple way is to estimate the typical standard deviation from the images.
float m_variance;
@@ -160,5 +158,3 @@ namespace Algorithms
};
}
}
-
-#endif
diff --git a/package_bgs/tb/T2FGMM_UM.cpp b/package_bgs/T2FGMM_UM.cpp
similarity index 64%
rename from package_bgs/tb/T2FGMM_UM.cpp
rename to package_bgs/T2FGMM_UM.cpp
index 31a5338..ad1b40e 100644
--- a/package_bgs/tb/T2FGMM_UM.cpp
+++ b/package_bgs/T2FGMM_UM.cpp
@@ -16,9 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "T2FGMM_UM.h"
-T2FGMM_UM::T2FGMM_UM() : firstTime(true), frameNumber(0), threshold(9.0), alpha(0.01), km(1.5f), kv(0.6f), gaussians(3), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+T2FGMM_UM::T2FGMM_UM() :
+ frameNumber(0), threshold(9.0), alpha(0.01), km(1.5f), kv(0.6f), gaussians(3)
{
std::cout << "T2FGMM_UM()" << std::endl;
+ setup("./config/T2FGMM_UM.xml");
}
T2FGMM_UM::~T2FGMM_UM()
@@ -28,23 +32,16 @@ T2FGMM_UM::~T2FGMM_UM()
void T2FGMM_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +52,7 @@ void T2FGMM_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
params.SetFrameSize(width, height);
params.LowThreshold() = threshold;
- params.HighThreshold() = 2*params.LowThreshold();
+ params.HighThreshold() = 2 * params.LowThreshold();
params.Alpha() = alpha;
params.MaxModes() = gaussians;
params.Type() = TYPE_T2FGMM_UM;
@@ -69,13 +66,18 @@ void T2FGMM_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("T2FGMM-UM", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("T2FGMM-UM", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
@@ -84,7 +86,7 @@ void T2FGMM_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
void T2FGMM_UM::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FGMM_UM.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -98,14 +100,14 @@ void T2FGMM_UM::saveConfig()
void T2FGMM_UM::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FGMM_UM.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 9.0);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.01);
- km = cvReadRealByName(fs, 0, "km", 1.5);
- kv = cvReadRealByName(fs, 0, "kv", 0.6);
- gaussians = cvReadIntByName(fs, 0, "gaussians", 3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 9.0);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.01);
+ km = cvReadRealByName(fs, nullptr, "km", 1.5);
+ kv = cvReadRealByName(fs, nullptr, "kv", 0.6);
+ gaussians = cvReadIntByName(fs, nullptr, "gaussians", 3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/tb/T2FGMM_UM.h b/package_bgs/T2FGMM_UM.h
similarity index 52%
rename from package_bgs/tb/T2FGMM_UM.h
rename to package_bgs/T2FGMM_UM.h
index ae6e29f..c58aeb7 100644
--- a/package_bgs/tb/T2FGMM_UM.h
+++ b/package_bgs/T2FGMM_UM.h
@@ -16,43 +16,42 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "T2FGMM.h"
+#include "IBGS.h"
+#include "T2F/T2FGMM.h"
using namespace Algorithms::BackgroundSubtraction;
-class T2FGMM_UM : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- T2FGMMParams params;
- T2FGMM bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- float km;
- float kv;
- int gaussians;
- bool showOutput;
-
-public:
- T2FGMM_UM();
- ~T2FGMM_UM();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class T2FGMM_UM : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ T2FGMMParams params;
+ T2FGMM bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ float km;
+ float kv;
+ int gaussians;
+
+ public:
+ T2FGMM_UM();
+ ~T2FGMM_UM();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/tb/T2FGMM_UV.cpp b/package_bgs/T2FGMM_UV.cpp
similarity index 64%
rename from package_bgs/tb/T2FGMM_UV.cpp
rename to package_bgs/T2FGMM_UV.cpp
index c6f99f1..4e9708f 100644
--- a/package_bgs/tb/T2FGMM_UV.cpp
+++ b/package_bgs/T2FGMM_UV.cpp
@@ -16,9 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "T2FGMM_UV.h"
-T2FGMM_UV::T2FGMM_UV() : firstTime(true), frameNumber(0), threshold(9.0), alpha(0.01), km(1.5f), kv(0.6f), gaussians(3), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+T2FGMM_UV::T2FGMM_UV() :
+ frameNumber(0), threshold(9.0), alpha(0.01), km(1.5f), kv(0.6f), gaussians(3)
{
std::cout << "T2FGMM_UV()" << std::endl;
+ setup("./config/T2FGMM_UV.xml");
}
T2FGMM_UV::~T2FGMM_UV()
@@ -28,23 +32,16 @@ T2FGMM_UV::~T2FGMM_UV()
void T2FGMM_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -55,7 +52,7 @@ void T2FGMM_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
params.SetFrameSize(width, height);
params.LowThreshold() = threshold;
- params.HighThreshold() = 2*params.LowThreshold();
+ params.HighThreshold() = 2 * params.LowThreshold();
params.Alpha() = alpha;
params.MaxModes() = gaussians;
params.Type() = TYPE_T2FGMM_UV;
@@ -69,13 +66,18 @@ void T2FGMM_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("T2FGMM-UV", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("T2FGMM-UV", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
firstTime = false;
@@ -84,7 +86,7 @@ void T2FGMM_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
void T2FGMM_UV::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FGMM_UV.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -98,14 +100,14 @@ void T2FGMM_UV::saveConfig()
void T2FGMM_UV::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FGMM_UV.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 9.0);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.01);
- km = cvReadRealByName(fs, 0, "km", 1.5);
- kv = cvReadRealByName(fs, 0, "kv", 0.6);
- gaussians = cvReadIntByName(fs, 0, "gaussians", 3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 9.0);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.01);
+ km = cvReadRealByName(fs, nullptr, "km", 1.5);
+ kv = cvReadRealByName(fs, nullptr, "kv", 0.6);
+ gaussians = cvReadIntByName(fs, nullptr, "gaussians", 3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/tb/T2FGMM_UV.h b/package_bgs/T2FGMM_UV.h
similarity index 52%
rename from package_bgs/tb/T2FGMM_UV.h
rename to package_bgs/T2FGMM_UV.h
index 79edcc2..6102f3a 100644
--- a/package_bgs/tb/T2FGMM_UV.h
+++ b/package_bgs/T2FGMM_UV.h
@@ -16,43 +16,42 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "T2FGMM.h"
+#include "IBGS.h"
+#include "T2F/T2FGMM.h"
using namespace Algorithms::BackgroundSubtraction;
-class T2FGMM_UV : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- T2FGMMParams params;
- T2FGMM bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- float km;
- float kv;
- int gaussians;
- bool showOutput;
-
-public:
- T2FGMM_UV();
- ~T2FGMM_UV();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
+ namespace algorithms
+ {
+ class T2FGMM_UV : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage* frame;
+ RgbImage frame_data;
+
+ T2FGMMParams params;
+ T2FGMM bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ float km;
+ float kv;
+ int gaussians;
+
+ public:
+ T2FGMM_UV();
+ ~T2FGMM_UV();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/tb/T2FMRF_UM.cpp b/package_bgs/T2FMRF_UM.cpp
similarity index 59%
rename from package_bgs/tb/T2FMRF_UM.cpp
rename to package_bgs/T2FMRF_UM.cpp
index 5b41d8a..e0e6dae 100644
--- a/package_bgs/tb/T2FMRF_UM.cpp
+++ b/package_bgs/T2FMRF_UM.cpp
@@ -16,10 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "T2FMRF_UM.h"
-T2FMRF_UM::T2FMRF_UM() : firstTime(true), frameNumber(0), threshold(9.0), alpha(0.01),
-km(2.f), kv(0.9f), gaussians(3), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+T2FMRF_UM::T2FMRF_UM() :
+ frameNumber(0), threshold(9.0), alpha(0.01), km(2.f), kv(0.9f), gaussians(3)
{
std::cout << "T2FMRF_UM()" << std::endl;
+ setup("./config/DPMean.xml");
}
T2FMRF_UM::~T2FMRF_UM()
@@ -29,23 +32,16 @@ T2FMRF_UM::~T2FMRF_UM()
void T2FMRF_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -56,7 +52,7 @@ void T2FMRF_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
params.SetFrameSize(width, height);
params.LowThreshold() = threshold;
- params.HighThreshold() = 2*params.LowThreshold();
+ params.HighThreshold() = 2 * params.LowThreshold();
params.Alpha() = alpha;
params.MaxModes() = gaussians;
params.Type() = TYPE_T2FMRF_UM;
@@ -70,7 +66,7 @@ void T2FMRF_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
old = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
mrf.height = height;
- mrf.width = width;
+ mrf.width = width;
mrf.Build_Classes_OldLabeling_InImage_LocalEnergy();
firstTime = false;
@@ -80,32 +76,37 @@ void T2FMRF_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
cvCopy(lowThresholdMask.Ptr(), old);
/************************************************************************/
- /* the code for MRF, it can be noted when using other methods */
- /************************************************************************/
- //the optimization process is done when the foreground detection is stable,
- if(frameNumber >= 10)
- {
- gmm = bgs.gmm();
- hmm = bgs.hmm();
- mrf.background2 = frame_data.Ptr();
- mrf.in_image = lowThresholdMask.Ptr();
- mrf.out_image = lowThresholdMask.Ptr();
- mrf.InitEvidence2(gmm,hmm,old_labeling);
- mrf.ICM2();
- cvCopy(mrf.out_image, lowThresholdMask.Ptr());
- }
+ /* the code for MRF, it can be noted when using other methods */
+ /************************************************************************/
+ //the optimization process is done when the foreground detection is stable,
+ if (frameNumber >= 10)
+ {
+ gmm = bgs.gmm();
+ hmm = bgs.hmm();
+ mrf.background2 = frame_data.Ptr();
+ mrf.in_image = lowThresholdMask.Ptr();
+ mrf.out_image = lowThresholdMask.Ptr();
+ mrf.InitEvidence2(gmm, hmm, old_labeling);
+ mrf.ICM2();
+ cvCopy(mrf.out_image, lowThresholdMask.Ptr());
+ }
cvCopy(old, old_labeling);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("T2FMRF-UM", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("T2FMRF-UM", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
frameNumber++;
@@ -113,7 +114,7 @@ void T2FMRF_UM::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
void T2FMRF_UM::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FMRF_UM.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -127,14 +128,14 @@ void T2FMRF_UM::saveConfig()
void T2FMRF_UM::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FMRF_UM.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 9.0);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.01);
- km = cvReadRealByName(fs, 0, "km", 2);
- kv = cvReadRealByName(fs, 0, "kv", 0.9);
- gaussians = cvReadIntByName(fs, 0, "gaussians", 3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 9.0);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.01);
+ km = cvReadRealByName(fs, nullptr, "km", 2);
+ kv = cvReadRealByName(fs, nullptr, "kv", 0.9);
+ gaussians = cvReadIntByName(fs, nullptr, "gaussians", 3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/T2FMRF_UM.h b/package_bgs/T2FMRF_UM.h
new file mode 100644
index 0000000..01f6014
--- /dev/null
+++ b/package_bgs/T2FMRF_UM.h
@@ -0,0 +1,64 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "T2F/MRF.h"
+
+using namespace Algorithms::BackgroundSubtraction;
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class T2FMRF_UM : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage *frame;
+ RgbImage frame_data;
+
+ IplImage *old_labeling;
+ IplImage *old;
+
+ T2FMRFParams params;
+ T2FMRF bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ float km;
+ float kv;
+ int gaussians;
+
+ MRF_TC mrf;
+ GMM *gmm;
+ HMM *hmm;
+
+ public:
+ T2FMRF_UM();
+ ~T2FMRF_UM();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/tb/T2FMRF_UV.cpp b/package_bgs/T2FMRF_UV.cpp
similarity index 59%
rename from package_bgs/tb/T2FMRF_UV.cpp
rename to package_bgs/T2FMRF_UV.cpp
index 03f2595..7f43c02 100644
--- a/package_bgs/tb/T2FMRF_UV.cpp
+++ b/package_bgs/T2FMRF_UV.cpp
@@ -16,10 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "T2FMRF_UV.h"
-T2FMRF_UV::T2FMRF_UV() : firstTime(true), frameNumber(0), threshold(9.0), alpha(0.01),
-km(2.f), kv(0.9f), gaussians(3), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+T2FMRF_UV::T2FMRF_UV() :
+ frameNumber(0), threshold(9.0), alpha(0.01), km(2.f), kv(0.9f), gaussians(3)
{
std::cout << "T2FMRF_UV()" << std::endl;
+ setup("./config/T2FMRF_UV.xml");
}
T2FMRF_UV::~T2FMRF_UV()
@@ -29,23 +32,16 @@ T2FMRF_UV::~T2FMRF_UV()
void T2FMRF_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
+ init(img_input, img_output, img_bgmodel);
frame = new IplImage(img_input);
-
- if(firstTime)
+
+ if (firstTime)
frame_data.ReleaseMemory(false);
frame_data = frame;
- if(firstTime)
+ if (firstTime)
{
- int width = img_input.size().width;
+ int width = img_input.size().width;
int height = img_input.size().height;
lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
@@ -56,7 +52,7 @@ void T2FMRF_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
params.SetFrameSize(width, height);
params.LowThreshold() = threshold;
- params.HighThreshold() = 2*params.LowThreshold();
+ params.HighThreshold() = 2 * params.LowThreshold();
params.Alpha() = alpha;
params.MaxModes() = gaussians;
params.Type() = TYPE_T2FMRF_UV;
@@ -70,7 +66,7 @@ void T2FMRF_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
old = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
mrf.height = height;
- mrf.width = width;
+ mrf.width = width;
mrf.Build_Classes_OldLabeling_InImage_LocalEnergy();
firstTime = false;
@@ -80,32 +76,37 @@ void T2FMRF_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
cvCopy(lowThresholdMask.Ptr(), old);
/************************************************************************/
- /* the code for MRF, it can be noted when using other methods */
- /************************************************************************/
- //the optimization process is done when the foreground detection is stable,
- if(frameNumber >= 10)
- {
- gmm = bgs.gmm();
- hmm = bgs.hmm();
- mrf.background2 = frame_data.Ptr();
- mrf.in_image = lowThresholdMask.Ptr();
- mrf.out_image = lowThresholdMask.Ptr();
- mrf.InitEvidence2(gmm,hmm,old_labeling);
- mrf.ICM2();
- cvCopy(mrf.out_image, lowThresholdMask.Ptr());
- }
+ /* the code for MRF, it can be noted when using other methods */
+ /************************************************************************/
+ //the optimization process is done when the foreground detection is stable,
+ if (frameNumber >= 10)
+ {
+ gmm = bgs.gmm();
+ hmm = bgs.hmm();
+ mrf.background2 = frame_data.Ptr();
+ mrf.in_image = lowThresholdMask.Ptr();
+ mrf.out_image = lowThresholdMask.Ptr();
+ mrf.InitEvidence2(gmm, hmm, old_labeling);
+ mrf.ICM2();
+ cvCopy(mrf.out_image, lowThresholdMask.Ptr());
+ }
cvCopy(old, old_labeling);
lowThresholdMask.Clear();
bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- if(showOutput)
- cv::imshow("T2FMRF-UV", foreground);
-
- foreground.copyTo(img_output);
+ img_foreground = cv::cvarrToMat(highThresholdMask.Ptr());
+ img_background = cv::cvarrToMat(bgs.Background()->Ptr());
+ //img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ cv::imshow("T2FMRF-UV", img_foreground);
+#endif
+
+ img_foreground.copyTo(img_output);
+ img_background.copyTo(img_bgmodel);
delete frame;
frameNumber++;
@@ -113,7 +114,7 @@ void T2FMRF_UV::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &
void T2FMRF_UV::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FMRF_UV.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteReal(fs, "threshold", threshold);
cvWriteReal(fs, "alpha", alpha);
@@ -127,14 +128,14 @@ void T2FMRF_UV::saveConfig()
void T2FMRF_UV::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/T2FMRF_UV.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadRealByName(fs, 0, "threshold", 9.0);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.01);
- km = cvReadRealByName(fs, 0, "km", 2);
- kv = cvReadRealByName(fs, 0, "kv", 0.9);
- gaussians = cvReadIntByName(fs, 0, "gaussians", 3);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 9.0);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.01);
+ km = cvReadRealByName(fs, nullptr, "km", 2);
+ kv = cvReadRealByName(fs, nullptr, "kv", 0.9);
+ gaussians = cvReadIntByName(fs, nullptr, "gaussians", 3);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/T2FMRF_UV.h b/package_bgs/T2FMRF_UV.h
new file mode 100644
index 0000000..1c69171
--- /dev/null
+++ b/package_bgs/T2FMRF_UV.h
@@ -0,0 +1,64 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "T2F/MRF.h"
+
+using namespace Algorithms::BackgroundSubtraction;
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class T2FMRF_UV : public IBGS
+ {
+ private:
+ long frameNumber;
+ IplImage *frame;
+ RgbImage frame_data;
+
+ IplImage *old_labeling;
+ IplImage *old;
+
+ T2FMRFParams params;
+ T2FMRF bgs;
+ BwImage lowThresholdMask;
+ BwImage highThresholdMask;
+
+ double threshold;
+ double alpha;
+ float km;
+ float kv;
+ int gaussians;
+
+ MRF_TC mrf;
+ GMM *gmm;
+ HMM *hmm;
+
+ public:
+ T2FMRF_UV();
+ ~T2FMRF_UV();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/TwoPoints.cpp b/package_bgs/TwoPoints.cpp
new file mode 100644
index 0000000..aee4684
--- /dev/null
+++ b/package_bgs/TwoPoints.cpp
@@ -0,0 +1,112 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+
+#include "TwoPoints.h"
+
+using namespace bgslibrary::algorithms;
+
+TwoPoints::TwoPoints() :
+ matchingThreshold(DEFAULT_MATCH_THRESH),
+ updateFactor(DEFAULT_UPDATE_FACTOR), model(nullptr)
+{
+ std::cout << "TwoPoints()" << std::endl;
+ //model = static_cast<twopointsModel_t*>(libtwopointsModel_New());
+ model = libtwopointsModel_New();
+ setup("./config/TwoPoints.xml");
+}
+
+TwoPoints::~TwoPoints()
+{
+ std::cout << "~TwoPoints()" << std::endl;
+ libtwopointsModel_Free(model);
+}
+
+void TwoPoints::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (img_input.empty())
+ return;
+
+ cv::Mat updatingMask;
+ cv::Mat img_input_grayscale;
+
+ // Convert input image to a grayscale image
+ cvtColor(img_input, img_input_grayscale, CV_BGR2GRAY);
+
+ if (firstTime)
+ {
+ // Create a buffer for the output image.
+ //img_output = Mat(img_input.rows, img_input.cols, CV_8UC1);
+
+ // Initialization of the ViBe model.
+ libtwopointsModel_AllocInit_8u_C1R(model, img_input_grayscale.data, img_input.cols, img_input.rows);
+
+ // Sets default model values.
+ // libvibeModel_Sequential_SetMatchingThreshold(model, matchingThreshold);
+ // libvibeModel_Sequential_SetUpdateFactor(model, updateFactor);
+ }
+
+ libtwopointsModel_Segmentation_8u_C1R(model, img_input_grayscale.data, img_output.data);
+
+ updatingMask = cv::Mat(img_input.rows, img_input.cols, CV_8UC1);
+ // Work on the output and define the updating mask
+ for (int i = 0; i < img_input.cols * img_input.rows; i++)
+ {
+ if (img_output.data[i] == 0) // Foreground pixel
+ {
+ updatingMask.data[i] = 0;
+ img_output.data[i] = 255;
+ }
+ else // Background
+ {
+ updatingMask.data[i] = 255;
+ img_output.data[i] = 0;
+ }
+ }
+
+ libtwopointsModel_Update_8u_C1R(model, img_input_grayscale.data, updatingMask.data);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ imshow("Two points", img_output);
+#endif
+
+ firstTime = false;
+}
+
+void TwoPoints::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "matchingThreshold", matchingThreshold);
+ cvWriteInt(fs, "updateFactor", updateFactor);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void TwoPoints::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ matchingThreshold = cvReadRealByName(fs, nullptr, "matchingThreshold", DEFAULT_MATCH_THRESH);
+ updateFactor = cvReadRealByName(fs, nullptr, "updateFactor", DEFAULT_UPDATE_FACTOR);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", false);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/TwoPoints.h b/package_bgs/TwoPoints.h
new file mode 100644
index 0000000..b42c231
--- /dev/null
+++ b/package_bgs/TwoPoints.h
@@ -0,0 +1,46 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "TwoPoints/two_points.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class TwoPoints : public IBGS
+ {
+ private:
+ static const int DEFAULT_MATCH_THRESH = 20;
+ static const int DEFAULT_UPDATE_FACTOR = 16;
+ int matchingThreshold;
+ int updateFactor;
+ twopointsModel_t* model;
+
+ public:
+ TwoPoints();
+ ~TwoPoints();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/TwoPoints/two_points.cpp b/package_bgs/TwoPoints/two_points.cpp
new file mode 100644
index 0000000..d8ee86b
--- /dev/null
+++ b/package_bgs/TwoPoints/two_points.cpp
@@ -0,0 +1,394 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include <assert.h>
+
+#include "two_points.h"
+
+static unsigned int abs_uint(const int i)
+{
+ return (i >= 0) ? i : -i;
+}
+
+struct twopointsModel
+{
+ /* Parameters. */
+ uint32_t width;
+ uint32_t height;
+ uint32_t numberOfSamples;
+ uint32_t matchingThreshold;
+ uint32_t matchingNumber;
+ uint32_t updateFactor;
+
+ /* Storage for the history. */
+ uint8_t *historyImage1;
+ uint8_t *historyImage2;
+
+ /* Buffers with random values. */
+ uint32_t *jump;
+ int *neighbor;
+};
+
+// -----------------------------------------------------------------------------
+// Creates the data structure
+// -----------------------------------------------------------------------------
+twopointsModel_t *libtwopointsModel_New()
+{
+ /* Model structure alloc. */
+ twopointsModel_t *model = NULL;
+ model = (twopointsModel_t*)calloc(1, sizeof(*model));
+ assert(model != NULL);
+
+ /* Default parameters values. */
+ model->matchingThreshold = 20;
+ model->updateFactor = 16;
+
+ /* Storage for the history. */
+ model->historyImage1 = NULL;
+ model->historyImage2 = NULL;
+
+ /* Buffers with random values. */
+ model->jump = NULL;
+ model->neighbor = NULL;
+
+ return(model);
+}
+
+// ----------------------------------------------------------------------------
+// Frees the structure
+// ----------------------------------------------------------------------------
+int32_t libtwopointsModel_Free(twopointsModel_t *model)
+{
+ if (model == NULL)
+ return(-1);
+
+ if (model->historyImage1 != NULL) {
+ free(model->historyImage1);
+ model->historyImage1 = NULL;
+ }
+ if (model->historyImage2 != NULL) {
+ free(model->historyImage2);
+ model->historyImage2 = NULL;
+ }
+ if (model->jump != NULL) {
+ free(model->jump);
+ model->jump = NULL;
+ }
+ if (model->neighbor != NULL) {
+ free(model->neighbor);
+ model->neighbor = NULL;
+ }
+ free(model);
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+// Allocates and initializes a C1R model structure
+// -----------------------------------------------------------------------------
+int32_t libtwopointsModel_AllocInit_8u_C1R(
+ twopointsModel_t *model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height
+)
+{
+ // Some basic checks. */
+ assert((image_data != NULL) && (model != NULL));
+ assert((width > 0) && (height > 0));
+
+ /* Finish model alloc - parameters values cannot be changed anymore. */
+ model->width = width;
+ model->height = height;
+
+ /* Creates the historyImage structure. */
+ model->historyImage1 = NULL;
+ model->historyImage1 = (uint8_t*)malloc(width * height * sizeof(uint8_t));
+ model->historyImage2 = NULL;
+ model->historyImage2 = (uint8_t*)malloc(width * height * sizeof(uint8_t));
+
+ assert(model->historyImage1 != NULL);
+ assert(model->historyImage2 != NULL);
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ uint8_t value = image_data[index];
+
+ int value_plus_noise = value - 10;
+ if (value_plus_noise < 0) { value_plus_noise = 0; }
+ if (value_plus_noise > 255) { value_plus_noise = 255; }
+ model->historyImage1[index] = value_plus_noise;
+
+ value_plus_noise = value + 10;
+ if (value_plus_noise < 0) { value_plus_noise = 0; }
+ if (value_plus_noise > 255) { value_plus_noise = 255; }
+ model->historyImage2[index] = value_plus_noise;
+
+ // Swaps the two values if needed
+ if (model->historyImage1[index] > model->historyImage2[index]) {
+ uint8_t val = model->historyImage1[index];
+ model->historyImage1[index] = model->historyImage2[index];
+ model->historyImage2[index] = val;
+ }
+ }
+
+ /* Fills the buffers with random values. */
+ int size = (width > height) ? 2 * width + 1 : 2 * height + 1;
+
+ model->jump = (uint32_t*)malloc(size * sizeof(*(model->jump)));
+ assert(model->jump != NULL);
+
+ model->neighbor = (int*)malloc(size * sizeof(*(model->neighbor)));
+ assert(model->neighbor != NULL);
+
+
+ for (int i = 0; i < size; ++i) {
+ model->jump[i] = (rand() % (2 * model->updateFactor)) + 1; // Values between 1 and 2 * updateFactor.
+ model->neighbor[i] = ((rand() % 3) - 1) + ((rand() % 3) - 1) * width; // Values between { -width - 1, ... , width + 1 }.
+ }
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+// Segmentation of a C1R model
+// -----------------------------------------------------------------------------
+int32_t libtwopointsModel_Segmentation_8u_C1R(
+ twopointsModel_t *model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map
+)
+{
+ assert((image_data != NULL) && (model != NULL) && (segmentation_map != NULL));
+ assert((model->width > 0) && (model->height > 0));
+ assert((model->jump != NULL) && (model->neighbor != NULL));
+
+ /* Some variables. */
+ uint32_t width = model->width;
+ uint32_t height = model->height;
+ uint32_t matchingThreshold = model->matchingThreshold;
+
+ uint8_t *historyImage1 = model->historyImage1;
+ uint8_t *historyImage2 = model->historyImage2;
+
+ /* Segmentation. */
+ memset(segmentation_map, 0, width * height);
+
+ uint8_t *first = historyImage1;
+ for (int index = width * height - 1; index >= 0; --index) {
+ // We adapt the threshold
+ matchingThreshold = model->matchingThreshold;
+ if (matchingThreshold < abs_uint(historyImage2[index] - historyImage1[index])) {
+ matchingThreshold = abs_uint(historyImage2[index] - historyImage1[index]);
+ }
+ if (abs_uint(image_data[index] - first[index]) <= matchingThreshold)
+ segmentation_map[index]++;
+ }
+
+ first = historyImage2;
+ for (int index = width * height - 1; index >= 0; --index) {
+ // We adapt the threshold
+ matchingThreshold = model->matchingThreshold;
+ if (matchingThreshold < abs_uint(historyImage2[index] - historyImage1[index])) {
+ matchingThreshold = abs_uint(historyImage2[index] - historyImage1[index]);
+ }
+ if (abs_uint(image_data[index] - first[index]) <= matchingThreshold)
+ segmentation_map[index]++;
+ }
+
+ return(0);
+}
+
+// ----------------------------------------------------------------------------
+// Update a C1R model
+// ----------------------------------------------------------------------------
+int doUpdate(const uint8_t value)
+{
+ if (value == 0) return 0;
+ else return 1;
+}
+
+
+int32_t libtwopointsModel_Update_8u_C1R(
+ twopointsModel_t *model,
+ const uint8_t *image_data,
+ uint8_t *updating_mask
+)
+{
+ assert((image_data != NULL) && (model != NULL) && (updating_mask != NULL));
+ assert((model->width > 0) && (model->height > 0));
+ assert((model->jump != NULL) && (model->neighbor != NULL));
+
+ // Some variables.
+ uint32_t width = model->width;
+ uint32_t height = model->height;
+
+ uint8_t *historyImage1 = model->historyImage1;
+ uint8_t *historyImage2 = model->historyImage2;
+
+ // Updating.
+ uint32_t *jump = model->jump;
+ int *neighbor = model->neighbor;
+
+ // All the frame, except the border.
+ uint32_t shift, indX, indY;
+ unsigned int x, y;
+
+ for (y = 1; y < height - 1; ++y) {
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX < width - 1) {
+ int index = indX + y * width;
+
+ if (doUpdate(updating_mask[index])) {
+ uint8_t value = image_data[index];
+ // In-place substitution.
+ // if (2*value < (historyImage1[index]+historyImage2[index]) ) {
+ if (rand() % 2 == 0) {
+ historyImage1[index] = value;
+ }
+ else {
+ historyImage2[index] = value;
+ }
+
+ // Propagation
+ int index_neighbor = index + neighbor[shift];
+ if (2 * value < (historyImage1[index_neighbor] + historyImage2[index_neighbor])) {
+ // if (rand()%2 == 0 ) {
+ historyImage1[index_neighbor] = value;
+ }
+ else {
+ historyImage2[index_neighbor] = value;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+ }
+
+ // First row.
+ y = 0;
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX <= width - 1) {
+ int index = indX + y * width;
+
+ if (doUpdate(updating_mask[index])) {
+ uint8_t value = image_data[index];
+ // In-place substitution.
+ // if (2*value < (historyImage1[index]+historyImage2[index]) ) {
+ if (rand() % 2 == 0) {
+ historyImage1[index] = value;
+ }
+ else {
+ historyImage2[index] = value;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+
+ // Last row.
+ y = height - 1;
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX <= width - 1) {
+ int index = indX + y * width;
+
+ if (doUpdate(updating_mask[index])) {
+ uint8_t value = image_data[index];
+ // In-place substitution.
+ // if (2*value < (historyImage1[index]+historyImage2[index]) ) {
+ if (rand() % 2 == 0) {
+ historyImage1[index] = value;
+ }
+ else {
+ historyImage2[index] = value;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+
+ // First column.
+ x = 0;
+ shift = rand() % height;
+ indY = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indY <= height - 1) {
+ int index = x + indY * width;
+
+ if (doUpdate(updating_mask[index])) {
+ uint8_t value = image_data[index];
+ // In-place substitution.
+ // if (2*value < (historyImage1[index]+historyImage2[index]) ) {
+ if (rand() % 2 == 0) {
+ historyImage1[index] = value;
+ }
+ else {
+ historyImage2[index] = value;
+ }
+ }
+
+ ++shift;
+ indY += jump[shift];
+ }
+
+ // Last column.
+ x = width - 1;
+ shift = rand() % height;
+ indY = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indY <= height - 1) {
+ int index = x + indY * width;
+
+ if (doUpdate(updating_mask[index])) {
+ uint8_t value = image_data[index];
+ // In-place substitution.
+ // if (2*value < (historyImage1[index]+historyImage2[index]) ) {
+ if (rand() % 2 == 0) {
+ historyImage1[index] = value;
+ }
+ else {
+ historyImage2[index] = value;
+ }
+ }
+
+ ++shift;
+ indY += jump[shift];
+ }
+
+ // The first pixel!
+ if (rand() % model->updateFactor == 0) {
+ if (doUpdate(updating_mask[0])) {
+ uint8_t value = image_data[0];
+ // In-place substitution.
+ if (rand() % 2 == 0) {
+ historyImage1[0] = value;
+ }
+ else {
+ historyImage2[0] = value;
+ }
+ }
+ }
+
+ return(0);
+}
diff --git a/package_bgs/TwoPoints/two_points.h b/package_bgs/TwoPoints/two_points.h
new file mode 100644
index 0000000..a64152a
--- /dev/null
+++ b/package_bgs/TwoPoints/two_points.h
@@ -0,0 +1,50 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <stdlib.h>
+#include <stdint.h>
+#include <stdio.h>
+#include <string.h>
+
+#define COLOR_BACKGROUND 0 /*!< Default label for background pixels */
+#define COLOR_FOREGROUND 255 /*!< Default label for foreground pixels. Note that some authors chose any value different from 0 instead */
+
+typedef struct twopointsModel twopointsModel_t;
+
+twopointsModel_t *libtwopointsModel_New();
+
+int32_t libtwopointsModel_Free(twopointsModel_t *model);
+
+int32_t libtwopointsModel_AllocInit_8u_C1R(
+ twopointsModel_t *model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height
+);
+
+int32_t libtwopointsModel_Segmentation_8u_C1R(
+ twopointsModel_t *model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map
+);
+
+int32_t libtwopointsModel_Update_8u_C1R(
+ twopointsModel_t *model,
+ const uint8_t *image_data,
+ uint8_t *updating_mask
+);
diff --git a/package_bgs/ViBe.cpp b/package_bgs/ViBe.cpp
new file mode 100644
index 0000000..0d3125f
--- /dev/null
+++ b/package_bgs/ViBe.cpp
@@ -0,0 +1,98 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+
+#include "ViBe.h"
+
+using namespace bgslibrary::algorithms;
+
+ViBe::ViBe() :
+ //numberOfSamples(DEFAULT_NUM_SAMPLES),
+ matchingThreshold(DEFAULT_MATCH_THRESH),
+ matchingNumber(DEFAULT_MATCH_NUM),
+ updateFactor(DEFAULT_UPDATE_FACTOR),
+ model(nullptr)
+{
+ std::cout << "ViBe()" << std::endl;
+ model = libvibeModel_Sequential_New();
+ setup("./config/ViBe.xml");
+}
+
+ViBe::~ViBe()
+{
+ std::cout << "~ViBe()" << std::endl;
+ libvibeModel_Sequential_Free(model);
+}
+
+void ViBe::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (img_input.empty())
+ return;
+
+ if (firstTime)
+ {
+ /* Create a buffer for the output image. */
+ //img_output = cv::Mat(img_input.rows, img_input.cols, CV_8UC1);
+
+ /* Initialization of the ViBe model. */
+ libvibeModel_Sequential_AllocInit_8u_C3R(model, img_input.data, img_input.cols, img_input.rows);
+
+ /* Sets default model values. */
+ //libvibeModel_Sequential_SetNumberOfSamples(model, numberOfSamples);
+ libvibeModel_Sequential_SetMatchingThreshold(model, matchingThreshold);
+ libvibeModel_Sequential_SetMatchingNumber(model, matchingNumber);
+ libvibeModel_Sequential_SetUpdateFactor(model, updateFactor);
+ }
+
+ libvibeModel_Sequential_Segmentation_8u_C3R(model, img_input.data, img_output.data);
+ //libvibeModel_Sequential_Update_8u_C3R(model, model_img_input.data, img_output.data);
+ libvibeModel_Sequential_Update_8u_C3R(model, img_input.data, img_output.data);
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ imshow("ViBe", img_output);
+#endif
+
+ firstTime = false;
+}
+
+void ViBe::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ //cvWriteInt(fs, "numberOfSamples", numberOfSamples);
+ cvWriteInt(fs, "matchingThreshold", matchingThreshold);
+ cvWriteInt(fs, "matchingNumber", matchingNumber);
+ cvWriteInt(fs, "updateFactor", updateFactor);
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void ViBe::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ //numberOfSamples = cvReadIntByName(fs, nullptr, "numberOfSamples", DEFAULT_NUM_SAMPLES);
+ matchingThreshold = cvReadRealByName(fs, nullptr, "matchingThreshold", DEFAULT_MATCH_THRESH);
+ matchingNumber = cvReadRealByName(fs, nullptr, "matchingNumber", DEFAULT_MATCH_NUM);
+ updateFactor = cvReadRealByName(fs, nullptr, "updateFactor", DEFAULT_UPDATE_FACTOR);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", false);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/ViBe.h b/package_bgs/ViBe.h
new file mode 100644
index 0000000..c8014cb
--- /dev/null
+++ b/package_bgs/ViBe.h
@@ -0,0 +1,52 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "ViBe/vibe-background-sequential.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class ViBe : public IBGS
+ {
+ private:
+ static const int DEFAULT_NUM_SAMPLES = 20;
+ static const int DEFAULT_MATCH_THRESH = 20;
+ static const int DEFAULT_MATCH_NUM = 2;
+ static const int DEFAULT_UPDATE_FACTOR = 16;
+
+ private:
+ //int numberOfSamples;
+ int matchingThreshold;
+ int matchingNumber;
+ int updateFactor;
+ vibeModel_Sequential_t* model;
+
+ public:
+ ViBe();
+ ~ViBe();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/ViBe/LICENSE b/package_bgs/ViBe/LICENSE
new file mode 100644
index 0000000..7f22a77
--- /dev/null
+++ b/package_bgs/ViBe/LICENSE
@@ -0,0 +1,44 @@
+ Authors:
+ --------
+ Olivier Barnich and
+ Marc Van Droogenbroeck <m.vandroogenbroeck@ulg.ac.be>
+
+ Licence:
+ --------
+ ViBe is covered by a patent (see http://www.ulg.ac.be/telecom/research/vibe).
+ We do not provide the source code but provide an object file and an interface.
+
+ Permission to use ViBe without payment of fee is granted
+ for nonprofit educational and research purposes only.
+
+ This work may not be copied or reproduced in whole or in part for any
+ purpose.
+
+ Copying, reproduction, or republishing for any purpose shall require
+ a license. Please contact the author in such cases.
+ All the code is provided without any guarantee.
+
+
+ How to refer to us:
+ -------------------
+
+ If you want to refer to this work, please cite the following publications:
+
+ Barnich and M. Van Droogenbroeck. ViBe: A universal background subtraction algorithm for video sequences. In IEEE Transactions on Image Processing, 20(6):1709-1724, June 2011.
+
+@article{Barnich2011ViBe,
+ title = {{ViBe}: A universal background subtraction algorithm for video sequences},
+ author = {O. Barnich and M. {Van Droogenbroeck}},
+ journal = {IEEE Transactions on Image Processing},
+ volume = {20},
+ number = {6},
+ pages = {1709-1724},
+ month = {June},
+ year = {2011},
+ keywords = {ViBe, Background, Background subtraction, Segmentation, Motion, Motion detection},
+ pdf = {http://orbi.ulg.ac.be/bitstream/2268/81248/1/Barnich2011ViBe.pdf},
+ doi = {10.1109/TIP.2010.2101613},
+ url = {http://hdl.handle.net/2268/81248}
+}
+
+
diff --git a/package_bgs/ViBe/vibe-background-sequential.cpp b/package_bgs/ViBe/vibe-background-sequential.cpp
new file mode 100644
index 0000000..c4b9178
--- /dev/null
+++ b/package_bgs/ViBe/vibe-background-sequential.cpp
@@ -0,0 +1,929 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/**
+@file vibe-background-sequential.c
+@brief Implementation of vibe-background-sequential.h
+@author Marc Van Droogenbroeck
+@date May 2014
+*/
+#include <assert.h>
+#include <time.h>
+
+#include "vibe-background-sequential.h"
+
+#define NUMBER_OF_HISTORY_IMAGES 2
+
+uint32_t distance_Han2014Improved(uint8_t pixel, uint8_t bg)
+{
+ uint8_t min, max;
+
+ // Computes R = 0.13 min{ max[bg,26], 230}
+ max = 26;
+ if (bg > max) { max = bg; }
+
+ min = 230;
+ if (min > max) { min = max; }
+
+ return (uint32_t)(0.13*min);
+}
+
+static int abs_uint(const int i)
+{
+ return (i >= 0) ? i : -i;
+}
+
+static int32_t distance_is_close_8u_C3R(uint8_t r1, uint8_t g1, uint8_t b1, uint8_t r2, uint8_t g2, uint8_t b2, uint32_t threshold)
+{
+ return (abs_uint(r1 - r2) + abs_uint(g1 - g2) + abs_uint(b1 - b2) <= 4.5 * threshold);
+}
+
+struct vibeModel_Sequential
+{
+ /* Parameters. */
+ uint32_t width;
+ uint32_t height;
+ uint32_t numberOfSamples;
+ uint32_t matchingThreshold;
+ uint32_t matchingNumber;
+ uint32_t updateFactor;
+
+ /* Storage for the history. */
+ uint8_t *historyImage;
+ uint8_t *historyBuffer;
+ uint32_t lastHistoryImageSwapped;
+
+ /* Buffers with random values. */
+ uint32_t *jump;
+ int *neighbor;
+ uint32_t *position;
+};
+
+// -----------------------------------------------------------------------------
+// Print parameters
+// -----------------------------------------------------------------------------
+uint32_t libvibeModel_Sequential_PrintParameters(const vibeModel_Sequential_t *model)
+{
+ printf(
+ "Using ViBe background subtraction algorithm\n"
+ " - Number of samples per pixel: %03d\n"
+ " - Number of matches needed: %03d\n"
+ " - Matching threshold: %03d\n"
+ " - Model update subsampling factor: %03d\n",
+ libvibeModel_Sequential_GetNumberOfSamples(model),
+ libvibeModel_Sequential_GetMatchingNumber(model),
+ libvibeModel_Sequential_GetMatchingThreshold(model),
+ libvibeModel_Sequential_GetUpdateFactor(model)
+ );
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+// Creates the data structure
+// -----------------------------------------------------------------------------
+vibeModel_Sequential_t *libvibeModel_Sequential_New()
+{
+ /* Model structure alloc. */
+ vibeModel_Sequential_t *model = NULL;
+ model = (vibeModel_Sequential_t*)calloc(1, sizeof(*model));
+ assert(model != NULL);
+
+ /* Default parameters values. */
+ model->numberOfSamples = 20;
+ model->matchingThreshold = 20;
+ model->matchingNumber = 2;
+ model->updateFactor = 16;
+
+ /* Storage for the history. */
+ model->historyImage = NULL;
+ model->historyBuffer = NULL;
+ model->lastHistoryImageSwapped = 0;
+
+ /* Buffers with random values. */
+ model->jump = NULL;
+ model->neighbor = NULL;
+ model->position = NULL;
+
+ return(model);
+}
+
+// -----------------------------------------------------------------------------
+// Some "Get-ers"
+// -----------------------------------------------------------------------------
+uint32_t libvibeModel_Sequential_GetNumberOfSamples(const vibeModel_Sequential_t *model)
+{
+ assert(model != NULL); return(model->numberOfSamples);
+}
+
+uint32_t libvibeModel_Sequential_GetMatchingNumber(const vibeModel_Sequential_t *model)
+{
+ assert(model != NULL); return(model->matchingNumber);
+}
+
+uint32_t libvibeModel_Sequential_GetMatchingThreshold(const vibeModel_Sequential_t *model)
+{
+ assert(model != NULL); return(model->matchingThreshold);
+}
+
+uint32_t libvibeModel_Sequential_GetUpdateFactor(const vibeModel_Sequential_t *model)
+{
+ assert(model != NULL); return(model->updateFactor);
+}
+
+// -----------------------------------------------------------------------------
+// Some "Set-ers"
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_SetMatchingThreshold(
+ vibeModel_Sequential_t *model,
+ const uint32_t matchingThreshold
+) {
+ assert(model != NULL);
+ assert(matchingThreshold > 0);
+
+ model->matchingThreshold = matchingThreshold;
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_SetMatchingNumber(
+ vibeModel_Sequential_t *model,
+ const uint32_t matchingNumber
+) {
+ assert(model != NULL);
+ assert(matchingNumber > 0);
+
+ model->matchingNumber = matchingNumber;
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_SetUpdateFactor(
+ vibeModel_Sequential_t *model,
+ const uint32_t updateFactor
+) {
+ assert(model != NULL);
+ assert(updateFactor > 0);
+
+ model->updateFactor = updateFactor;
+
+ /* We also need to change the values of the jump buffer ! */
+ assert(model->jump != NULL);
+
+ /* Shifts. */
+ int size = (model->width > model->height) ? 2 * model->width + 1 : 2 * model->height + 1;
+
+ for (int i = 0; i < size; ++i)
+ model->jump[i] = (updateFactor == 1) ? 1 : (rand() % (2 * model->updateFactor)) + 1; // 1 or values between 1 and 2 * updateFactor.
+
+ return(0);
+}
+
+// ----------------------------------------------------------------------------
+// Frees the structure
+// ----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_Free(vibeModel_Sequential_t *model)
+{
+ if (model == NULL)
+ return(-1);
+
+ if (model->historyBuffer == NULL) {
+ free(model);
+ return(0);
+ }
+
+ free(model->historyImage);
+ free(model->historyBuffer);
+ free(model->jump);
+ free(model->neighbor);
+ free(model->position);
+ free(model);
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+// Allocates and initializes a C1R model structure
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_AllocInit_8u_C1R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height
+) {
+ // Some basic checks. */
+ assert((image_data != NULL) && (model != NULL));
+ assert((width > 0) && (height > 0));
+
+ /* Finish model alloc - parameters values cannot be changed anymore. */
+ model->width = width;
+ model->height = height;
+
+ /* Creates the historyImage structure. */
+ model->historyImage = NULL;
+ model->historyImage = (uint8_t*)malloc(NUMBER_OF_HISTORY_IMAGES * width * height * sizeof(*(model->historyImage)));
+
+ assert(model->historyImage != NULL);
+
+ for (int i = 0; i < NUMBER_OF_HISTORY_IMAGES; ++i) {
+ for (int index = width * height - 1; index >= 0; --index)
+ model->historyImage[i * width * height + index] = image_data[index];
+ }
+
+ /* Now creates and fills the history buffer. */
+ model->historyBuffer = (uint8_t*)malloc(width * height * (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES) * sizeof(uint8_t));
+ assert(model->historyBuffer != NULL);
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ uint8_t value = image_data[index];
+
+ for (int x = 0; x < model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES; ++x) {
+ int value_plus_noise = value + rand() % 20 - 10;
+
+ if (value_plus_noise < 0) { value_plus_noise = 0; }
+ if (value_plus_noise > 255) { value_plus_noise = 255; }
+
+ model->historyBuffer[index * (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES) + x] = value_plus_noise;
+ }
+ }
+
+ /* Fills the buffers with random values. */
+ int size = (width > height) ? 2 * width + 1 : 2 * height + 1;
+
+ model->jump = (uint32_t*)malloc(size * sizeof(*(model->jump)));
+ assert(model->jump != NULL);
+
+ model->neighbor = (int*)malloc(size * sizeof(*(model->neighbor)));
+ assert(model->neighbor != NULL);
+
+ model->position = (uint32_t*)malloc(size * sizeof(*(model->position)));
+ assert(model->position != NULL);
+
+ for (int i = 0; i < size; ++i) {
+ model->jump[i] = (rand() % (2 * model->updateFactor)) + 1; // Values between 1 and 2 * updateFactor.
+ model->neighbor[i] = ((rand() % 3) - 1) + ((rand() % 3) - 1) * width; // Values between { -width - 1, ... , width + 1 }.
+ model->position[i] = rand() % (model->numberOfSamples); // Values between 0 and numberOfSamples - 1.
+ }
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+// Segmentation of a C1R model
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_Segmentation_8u_C1R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map
+) {
+ /* Basic checks. */
+ assert((image_data != NULL) && (model != NULL) && (segmentation_map != NULL));
+ assert((model->width > 0) && (model->height > 0));
+ assert(model->historyBuffer != NULL);
+ assert((model->jump != NULL) && (model->neighbor != NULL) && (model->position != NULL));
+
+ /* Some variables. */
+ uint32_t width = model->width;
+ uint32_t height = model->height;
+ uint32_t matchingNumber = model->matchingNumber;
+ uint32_t matchingThreshold = model->matchingThreshold;
+
+ uint8_t *historyImage = model->historyImage;
+ uint8_t *historyBuffer = model->historyBuffer;
+
+ /* Segmentation. */
+ memset(segmentation_map, matchingNumber - 1, width * height);
+
+ /* First history Image structure. */
+ for (int index = width * height - 1; index >= 0; --index) {
+ //if (abs_uint(image_data[index] - historyImage[index]) > matchingThreshold)
+ if (abs_uint(image_data[index] - historyImage[index]) > distance_Han2014Improved(image_data[index], historyImage[index]))
+ segmentation_map[index] = matchingNumber;
+ }
+
+ /* Next historyImages. */
+ for (int i = 1; i < NUMBER_OF_HISTORY_IMAGES; ++i) {
+ uint8_t *pels = historyImage + i * width * height;
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ // if (abs_uint(image_data[index] - pels[index]) <= matchingThreshold)
+ if (abs_uint(image_data[index] - pels[index]) <= distance_Han2014Improved(image_data[index], pels[index]))
+ --segmentation_map[index];
+ }
+ }
+
+ /* For swapping. */
+ model->lastHistoryImageSwapped = (model->lastHistoryImageSwapped + 1) % NUMBER_OF_HISTORY_IMAGES;
+ uint8_t *swappingImageBuffer = historyImage + (model->lastHistoryImageSwapped) * width * height;
+
+ /* Now, we move in the buffer and leave the historyImages. */
+ int numberOfTests = (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES);
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ if (segmentation_map[index] > 0) {
+ /* We need to check the full border and swap values with the first or second historyImage.
+ * We still need to find a match before we can stop our search.
+ */
+ uint32_t indexHistoryBuffer = index * numberOfTests;
+ uint8_t currentValue = image_data[index];
+
+ for (int i = numberOfTests; i > 0; --i, ++indexHistoryBuffer) {
+ // if (abs_uint(currentValue - historyBuffer[indexHistoryBuffer]) <= matchingThreshold) {
+ if (abs_uint(currentValue - historyBuffer[indexHistoryBuffer]) <= distance_Han2014Improved(currentValue, historyBuffer[indexHistoryBuffer])) {
+ --segmentation_map[index];
+
+ /* Swaping: Putting found value in history image buffer. */
+ uint8_t temp = swappingImageBuffer[index];
+ swappingImageBuffer[index] = historyBuffer[indexHistoryBuffer];
+ historyBuffer[indexHistoryBuffer] = temp;
+
+ /* Exit inner loop. */
+ if (segmentation_map[index] <= 0) break;
+ }
+ } // for
+ } // if
+ } // for
+
+ /* Produces the output. Note that this step is application-dependent. */
+ for (uint8_t *mask = segmentation_map; mask < segmentation_map + (width * height); ++mask)
+ if (*mask > 0) *mask = COLOR_FOREGROUND;
+
+ return(0);
+}
+
+// ----------------------------------------------------------------------------
+// Update a C1R model
+// ----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_Update_8u_C1R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *updating_mask
+) {
+ /* Basic checks . */
+ assert((image_data != NULL) && (model != NULL) && (updating_mask != NULL));
+ assert((model->width > 0) && (model->height > 0));
+ assert(model->historyBuffer != NULL);
+ assert((model->jump != NULL) && (model->neighbor != NULL) && (model->position != NULL));
+
+ /* Some variables. */
+ uint32_t width = model->width;
+ uint32_t height = model->height;
+
+ uint8_t *historyImage = model->historyImage;
+ uint8_t *historyBuffer = model->historyBuffer;
+
+ /* Some utility variable. */
+ int numberOfTests = (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES);
+
+ /* Updating. */
+ uint32_t *jump = model->jump;
+ int *neighbor = model->neighbor;
+ uint32_t *position = model->position;
+
+ /* All the frame, except the border. */
+ uint32_t shift, indX, indY;
+ int x, y;
+
+ for (y = 1; y < height - 1; ++y) {
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX < width - 1) {
+ int index = indX + y * width;
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ /* In-place substitution. */
+ uint8_t value = image_data[index];
+ int index_neighbor = index + neighbor[shift];
+
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[index + position[shift] * width * height] = value;
+ historyImage[index_neighbor + position[shift] * width * height] = value;
+ }
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[index * numberOfTests + pos] = value;
+ historyBuffer[index_neighbor * numberOfTests + pos] = value;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+ }
+
+ /* First row. */
+ y = 0;
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX <= width - 1) {
+ int index = indX + y * width;
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES)
+ historyImage[index + position[shift] * width * height] = image_data[index];
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[index * numberOfTests + pos] = image_data[index];
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+
+ /* Last row. */
+ y = height - 1;
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX <= width - 1) {
+ int index = indX + y * width;
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES)
+ historyImage[index + position[shift] * width * height] = image_data[index];
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[index * numberOfTests + pos] = image_data[index];
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+
+ /* First column. */
+ x = 0;
+ shift = rand() % height;
+ indY = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indY <= height - 1) {
+ int index = x + indY * width;
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES)
+ historyImage[index + position[shift] * width * height] = image_data[index];
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[index * numberOfTests + pos] = image_data[index];
+ }
+ }
+
+ ++shift;
+ indY += jump[shift];
+ }
+
+ /* Last column. */
+ x = width - 1;
+ shift = rand() % height;
+ indY = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indY <= height - 1) {
+ int index = x + indY * width;
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES)
+ historyImage[index + position[shift] * width * height] = image_data[index];
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[index * numberOfTests + pos] = image_data[index];
+ }
+ }
+
+ ++shift;
+ indY += jump[shift];
+ }
+
+ /* The first pixel! */
+ if (rand() % model->updateFactor == 0) {
+ if (updating_mask[0] == 0) {
+ int position = rand() % model->numberOfSamples;
+
+ if (position < NUMBER_OF_HISTORY_IMAGES)
+ historyImage[position * width * height] = image_data[0];
+ else {
+ int pos = position - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[pos] = image_data[0];
+ }
+ }
+ }
+
+ return(0);
+}
+
+// ----------------------------------------------------------------------------
+// -------------------------- The same for C3R models -------------------------
+// ----------------------------------------------------------------------------
+
+// -----------------------------------------------------------------------------
+// Allocates and initializes a C3R model structure
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_AllocInit_8u_C3R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height
+) {
+ /* Some basic checks. */
+ assert((image_data != NULL) && (model != NULL));
+ assert((width > 0) && (height > 0));
+
+ /* Finish model alloc - parameters values cannot be changed anymore. */
+ model->width = width;
+ model->height = height;
+
+ /* Creates the historyImage structure. */
+ model->historyImage = NULL;
+ model->historyImage = (uint8_t*)malloc(NUMBER_OF_HISTORY_IMAGES * (3 * width) * height * sizeof(uint8_t));
+ assert(model->historyImage != NULL);
+
+ for (int i = 0; i < NUMBER_OF_HISTORY_IMAGES; ++i) {
+ for (int index = (3 * width) * height - 1; index >= 0; --index)
+ model->historyImage[i * (3 * width) * height + index] = image_data[index];
+ }
+
+ assert(model->historyImage != NULL);
+
+ /* Now creates and fills the history buffer. */
+ model->historyBuffer = (uint8_t *)malloc((3 * width) * height * (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES) * sizeof(uint8_t));
+ assert(model->historyBuffer != NULL);
+
+ for (int index = (3 * width) * height - 1; index >= 0; --index) {
+ uint8_t value = image_data[index];
+
+ for (int x = 0; x < model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES; ++x) {
+ int value_plus_noise = value + rand() % 20 - 10;
+
+ if (value_plus_noise < 0) { value_plus_noise = 0; }
+ if (value_plus_noise > 255) { value_plus_noise = 255; }
+
+ model->historyBuffer[index * (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES) + x] = value_plus_noise;
+ }
+ }
+
+ /* Fills the buffers with random values. */
+ int size = (width > height) ? 2 * width + 1 : 2 * height + 1;
+
+ model->jump = (uint32_t*)malloc(size * sizeof(*(model->jump)));
+ assert(model->jump != NULL);
+
+ model->neighbor = (int*)malloc(size * sizeof(*(model->neighbor)));
+ assert(model->neighbor != NULL);
+
+ model->position = (uint32_t*)malloc(size * sizeof(*(model->position)));
+ assert(model->position != NULL);
+
+ for (int i = 0; i < size; ++i) {
+ model->jump[i] = (rand() % (2 * model->updateFactor)) + 1; // Values between 1 and 2 * updateFactor.
+ model->neighbor[i] = ((rand() % 3) - 1) + ((rand() % 3) - 1) * width; // Values between { width - 1, ... , width + 1 }.
+ model->position[i] = rand() % (model->numberOfSamples); // Values between 0 and numberOfSamples - 1.
+ }
+
+ return(0);
+}
+
+// -----------------------------------------------------------------------------
+// Segmentation of a C3R model
+// -----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_Segmentation_8u_C3R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map
+) {
+ /* Basic checks. */
+ assert((image_data != NULL) && (model != NULL) && (segmentation_map != NULL));
+ assert((model->width > 0) && (model->height > 0));
+ assert(model->historyBuffer != NULL);
+ assert((model->jump != NULL) && (model->neighbor != NULL) && (model->position != NULL));
+
+ /* Some variables. */
+ uint32_t width = model->width;
+ uint32_t height = model->height;
+ uint32_t matchingNumber = model->matchingNumber;
+ uint32_t matchingThreshold = model->matchingThreshold;
+
+ uint8_t *historyImage = model->historyImage;
+ uint8_t *historyBuffer = model->historyBuffer;
+
+ /* Segmentation. */
+ memset(segmentation_map, matchingNumber - 1, width * height);
+
+ /* First history Image structure. */
+ uint8_t *first = historyImage;
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ if (
+ !distance_is_close_8u_C3R(
+ image_data[3 * index], image_data[3 * index + 1], image_data[3 * index + 2],
+ first[3 * index], first[3 * index + 1], first[3 * index + 2], matchingThreshold
+ )
+ )
+ segmentation_map[index] = matchingNumber;
+ }
+
+ /* Next historyImages. */
+ for (int i = 1; i < NUMBER_OF_HISTORY_IMAGES; ++i) {
+ uint8_t *pels = historyImage + i * (3 * width) * height;
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ if (
+ distance_is_close_8u_C3R(
+ image_data[3 * index], image_data[3 * index + 1], image_data[3 * index + 2],
+ pels[3 * index], pels[3 * index + 1], pels[3 * index + 2], matchingThreshold
+ )
+ )
+ --segmentation_map[index];
+ }
+ }
+
+ // For swapping
+ model->lastHistoryImageSwapped = (model->lastHistoryImageSwapped + 1) % NUMBER_OF_HISTORY_IMAGES;
+ uint8_t *swappingImageBuffer = historyImage + (model->lastHistoryImageSwapped) * (3 * width) * height;
+
+ // Now, we move in the buffer and leave the historyImages
+ int numberOfTests = (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES);
+
+ for (int index = width * height - 1; index >= 0; --index) {
+ if (segmentation_map[index] > 0) {
+ /* We need to check the full border and swap values with the first or second historyImage.
+ * We still need to find a match before we can stop our search.
+ */
+ uint32_t indexHistoryBuffer = (3 * index) * numberOfTests;
+
+ for (int i = numberOfTests; i > 0; --i, indexHistoryBuffer += 3) {
+ if (
+ distance_is_close_8u_C3R(
+ image_data[(3 * index)], image_data[(3 * index) + 1], image_data[(3 * index) + 2],
+ historyBuffer[indexHistoryBuffer], historyBuffer[indexHistoryBuffer + 1], historyBuffer[indexHistoryBuffer + 2],
+ matchingThreshold
+ )
+ )
+ --segmentation_map[index];
+
+ /* Swaping: Putting found value in history image buffer. */
+ uint8_t temp_r = swappingImageBuffer[(3 * index)];
+ uint8_t temp_g = swappingImageBuffer[(3 * index) + 1];
+ uint8_t temp_b = swappingImageBuffer[(3 * index) + 2];
+
+ swappingImageBuffer[(3 * index)] = historyBuffer[indexHistoryBuffer];
+ swappingImageBuffer[(3 * index) + 1] = historyBuffer[indexHistoryBuffer + 1];
+ swappingImageBuffer[(3 * index) + 2] = historyBuffer[indexHistoryBuffer + 2];
+
+ historyBuffer[indexHistoryBuffer] = temp_r;
+ historyBuffer[indexHistoryBuffer + 1] = temp_g;
+ historyBuffer[indexHistoryBuffer + 2] = temp_b;
+
+ /* Exit inner loop. */
+ if (segmentation_map[index] <= 0) break;
+ } // for
+ } // if
+ } // for
+
+ /* Produces the output. Note that this step is application-dependent. */
+ for (uint8_t *mask = segmentation_map; mask < segmentation_map + (width * height); ++mask)
+ if (*mask > 0) *mask = COLOR_FOREGROUND;
+
+ return(0);
+}
+
+// ----------------------------------------------------------------------------
+// Update a C3R model
+// ----------------------------------------------------------------------------
+int32_t libvibeModel_Sequential_Update_8u_C3R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *updating_mask
+) {
+ /* Basic checks. */
+ assert((image_data != NULL) && (model != NULL) && (updating_mask != NULL));
+ assert((model->width > 0) && (model->height > 0));
+ assert(model->historyBuffer != NULL);
+ assert((model->jump != NULL) && (model->neighbor != NULL) && (model->position != NULL));
+
+ /* Some variables. */
+ uint32_t width = model->width;
+ uint32_t height = model->height;
+
+ uint8_t *historyImage = model->historyImage;
+ uint8_t *historyBuffer = model->historyBuffer;
+
+ /* Some utility variable. */
+ int numberOfTests = (model->numberOfSamples - NUMBER_OF_HISTORY_IMAGES);
+
+ /* Updating. */
+ uint32_t *jump = model->jump;
+ int *neighbor = model->neighbor;
+ uint32_t *position = model->position;
+
+ /* All the frame, except the border. */
+ uint32_t shift, indX, indY;
+ int x, y;
+
+ for (y = 1; y < height - 1; ++y) {
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX < width - 1) {
+ int index = indX + y * width;
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ /* In-place substitution. */
+ uint8_t r = image_data[3 * index];
+ uint8_t g = image_data[3 * index + 1];
+ uint8_t b = image_data[3 * index + 2];
+
+ int index_neighbor = 3 * (index + neighbor[shift]);
+
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[3 * index + position[shift] * (3 * width) * height] = r;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 1] = g;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 2] = b;
+
+ historyImage[index_neighbor + position[shift] * (3 * width) * height] = r;
+ historyImage[index_neighbor + position[shift] * (3 * width) * height + 1] = g;
+ historyImage[index_neighbor + position[shift] * (3 * width) * height + 2] = r;
+ }
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos] = r;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 1] = g;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 2] = b;
+
+ historyBuffer[index_neighbor * numberOfTests + 3 * pos] = r;
+ historyBuffer[index_neighbor * numberOfTests + 3 * pos + 1] = g;
+ historyBuffer[index_neighbor * numberOfTests + 3 * pos + 2] = b;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+ }
+
+ /* First row. */
+ y = 0;
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX <= width - 1) {
+ int index = indX + y * width;
+
+ uint8_t r = image_data[3 * index];
+ uint8_t g = image_data[3 * index + 1];
+ uint8_t b = image_data[3 * index + 2];
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[3 * index + position[shift] * (3 * width) * height] = r;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 1] = g;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 2] = b;
+ }
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos] = r;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 1] = g;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 2] = b;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+
+ /* Last row. */
+ y = height - 1;
+ shift = rand() % width;
+ indX = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indX <= width - 1) {
+ int index = indX + y * width;
+
+ uint8_t r = image_data[3 * index];
+ uint8_t g = image_data[3 * index + 1];
+ uint8_t b = image_data[3 * index + 2];
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[3 * index + position[shift] * (3 * width) * height] = r;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 1] = g;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 2] = b;
+ }
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos] = r;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 1] = g;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 2] = b;
+ }
+ }
+
+ ++shift;
+ indX += jump[shift];
+ }
+
+ /* First column. */
+ x = 0;
+ shift = rand() % height;
+ indY = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indY <= height - 1) {
+ int index = x + indY * width;
+
+ uint8_t r = image_data[3 * index];
+ uint8_t g = image_data[3 * index + 1];
+ uint8_t b = image_data[3 * index + 2];
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[3 * index + position[shift] * (3 * width) * height] = r;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 1] = g;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 2] = b;
+ }
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos] = r;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 1] = g;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 2] = b;
+ }
+ }
+
+ ++shift;
+ indY += jump[shift];
+ }
+
+ /* Last column. */
+ x = width - 1;
+ shift = rand() % height;
+ indY = jump[shift]; // index_jump should never be zero (> 1).
+
+ while (indY <= height - 1) {
+ int index = x + indY * width;
+
+ uint8_t r = image_data[3 * index];
+ uint8_t g = image_data[3 * index + 1];
+ uint8_t b = image_data[3 * index + 2];
+
+ if (updating_mask[index] == COLOR_BACKGROUND) {
+ if (position[shift] < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[3 * index + position[shift] * (3 * width) * height] = r;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 1] = g;
+ historyImage[3 * index + position[shift] * (3 * width) * height + 2] = b;
+ }
+ else {
+ int pos = position[shift] - NUMBER_OF_HISTORY_IMAGES;
+
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos] = r;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 1] = g;
+ historyBuffer[(3 * index) * numberOfTests + 3 * pos + 2] = b;
+ }
+ }
+
+ ++shift;
+ indY += jump[shift];
+ }
+
+ /* The first pixel! */
+ if (rand() % model->updateFactor == 0) {
+ if (updating_mask[0] == 0) {
+ int position = rand() % model->numberOfSamples;
+
+ uint8_t r = image_data[0];
+ uint8_t g = image_data[1];
+ uint8_t b = image_data[2];
+
+ if (position < NUMBER_OF_HISTORY_IMAGES) {
+ historyImage[position * (3 * width) * height] = r;
+ historyImage[position * (3 * width) * height + 1] = g;
+ historyImage[position * (3 * width) * height + 2] = b;
+ }
+ else {
+ int pos = position - NUMBER_OF_HISTORY_IMAGES;
+
+ historyBuffer[3 * pos] = r;
+ historyBuffer[3 * pos + 1] = g;
+ historyBuffer[3 * pos + 2] = b;
+ }
+ }
+ }
+
+ return(0);
+}
diff --git a/package_bgs/ViBe/vibe-background-sequential.h b/package_bgs/ViBe/vibe-background-sequential.h
new file mode 100644
index 0000000..068c7d1
--- /dev/null
+++ b/package_bgs/ViBe/vibe-background-sequential.h
@@ -0,0 +1,293 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+/**
+ @file vibe-background-sequential.h
+ @brief Interface for the ViBe library
+ @author Marc Van Droogenbroeck
+ @date July 2014
+ @details
+
+ Full documentation is available online at:
+ http://www.ulg.ac.be/telecom/research/vibe/doc
+
+ All technical details are available in the following paper:
+<em>O. Barnich and M. Van Droogenbroeck. ViBe: A universal background subtraction algorithm for video sequences. IEEE Transactions on Image Processing, 20(6):1709-1724, June 2011.</em>
+
+\verbatim
+BiBTeX information
+
+ @article{Barnich2011ViBe,
+ title = {{ViBe}: A universal background subtraction algorithm for video sequences},
+ author = {O. Barnich and M. {Van Droogenbroeck}},
+ journal = {IEEE Transactions on Image Processing},
+ volume = {20},
+ number = {6},
+ pages = {1709-1724},
+ month = {June},
+ year = {2011},
+ keywords = {ViBe, Background, Background subtraction, Segmentation, Motion, Motion detection},
+ pdf = {http://orbi.ulg.ac.be/bitstream/2268/145853/1/Barnich2011ViBe.pdf},
+ doi = {10.1109/TIP.2010.2101613},
+ url = {http://hdl.handle.net/2268/145853}
+ }
+\endverbatim
+See
+\cite Barnich2011ViBe
+*/
+#pragma once
+
+#include <stdlib.h>
+#include <stdint.h>
+#include <stdio.h>
+#include <string.h>
+
+#define COLOR_BACKGROUND 0 /*!< Default label for background pixels */
+#define COLOR_FOREGROUND 255 /*!< Default label for foreground pixels. Note that some authors chose any value different from 0 instead */
+
+/**
+ * \typedef struct vibeModel_Sequential_t
+ * \brief Data structure for the background subtraction model.
+ *
+ * This data structure contains the background model as well as some paramaters value.
+ * The code is designed to hide all the implementation details to the user to ease its use.
+ */
+typedef struct vibeModel_Sequential vibeModel_Sequential_t;
+
+/**
+ * Allocation of a new data structure where the background model will be stored.
+ * Please note that this function only creates the structure to host the data.
+ * This data structures will only be filled with a call to \ref libvibeModel_Sequential_AllocInit_8u_C1R.
+ *
+ * \result A pointer to a newly allocated \ref vibeModel_Sequential_t
+ * structure, or <tt>NULL</tt> in the case of an error.
+ */
+vibeModel_Sequential_t *libvibeModel_Sequential_New();
+
+/**
+ * ViBe uses several parameters.
+ * You can print and change some of them if you want. However, default
+ * value should meet your needs for most videos.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @return
+ */
+uint32_t libvibeModel_Sequential_PrintParameters(const vibeModel_Sequential_t *model);
+
+/**
+ * Setter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param numberOfSamples
+ * @return
+ */
+int32_t libvibeModel_Sequential_SetNumberOfSamples(
+ vibeModel_Sequential_t *model,
+ const uint32_t numberOfSamples
+);
+
+/**
+ * Setter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @return
+ */
+uint32_t libvibeModel_Sequential_GetNumberOfSamples(const vibeModel_Sequential_t *model);
+
+/**
+ * Setter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param matchingThreshold
+ * @return
+ */
+int32_t libvibeModel_Sequential_SetMatchingThreshold(
+ vibeModel_Sequential_t *model,
+ const uint32_t matchingThreshold
+);
+
+/**
+ * Setter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @return
+ */
+uint32_t libvibeModel_Sequential_GetMatchingThreshold(const vibeModel_Sequential_t *model);
+
+/**
+ * Setter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param matchingNumber
+ * @return
+ */
+int32_t libvibeModel_Sequential_SetMatchingNumber(
+ vibeModel_Sequential_t *model,
+ const uint32_t matchingNumber
+);
+
+/**
+ * Setter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param updateFactor New value for the update factor. Please note that the update factor is to be understood as a probability of updating. More specifically, an update factor of 16 means that 1 out of every 16 background pixels is updated. Likewise, an update factor of 1 means that every background pixel is updated.
+ * @return
+ */
+int32_t libvibeModel_Sequential_SetUpdateFactor(
+ vibeModel_Sequential_t *model,
+ const uint32_t updateFactor
+);
+
+/**
+ * Getter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @return
+ */
+uint32_t libvibeModel_Sequential_GetMatchingNumber(const vibeModel_Sequential_t *model);
+
+
+/**
+ * Getter.
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @return
+ */
+uint32_t libvibeModel_Sequential_GetUpdateFactor(const vibeModel_Sequential_t *model);
+
+/**
+ * \brief Frees all the memory used by the <tt>model</tt> and deallocates the structure.
+ *
+ * This function frees all the memory allocated by \ref libvibeModel_SequentialNew and
+ * \ref libvibeModel_Sequential_AllocInit_8u_C1R or \ref libvibeModel_Sequential_AllocInit_8u_C3R.
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @return
+ */
+int32_t libvibeModel_Sequential_Free(vibeModel_Sequential_t *model);
+
+/**
+ * The two following functions allocate the required memory according to the
+ * model parameters and the dimensions of the input images.
+ * You must use the "C1R" function for grayscale images and the "C3R" for color
+ * images.
+ * These 2 functions also initialize the background model using the content
+ * of *image_data which is the pixel buffer of the first image of your stream.
+ */
+ // ------------------------- Single channel images ----------------------------
+ /**
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param image_data
+ * @param width
+ * @param height
+ * @return
+ */
+int32_t libvibeModel_Sequential_AllocInit_8u_C1R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height
+);
+
+/* These 2 functions perform 2 operations:
+ * - they classify the pixels *image_data using the provided model and store
+ * the results in *segmentation_map.
+ * - they update *model according to these results and the content of
+ * *image_data.
+ * You must use the "C1R" function for grayscale images and the "C3R" for color
+ * images.
+ */
+ /**
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param image_data
+ * @param segmentation_map
+ * @return
+ */
+int32_t libvibeModel_Sequential_Segmentation_8u_C1R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map
+);
+
+/**
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param image_data
+ * @param updating_mask
+ * @return
+ */
+int32_t libvibeModel_Sequential_Update_8u_C1R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *updating_mask
+);
+
+// ------------------------- Three channel images -----------------------------
+/**
+ * The pixel values of color images are arranged in the following order
+ * RGBRGBRGB... (or HSVHSVHSVHSVHSVHSV...)
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param image_data
+ * @param width
+ * @param height
+ * @return
+ */
+int32_t libvibeModel_Sequential_AllocInit_8u_C3R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height
+);
+
+/* These 2 functions perform 2 operations:
+ * - they classify the pixels *image_data using the provided model and store
+ * the results in *segmentation_map.
+ * - they update *model according to these results and the content of
+ * *image_data.
+ * You must use the "C1R" function for grayscale images and the "C3R" for color
+ * images.
+ */
+ /**
+ * The pixel values of color images are arranged in the following order
+ * RGBRGBRGB... (or HSVHSVHSVHSVHSVHSV...)
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param image_data
+ * @param segmentation_map
+ * @return
+ */
+int32_t libvibeModel_Sequential_Segmentation_8u_C3R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map
+);
+
+/**
+ * The pixel values of color images are arranged in the following order
+ * RGBRGBRGB... (or HSVHSVHSVHSVHSVHSV...)
+ *
+ * @param model The data structure with ViBe's background subtraction model and parameters.
+ * @param image_data
+ * @param updating_mask
+ * @return
+ */
+int32_t libvibeModel_Sequential_Update_8u_C3R(
+ vibeModel_Sequential_t *model,
+ const uint8_t *image_data,
+ uint8_t *updating_mask
+);
diff --git a/package_bgs/av/VuMeter.cpp b/package_bgs/VuMeter.cpp
similarity index 52%
rename from package_bgs/av/VuMeter.cpp
rename to package_bgs/VuMeter.cpp
index 29a1477..99baee9 100644
--- a/package_bgs/av/VuMeter.cpp
+++ b/package_bgs/VuMeter.cpp
@@ -16,9 +16,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "VuMeter.h"
-VuMeter::VuMeter() : firstTime(true), showOutput(true), enableFilter(true), binSize(8), alpha(0.995), threshold(0.03)
+using namespace bgslibrary::algorithms;
+
+VuMeter::VuMeter() :
+ enableFilter(true), binSize(8), alpha(0.995), threshold(0.03)
{
std::cout << "VuMeter()" << std::endl;
+ setup("./config/VuMeter.xml");
}
VuMeter::~VuMeter()
@@ -32,69 +36,62 @@ VuMeter::~VuMeter()
void VuMeter::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
- else
- frame = new IplImage(img_input);
-
- loadConfig();
+ init(img_input, img_output, img_bgmodel);
+ frame = new IplImage(img_input);
- if(firstTime)
+ if (firstTime)
{
bgs.SetAlpha(alpha);
bgs.SetBinSize(binSize);
bgs.SetThreshold(threshold);
- gray = cvCreateImage(cvGetSize(frame),IPL_DEPTH_8U,1);
- cvCvtColor(frame,gray,CV_RGB2GRAY);
+ gray = cvCreateImage(cvGetSize(frame), IPL_DEPTH_8U, 1);
+ cvCvtColor(frame, gray, CV_RGB2GRAY);
- background = cvCreateImage(cvGetSize(gray),IPL_DEPTH_8U,1);
+ background = cvCreateImage(cvGetSize(gray), IPL_DEPTH_8U, 1);
cvCopy(gray, background);
- mask = cvCreateImage(cvGetSize(gray),IPL_DEPTH_8U,1);
+ mask = cvCreateImage(cvGetSize(gray), IPL_DEPTH_8U, 1);
cvZero(mask);
-
- saveConfig();
}
else
- cvCvtColor(frame,gray,CV_RGB2GRAY);
-
- bgs.UpdateBackground(gray,background,mask);
- cv::Mat img_foreground(mask);
- cv::Mat img_bkg(background);
+ cvCvtColor(frame, gray, CV_RGB2GRAY);
+
+ bgs.UpdateBackground(gray, background, mask);
+ img_foreground = cv::cvarrToMat(mask);
+ img_background = cv::cvarrToMat(background);
- if(enableFilter)
+ if (enableFilter)
{
- cv::erode(img_foreground,img_foreground,cv::Mat());
+ cv::erode(img_foreground, img_foreground, cv::Mat());
cv::medianBlur(img_foreground, img_foreground, 5);
}
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
{
- if(!img_foreground.empty())
- cv::imshow("VuMeter", img_foreground);
-
- if(!img_bkg.empty())
- cv::imshow("VuMeter Bkg Model", img_bkg);
+ cv::imshow("VuMeter", img_foreground);
+ cv::imshow("VuMeter Bkg Model", img_background);
}
+#endif
img_foreground.copyTo(img_output);
- img_bkg.copyTo(img_bgmodel);
-
+ img_background.copyTo(img_bgmodel);
+
delete frame;
firstTime = false;
}
void VuMeter::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/VuMeter.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "enableFilter", enableFilter);
-
+
cvWriteInt(fs, "binSize", binSize);
cvWriteReal(fs, "alpha", alpha);
cvWriteReal(fs, "threshold", threshold);
-
+
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
@@ -102,15 +99,15 @@ void VuMeter::saveConfig()
void VuMeter::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/VuMeter.xml", 0, CV_STORAGE_READ);
-
- enableFilter = cvReadIntByName(fs, 0, "enableFilter", true);
-
- binSize = cvReadIntByName(fs, 0, "binSize", 8);
- alpha = cvReadRealByName(fs, 0, "alpha", 0.995);
- threshold = cvReadRealByName(fs, 0, "threshold", 0.03);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ enableFilter = cvReadIntByName(fs, nullptr, "enableFilter", true);
+
+ binSize = cvReadIntByName(fs, nullptr, "binSize", 8);
+ alpha = cvReadRealByName(fs, nullptr, "alpha", 0.995);
+ threshold = cvReadRealByName(fs, nullptr, "threshold", 0.03);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/VuMeter.h b/package_bgs/VuMeter.h
new file mode 100644
index 0000000..fefd3ec
--- /dev/null
+++ b/package_bgs/VuMeter.h
@@ -0,0 +1,52 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+#include "VuMeter/TBackgroundVuMeter.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class VuMeter : public IBGS
+ {
+ private:
+ TBackgroundVuMeter bgs;
+
+ IplImage *frame;
+ IplImage *gray;
+ IplImage *background;
+ IplImage *mask;
+
+ bool enableFilter;
+ int binSize;
+ double alpha;
+ double threshold;
+
+ public:
+ VuMeter();
+ ~VuMeter();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/av/TBackground.cpp b/package_bgs/VuMeter/TBackground.cpp
similarity index 77%
rename from package_bgs/av/TBackground.cpp
rename to package_bgs/VuMeter/TBackground.cpp
index d05bbd2..4e93729 100644
--- a/package_bgs/av/TBackground.cpp
+++ b/package_bgs/VuMeter/TBackground.cpp
@@ -72,19 +72,19 @@ bool TBackground::isInitOk(IplImage * pSource, IplImage *pBackground, IplImage *
{
bool bResult = true;
- if(pSource == NULL || pSource->nChannels != 1 || pSource->depth != IPL_DEPTH_8U)
+ if (pSource == NULL || pSource->nChannels != 1 || pSource->depth != IPL_DEPTH_8U)
bResult = false;
- if(bResult)
+ if (bResult)
{
int nbl, nbc;
nbl = pSource->height;
nbc = pSource->width;
-
- if(pBackground == NULL || pBackground->width != nbc || pBackground->height != nbl || pBackground->imageSize != pSource->imageSize)
+
+ if (pBackground == NULL || pBackground->width != nbc || pBackground->height != nbl || pBackground->imageSize != pSource->imageSize)
bResult = false;
-
- if(pMotionMask == NULL || pMotionMask->width != nbc || pMotionMask->height != nbl || pMotionMask->imageSize != pSource->imageSize)
+
+ if (pMotionMask == NULL || pMotionMask->width != nbc || pMotionMask->height != nbl || pMotionMask->imageSize != pSource->imageSize)
bResult = false;
}
@@ -100,7 +100,7 @@ IplImage *TBackground::CreateTestImg()
{
IplImage *pImage = cvCreateImage(cvSize(256, 256), IPL_DEPTH_8U, 3);
- if(pImage != NULL)
+ if (pImage != NULL)
cvSetZero(pImage);
return pImage;
@@ -112,33 +112,33 @@ int TBackground::UpdateTest(IplImage *pSource, IplImage *pBackground, IplImage *
CvScalar Color;
unsigned char *ptr;
- if(pTest == NULL || !isInitOk(pSource, pBackground, pSource))
+ if (pTest == NULL || !isInitOk(pSource, pBackground, pSource))
nErr = 1;
- if(!nErr)
+ if (!nErr)
{
- if(pTest->width != 256 || pTest->height != 256 || pTest->nChannels != 3)
+ if (pTest->width != 256 || pTest->height != 256 || pTest->nChannels != 3)
nErr = 1;
- if(nX < 0 || nX > pSource->width || nY < 0 || nY > pSource->height)
+ if (nX < 0 || nX > pSource->width || nY < 0 || nY > pSource->height)
nErr = 1;
- switch(nInd)
+ switch (nInd)
{
- case 0 : Color = cvScalar(128, 0, 0); break;
- case 1 : Color = cvScalar(0, 128, 0); break;
- case 2 : Color = cvScalar(0, 0, 128); break;
- default : nErr = 1;
+ case 0: Color = cvScalar(128, 0, 0); break;
+ case 1: Color = cvScalar(0, 128, 0); break;
+ case 2: Color = cvScalar(0, 0, 128); break;
+ default: nErr = 1;
}
}
- if(!nErr)
+ if (!nErr)
{
int l, c;
// recupere l'indice de la colonne
ptr = (unsigned char *)(pTest->imageData);
c = *ptr;
-
+
// efface la colonne
cvLine(pTest, cvPoint(c, 0), cvPoint(c, 255), cvScalar(0));
*ptr += 1;
diff --git a/package_bgs/av/TBackground.h b/package_bgs/VuMeter/TBackground.h
similarity index 99%
rename from package_bgs/av/TBackground.h
rename to package_bgs/VuMeter/TBackground.h
index 463063f..dbaaa6c 100644
--- a/package_bgs/av/TBackground.h
+++ b/package_bgs/VuMeter/TBackground.h
@@ -26,7 +26,6 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
#include <iostream>
#include <opencv2/opencv.hpp>
-
class TBackground
{
public:
diff --git a/package_bgs/av/TBackgroundVuMeter.cpp b/package_bgs/VuMeter/TBackgroundVuMeter.cpp
similarity index 74%
rename from package_bgs/av/TBackgroundVuMeter.cpp
rename to package_bgs/VuMeter/TBackgroundVuMeter.cpp
index 7fade7a..c4fd7a7 100644
--- a/package_bgs/av/TBackgroundVuMeter.cpp
+++ b/package_bgs/VuMeter/TBackgroundVuMeter.cpp
@@ -46,11 +46,11 @@ void TBackgroundVuMeter::Clear(void)
{
TBackground::Clear();
- if(m_pHist != NULL)
+ if (m_pHist != NULL)
{
- for(int i = 0; i < m_nBinCount; ++i)
+ for (int i = 0; i < m_nBinCount; ++i)
{
- if(m_pHist[i] != NULL)
+ if (m_pHist[i] != NULL)
cvReleaseImage(&m_pHist[i]);
}
@@ -68,14 +68,14 @@ void TBackgroundVuMeter::Reset(void)
TBackground::Reset();
- if(m_pHist != NULL)
+ if (m_pHist != NULL)
{
// fVal = (m_nBinCount != 0) ? (float)(1.0 / (double)m_nBinCount) : (float)0.0;
fVal = 0.0;
- for(int i = 0; i < m_nBinCount; ++i)
+ for (int i = 0; i < m_nBinCount; ++i)
{
- if(m_pHist[i] != NULL)
+ if (m_pHist[i] != NULL)
{
cvSetZero(m_pHist[i]);
cvAddS(m_pHist[i], cvScalar(fVal), m_pHist[i]);
@@ -98,18 +98,18 @@ std::string TBackgroundVuMeter::GetParameterName(int nInd)
nNb = TBackground::GetParameterCount();
- if(nInd >= nNb)
+ if (nInd >= nNb)
{
nInd -= nNb;
- switch(nInd)
+ switch (nInd)
{
- case 0 : csResult = "Bin size"; break;
- case 1 : csResult = "Alpha"; break;
- case 2 : csResult = "Threshold"; break;
+ case 0: csResult = "Bin size"; break;
+ case 1: csResult = "Alpha"; break;
+ case 2: csResult = "Threshold"; break;
}
}
- else
+ else
csResult = TBackground::GetParameterName(nInd);
return csResult;
@@ -122,22 +122,22 @@ std::string TBackgroundVuMeter::GetParameterValue(int nInd)
nNb = TBackground::GetParameterCount();
- if(nInd >= nNb)
+ if (nInd >= nNb)
{
nInd -= nNb;
char buff[100];
-
- switch(nInd)
+
+ switch (nInd)
{
- case 0 : sprintf(buff, "%d", m_nBinSize); break;
- case 1 : sprintf(buff, "%.3f", m_fAlpha); break;
- case 2 : sprintf(buff, "%.2f", m_fThreshold); break;
+ case 0: sprintf(buff, "%d", m_nBinSize); break;
+ case 1: sprintf(buff, "%.3f", m_fAlpha); break;
+ case 2: sprintf(buff, "%.2f", m_fThreshold); break;
}
csResult = buff;
}
- else
+ else
csResult = TBackground::GetParameterValue(nInd);
return csResult;
@@ -151,19 +151,19 @@ int TBackgroundVuMeter::SetParameterValue(int nInd, std::string csNew)
nNb = TBackground::GetParameterCount();
- if(nInd >= nNb)
+ if (nInd >= nNb)
{
nInd -= nNb;
- switch(nInd)
+ switch (nInd)
{
- case 0 : SetBinSize(atoi(csNew.c_str())); break;
- case 1 : SetAlpha(atof(csNew.c_str())); break;
- case 2 : SetThreshold(atof(csNew.c_str())); break;
- default : nErr = 1;
+ case 0: SetBinSize(atoi(csNew.c_str())); break;
+ case 1: SetAlpha(atof(csNew.c_str())); break;
+ case 2: SetThreshold(atof(csNew.c_str())); break;
+ default: nErr = 1;
}
}
- else
+ else
nErr = TBackground::SetParameterValue(nInd, csNew);
return nErr;
@@ -178,42 +178,42 @@ int TBackgroundVuMeter::Init(IplImage * pSource)
nErr = TBackground::Init(pSource);
- if(pSource == NULL)
+ if (pSource == NULL)
nErr = 1;
// calcul le nb de bin
- if(!nErr)
+ if (!nErr)
{
nbl = pSource->height;
nbc = pSource->width;
m_nBinCount = (m_nBinSize != 0) ? 256 / m_nBinSize : 0;
- if(m_nBinCount <= 0 || m_nBinCount > 256)
+ if (m_nBinCount <= 0 || m_nBinCount > 256)
nErr = 1;
}
// creation du tableau de pointeur
- if(!nErr)
+ if (!nErr)
{
m_pHist = new IplImage *[m_nBinCount];
- if(m_pHist == NULL)
+ if (m_pHist == NULL)
nErr = 1;
}
// creation des images
- if(!nErr)
+ if (!nErr)
{
- for(int i = 0; i < m_nBinCount; ++i)
+ for (int i = 0; i < m_nBinCount; ++i)
{
m_pHist[i] = cvCreateImage(cvSize(nbc, nbl), IPL_DEPTH_32F, 1);
- if(m_pHist[i] == NULL)
+ if (m_pHist[i] == NULL)
nErr = 1;
}
}
- if(!nErr)
+ if (!nErr)
Reset();
else
Clear();
@@ -228,28 +228,28 @@ bool TBackgroundVuMeter::isInitOk(IplImage * pSource, IplImage *pBackground, Ipl
bResult = TBackground::isInitOk(pSource, pBackground, pMotionMask);
- if(pSource == NULL)
+ if (pSource == NULL)
bResult = false;
- if(m_nBinSize == 0)
+ if (m_nBinSize == 0)
bResult = false;
- if(bResult)
+ if (bResult)
{
i = (m_nBinSize != 0) ? 256 / m_nBinSize : 0;
- if(i != m_nBinCount || m_pHist == NULL)
+ if (i != m_nBinCount || m_pHist == NULL)
bResult = false;
}
- if(bResult)
+ if (bResult)
{
int nbl = pSource->height;
int nbc = pSource->width;
- for(i = 0; i < m_nBinCount; ++i)
+ for (i = 0; i < m_nBinCount; ++i)
{
- if(m_pHist[i] == NULL || m_pHist[i]->width != nbc || m_pHist[i]->height != nbl)
+ if (m_pHist[i] == NULL || m_pHist[i]->width != nbc || m_pHist[i]->height != nbl)
bResult = false;
}
}
@@ -263,10 +263,10 @@ int TBackgroundVuMeter::UpdateBackground(IplImage *pSource, IplImage *pBackgroun
unsigned char *ptrs, *ptrb, *ptrm;
float *ptr1, *ptr2;
- if(!isInitOk(pSource, pBackground, pMotionMask))
+ if (!isInitOk(pSource, pBackground, pMotionMask))
nErr = Init(pSource);
-
- if(!nErr)
+
+ if (!nErr)
{
m_nCount++;
int nbc = pSource->width;
@@ -274,23 +274,23 @@ int TBackgroundVuMeter::UpdateBackground(IplImage *pSource, IplImage *pBackgroun
unsigned char v = m_nBinSize;
// multiplie tout par alpha
- for(int i = 0; i < m_nBinCount; ++i)
+ for (int i = 0; i < m_nBinCount; ++i)
cvConvertScale(m_pHist[i], m_pHist[i], m_fAlpha, 0.0);
- for(int l = 0; l < nbl; ++l)
+ for (int l = 0; l < nbl; ++l)
{
ptrs = (unsigned char *)(pSource->imageData + pSource->widthStep * l);
ptrm = (unsigned char *)(pMotionMask->imageData + pMotionMask->widthStep * l);
ptrb = (unsigned char *)(pBackground->imageData + pBackground->widthStep * l);
- for(int c = 0; c < nbc; ++c, ptrs++, ptrb++, ptrm++)
+ for (int c = 0; c < nbc; ++c, ptrs++, ptrb++, ptrm++)
{
- // recherche le bin � augmenter
+ // recherche le bin à augmenter
int i = *ptrs / v;
-
- if(i < 0 || i >= m_nBinCount)
+
+ if (i < 0 || i >= m_nBinCount)
i = 0;
-
+
ptr1 = (float *)(m_pHist[i]->imageData + m_pHist[i]->widthStep * l);
ptr1 += c;
@@ -299,19 +299,19 @@ int TBackgroundVuMeter::UpdateBackground(IplImage *pSource, IplImage *pBackgroun
// recherche le bin du fond actuel
i = *ptrb / v;
-
- if(i < 0 || i >= m_nBinCount)
+
+ if (i < 0 || i >= m_nBinCount)
i = 0;
-
+
ptr2 = (float *)(m_pHist[i]->imageData + m_pHist[i]->widthStep * l);
ptr2 += c;
- if(*ptr2 < *ptr1)
+ if (*ptr2 < *ptr1)
*ptrb = *ptrs;
}
}
- if(m_nCount < 5)
+ if (m_nCount < 5)
cvSetZero(pMotionMask);
}
@@ -322,10 +322,10 @@ IplImage *TBackgroundVuMeter::CreateTestImg()
{
IplImage *pImage = NULL;
- if(m_nBinCount > 0)
+ if (m_nBinCount > 0)
pImage = cvCreateImage(cvSize(m_nBinCount, 100), IPL_DEPTH_8U, 3);
- if(pImage != NULL)
+ if (pImage != NULL)
cvSetZero(pImage);
return pImage;
@@ -336,31 +336,31 @@ int TBackgroundVuMeter::UpdateTest(IplImage *pSource, IplImage *pBackground, Ipl
int nErr = 0;
float *ptrf;
- if(pTest == NULL || !isInitOk(pSource, pBackground, pSource))
+ if (pTest == NULL || !isInitOk(pSource, pBackground, pSource))
nErr = 1;
- if(!nErr)
+ if (!nErr)
{
int nbl = pTest->height;
int nbc = pTest->width;
- if(nbl != 100 || nbc != m_nBinCount)
+ if (nbl != 100 || nbc != m_nBinCount)
nErr = 1;
- if(nX < 0 || nX >= pSource->width || nY < 0 || nY >= pSource->height)
+ if (nX < 0 || nX >= pSource->width || nY < 0 || nY >= pSource->height)
nErr = 1;
}
- if(!nErr)
+ if (!nErr)
{
cvSetZero(pTest);
- for(int i = 0; i < m_nBinCount; ++i)
+ for (int i = 0; i < m_nBinCount; ++i)
{
ptrf = (float *)(m_pHist[i]->imageData + m_pHist[i]->widthStep * nY);
ptrf += nX;
- if(*ptrf >= 0 || *ptrf <= 1.0) {
+ if (*ptrf >= 0 || *ptrf <= 1.0) {
cvLine(pTest, cvPoint(i, 100), cvPoint(i, (int)(100.0 * (1.0 - *ptrf))), cvScalar(0, 255, 0));
}
}
diff --git a/package_bgs/av/TBackgroundVuMeter.h b/package_bgs/VuMeter/TBackgroundVuMeter.h
similarity index 95%
rename from package_bgs/av/TBackgroundVuMeter.h
rename to package_bgs/VuMeter/TBackgroundVuMeter.h
index 1a19324..36fe0d0 100644
--- a/package_bgs/av/TBackgroundVuMeter.h
+++ b/package_bgs/VuMeter/TBackgroundVuMeter.h
@@ -44,13 +44,13 @@ public:
virtual std::string GetParameterValue(int nInd);
virtual int SetParameterValue(int nInd, std::string csNew);
- inline void SetBinSize(int nNew) { m_nBinSize = (nNew > 0 && nNew < 255) ? nNew : 8; }
+ inline void SetBinSize(int nNew) { m_nBinSize = (nNew > 0 && nNew < 255) ? nNew : 8; }
inline double GetBinSize() { return m_nBinSize; }
- inline void SetAlpha(double fNew) { m_fAlpha = (fNew > 0.0 && fNew < 1.0) ? fNew : 0.995; }
+ inline void SetAlpha(double fNew) { m_fAlpha = (fNew > 0.0 && fNew < 1.0) ? fNew : 0.995; }
inline double GetAlpha() { return m_fAlpha; }
- inline void SetThreshold(double fNew) { m_fThreshold = (fNew > 0.0 && fNew < 1.0) ? fNew : 0.03; }
+ inline void SetThreshold(double fNew) { m_fThreshold = (fNew > 0.0 && fNew < 1.0) ? fNew : 0.03; }
inline double GetThreshold() { return m_fThreshold; }
protected:
diff --git a/package_bgs/WeightedMovingMeanBGS.cpp b/package_bgs/WeightedMovingMean.cpp
similarity index 51%
rename from package_bgs/WeightedMovingMeanBGS.cpp
rename to package_bgs/WeightedMovingMean.cpp
index 841c467..3a427fc 100644
--- a/package_bgs/WeightedMovingMeanBGS.cpp
+++ b/package_bgs/WeightedMovingMean.cpp
@@ -14,77 +14,72 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "WeightedMovingMeanBGS.h"
+#include "WeightedMovingMean.h"
-WeightedMovingMeanBGS::WeightedMovingMeanBGS() : firstTime(true), enableWeight(true), enableThreshold(true), threshold(15), showOutput(true), showBackground(false)
+using namespace bgslibrary::algorithms;
+
+WeightedMovingMean::WeightedMovingMean() :
+ enableWeight(true), enableThreshold(true), threshold(15)
{
- std::cout << "WeightedMovingMeanBGS()" << std::endl;
+ std::cout << "WeightedMovingMean()" << std::endl;
+ setup("./config/WeightedMovingMean.xml");
}
-WeightedMovingMeanBGS::~WeightedMovingMeanBGS()
+WeightedMovingMean::~WeightedMovingMean()
{
- std::cout << "~WeightedMovingMeanBGS()" << std::endl;
+ std::cout << "~WeightedMovingMean()" << std::endl;
}
-void WeightedMovingMeanBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void WeightedMovingMean::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
+ init(img_input, img_output, img_bgmodel);
- if(img_input_prev_1.empty())
- {
+ if (img_input_prev_1.empty()) {
img_input.copyTo(img_input_prev_1);
return;
}
- if(img_input_prev_2.empty())
- {
+ if (img_input_prev_2.empty()) {
img_input_prev_1.copyTo(img_input_prev_2);
img_input.copyTo(img_input_prev_1);
return;
}
-
+
cv::Mat img_input_f(img_input.size(), CV_32F);
- img_input.convertTo(img_input_f, CV_32F, 1./255.);
+ img_input.convertTo(img_input_f, CV_32F, 1. / 255.);
cv::Mat img_input_prev_1_f(img_input.size(), CV_32F);
- img_input_prev_1.convertTo(img_input_prev_1_f, CV_32F, 1./255.);
+ img_input_prev_1.convertTo(img_input_prev_1_f, CV_32F, 1. / 255.);
cv::Mat img_input_prev_2_f(img_input.size(), CV_32F);
- img_input_prev_2.convertTo(img_input_prev_2_f, CV_32F, 1./255.);
+ img_input_prev_2.convertTo(img_input_prev_2_f, CV_32F, 1. / 255.);
cv::Mat img_background_f(img_input.size(), CV_32F);
-
- if(enableWeight)
+
+ if (enableWeight)
img_background_f = ((img_input_f * 0.5) + (img_input_prev_1_f * 0.3) + (img_input_prev_2_f * 0.2));
else
- img_background_f = ((img_input_f) + (img_input_prev_1_f) + (img_input_prev_2_f)) / 3.0;
-
- cv::Mat img_background(img_background_f.size(), CV_8U);
+ img_background_f = ((img_input_f)+(img_input_prev_1_f)+(img_input_prev_2_f)) / 3.0;
double minVal, maxVal;
minVal = 0.; maxVal = 1.;
- img_background_f.convertTo(img_background, CV_8U, 255.0/(maxVal - minVal), -minVal);
-
- if(showBackground)
- cv::imshow("W Moving Mean BG Model", img_background);
+ img_background_f.convertTo(img_background, CV_8U, 255.0 / (maxVal - minVal), -minVal);
- cv::Mat img_foreground;
cv::absdiff(img_input, img_background, img_foreground);
- if(img_foreground.channels() == 3)
+ if (img_foreground.channels() == 3)
cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
- if(enableThreshold)
+ if (enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ {
cv::imshow("W Moving Mean FG Mask", img_foreground);
+ cv::imshow("W Moving Mean BG Model", img_background);
+ }
+#endif
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
@@ -95,28 +90,26 @@ void WeightedMovingMeanBGS::process(const cv::Mat &img_input, cv::Mat &img_outpu
firstTime = false;
}
-void WeightedMovingMeanBGS::saveConfig()
+void WeightedMovingMean::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/WeightedMovingMeanBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "enableWeight", enableWeight);
cvWriteInt(fs, "enableThreshold", enableThreshold);
cvWriteInt(fs, "threshold", threshold);
cvWriteInt(fs, "showOutput", showOutput);
- cvWriteInt(fs, "showBackground", showBackground);
cvReleaseFileStorage(&fs);
}
-void WeightedMovingMeanBGS::loadConfig()
+void WeightedMovingMean::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/WeightedMovingMeanBGS.xml", 0, CV_STORAGE_READ);
-
- enableWeight = cvReadIntByName(fs, 0, "enableWeight", true);
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
- showBackground = cvReadIntByName(fs, 0, "showBackground", false);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ enableWeight = cvReadIntByName(fs, nullptr, "enableWeight", true);
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
cvReleaseFileStorage(&fs);
-}
\ No newline at end of file
+}
diff --git a/package_bgs/WeightedMovingMean.h b/package_bgs/WeightedMovingMean.h
new file mode 100644
index 0000000..4a1a3c5
--- /dev/null
+++ b/package_bgs/WeightedMovingMean.h
@@ -0,0 +1,45 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class WeightedMovingMean : public IBGS
+ {
+ private:
+ cv::Mat img_input_prev_1;
+ cv::Mat img_input_prev_2;
+ bool enableWeight;
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ WeightedMovingMean();
+ ~WeightedMovingMean();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/WeightedMovingVarianceBGS.cpp b/package_bgs/WeightedMovingVariance.cpp
similarity index 62%
rename from package_bgs/WeightedMovingVarianceBGS.cpp
rename to package_bgs/WeightedMovingVariance.cpp
index 0317a3c..2855a92 100644
--- a/package_bgs/WeightedMovingVarianceBGS.cpp
+++ b/package_bgs/WeightedMovingVariance.cpp
@@ -14,68 +14,61 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-#include "WeightedMovingVarianceBGS.h"
+#include "WeightedMovingVariance.h"
-WeightedMovingVarianceBGS::WeightedMovingVarianceBGS() : firstTime(true), enableWeight(true),
- enableThreshold(true), threshold(15), showOutput(true)
+using namespace bgslibrary::algorithms;
+
+WeightedMovingVariance::WeightedMovingVariance() :
+ enableWeight(true), enableThreshold(true), threshold(15)
{
- std::cout << "WeightedMovingVarianceBGS()" << std::endl;
+ std::cout << "WeightedMovingVariance()" << std::endl;
+ setup("./config/WeightedMovingVariance.xml");
}
-WeightedMovingVarianceBGS::~WeightedMovingVarianceBGS()
+WeightedMovingVariance::~WeightedMovingVariance()
{
- std::cout << "~WeightedMovingVarianceBGS()" << std::endl;
+ std::cout << "~WeightedMovingVariance()" << std::endl;
}
-void WeightedMovingVarianceBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+void WeightedMovingVariance::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
- if(img_input.empty())
- return;
-
- loadConfig();
+ init(img_input, img_output, img_bgmodel);
- if(firstTime)
- saveConfig();
-
- if(img_input_prev_1.empty())
- {
+ if (img_input_prev_1.empty()) {
img_input.copyTo(img_input_prev_1);
return;
}
- if(img_input_prev_2.empty())
- {
+ if (img_input_prev_2.empty()) {
img_input_prev_1.copyTo(img_input_prev_2);
img_input.copyTo(img_input_prev_1);
return;
}
cv::Mat img_input_f(img_input.size(), CV_32F);
- img_input.convertTo(img_input_f, CV_32F, 1./255.);
+ img_input.convertTo(img_input_f, CV_32F, 1. / 255.);
cv::Mat img_input_prev_1_f(img_input.size(), CV_32F);
- img_input_prev_1.convertTo(img_input_prev_1_f, CV_32F, 1./255.);
+ img_input_prev_1.convertTo(img_input_prev_1_f, CV_32F, 1. / 255.);
cv::Mat img_input_prev_2_f(img_input.size(), CV_32F);
- img_input_prev_2.convertTo(img_input_prev_2_f, CV_32F, 1./255.);
-
- cv::Mat img_foreground;
+ img_input_prev_2.convertTo(img_input_prev_2_f, CV_32F, 1. / 255.);
// Weighted mean
cv::Mat img_mean_f(img_input.size(), CV_32F);
-
- if(enableWeight)
+
+ if (enableWeight)
img_mean_f = ((img_input_f * 0.5) + (img_input_prev_1_f * 0.3) + (img_input_prev_2_f * 0.2));
else
img_mean_f = ((img_input_f * 0.3) + (img_input_prev_1_f * 0.3) + (img_input_prev_2_f * 0.3));
-
+
// Weighted variance
cv::Mat img_1_f(img_input.size(), CV_32F);
cv::Mat img_2_f(img_input.size(), CV_32F);
cv::Mat img_3_f(img_input.size(), CV_32F);
cv::Mat img_4_f(img_input.size(), CV_32F);
- if(enableWeight)
+ if (enableWeight)
{
img_1_f = computeWeightedVariance(img_input_f, img_mean_f, 0.5);
img_2_f = computeWeightedVariance(img_input_prev_1_f, img_mean_f, 0.3);
@@ -89,73 +82,71 @@ void WeightedMovingVarianceBGS::process(const cv::Mat &img_input, cv::Mat &img_o
img_3_f = computeWeightedVariance(img_input_prev_2_f, img_mean_f, 0.3);
img_4_f = (img_1_f + img_2_f + img_3_f);
}
-
+
// Standard deviation
cv::Mat img_sqrt_f(img_input.size(), CV_32F);
cv::sqrt(img_4_f, img_sqrt_f);
cv::Mat img_sqrt(img_input.size(), CV_8U);
double minVal, maxVal;
minVal = 0.; maxVal = 1.;
- img_sqrt_f.convertTo(img_sqrt, CV_8U, 255.0/(maxVal - minVal), -minVal);
+ img_sqrt_f.convertTo(img_sqrt, CV_8U, 255.0 / (maxVal - minVal), -minVal);
img_sqrt.copyTo(img_foreground);
- if(img_foreground.channels() == 3)
+ if (img_foreground.channels() == 3)
cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
- if(enableThreshold)
+ if (enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
- if(showOutput)
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
cv::imshow("W Moving Variance", img_foreground);
+#endif
img_foreground.copyTo(img_output);
+ img_background = cv::Mat::zeros(img_input.size(), img_input.type());
+ img_background.copyTo(img_bgmodel);
+
img_input_prev_1.copyTo(img_input_prev_2);
img_input.copyTo(img_input_prev_1);
-
- firstTime = false;
-}
-//unused
-cv::Mat WeightedMovingVarianceBGS::computeWeightedMean(const std::vector<cv::Mat> &v_img_input_f, const std::vector<double> &weights)
-{
- cv::Mat img;
- return img;
+ firstTime = false;
}
-cv::Mat WeightedMovingVarianceBGS::computeWeightedVariance(const cv::Mat &img_input_f, const cv::Mat &img_mean_f, const double weight)
+cv::Mat WeightedMovingVariance::computeWeightedVariance(const cv::Mat &img_input_f, const cv::Mat &img_mean_f, const double weight)
{
//ERROR in return (weight * ((cv::abs(img_input_f - img_mean_f))^2.));
-
+
cv::Mat img_f_absdiff(img_input_f.size(), CV_32F);
cv::absdiff(img_input_f, img_mean_f, img_f_absdiff);
cv::Mat img_f_pow(img_input_f.size(), CV_32F);
cv::pow(img_f_absdiff, 2.0, img_f_pow);
cv::Mat img_f = weight * img_f_pow;
-
+
return img_f;
}
-void WeightedMovingVarianceBGS::saveConfig()
+void WeightedMovingVariance::saveConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/WeightedMovingVarianceBGS.xml", 0, CV_STORAGE_WRITE);
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
cvWriteInt(fs, "enableWeight", enableWeight);
cvWriteInt(fs, "enableThreshold", enableThreshold);
cvWriteInt(fs, "threshold", threshold);
cvWriteInt(fs, "showOutput", showOutput);
-
+
cvReleaseFileStorage(&fs);
}
-void WeightedMovingVarianceBGS::loadConfig()
+void WeightedMovingVariance::loadConfig()
{
- CvFileStorage* fs = cvOpenFileStorage("./config/WeightedMovingVarianceBGS.xml", 0, CV_STORAGE_READ);
-
- enableWeight = cvReadIntByName(fs, 0, "enableWeight", true);
- enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
- threshold = cvReadIntByName(fs, 0, "threshold", 15);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ enableWeight = cvReadIntByName(fs, nullptr, "enableWeight", true);
+ enableThreshold = cvReadIntByName(fs, nullptr, "enableThreshold", true);
+ threshold = cvReadIntByName(fs, nullptr, "threshold", 15);
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", true);
+
cvReleaseFileStorage(&fs);
}
diff --git a/package_bgs/WeightedMovingVariance.h b/package_bgs/WeightedMovingVariance.h
new file mode 100644
index 0000000..79198b4
--- /dev/null
+++ b/package_bgs/WeightedMovingVariance.h
@@ -0,0 +1,46 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "IBGS.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class WeightedMovingVariance : public IBGS
+ {
+ private:
+ cv::Mat img_input_prev_1;
+ cv::Mat img_input_prev_2;
+ bool enableWeight;
+ bool enableThreshold;
+ int threshold;
+
+ public:
+ WeightedMovingVariance();
+ ~WeightedMovingVariance();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+ cv::Mat computeWeightedVariance(const cv::Mat &img_input_f, const cv::Mat &img_mean_f, const double weight);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/WeightedMovingVarianceBGS.h b/package_bgs/WeightedMovingVarianceBGS.h
deleted file mode 100644
index 88c2ec8..0000000
--- a/package_bgs/WeightedMovingVarianceBGS.h
+++ /dev/null
@@ -1,48 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "IBGS.h"
-
-class WeightedMovingVarianceBGS : public IBGS
-{
-private:
- bool firstTime;
- cv::Mat img_input_prev_1;
- cv::Mat img_input_prev_2;
- bool enableWeight;
- bool enableThreshold;
- int threshold;
- bool showOutput;
-
-public:
- WeightedMovingVarianceBGS();
- ~WeightedMovingVarianceBGS();
-
- cv::Mat computeWeightedMean(const std::vector<cv::Mat> &v_img_input_f, const std::vector<double> &weights);
- cv::Mat computeWeightedVariance(const cv::Mat &img_input_f, const cv::Mat &img_mean_f, const double weight);
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/_template_/Amber.cpp b/package_bgs/_template_/Amber.cpp
new file mode 100644
index 0000000..2e29ac0
--- /dev/null
+++ b/package_bgs/_template_/Amber.cpp
@@ -0,0 +1,112 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+
+#include "Amber.h"
+
+using namespace bgslibrary::algorithms;
+
+Amber::Amber() : model(nullptr)
+{
+ std::cout << "Amber()" << std::endl;
+ /* Initialization of the Amber model */
+ model = libamberModelNew();
+ setup("./config/Amber.xml");
+}
+
+Amber::~Amber()
+{
+ std::cout << "~Amber()" << std::endl;
+ libamberModelFree(model);
+}
+
+void Amber::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ init(img_input, img_output, img_bgmodel);
+
+ if (img_input.empty())
+ return;
+
+ // Start the initialization
+ unsigned int width = img_input.cols;
+ unsigned int height = img_input.rows;
+
+ if (img_input.channels() != 3)
+ {
+ std::cout << "Only works for 3 channels images. Sorry for that" << std::endl;
+ return;
+ }
+
+ unsigned int stride = width * 3;
+ unsigned char* image = static_cast<unsigned char*>(img_input.data);
+
+ if (firstTime)
+ {
+ /* Create a buffer for the output image */
+ //img_output = Mat(img_input.rows, img_input.cols, CV_8UC1);
+
+ /* Sets default model values */
+ // libamberModelSetNumberOfSamples(model, nbSamples);
+ // libamberModelSetMatchingThreshold(model, matchingThreshold);
+ // libamberModelSetMatchingNumber(model, matchingNumber);
+ // libamberModelSetUpdateFactor(model, init_subsamplingFactor);
+ // libamberModelPrintParameters(model);
+
+ /* Initiliazes the Amber model */
+ libamberModelAllocInit_8u_C3R(model, image, width, height);
+ }
+
+ /* Create temporary buffers */
+ unsigned char* output_segmentationMap = static_cast<unsigned char*>(calloc(width * height, sizeof(unsigned char)));
+ libamberGetSegmentation_8u_C3R(model, image, output_segmentationMap);
+
+ unsigned char* oBuffer = static_cast<unsigned char*>(img_output.data);
+ unsigned char* tmpSegmentationMap = output_segmentationMap;
+
+ for (int i = 0; i < width * height; i++)
+ {
+ *oBuffer = *tmpSegmentationMap;
+
+ ++oBuffer;
+ ++tmpSegmentationMap;
+ }
+
+#ifndef MEX_COMPILE_FLAG
+ if (showOutput)
+ imshow("Amber", img_output);
+#endif
+
+ firstTime = false;
+ free(output_segmentationMap);
+}
+
+void Amber::saveConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_WRITE);
+
+ cvWriteInt(fs, "showOutput", showOutput);
+
+ cvReleaseFileStorage(&fs);
+}
+
+void Amber::loadConfig()
+{
+ CvFileStorage* fs = cvOpenFileStorage(config_xml.c_str(), nullptr, CV_STORAGE_READ);
+
+ showOutput = cvReadIntByName(fs, nullptr, "showOutput", false);
+
+ cvReleaseFileStorage(&fs);
+}
diff --git a/package_bgs/_template_/Amber.h b/package_bgs/_template_/Amber.h
new file mode 100644
index 0000000..37f0f8d
--- /dev/null
+++ b/package_bgs/_template_/Amber.h
@@ -0,0 +1,45 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <math.h>
+#include <sys/types.h>
+
+#include "../IBGS.h"
+#include "amber/amber.h"
+
+namespace bgslibrary
+{
+ namespace algorithms
+ {
+ class Amber : public IBGS
+ {
+ private:
+ amberModel* model;
+
+ public:
+ Amber();
+ ~Amber();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig();
+ void loadConfig();
+ };
+ }
+}
diff --git a/package_bgs/_template_/MyBGS.cpp b/package_bgs/_template_/MyBGS.cpp
new file mode 100644
index 0000000..10d5588
--- /dev/null
+++ b/package_bgs/_template_/MyBGS.cpp
@@ -0,0 +1,44 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "MyBGS.h"
+
+using namespace bgslibrary::algorithms;
+
+MyBGS::MyBGS() {}
+MyBGS::~MyBGS() {}
+
+void MyBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
+{
+ if (img_input.empty())
+ return;
+
+ if (img_previous.empty())
+ img_input.copyTo(img_previous);
+
+ cv::Mat img_foreground;
+ cv::absdiff(img_previous, img_input, img_foreground);
+
+ if (img_foreground.channels() == 3)
+ cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
+
+ cv::threshold(img_foreground, img_foreground, 15, 255, cv::THRESH_BINARY);
+
+ img_foreground.copyTo(img_output);
+ img_previous.copyTo(img_bgmodel);
+
+ img_input.copyTo(img_previous);
+}
diff --git a/package_bgs/ck/LbpMrf.h b/package_bgs/_template_/MyBGS.h
similarity index 65%
rename from package_bgs/ck/LbpMrf.h
rename to package_bgs/_template_/MyBGS.h
index 6fd7267..dea2a2f 100644
--- a/package_bgs/ck/LbpMrf.h
+++ b/package_bgs/_template_/MyBGS.h
@@ -16,29 +16,28 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
-#include <iostream>
#include <opencv2/opencv.hpp>
#include "../IBGS.h"
-class MotionDetection;
-
-class LbpMrf : public IBGS
+namespace bgslibrary
{
-private:
- bool firstTime;
- MotionDetection* Detector;
- cv::Mat img_foreground;
- cv::Mat img_segmentation;
- bool showOutput;
-
-public:
- LbpMrf();
- ~LbpMrf();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
+ namespace algorithms
+ {
+ class MyBGS : public IBGS
+ {
+ private:
+ cv::Mat img_previous;
+
+ public:
+ MyBGS();
+ ~MyBGS();
+
+ void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
+
+ private:
+ void saveConfig() {}
+ void loadConfig() {}
+ };
+ }
+}
diff --git a/package_bgs/_template_/amber/amber.c b/package_bgs/_template_/amber/amber.c
new file mode 100644
index 0000000..00bdfb1
--- /dev/null
+++ b/package_bgs/_template_/amber/amber.c
@@ -0,0 +1,80 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+
+#include "amber.h"
+
+#define COLOR_BACKGROUND 0
+#define COLOR_FOREGROUND 255
+
+amberModel* libamberModelNew()
+{
+ /* model structure alloc */
+ amberModel* model = NULL;
+ model = (amberModel*)calloc(1, sizeof(amberModel));
+ assert(model != NULL);
+
+ /* default parameters values */
+ model->height = 0;
+
+ return(model);
+}
+
+// --------------------------------------------------
+int32_t libamberModelAllocInit_8u_C3R(amberModel* model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height)
+{
+
+ /* basic checks */
+ assert((image_data != NULL) && (model != NULL));
+ assert((model->width > 0) && (model->height > 0));
+
+ /* finish model alloc - parameters values cannot be changed anymore */
+ model->width = width;
+ model->height = height;
+
+ return(0);
+}
+
+// --------------------------------------------------
+int32_t libamberGetSegmentation_8u_C3R(amberModel* model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map)
+{
+ /* basic checks */
+ assert((image_data != NULL) && (model != NULL) && (segmentation_map != NULL));
+ assert((model->width > 0) && (model->height > 0));
+
+ return(0);
+}
+
+// --------------------------------------------------
+int32_t libamberModelFree(amberModel* model)
+{
+ if (model == NULL)
+ return(-1);
+
+ free(model);
+
+ return(0);
+}
+
+/* For compilation with g++ */
+#ifdef __cplusplus
+}
+#endif
diff --git a/package_bgs/_template_/amber/amber.h b/package_bgs/_template_/amber/amber.h
new file mode 100644
index 0000000..0206179
--- /dev/null
+++ b/package_bgs/_template_/amber/amber.h
@@ -0,0 +1,64 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <assert.h>
+
+#define COLOR_BACKGROUND 0
+#define COLOR_FOREGROUND 255
+
+/* For compilation with g++ */
+#ifdef __cplusplus
+extern "C"
+{
+#endif
+ /* end of addition for compilation with g++ */
+
+#ifndef _STDINT_H
+// This is used to make it compatible for cross-compilation
+ typedef unsigned char uint8_t;
+ typedef int int32_t;
+ typedef unsigned int uint32_t;
+#endif // _STDINT_H
+
+ typedef struct {
+ uint32_t width;
+ uint32_t height;
+ } amberModel;
+
+ /** Allocation of a new data structure where the background model
+ will be stored */
+ amberModel* libamberModelNew();
+
+ int32_t libamberModelAllocInit_8u_C3R(amberModel* model,
+ const uint8_t *image_data,
+ const uint32_t width,
+ const uint32_t height);
+
+ int32_t libamberGetSegmentation_8u_C3R(amberModel* model,
+ const uint8_t *image_data,
+ uint8_t *segmentation_map);
+
+
+ int32_t libamberModelFree(amberModel* model);
+
+ /* For compilation with g++ */
+#ifdef __cplusplus
+}
+#endif
diff --git a/package_bgs/ae/KDE.h b/package_bgs/ae/KDE.h
deleted file mode 100644
index adcc659..0000000
--- a/package_bgs/ae/KDE.h
+++ /dev/null
@@ -1,58 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "NPBGSubtractor.h"
-#include "../IBGS.h"
-
-class KDE : public IBGS
-{
-private:
- NPBGSubtractor *p;
- int rows;
- int cols;
- int color_channels;
- int SequenceLength;
- int TimeWindowSize;
- int SDEstimationFlag;
- int lUseColorRatiosFlag;
- double th;
- double alpha;
- int framesToLearn;
- int frameNumber;
- bool firstTime;
- bool showOutput;
-
- cv::Mat img_foreground;
- unsigned char *FGImage;
- unsigned char *FilteredFGImage;
- unsigned char **DisplayBuffers;
-
-public:
- KDE();
- ~KDE();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/ae/NPBGSubtractor.cpp b/package_bgs/ae/NPBGSubtractor.cpp
deleted file mode 100644
index 3f0620f..0000000
--- a/package_bgs/ae/NPBGSubtractor.cpp
+++ /dev/null
@@ -1,1160 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-/*
-*
-* Copyright 2001 by Ahmed Elgammal All rights reserved.
-*
-* Permission to use, copy, or modify this software and its documentation
-* for educational and research purposes only and without fee is hereby
-* granted, provided that this copyright notice and the original authors's
-* name appear on all copies and supporting documentation. If individual
-* files are separated from this distribution directory structure, this
-* copyright notice must be included. For any other uses of this software,
-* in original or modified form, including but not limited to distribution
-* in whole or in part, specific prior permission must be obtained from
-* Author or UMIACS. These programs shall not be used, rewritten, or
-* adapted as the basis of a commercial software or hardware product
-* without first obtaining appropriate licenses from Author.
-* Other than these cases, no part of this software may be used or
-* distributed without written permission of the author.
-*
-* Neither the author nor UMIACS make any representations about the
-* suitability of this software for any purpose. It is provided
-* "as is" without express or implied warranty.
-*
-* Ahmed Elgammal
-*
-* University of Maryland at College Park
-* UMIACS
-* A.V. Williams Bldg.
-* CollegePark, MD 20742
-* E-mail: elgammal@umiacs.umd.edu
-*
-**/
-
-// NPBGSubtractor.cpp: implementation of the NPBGSubtractor class.
-//
-//////////////////////////////////////////////////////////////////////
-
-#include "NPBGSubtractor.h"
-#include <assert.h>
-#include <math.h>
-#include <string.h>
-
-//#ifdef _DEBUG
-//#undef THIS_FILE
-//static char THIS_FILE[]=__FILE__;
-//#define new DEBUG_NEW
-//#endif
-
-void BGR2SnGnRn(unsigned char * in_image,
- unsigned char * out_image,
- unsigned int rows,
- unsigned int cols)
-{
- unsigned int i;
- unsigned int r2,r3;
- unsigned int r,g,b;
- double s;
-
- for(i = 0; i < rows*cols*3; i += 3)
- {
- b=in_image[i];
- g=in_image[i+1];
- r=in_image[i+2];
-
- // calculate color ratios
- s = (double) 255 / (double) (b+g+r+30);
-
- r2 =(unsigned int) ((g+10) * s );
- r3 =(unsigned int) ((r+10) * s );
-
- out_image[i] = (unsigned char) (((unsigned int) b+g+r) / 3);
- out_image[i+1] = (unsigned char) (r2 > 255 ? 255 : r2) ;
- out_image[i+2] = (unsigned char) (r3 > 255 ? 255 : r3) ;
- }
-}
-
-void UpdateDiffHist(unsigned char * image1, unsigned char * image2, DynamicMedianHistogram * pHist)
-{
- unsigned int j;
- int bin,diff;
-
- unsigned int imagesize = pHist->imagesize;
- unsigned char histbins = pHist->histbins;
- unsigned char *pAbsDiffHist = pHist->Hist;
-
- int histbins_1 = histbins-1;
-
- for(j = 0; j < imagesize; j++)
- {
- diff = (int) image1[j] - (int) image2[j];
- diff = abs(diff);
- // update histogram
- bin = (diff < histbins ? diff : histbins_1);
- pAbsDiffHist[j*histbins+bin]++;
- }
-}
-
-void FindHistMedians(DynamicMedianHistogram * pAbsDiffHist)
-{
- unsigned char * Hist = pAbsDiffHist->Hist;
- unsigned char * MedianBins = pAbsDiffHist->MedianBins;
- unsigned char * AccSum = pAbsDiffHist->AccSum;
- unsigned char histsum = pAbsDiffHist->histsum;
- unsigned char histbins = pAbsDiffHist->histbins;
- unsigned int imagesize = pAbsDiffHist->imagesize;
-
- int sum;
- int bin;
- unsigned int histindex;
- unsigned char medianCount=histsum/2;
- unsigned int j;
-
- // find medians
- for(j = 0; j < imagesize; j++)
- {
- // find the median
- bin=0;
- sum=0;
-
- histindex=j*histbins;
-
- while(sum < medianCount)
- {
- sum+=Hist[histindex+bin];
- bin++;
- }
-
- bin--;
-
- MedianBins[j]=bin;
- AccSum[j]=sum;
- }
-}
-
-DynamicMedianHistogram BuildAbsDiffHist(unsigned char * pSequence,
- unsigned int rows,
- unsigned int cols,
- unsigned int color_channels,
- unsigned int SequenceLength,
- unsigned int histbins)
-{
-
- unsigned int imagesize=rows*cols*color_channels;
- unsigned int i;
-
- DynamicMedianHistogram Hist;
-
- unsigned char *pAbsDiffHist = new unsigned char[rows*cols*color_channels*histbins];
- unsigned char *pMedianBins = new unsigned char[rows*cols*color_channels];
- unsigned char *pMedianFreq = new unsigned char[rows*cols*color_channels];
- unsigned char *pAccSum = new unsigned char[rows*cols*color_channels];
-
- memset(pAbsDiffHist,0,rows*cols*color_channels*histbins);
-
- Hist.Hist = pAbsDiffHist;
- Hist.MedianBins = pMedianBins;
- Hist.MedianFreq = pMedianFreq;
- Hist.AccSum = pAccSum;
- Hist.histbins = histbins;
- Hist.imagesize = rows*cols*color_channels;
- Hist.histsum = SequenceLength-1;
-
- unsigned char *image1, *image2;
- for(i = 1; i < SequenceLength; i++)
- {
- // find diff between frame i,i-1;
- image1 = pSequence+(i-1)*imagesize;
- image2 = pSequence+(i)*imagesize;
-
- UpdateDiffHist(image1,image2,&Hist);
- }
-
- FindHistMedians(&Hist);
-
- return Hist;
-}
-
-void EstimateSDsFromAbsDiffHist(DynamicMedianHistogram * pAbsDiffHist,
- unsigned char * pSDs,
- unsigned int imagesize,
- double MinSD,
- double MaxSD,
- unsigned int kernelbins)
-{
- double v;
- double kernelbinfactor=(kernelbins-1)/(MaxSD-MinSD);
- int medianCount;
- int sum;
- int bin;
- unsigned int histindex;
- unsigned int j;
- unsigned int x1,x2;
-
- unsigned char *Hist =pAbsDiffHist->Hist;
- unsigned char *MedianBins =pAbsDiffHist->MedianBins;
- unsigned char *AccSum =pAbsDiffHist->AccSum;
- unsigned char histsum =pAbsDiffHist->histsum;
- unsigned char histbins =pAbsDiffHist->histbins;
-
- medianCount=(histsum)/2 ;
-
- for(j = 0; j < imagesize; j++)
- {
- histindex=j*histbins;
-
- bin=MedianBins[j];
- sum=AccSum[j];
-
- x1=sum-Hist[histindex+bin];
- x2=sum;
-
- // interpolate to get the median
- // x1 < 50 % < x2
-
- v =1.04 * ((double) bin-(double) (x2-medianCount)/ (double) (x2-x1));
- v=( v <= MinSD ? MinSD : v);
-
- // convert sd to kernel table bin
-
- bin=(int) (v>=MaxSD ? kernelbins-1 : floor((v-MinSD)*kernelbinfactor+.5));
-
- assert(bin>=0 && bin < kernelbins );
-
- pSDs[j]=bin;
- }
-}
-
-//////////////////////////////////////////////////////////////////////
-// Construction/Destruction
-//////////////////////////////////////////////////////////////////////
-
-NPBGSubtractor::NPBGSubtractor(){}
-
-NPBGSubtractor::~NPBGSubtractor()
-{
- delete AbsDiffHist.Hist;
- delete AbsDiffHist.MedianBins;
- delete AbsDiffHist.MedianFreq;
- delete AbsDiffHist.AccSum;
- delete KernelTable;
- delete BGModel->SDbinsImage;
- delete BGModel;
- delete Pimage1;
- delete Pimage2;
- delete tempFrame;
- delete imageindex->List;
- delete imageindex;
-}
-
-int NPBGSubtractor::Intialize(unsigned int prows,
- unsigned int pcols,
- unsigned int pcolor_channels,
- unsigned int SequenceLength,
- unsigned int pTimeWindowSize,
- unsigned char pSDEstimationFlag,
- unsigned char pUseColorRatiosFlag)
-{
-
- rows=prows;
- cols=pcols;
- color_channels=pcolor_channels;
- imagesize=rows*cols*color_channels;
- SdEstimateFlag = pSDEstimationFlag;
- UseColorRatiosFlag=pUseColorRatiosFlag;
- //SampleSize = SequenceLength;
-
- AdaptBGFlag = FALSE;
- //
- SubsetFlag = TRUE;
-
- UpdateSDRate = 0;
-
- BGModel = new NPBGmodel(rows,cols,color_channels,SequenceLength,pTimeWindowSize,500);
-
- Pimage1= new double[rows*cols];
- Pimage2= new double[rows*cols];
-
- tempFrame= new unsigned char[rows*cols*3];
-
- imageindex = new ImageIndex;
- imageindex->List= new unsigned int [rows*cols];
-
- // error checking
- if (BGModel==NULL)
- return 0;
-
- return 1;
-}
-
-void NPBGSubtractor::AddFrame(unsigned char *ImageBuffer)
-{
- if(UseColorRatiosFlag && color_channels==3)
- BGR2SnGnRn(ImageBuffer,ImageBuffer,rows,cols);
-
- BGModel->AddFrame(ImageBuffer);
-}
-
-void NPBGSubtractor::Estimation()
-{
- int SampleSize=BGModel->SampleSize;
-
- memset(BGModel->TemporalMask,0,rows*cols*BGModel->TemporalBufferLength);
-
- //BGModel->AccMask= new unsigned int [rows*cols];
- memset(BGModel->AccMask,0,rows*cols*sizeof(unsigned int));
-
- unsigned char *pSDs = new unsigned char[rows*cols*color_channels];
-
- //DynamicMedianHistogram AbsDiffHist;
-
- int Abshistbins = 20;
-
- TimeIndex=0;
-
- // estimate standard deviations
-
- if(SdEstimateFlag)
- {
- AbsDiffHist = BuildAbsDiffHist(BGModel->Sequence,rows,cols,color_channels,SampleSize,Abshistbins);
- EstimateSDsFromAbsDiffHist(&AbsDiffHist,pSDs,imagesize,SEGMAMIN,SEGMAMAX,SEGMABINS);
- }
- else
- {
- unsigned int bin;
- bin = (unsigned int) floor(((DEFAULTSEGMA-SEGMAMIN)*SEGMABINS)/(SEGMAMAX-SEGMAMIN));
- memset(pSDs,bin,rows*cols*color_channels*sizeof(unsigned char));
- }
-
- BGModel->SDbinsImage=pSDs;
-
- // Generate the Kernel
- KernelTable = new KernelLUTable(KERNELHALFWIDTH,SEGMAMIN,SEGMAMAX,SEGMABINS);
-}
-
-/*********************************************************************/
-
-void BuildImageIndex(unsigned char * Image,
- ImageIndex * imageIndex,
- unsigned int rows,
- unsigned int cols)
-{
- unsigned int i,j;
- unsigned int r,c;
- unsigned int * image_list;
-
- j=cols+1;
- i=0;
- image_list=imageIndex->List;
-
- for(r = 1; r < rows-1; r++)
- {
- for(c = 1; c < cols-1; c++)
- {
- if(Image[j])
- image_list[i++]=j;
-
- j++;
- }
- j+=2;
- }
-
- imageIndex->cnt = i;
-}
-
-/*********************************************************************/
-
-void HystExpandOperatorIndexed(unsigned char * inImage,
- ImageIndex * inIndex,
- double * Pimage,
- double hyst_th,
- unsigned char * outImage,
- ImageIndex * outIndex,
- unsigned int urows,
- unsigned int ucols)
-{
- unsigned int * in_list;
- unsigned int in_cnt;
- unsigned int * out_list;
-
- int rows,cols;
-
- int Nbr[9];
- unsigned int i,j;
- unsigned int k;
- unsigned int idx;
-
- rows=(int) urows;
- cols=(int) ucols;
-
- in_cnt=inIndex->cnt;
- in_list=inIndex->List;
-
- Nbr[0]=-cols-1;
- Nbr[1]=-cols;
- Nbr[2]=-cols+1;
- Nbr[3]=-1;
- Nbr[4]=0;
- Nbr[5]=1;
- Nbr[6]=cols-1;
- Nbr[7]=cols;
- Nbr[8]=cols+1;
-
- memset(outImage,0,rows*cols);
-
- out_list=outIndex->List;
- k=0;
-
- for(i = 0; i < in_cnt; i++)
- {
- for(j = 0; j < 9; j++)
- {
- idx = in_list[i] + Nbr[j];
-
- if(Pimage[idx] < hyst_th)
- outImage[idx] = 255;
- }
- }
-
- // build index for out image
- BuildImageIndex(outImage,outIndex,urows,ucols);
-}
-
-/*********************************************************************/
-
-void HystShrinkOperatorIndexed(unsigned char * inImage,
- ImageIndex * inIndex,
- double * Pimage,
- double hyst_th,
- unsigned char * outImage,
- ImageIndex * outIndex,
- unsigned int urows,
- unsigned int ucols)
-{
- unsigned int * in_list;
- unsigned int in_cnt;
- unsigned int * out_list;
-
- int rows,cols;
-
- int Nbr[9];
- unsigned int i,j;
- unsigned int k,idx;
-
- rows=(int) urows;
- cols=(int) ucols;
-
- in_cnt=inIndex->cnt;
- in_list=inIndex->List;
-
- Nbr[0]=-cols-1;
- Nbr[1]=-cols;
- Nbr[2]=-cols+1;
- Nbr[3]=-1;
- Nbr[4]=0;
- Nbr[5]=1;
- Nbr[6]=cols-1;
- Nbr[7]=cols;
- Nbr[8]=cols+1;
-
- memset(outImage,0,rows*cols);
-
- out_list=outIndex->List;
- k=0;
-
- for(i = 0; i < in_cnt; i++)
- {
- idx = in_list[i];
- j = 0;
-
- while(j < 9 && inImage[idx+Nbr[j]])
- j++;
-
- if(j >= 9 || Pimage[idx] <= hyst_th)
- outImage[idx]=255;
- }
-
- BuildImageIndex(outImage,outIndex,rows,cols);
-}
-
-/*********************************************************************/
-
-void ExpandOperatorIndexed(unsigned char * inImage,
- ImageIndex * inIndex,
- unsigned char * outImage,
- ImageIndex * outIndex,
- unsigned int urows,
- unsigned int ucols)
-{
- unsigned int * in_list;
- unsigned int in_cnt;
- unsigned int * out_list;
-
- int rows,cols;
-
- int Nbr[9];
- unsigned int i,j;
- unsigned int k;
- unsigned int idx;
-
- rows=(int) urows;
- cols=(int) ucols;
-
- in_cnt=inIndex->cnt;
- in_list=inIndex->List;
-
- Nbr[0]=-cols-1;
- Nbr[1]=-cols;
- Nbr[2]=-cols+1;
- Nbr[3]=-1;
- Nbr[4]=0;
- Nbr[5]=1;
- Nbr[6]=cols-1;
- Nbr[7]=cols;
- Nbr[8]=cols+1;
-
-
- memset(outImage,0,rows*cols);
-
-
- out_list=outIndex->List;
- k=0;
- for (i=0; i<in_cnt;i++)
- for (j=0;j<9;j++) {
- idx=in_list[i]+Nbr[j];
- outImage[idx]=255;
- }
-
-
- // build index for out image
-
- BuildImageIndex(outImage,outIndex,rows,cols);
-
-}
-
-/*********************************************************************/
-
-void ShrinkOperatorIndexed(unsigned char * inImage,
- ImageIndex * inIndex,
- unsigned char * outImage,
- ImageIndex * outIndex,
- unsigned int urows,
- unsigned int ucols)
-{
-
- unsigned int * in_list;
- unsigned int in_cnt;
- unsigned int * out_list;
-
- int rows,cols;
-
- int Nbr[9];
- unsigned int i,j;
- unsigned int k,idx;
-
- rows=(int) urows;
- cols=(int) ucols;
-
- in_cnt=inIndex->cnt;
- in_list=inIndex->List;
-
- Nbr[0]=-cols-1;
- Nbr[1]=-cols;
- Nbr[2]=-cols+1;
- Nbr[3]=-1;
- Nbr[4]=0;
- Nbr[5]=1;
- Nbr[6]=cols-1;
- Nbr[7]=cols;
- Nbr[8]=cols+1;
-
-
- memset(outImage,0,rows*cols);
-
- out_list=outIndex->List;
- k=0;
- for (i=0; i<in_cnt;i++) {
- idx=in_list[i];
- j=0;
-
- while ( j<9 && inImage[idx+Nbr[j]]){
- j++;
- }
-
- if (j>=9) {
- outImage[idx]=255;
- }
- }
-
- BuildImageIndex(outImage,outIndex,rows,cols);
-}
-
-/*********************************************************************/
-
-void NoiseFilter_o(unsigned char * Image,
- unsigned char * ResultIm,
- int rows,
- int cols,
- unsigned char th)
-{
- /* assuming input is 1 for on, 0 for off */
-
-
- int r,c;
- unsigned char *p,*n,*nw,*ne,*e,*w,*s,*sw,*se;
- unsigned int v;
- unsigned int TH;
-
- unsigned char * ResultPtr;
-
- TH=255*th;
-
- memset(ResultIm,0,rows*cols);
-
- p=Image+cols+1;
- ResultPtr=ResultIm+cols+1;
-
- for(r=1;r<rows-1;r++)
- {
- for(c=1;c<cols-1;c++)
- {
- if (*p)
- {
- n=p-cols;
- ne=n+1;
- nw=n-1;
- e=p+1;
- w=p-1;
- s=p+cols;
- se=s+1;
- sw=s-1;
-
- v=(unsigned int) *nw+*n+*ne+*w+*e+*sw+*s+*se;
-
- if (v>=TH)
- *ResultPtr=255;
- else
- *ResultPtr=0;
- }
- p++;
- ResultPtr++;
- }
- p+=2;
- ResultPtr+=2;
- }
-}
-
-/*********************************************************************/
-
-void NPBGSubtractor::SequenceBGUpdate_Pairs(unsigned char * image,
- unsigned char * Mask)
-{
- unsigned int i,ic;
- unsigned char * pSequence =BGModel->Sequence;
- unsigned char * PixelQTop =BGModel->PixelQTop;
- unsigned int Top =BGModel->Top;
- unsigned int rate;
-
- int TemporalBufferTop =(int) BGModel->TemporalBufferTop;
- unsigned char * pTemporalBuffer = BGModel->TemporalBuffer;
- unsigned char * pTemporalMask = BGModel->TemporalMask;
- int TemporalBufferLength = BGModel->TemporalBufferLength;
-
- unsigned int * AccMask = BGModel->AccMask;
- unsigned int ResetMaskTh = BGModel->ResetMaskTh;
-
- unsigned char *pAbsDiffHist = AbsDiffHist.Hist;
- unsigned char histbins = AbsDiffHist.histbins;
- int histbins_1=histbins-1;
-
- int TimeWindowSize = BGModel->TimeWindowSize;
- int SampleSize = BGModel->SampleSize;
-
- int TemporalBufferNext;
-
- unsigned int imagebuffersize=rows*cols*color_channels;
- unsigned int imagespatialsize=rows*cols;
-
- unsigned char mask;
-
- unsigned int histindex;
- unsigned char diff;
- unsigned char bin;
-
- static int TBCount=0;
-
- unsigned char * pTBbase1, * pTBbase2;
- unsigned char * pModelbase1, * pModelbase2;
-
- rate=TimeWindowSize/SampleSize;
- rate=(rate > 2) ? rate : 2;
-
-
- TemporalBufferNext=(TemporalBufferTop+1)
- % TemporalBufferLength;
-
- // pointers to Masks : Top and Next
- unsigned char * pTMaskTop=pTemporalMask+TemporalBufferTop*imagespatialsize;
- unsigned char * pTMaskNext=pTemporalMask+TemporalBufferNext*imagespatialsize;
-
- // pointers to TB frames: Top and Next
- unsigned char * pTBTop=pTemporalBuffer+TemporalBufferTop*imagebuffersize;
- unsigned char * pTBNext=pTemporalBuffer+TemporalBufferNext*imagebuffersize;
-
- if ( ((TimeIndex) % rate == 0) && TBCount >= TemporalBufferLength )
- {
- for(i=0,ic=0;i<imagespatialsize;i++,ic+=color_channels)
- {
- mask= * (pTMaskTop+i) || * (pTMaskNext+i);
-
- if(!mask)
- {
- // pointer to TB pixels to be added to the model
- pTBbase1=pTBTop+ic;
- pTBbase2=pTBNext+ic;
-
- // pointers to Model pixels to be replaced
- pModelbase1=pSequence+PixelQTop[i]*imagebuffersize+ic;
- pModelbase2=pSequence+((PixelQTop[i]+1)% SampleSize)*imagebuffersize+ic;
-
- // update Deviation Histogram
- if(SdEstimateFlag)
- {
- if(color_channels==1)
- {
- histindex=i*histbins;
-
- // add new pair from temporal buffer
- diff=(unsigned char) abs((int) *pTBbase1 - (int) *pTBbase2);
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]++;
-
-
- // remove old pair from the model
- diff=(unsigned char) abs((int) *pModelbase1-(int) *pModelbase2);
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]--;
- }
- else
- {
- // color
-
- // add new pair from temporal buffer
- histindex=ic*histbins;
- diff=abs(*pTBbase1 -
- *pTBbase2);
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]++;
-
- histindex+=histbins;
- diff=abs(*(pTBbase1+1) -
- *(pTBbase2+1));
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]++;
-
- histindex+=histbins;
- diff=abs(*(pTBbase1+2) -
- *(pTBbase2+2));
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]++;
-
- // remove old pair from the model
- histindex=ic*histbins;
-
- diff=abs(*pModelbase1-
- *pModelbase2);
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]--;
-
- histindex+=histbins;
- diff=abs(*(pModelbase1+1)-
- *(pModelbase2+1));
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]--;
-
- histindex+=histbins;
- diff=abs(*(pModelbase1+2)-
- *(pModelbase2+2));
- bin=(diff < histbins ? diff : histbins_1);
- pAbsDiffHist[histindex+bin]--;
- }
- }
-
- // add new pair into the model
- memcpy(pModelbase1,pTBbase1, color_channels*sizeof(unsigned char));
-
- memcpy(pModelbase2,pTBbase2, color_channels*sizeof(unsigned char));
-
- PixelQTop[i]=(PixelQTop[i]+2) % SampleSize;
- }
- }
- } // end if (sampling event)
-
- // update temporal buffer
- // add new frame to Temporal buffer.
- memcpy(pTBTop,image,imagebuffersize);
-
- // update AccMask
- // update new Mask with information in AccMask
-
- for (i=0;i<rows*cols;i++)
- {
- if (Mask[i])
- AccMask[i]++;
- else
- AccMask[i]=0;
-
- if (AccMask[i] > ResetMaskTh)
- Mask[i]=0;
- }
-
- // add new mask
- memcpy(pTMaskTop,Mask,imagespatialsize);
-
- // advance Temporal buffer pointer
- TemporalBufferTop=(TemporalBufferTop+1) % TemporalBufferLength;
-
- BGModel->TemporalBufferTop=TemporalBufferTop;
-
- TBCount++;
-
- // estimate SDs
-
- if (SdEstimateFlag && UpdateSDRate && ((TimeIndex) % UpdateSDRate == 0))
- {
- double MaxSD = KernelTable->maxsegma;
- double MinSD = KernelTable->minsegma;
- int KernelBins = KernelTable->segmabins;
-
- unsigned char * pSDs= BGModel->SDbinsImage;
-
- FindHistMedians(&(AbsDiffHist));
- EstimateSDsFromAbsDiffHist(&(AbsDiffHist),pSDs,imagebuffersize,MinSD,MaxSD,KernelBins);
- }
-
- TimeIndex++;
-}
-
-/*********************************************************************/
-
-void DisplayPropabilityImageWithThresholding(double * Pimage,
- unsigned char * DisplayImage,
- double Threshold,
- unsigned int rows,
- unsigned int cols)
-{
- double p;
-
- for(unsigned int i=0;i<rows*cols;i++)
- {
- p = Pimage[i];
-
- DisplayImage[i]=(p > Threshold) ? 0 : 255;
- }
-}
-
-/*********************************************************************/
-
-void NPBGSubtractor::NPBGSubtraction_Subset_Kernel(
- unsigned char * image,
- unsigned char * FGImage,
- unsigned char * FilteredFGImage)
-{
- unsigned int i,j;
- unsigned char *pSequence =BGModel->Sequence;
-
- unsigned int SampleSize = BGModel->SampleSize;
-
- double *kerneltable = KernelTable->kerneltable;
- int KernelHalfWidth = KernelTable->tablehalfwidth;
- double *KernelSum = KernelTable->kernelsums;
- double KernelMaxSigma = KernelTable->maxsegma;
- double KernelMinSigma = KernelTable->minsegma;
- int KernelBins = KernelTable->segmabins;
- unsigned char * SDbins= BGModel->SDbinsImage;
-
- unsigned char * SaturationImage=FilteredFGImage;
-
- // default sigmas .. to be removed.
- double sigma1;
- double sigma2;
- double sigma3;
-
- sigma1=2.25;
- sigma2=2.25;
- sigma3=2.25;
-
- double p;
- double th;
-
- double alpha;
-
- alpha= AlphaValue;
-
- /* intialize FG image */
-
- memset(FGImage,0,rows*cols);
-
- //Threshold=1;
- th = Threshold * SampleSize;
-
- double sum=0,kernel1,kernel2,kernel3;
- int k,g;
-
-
- if (color_channels==1)
- {
- // gray scale
-
- int kernelbase;
-
- for (i=0;i<rows*cols;i++)
- {
- kernelbase=SDbins[i]*(2*KernelHalfWidth+1);
- sum=0;
- j=0;
-
- while (j<SampleSize && sum < th)
- {
- g=pSequence[j*imagesize+i];
- k= g- image[i] +KernelHalfWidth;
- sum+=kerneltable[kernelbase+k];
- j++;
- }
-
- p=sum/j;
- Pimage1[i]=p;
- }
- }
- else if (UseColorRatiosFlag && SubsetFlag)
- {
- // color ratios
-
- unsigned int ig;
- int base;
-
- int kernelbase1;
- int kernelbase2;
- int kernelbase3;
-
- unsigned int kerneltablewidth=2*KernelHalfWidth+1;
-
- double beta=3.0; // minimum bound on the range.
- double betau=100.0;
-
- double beta_over_alpha = beta / alpha;
- double betau_over_alpha = betau / alpha;
-
-
- double brightness_lowerbound = 1-alpha;
- double brightness_upperbound = 1+alpha;
- int x1,x2;
- unsigned int SubsampleCount;
-
- for (i=0,ig=0;i<imagesize;i+=3,ig++)
- {
- kernelbase1=SDbins[i]*kerneltablewidth;
- kernelbase2=SDbins[i+1]*kerneltablewidth;
- kernelbase3=SDbins[i+2]*kerneltablewidth;
-
- sum=0;
- j=0;
- SubsampleCount=0;
-
- while (j<SampleSize && sum < th)
- {
- base=j*imagesize+i;
- g=pSequence[base];
-
- if (g < beta_over_alpha)
- {
- x1=(int) (g-beta);
- x2=(int) (g+beta);
- }
- else if (g > betau_over_alpha)
- {
- x1=(int) (g-betau);
- x2=(int) (g+betau);
- }
- else
- {
- x1=(int) (g*brightness_lowerbound+0.5);
- x2=(int) (g*brightness_upperbound+0.5);
- }
-
- if(x1<image[i] && image[i] <x2)
- {
- g=pSequence[base+1];
- k= (g- image[i+1]) +KernelHalfWidth;
- kernel2=kerneltable[kernelbase2+k];
-
- g=pSequence[base+2];
- k= (g- image[i+2]) +KernelHalfWidth;
- kernel3=kerneltable[kernelbase3+k];
-
- sum+=kernel2*kernel3;
-
- SubsampleCount++;
- }
- j++;
- }
-
- p=sum / j;
- Pimage1[ig]=p;
- }
- }
- else if (UseColorRatiosFlag && ! SubsetFlag)
- {
- // color ratios
-
- unsigned int ig;
- int base;
- int bin;
-
- int kernelbase1;
- int kernelbase2;
- int kernelbase3;
-
- unsigned int kerneltablewidth=2*KernelHalfWidth+1;
-
- int gmin,gmax;
- double gfactor;
-
- gmax=200;
- gmin=10;
-
- gfactor = (KernelMaxSigma-KernelMinSigma) / (double) (gmax - gmin);
-
- for (i=0,ig=0;i<imagesize;i+=3,ig++)
- {
-
- bin=(int) floor(((alpha*16-KernelMinSigma)*KernelBins)/(KernelMaxSigma-KernelMinSigma));
-
- kernelbase1=bin*kerneltablewidth;
- kernelbase2=SDbins[i+1]*kerneltablewidth;
- kernelbase3=SDbins[i+2]*kerneltablewidth;
-
- sum=0;
- j=0;
-
- while (j<SampleSize && sum < th)
- {
- base=j*imagesize+i;
- g=pSequence[base];
-
- if (g < gmin )
- bin=0;
- else if (g > gmax)
- bin = KernelBins -1 ;
- else
- bin= (int) ((g-gmin) * gfactor + 0.5);
-
- kernelbase1=bin*kerneltablewidth;
-
- k= (g- image[i]) +KernelHalfWidth;
- kernel1=kerneltable[kernelbase1+k];
-
- g=pSequence[base+1];
- k= (g- image[i+1]) +KernelHalfWidth;
- kernel2=kerneltable[kernelbase2+k];
-
- g=pSequence[base+2];
- k= (g- image[i+2]) +KernelHalfWidth;
- kernel3=kerneltable[kernelbase3+k];
-
- sum+=kernel1*kernel2*kernel3;
- j++;
- }
-
- p=sum / j;
- Pimage1[ig]=p;
- }
- }
- else // RGB color
- {
- unsigned int ig;
- int base;
-
- int kernelbase1;
- int kernelbase2;
- int kernelbase3;
- unsigned int kerneltablewidth=2*KernelHalfWidth+1;
-
- for (i=0,ig=0;i<imagesize;i+=3,ig++)
- {
- // used extimated kernel width to access the right kernel
- kernelbase1=SDbins[i]*kerneltablewidth;
- kernelbase2=SDbins[i+1]*kerneltablewidth;
- kernelbase3=SDbins[i+2]*kerneltablewidth;
-
- sum=0;
- j=0;
- while (j<SampleSize && sum < th)
- {
- base=j*imagesize+i;
- g=pSequence[base];
- k= (g- image[i]) +KernelHalfWidth;
- kernel1=kerneltable[kernelbase1+k];
-
- g=pSequence[base+1];
- k= (g- image[i+1]) +KernelHalfWidth;
- kernel2=kerneltable[kernelbase2+k];
-
- g=pSequence[base+2];
- k= (g- image[i+2]) +KernelHalfWidth;
- kernel3=kerneltable[kernelbase3+k];
-
- sum+=kernel1*kernel2*kernel3;
- j++;
- }
-
- p=sum/j;
- Pimage1[ig]=p;
- }
- }
-
- DisplayPropabilityImageWithThresholding(Pimage1,FGImage,Threshold,rows,cols);
-}
-
-/*********************************************************************/
-
-void NPBGSubtractor::NBBGSubtraction(unsigned char * Frame,
- unsigned char * FGImage,
- unsigned char * FilteredFGImage,
- unsigned char ** DisplayBuffers)
-{
- if(UseColorRatiosFlag)
- BGR2SnGnRn(Frame,tempFrame,rows,cols);
- else
- memcpy(tempFrame,Frame,rows*cols*color_channels);
-
- NPBGSubtraction_Subset_Kernel(tempFrame,FGImage,FilteredFGImage);
- /*NoiseFilter_o(FGImage,DisplayBuffers[3],rows,cols,4);
- BuildImageIndex(DisplayBuffers[3],imageindex,rows,cols);
-
- ExpandOperatorIndexed(DisplayBuffers[3],imageindex,DisplayBuffers[4],imageindex,rows,cols);
- ShrinkOperatorIndexed(DisplayBuffers[4],imageindex,FilteredFGImage,imageindex,rows,cols);
-
- memset(DisplayBuffers[3],0,rows*cols);*/
-}
-
-void NPBGSubtractor::Update(unsigned char * FGMask)
-{
- if(UpdateBGFlag)
- SequenceBGUpdate_Pairs(tempFrame,FGMask);
-}
diff --git a/package_bgs/av/VuMeter.h b/package_bgs/av/VuMeter.h
deleted file mode 100644
index a2334ca..0000000
--- a/package_bgs/av/VuMeter.h
+++ /dev/null
@@ -1,53 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "TBackgroundVuMeter.h"
-#include "../IBGS.h"
-
-class VuMeter : public IBGS
-{
-private:
- TBackgroundVuMeter bgs;
-
- IplImage *frame;
- IplImage *gray;
- IplImage *background;
- IplImage *mask;
-
- bool firstTime;
- bool showOutput;
- bool enableFilter;
-
- int binSize;
- double alpha;
- double threshold;
-
-public:
- VuMeter();
- ~VuMeter();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/bgslibrary.h b/package_bgs/bgslibrary.h
new file mode 100644
index 0000000..3895ba8
--- /dev/null
+++ b/package_bgs/bgslibrary.h
@@ -0,0 +1,65 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include "FrameDifference.h"
+#include "StaticFrameDifference.h"
+#include "WeightedMovingMean.h"
+#include "WeightedMovingVariance.h"
+#include "MixtureOfGaussianV1.h" // Only for OpenCV >= 2
+#include "MixtureOfGaussianV2.h"
+#include "AdaptiveBackgroundLearning.h"
+#include "AdaptiveSelectiveBackgroundLearning.h"
+#include "KNN.h" // Only for OpenCV >= 3
+#include "GMG.h" // Only for OpenCV >= 2.4.3
+#include "DPAdaptiveMedian.h"
+#include "DPGrimsonGMM.h"
+#include "DPZivkovicAGMM.h"
+#include "DPMean.h"
+#include "DPWrenGA.h"
+#include "DPPratiMediod.h"
+#include "DPEigenbackground.h"
+#include "DPTexture.h"
+#include "T2FGMM_UM.h"
+#include "T2FGMM_UV.h"
+#include "T2FMRF_UM.h"
+#include "T2FMRF_UV.h"
+#include "FuzzySugenoIntegral.h"
+#include "FuzzyChoquetIntegral.h"
+#include "LBSimpleGaussian.h"
+#include "LBFuzzyGaussian.h"
+#include "LBMixtureOfGaussians.h"
+#include "LBAdaptiveSOM.h"
+#include "LBFuzzyAdaptiveSOM.h"
+#include "LBP_MRF.h"
+#include "MultiLayer.h"
+#include "PixelBasedAdaptiveSegmenter.h"
+#include "VuMeter.h"
+#include "KDE.h"
+#include "IndependentMultimodal.h"
+#include "MultiCue.h"
+#include "SigmaDelta.h"
+#include "SuBSENSE.h"
+#include "LOBSTER.h"
+#include "PAWCS.h"
+#include "TwoPoints.h"
+#include "ViBe.h"
+
+//#include "_template_/MyBGS.h"
+//#include "_template_/Amber.h"
+
+using namespace bgslibrary::algorithms;
diff --git a/package_bgs/bl/SigmaDeltaBGS.cpp b/package_bgs/bl/SigmaDeltaBGS.cpp
deleted file mode 100644
index a9c7914..0000000
--- a/package_bgs/bl/SigmaDeltaBGS.cpp
+++ /dev/null
@@ -1,85 +0,0 @@
-#include "SigmaDeltaBGS.h"
-
-SigmaDeltaBGS::SigmaDeltaBGS() :
-firstTime(true),
-ampFactor(1),
-minVar(15),
-maxVar(255),
-algorithm(sdLaMa091New()),
-showOutput(true) {
-
- applyParams();
- std::cout << "SigmaDeltaBGS()" << std::endl;
-}
-
-SigmaDeltaBGS::~SigmaDeltaBGS() {
- sdLaMa091Free(algorithm);
- std::cout << "~SigmaDeltaBGS()" << std::endl;
-}
-
-void SigmaDeltaBGS::process(
- const cv::Mat &img_input,
- cv::Mat &img_output,
- cv::Mat &img_bgmodel
- ) {
- if (img_input.empty())
- return;
-
- loadConfig();
-
- if (firstTime) {
- saveConfig();
- sdLaMa091AllocInit_8u_C3R(algorithm, img_input.data, img_input.cols, img_input.rows, img_input.step);
-
- firstTime = false;
- return;
- }
-
- img_output = cv::Mat(img_input.rows, img_input.cols, CV_8UC1);
- cv::Mat img_output_tmp(img_input.rows, img_input.cols, CV_8UC3);
-
- sdLaMa091Update_8u_C3R(algorithm, img_input.data, img_output_tmp.data);
-
- unsigned char* tmpBuffer = (unsigned char*)img_output_tmp.data;
- unsigned char* outBuffer = (unsigned char*)img_output.data;
-
- for (size_t i = 0; i < img_output.total(); ++i) {
- *outBuffer = *tmpBuffer;
-
- ++outBuffer;
- tmpBuffer += img_output_tmp.channels();
- }
-
- if (showOutput)
- cv::imshow("Sigma-Delta", img_output);
-}
-
-void SigmaDeltaBGS::saveConfig() {
- CvFileStorage* fs = cvOpenFileStorage("./config/SigmaDeltaBGS.xml", 0, CV_STORAGE_WRITE);
-
- cvWriteInt(fs, "ampFactor", ampFactor);
- cvWriteInt(fs, "minVar", minVar);
- cvWriteInt(fs, "maxVar", maxVar);
- cvWriteInt(fs, "showOutput", showOutput);
-
- cvReleaseFileStorage(&fs);
-}
-
-void SigmaDeltaBGS::loadConfig() {
- CvFileStorage* fs = cvOpenFileStorage("./config/SigmaDeltaBGS.xml", 0, CV_STORAGE_READ);
-
- ampFactor = cvReadIntByName(fs, 0, "ampFactor", 1);
- minVar = cvReadIntByName(fs, 0, "minVar", 15);
- maxVar = cvReadIntByName(fs, 0, "maxVar", 255);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
- applyParams();
-
- cvReleaseFileStorage(&fs);
-}
-
-void SigmaDeltaBGS::applyParams() {
- sdLaMa091SetAmplificationFactor(algorithm, ampFactor);
- sdLaMa091SetMinimalVariance(algorithm, minVar);
- sdLaMa091SetMaximalVariance(algorithm, maxVar);
-}
diff --git a/package_bgs/bl/SigmaDeltaBGS.h b/package_bgs/bl/SigmaDeltaBGS.h
deleted file mode 100644
index a4be271..0000000
--- a/package_bgs/bl/SigmaDeltaBGS.h
+++ /dev/null
@@ -1,42 +0,0 @@
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-
-//extern "C" {
-#include "sdLaMa091.h"
-//}
-
-class SigmaDeltaBGS : public IBGS {
-private:
-
- bool firstTime;
- unsigned int ampFactor;
- unsigned int minVar;
- unsigned int maxVar;
- sdLaMa091_t* algorithm;
- bool showOutput;
-
-public:
-
- SigmaDeltaBGS();
-
- ~SigmaDeltaBGS();
-
- void process(
- const cv::Mat &img_input,
- cv::Mat &img_output,
- cv::Mat &img_bgmodel
- );
-
-private:
-
- void saveConfig();
-
- void loadConfig();
-
- void applyParams();
-};
diff --git a/package_bgs/bl/stdbool.h b/package_bgs/bl/stdbool.h
deleted file mode 100644
index abeb3b8..0000000
--- a/package_bgs/bl/stdbool.h
+++ /dev/null
@@ -1,16 +0,0 @@
-#pragma once
-
-//#ifndef false
-// #define false 0
-//#endif
-
-//#ifndef true
-// #define true 1
-//#endif
-
-//#ifndef bool
-// #define bool int
-//#endif
-
-// #ifdef _WIN32
-// #endif
diff --git a/package_bgs/ck/MEDefs.cpp b/package_bgs/ck/MEDefs.cpp
deleted file mode 100644
index 9347353..0000000
--- a/package_bgs/ck/MEDefs.cpp
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * This file is part of the AiBO+ project
- *
- * Copyright (C) 2005-2013 Csaba Kertész (csaba.kertesz@gmail.com)
- *
- * AiBO+ is free software; you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation; either version 2 of the License, or
- * (at your option) any later version.
- *
- * AiBO+ is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with this program; if not, write to the Free Software
- * Foundation, Inc., 59 Temple Street #330, Boston, MA 02111-1307, USA.
- *
- */
-
-#include "MEDefs.hpp"
-
-#include <math.h>
-
-float MERound(float number)
-{
- double FracPart = 0.0;
- double IntPart = 0.0;
- float Ret = 0.0;
-
- FracPart = modf((double)number, &IntPart);
- if (number >= 0)
- {
- Ret = (float)(FracPart >= 0.5 ? IntPart+1 : IntPart);
- } else {
- Ret = (float)(FracPart <= -0.5 ? IntPart-1 : IntPart);
- }
- return Ret;
-}
diff --git a/package_bgs/ck/README.TXT b/package_bgs/ck/README.TXT
deleted file mode 100644
index d76c6a3..0000000
--- a/package_bgs/ck/README.TXT
+++ /dev/null
@@ -1,135 +0,0 @@
-###################################################################
-# #
-# MAXFLOW - software for computing mincut/maxflow in a graph #
-# Version 2.2 #
-# http://www.cs.cornell.edu/People/vnk/software.html #
-# #
-# Yuri Boykov (yuri@csd.uwo.ca) #
-# Vladimir Kolmogorov (vnk@cs.cornell.edu) #
-# 2001 #
-# #
-###################################################################
-
-1. Introduction.
-
-This software library implements the maxflow algorithm
-described in
-
- An Experimental Comparison of Min-Cut/Max-Flow Algorithms
- for Energy Minimization in Vision.
- Yuri Boykov and Vladimir Kolmogorov.
- In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),
- September 2004
-
-This algorithm was developed by Yuri Boykov and Vladimir Kolmogorov
-at Siemens Corporate Research. To make it available for public use,
-it was later reimplemented by Vladimir Kolmogorov based on open publications.
-
-If you use this software for research purposes, you should cite
-the aforementioned paper in any resulting publication.
-
-Tested under windows, Visual C++ 6.0 compiler and unix (SunOS 5.8
-and RedHat Linux 7.0, GNU c++ compiler).
-
-##################################################################
-
-2. License.
-
- Copyright 2001 Vladimir Kolmogorov (vnk@cs.cornell.edu), Yuri Boykov (yuri@csd.uwo.ca).
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation; either version 2 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program; if not, write to the Free Software
- Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
-
-##################################################################
-
-3. Graph representation.
-
-There are two versions of the algorithm using different
-graph representations (adjacency list and forward star).
-The former one uses more than twice as much memory as the
-latter one but is 10-20% faster.
-
-Memory allocation (assuming that all capacities are 'short' - 2 bytes):
-
- | Nodes | Arcs
-------------------------------------------
-Adjacency list | *24 bytes | *14 bytes
-Forward star | *28 bytes | 6 bytes
-
-(* means that often it should be rounded up to be a multiple of 4
-- some compilers (e.g. Visual C++) seem to round up elements
-of arrays unless the are structures containing only char[].)
-
-Note that arcs are always added in pairs - in forward and reverse directions.
-Arcs between nodes and terminals (the source and the sink) are
-not stored as arcs, but rather as a part of nodes.
-
-The assumption for the forward star representation is that
-the maximum number of arcs per node (except the source
-and the sink) is much less than ARC_BLOCK_SIZE (1024 by default).
-
-Both versions have the same interface.
-
-##################################################################
-
-4. Example usage.
-
-This section shows how to use the library to compute
-a minimum cut on the following graph:
-
- SOURCE
- / \
- 1/ \2
- / 3 \
- node0 -----> node1
- | <----- |
- | 4 |
- \ /
- 5\ /6
- \ /
- SINK
-
-///////////////////////////////////////////////////
-
-#include <stdio.h>
-#include "graph.h"
-
-void main()
-{
- Graph::node_id nodes[2];
- Graph *g = new Graph();
-
- nodes[0] = g -> add_node();
- nodes[1] = g -> add_node();
- g -> set_tweights(nodes[0], 1, 5);
- g -> set_tweights(nodes[1], 2, 6);
- g -> add_edge(nodes[0], nodes[1], 3, 4);
-
- Graph::flowtype flow = g -> maxflow();
-
- printf("Flow = %d\n", flow);
- printf("Minimum cut:\n");
- if (g->what_segment(nodes[0]) == Graph::SOURCE)
- printf("node0 is in the SOURCE set\n");
- else
- printf("node0 is in the SINK set\n");
- if (g->what_segment(nodes[1]) == Graph::SOURCE)
- printf("node1 is in the SOURCE set\n");
- else
- printf("node1 is in the SINK set\n");
-
- delete g;
-}
-
-///////////////////////////////////////////////////
diff --git a/package_bgs/db/IndependentMultimodalBGS.cpp b/package_bgs/db/IndependentMultimodalBGS.cpp
deleted file mode 100644
index 5312075..0000000
--- a/package_bgs/db/IndependentMultimodalBGS.cpp
+++ /dev/null
@@ -1,54 +0,0 @@
-#include "IndependentMultimodalBGS.h"
-
-IndependentMultimodalBGS::IndependentMultimodalBGS() : fps(10), firstTime(true), showOutput(true){
- pIMBS = new BackgroundSubtractorIMBS(fps);
-}
-IndependentMultimodalBGS::~IndependentMultimodalBGS(){
- delete pIMBS;
-}
-
-void IndependentMultimodalBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
-{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if (firstTime)
- saveConfig();
-
- //get the fgmask and update the background model
- pIMBS->apply(img_input, img_foreground);
-
- //get background image
- pIMBS->getBackgroundImage(img_background);
-
- img_foreground.copyTo(img_output);
- img_background.copyTo(img_bgmodel);
-
- if (showOutput)
- {
- cv::imshow("IMBS FG", img_foreground);
- cv::imshow("IMBS BG", img_background);
- }
-
- firstTime = false;
-}
-
-void IndependentMultimodalBGS::saveConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/IndependentMultimodalBGS.xml", 0, CV_STORAGE_WRITE);
-
- cvWriteInt(fs, "showOutput", showOutput);
-
- cvReleaseFileStorage(&fs);
-}
-
-void IndependentMultimodalBGS::loadConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/IndependentMultimodalBGS.xml", 0, CV_STORAGE_READ);
-
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
- cvReleaseFileStorage(&fs);
-}
diff --git a/package_bgs/db/IndependentMultimodalBGS.h b/package_bgs/db/IndependentMultimodalBGS.h
deleted file mode 100644
index 64b83bd..0000000
--- a/package_bgs/db/IndependentMultimodalBGS.h
+++ /dev/null
@@ -1,29 +0,0 @@
-#pragma once
-
-#include <opencv2/opencv.hpp>
-
-
-#include "imbs.hpp"
-
-#include "../IBGS.h"
-
-class IndependentMultimodalBGS : public IBGS
-{
-private:
- BackgroundSubtractorIMBS* pIMBS;
- int fps;
- bool firstTime;
- cv::Mat img_foreground;
- cv::Mat img_background;
- bool showOutput;
-
-public:
- IndependentMultimodalBGS();
- ~IndependentMultimodalBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
diff --git a/package_bgs/dp/AdaptiveMedianBGS.cpp b/package_bgs/dp/AdaptiveMedianBGS.cpp
index 16b3988..da1add9 100644
--- a/package_bgs/dp/AdaptiveMedianBGS.cpp
+++ b/package_bgs/dp/AdaptiveMedianBGS.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* AdaptiveMedianBGS.cpp
*
-* Purpose: Implementation of the simple adaptive median background
+* Purpose: Implementation of the simple adaptive median background
* subtraction algorithm described in:
* "Segmentation and tracking of piglets in images"
* by McFarlane and Schofield
@@ -37,77 +37,77 @@ using namespace Algorithms::BackgroundSubtraction;
void AdaptiveMedianBGS::Initalize(const BgsParams& param)
{
- m_params = (AdaptiveMedianParams&)param;
+ m_params = (AdaptiveMedianParams&)param;
- m_median = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
- cvSet(m_median.Ptr(), CV_RGB(BACKGROUND,BACKGROUND,BACKGROUND));
+ m_median = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ cvSet(m_median.Ptr(), CV_RGB(BACKGROUND, BACKGROUND, BACKGROUND));
}
RgbImage* AdaptiveMedianBGS::Background()
{
- return &m_median;
+ return &m_median;
}
void AdaptiveMedianBGS::InitModel(const RgbImage& data)
{
- // initialize the background model
- for (unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- m_median(r,c) = data(r,c);
- }
- }
+ // initialize the background model
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ m_median(r, c) = data(r, c);
+ }
+ }
}
-void AdaptiveMedianBGS::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void AdaptiveMedianBGS::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- if(frame_num % m_params.SamplingRate() == 1)
- {
- // update background model
- for (unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // perform conditional updating only if we are passed the learning phase
- if(update_mask(r,c) == BACKGROUND || frame_num < m_params.LearningFrames())
- {
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- if(data(r,c,ch) > m_median(r,c,ch))
- {
- m_median(r,c,ch)++;
- }
- else if(data(r,c,ch) < m_median(r,c,ch))
- {
- m_median(r,c,ch)--;
- }
- }
- }
- }
- }
- }
+ if (frame_num % m_params.SamplingRate() == 1)
+ {
+ // update background model
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // perform conditional updating only if we are passed the learning phase
+ if (update_mask(r, c) == BACKGROUND || frame_num < m_params.LearningFrames())
+ {
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ if (data(r, c, ch) > m_median(r, c, ch))
+ {
+ m_median(r, c, ch)++;
+ }
+ else if (data(r, c, ch) < m_median(r, c, ch))
+ {
+ m_median(r, c, ch)--;
+ }
+ }
+ }
+ }
+ }
+ }
}
-void AdaptiveMedianBGS::SubtractPixel(int r, int c, const RgbPixel& pixel,
- unsigned char& low_threshold, unsigned char& high_threshold)
+void AdaptiveMedianBGS::SubtractPixel(int r, int c, const RgbPixel& pixel,
+ unsigned char& low_threshold, unsigned char& high_threshold)
{
- // perform background subtraction
- low_threshold = high_threshold = FOREGROUND;
-
- int diffR = abs(pixel(0) - m_median(r,c,0));
- int diffG = abs(pixel(1) - m_median(r,c,1));
- int diffB = abs(pixel(2) - m_median(r,c,2));
-
- if(diffR <= m_params.LowThreshold() && diffG <= m_params.LowThreshold() && diffB <= m_params.LowThreshold())
- {
- low_threshold = BACKGROUND;
- }
-
- if(diffR <= m_params.HighThreshold() && diffG <= m_params.HighThreshold() && diffB <= m_params.HighThreshold())
- {
- high_threshold = BACKGROUND;
- }
+ // perform background subtraction
+ low_threshold = high_threshold = FOREGROUND;
+
+ int diffR = abs(pixel(0) - m_median(r, c, 0));
+ int diffG = abs(pixel(1) - m_median(r, c, 1));
+ int diffB = abs(pixel(2) - m_median(r, c, 2));
+
+ if (diffR <= m_params.LowThreshold() && diffG <= m_params.LowThreshold() && diffB <= m_params.LowThreshold())
+ {
+ low_threshold = BACKGROUND;
+ }
+
+ if (diffR <= m_params.HighThreshold() && diffG <= m_params.HighThreshold() && diffB <= m_params.HighThreshold())
+ {
+ high_threshold = BACKGROUND;
+ }
}
///////////////////////////////////////////////////////////////////////////////
@@ -118,23 +118,23 @@ void AdaptiveMedianBGS::SubtractPixel(int r, int c, const RgbPixel& pixel,
// (the memory should already be reserved)
// values: 255-foreground, 0-background
///////////////////////////////////////////////////////////////////////////////
-void AdaptiveMedianBGS::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void AdaptiveMedianBGS::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
- unsigned char low_threshold, high_threshold;
-
- // update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // perform background subtraction
- SubtractPixel(r, c, data(r,c), low_threshold, high_threshold);
-
- // setup silhouette mask
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
- }
- }
+ unsigned char low_threshold, high_threshold;
+
+ // update each pixel of the image
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // perform background subtraction
+ SubtractPixel(r, c, data(r, c), low_threshold, high_threshold);
+
+ // setup silhouette mask
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
+ }
+ }
}
diff --git a/package_bgs/dp/AdaptiveMedianBGS.h b/package_bgs/dp/AdaptiveMedianBGS.h
index d199b81..79a04b3 100644
--- a/package_bgs/dp/AdaptiveMedianBGS.h
+++ b/package_bgs/dp/AdaptiveMedianBGS.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* AdaptiveMedianBGS.hpp
*
-* Purpose: Implementation of the simple adaptive median background
+* Purpose: Implementation of the simple adaptive median background
* subtraction algorithm described in:
* "Segmentation and tracking of piglets in images"
* by McFarlane and Schofield
@@ -26,64 +26,65 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* Author: Donovan Parks, September 2007
Example:
- Algorithms::BackgroundSubtraction::AdaptiveMedianParams params;
- params.SetFrameSize(width, height);
- params.LowThreshold() = 40;
- params.HighThreshold() = 2*params.LowThreshold();
- params.SamplingRate() = 7;
- params.LearningFrames() = 30;
-
- Algorithms::BackgroundSubtraction::AdaptiveMedianBGS bgs;
- bgs.Initalize(params);
+ Algorithms::BackgroundSubtraction::AdaptiveMedianParams params;
+ params.SetFrameSize(width, height);
+ params.LowThreshold() = 40;
+ params.HighThreshold() = 2*params.LowThreshold();
+ params.SamplingRate() = 7;
+ params.LearningFrames() = 30;
+
+ Algorithms::BackgroundSubtraction::AdaptiveMedianBGS bgs;
+ bgs.Initalize(params);
******************************************************************************/
+#pragma once
#include "Bgs.h"
namespace Algorithms
{
- namespace BackgroundSubtraction
- {
- // --- Parameters used by the Adaptive Median BGS algorithm ---
- class AdaptiveMedianParams : public BgsParams
- {
- public:
- unsigned char &LowThreshold() { return m_low_threshold; }
- unsigned char &HighThreshold() { return m_high_threshold; }
+ namespace BackgroundSubtraction
+ {
+ // --- Parameters used by the Adaptive Median BGS algorithm ---
+ class AdaptiveMedianParams : public BgsParams
+ {
+ public:
+ unsigned char &LowThreshold() { return m_low_threshold; }
+ unsigned char &HighThreshold() { return m_high_threshold; }
- int &SamplingRate() { return m_samplingRate; }
- int &LearningFrames() { return m_learning_frames; }
+ int &SamplingRate() { return m_samplingRate; }
+ int &LearningFrames() { return m_learning_frames; }
- private:
- unsigned char m_low_threshold;
- unsigned char m_high_threshold;
+ private:
+ unsigned char m_low_threshold;
+ unsigned char m_high_threshold;
- int m_samplingRate;
- int m_learning_frames;
- };
+ int m_samplingRate;
+ int m_learning_frames;
+ };
- // --- Adaptive Median BGS algorithm ---
- class AdaptiveMedianBGS : public Bgs
- {
- public:
- virtual ~AdaptiveMedianBGS() {}
+ // --- Adaptive Median BGS algorithm ---
+ class AdaptiveMedianBGS : public Bgs
+ {
+ public:
+ virtual ~AdaptiveMedianBGS() {}
- void Initalize(const BgsParams& param);
+ void Initalize(const BgsParams& param);
- void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+ void InitModel(const RgbImage& data);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
- RgbImage* Background();
+ RgbImage* Background();
- private:
- void SubtractPixel(int r, int c, const RgbPixel& pixel,
- unsigned char& low_threshold, unsigned char& high_threshold);
+ private:
+ void SubtractPixel(int r, int c, const RgbPixel& pixel,
+ unsigned char& low_threshold, unsigned char& high_threshold);
- AdaptiveMedianParams m_params;
+ AdaptiveMedianParams m_params;
- RgbImage m_median;
- };
- }
+ RgbImage m_median;
+ };
+ }
}
diff --git a/package_bgs/dp/Bgs.h b/package_bgs/dp/Bgs.h
index 5f91246..26fff70 100644
--- a/package_bgs/dp/Bgs.h
+++ b/package_bgs/dp/Bgs.h
@@ -23,45 +23,41 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* Author: Donovan Parks, October 2007
*
******************************************************************************/
-
-#ifndef BGS_H_
-#define BGS_H_
+#pragma once
#include "Image.h"
#include "BgsParams.h"
namespace Algorithms
{
- namespace BackgroundSubtraction
- {
- class Bgs
- {
- public:
- static const int BACKGROUND = 0;
- static const int FOREGROUND = 255;
+namespace BackgroundSubtraction
+{
+class Bgs
+{
+public:
+ static const int BACKGROUND = 0;
+ static const int FOREGROUND = 255;
- virtual ~Bgs() {}
+ virtual ~Bgs() {}
- // Initialize any data required by the BGS algorithm. Should be called once before calling
- // any of the following functions.
- virtual void Initalize(const BgsParams& param) = 0;
+ // Initialize any data required by the BGS algorithm. Should be called once before calling
+ // any of the following functions.
+ virtual void Initalize(const BgsParams& param) = 0;
- // Initialize the background model. Typically, the background model is initialized using the first
- // frame of the incoming video stream, but alternatives are possible.
- virtual void InitModel(const RgbImage& data) = 0;
+ // Initialize the background model. Typically, the background model is initialized using the first
+ // frame of the incoming video stream, but alternatives are possible.
+ virtual void InitModel(const RgbImage& data) = 0;
- // Subtract the current frame from the background model and produce a binary foreground mask using
- // both a low and high threshold value.
- virtual void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask) = 0;
+ // Subtract the current frame from the background model and produce a binary foreground mask using
+ // both a low and high threshold value.
+ virtual void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask) = 0;
- // Update the background model. Only pixels set to background in update_mask are updated.
- virtual void Update(int frame_num, const RgbImage& data, const BwImage& update_mask) = 0;
+ // Update the background model. Only pixels set to background in update_mask are updated.
+ virtual void Update(int frame_num, const RgbImage& data, const BwImage& update_mask) = 0;
- // Return the current background model.
- virtual RgbImage *Background() = 0;
- };
- }
+ // Return the current background model.
+ virtual RgbImage *Background() = 0;
+};
+}
}
-
-#endif
diff --git a/package_bgs/dp/BgsParams.h b/package_bgs/dp/BgsParams.h
index a63b1ac..d2e7d29 100644
--- a/package_bgs/dp/BgsParams.h
+++ b/package_bgs/dp/BgsParams.h
@@ -24,36 +24,32 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* Author: Donovan Parks, May 2008
*
******************************************************************************/
-
-#ifndef BGS_PARAMS_H_
-#define BGS_PARAMS_H_
+#pragma once
namespace Algorithms
{
- namespace BackgroundSubtraction
- {
- class BgsParams
- {
- public:
- virtual ~BgsParams() {}
-
- virtual void SetFrameSize(unsigned int width, unsigned int height)
- {
- m_width = width;
- m_height = height;
- m_size = width*height;
- }
-
- unsigned int &Width() { return m_width; }
- unsigned int &Height() { return m_height; }
- unsigned int &Size() { return m_size; }
-
- protected:
- unsigned int m_width;
- unsigned int m_height;
- unsigned int m_size;
- };
- }
+namespace BackgroundSubtraction
+{
+class BgsParams
+{
+public:
+ virtual ~BgsParams() {}
+
+ virtual void SetFrameSize(unsigned int width, unsigned int height)
+ {
+ m_width = width;
+ m_height = height;
+ m_size = width*height;
+ }
+
+ unsigned int &Width() { return m_width; }
+ unsigned int &Height() { return m_height; }
+ unsigned int &Size() { return m_size; }
+
+protected:
+ unsigned int m_width;
+ unsigned int m_height;
+ unsigned int m_size;
+};
+}
}
-
-#endif
diff --git a/package_bgs/dp/DPAdaptiveMedianBGS.cpp b/package_bgs/dp/DPAdaptiveMedianBGS.cpp
deleted file mode 100644
index 0ae68fe..0000000
--- a/package_bgs/dp/DPAdaptiveMedianBGS.cpp
+++ /dev/null
@@ -1,113 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#include "DPAdaptiveMedianBGS.h"
-
-DPAdaptiveMedianBGS::DPAdaptiveMedianBGS() : firstTime(true), frameNumber(0), threshold(40), samplingRate(7), learningFrames(30), showOutput(true)
-{
- std::cout << "DPAdaptiveMedianBGS()" << std::endl;
-}
-
-DPAdaptiveMedianBGS::~DPAdaptiveMedianBGS()
-{
- std::cout << "~DPAdaptiveMedianBGS()" << std::endl;
-}
-
-void DPAdaptiveMedianBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
-{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if(firstTime)
- saveConfig();
-
- frame = new IplImage(img_input);
-
- if(firstTime)
- frame_data.ReleaseMemory(false);
- frame_data = frame;
-
- if(firstTime)
- {
- int width = img_input.size().width;
- int height = img_input.size().height;
-
- lowThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
- lowThresholdMask.Ptr()->origin = IPL_ORIGIN_BL;
-
- highThresholdMask = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);
- highThresholdMask.Ptr()->origin = IPL_ORIGIN_BL;
-
- params.SetFrameSize(width, height);
- params.LowThreshold() = threshold;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
- params.SamplingRate() = samplingRate;
- params.LearningFrames() = learningFrames;
-
- bgs.Initalize(params);
- bgs.InitModel(frame_data);
-
- std::cout << "threshold: " << threshold << std::endl;
- std::cout << "samplingRate: " << samplingRate << std::endl;
- std::cout << "learningFrames: " << learningFrames << std::endl;
- std::cout << "showOutput: " << showOutput << std::endl;
- }
-
- bgs.Subtract(frameNumber, frame_data, lowThresholdMask, highThresholdMask);
- lowThresholdMask.Clear();
- bgs.Update(frameNumber, frame_data, lowThresholdMask);
-
- cv::Mat foreground(highThresholdMask.Ptr());
- cv::Mat background(bgs.Background()->Ptr());
-
- if(showOutput){
- cv::imshow("Adaptive Median FG (McFarlane&Schofield)", foreground);
- cv::imshow("Adaptive Median BG (McFarlane&Schofield)", background);
- }
-
- foreground.copyTo(img_output);
- background.copyTo(img_bgmodel);
-
- delete frame;
- firstTime = false;
- frameNumber++;
-}
-
-void DPAdaptiveMedianBGS::saveConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPAdaptiveMedianBGS.xml", 0, CV_STORAGE_WRITE);
-
- cvWriteInt(fs, "threshold", threshold);
- cvWriteInt(fs, "samplingRate", samplingRate);
- cvWriteInt(fs, "learningFrames", learningFrames);
- cvWriteInt(fs, "showOutput", showOutput);
-
- cvReleaseFileStorage(&fs);
-}
-
-void DPAdaptiveMedianBGS::loadConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/DPAdaptiveMedianBGS.xml", 0, CV_STORAGE_READ);
-
- threshold = cvReadIntByName(fs, 0, "threshold", 40);
- samplingRate = cvReadIntByName(fs, 0, "samplingRate", 7);
- learningFrames = cvReadIntByName(fs, 0, "learningFrames", 30);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
- cvReleaseFileStorage(&fs);
-}
diff --git a/package_bgs/dp/DPAdaptiveMedianBGS.h b/package_bgs/dp/DPAdaptiveMedianBGS.h
deleted file mode 100644
index a5dd387..0000000
--- a/package_bgs/dp/DPAdaptiveMedianBGS.h
+++ /dev/null
@@ -1,56 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "AdaptiveMedianBGS.h"
-
-using namespace Algorithms::BackgroundSubtraction;
-
-class DPAdaptiveMedianBGS : public IBGS
-{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- AdaptiveMedianParams params;
- AdaptiveMedianBGS bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- int threshold;
- int samplingRate;
- int learningFrames;
- bool showOutput;
-
-public:
- DPAdaptiveMedianBGS();
- ~DPAdaptiveMedianBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
diff --git a/package_bgs/dp/DPPratiMediodBGS.h b/package_bgs/dp/DPPratiMediodBGS.h
deleted file mode 100644
index 8aa6416..0000000
--- a/package_bgs/dp/DPPratiMediodBGS.h
+++ /dev/null
@@ -1,57 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "PratiMediodBGS.h"
-
-using namespace Algorithms::BackgroundSubtraction;
-
-class DPPratiMediodBGS : public IBGS
-{
-private:
- bool firstTime;
- long frameNumber;
- IplImage* frame;
- RgbImage frame_data;
-
- PratiParams params;
- PratiMediodBGS bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- int threshold;
- int samplingRate;
- int historySize;
- int weight;
- bool showOutput;
-
-public:
- DPPratiMediodBGS();
- ~DPPratiMediodBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
diff --git a/package_bgs/dp/DPTextureBGS.h b/package_bgs/dp/DPTextureBGS.h
deleted file mode 100644
index c29e7e9..0000000
--- a/package_bgs/dp/DPTextureBGS.h
+++ /dev/null
@@ -1,60 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "TextureBGS.h"
-//#include "ConnectedComponents.h"
-
-class DPTextureBGS : public IBGS
-{
-private:
- bool firstTime;
- bool showOutput;
-
- int width;
- int height;
- int size;
- TextureBGS bgs;
- IplImage* frame;
- RgbImage image;
- BwImage fgMask;
- BwImage tempMask;
- TextureArray* bgModel;
- RgbImage texture;
- unsigned char* modeArray;
- TextureHistogram* curTextureHist;
- //ConnectedComponents cc;
- //CBlobResult largeBlobs;
- //IplConvKernel* dilateElement;
- //IplConvKernel* erodeElement;
- //bool enableFiltering;
-
-public:
- DPTextureBGS();
- ~DPTextureBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/dp/Eigenbackground.cpp b/package_bgs/dp/Eigenbackground.cpp
index 2d2c3ef..dceb4cd 100644
--- a/package_bgs/dp/Eigenbackground.cpp
+++ b/package_bgs/dp/Eigenbackground.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* Eigenbackground.cpp
*
-* Purpose: Implementation of the Eigenbackground background subtraction
+* Purpose: Implementation of the Eigenbackground background subtraction
* algorithm developed by Oliver et al.
*
* Author: Donovan Parks, September 2007
@@ -34,157 +34,157 @@ using namespace Algorithms::BackgroundSubtraction;
Eigenbackground::Eigenbackground()
{
- m_pcaData = NULL;
- m_pcaAvg = NULL;
- m_eigenValues = NULL;
- m_eigenVectors = NULL;
+ m_pcaData = NULL;
+ m_pcaAvg = NULL;
+ m_eigenValues = NULL;
+ m_eigenVectors = NULL;
}
Eigenbackground::~Eigenbackground()
{
- if(m_pcaData != NULL) cvReleaseMat(&m_pcaData);
- if(m_pcaAvg != NULL) cvReleaseMat(&m_pcaAvg);
- if(m_eigenValues != NULL) cvReleaseMat(&m_eigenValues);
- if(m_eigenVectors != NULL) cvReleaseMat(&m_eigenVectors);
+ if (m_pcaData != NULL) cvReleaseMat(&m_pcaData);
+ if (m_pcaAvg != NULL) cvReleaseMat(&m_pcaAvg);
+ if (m_eigenValues != NULL) cvReleaseMat(&m_eigenValues);
+ if (m_eigenVectors != NULL) cvReleaseMat(&m_eigenVectors);
}
void Eigenbackground::Initalize(const BgsParams& param)
{
- m_params = (EigenbackgroundParams&)param;
-
- m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
- m_background.Clear();
+ m_params = (EigenbackgroundParams&)param;
+
+ m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ m_background.Clear();
}
void Eigenbackground::InitModel(const RgbImage& data)
{
- if(m_pcaData != NULL) cvReleaseMat(&m_pcaData);
- if(m_pcaAvg != NULL) cvReleaseMat(&m_pcaAvg);
- if(m_eigenValues != NULL) cvReleaseMat(&m_eigenValues);
- if(m_eigenVectors != NULL) cvReleaseMat(&m_eigenVectors);
+ if (m_pcaData != NULL) cvReleaseMat(&m_pcaData);
+ if (m_pcaAvg != NULL) cvReleaseMat(&m_pcaAvg);
+ if (m_eigenValues != NULL) cvReleaseMat(&m_eigenValues);
+ if (m_eigenVectors != NULL) cvReleaseMat(&m_eigenVectors);
- m_pcaData = cvCreateMat(m_params.HistorySize(), m_params.Size()*3, CV_8UC1);
+ m_pcaData = cvCreateMat(m_params.HistorySize(), m_params.Size() * 3, CV_8UC1);
- m_background.Clear();
+ m_background.Clear();
}
-void Eigenbackground::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void Eigenbackground::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- // the eigenbackground model is not updated (serious limitation!)
+ // the eigenbackground model is not updated (serious limitation!)
}
-void Eigenbackground::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void Eigenbackground::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
- // create eigenbackground
- if(frame_num == m_params.HistorySize())
- {
- // create the eigenspace
- m_pcaAvg = cvCreateMat( 1, m_pcaData->cols, CV_32F );
- m_eigenValues = cvCreateMat( m_pcaData->rows, 1, CV_32F );
- m_eigenVectors = cvCreateMat( m_pcaData->rows, m_pcaData->cols, CV_32F );
- cvCalcPCA(m_pcaData, m_pcaAvg, m_eigenValues, m_eigenVectors, CV_PCA_DATA_AS_ROW);
-
- int index = 0;
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- for(int ch = 0; ch < m_background.Ptr()->nChannels; ++ch)
- {
- m_background(r,c,0) = static_cast<unsigned char>(cvmGet(m_pcaAvg,0,index)+0.5);
- index++;
- }
- }
- }
- }
-
- if(frame_num >= m_params.HistorySize())
- {
- // project new image into the eigenspace
- int w = data.Ptr()->width;
- int h = data.Ptr()->height;
- int ch = data.Ptr()->nChannels;
- CvMat* dataPt = cvCreateMat(1, w*h*ch, CV_8UC1);
- CvMat data_row;
- cvGetRow(dataPt, &data_row, 0);
- cvReshape(&data_row, &data_row, 3, data.Ptr()->height);
- cvCopy(data.Ptr(), &data_row);
-
- CvMat* proj = cvCreateMat(1, m_params.EmbeddedDim(), CV_32F);
- cvProjectPCA(dataPt, m_pcaAvg, m_eigenVectors, proj);
-
- // reconstruct point
- CvMat* result = cvCreateMat(1, m_pcaData->cols, CV_32F);
- cvBackProjectPCA(proj, m_pcaAvg, m_eigenVectors, result);
-
- // calculate Euclidean distance between new image and its eigenspace projection
- int index = 0;
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- double dist = 0;
- bool bgLow = true;
- bool bgHigh = true;
- for(int ch = 0; ch < 3; ++ch)
- {
- dist = (data(r,c,ch) - cvmGet(result,0,index))*(data(r,c,ch) - cvmGet(result,0,index));
- if(dist > m_params.LowThreshold())
- bgLow = false;
- if(dist > m_params.HighThreshold())
- bgHigh = false;
- index++;
- }
-
- if(!bgLow)
- {
- low_threshold_mask(r,c) = FOREGROUND;
- }
- else
- {
- low_threshold_mask(r,c) = BACKGROUND;
- }
-
- if(!bgHigh)
- {
- high_threshold_mask(r,c) = FOREGROUND;
- }
- else
- {
- high_threshold_mask(r,c) = BACKGROUND;
- }
- }
- }
-
- cvReleaseMat(&result);
- cvReleaseMat(&proj);
- cvReleaseMat(&dataPt);
- }
- else
- {
- // set entire image to background since there is not enough information yet
- // to start performing background subtraction
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- low_threshold_mask(r,c) = BACKGROUND;
- high_threshold_mask(r,c) = BACKGROUND;
- }
- }
- }
-
- UpdateHistory(frame_num, data);
+ // create eigenbackground
+ if (frame_num == m_params.HistorySize())
+ {
+ // create the eigenspace
+ m_pcaAvg = cvCreateMat(1, m_pcaData->cols, CV_32F);
+ m_eigenValues = cvCreateMat(m_pcaData->rows, 1, CV_32F);
+ m_eigenVectors = cvCreateMat(m_pcaData->rows, m_pcaData->cols, CV_32F);
+ cvCalcPCA(m_pcaData, m_pcaAvg, m_eigenValues, m_eigenVectors, CV_PCA_DATA_AS_ROW);
+
+ int index = 0;
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ for (int ch = 0; ch < m_background.Ptr()->nChannels; ++ch)
+ {
+ m_background(r, c, 0) = static_cast<unsigned char>(cvmGet(m_pcaAvg, 0, index) + 0.5);
+ index++;
+ }
+ }
+ }
+ }
+
+ if (frame_num >= m_params.HistorySize())
+ {
+ // project new image into the eigenspace
+ int w = data.Ptr()->width;
+ int h = data.Ptr()->height;
+ int ch = data.Ptr()->nChannels;
+ CvMat* dataPt = cvCreateMat(1, w*h*ch, CV_8UC1);
+ CvMat data_row;
+ cvGetRow(dataPt, &data_row, 0);
+ cvReshape(&data_row, &data_row, 3, data.Ptr()->height);
+ cvCopy(data.Ptr(), &data_row);
+
+ CvMat* proj = cvCreateMat(1, m_params.EmbeddedDim(), CV_32F);
+ cvProjectPCA(dataPt, m_pcaAvg, m_eigenVectors, proj);
+
+ // reconstruct point
+ CvMat* result = cvCreateMat(1, m_pcaData->cols, CV_32F);
+ cvBackProjectPCA(proj, m_pcaAvg, m_eigenVectors, result);
+
+ // calculate Euclidean distance between new image and its eigenspace projection
+ int index = 0;
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ double dist = 0;
+ bool bgLow = true;
+ bool bgHigh = true;
+ for (int ch = 0; ch < 3; ++ch)
+ {
+ dist = (data(r, c, ch) - cvmGet(result, 0, index))*(data(r, c, ch) - cvmGet(result, 0, index));
+ if (dist > m_params.LowThreshold())
+ bgLow = false;
+ if (dist > m_params.HighThreshold())
+ bgHigh = false;
+ index++;
+ }
+
+ if (!bgLow)
+ {
+ low_threshold_mask(r, c) = FOREGROUND;
+ }
+ else
+ {
+ low_threshold_mask(r, c) = BACKGROUND;
+ }
+
+ if (!bgHigh)
+ {
+ high_threshold_mask(r, c) = FOREGROUND;
+ }
+ else
+ {
+ high_threshold_mask(r, c) = BACKGROUND;
+ }
+ }
+ }
+
+ cvReleaseMat(&result);
+ cvReleaseMat(&proj);
+ cvReleaseMat(&dataPt);
+ }
+ else
+ {
+ // set entire image to background since there is not enough information yet
+ // to start performing background subtraction
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ low_threshold_mask(r, c) = BACKGROUND;
+ high_threshold_mask(r, c) = BACKGROUND;
+ }
+ }
+ }
+
+ UpdateHistory(frame_num, data);
}
void Eigenbackground::UpdateHistory(int frame_num, const RgbImage& new_frame)
{
- if(frame_num < m_params.HistorySize())
- {
- CvMat src_row;
- cvGetRow(m_pcaData, &src_row, frame_num);
- cvReshape(&src_row, &src_row, 3, new_frame.Ptr()->height);
- cvCopy(new_frame.Ptr(), &src_row);
- }
+ if (frame_num < m_params.HistorySize())
+ {
+ CvMat src_row;
+ cvGetRow(m_pcaData, &src_row, frame_num);
+ cvReshape(&src_row, &src_row, 3, new_frame.Ptr()->height);
+ cvCopy(new_frame.Ptr(), &src_row);
+ }
}
diff --git a/package_bgs/dp/Eigenbackground.h b/package_bgs/dp/Eigenbackground.h
index 721b735..10ed189 100644
--- a/package_bgs/dp/Eigenbackground.h
+++ b/package_bgs/dp/Eigenbackground.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* Eigenbackground.hpp
*
-* Purpose: Implementation of the Eigenbackground background subtraction
+* Purpose: Implementation of the Eigenbackground background subtraction
* algorithm developed by Oliver et al.
*
* Author: Donovan Parks, September 2007
@@ -30,16 +30,14 @@ Example:
Algorithms::BackgroundSubtraction::EigenbackgroundParams params;
params.SetFrameSize(width, height);
params.LowThreshold() = 15*15;
-params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
params.HistorySize() = 100;
params.EmbeddedDim() = 20;
Algorithms::BackgroundSubtraction::Eigenbackground bgs;
bgs.Initalize(params);
******************************************************************************/
-
-#ifndef _ELGAMMAL_H_
-#define _ELGAMMAL_H_
+#pragma once
#include "Bgs.h"
@@ -77,9 +75,9 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background() { return &m_background; }
@@ -90,12 +88,10 @@ namespace Algorithms
CvMat* m_pcaData;
CvMat* m_pcaAvg;
- CvMat* m_eigenValues;
+ CvMat* m_eigenValues;
CvMat* m_eigenVectors;
RgbImage m_background;
};
}
}
-
-#endif
diff --git a/package_bgs/dp/Error.h b/package_bgs/dp/Error.h
index cdbb222..81cbbeb 100644
--- a/package_bgs/dp/Error.h
+++ b/package_bgs/dp/Error.h
@@ -23,14 +23,9 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* Author: Donovan Parks, July 2007
*
******************************************************************************/
-
-#ifndef ERROR_H
-#define ERROR_H
+#pragma once
bool Error(const char* msg, const char* code, int data);
-
bool TraceInit(const char* filename);
void Trace(const char* msg);
void TraceClose();
-
-#endif
diff --git a/package_bgs/dp/GrimsonGMM.cpp b/package_bgs/dp/GrimsonGMM.cpp
index ff9c262..4cf6f35 100644
--- a/package_bgs/dp/GrimsonGMM.cpp
+++ b/package_bgs/dp/GrimsonGMM.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* GrimsonGMM.cpp
*
-* Purpose: Implementation of the Gaussian mixture model (GMM) background
+* Purpose: Implementation of the Gaussian mixture model (GMM) background
* subtraction described in:
* "Adaptive background mixture models for real-time tracking"
* by Chris Stauffer and W.E.L Grimson
@@ -26,16 +26,16 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* Author: Donovan Parks, September 2007
*
* This code is based on code by Z. Zivkovic's written for his enhanced GMM
-* background subtraction algorithm:
+* background subtraction algorithm:
*
* "Improved adaptive Gausian mixture model for background subtraction"
-* Z.Zivkovic
+* Z.Zivkovic
* International Conference Pattern Recognition, UK, August, 2004
*
*
-* "Efficient Adaptive Density Estimapion per Image Pixel for the
+* "Efficient Adaptive Density Estimapion per Image Pixel for the
* Task of Background Subtraction"
-* Z.Zivkovic, F. van der Heijden
+* Z.Zivkovic, F. van der Heijden
* Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
*
* Zivkovic's code can be obtained at: www.zoranz.net
@@ -47,252 +47,252 @@ using namespace Algorithms::BackgroundSubtraction;
int compareGMM(const void* _gmm1, const void* _gmm2)
{
- GMM gmm1 = *(GMM*)_gmm1;
- GMM gmm2 = *(GMM*)_gmm2;
-
- if(gmm1.significants < gmm2.significants)
- return 1;
- else if(gmm1.significants == gmm2.significants)
- return 0;
- else
- return -1;
+ GMM gmm1 = *(GMM*)_gmm1;
+ GMM gmm2 = *(GMM*)_gmm2;
+
+ if (gmm1.significants < gmm2.significants)
+ return 1;
+ else if (gmm1.significants == gmm2.significants)
+ return 0;
+ else
+ return -1;
}
GrimsonGMM::GrimsonGMM()
{
- m_modes = NULL;
+ m_modes = NULL;
}
GrimsonGMM::~GrimsonGMM()
{
- delete[] m_modes;
+ delete[] m_modes;
}
void GrimsonGMM::Initalize(const BgsParams& param)
{
- m_params = (GrimsonParams&)param;
+ m_params = (GrimsonParams&)param;
- // Tbf - the threshold
- m_bg_threshold = 0.75f; // 1-cf from the paper
+ // Tbf - the threshold
+ m_bg_threshold = 0.75f; // 1-cf from the paper
- // Tgenerate - the threshold
- m_variance = 36.0f; // sigma for the new mode
+ // Tgenerate - the threshold
+ m_variance = 36.0f; // sigma for the new mode
- // GMM for each pixel
- m_modes = new GMM[m_params.Size()*m_params.MaxModes()];
+ // GMM for each pixel
+ m_modes = new GMM[m_params.Size()*m_params.MaxModes()];
- // used modes per pixel
- m_modes_per_pixel = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 1);
+ // used modes per pixel
+ m_modes_per_pixel = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 1);
- m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
}
RgbImage* GrimsonGMM::Background()
{
- return &m_background;
+ return &m_background;
}
void GrimsonGMM::InitModel(const RgbImage& data)
{
- m_modes_per_pixel.Clear();
-
- for(unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
- {
- m_modes[i].weight = 0;
- m_modes[i].variance = 0;
- m_modes[i].muR = 0;
- m_modes[i].muG = 0;
- m_modes[i].muB = 0;
- m_modes[i].significants = 0;
- }
+ m_modes_per_pixel.Clear();
+
+ for (unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
+ {
+ m_modes[i].weight = 0;
+ m_modes[i].variance = 0;
+ m_modes[i].muR = 0;
+ m_modes[i].muG = 0;
+ m_modes[i].muB = 0;
+ m_modes[i].significants = 0;
+ }
}
-void GrimsonGMM::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void GrimsonGMM::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- // it doesn't make sense to have conditional updates in the GMM framework
+ // it doesn't make sense to have conditional updates in the GMM framework
}
-void GrimsonGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes,
- unsigned char& low_threshold, unsigned char& high_threshold)
+void GrimsonGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes,
+ unsigned char& low_threshold, unsigned char& high_threshold)
{
- // calculate distances to the modes (+ sort???)
- // here we need to go in descending order!!!
- long pos;
- bool bFitsPDF=false;
- bool bBackgroundLow=false;
- bool bBackgroundHigh=false;
-
- float fOneMinAlpha = 1-m_params.Alpha();
-
- float totalWeight = 0.0f;
-
- // calculate number of Gaussians to include in the background model
- int backgroundGaussians = 0;
- double sum = 0.0;
- for(int i = 0; i < numModes; ++i)
- {
- if(sum < m_bg_threshold)
- {
- backgroundGaussians++;
- sum += m_modes[posPixel+i].weight;
- }
- else
- {
- break;
- }
- }
-
- // update all distributions and check for match with current pixel
- for (int iModes=0; iModes < numModes; iModes++)
- {
- pos=posPixel+iModes;
- float weight = m_modes[pos].weight;
-
- // fit not found yet
- if (!bFitsPDF)
- {
- //check if it belongs to some of the modes
- //calculate distance
- float var = m_modes[pos].variance;
- float muR = m_modes[pos].muR;
- float muG = m_modes[pos].muG;
- float muB = m_modes[pos].muB;
-
- float dR=muR - pixel(0);
- float dG=muG - pixel(1);
- float dB=muB - pixel(2);
-
- // calculate the squared distance
- float dist = (dR*dR + dG*dG + dB*dB);
-
- if(dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
- bBackgroundHigh = true;
-
- // a match occurs when the pixel is within sqrt(fTg) standard deviations of the distribution
- if(dist < m_params.LowThreshold()*var)
- {
- bFitsPDF=true;
-
- // check if this Gaussian is part of the background model
- if(iModes < backgroundGaussians)
- bBackgroundLow = true;
-
- //update distribution
- float k = m_params.Alpha()/weight;
- weight = fOneMinAlpha*weight + m_params.Alpha();
- m_modes[pos].weight = weight;
- m_modes[pos].muR = muR - k*(dR);
- m_modes[pos].muG = muG - k*(dG);
- m_modes[pos].muB = muB - k*(dB);
-
- //limit the variance
- float sigmanew = var + k*(dist-var);
- m_modes[pos].variance = sigmanew < 4 ? 4 : sigmanew > 5*m_variance ? 5*m_variance : sigmanew;
- m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
- }
- else
- {
- weight = fOneMinAlpha*weight;
- if (weight < 0.0)
- {
- weight=0.0;
- numModes--;
- }
-
- m_modes[pos].weight = weight;
- m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
- }
- }
- else
- {
- weight = fOneMinAlpha*weight;
- if (weight < 0.0)
- {
- weight=0.0;
- numModes--;
- }
- m_modes[pos].weight = weight;
- m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
- }
-
- totalWeight += weight;
- }
-
- // renormalize weights so they add to one
- double invTotalWeight = 1.0 / totalWeight;
- for (int iLocal = 0; iLocal < numModes; iLocal++)
- {
- m_modes[posPixel + iLocal].weight *= (float)invTotalWeight;
- m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight
- / sqrt(m_modes[posPixel + iLocal].variance);
- }
-
- // Sort significance values so they are in desending order.
- qsort(&m_modes[posPixel], numModes, sizeof(GMM), compareGMM);
-
- // make new mode if needed and exit
- if (!bFitsPDF)
- {
- if (numModes < m_params.MaxModes())
- {
- numModes++;
- }
- else
- {
- // the weakest mode will be replaced
- }
-
- pos = posPixel + numModes-1;
-
- m_modes[pos].muR = pixel.ch[0];
- m_modes[pos].muG = pixel.ch[1];
- m_modes[pos].muB = pixel.ch[2];
- m_modes[pos].variance = m_variance;
- m_modes[pos].significants = 0; // will be set below
-
- if (numModes==1)
- m_modes[pos].weight = 1;
- else
- m_modes[pos].weight = m_params.Alpha();
-
- //renormalize weights
- int iLocal;
- float sum = 0.0;
- for (iLocal = 0; iLocal < numModes; iLocal++)
- {
- sum += m_modes[posPixel+ iLocal].weight;
- }
-
- double invSum = 1.0/sum;
- for (iLocal = 0; iLocal < numModes; iLocal++)
- {
- m_modes[posPixel + iLocal].weight *= (float)invSum;
- m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight
- / sqrt(m_modes[posPixel + iLocal].variance);
-
- }
- }
-
- // Sort significance values so they are in desending order.
- qsort(&(m_modes[posPixel]), numModes, sizeof(GMM), compareGMM);
-
- if(bBackgroundLow)
- {
- low_threshold = BACKGROUND;
- }
- else
- {
- low_threshold = FOREGROUND;
- }
-
- if(bBackgroundHigh)
- {
- high_threshold = BACKGROUND;
- }
- else
- {
- high_threshold = FOREGROUND;
- }
+ // calculate distances to the modes (+ sort???)
+ // here we need to go in descending order!!!
+ long pos;
+ bool bFitsPDF = false;
+ bool bBackgroundLow = false;
+ bool bBackgroundHigh = false;
+
+ float fOneMinAlpha = 1 - m_params.Alpha();
+
+ float totalWeight = 0.0f;
+
+ // calculate number of Gaussians to include in the background model
+ int backgroundGaussians = 0;
+ double sum = 0.0;
+ for (int i = 0; i < numModes; ++i)
+ {
+ if (sum < m_bg_threshold)
+ {
+ backgroundGaussians++;
+ sum += m_modes[posPixel + i].weight;
+ }
+ else
+ {
+ break;
+ }
+ }
+
+ // update all distributions and check for match with current pixel
+ for (int iModes = 0; iModes < numModes; iModes++)
+ {
+ pos = posPixel + iModes;
+ float weight = m_modes[pos].weight;
+
+ // fit not found yet
+ if (!bFitsPDF)
+ {
+ //check if it belongs to some of the modes
+ //calculate distance
+ float var = m_modes[pos].variance;
+ float muR = m_modes[pos].muR;
+ float muG = m_modes[pos].muG;
+ float muB = m_modes[pos].muB;
+
+ float dR = muR - pixel(0);
+ float dG = muG - pixel(1);
+ float dB = muB - pixel(2);
+
+ // calculate the squared distance
+ float dist = (dR*dR + dG*dG + dB*dB);
+
+ if (dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
+ bBackgroundHigh = true;
+
+ // a match occurs when the pixel is within sqrt(fTg) standard deviations of the distribution
+ if (dist < m_params.LowThreshold()*var)
+ {
+ bFitsPDF = true;
+
+ // check if this Gaussian is part of the background model
+ if (iModes < backgroundGaussians)
+ bBackgroundLow = true;
+
+ //update distribution
+ float k = m_params.Alpha() / weight;
+ weight = fOneMinAlpha*weight + m_params.Alpha();
+ m_modes[pos].weight = weight;
+ m_modes[pos].muR = muR - k*(dR);
+ m_modes[pos].muG = muG - k*(dG);
+ m_modes[pos].muB = muB - k*(dB);
+
+ //limit the variance
+ float sigmanew = var + k*(dist - var);
+ m_modes[pos].variance = sigmanew < 4 ? 4 : sigmanew > 5 * m_variance ? 5 * m_variance : sigmanew;
+ m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
+ }
+ else
+ {
+ weight = fOneMinAlpha*weight;
+ if (weight < 0.0)
+ {
+ weight = 0.0;
+ numModes--;
+ }
+
+ m_modes[pos].weight = weight;
+ m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
+ }
+ }
+ else
+ {
+ weight = fOneMinAlpha*weight;
+ if (weight < 0.0)
+ {
+ weight = 0.0;
+ numModes--;
+ }
+ m_modes[pos].weight = weight;
+ m_modes[pos].significants = m_modes[pos].weight / sqrt(m_modes[pos].variance);
+ }
+
+ totalWeight += weight;
+ }
+
+ // renormalize weights so they add to one
+ double invTotalWeight = 1.0 / totalWeight;
+ for (int iLocal = 0; iLocal < numModes; iLocal++)
+ {
+ m_modes[posPixel + iLocal].weight *= (float)invTotalWeight;
+ m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight
+ / sqrt(m_modes[posPixel + iLocal].variance);
+ }
+
+ // Sort significance values so they are in desending order.
+ qsort(&m_modes[posPixel], numModes, sizeof(GMM), compareGMM);
+
+ // make new mode if needed and exit
+ if (!bFitsPDF)
+ {
+ if (numModes < m_params.MaxModes())
+ {
+ numModes++;
+ }
+ else
+ {
+ // the weakest mode will be replaced
+ }
+
+ pos = posPixel + numModes - 1;
+
+ m_modes[pos].muR = pixel.ch[0];
+ m_modes[pos].muG = pixel.ch[1];
+ m_modes[pos].muB = pixel.ch[2];
+ m_modes[pos].variance = m_variance;
+ m_modes[pos].significants = 0; // will be set below
+
+ if (numModes == 1)
+ m_modes[pos].weight = 1;
+ else
+ m_modes[pos].weight = m_params.Alpha();
+
+ //renormalize weights
+ int iLocal;
+ float sum = 0.0;
+ for (iLocal = 0; iLocal < numModes; iLocal++)
+ {
+ sum += m_modes[posPixel + iLocal].weight;
+ }
+
+ double invSum = 1.0 / sum;
+ for (iLocal = 0; iLocal < numModes; iLocal++)
+ {
+ m_modes[posPixel + iLocal].weight *= (float)invSum;
+ m_modes[posPixel + iLocal].significants = m_modes[posPixel + iLocal].weight
+ / sqrt(m_modes[posPixel + iLocal].variance);
+
+ }
+ }
+
+ // Sort significance values so they are in desending order.
+ qsort(&(m_modes[posPixel]), numModes, sizeof(GMM), compareGMM);
+
+ if (bBackgroundLow)
+ {
+ low_threshold = BACKGROUND;
+ }
+ else
+ {
+ low_threshold = FOREGROUND;
+ }
+
+ if (bBackgroundHigh)
+ {
+ high_threshold = BACKGROUND;
+ }
+ else
+ {
+ high_threshold = FOREGROUND;
+ }
}
///////////////////////////////////////////////////////////////////////////////
@@ -303,29 +303,29 @@ void GrimsonGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned ch
// (the memory should already be reserved)
// values: 255-foreground, 125-shadow, 0-background
///////////////////////////////////////////////////////////////////////////////
-void GrimsonGMM::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void GrimsonGMM::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
- unsigned char low_threshold, high_threshold;
- long posPixel;
-
- // update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // update model + background subtract
- posPixel=(r*m_params.Width()+c)*m_params.MaxModes();
-
- SubtractPixel(posPixel, data(r,c), m_modes_per_pixel(r,c), low_threshold, high_threshold);
-
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
-
- m_background(r,c,0) = (unsigned char)m_modes[posPixel].muR;
- m_background(r,c,1) = (unsigned char)m_modes[posPixel].muG;
- m_background(r,c,2) = (unsigned char)m_modes[posPixel].muB;
- }
- }
+ unsigned char low_threshold, high_threshold;
+ long posPixel;
+
+ // update each pixel of the image
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // update model + background subtract
+ posPixel = (r*m_params.Width() + c)*m_params.MaxModes();
+
+ SubtractPixel(posPixel, data(r, c), m_modes_per_pixel(r, c), low_threshold, high_threshold);
+
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
+
+ m_background(r, c, 0) = (unsigned char)m_modes[posPixel].muR;
+ m_background(r, c, 1) = (unsigned char)m_modes[posPixel].muG;
+ m_background(r, c, 2) = (unsigned char)m_modes[posPixel].muB;
+ }
+ }
}
diff --git a/package_bgs/dp/GrimsonGMM.h b/package_bgs/dp/GrimsonGMM.h
index a177a80..2c0f772 100644
--- a/package_bgs/dp/GrimsonGMM.h
+++ b/package_bgs/dp/GrimsonGMM.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* GrimsonGMM.cpp
*
-* Purpose: Implementation of the Gaussian mixture model (GMM) background
+* Purpose: Implementation of the Gaussian mixture model (GMM) background
* subtraction described in:
* "Adaptive background mixture models for real-time tracking"
* by Chris Stauffer and W.E.L Grimson
@@ -26,125 +26,121 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* Author: Donovan Parks, September 2007
*
* This code is based on code by Z. Zivkovic's written for his enhanced GMM
-* background subtraction algorithm:
+* background subtraction algorithm:
*
* "Improved adaptive Gausian mixture model for background subtraction"
-* Z.Zivkovic
+* Z.Zivkovic
* International Conference Pattern Recognition, UK, August, 2004
*
*
-* "Efficient Adaptive Density Estimapion per Image Pixel for the
+* "Efficient Adaptive Density Estimapion per Image Pixel for the
* Task of Background Subtraction"
-* Z.Zivkovic, F. van der Heijden
+* Z.Zivkovic, F. van der Heijden
* Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
*
* Zivkovic's code can be obtained at: www.zoranz.net
Example:
- Algorithms::BackgroundSubtraction::GrimsonParams params;
- params.SetFrameSize(width, height);
- params.LowThreshold() = 3.0f*3.0f;
- params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
- params.Alpha() = 0.001f;
- params.MaxModes() = 3;
-
- Algorithms::BackgroundSubtraction::GrimsonGMM bgs;
- bgs.Initalize(params);
+ Algorithms::BackgroundSubtraction::GrimsonParams params;
+ params.SetFrameSize(width, height);
+ params.LowThreshold() = 3.0f*3.0f;
+ params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+ params.Alpha() = 0.001f;
+ params.MaxModes() = 3;
+
+ Algorithms::BackgroundSubtraction::GrimsonGMM bgs;
+ bgs.Initalize(params);
******************************************************************************/
-
-#ifndef GRIMSON_GMM_
-#define GRIMSON_GMM_
+#pragma once
#include "Bgs.h"
namespace Algorithms
{
- namespace BackgroundSubtraction
- {
- typedef struct GMMGaussian
- {
- float variance;
- float muR;
- float muG;
- float muB;
- float weight;
- float significants; // this is equal to weight / standard deviation and is used to
- // determine which Gaussians should be part of the background model
- } GMM;
-
- // --- User adjustable parameters used by the Grimson GMM BGS algorithm ---
- class GrimsonParams : public BgsParams
- {
- public:
- float &LowThreshold() { return m_low_threshold; }
- float &HighThreshold() { return m_high_threshold; }
-
- float &Alpha() { return m_alpha; }
- int &MaxModes() { return m_max_modes; }
-
- private:
- // Threshold on the squared dist. to decide when a sample is close to an existing
- // components. If it is not close to any a new component will be generated.
- // Smaller threshold values lead to more generated components and higher threshold values
- // lead to a small number of components but they can grow too large.
- //
- // It is usual easiest to think of these thresholds as being the number of variances away
- // from the mean of a pixel before it is considered to be from the foreground.
- float m_low_threshold;
- float m_high_threshold;
-
- // alpha - speed of update - if the time interval you want to average over is T
- // set alpha=1/T.
- float m_alpha;
-
- // Maximum number of modes (Gaussian components) that will be used per pixel
- int m_max_modes;
- };
-
- // --- Grimson GMM BGS algorithm ---
- class GrimsonGMM : public Bgs
- {
- public:
- GrimsonGMM();
- ~GrimsonGMM();
-
- void Initalize(const BgsParams& param);
-
- void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
-
- RgbImage* Background();
-
- private:
- void SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes,
- unsigned char& lowThreshold, unsigned char& highThreshold);
-
- // User adjustable parameters
- GrimsonParams m_params;
-
- // Threshold when the component becomes significant enough to be included into
- // the background model. It is the TB = 1-cf from the paper. So I use cf=0.1 => TB=0.9
- // For alpha=0.001 it means that the mode should exist for approximately 105 frames before
- // it is considered foreground
- float m_bg_threshold; //1-cf from the paper
-
- // Initial variance for the newly generated components.
- // It will will influence the speed of adaptation. A good guess should be made.
- // A simple way is to estimate the typical standard deviation from the images.
- float m_variance;
-
- // Dynamic array for the mixture of Gaussians
- GMM* m_modes;
-
- // Number of Gaussian components per pixel
- BwImage m_modes_per_pixel;
-
- // Current background model
- RgbImage m_background;
- };
- }
+ namespace BackgroundSubtraction
+ {
+ typedef struct GMMGaussian
+ {
+ float variance;
+ float muR;
+ float muG;
+ float muB;
+ float weight;
+ float significants; // this is equal to weight / standard deviation and is used to
+ // determine which Gaussians should be part of the background model
+ } GMM;
+
+ // --- User adjustable parameters used by the Grimson GMM BGS algorithm ---
+ class GrimsonParams : public BgsParams
+ {
+ public:
+ float &LowThreshold() { return m_low_threshold; }
+ float &HighThreshold() { return m_high_threshold; }
+
+ float &Alpha() { return m_alpha; }
+ int &MaxModes() { return m_max_modes; }
+
+ private:
+ // Threshold on the squared dist. to decide when a sample is close to an existing
+ // components. If it is not close to any a new component will be generated.
+ // Smaller threshold values lead to more generated components and higher threshold values
+ // lead to a small number of components but they can grow too large.
+ //
+ // It is usual easiest to think of these thresholds as being the number of variances away
+ // from the mean of a pixel before it is considered to be from the foreground.
+ float m_low_threshold;
+ float m_high_threshold;
+
+ // alpha - speed of update - if the time interval you want to average over is T
+ // set alpha=1/T.
+ float m_alpha;
+
+ // Maximum number of modes (Gaussian components) that will be used per pixel
+ int m_max_modes;
+ };
+
+ // --- Grimson GMM BGS algorithm ---
+ class GrimsonGMM : public Bgs
+ {
+ public:
+ GrimsonGMM();
+ ~GrimsonGMM();
+
+ void Initalize(const BgsParams& param);
+
+ void InitModel(const RgbImage& data);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+
+ RgbImage* Background();
+
+ private:
+ void SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char& numModes,
+ unsigned char& lowThreshold, unsigned char& highThreshold);
+
+ // User adjustable parameters
+ GrimsonParams m_params;
+
+ // Threshold when the component becomes significant enough to be included into
+ // the background model. It is the TB = 1-cf from the paper. So I use cf=0.1 => TB=0.9
+ // For alpha=0.001 it means that the mode should exist for approximately 105 frames before
+ // it is considered foreground
+ float m_bg_threshold; //1-cf from the paper
+
+ // Initial variance for the newly generated components.
+ // It will will influence the speed of adaptation. A good guess should be made.
+ // A simple way is to estimate the typical standard deviation from the images.
+ float m_variance;
+
+ // Dynamic array for the mixture of Gaussians
+ GMM* m_modes;
+
+ // Number of Gaussian components per pixel
+ BwImage m_modes_per_pixel;
+
+ // Current background model
+ RgbImage m_background;
+ };
+ }
}
-
-#endif
diff --git a/package_bgs/dp/Image.cpp b/package_bgs/dp/Image.cpp
index f00febd..92119c2 100644
--- a/package_bgs/dp/Image.cpp
+++ b/package_bgs/dp/Image.cpp
@@ -18,59 +18,59 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* Image.hpp
*
-* Purpose: C++ wrapper for OpenCV IplImage which supports simple and
+* Purpose: C++ wrapper for OpenCV IplImage which supports simple and
* efficient access to the image data
*
* Author: Donovan Parks, September 2007
*
-* Based on code from:
+* Based on code from:
* http://www.cs.iit.edu/~agam/cs512/lect-notes/opencv-intro/opencv-intro.hpptml
******************************************************************************/
#include "Image.h"
ImageBase::~ImageBase()
-{
- if(imgp != NULL && m_bReleaseMemory)
+{
+ if (imgp != NULL && m_bReleaseMemory)
cvReleaseImage(&imgp);
- imgp = NULL;
+ imgp = NULL;
}
void DensityFilter(BwImage& image, BwImage& filtered, int minDensity, unsigned char fgValue)
{
- for(int r = 1; r < image.Ptr()->height-1; ++r)
+ for (int r = 1; r < image.Ptr()->height - 1; ++r)
{
- for(int c = 1; c < image.Ptr()->width-1; ++c)
+ for (int c = 1; c < image.Ptr()->width - 1; ++c)
{
int count = 0;
- if(image(r,c) == fgValue)
+ if (image(r, c) == fgValue)
{
- if(image(r-1,c-1) == fgValue)
+ if (image(r - 1, c - 1) == fgValue)
count++;
- if(image(r-1,c) == fgValue)
+ if (image(r - 1, c) == fgValue)
count++;
- if(image(r-1,c+1) == fgValue)
+ if (image(r - 1, c + 1) == fgValue)
count++;
- if(image(r,c-1) == fgValue)
+ if (image(r, c - 1) == fgValue)
count++;
- if(image(r,c+1) == fgValue)
+ if (image(r, c + 1) == fgValue)
count++;
- if(image(r+1,c-1) == fgValue)
+ if (image(r + 1, c - 1) == fgValue)
count++;
- if(image(r+1,c) == fgValue)
+ if (image(r + 1, c) == fgValue)
count++;
- if(image(r+1,c+1) == fgValue)
+ if (image(r + 1, c + 1) == fgValue)
count++;
- if(count < minDensity)
- filtered(r,c) = 0;
+ if (count < minDensity)
+ filtered(r, c) = 0;
else
- filtered(r,c) = fgValue;
+ filtered(r, c) = fgValue;
}
else
{
- filtered(r,c) = 0;
+ filtered(r, c) = 0;
}
}
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/dp/Image.h b/package_bgs/dp/Image.h
index 58fe50d..6c0b5b3 100644
--- a/package_bgs/dp/Image.h
+++ b/package_bgs/dp/Image.h
@@ -18,17 +18,15 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* Image.h
*
-* Purpose: C++ wrapper for OpenCV IplImage which supports simple and
+* Purpose: C++ wrapper for OpenCV IplImage which supports simple and
* efficient access to the image data
*
* Author: Donovan Parks, September 2007
*
-* Based on code from:
+* Based on code from:
* http://www.cs.iit.edu/~agam/cs512/lect-notes/opencv-intro/opencv-intro.html
******************************************************************************/
-
-#ifndef _IMAGE_H_
-#define _IMAGE_H_
+#pragma once
#include <opencv2/opencv.hpp>
//#include <cxcore.h>
@@ -36,30 +34,30 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
// --- Image Iterator ---------------------------------------------------------
template <class T>
-class ImageIterator
+class ImageIterator
{
-public:
- ImageIterator(IplImage* image, int x=0, int y=0, int dx= 0, int dy=0) :
- i(x), j(y), i0(0)
- {
+public:
+ ImageIterator(IplImage* image, int x = 0, int y = 0, int dx = 0, int dy = 0) :
+ i(x), j(y), i0(0)
+ {
data = reinterpret_cast<T*>(image->imageData);
step = image->widthStep / sizeof(T);
- nl= image->height;
- if ((y+dy)>0 && (y+dy) < nl)
- nl= y+dy;
+ nl = image->height;
+ if ((y + dy) > 0 && (y + dy) < nl)
+ nl = y + dy;
- if (y<0)
- j=0;
+ if (y < 0)
+ j = 0;
data += step*j;
nc = image->width;
- if ((x+dx) > 0 && (x+dx) < nc)
- nc = x+dx;
+ if ((x + dx) > 0 && (x + dx) < nc)
+ nc = x + dx;
nc *= image->nChannels;
- if (x>0)
+ if (x > 0)
i0 = x*image->nChannels;
i = i0;
@@ -71,26 +69,26 @@ public:
bool operator!() const { return j < nl; }
/* next pixel */
- ImageIterator& operator++()
+ ImageIterator& operator++()
{
i++;
- if (i >= nc)
- {
- i=i0;
- j++;
- data += step;
+ if (i >= nc)
+ {
+ i = i0;
+ j++;
+ data += step;
}
return *this;
}
- ImageIterator& operator+=(int s)
+ ImageIterator& operator+=(int s)
{
- i+=s;
- if (i >= nc)
- {
- i=i0;
- j++;
- data += step;
+ i += s;
+ if (i >= nc)
+ {
+ i = i0;
+ j++;
+ data += step;
}
return *this;
}
@@ -101,18 +99,18 @@ public:
const T operator*() const { return data[i]; }
const T neighbor(int dx, int dy) const
- {
- return *(data+dy*step+i+dx);
+ {
+ return *(data + dy*step + i + dx);
}
- T* operator&() const { return data+i; }
+ T* operator&() const { return data + i; }
/* current pixel coordinates */
- int column() const { return i/nch; }
+ int column() const { return i / nch; }
int line() const { return j; }
private:
- int i, i0,j;
+ int i, i0, j;
T* data;
int step;
int nl, nc;
@@ -128,7 +126,7 @@ const unsigned char NUM_CHANNELS = 3;
class RgbPixel
{
public:
- RgbPixel() {;}
+ RgbPixel() { ; }
RgbPixel(unsigned char _r, unsigned char _g, unsigned char _b)
{
ch[0] = _r; ch[1] = _g; ch[2] = _b;
@@ -156,7 +154,7 @@ public:
class RgbPixelFloat
{
public:
- RgbPixelFloat() {;}
+ RgbPixelFloat() { ; }
RgbPixelFloat(float _r, float _g, float _b)
{
ch[0] = _r; ch[1] = _g; ch[2] = _b;
@@ -199,14 +197,14 @@ public:
cvReleaseImage(&imgp);
}
- void operator=(IplImage* img)
- {
+ void operator=(IplImage* img)
+ {
imgp = img;
}
// copy-constructor
ImageBase(const ImageBase& rhs)
- {
+ {
// it is very inefficent if this copy-constructor is called
assert(false);
}
@@ -237,31 +235,31 @@ public:
cvZero(imgp);
}
- void operator=(IplImage* img)
- {
+ void operator=(IplImage* img)
+ {
imgp = img;
}
// channel-level access using image(row, col, channel)
inline unsigned char& operator()(const int r, const int c, const int ch)
{
- return (unsigned char &)imgp->imageData[r*imgp->widthStep+c*imgp->nChannels+ch];
+ return (unsigned char &)imgp->imageData[r*imgp->widthStep + c*imgp->nChannels + ch];
}
inline const unsigned char& operator()(const int r, const int c, const int ch) const
{
- return (unsigned char &)imgp->imageData[r*imgp->widthStep+c*imgp->nChannels+ch];
+ return (unsigned char &)imgp->imageData[r*imgp->widthStep + c*imgp->nChannels + ch];
}
// RGB pixel-level access using image(row, col)
- inline RgbPixel& operator()(const int r, const int c)
+ inline RgbPixel& operator()(const int r, const int c)
{
- return (RgbPixel &)imgp->imageData[r*imgp->widthStep+c*imgp->nChannels];
+ return (RgbPixel &)imgp->imageData[r*imgp->widthStep + c*imgp->nChannels];
}
inline const RgbPixel& operator()(const int r, const int c) const
{
- return (RgbPixel &)imgp->imageData[r*imgp->widthStep+c*imgp->nChannels];
+ return (RgbPixel &)imgp->imageData[r*imgp->widthStep + c*imgp->nChannels];
}
};
@@ -275,31 +273,31 @@ public:
cvZero(imgp);
}
- void operator=(IplImage* img)
- {
+ void operator=(IplImage* img)
+ {
imgp = img;
}
// channel-level access using image(row, col, channel)
inline float& operator()(const int r, const int c, const int ch)
{
- return (float &)imgp->imageData[r*imgp->widthStep+(c*imgp->nChannels+ch)*sizeof(float)];
+ return (float &)imgp->imageData[r*imgp->widthStep + (c*imgp->nChannels + ch) * sizeof(float)];
}
inline float operator()(const int r, const int c, const int ch) const
{
- return (float)imgp->imageData[r*imgp->widthStep+(c*imgp->nChannels+ch)*sizeof(float)];
+ return (float)imgp->imageData[r*imgp->widthStep + (c*imgp->nChannels + ch) * sizeof(float)];
}
// RGB pixel-level access using image(row, col)
- inline RgbPixelFloat& operator()(const int r, const int c)
+ inline RgbPixelFloat& operator()(const int r, const int c)
{
- return (RgbPixelFloat &)imgp->imageData[r*imgp->widthStep+c*imgp->nChannels*sizeof(float)];
+ return (RgbPixelFloat &)imgp->imageData[r*imgp->widthStep + c*imgp->nChannels * sizeof(float)];
}
inline const RgbPixelFloat& operator()(const int r, const int c) const
{
- return (RgbPixelFloat &)imgp->imageData[r*imgp->widthStep+c*imgp->nChannels*sizeof(float)];
+ return (RgbPixelFloat &)imgp->imageData[r*imgp->widthStep + c*imgp->nChannels * sizeof(float)];
}
};
@@ -313,20 +311,20 @@ public:
cvZero(imgp);
}
- void operator=(IplImage* img)
- {
+ void operator=(IplImage* img)
+ {
imgp = img;
}
// pixel-level access using image(row, col)
inline unsigned char& operator()(const int r, const int c)
{
- return (unsigned char &)imgp->imageData[r*imgp->widthStep+c];
+ return (unsigned char &)imgp->imageData[r*imgp->widthStep + c];
}
inline unsigned char operator()(const int r, const int c) const
{
- return (unsigned char)imgp->imageData[r*imgp->widthStep+c];
+ return (unsigned char)imgp->imageData[r*imgp->widthStep + c];
}
};
@@ -340,25 +338,23 @@ public:
cvZero(imgp);
}
- void operator=(IplImage* img)
- {
+ void operator=(IplImage* img)
+ {
imgp = img;
}
// pixel-level access using image(row, col)
inline float& operator()(const int r, const int c)
{
- return (float &)imgp->imageData[r*imgp->widthStep+c*sizeof(float)];
+ return (float &)imgp->imageData[r*imgp->widthStep + c * sizeof(float)];
}
inline float operator()(const int r, const int c) const
{
- return (float)imgp->imageData[r*imgp->widthStep+c*sizeof(float)];
+ return (float)imgp->imageData[r*imgp->widthStep + c * sizeof(float)];
}
};
// --- Image Functions --------------------------------------------------------
void DensityFilter(BwImage& image, BwImage& filtered, int minDensity, unsigned char fgValue);
-
-#endif
diff --git a/package_bgs/dp/MeanBGS.cpp b/package_bgs/dp/MeanBGS.cpp
index b8df895..5178158 100644
--- a/package_bgs/dp/MeanBGS.cpp
+++ b/package_bgs/dp/MeanBGS.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* MeanBGS.h
*
-* Purpose: Implementation of a simple temporal mean background
+* Purpose: Implementation of a simple temporal mean background
* subtraction algorithm.
*
* Author: Donovan Parks, September 2007
@@ -31,72 +31,72 @@ using namespace Algorithms::BackgroundSubtraction;
void MeanBGS::Initalize(const BgsParams& param)
{
- m_params = (MeanParams&)param;
+ m_params = (MeanParams&)param;
- m_mean = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_32F, 3);
- m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ m_mean = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_32F, 3);
+ m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
}
void MeanBGS::InitModel(const RgbImage& data)
{
- for (unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- m_mean(r,c,ch) = (float)data(r,c,ch);
- }
- }
- }
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ m_mean(r, c, ch) = (float)data(r, c, ch);
+ }
+ }
+ }
}
-void MeanBGS::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void MeanBGS::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- // update background model
- for (unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // perform conditional updating only if we are passed the learning phase
- if(update_mask(r,c) == BACKGROUND || frame_num < m_params.LearningFrames())
- {
- // update B/G model
- float mean;
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- mean = m_params.Alpha() * m_mean(r,c,ch) + (1.0f-m_params.Alpha()) * data(r,c,ch);
- m_mean(r,c,ch) = mean;
- m_background(r,c,ch) = (unsigned char)(mean + 0.5);
- }
- }
- }
- }
+ // update background model
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // perform conditional updating only if we are passed the learning phase
+ if (update_mask(r, c) == BACKGROUND || frame_num < m_params.LearningFrames())
+ {
+ // update B/G model
+ float mean;
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ mean = m_params.Alpha() * m_mean(r, c, ch) + (1.0f - m_params.Alpha()) * data(r, c, ch);
+ m_mean(r, c, ch) = mean;
+ m_background(r, c, ch) = (unsigned char)(mean + 0.5);
+ }
+ }
+ }
+ }
}
-void MeanBGS::SubtractPixel(int r, int c, const RgbPixel& pixel,
- unsigned char& low_threshold,
- unsigned char& high_threshold)
+void MeanBGS::SubtractPixel(int r, int c, const RgbPixel& pixel,
+ unsigned char& low_threshold,
+ unsigned char& high_threshold)
{
- // calculate distance to sample point
- float dist = 0;
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- dist += (pixel(ch)-m_mean(r,c,ch))*(pixel(ch)-m_mean(r,c,ch));
- }
-
- // determine if sample point is F/G or B/G pixel
- low_threshold = BACKGROUND;
- if(dist > m_params.LowThreshold())
- {
- low_threshold = FOREGROUND;
- }
-
- high_threshold = BACKGROUND;
- if(dist > m_params.HighThreshold())
- {
- high_threshold = FOREGROUND;
- }
+ // calculate distance to sample point
+ float dist = 0;
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ dist += (pixel(ch) - m_mean(r, c, ch))*(pixel(ch) - m_mean(r, c, ch));
+ }
+
+ // determine if sample point is F/G or B/G pixel
+ low_threshold = BACKGROUND;
+ if (dist > m_params.LowThreshold())
+ {
+ low_threshold = FOREGROUND;
+ }
+
+ high_threshold = BACKGROUND;
+ if (dist > m_params.HighThreshold())
+ {
+ high_threshold = FOREGROUND;
+ }
}
///////////////////////////////////////////////////////////////////////////////
@@ -106,26 +106,22 @@ void MeanBGS::SubtractPixel(int r, int c, const RgbPixel& pixel,
// output - a pointer to the data of a gray value image of the same size
// values: 255-foreground, 0-background
///////////////////////////////////////////////////////////////////////////////
-void MeanBGS::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void MeanBGS::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
- unsigned char low_threshold, high_threshold;
-
- // update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // perform background subtraction + update background model
- SubtractPixel(r, c, data(r,c), low_threshold, high_threshold);
-
- // setup silhouette mask
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
- }
- }
+ unsigned char low_threshold, high_threshold;
+
+ // update each pixel of the image
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // perform background subtraction + update background model
+ SubtractPixel(r, c, data(r, c), low_threshold, high_threshold);
+
+ // setup silhouette mask
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
+ }
+ }
}
-
-
-
-
diff --git a/package_bgs/dp/MeanBGS.h b/package_bgs/dp/MeanBGS.h
index 247e094..306af1a 100644
--- a/package_bgs/dp/MeanBGS.h
+++ b/package_bgs/dp/MeanBGS.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* MeanBGS.hpp
*
-* Purpose: Implementation of a simple temporal mean background
+* Purpose: Implementation of a simple temporal mean background
* subtraction algorithm.
*
* Author: Donovan Parks, September 2007
@@ -28,13 +28,14 @@ Example:
Algorithms::BackgroundSubtraction::MeanParams params;
params.SetFrameSize(width, height);
params.LowThreshold() = 3*30*30;
-params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
params.Alpha() = 1e-6f;
params.LearningFrames() = 30;
Algorithms::BackgroundSubtraction::MeanBGS bgs;
bgs.Initalize(params);
******************************************************************************/
+#pragma once
#include "Bgs.h"
@@ -54,7 +55,7 @@ namespace Algorithms
int &LearningFrames() { return m_learning_frames; }
private:
- // A pixel is considered to be from the background if the squared distance between
+ // A pixel is considered to be from the background if the squared distance between
// it and the background model is less than the threshold.
unsigned int m_low_threshold;
unsigned int m_high_threshold;
@@ -73,14 +74,14 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background() { return &m_background; }
- private:
- void SubtractPixel(int r, int c, const RgbPixel& pixel,
+ private:
+ void SubtractPixel(int r, int c, const RgbPixel& pixel,
unsigned char& lowThreshold, unsigned char& highThreshold);
MeanParams m_params;
@@ -91,8 +92,3 @@ namespace Algorithms
}
}
-
-
-
-
-
diff --git a/package_bgs/dp/PratiMediodBGS.cpp b/package_bgs/dp/PratiMediodBGS.cpp
index 2256ceb..5a15cec 100644
--- a/package_bgs/dp/PratiMediodBGS.cpp
+++ b/package_bgs/dp/PratiMediodBGS.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* PratiMediodBGS.h
*
-* Purpose: Implementation of the temporal median background
+* Purpose: Implementation of the temporal median background
* subtraction algorithm described in:
*
* [1] "Detecting Moving Objects, Shosts, and Shadows in Video Stream"
@@ -29,7 +29,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* Author: Donovan Parks, September 2007
*
-* Please note that this is not an implementation of the complete system
+* Please note that this is not an implementation of the complete system
* given in the above papers. It simply implements the temporal media background
* subtraction algorithm.
******************************************************************************/
@@ -40,202 +40,202 @@ using namespace Algorithms::BackgroundSubtraction;
PratiMediodBGS::PratiMediodBGS()
{
- m_median_buffer = NULL;
+ m_median_buffer = NULL;
}
PratiMediodBGS::~PratiMediodBGS()
{
- delete[] m_median_buffer;
+ delete[] m_median_buffer;
}
void PratiMediodBGS::Initalize(const BgsParams& param)
{
- m_params = (PratiParams&)param;
+ m_params = (PratiParams&)param;
- m_mask_low_threshold = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 1);
- m_mask_high_threshold = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 1);
+ m_mask_low_threshold = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 1);
+ m_mask_high_threshold = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 1);
- m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
- m_median_buffer = new MEDIAN_BUFFER[m_params.Size()];
+ m_median_buffer = new MEDIAN_BUFFER[m_params.Size()];
}
void PratiMediodBGS::InitModel(const RgbImage& data)
{
- // there is no need to initialize the mode since it needs a buffer of frames
- // before it can performing background subtraction
+ // there is no need to initialize the mode since it needs a buffer of frames
+ // before it can performing background subtraction
}
-void PratiMediodBGS::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void PratiMediodBGS::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- // update the image buffer with the new frame and calculate new median values
- if(frame_num % m_params.SamplingRate() == 0)
- {
- if(m_median_buffer[0].dist.size() == m_params.HistorySize())
- {
- // subtract distance to sample being removed from all distances
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- int i = r*m_params.Width()+c;
-
- if(update_mask(r,c) == BACKGROUND)
- {
- int oldPos = m_median_buffer[i].pos;
- for(unsigned int s = 0; s < m_median_buffer[i].pixels.size(); ++s)
- {
- int maxDist = 0;
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- int tempDist = abs(m_median_buffer[i].pixels.at(oldPos)(ch)
- - m_median_buffer[i].pixels.at(s)(ch));
- if(tempDist > maxDist)
- maxDist = tempDist;
- }
-
- m_median_buffer[i].dist.at(s) -= maxDist;
- }
-
- int dist;
- UpdateMediod(r, c, data, dist);
- m_median_buffer[i].dist.at(oldPos) = dist;
- m_median_buffer[i].pixels.at(oldPos) = data(r,c);
- m_median_buffer[i].pos++;
- if(m_median_buffer[i].pos >= m_params.HistorySize())
- m_median_buffer[i].pos = 0;
- }
- }
- }
- }
- else
- {
- // calculate sum of L-inf distances for new point and
- // add distance from each sample point to this point to their L-inf sum
- int dist;
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- int index = r*m_params.Width()+c;
- UpdateMediod(r, c, data, dist);
- m_median_buffer[index].dist.push_back(dist);
- m_median_buffer[index].pos = 0;
- m_median_buffer[index].pixels.push_back(data(r,c));
- }
- }
- }
- }
+ // update the image buffer with the new frame and calculate new median values
+ if (frame_num % m_params.SamplingRate() == 0)
+ {
+ if (m_median_buffer[0].dist.size() == m_params.HistorySize())
+ {
+ // subtract distance to sample being removed from all distances
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ int i = r*m_params.Width() + c;
+
+ if (update_mask(r, c) == BACKGROUND)
+ {
+ int oldPos = m_median_buffer[i].pos;
+ for (unsigned int s = 0; s < m_median_buffer[i].pixels.size(); ++s)
+ {
+ int maxDist = 0;
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ int tempDist = abs(m_median_buffer[i].pixels.at(oldPos)(ch)
+ - m_median_buffer[i].pixels.at(s)(ch));
+ if (tempDist > maxDist)
+ maxDist = tempDist;
+ }
+
+ m_median_buffer[i].dist.at(s) -= maxDist;
+ }
+
+ int dist;
+ UpdateMediod(r, c, data, dist);
+ m_median_buffer[i].dist.at(oldPos) = dist;
+ m_median_buffer[i].pixels.at(oldPos) = data(r, c);
+ m_median_buffer[i].pos++;
+ if (m_median_buffer[i].pos >= m_params.HistorySize())
+ m_median_buffer[i].pos = 0;
+ }
+ }
+ }
+ }
+ else
+ {
+ // calculate sum of L-inf distances for new point and
+ // add distance from each sample point to this point to their L-inf sum
+ int dist;
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ int index = r*m_params.Width() + c;
+ UpdateMediod(r, c, data, dist);
+ m_median_buffer[index].dist.push_back(dist);
+ m_median_buffer[index].pos = 0;
+ m_median_buffer[index].pixels.push_back(data(r, c));
+ }
+ }
+ }
+ }
}
void PratiMediodBGS::UpdateMediod(int r, int c, const RgbImage& new_frame, int& dist)
{
- // calculate sum of L-inf distances for new point and
- // add distance from each sample point to this point to their L-inf sum
- unsigned int i = (r*m_params.Width()+c);
-
- m_median_buffer[i].medianDist = INT_MAX;
-
- int L_inf_dist = 0;
- for(unsigned int s = 0; s < m_median_buffer[i].dist.size(); ++s)
- {
- int maxDist = 0;
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- int tempDist = abs(m_median_buffer[i].pixels.at(s)(ch) - new_frame(r,c,ch));
- if(tempDist > maxDist)
- maxDist = tempDist;
- }
-
- // check if point from this frame in the image buffer is the median
- m_median_buffer[i].dist.at(s) += maxDist;
- if(m_median_buffer[i].dist.at(s) < m_median_buffer[i].medianDist)
- {
- m_median_buffer[i].medianDist = m_median_buffer[i].dist.at(s);
- m_median_buffer[i].median = m_median_buffer[i].pixels.at(s);
- }
-
- L_inf_dist += maxDist;
- }
-
- dist = L_inf_dist;
-
- // check if the new point is the median
- if(L_inf_dist < m_median_buffer[i].medianDist)
- {
- m_median_buffer[i].medianDist = L_inf_dist;
- m_median_buffer[i].median = new_frame(r,c);
- }
+ // calculate sum of L-inf distances for new point and
+ // add distance from each sample point to this point to their L-inf sum
+ unsigned int i = (r*m_params.Width() + c);
+
+ m_median_buffer[i].medianDist = INT_MAX;
+
+ int L_inf_dist = 0;
+ for (unsigned int s = 0; s < m_median_buffer[i].dist.size(); ++s)
+ {
+ int maxDist = 0;
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ int tempDist = abs(m_median_buffer[i].pixels.at(s)(ch) - new_frame(r, c, ch));
+ if (tempDist > maxDist)
+ maxDist = tempDist;
+ }
+
+ // check if point from this frame in the image buffer is the median
+ m_median_buffer[i].dist.at(s) += maxDist;
+ if (m_median_buffer[i].dist.at(s) < m_median_buffer[i].medianDist)
+ {
+ m_median_buffer[i].medianDist = m_median_buffer[i].dist.at(s);
+ m_median_buffer[i].median = m_median_buffer[i].pixels.at(s);
+ }
+
+ L_inf_dist += maxDist;
+ }
+
+ dist = L_inf_dist;
+
+ // check if the new point is the median
+ if (L_inf_dist < m_median_buffer[i].medianDist)
+ {
+ m_median_buffer[i].medianDist = L_inf_dist;
+ m_median_buffer[i].median = new_frame(r, c);
+ }
}
void PratiMediodBGS::Combine(const BwImage& low_mask, const BwImage& high_mask, BwImage& output)
{
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- output(r,c) = BACKGROUND;
-
- if(r == 0 || c == 0 || r == m_params.Height()-1 || c == m_params.Width()-1)
- continue;
-
- if(high_mask(r,c) == FOREGROUND)
- {
- output(r,c) = FOREGROUND;
- }
- else if(low_mask(r,c) == FOREGROUND)
- {
- // consider the pixel to be a F/G pixel if it is 8-connected to
- // a F/G pixel in the high mask
- // check if there is an 8-connected foreground pixel
- if(high_mask(r-1,c-1))
- output(r,c) = FOREGROUND;
- else if(high_mask(r-1,c))
- output(r,c) = FOREGROUND;
- else if(high_mask(r-1,c+1))
- output(r,c) = FOREGROUND;
- else if(high_mask(r,c-1))
- output(r,c) = FOREGROUND;
- else if(high_mask(r,c+1))
- output(r,c) = FOREGROUND;
- else if(high_mask(r+1,c-1))
- output(r,c) = FOREGROUND;
- else if(high_mask(r+1,c))
- output(r,c) = FOREGROUND;
- else if(high_mask(r+1,c+1))
- output(r,c) = FOREGROUND;
- }
- }
- }
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ output(r, c) = BACKGROUND;
+
+ if (r == 0 || c == 0 || r == m_params.Height() - 1 || c == m_params.Width() - 1)
+ continue;
+
+ if (high_mask(r, c) == FOREGROUND)
+ {
+ output(r, c) = FOREGROUND;
+ }
+ else if (low_mask(r, c) == FOREGROUND)
+ {
+ // consider the pixel to be a F/G pixel if it is 8-connected to
+ // a F/G pixel in the high mask
+ // check if there is an 8-connected foreground pixel
+ if (high_mask(r - 1, c - 1))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r - 1, c))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r - 1, c + 1))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r, c - 1))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r, c + 1))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r + 1, c - 1))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r + 1, c))
+ output(r, c) = FOREGROUND;
+ else if (high_mask(r + 1, c + 1))
+ output(r, c) = FOREGROUND;
+ }
+ }
+ }
}
void PratiMediodBGS::CalculateMasks(int r, int c, const RgbPixel& pixel)
{
- int pos = r*m_params.Width()+c;
-
- // calculate l-inf distance between current value and median value
- unsigned char dist = 0;
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- int tempDist = abs(pixel(ch) - m_median_buffer[pos].median(ch));
- if(tempDist > dist)
- dist = tempDist;
- }
- m_background(r,c) = m_median_buffer[pos].median;
-
- // check if pixel is a B/G or F/G pixel according to the low threshold B/G model
- m_mask_low_threshold(r,c) = BACKGROUND;
- if(dist > m_params.LowThreshold())
- {
- m_mask_low_threshold(r,c) = FOREGROUND;
- }
-
- // check if pixel is a B/G or F/G pixel according to the high threshold B/G model
- m_mask_high_threshold(r,c)= BACKGROUND;
- if(dist > m_params.HighThreshold())
- {
- m_mask_high_threshold(r,c) = FOREGROUND;
- }
+ int pos = r*m_params.Width() + c;
+
+ // calculate l-inf distance between current value and median value
+ unsigned char dist = 0;
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ int tempDist = abs(pixel(ch) - m_median_buffer[pos].median(ch));
+ if (tempDist > dist)
+ dist = tempDist;
+ }
+ m_background(r, c) = m_median_buffer[pos].median;
+
+ // check if pixel is a B/G or F/G pixel according to the low threshold B/G model
+ m_mask_low_threshold(r, c) = BACKGROUND;
+ if (dist > m_params.LowThreshold())
+ {
+ m_mask_low_threshold(r, c) = FOREGROUND;
+ }
+
+ // check if pixel is a B/G or F/G pixel according to the high threshold B/G model
+ m_mask_high_threshold(r, c) = BACKGROUND;
+ if (dist > m_params.HighThreshold())
+ {
+ m_mask_high_threshold(r, c) = FOREGROUND;
+ }
}
///////////////////////////////////////////////////////////////////////////////
@@ -245,29 +245,29 @@ void PratiMediodBGS::CalculateMasks(int r, int c, const RgbPixel& pixel)
// output - a pointer to the data of a gray value image of the same size
// values: 255-foreground, 0-background
///////////////////////////////////////////////////////////////////////////////
-void PratiMediodBGS::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mark, BwImage& high_threshold_mark)
+void PratiMediodBGS::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mark, BwImage& high_threshold_mark)
{
- if(frame_num < m_params.HistorySize())
- {
- low_threshold_mark.Clear();
- high_threshold_mark.Clear();
- return;
- }
-
- // update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // need at least one frame of data before we can start calculating the masks
- CalculateMasks(r, c, data(r,c));
- }
- }
-
- // combine low and high threshold masks
- Combine(m_mask_low_threshold, m_mask_high_threshold, low_threshold_mark);
- Combine(m_mask_low_threshold, m_mask_high_threshold, high_threshold_mark);
+ if (frame_num < m_params.HistorySize())
+ {
+ low_threshold_mark.Clear();
+ high_threshold_mark.Clear();
+ return;
+ }
+
+ // update each pixel of the image
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // need at least one frame of data before we can start calculating the masks
+ CalculateMasks(r, c, data(r, c));
+ }
+ }
+
+ // combine low and high threshold masks
+ Combine(m_mask_low_threshold, m_mask_high_threshold, low_threshold_mark);
+ Combine(m_mask_low_threshold, m_mask_high_threshold, high_threshold_mark);
}
diff --git a/package_bgs/dp/PratiMediodBGS.h b/package_bgs/dp/PratiMediodBGS.h
index bc8cb7f..6bc8f92 100644
--- a/package_bgs/dp/PratiMediodBGS.h
+++ b/package_bgs/dp/PratiMediodBGS.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* PratiMediodBGS.hpp
*
-* Purpose: Implementation of the temporal median background
+* Purpose: Implementation of the temporal median background
* subtraction algorithm described in:
*
* [1] "Detecting Moving Objects, Shosts, and Shadows in Video Stream"
@@ -29,7 +29,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* Author: Donovan Parks, September 2007
*
-* Please note that this is not an implementation of the complete system
+* Please note that this is not an implementation of the complete system
* given in the above papers. It simply implements the temporal media background
* subtraction algorithm.
@@ -37,7 +37,7 @@ Example:
Algorithms::BackgroundSubtraction::PratiParams params;
params.SetFrameSize(width, height);
params.LowThreshold() = 30;
-params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
params.SamplingRate() = 5;
params.HistorySize() = 16;
params.Weight() = 5;
@@ -45,9 +45,7 @@ params.Weight() = 5;
Algorithms::BackgroundSubtraction::PratiMediodBGS bgs;
bgs.Initalize(params);
******************************************************************************/
-
-#ifndef PRATI_MEDIA_BGS_H
-#define PRATI_MEDIA_BGS_H
+#pragma once
#include <vector>
#include "Bgs.h"
@@ -68,9 +66,9 @@ namespace Algorithms
int &HistorySize() { return m_history_size; }
private:
- // The low threshold is used to supress noise. The high thresohld is used
- // to find pixels highly likely to be foreground. This implementation uses an L-inf
- // distance measure and a pixel p is considered F/G if D(I(p), B(p)) > threshold.
+ // The low threshold is used to supress noise. The high thresohld is used
+ // to find pixels highly likely to be foreground. This implementation uses an L-inf
+ // distance measure and a pixel p is considered F/G if D(I(p), B(p)) > threshold.
// The two threshold maps are combined as in [2].
unsigned int m_low_threshold;
unsigned int m_high_threshold;
@@ -88,9 +86,9 @@ namespace Algorithms
};
// --- Prati Mediod BGS algorithm ---
- class PratiMediodBGS : public Bgs
+ class PratiMediodBGS : public Bgs
{
- private:
+ private:
// sum of L-inf distances from a sample point to all other sample points
struct MEDIAN_BUFFER
{
@@ -109,13 +107,13 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background() { return &m_background; }
- private:
+ private:
MEDIAN_BUFFER* m_median_buffer;
void CalculateMasks(int r, int c, const RgbPixel& pixel);
@@ -132,11 +130,3 @@ namespace Algorithms
}
}
-
-#endif
-
-
-
-
-
-
diff --git a/package_bgs/dp/TextureBGS.cpp b/package_bgs/dp/TextureBGS.cpp
index 62684f8..920f140 100644
--- a/package_bgs/dp/TextureBGS.cpp
+++ b/package_bgs/dp/TextureBGS.cpp
@@ -16,40 +16,40 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "TextureBGS.h"
-TextureBGS::TextureBGS(){}
-TextureBGS::~TextureBGS(){}
+TextureBGS::TextureBGS() {}
+TextureBGS::~TextureBGS() {}
void TextureBGS::LBP(RgbImage& image, RgbImage& texture)
{
- for(int y = TEXTURE_R; y < image.Ptr()->height-TEXTURE_R; ++y)
+ for (int y = TEXTURE_R; y < image.Ptr()->height - TEXTURE_R; ++y)
{
- for(int x = TEXTURE_R; x < image.Ptr()->width-TEXTURE_R; ++x)
- {
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
+ for (int x = TEXTURE_R; x < image.Ptr()->width - TEXTURE_R; ++x)
+ {
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
{
unsigned char textureCode = 0;
int centerValue = (int)image(y, x, ch);
// this only works for a texture radius of 2
- if(centerValue - (int)image(y-2, x, ch) + HYSTERSIS >= 0)
+ if (centerValue - (int)image(y - 2, x, ch) + HYSTERSIS >= 0)
textureCode += 1;
- if(centerValue - (int)image(y-1, x-2, ch) + HYSTERSIS >= 0)
+ if (centerValue - (int)image(y - 1, x - 2, ch) + HYSTERSIS >= 0)
textureCode += 2;
- if(centerValue - (int)image(y-1, x+2, ch) + HYSTERSIS >= 0)
+ if (centerValue - (int)image(y - 1, x + 2, ch) + HYSTERSIS >= 0)
textureCode += 4;
- if(centerValue - (int)image(y+1, x-2, ch) + HYSTERSIS >= 0)
+ if (centerValue - (int)image(y + 1, x - 2, ch) + HYSTERSIS >= 0)
textureCode += 8;
- if(centerValue - (int)image(y+1, x+2, ch) + HYSTERSIS >= 0)
+ if (centerValue - (int)image(y + 1, x + 2, ch) + HYSTERSIS >= 0)
textureCode += 16;
- if(centerValue - (int)image(y+2, x, ch) + HYSTERSIS >= 0)
+ if (centerValue - (int)image(y + 2, x, ch) + HYSTERSIS >= 0)
textureCode += 32;
- texture(y,x,ch) = textureCode;
+ texture(y, x, ch) = textureCode;
}
}
}
@@ -58,14 +58,14 @@ void TextureBGS::LBP(RgbImage& image, RgbImage& texture)
void TextureBGS::Histogram(RgbImage& texture, TextureHistogram* curTextureHist)
{
// calculate histogram within a 2*REGION_R square
- for(int y = REGION_R+TEXTURE_R; y < texture.Ptr()->height-REGION_R-TEXTURE_R; ++y)
+ for (int y = REGION_R + TEXTURE_R; y < texture.Ptr()->height - REGION_R - TEXTURE_R; ++y)
{
- for(int x = REGION_R+TEXTURE_R; x < texture.Ptr()->width-REGION_R-TEXTURE_R; ++x)
- {
- int index = x+y*(texture.Ptr()->width);
+ for (int x = REGION_R + TEXTURE_R; x < texture.Ptr()->width - REGION_R - TEXTURE_R; ++x)
+ {
+ int index = x + y*(texture.Ptr()->width);
// clear histogram
- for(int i = 0; i < NUM_BINS; ++i)
+ for (int i = 0; i < NUM_BINS; ++i)
{
curTextureHist[index].r[i] = 0;
curTextureHist[index].g[i] = 0;
@@ -73,13 +73,13 @@ void TextureBGS::Histogram(RgbImage& texture, TextureHistogram* curTextureHist)
}
// calculate histogram
- for(int j = -REGION_R; j <= REGION_R; ++j)
+ for (int j = -REGION_R; j <= REGION_R; ++j)
{
- for(int i = -REGION_R; i <= REGION_R; ++i)
+ for (int i = -REGION_R; i <= REGION_R; ++i)
{
- curTextureHist[index].r[texture(y+j,x+i,2)]++;
- curTextureHist[index].g[texture(y+j,x+i,1)]++;
- curTextureHist[index].b[texture(y+j,x+i,0)]++;
+ curTextureHist[index].r[texture(y + j, x + i, 2)]++;
+ curTextureHist[index].g[texture(y + j, x + i, 1)]++;
+ curTextureHist[index].b[texture(y + j, x + i, 0)]++;
}
}
}
@@ -88,66 +88,66 @@ void TextureBGS::Histogram(RgbImage& texture, TextureHistogram* curTextureHist)
int TextureBGS::ProximityMeasure(TextureHistogram& bgTexture, TextureHistogram& curTextureHist)
{
- int proximity = 0;
- for(int i = 0; i < NUM_BINS; ++i)
+ int proximity = 0;
+ for (int i = 0; i < NUM_BINS; ++i)
{
proximity += std::min(bgTexture.r[i], curTextureHist.r[i]);
proximity += std::min(bgTexture.g[i], curTextureHist.g[i]);
proximity += std::min(bgTexture.b[i], curTextureHist.b[i]);
}
- return proximity;
+ return proximity;
}
-void TextureBGS::BgsCompare(TextureArray* bgModel, TextureHistogram* curTextureHist,
- unsigned char* modeArray, float threshold, BwImage& fgMask)
+void TextureBGS::BgsCompare(TextureArray* bgModel, TextureHistogram* curTextureHist,
+ unsigned char* modeArray, float threshold, BwImage& fgMask)
{
cvZero(fgMask.Ptr());
- for(int y = REGION_R+TEXTURE_R; y < fgMask.Ptr()->height-REGION_R-TEXTURE_R; ++y)
+ for (int y = REGION_R + TEXTURE_R; y < fgMask.Ptr()->height - REGION_R - TEXTURE_R; ++y)
{
- for(int x = REGION_R+TEXTURE_R; x < fgMask.Ptr()->width-REGION_R-TEXTURE_R; ++x)
- {
- int index = x+y*(fgMask.Ptr()->width);
+ for (int x = REGION_R + TEXTURE_R; x < fgMask.Ptr()->width - REGION_R - TEXTURE_R; ++x)
+ {
+ int index = x + y*(fgMask.Ptr()->width);
// find closest matching texture in background model
int maxProximity = -1;
- for(int m = 0; m < NUM_MODES; ++m)
+ for (int m = 0; m < NUM_MODES; ++m)
{
int proximity = ProximityMeasure(bgModel[index].mode[m], curTextureHist[index]);
- if(proximity > maxProximity)
+ if (proximity > maxProximity)
{
maxProximity = proximity;
modeArray[index] = m;
}
}
- if(maxProximity < threshold)
- fgMask(y,x) = 255;
+ if (maxProximity < threshold)
+ fgMask(y, x) = 255;
}
}
}
-void TextureBGS::UpdateModel(BwImage& fgMask, TextureArray* bgModel,
- TextureHistogram* curTextureHist, unsigned char* modeArray)
+void TextureBGS::UpdateModel(BwImage& fgMask, TextureArray* bgModel,
+ TextureHistogram* curTextureHist, unsigned char* modeArray)
{
- for(int y = REGION_R+TEXTURE_R; y < fgMask.Ptr()->height-REGION_R-TEXTURE_R; ++y)
+ for (int y = REGION_R + TEXTURE_R; y < fgMask.Ptr()->height - REGION_R - TEXTURE_R; ++y)
{
- for(int x = REGION_R+TEXTURE_R; x < fgMask.Ptr()->width-REGION_R-TEXTURE_R; ++x)
- {
- int index = x+y*(fgMask.Ptr()->width);
+ for (int x = REGION_R + TEXTURE_R; x < fgMask.Ptr()->width - REGION_R - TEXTURE_R; ++x)
+ {
+ int index = x + y*(fgMask.Ptr()->width);
- if(fgMask(y,x) == 0)
+ if (fgMask(y, x) == 0)
{
- for(int i = 0; i < NUM_BINS; ++i)
+ for (int i = 0; i < NUM_BINS; ++i)
{
bgModel[index].mode[modeArray[index]].r[i]
- = (unsigned char)(ALPHA*curTextureHist[index].r[i]
- + (1-ALPHA)*bgModel[index].mode[modeArray[index]].r[i] + 0.5);
+ = (unsigned char)(ALPHA*curTextureHist[index].r[i]
+ + (1 - ALPHA)*bgModel[index].mode[modeArray[index]].r[i] + 0.5);
}
- }
+ }
}
- }
+ }
}
diff --git a/package_bgs/dp/TextureBGS.h b/package_bgs/dp/TextureBGS.h
index 573e6f9..2650f04 100644
--- a/package_bgs/dp/TextureBGS.h
+++ b/package_bgs/dp/TextureBGS.h
@@ -14,6 +14,8 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
+#pragma once
+
#include <math.h>
#include "Image.h"
@@ -23,7 +25,7 @@ const int TEXTURE_R = 2; // Note: the code currently assumes this value is 2
const int NUM_BINS = 64; // 2^TEXTURE_POINTS
const int HYSTERSIS = 3;
const double ALPHA = 0.05f;
-const double THRESHOLD = 0.5*(REGION_R+REGION_R+1)*(REGION_R+REGION_R+1)*NUM_CHANNELS;
+const double THRESHOLD = 0.5*(REGION_R + REGION_R + 1)*(REGION_R + REGION_R + 1)*NUM_CHANNELS;
const int NUM_MODES = 1; // The paper describes how multiple modes can be maintained,
// but this implementation does not fully support more than one
@@ -48,8 +50,8 @@ public:
void LBP(RgbImage& image, RgbImage& texture);
void Histogram(RgbImage& texture, TextureHistogram* curTextureHist);
int ProximityMeasure(TextureHistogram& bgTexture, TextureHistogram& curTextureHist);
- void BgsCompare(TextureArray* bgModel, TextureHistogram* curTextureHist,
- unsigned char* modeArray, float threshold, BwImage& fgMask);
- void UpdateModel(BwImage& fgMask, TextureArray* bgModel,
- TextureHistogram* curTextureHist, unsigned char* modeArray);
+ void BgsCompare(TextureArray* bgModel, TextureHistogram* curTextureHist,
+ unsigned char* modeArray, float threshold, BwImage& fgMask);
+ void UpdateModel(BwImage& fgMask, TextureArray* bgModel,
+ TextureHistogram* curTextureHist, unsigned char* modeArray);
};
diff --git a/package_bgs/dp/WrenGA.cpp b/package_bgs/dp/WrenGA.cpp
index 16e2640..80a9e27 100644
--- a/package_bgs/dp/WrenGA.cpp
+++ b/package_bgs/dp/WrenGA.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* WrenGA.h
*
-* Purpose: Implementation of the running Gaussian average background
+* Purpose: Implementation of the running Gaussian average background
* subtraction algorithm described in:
* "Pfinder: real-time tracking of the human body"
* by C. Wren et al (1997)
@@ -36,114 +36,114 @@ using namespace Algorithms::BackgroundSubtraction;
WrenGA::WrenGA()
{
- m_gaussian = NULL;
+ m_gaussian = NULL;
}
WrenGA::~WrenGA()
{
- delete[] m_gaussian;
+ delete[] m_gaussian;
}
void WrenGA::Initalize(const BgsParams& param)
{
- m_params = (WrenParams&)param;
-
- m_variance = 36.0f;
-
- // GMM for each pixel
- m_gaussian = new GAUSSIAN[m_params.Size()];
- for(unsigned int i = 0; i < m_params.Size(); ++i)
- {
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- m_gaussian[i].mu[ch] = 0;
- m_gaussian[i].var[ch] = 0;
- }
- }
-
- m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ m_params = (WrenParams&)param;
+
+ m_variance = 36.0f;
+
+ // GMM for each pixel
+ m_gaussian = new GAUSSIAN[m_params.Size()];
+ for (unsigned int i = 0; i < m_params.Size(); ++i)
+ {
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ m_gaussian[i].mu[ch] = 0;
+ m_gaussian[i].var[ch] = 0;
+ }
+ }
+
+ m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
}
void WrenGA::InitModel(const RgbImage& data)
{
- int pos = 0;
-
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- m_gaussian[pos].mu[ch] = data(r,c,ch);
- m_gaussian[pos].var[ch] = m_variance;
- }
-
- pos++;
- }
- }
+ int pos = 0;
+
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ m_gaussian[pos].mu[ch] = data(r, c, ch);
+ m_gaussian[pos].var[ch] = m_variance;
+ }
+
+ pos++;
+ }
+ }
}
-void WrenGA::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void WrenGA::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- int pos = 0;
-
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- // perform conditional updating only if we are passed the learning phase
- if(update_mask(r,c) == BACKGROUND || frame_num < m_params.LearningFrames())
- {
- float dR = m_gaussian[pos].mu[0] - data(r,c,0);
- float dG = m_gaussian[pos].mu[1] - data(r,c,1);
- float dB = m_gaussian[pos].mu[2] - data(r,c,2);
-
- float dist = (dR*dR + dG*dG + dB*dB);
-
- m_gaussian[pos].mu[0] -= m_params.Alpha()*(dR);
- m_gaussian[pos].mu[1] -= m_params.Alpha()*(dG);
- m_gaussian[pos].mu[2] -= m_params.Alpha()*(dB);
-
- float sigmanew = m_gaussian[pos].var[0] + m_params.Alpha()*(dist-m_gaussian[pos].var[0]);
- m_gaussian[pos].var[0] = sigmanew < 4 ? 4 : sigmanew > 5*m_variance ? 5*m_variance : sigmanew;
-
- m_background(r, c, 0) = (unsigned char)(m_gaussian[pos].mu[0] + 0.5);
- m_background(r, c, 1) = (unsigned char)(m_gaussian[pos].mu[1] + 0.5);
- m_background(r, c, 2) = (unsigned char)(m_gaussian[pos].mu[2] + 0.5);
- }
-
- pos++;
- }
- }
+ int pos = 0;
+
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ // perform conditional updating only if we are passed the learning phase
+ if (update_mask(r, c) == BACKGROUND || frame_num < m_params.LearningFrames())
+ {
+ float dR = m_gaussian[pos].mu[0] - data(r, c, 0);
+ float dG = m_gaussian[pos].mu[1] - data(r, c, 1);
+ float dB = m_gaussian[pos].mu[2] - data(r, c, 2);
+
+ float dist = (dR*dR + dG*dG + dB*dB);
+
+ m_gaussian[pos].mu[0] -= m_params.Alpha()*(dR);
+ m_gaussian[pos].mu[1] -= m_params.Alpha()*(dG);
+ m_gaussian[pos].mu[2] -= m_params.Alpha()*(dB);
+
+ float sigmanew = m_gaussian[pos].var[0] + m_params.Alpha()*(dist - m_gaussian[pos].var[0]);
+ m_gaussian[pos].var[0] = sigmanew < 4 ? 4 : sigmanew > 5 * m_variance ? 5 * m_variance : sigmanew;
+
+ m_background(r, c, 0) = (unsigned char)(m_gaussian[pos].mu[0] + 0.5);
+ m_background(r, c, 1) = (unsigned char)(m_gaussian[pos].mu[1] + 0.5);
+ m_background(r, c, 2) = (unsigned char)(m_gaussian[pos].mu[2] + 0.5);
+ }
+
+ pos++;
+ }
+ }
}
-void WrenGA::SubtractPixel(int r, int c, const RgbPixel& pixel,
- unsigned char& low_threshold,
- unsigned char& high_threshold)
+void WrenGA::SubtractPixel(int r, int c, const RgbPixel& pixel,
+ unsigned char& low_threshold,
+ unsigned char& high_threshold)
{
- unsigned int pos = r*m_params.Width()+c;
-
- // calculate distance between model and pixel
- float mu[NUM_CHANNELS];
- float var[1];
- float delta[NUM_CHANNELS];
- float dist = 0;
- for(int ch = 0; ch < NUM_CHANNELS; ++ch)
- {
- mu[ch] = m_gaussian[pos].mu[ch];
- var[0] = m_gaussian[pos].var[0];
- delta[ch] = mu[ch] - pixel(ch);
- dist += delta[ch]*delta[ch];
- }
-
- // calculate the squared distance and see if pixel fits the B/G model
- low_threshold = BACKGROUND;
- high_threshold = BACKGROUND;
-
- if(dist > m_params.LowThreshold()*var[0])
- low_threshold = FOREGROUND;
- if(dist > m_params.HighThreshold()*var[0])
- high_threshold = FOREGROUND;
+ unsigned int pos = r*m_params.Width() + c;
+
+ // calculate distance between model and pixel
+ float mu[NUM_CHANNELS];
+ float var[1];
+ float delta[NUM_CHANNELS];
+ float dist = 0;
+ for (int ch = 0; ch < NUM_CHANNELS; ++ch)
+ {
+ mu[ch] = m_gaussian[pos].mu[ch];
+ var[0] = m_gaussian[pos].var[0];
+ delta[ch] = mu[ch] - pixel(ch);
+ dist += delta[ch] * delta[ch];
+ }
+
+ // calculate the squared distance and see if pixel fits the B/G model
+ low_threshold = BACKGROUND;
+ high_threshold = BACKGROUND;
+
+ if (dist > m_params.LowThreshold()*var[0])
+ low_threshold = FOREGROUND;
+ if (dist > m_params.HighThreshold()*var[0])
+ high_threshold = FOREGROUND;
}
///////////////////////////////////////////////////////////////////////////////
@@ -154,20 +154,20 @@ void WrenGA::SubtractPixel(int r, int c, const RgbPixel& pixel,
// (the memory should already be reserved)
// values: 255-foreground, 125-shadow, 0-background
///////////////////////////////////////////////////////////////////////////////
-void WrenGA::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void WrenGA::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
- unsigned char low_threshold, high_threshold;
-
- // update each pixel of the image
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- SubtractPixel(r, c, data(r,c), low_threshold, high_threshold);
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
- }
- }
+ unsigned char low_threshold, high_threshold;
+
+ // update each pixel of the image
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ SubtractPixel(r, c, data(r, c), low_threshold, high_threshold);
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
+ }
+ }
}
diff --git a/package_bgs/dp/WrenGA.h b/package_bgs/dp/WrenGA.h
index 116c292..97e97ee 100644
--- a/package_bgs/dp/WrenGA.h
+++ b/package_bgs/dp/WrenGA.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* WrenGA.hpp
*
-* Purpose: Implementation of the running Gaussian average background
+* Purpose: Implementation of the running Gaussian average background
* subtraction algorithm described in:
* "Pfinder: real-time tracking of the human body"
* by C. Wren et al (1997)
@@ -33,16 +33,14 @@ Example:
Algorithms::BackgroundSubtraction::WrenParams params;
params.SetFrameSize(width, height);
params.LowThreshold() = 3.5f*3.5f;
-params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
params.Alpha() = 0.005f;
params.LearningFrames() = 30;
Algorithms::BackgroundSubtraction::WrenGA bgs;
bgs.Initalize(params);
******************************************************************************/
-
-#ifndef WREN_GA_H
-#define WREN_GA_H
+#pragma once
#include "Bgs.h"
@@ -74,7 +72,7 @@ namespace Algorithms
// --- Mean BGS algorithm ---
class WrenGA : public Bgs
{
- private:
+ private:
struct GAUSSIAN
{
float mu[NUM_CHANNELS];
@@ -88,19 +86,19 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background() { return &m_background; }
- private:
- void SubtractPixel(int r, int c, const RgbPixel& pixel,
+ private:
+ void SubtractPixel(int r, int c, const RgbPixel& pixel,
unsigned char& lowThreshold, unsigned char& highThreshold);
WrenParams m_params;
- // Initial variance for the newly generated components.
+ // Initial variance for the newly generated components.
float m_variance;
// dynamic array for the mixture of Gaussians
@@ -110,11 +108,3 @@ namespace Algorithms
};
}
}
-
-#endif
-
-
-
-
-
-
diff --git a/package_bgs/dp/ZivkovicAGMM.cpp b/package_bgs/dp/ZivkovicAGMM.cpp
index 041ffc4..f73d5a1 100644
--- a/package_bgs/dp/ZivkovicAGMM.cpp
+++ b/package_bgs/dp/ZivkovicAGMM.cpp
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* ZivkovicAGMM.cpp
*
-* Purpose: Implementation of the Gaussian mixture model (GMM) background
+* Purpose: Implementation of the Gaussian mixture model (GMM) background
* subtraction algorithm developed by Z. Zivkovic.
*
* Author: Donovan Parks, September 2007
@@ -28,13 +28,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* following papers:
*
* "Improved adaptive Gausian mixture model for background subtraction"
-* Z.Zivkovic
+* Z.Zivkovic
* International Conference Pattern Recognition, UK, August, 2004
*
*
-* "Efficient Adaptive Density Estimapion per Image Pixel for the
+* "Efficient Adaptive Density Estimapion per Image Pixel for the
* Task of Background Subtraction"
-* Z.Zivkovic, F. van der Heijden
+* Z.Zivkovic, F. van der Heijden
* Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
*
* Zivkovic's code can be obtained at: www.zoranz.net
@@ -46,328 +46,328 @@ using namespace Algorithms::BackgroundSubtraction;
ZivkovicAGMM::ZivkovicAGMM()
{
- m_modes = NULL;
- m_modes_per_pixel = NULL;
+ m_modes = NULL;
+ m_modes_per_pixel = NULL;
}
ZivkovicAGMM::~ZivkovicAGMM()
{
- delete[] m_modes;
- delete[] m_modes_per_pixel;
+ delete[] m_modes;
+ delete[] m_modes_per_pixel;
}
void ZivkovicAGMM::Initalize(const BgsParams& param)
{
- m_params = (ZivkovicParams&)param;
+ m_params = (ZivkovicParams&)param;
- m_num_bands = 3; //always 3 - not implemented for other values!
- m_bg_threshold = 0.75f; //1-cf from the paper
- m_variance = 36.0f; // variance for the new mode
- m_complexity_prior = 0.05f; // complexity reduction prior constant
+ m_num_bands = 3; //always 3 - not implemented for other values!
+ m_bg_threshold = 0.75f; //1-cf from the paper
+ m_variance = 36.0f; // variance for the new mode
+ m_complexity_prior = 0.05f; // complexity reduction prior constant
- // GMM for each pixel
- m_modes = new GMM[m_params.Size()*m_params.MaxModes()];
+ // GMM for each pixel
+ m_modes = new GMM[m_params.Size()*m_params.MaxModes()];
- // used modes per pixel
- m_modes_per_pixel = new unsigned char[m_params.Size()];
+ // used modes per pixel
+ m_modes_per_pixel = new unsigned char[m_params.Size()];
- m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
+ m_background = cvCreateImage(cvSize(m_params.Width(), m_params.Height()), IPL_DEPTH_8U, 3);
}
void ZivkovicAGMM::InitModel(const RgbImage& data)
{
- for(unsigned int i = 0; i < m_params.Size(); ++i)
- {
- m_modes_per_pixel[i] = 0;
- }
-
- for(unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
- {
- m_modes[i].weight = 0;
- m_modes[i].sigma = 0;
- m_modes[i].muR = 0;
- m_modes[i].muG = 0;
- m_modes[i].muB = 0;
- }
+ for (unsigned int i = 0; i < m_params.Size(); ++i)
+ {
+ m_modes_per_pixel[i] = 0;
+ }
+
+ for (unsigned int i = 0; i < m_params.Size()*m_params.MaxModes(); ++i)
+ {
+ m_modes[i].weight = 0;
+ m_modes[i].sigma = 0;
+ m_modes[i].muR = 0;
+ m_modes[i].muG = 0;
+ m_modes[i].muB = 0;
+ }
}
-void ZivkovicAGMM::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
+void ZivkovicAGMM::Update(int frame_num, const RgbImage& data, const BwImage& update_mask)
{
- // it doesn't make sense to have conditional updates in the GMM framework
+ // it doesn't make sense to have conditional updates in the GMM framework
}
-void ZivkovicAGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char* pModesUsed,
- unsigned char& low_threshold, unsigned char& high_threshold)
+void ZivkovicAGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char* pModesUsed,
+ unsigned char& low_threshold, unsigned char& high_threshold)
{
- //calculate distances to the modes (+ sort???)
- //here we need to go in descending order!!!
- long pos;
- bool bFitsPDF=0;
- bool bBackgroundLow=false;
- bool bBackgroundHigh=false;
-
- float fOneMinAlpha = 1-m_params.Alpha();
-
- float prune = -m_params.Alpha()*m_complexity_prior;
-
- int nModes =* pModesUsed;
- float totalWeight = 0.0f;
-
- // calculate number of Gaussians to include in the background model
- int backgroundGaussians = 0;
- double sum = 0.0;
- for(int i = 0; i < nModes; ++i)
- {
- if(sum < m_bg_threshold)
- {
- backgroundGaussians++;
- sum += m_modes[posPixel+i].weight;
- }
- else
- {
- break;
- }
- }
-
- // update all distributions and check for match with current pixel
- for (int iModes = 0; iModes < nModes; iModes++)
- {
- pos=posPixel+iModes;
- float weight = m_modes[pos].weight;
-
- //fit not found yet
- if (!bFitsPDF)
- {
- //check if it belongs to some of the modes
- //calculate distance
- float var = m_modes[pos].sigma;
- float muR = m_modes[pos].muR;
- float muG = m_modes[pos].muG;
- float muB = m_modes[pos].muB;
-
- float dR=muR - pixel(0);
- float dG=muG - pixel(1);
- float dB=muB - pixel(2);
-
- // calculate the squared distance
- float dist = (dR*dR + dG*dG + dB*dB);
-
- if(dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
- bBackgroundHigh = true;
-
- //check fit
- if (dist < m_params.LowThreshold()*var)
- {
- /////
- //belongs to the mode
- bFitsPDF = true;
-
- // check if this Gaussian is part of the background model
- if(iModes < backgroundGaussians)
- bBackgroundLow = true;
-
- //update distribution
- float k = m_params.Alpha()/weight;
- weight = fOneMinAlpha*weight+prune;
- weight += m_params.Alpha();
- m_modes[pos].weight = weight;
- m_modes[pos].muR = muR - k*(dR);
- m_modes[pos].muG = muG - k*(dG);
- m_modes[pos].muB = muB - k*(dB);
-
- //limit update speed for cov matrice
- //not needed
- //k=k>20*m_m_params.Alpha()?20*m_m_params.Alpha():k;
- //float sigmanew = var + k*((0.33*(dR*dR+dG*dG+dB*dB))-var);
- //float sigmanew = var + k*((dR*dR+dG*dG+dB*dB)-var);
- //float sigmanew = var + k*((0.33*dist)-var);
- float sigmanew = var + k*(dist-var);
-
- //limit the variance
- m_modes[pos].sigma = sigmanew < 4 ? 4 : sigmanew > 5*m_variance ? 5*m_variance : sigmanew;
-
- // Sort weights so they are in desending order. Note that only the weight for this
- // mode will increase and that the weight for all modes that were previously larger than
- // this one have already been modified and will not be modified again. Thus, we just need to
- // the correct position of this mode in the already sorted list.
-
- // Zivkovic implementation has been modified for clarity, but the results are equivalent
- /*
- for (int iLocal = iModes;iLocal>0;iLocal--)
- {
- long posLocal=posPixel + iLocal;
- if (weight < (m_modes[posLocal-1].weight))
- {
- break;
- }
- else
- {
- //swap
- GMM temp = m_modes[posLocal];
- m_modes[posLocal] = m_modes[posLocal-1];
- m_modes[posLocal-1] = temp;
- }
- }
- */
-
- for (int iLocal = iModes; iLocal > 0; iLocal--)
- {
- long posLocal = posPixel + iLocal;
- if (m_modes[posLocal].weight > m_modes[posLocal-1].weight)
- {
- //swap
- GMM temp = m_modes[posLocal];
- m_modes[posLocal] = m_modes[posLocal-1];
- m_modes[posLocal-1] = temp;
- }
- else
- {
- break;
- }
- }
- }
- else
- {
- weight = fOneMinAlpha*weight+prune;
- //check prune
- if (weight < -prune)
- {
- weight=0.0;
- nModes--;
- }
- m_modes[pos].weight = weight;
- }
- //check if it fits the current mode (2.5 sigma)
- ///////
- }
- //fit not found yet
- /////
- else
- {
- weight = fOneMinAlpha*weight + prune;
- //check prune
- if (weight < -prune)
- {
- weight=0.0;
- nModes--;
- }
- m_modes[pos].weight = weight;
- }
- totalWeight += weight;
- }
-
- //renormalize weights so they sum to 1
- for (int iLocal = 0; iLocal < nModes; iLocal++)
- {
- m_modes[posPixel+ iLocal].weight = m_modes[posPixel+ iLocal].weight/totalWeight;
- }
-
- //make new mode if needed and exit
- if (!bFitsPDF)
- {
- if (nModes == m_params.MaxModes())
- {
- //replace the weakest
- }
- else
- {
- nModes++;
- }
- pos = posPixel + nModes-1;
-
- if (nModes==1)
- m_modes[pos].weight=1;
- else
- m_modes[pos].weight=m_params.Alpha();
-
- // Zivkovic implementation changes as this will not result in the
- // weights adding to 1
- /*
- int iLocal;
- for (iLocal = 0; iLocal < m_params.MaxModes()odes-1; iLocal++)
- {
- m_modes[posPixel+ iLocal].weight *= fOneMinAlpha;
- }
- */
-
- // Revised implementation:
- //renormalize weights
- int iLocal;
- float sum = 0.0;
- for (iLocal = 0; iLocal < nModes; iLocal++)
- {
- sum += m_modes[posPixel+ iLocal].weight;
- }
-
- float invSum = 1.0f/sum;
- for (iLocal = 0; iLocal < nModes; iLocal++)
- {
- m_modes[posPixel+ iLocal].weight *= invSum;
- }
-
- m_modes[pos].muR=pixel(0);
- m_modes[pos].muG=pixel(1);
- m_modes[pos].muB=pixel(2);
- m_modes[pos].sigma=m_variance;
-
- // Zivkovic implementation to sort GMM so they are sorted in descending order according to their weight.
- // It has been revised for clarity, but the results are equivalent
- /*
- for (iLocal = m_params.MaxModes()odes-1; iLocal > 0; iLocal--)
- {
- long posLocal = posPixel + iLocal;
- if (m_params.Alpha() < (m_modes[posLocal-1].weight))
- {
- break;
- }
- else
- {
- //swap
- GMM temp = m_modes[posLocal];
- m_modes[posLocal] = m_modes[posLocal-1];
- m_modes[posLocal-1] = temp;
- }
- }
- */
-
- // sort GMM so they are sorted in descending order according to their weight
- for (iLocal = nModes-1; iLocal > 0; iLocal--)
- {
- long posLocal = posPixel + iLocal;
- if (m_modes[posLocal].weight > m_modes[posLocal-1].weight)
- {
- //swap
- GMM temp = m_modes[posLocal];
- m_modes[posLocal] = m_modes[posLocal-1];
- m_modes[posLocal-1] = temp;
- }
- else
- {
- break;
- }
- }
- }
-
- //set the number of modes
- *pModesUsed=nModes;
-
- if(bBackgroundLow)
- {
- low_threshold = BACKGROUND;
- }
- else
- {
- low_threshold = FOREGROUND;
- }
-
- if(bBackgroundHigh)
- {
- high_threshold = BACKGROUND;
- }
- else
- {
- high_threshold = FOREGROUND;
- }
+ //calculate distances to the modes (+ sort???)
+ //here we need to go in descending order!!!
+ long pos;
+ bool bFitsPDF = 0;
+ bool bBackgroundLow = false;
+ bool bBackgroundHigh = false;
+
+ float fOneMinAlpha = 1 - m_params.Alpha();
+
+ float prune = -m_params.Alpha()*m_complexity_prior;
+
+ int nModes = *pModesUsed;
+ float totalWeight = 0.0f;
+
+ // calculate number of Gaussians to include in the background model
+ int backgroundGaussians = 0;
+ double sum = 0.0;
+ for (int i = 0; i < nModes; ++i)
+ {
+ if (sum < m_bg_threshold)
+ {
+ backgroundGaussians++;
+ sum += m_modes[posPixel + i].weight;
+ }
+ else
+ {
+ break;
+ }
+ }
+
+ // update all distributions and check for match with current pixel
+ for (int iModes = 0; iModes < nModes; iModes++)
+ {
+ pos = posPixel + iModes;
+ float weight = m_modes[pos].weight;
+
+ //fit not found yet
+ if (!bFitsPDF)
+ {
+ //check if it belongs to some of the modes
+ //calculate distance
+ float var = m_modes[pos].sigma;
+ float muR = m_modes[pos].muR;
+ float muG = m_modes[pos].muG;
+ float muB = m_modes[pos].muB;
+
+ float dR = muR - pixel(0);
+ float dG = muG - pixel(1);
+ float dB = muB - pixel(2);
+
+ // calculate the squared distance
+ float dist = (dR*dR + dG*dG + dB*dB);
+
+ if (dist < m_params.HighThreshold()*var && iModes < backgroundGaussians)
+ bBackgroundHigh = true;
+
+ //check fit
+ if (dist < m_params.LowThreshold()*var)
+ {
+ /////
+ //belongs to the mode
+ bFitsPDF = true;
+
+ // check if this Gaussian is part of the background model
+ if (iModes < backgroundGaussians)
+ bBackgroundLow = true;
+
+ //update distribution
+ float k = m_params.Alpha() / weight;
+ weight = fOneMinAlpha*weight + prune;
+ weight += m_params.Alpha();
+ m_modes[pos].weight = weight;
+ m_modes[pos].muR = muR - k*(dR);
+ m_modes[pos].muG = muG - k*(dG);
+ m_modes[pos].muB = muB - k*(dB);
+
+ //limit update speed for cov matrice
+ //not needed
+ //k=k>20*m_m_params.Alpha()?20*m_m_params.Alpha():k;
+ //float sigmanew = var + k*((0.33*(dR*dR+dG*dG+dB*dB))-var);
+ //float sigmanew = var + k*((dR*dR+dG*dG+dB*dB)-var);
+ //float sigmanew = var + k*((0.33*dist)-var);
+ float sigmanew = var + k*(dist - var);
+
+ //limit the variance
+ m_modes[pos].sigma = sigmanew < 4 ? 4 : sigmanew > 5 * m_variance ? 5 * m_variance : sigmanew;
+
+ // Sort weights so they are in desending order. Note that only the weight for this
+ // mode will increase and that the weight for all modes that were previously larger than
+ // this one have already been modified and will not be modified again. Thus, we just need to
+ // the correct position of this mode in the already sorted list.
+
+ // Zivkovic implementation has been modified for clarity, but the results are equivalent
+ /*
+ for (int iLocal = iModes;iLocal>0;iLocal--)
+ {
+ long posLocal=posPixel + iLocal;
+ if (weight < (m_modes[posLocal-1].weight))
+ {
+ break;
+ }
+ else
+ {
+ //swap
+ GMM temp = m_modes[posLocal];
+ m_modes[posLocal] = m_modes[posLocal-1];
+ m_modes[posLocal-1] = temp;
+ }
+ }
+ */
+
+ for (int iLocal = iModes; iLocal > 0; iLocal--)
+ {
+ long posLocal = posPixel + iLocal;
+ if (m_modes[posLocal].weight > m_modes[posLocal - 1].weight)
+ {
+ //swap
+ GMM temp = m_modes[posLocal];
+ m_modes[posLocal] = m_modes[posLocal - 1];
+ m_modes[posLocal - 1] = temp;
+ }
+ else
+ {
+ break;
+ }
+ }
+ }
+ else
+ {
+ weight = fOneMinAlpha*weight + prune;
+ //check prune
+ if (weight < -prune)
+ {
+ weight = 0.0;
+ nModes--;
+ }
+ m_modes[pos].weight = weight;
+ }
+ //check if it fits the current mode (2.5 sigma)
+ ///////
+ }
+ //fit not found yet
+ /////
+ else
+ {
+ weight = fOneMinAlpha*weight + prune;
+ //check prune
+ if (weight < -prune)
+ {
+ weight = 0.0;
+ nModes--;
+ }
+ m_modes[pos].weight = weight;
+ }
+ totalWeight += weight;
+ }
+
+ //renormalize weights so they sum to 1
+ for (int iLocal = 0; iLocal < nModes; iLocal++)
+ {
+ m_modes[posPixel + iLocal].weight = m_modes[posPixel + iLocal].weight / totalWeight;
+ }
+
+ //make new mode if needed and exit
+ if (!bFitsPDF)
+ {
+ if (nModes == m_params.MaxModes())
+ {
+ //replace the weakest
+ }
+ else
+ {
+ nModes++;
+ }
+ pos = posPixel + nModes - 1;
+
+ if (nModes == 1)
+ m_modes[pos].weight = 1;
+ else
+ m_modes[pos].weight = m_params.Alpha();
+
+ // Zivkovic implementation changes as this will not result in the
+ // weights adding to 1
+ /*
+ int iLocal;
+ for (iLocal = 0; iLocal < m_params.MaxModes()odes-1; iLocal++)
+ {
+ m_modes[posPixel+ iLocal].weight *= fOneMinAlpha;
+ }
+ */
+
+ // Revised implementation:
+ //renormalize weights
+ int iLocal;
+ float sum = 0.0;
+ for (iLocal = 0; iLocal < nModes; iLocal++)
+ {
+ sum += m_modes[posPixel + iLocal].weight;
+ }
+
+ float invSum = 1.0f / sum;
+ for (iLocal = 0; iLocal < nModes; iLocal++)
+ {
+ m_modes[posPixel + iLocal].weight *= invSum;
+ }
+
+ m_modes[pos].muR = pixel(0);
+ m_modes[pos].muG = pixel(1);
+ m_modes[pos].muB = pixel(2);
+ m_modes[pos].sigma = m_variance;
+
+ // Zivkovic implementation to sort GMM so they are sorted in descending order according to their weight.
+ // It has been revised for clarity, but the results are equivalent
+ /*
+ for (iLocal = m_params.MaxModes()odes-1; iLocal > 0; iLocal--)
+ {
+ long posLocal = posPixel + iLocal;
+ if (m_params.Alpha() < (m_modes[posLocal-1].weight))
+ {
+ break;
+ }
+ else
+ {
+ //swap
+ GMM temp = m_modes[posLocal];
+ m_modes[posLocal] = m_modes[posLocal-1];
+ m_modes[posLocal-1] = temp;
+ }
+ }
+ */
+
+ // sort GMM so they are sorted in descending order according to their weight
+ for (iLocal = nModes - 1; iLocal > 0; iLocal--)
+ {
+ long posLocal = posPixel + iLocal;
+ if (m_modes[posLocal].weight > m_modes[posLocal - 1].weight)
+ {
+ //swap
+ GMM temp = m_modes[posLocal];
+ m_modes[posLocal] = m_modes[posLocal - 1];
+ m_modes[posLocal - 1] = temp;
+ }
+ else
+ {
+ break;
+ }
+ }
+ }
+
+ //set the number of modes
+ *pModesUsed = nModes;
+
+ if (bBackgroundLow)
+ {
+ low_threshold = BACKGROUND;
+ }
+ else
+ {
+ low_threshold = FOREGROUND;
+ }
+
+ if (bBackgroundHigh)
+ {
+ high_threshold = BACKGROUND;
+ }
+ else
+ {
+ high_threshold = FOREGROUND;
+ }
}
@@ -379,30 +379,30 @@ void ZivkovicAGMM::SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned
// (the memory should already be reserved)
// values: 255-foreground, 125-shadow, 0-background
///////////////////////////////////////////////////////////////////////////////
-void ZivkovicAGMM::Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask)
+void ZivkovicAGMM::Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask)
{
- unsigned char low_threshold, high_threshold;
-
- // update each pixel of the image
- long posPixel;
- unsigned char* pUsedModes=m_modes_per_pixel;
- for(unsigned int r = 0; r < m_params.Height(); ++r)
- {
- for(unsigned int c = 0; c < m_params.Width(); ++c)
- {
- //update model+ background subtract
- posPixel=(r*m_params.Width()+c)*m_params.MaxModes();
- SubtractPixel(posPixel, data(r,c), pUsedModes, low_threshold, high_threshold);
- low_threshold_mask(r,c) = low_threshold;
- high_threshold_mask(r,c) = high_threshold;
-
- m_background(r,c,0) = (unsigned char)m_modes[posPixel].muR;
- m_background(r,c,1) = (unsigned char)m_modes[posPixel].muG;
- m_background(r,c,2) = (unsigned char)m_modes[posPixel].muB;
-
- pUsedModes++;
- }
- }
+ unsigned char low_threshold, high_threshold;
+
+ // update each pixel of the image
+ long posPixel;
+ unsigned char* pUsedModes = m_modes_per_pixel;
+ for (unsigned int r = 0; r < m_params.Height(); ++r)
+ {
+ for (unsigned int c = 0; c < m_params.Width(); ++c)
+ {
+ //update model+ background subtract
+ posPixel = (r*m_params.Width() + c)*m_params.MaxModes();
+ SubtractPixel(posPixel, data(r, c), pUsedModes, low_threshold, high_threshold);
+ low_threshold_mask(r, c) = low_threshold;
+ high_threshold_mask(r, c) = high_threshold;
+
+ m_background(r, c, 0) = (unsigned char)m_modes[posPixel].muR;
+ m_background(r, c, 1) = (unsigned char)m_modes[posPixel].muG;
+ m_background(r, c, 2) = (unsigned char)m_modes[posPixel].muB;
+
+ pUsedModes++;
+ }
+ }
}
diff --git a/package_bgs/dp/ZivkovicAGMM.h b/package_bgs/dp/ZivkovicAGMM.h
index 1cd99b0..07da9c3 100644
--- a/package_bgs/dp/ZivkovicAGMM.h
+++ b/package_bgs/dp/ZivkovicAGMM.h
@@ -18,7 +18,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*
* ZivkovicAGMM.hpp
*
-* Purpose: Implementation of the Gaussian mixture model (GMM) background
+* Purpose: Implementation of the Gaussian mixture model (GMM) background
* subtraction algorithm developed by Z. Zivkovic.
*
* Author: Donovan Parks, September 2007
@@ -28,13 +28,13 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
* following papers:
*
* "Improved adaptive Gausian mixture model for background subtraction"
-* Z.Zivkovic
+* Z.Zivkovic
* International Conference Pattern Recognition, UK, August, 2004
*
*
-* "Efficient Adaptive Density Estimapion per Image Pixel for the
+* "Efficient Adaptive Density Estimapion per Image Pixel for the
* Task of Background Subtraction"
-* Z.Zivkovic, F. van der Heijden
+* Z.Zivkovic, F. van der Heijden
* Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
*
* Zivkovic's code can be obtained at: www.zoranz.net
@@ -43,16 +43,14 @@ Example:
Algorithms::BackgroundSubtraction::ZivkovicParams params;
params.SetFrameSize(width, height);
params.LowThreshold() = 5.0f*5.0f;
-params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
+params.HighThreshold() = 2*params.LowThreshold(); // Note: high threshold is used by post-processing
params.Alpha() = 0.001f;
params.MaxModes() = 3;
Algorithms::BackgroundSubtraction::ZivkovicAGMM bgs;
bgs.Initalize(params);
******************************************************************************/
-
-#ifndef ZIVKOVIC_AGMM_H
-#define ZIVKOVIC_AGMM_H
+#pragma once
#include "Bgs.h"
@@ -71,18 +69,18 @@ namespace Algorithms
int &MaxModes() { return m_max_modes; }
private:
- // Threshold on the squared dist. to decide when a sample is close to an existing
- // components. If it is not close to any a new component will be generated.
- // Smaller threshold values lead to more generated components and higher threshold values
+ // Threshold on the squared dist. to decide when a sample is close to an existing
+ // components. If it is not close to any a new component will be generated.
+ // Smaller threshold values lead to more generated components and higher threshold values
// lead to a small number of components but they can grow too large.
//
- // It is usual easiest to think of these thresholds as being the number of variances (not standard deviations)
+ // It is usual easiest to think of these thresholds as being the number of variances (not standard deviations)
// away from the mean of a pixel before it is considered to be from the foreground.
float m_low_threshold;
float m_high_threshold;
// alpha - speed of update - if the time interval you want to average over is T
- // set alpha=1/T.
+ // set alpha=1/T.
float m_alpha;
// Maximum number of modes (Gaussian components) that will be used per pixel
@@ -109,14 +107,14 @@ namespace Algorithms
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
- void Subtract(int frame_num, const RgbImage& data,
- BwImage& low_threshold_mask, BwImage& high_threshold_mask);
- void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
+ void Subtract(int frame_num, const RgbImage& data,
+ BwImage& low_threshold_mask, BwImage& high_threshold_mask);
+ void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background() { return &m_background; }
private:
- void SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char* pModesUsed,
+ void SubtractPixel(long posPixel, const RgbPixel& pixel, unsigned char* pModesUsed,
unsigned char& lowThreshold, unsigned char& highThreshold);
// User adjustable parameters
@@ -128,13 +126,13 @@ namespace Algorithms
// it is considered foreground
float m_bg_threshold; //1-cf from the paper
- // Initial variance for the newly generated components.
- // It will will influence the speed of adaptation. A good guess should be made.
+ // Initial variance for the newly generated components.
+ // It will will influence the speed of adaptation. A good guess should be made.
// A simple way is to estimate the typical standard deviation from the images.
float m_variance;
// This is related to the number of samples needed to accept that a component
- // actually exists.
+ // actually exists.
float m_complexity_prior;
//data
@@ -150,11 +148,3 @@ namespace Algorithms
};
}
}
-
-#endif
-
-
-
-
-
-
diff --git a/package_bgs/jmo/BlobResult.cpp b/package_bgs/jmo/BlobResult.cpp
deleted file mode 100644
index 1a047c7..0000000
--- a/package_bgs/jmo/BlobResult.cpp
+++ /dev/null
@@ -1,847 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-/* --- --- ---
-* Copyright (C) 2008--2010 Idiap Research Institute (.....@idiap.ch)
-* All rights reserved.
-*
-* Redistribution and use in source and binary forms, with or without
-* modification, are permitted provided that the following conditions
-* are met:
-* 1. Redistributions of source code must retain the above copyright
-* notice, this list of conditions and the following disclaimer.
-* 2. Redistributions in binary form must reproduce the above copyright
-* notice, this list of conditions and the following disclaimer in the
-* documentation and/or other materials provided with the distribution.
-* 3. The name of the author may not be used to endorse or promote products
-* derived from this software without specific prior written permission.
-*
-* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
-* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
-* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
-* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
-* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
-* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
-* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
-* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
-* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-*/
-/************************************************************************
-BlobResult.cpp
-
-FUNCIONALITAT: Implementaci� de la classe CBlobResult
-AUTOR: Inspecta S.L.
-MODIFICACIONS (Modificaci�, Autor, Data):
-
-**************************************************************************/
-
-#include <limits.h>
-#include <stdio.h>
-#include <functional>
-#include <algorithm>
-#include "BlobResult.h"
-#include "BlobExtraction.h"
-
-/**************************************************************************
-Constructors / Destructors
-**************************************************************************/
-
-namespace Blob
-{
-
- /**
- - FUNCI�: CBlobResult
- - FUNCIONALITAT: Constructor estandard.
- - PAR�METRES:
- - RESULTAT:
- - Crea un CBlobResult sense cap blob
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobResult
- - FUNCTIONALITY: Standard constructor
- - PARAMETERS:
- - RESULT:
- - creates an empty set of blobs
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlobResult::CBlobResult()
- {
- m_blobs = blob_vector();
- }
-
- /**
- - FUNCI�: CBlobResult
- - FUNCIONALITAT: Constructor a partir d'una imatge. Inicialitza la seq��ncia de blobs
- amb els blobs resultants de l'an�lisi de blobs de la imatge.
- - PAR�METRES:
- - source: imatge d'on s'extreuran els blobs
- - mask: m�scara a aplicar. Nom�s es calcularan els blobs on la m�scara sigui
- diferent de 0. Els blobs que toquin a un pixel 0 de la m�scara seran
- considerats exteriors.
- - threshold: llindar que s'aplicar� a la imatge source abans de calcular els blobs
- - findmoments: indica si s'han de calcular els moments de cada blob
- - RESULTAT:
- - objecte CBlobResult amb els blobs de la imatge source
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlob
- - FUNCTIONALITY: Constructor from an image. Fills an object with all the blobs in
- the image
- - PARAMETERS:
- - source: image to extract the blobs from
- - mask: optional mask to apply. The blobs will be extracted where the mask is
- not 0. All the neighbouring blobs where the mask is 0 will be extern blobs
- - threshold: threshold level to apply to the image before computing blobs
- - findmoments: true to calculate the blob moments (slower)
- - RESULT:
- - object with all the blobs in the image. It throws an EXCEPCIO_CALCUL_BLOBS
- if some error appears in the BlobAnalysis function
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlobResult::CBlobResult(IplImage *source, IplImage *mask, int threshold, bool findmoments)
- {
- bool success;
-
- try
- {
- // cridem la funci� amb el marc a true=1=blanc (aix� no unir� els blobs externs)
- success = BlobAnalysis(source, (uchar)threshold, mask, true, findmoments, m_blobs);
- }
- catch (...)
- {
- success = false;
- }
-
- if (!success) throw EXCEPCIO_CALCUL_BLOBS;
- }
-
- /**
- - FUNCI�: CBlobResult
- - FUNCIONALITAT: Constructor de c�pia. Inicialitza la seq��ncia de blobs
- amb els blobs del par�metre.
- - PAR�METRES:
- - source: objecte que es copiar�
- - RESULTAT:
- - objecte CBlobResult amb els blobs de l'objecte source
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobResult
- - FUNCTIONALITY: Copy constructor
- - PARAMETERS:
- - source: object to copy
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlobResult::CBlobResult(const CBlobResult &source)
- {
- m_blobs = blob_vector(source.GetNumBlobs());
-
- // creem el nou a partir del passat com a par�metre
- m_blobs = blob_vector(source.GetNumBlobs());
- // copiem els blobs de l'origen a l'actual
- blob_vector::const_iterator pBlobsSrc = source.m_blobs.begin();
- blob_vector::iterator pBlobsDst = m_blobs.begin();
-
- while (pBlobsSrc != source.m_blobs.end())
- {
- // no podem cridar a l'operador = ja que blob_vector �s un
- // vector de CBlob*. Per tant, creem un blob nou a partir del
- // blob original
- *pBlobsDst = new CBlob(**pBlobsSrc);
- ++pBlobsSrc;
- ++pBlobsDst;
- }
- }
-
-
-
- /**
- - FUNCI�: ~CBlobResult
- - FUNCIONALITAT: Destructor estandard.
- - PAR�METRES:
- - RESULTAT:
- - Allibera la mem�ria reservada de cadascun dels blobs de la classe
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: ~CBlobResult
- - FUNCTIONALITY: Destructor
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlobResult::~CBlobResult()
- {
- ClearBlobs();
- }
-
- /**************************************************************************
- Operadors / Operators
- **************************************************************************/
-
-
- /**
- - FUNCI�: operador =
- - FUNCIONALITAT: Assigna un objecte source a l'actual
- - PAR�METRES:
- - source: objecte a assignar
- - RESULTAT:
- - Substitueix els blobs actuals per els de l'objecte source
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: Assigment operator
- - FUNCTIONALITY:
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlobResult& CBlobResult::operator=(const CBlobResult& source)
- {
- // si ja s�n el mateix, no cal fer res
- if (this != &source)
- {
- // alliberem el conjunt de blobs antic
- for (int i = 0; i < GetNumBlobs(); i++)
- {
- delete m_blobs[i];
- }
- m_blobs.clear();
- // creem el nou a partir del passat com a par�metre
- m_blobs = blob_vector(source.GetNumBlobs());
- // copiem els blobs de l'origen a l'actual
- blob_vector::const_iterator pBlobsSrc = source.m_blobs.begin();
- blob_vector::iterator pBlobsDst = m_blobs.begin();
-
- while (pBlobsSrc != source.m_blobs.end())
- {
- // no podem cridar a l'operador = ja que blob_vector �s un
- // vector de CBlob*. Per tant, creem un blob nou a partir del
- // blob original
- *pBlobsDst = new CBlob(**pBlobsSrc);
- ++pBlobsSrc;
- ++pBlobsDst;
- }
- }
- return *this;
- }
-
-
- /**
- - FUNCI�: operador +
- - FUNCIONALITAT: Concatena els blobs de dos CBlobResult
- - PAR�METRES:
- - source: d'on s'agafaran els blobs afegits a l'actual
- - RESULTAT:
- - retorna un nou CBlobResult amb els dos CBlobResult concatenats
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - NOTA: per la implementaci�, els blobs del par�metre es posen en ordre invers
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: + operator
- - FUNCTIONALITY: Joins the blobs in source with the current ones
- - PARAMETERS:
- - source: object to copy the blobs
- - RESULT:
- - object with the actual blobs and the source blobs
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlobResult CBlobResult::operator+(const CBlobResult& source)
- {
- //creem el resultat a partir dels blobs actuals
- CBlobResult resultat(*this);
-
- // reservem mem�ria per als nous blobs
- resultat.m_blobs.resize(resultat.GetNumBlobs() + source.GetNumBlobs());
-
- // declarem els iterador per rec�rrer els blobs d'origen i desti
- blob_vector::const_iterator pBlobsSrc = source.m_blobs.begin();
- blob_vector::iterator pBlobsDst = resultat.m_blobs.end();
-
- // insertem els blobs de l'origen a l'actual
- while (pBlobsSrc != source.m_blobs.end())
- {
- --pBlobsDst;
- *pBlobsDst = new CBlob(**pBlobsSrc);
- ++pBlobsSrc;
- }
-
- return resultat;
- }
-
- /**************************************************************************
- Operacions / Operations
- **************************************************************************/
-
- /**
- - FUNCI�: AddBlob
- - FUNCIONALITAT: Afegeix un blob al conjunt
- - PAR�METRES:
- - blob: blob a afegir
- - RESULTAT:
- - modifica el conjunt de blobs actual
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 2006/03/01
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- void CBlobResult::AddBlob(CBlob *blob)
- {
- if (blob != NULL)
- m_blobs.push_back(new CBlob(blob));
- }
-
-
- /**
- - FUNCI�: GetSTLResult
- - FUNCIONALITAT: Calcula el resultat especificat sobre tots els blobs de la classe
- - PAR�METRES:
- - evaluador: Qualsevol objecte derivat de COperadorBlob
- - RESULTAT:
- - Retorna un array de double's STL amb el resultat per cada blob
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: GetResult
- - FUNCTIONALITY: Computes the function evaluador on all the blobs of the class
- and returns a vector with the result
- - PARAMETERS:
- - evaluador: function to apply to each blob (any object derived from the
- COperadorBlob class )
- - RESULT:
- - vector with all the results in the same order as the blobs
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double_stl_vector CBlobResult::GetSTLResult(funcio_calculBlob *evaluador) const
- {
- if (GetNumBlobs() <= 0)
- {
- return double_stl_vector();
- }
-
- // definim el resultat
- double_stl_vector result = double_stl_vector(GetNumBlobs());
- // i iteradors sobre els blobs i el resultat
- double_stl_vector::iterator itResult = result.begin();
- blob_vector::const_iterator itBlobs = m_blobs.begin();
-
- // avaluem la funci� en tots els blobs
- while (itBlobs != m_blobs.end())
- {
- *itResult = (*evaluador)(**itBlobs);
- ++itBlobs;
- ++itResult;
- }
- return result;
- }
-
- /**
- - FUNCI�: GetNumber
- - FUNCIONALITAT: Calcula el resultat especificat sobre un �nic blob de la classe
- - PAR�METRES:
- - evaluador: Qualsevol objecte derivat de COperadorBlob
- - indexblob: n�mero de blob del que volem calcular el resultat.
- - RESULTAT:
- - Retorna un double amb el resultat
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: GetNumber
- - FUNCTIONALITY: Computes the function evaluador on a blob of the class
- - PARAMETERS:
- - indexBlob: index of the blob to compute the function
- - evaluador: function to apply to each blob (any object derived from the
- COperadorBlob class )
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobResult::GetNumber(int indexBlob, funcio_calculBlob *evaluador) const
- {
- if (indexBlob < 0 || indexBlob >= GetNumBlobs())
- RaiseError(EXCEPTION_BLOB_OUT_OF_BOUNDS);
- return (*evaluador)(*m_blobs[indexBlob]);
- }
-
- /////////////////////////// FILTRAT DE BLOBS ////////////////////////////////////
-
- /**
- - FUNCI�: Filter
- - FUNCIONALITAT: Filtra els blobs de la classe i deixa el resultat amb nom�s
- els blobs que han passat el filtre.
- El filtrat es basa en especificar condicions sobre un resultat dels blobs
- i seleccionar (o excloure) aquells blobs que no compleixen una determinada
- condicio
- - PAR�METRES:
- - dst: variable per deixar els blobs filtrats
- - filterAction: acci� de filtrat. Incloure els blobs trobats (B_INCLUDE),
- o excloure els blobs trobats (B_EXCLUDE)
- - evaluador: Funci� per evaluar els blobs (qualsevol objecte derivat de COperadorBlob
- - Condition: tipus de condici� que ha de superar la mesura (FilterType)
- sobre cada blob per a ser considerat.
- B_EQUAL,B_NOT_EQUAL,B_GREATER,B_LESS,B_GREATER_OR_EQUAL,
- B_LESS_OR_EQUAL,B_INSIDE,B_OUTSIDE
- - LowLimit: valor num�ric per a la comparaci� (Condition) de la mesura (FilterType)
- - HighLimit: valor num�ric per a la comparaci� (Condition) de la mesura (FilterType)
- (nom�s t� sentit per a aquelles condicions que tenen dos valors
- (B_INSIDE, per exemple).
- - RESULTAT:
- - Deixa els blobs resultants del filtrat a destination
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: Filter
- - FUNCTIONALITY: Get some blobs from the class based on conditions on measures
- of the blobs.
- - PARAMETERS:
- - dst: where to store the selected blobs
- - filterAction: B_INCLUDE: include the blobs which pass the filter in the result
- B_EXCLUDE: exclude the blobs which pass the filter in the result
- - evaluador: Object to evaluate the blob
- - Condition: How to decide if the result returned by evaluador on each blob
- is included or not. It can be:
- B_EQUAL,B_NOT_EQUAL,B_GREATER,B_LESS,B_GREATER_OR_EQUAL,
- B_LESS_OR_EQUAL,B_INSIDE,B_OUTSIDE
- - LowLimit: numerical value to evaluate the Condition on evaluador(blob)
- - HighLimit: numerical value to evaluate the Condition on evaluador(blob).
- Only useful for B_INSIDE and B_OUTSIDE
- - RESULT:
- - It returns on dst the blobs that accomplish (B_INCLUDE) or discards (B_EXCLUDE)
- the Condition on the result returned by evaluador on each blob
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlobResult::Filter(CBlobResult &dst,
- int filterAction,
- funcio_calculBlob *evaluador,
- int condition,
- double lowLimit, double highLimit /*=0*/)
-
- {
- int i, numBlobs;
- bool resultavaluacio;
- double_stl_vector avaluacioBlobs;
- double_stl_vector::iterator itavaluacioBlobs;
-
- if (GetNumBlobs() <= 0) return;
- if (!evaluador) return;
- //avaluem els blobs amb la funci� pertinent
- avaluacioBlobs = GetSTLResult(evaluador);
- itavaluacioBlobs = avaluacioBlobs.begin();
- numBlobs = GetNumBlobs();
- switch (condition)
- {
- case B_EQUAL:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = *itavaluacioBlobs == lowLimit;
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_NOT_EQUAL:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = *itavaluacioBlobs != lowLimit;
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_GREATER:
- for (i = 0; i<numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = *itavaluacioBlobs > lowLimit;
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_LESS:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = *itavaluacioBlobs < lowLimit;
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_GREATER_OR_EQUAL:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = *itavaluacioBlobs >= lowLimit;
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_LESS_OR_EQUAL:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = *itavaluacioBlobs <= lowLimit;
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_INSIDE:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = (*itavaluacioBlobs >= lowLimit) && (*itavaluacioBlobs <= highLimit);
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- case B_OUTSIDE:
- for (i = 0; i < numBlobs; i++, itavaluacioBlobs++)
- {
- resultavaluacio = (*itavaluacioBlobs < lowLimit) || (*itavaluacioBlobs > highLimit);
- if ((resultavaluacio && filterAction == B_INCLUDE) ||
- (!resultavaluacio && filterAction == B_EXCLUDE))
- {
- dst.m_blobs.push_back(new CBlob(GetBlob(i)));
- }
- }
- break;
- }
-
-
- // en cas de voler filtrar un CBlobResult i deixar-ho en el mateix CBlobResult
- // ( operacio inline )
- if (&dst == this)
- {
- // esborrem els primers blobs ( que s�n els originals )
- // ja que els tindrem replicats al final si passen el filtre
- blob_vector::iterator itBlobs = m_blobs.begin();
- for (int i = 0; i < numBlobs; i++)
- {
- delete *itBlobs;
- ++itBlobs;
- }
- m_blobs.erase(m_blobs.begin(), itBlobs);
- }
- }
-
-
- /**
- - FUNCI�: GetBlob
- - FUNCIONALITAT: Retorna un blob si aquest existeix (index != -1)
- - PAR�METRES:
- - indexblob: index del blob a retornar
- - RESULTAT:
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /*
- - FUNCTION: GetBlob
- - FUNCTIONALITY: Gets the n-th blob (without ordering the blobs)
- - PARAMETERS:
- - indexblob: index in the blob array
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlob CBlobResult::GetBlob(int indexblob) const
- {
- if (indexblob < 0 || indexblob >= GetNumBlobs())
- RaiseError(EXCEPTION_BLOB_OUT_OF_BOUNDS);
-
- return *m_blobs[indexblob];
- }
- CBlob *CBlobResult::GetBlob(int indexblob)
- {
- if (indexblob < 0 || indexblob >= GetNumBlobs())
- RaiseError(EXCEPTION_BLOB_OUT_OF_BOUNDS);
-
- return m_blobs[indexblob];
- }
-
- /**
- - FUNCI�: GetNthBlob
- - FUNCIONALITAT: Retorna l'en�ssim blob segons un determinat criteri
- - PAR�METRES:
- - criteri: criteri per ordenar els blobs (objectes derivats de COperadorBlob)
- - nBlob: index del blob a retornar
- - dst: on es retorna el resultat
- - RESULTAT:
- - retorna el blob nBlob a dst ordenant els blobs de la classe segons el criteri
- en ordre DESCENDENT. Per exemple, per obtenir el blob major:
- GetNthBlob( CBlobGetArea(), 0, blobMajor );
- GetNthBlob( CBlobGetArea(), 1, blobMajor ); (segon blob m�s gran)
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /*
- - FUNCTION: GetNthBlob
- - FUNCTIONALITY: Gets the n-th blob ordering first the blobs with some criteria
- - PARAMETERS:
- - criteri: criteria to order the blob array
- - nBlob: index of the returned blob in the ordered blob array
- - dst: where to store the result
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlobResult::GetNthBlob(funcio_calculBlob *criteri, int nBlob, CBlob &dst) const
- {
- // verifiquem que no estem accedint fora el vector de blobs
- if (nBlob < 0 || nBlob >= GetNumBlobs())
- {
- //RaiseError( EXCEPTION_BLOB_OUT_OF_BOUNDS );
- dst = CBlob();
- return;
- }
-
- double_stl_vector avaluacioBlobs, avaluacioBlobsOrdenat;
- double valorEnessim;
-
- //avaluem els blobs amb la funci� pertinent
- avaluacioBlobs = GetSTLResult(criteri);
-
- avaluacioBlobsOrdenat = double_stl_vector(GetNumBlobs());
-
- // obtenim els nBlob primers resultats (en ordre descendent)
- std::partial_sort_copy(avaluacioBlobs.begin(),
- avaluacioBlobs.end(),
- avaluacioBlobsOrdenat.begin(),
- avaluacioBlobsOrdenat.end(),
- std::greater<double>());
-
- valorEnessim = avaluacioBlobsOrdenat[nBlob];
-
- // busquem el primer blob que t� el valor n-ssim
- double_stl_vector::const_iterator itAvaluacio = avaluacioBlobs.begin();
-
- bool trobatBlob = false;
- int indexBlob = 0;
- while (itAvaluacio != avaluacioBlobs.end() && !trobatBlob)
- {
- if (*itAvaluacio == valorEnessim)
- {
- trobatBlob = true;
- dst = CBlob(GetBlob(indexBlob));
- }
- ++itAvaluacio;
- indexBlob++;
- }
- }
-
- /**
- - FUNCI�: ClearBlobs
- - FUNCIONALITAT: Elimina tots els blobs de l'objecte
- - PAR�METRES:
- - RESULTAT:
- - Allibera tota la mem�ria dels blobs
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s Navarra
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /*
- - FUNCTION: ClearBlobs
- - FUNCTIONALITY: Clears all the blobs from the object and releases all its memory
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlobResult::ClearBlobs()
- {
- /*for( int i = 0; i < GetNumBlobs(); i++ )
- {
- delete m_blobs[i];
- }*/
- blob_vector::iterator itBlobs = m_blobs.begin();
- while (itBlobs != m_blobs.end())
- {
- delete *itBlobs;
- ++itBlobs;
- }
-
- m_blobs.clear();
- }
-
- /**
- - FUNCI�: RaiseError
- - FUNCIONALITAT: Funci� per a notificar errors al l'usuari (en debug) i llen�a
- les excepcions
- - PAR�METRES:
- - errorCode: codi d'error
- - RESULTAT:
- - Ensenya un missatge a l'usuari (en debug) i llen�a una excepci�
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s Navarra
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /*
- - FUNCTION: RaiseError
- - FUNCTIONALITY: Error handling function
- - PARAMETERS:
- - errorCode: reason of the error
- - RESULT:
- - in _DEBUG version, shows a message box with the error. In release is silent.
- In both cases throws an exception with the error.
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlobResult::RaiseError(const int errorCode) const
- {
- throw errorCode;
- }
-
-
-
- /**************************************************************************
- Auxiliars / Auxiliary functions
- **************************************************************************/
-
-
- /**
- - FUNCI�: PrintBlobs
- - FUNCIONALITAT: Escriu els par�metres (�rea, per�metre, exterior, mitjana)
- de tots els blobs a un fitxer.
- - PAR�METRES:
- - nom_fitxer: path complet del fitxer amb el resultat
- - RESULTAT:
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /*
- - FUNCTION: PrintBlobs
- - FUNCTIONALITY: Prints some blob features in an ASCII file
- - PARAMETERS:
- - nom_fitxer: full path + filename to generate
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlobResult::PrintBlobs(char *nom_fitxer) const
- {
- double_stl_vector area, /*perimetre,*/ exterior, mitjana, compacitat, longitud,
- externPerimeter, perimetreConvex, perimetre;
- int i;
- FILE *fitxer_sortida;
-
- area = GetSTLResult(CBlobGetArea());
- perimetre = GetSTLResult(CBlobGetPerimeter());
- exterior = GetSTLResult(CBlobGetExterior());
- mitjana = GetSTLResult(CBlobGetMean());
- compacitat = GetSTLResult(CBlobGetCompactness());
- longitud = GetSTLResult(CBlobGetLength());
- externPerimeter = GetSTLResult(CBlobGetExternPerimeter());
- perimetreConvex = GetSTLResult(CBlobGetHullPerimeter());
-
- fitxer_sortida = fopen(nom_fitxer, "w");
-
- for (i = 0; i < GetNumBlobs(); i++)
- {
- fprintf(fitxer_sortida, "blob %d ->\t a=%7.0f\t p=%8.2f (%8.2f extern)\t pconvex=%8.2f\t ext=%.0f\t m=%7.2f\t c=%3.2f\t l=%8.2f\n",
- i, area[i], perimetre[i], externPerimeter[i], perimetreConvex[i], exterior[i], mitjana[i], compacitat[i], longitud[i]);
- }
- fclose(fitxer_sortida);
-
- }
-
-}
diff --git a/package_bgs/jmo/MultiLayerBGS.h b/package_bgs/jmo/MultiLayerBGS.h
deleted file mode 100644
index 29db946..0000000
--- a/package_bgs/jmo/MultiLayerBGS.h
+++ /dev/null
@@ -1,101 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "CMultiLayerBGS.h"
-
-class MultiLayerBGS : public IBGS
-{
-public:
- enum Status
- {
- MLBGS_NONE = -1,
- MLBGS_LEARN = 0,
- MLBGS_DETECT = 1
- };
-
-private:
- bool firstTime;
- long long frameNumber;
- cv::Mat img_foreground;
- cv::Mat img_merged;
- cv::Mat img_background;
- bool showOutput;
- bool saveModel;
- bool disableDetectMode;
- bool disableLearning;
- int detectAfter;
- CMultiLayerBGS* BGS;
- Status status;
- IplImage* img;
- IplImage* org_img;
- IplImage* fg_img;
- IplImage* bg_img;
- IplImage* fg_prob_img;
- IplImage* fg_mask_img;
- IplImage* fg_prob_img3;
- IplImage* merged_img;
- std::string bg_model_preload;
-
- bool loadDefaultParams;
-
- int max_mode_num;
- float weight_updating_constant;
- float texture_weight;
- float bg_mode_percent;
- int pattern_neig_half_size;
- float pattern_neig_gaus_sigma;
- float bg_prob_threshold;
- float bg_prob_updating_threshold;
- int robust_LBP_constant;
- float min_noised_angle;
- float shadow_rate;
- float highlight_rate;
- float bilater_filter_sigma_s;
- float bilater_filter_sigma_r;
-
- float frame_duration;
-
- float mode_learn_rate_per_second;
- float weight_learn_rate_per_second;
- float init_mode_weight;
-
- float learn_mode_learn_rate_per_second;
- float learn_weight_learn_rate_per_second;
- float learn_init_mode_weight;
-
- float detect_mode_learn_rate_per_second;
- float detect_weight_learn_rate_per_second;
- float detect_init_mode_weight;
-
-public:
- MultiLayerBGS();
- ~MultiLayerBGS();
-
- void setStatus(Status status);
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void finish(void);
- void saveConfig();
- void loadConfig();
-};
\ No newline at end of file
diff --git a/package_bgs/jmo/blob.cpp b/package_bgs/jmo/blob.cpp
deleted file mode 100644
index 3629714..0000000
--- a/package_bgs/jmo/blob.cpp
+++ /dev/null
@@ -1,1149 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-/* --- --- ---
-* Copyright (C) 2008--2010 Idiap Research Institute (.....@idiap.ch)
-* All rights reserved.
-*
-* Redistribution and use in source and binary forms, with or without
-* modification, are permitted provided that the following conditions
-* are met:
-* 1. Redistributions of source code must retain the above copyright
-* notice, this list of conditions and the following disclaimer.
-* 2. Redistributions in binary form must reproduce the above copyright
-* notice, this list of conditions and the following disclaimer in the
-* documentation and/or other materials provided with the distribution.
-* 3. The name of the author may not be used to endorse or promote products
-* derived from this software without specific prior written permission.
-*
-* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
-* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
-* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
-* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
-* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
-* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
-* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
-* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
-* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-*/
-/************************************************************************
-Blob.cpp
-
-- FUNCIONALITAT: Implementaci� de la classe CBlob
-- AUTOR: Inspecta S.L.
-MODIFICACIONS (Modificaci�, Autor, Data):
-
-
-FUNCTIONALITY: Implementation of the CBlob class and some helper classes to perform
-some calculations on it
-AUTHOR: Inspecta S.L.
-MODIFICATIONS (Modification, Author, Date):
-
-**************************************************************************/
-
-
-#include <limits.h>
-#include "blob.h"
-#include <opencv2/opencv.hpp>
-
-namespace Blob
-{
-
- /**
- - FUNCI�: CBlob
- - FUNCIONALITAT: Constructor est�ndard
- - PAR�METRES:
- - RESULTAT:
- - inicialitzaci� de totes les variables internes i de l'storage i la sequencia
- per a les cantonades del blob
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlob
- - FUNCTIONALITY: Standard constructor
- - PARAMETERS:
- - RESULT:
- - memory allocation for the blob edges and initialization of member variables
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlob::CBlob()
- {
- etiqueta = -1; // Flag indicates null region
- exterior = 0;
- area = 0.0f;
- perimeter = 0.0f;
- parent = -1;
- minx = LONG_MAX;
- maxx = 0;
- miny = LONG_MAX;
- maxy = 0;
- sumx = 0;
- sumy = 0;
- sumxx = 0;
- sumyy = 0;
- sumxy = 0;
- mean = 0;
- stddev = 0;
- externPerimeter = 0;
-
- m_storage = cvCreateMemStorage(0);
- edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
- sizeof(CvContour),
- sizeof(CvPoint), m_storage);
- }
-
- /**
- - FUNCI�: CBlob
- - FUNCIONALITAT: Constructor de c�pia
- - PAR�METRES:
- - RESULTAT:
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlob
- - FUNCTIONALITY: Copy constructor
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlob::CBlob(const CBlob &src)
- {
- // copiem les propietats del blob origen a l'actual
- etiqueta = src.etiqueta;
- exterior = src.exterior;
- area = src.Area();
- perimeter = src.Perimeter();
- parent = src.parent;
- minx = src.minx;
- maxx = src.maxx;
- miny = src.miny;
- maxy = src.maxy;
- sumx = src.sumx;
- sumy = src.sumy;
- sumxx = src.sumxx;
- sumyy = src.sumyy;
- sumxy = src.sumxy;
- mean = src.mean;
- stddev = src.stddev;
- externPerimeter = src.externPerimeter;
-
- // copiem els edges del blob origen a l'actual
- CvSeqReader reader;
- CvSeqWriter writer;
- CvPoint edgeactual;
-
- // creem una sequencia buida per als edges
- m_storage = cvCreateMemStorage(0);
- edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
- sizeof(CvContour),
- sizeof(CvPoint), m_storage);
-
- cvStartReadSeq(src.Edges(), &reader);
- cvStartAppendToSeq(edges, &writer);
-
- for (int i = 0; i < src.Edges()->total; i++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- CV_WRITE_SEQ_ELEM(edgeactual, writer);
- }
-
- cvEndWriteSeq(&writer);
- }
- CBlob::CBlob(const CBlob *src)
- {
- // copiem les propietats del blob origen a l'actual
- etiqueta = src->etiqueta;
- exterior = src->exterior;
- area = src->Area();
- perimeter = src->Perimeter();
- parent = src->parent;
- minx = src->minx;
- maxx = src->maxx;
- miny = src->miny;
- maxy = src->maxy;
- sumx = src->sumx;
- sumy = src->sumy;
- sumxx = src->sumxx;
- sumyy = src->sumyy;
- sumxy = src->sumxy;
- mean = src->mean;
- stddev = src->stddev;
- externPerimeter = src->externPerimeter;
-
- // copiem els edges del blob origen a l'actual
- CvSeqReader reader;
- CvSeqWriter writer;
- CvPoint edgeactual;
-
- // creem una sequencia buida per als edges
- m_storage = cvCreateMemStorage(0);
- edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
- sizeof(CvContour),
- sizeof(CvPoint), m_storage);
-
- cvStartReadSeq(src->Edges(), &reader);
- cvStartAppendToSeq(edges, &writer);
-
- for (int i = 0; i < src->Edges()->total; i++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- CV_WRITE_SEQ_ELEM(edgeactual, writer);
- }
-
- cvEndWriteSeq(&writer);
- }
-
- /**
- - FUNCI�: ~CBlob
- - FUNCIONALITAT: Destructor est�ndard
- - PAR�METRES:
- - RESULTAT:
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlob
- - FUNCTIONALITY: Standard destructor
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlob::~CBlob()
- {
- // Eliminar v�rtexs del blob
- cvClearSeq(edges);
- // i la zona de mem�ria on s�n
- cvReleaseMemStorage(&m_storage);
- }
-
- /**
- - FUNCI�: operator=
- - FUNCIONALITAT: Operador d'assignaci�
- - PAR�METRES:
- - src: blob a assignar a l'actual
- - RESULTAT:
- - Substitueix el blob actual per el src
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: Assigment operator
- - FUNCTIONALITY: Assigns a blob to the current
- - PARAMETERS:
- - src: blob to assign
- - RESULT:
- - the current blob is replaced by the src blob
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CBlob& CBlob::operator=(const CBlob &src)
- {
- // si ja s�n el mateix, no cal fer res
- if (this != &src)
- {
- // Eliminar v�rtexs del blob
- cvClearSeq(edges);
- // i la zona de mem�ria on s�n
- cvReleaseMemStorage(&m_storage);
-
- // creem una sequencia buida per als edges
- m_storage = cvCreateMemStorage(0);
- edges = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2,
- sizeof(CvContour),
- sizeof(CvPoint), m_storage);
-
- // copiem les propietats del blob origen a l'actual
- etiqueta = src.etiqueta;
- exterior = src.exterior;
- area = src.Area();
- perimeter = src.Perimeter();
- parent = src.parent;
- minx = src.minx;
- maxx = src.maxx;
- miny = src.miny;
- maxy = src.maxy;
- sumx = src.sumx;
- sumy = src.sumy;
- sumxx = src.sumxx;
- sumyy = src.sumyy;
- sumxy = src.sumxy;
- mean = src.mean;
- stddev = src.stddev;
- externPerimeter = src.externPerimeter;
-
- // copiem els edges del blob origen a l'actual
- CvSeqReader reader;
- CvSeqWriter writer;
- CvPoint edgeactual;
-
- cvStartReadSeq(src.Edges(), &reader);
- cvStartAppendToSeq(edges, &writer);
-
- for (int i = 0; i < src.Edges()->total; i++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- CV_WRITE_SEQ_ELEM(edgeactual, writer);
- }
-
- cvEndWriteSeq(&writer);
- }
- return *this;
- }
-
- /**
- - FUNCI�: FillBlob
- - FUNCIONALITAT: Pinta l'interior d'un blob amb el color especificat
- - PAR�METRES:
- - imatge: imatge on es vol pintar el el blob
- - color: color amb que es vol pintar el blob
- - RESULTAT:
- - retorna la imatge d'entrada amb el blob pintat
- - RESTRICCIONS:
- - AUTOR:
- - Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: FillBlob
- - FUNCTIONALITY:
- - Fills the blob with a specified colour
- - PARAMETERS:
- - imatge: where to paint
- - color: colour to paint the blob
- - RESULT:
- - modifies input image and returns the seed point used to fill the blob
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlob::FillBlob(IplImage *imatge, CvScalar color, int offsetX /*=0*/, int offsetY /*=0*/) const
- {
-
- //verifiquem que existeixi el blob i que tingui cantonades
- if (edges == NULL || edges->total == 0) return;
-
- CvPoint edgeactual, pt1, pt2;
- CvSeqReader reader;
- vectorPunts vectorEdges = vectorPunts(edges->total);
- vectorPunts::iterator itEdges, itEdgesSeguent;
- bool dinsBlob;
- int yActual;
-
- // passem els punts del blob a un vector de punts de les STL
- cvStartReadSeq(edges, &reader);
- itEdges = vectorEdges.begin();
- while (itEdges != vectorEdges.end())
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- *itEdges = edgeactual;
- ++itEdges;
- }
- // ordenem el vector per les Y's i les X's d'esquerra a dreta
- std::sort(vectorEdges.begin(), vectorEdges.end(), comparaCvPoint());
-
- // recorrem el vector ordenat i fem linies entre punts consecutius
- itEdges = vectorEdges.begin();
- itEdgesSeguent = vectorEdges.begin() + 1;
- dinsBlob = true;
- while (itEdges != (vectorEdges.end() - 1))
- {
- yActual = (*itEdges).y;
-
- if (((*itEdges).x != (*itEdgesSeguent).x) &&
- ((*itEdgesSeguent).y == yActual)
- )
- {
- if (dinsBlob)
- {
- pt1 = *itEdges;
- pt1.x += offsetX;
- pt1.y += offsetY;
-
- pt2 = *itEdgesSeguent;
- pt2.x += offsetX;
- pt2.y += offsetY;
-
- cvLine(imatge, pt1, pt2, color);
- }
- dinsBlob = !dinsBlob;
- }
- ++itEdges;
- ++itEdgesSeguent;
- if ((*itEdges).y != yActual) dinsBlob = true;
- }
- vectorEdges.clear();
- }
-
- /**
- - FUNCI�: CopyEdges
- - FUNCIONALITAT: Afegeix els v�rtexs del blob al blob destination
- - PAR�METRES:
- - destination: blob al que volem afegir els v�rtexs
- - RESULTAT:
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CopyEdges
- - FUNCTIONALITY: Adds the blob edges to destination
- - PARAMETERS:
- - destination: where to add the edges
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlob::CopyEdges(CBlob &destination) const
- {
- CvSeqReader reader;
- CvSeqWriter writer;
- CvPoint edgeactual;
-
- cvStartReadSeq(edges, &reader);
- cvStartAppendToSeq(destination.Edges(), &writer);
-
- for (int i = 0; i < edges->total; i++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- CV_WRITE_SEQ_ELEM(edgeactual, writer);
- }
-
- cvEndWriteSeq(&writer);
- }
-
- /**
- - FUNCI�: ClearEdges
- - FUNCIONALITAT: Elimina els v�rtexs del blob
- - PAR�METRES:
- - RESULTAT:
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: ClearEdges
- - FUNCTIONALITY: Delete current blob edges
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- void CBlob::ClearEdges()
- {
- // Eliminar v�rtexs del blob eliminat
- cvClearSeq(edges);
- }
-
- /**
- - FUNCI�: GetConvexHull
- - FUNCIONALITAT: Retorna el poligon convex del blob
- - PAR�METRES:
- - dst: sequencia on desarem el resultat (no ha d'estar inicialitzada)
- - RESULTAT:
- - true si tot ha anat b�
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: GetConvexHull
- - FUNCTIONALITY: Calculates the convex hull polygon of the blob
- - PARAMETERS:
- - dst: where to store the result
- - RESULT:
- - true if no error ocurred
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- bool CBlob::GetConvexHull(CvSeq **dst) const
- {
- if (edges != NULL && edges->total > 0)
- {
- *dst = cvConvexHull2(edges, 0, CV_CLOCKWISE, 0);
- return true;
- }
- return false;
- }
-
- /**
- - FUNCI�: GetEllipse
- - FUNCIONALITAT: Retorna l'ellipse que s'ajusta millor a les cantonades del blob
- - PAR�METRES:
- - RESULTAT:
- - estructura amb l'ellipse
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 25-05-2005.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: GetEllipse
- - FUNCTIONALITY: Calculates the ellipse that best fits the edges of the blob
- - PARAMETERS:
- - RESULT:
- - CvBox2D struct with the calculated ellipse
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- CvBox2D CBlob::GetEllipse() const
- {
- CvBox2D elipse;
- // necessitem 6 punts per calcular l'elipse
- if (edges != NULL && edges->total > 6)
- {
- elipse = cvFitEllipse2(edges);
- }
- else
- {
- elipse.center.x = 0.0;
- elipse.center.y = 0.0;
- elipse.size.width = 0.0;
- elipse.size.height = 0.0;
- elipse.angle = 0.0;
- }
- return elipse;
- }
-
-
-
- /***************************************************************************
- Implementaci� de les classes per al c�lcul de caracter�stiques sobre el blob
-
- Implementation of the helper classes to perform operations on blobs
- **************************************************************************/
-
- /**
- - FUNCI�: Moment
- - FUNCIONALITAT: Calcula el moment pq del blob
- - RESULTAT:
- - retorna el moment pq especificat o 0 si el moment no est� implementat
- - RESTRICCIONS:
- - Implementats els moments pq: 00, 01, 10, 20, 02
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: Moment
- - FUNCTIONALITY: Calculates the pq moment of the blob
- - PARAMETERS:
- - RESULT:
- - returns the pq moment or 0 if the moment it is not implemented
- - RESTRICTIONS:
- - Currently, only implemented the 00, 01, 10, 20, 02 pq moments
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 20-07-2004.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetMoment::operator()(const CBlob &blob) const
- {
- //Moment 00
- if ((m_p == 0) && (m_q == 0))
- return blob.Area();
-
- //Moment 10
- if ((m_p == 1) && (m_q == 0))
- return blob.SumX();
-
- //Moment 01
- if ((m_p == 0) && (m_q == 1))
- return blob.SumY();
-
- //Moment 20
- if ((m_p == 2) && (m_q == 0))
- return blob.SumXX();
-
- //Moment 02
- if ((m_p == 0) && (m_q == 2))
- return blob.SumYY();
-
- return 0;
- }
-
- /**
- - FUNCI�: HullPerimeter
- - FUNCIONALITAT: Calcula la longitud del perimetre convex del blob.
- Fa servir la funci� d'OpenCV cvConvexHull2 per a
- calcular el perimetre convex.
-
- - PAR�METRES:
- - RESULTAT:
- - retorna la longitud del per�metre convex del blob. Si el blob no t� coordenades
- associades retorna el per�metre normal del blob.
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobGetHullPerimeter
- - FUNCTIONALITY: Calculates the convex hull perimeter of the blob
- - PARAMETERS:
- - RESULT:
- - returns the convex hull perimeter of the blob or the perimeter if the
- blob edges could not be retrieved
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetHullPerimeter::operator()(const CBlob &blob) const
- {
- if (blob.Edges() != NULL && blob.Edges()->total > 0)
- {
- CvSeq *hull = cvConvexHull2(blob.Edges(), 0, CV_CLOCKWISE, 1);
- return fabs(cvArcLength(hull, CV_WHOLE_SEQ, 1));
- }
- return blob.Perimeter();
- }
-
- double CBlobGetHullArea::operator()(const CBlob &blob) const
- {
- if (blob.Edges() != NULL && blob.Edges()->total > 0)
- {
- CvSeq *hull = cvConvexHull2(blob.Edges(), 0, CV_CLOCKWISE, 1);
- return fabs(cvContourArea(hull));
- }
- return blob.Perimeter();
- }
-
- /**
- - FUNCI�: MinX_at_MinY
- - FUNCIONALITAT: Calcula el valor MinX a MinY.
- - PAR�METRES:
- - blob: blob del que volem calcular el valor
- - RESULTAT:
- - retorna la X minima en la Y minima.
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobGetMinXatMinY
- - FUNCTIONALITY: Calculates the minimum X on the minimum Y
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetMinXatMinY::operator()(const CBlob &blob) const
- {
- double MinX_at_MinY = LONG_MAX;
-
- CvSeqReader reader;
- CvPoint edgeactual;
-
- cvStartReadSeq(blob.Edges(), &reader);
-
- for (int j = 0; j < blob.Edges()->total; j++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- if ((edgeactual.y == blob.MinY()) && (edgeactual.x < MinX_at_MinY))
- {
- MinX_at_MinY = edgeactual.x;
- }
- }
-
- return MinX_at_MinY;
- }
-
- /**
- - FUNCI�: MinY_at_MaxX
- - FUNCIONALITAT: Calcula el valor MinX a MaxX.
- - PAR�METRES:
- - blob: blob del que volem calcular el valor
- - RESULTAT:
- - retorna la Y minima en la X maxima.
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobGetMinXatMinY
- - FUNCTIONALITY: Calculates the minimum Y on the maximum X
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetMinYatMaxX::operator()(const CBlob &blob) const
- {
- double MinY_at_MaxX = LONG_MAX;
-
- CvSeqReader reader;
- CvPoint edgeactual;
-
- cvStartReadSeq(blob.Edges(), &reader);
-
- for (int j = 0; j < blob.Edges()->total; j++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- if ((edgeactual.x == blob.MaxX()) && (edgeactual.y < MinY_at_MaxX))
- {
- MinY_at_MaxX = edgeactual.y;
- }
- }
-
- return MinY_at_MaxX;
- }
-
- /**
- - FUNCI�: MaxX_at_MaxY
- - FUNCIONALITAT: Calcula el valor MaxX a MaxY.
- - PAR�METRES:
- - blob: blob del que volem calcular el valor
- - RESULTAT:
- - retorna la X maxima en la Y maxima.
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobGetMaxXatMaxY
- - FUNCTIONALITY: Calculates the maximum X on the maximum Y
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetMaxXatMaxY::operator()(const CBlob &blob) const
- {
- double MaxX_at_MaxY = LONG_MIN;
-
- CvSeqReader reader;
- CvPoint edgeactual;
-
- cvStartReadSeq(blob.Edges(), &reader);
-
- for (int j = 0; j<blob.Edges()->total; j++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- if ((edgeactual.y == blob.MaxY()) && (edgeactual.x > MaxX_at_MaxY))
- {
- MaxX_at_MaxY = edgeactual.x;
- }
- }
-
- return MaxX_at_MaxY;
- }
-
- /**
- - FUNCI�: MaxY_at_MinX
- - FUNCIONALITAT: Calcula el valor MaxY a MinX.
- - PAR�METRES:
- - blob: blob del que volem calcular el valor
- - RESULTAT:
- - retorna la Y maxima en la X minima.
- - RESTRICCIONS:
- - AUTOR: Ricard Borr�s
- - DATA DE CREACI�: 20-07-2004.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: CBlobGetMaxYatMinX
- - FUNCTIONALITY: Calculates the maximum Y on the minimum X
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetMaxYatMinX::operator()(const CBlob &blob) const
- {
- double MaxY_at_MinX = LONG_MIN;
-
- CvSeqReader reader;
- CvPoint edgeactual;
-
- cvStartReadSeq(blob.Edges(), &reader);
-
- for (int j = 0; j<blob.Edges()->total; j++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- if ((edgeactual.x == blob.MinY()) && (edgeactual.y > MaxY_at_MinX))
- {
- MaxY_at_MinX = edgeactual.y;
- }
- }
-
- return MaxY_at_MinX;
- }
-
- /**
- Retorna l'elongaci� del blob (longitud/amplada)
- */
- /**
- - FUNCTION: CBlobGetElongation
- - FUNCTIONALITY: Calculates the elongation of the blob ( length/breadth )
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - See below to see how the lenght and the breadth are aproximated
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetElongation::operator()(const CBlob &blob) const
- {
- double ampladaC, longitudC, amplada, longitud;
-
- ampladaC = (double)(blob.Perimeter() + sqrt(pow(blob.Perimeter(), 2) - 16 * blob.Area())) / 4;
- if (ampladaC <= 0.0) return 0;
- longitudC = (double)blob.Area() / ampladaC;
-
- longitud = MAX(longitudC, ampladaC);
- amplada = MIN(longitudC, ampladaC);
-
- return (double)longitud / amplada;
- }
-
- /**
- Retorna la compacitat del blob
- */
- /**
- - FUNCTION: CBlobGetCompactness
- - FUNCTIONALITY: Calculates the compactness of the blob
- ( maximum for circle shaped blobs, minimum for the rest)
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetCompactness::operator()(const CBlob &blob) const
- {
- if (blob.Area() != 0.0)
- return (double)pow(blob.Perimeter(), 2) / (4 * CV_PI*blob.Area());
- else
- return 0.0;
- }
-
- /**
- Retorna la rugositat del blob
- */
- /**
- - FUNCTION: CBlobGetRoughness
- - FUNCTIONALITY: Calculates the roughness of the blob
- ( ratio between perimeter and convex hull perimeter)
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetRoughness::operator()(const CBlob &blob) const
- {
- CBlobGetHullPerimeter getHullPerimeter = CBlobGetHullPerimeter();
-
- double hullPerimeter = getHullPerimeter(blob);
-
- if (hullPerimeter != 0.0)
- return blob.Perimeter() / hullPerimeter;//HullPerimeter();
-
- return 0.0;
- }
-
- /**
- Retorna la longitud del blob
- */
- /**
- - FUNCTION: CBlobGetLength
- - FUNCTIONALITY: Calculates the lenght of the blob (the biggest axis of the blob)
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - The lenght is an aproximation to the real lenght
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetLength::operator()(const CBlob &blob) const
- {
- double ampladaC, longitudC;
- double tmp;
-
- tmp = blob.Perimeter()*blob.Perimeter() - 16 * blob.Area();
-
- if (tmp > 0.0)
- ampladaC = (double)(blob.Perimeter() + sqrt(tmp)) / 4;
- // error intr�nsec en els c�lculs de l'�rea i el per�metre
- else
- ampladaC = (double)(blob.Perimeter()) / 4;
-
- if (ampladaC <= 0.0) return 0;
- longitudC = (double)blob.Area() / ampladaC;
-
- return MAX(longitudC, ampladaC);
- }
-
- /**
- Retorna l'amplada del blob
- */
- /**
- - FUNCTION: CBlobGetBreadth
- - FUNCTIONALITY: Calculates the breadth of the blob (the smallest axis of the blob)
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - The breadth is an aproximation to the real breadth
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetBreadth::operator()(const CBlob &blob) const
- {
- double ampladaC, longitudC;
- double tmp;
-
- tmp = blob.Perimeter()*blob.Perimeter() - 16 * blob.Area();
-
- if (tmp > 0.0)
- ampladaC = (double)(blob.Perimeter() + sqrt(tmp)) / 4;
- // error intr�nsec en els c�lculs de l'�rea i el per�metre
- else
- ampladaC = (double)(blob.Perimeter()) / 4;
-
- if (ampladaC <= 0.0) return 0;
- longitudC = (double)blob.Area() / ampladaC;
-
- return MIN(longitudC, ampladaC);
- }
-
- /**
- Calcula la dist�ncia entre un punt i el centre del blob
- */
- /**
- - FUNCTION: CBlobGetDistanceFromPoint
- - FUNCTIONALITY: Calculates the euclidean distance between the blob center and
- the point specified in the constructor
- - PARAMETERS:
- - RESULT:
- - RESTRICTIONS:
- - AUTHOR: Ricard Borr�s
- - CREATION DATE: 25-05-2005.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetDistanceFromPoint::operator()(const CBlob &blob) const
- {
- double xmitjana, ymitjana;
- CBlobGetXCenter getXCenter;
- CBlobGetYCenter getYCenter;
-
- xmitjana = m_x - getXCenter(blob);
- ymitjana = m_y - getYCenter(blob);
-
- return sqrt((xmitjana*xmitjana) + (ymitjana*ymitjana));
- }
-
- /**
- - FUNCI�: BlobGetXYInside
- - FUNCIONALITAT: Calcula si un punt cau dins de la capsa rectangular
- del blob
- - RESULTAT:
- - retorna 1 si hi est�; 0 si no
- - RESTRICCIONS:
- - AUTOR: Francesc Pinyol Margalef
- - DATA DE CREACI�: 16-01-2006.
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- /**
- - FUNCTION: BlobGetXYInside
- - FUNCTIONALITY: Calculates whether a point is inside the
- rectangular bounding box of a blob
- - PARAMETERS:
- - RESULT:
- - returns 1 if it is inside; o if not
- - RESTRICTIONS:
- - AUTHOR: Francesc Pinyol Margalef
- - CREATION DATE: 16-01-2006.
- - MODIFICATION: Date. Author. Description.
- */
- double CBlobGetXYInside::operator()(const CBlob &blob) const
- {
- if (blob.Edges() == NULL || blob.Edges()->total == 0) return 0.0;
-
- // passem els punts del blob a un vector de punts de les STL
- CvSeqReader reader;
- CBlob::vectorPunts vectorEdges;
- CBlob::vectorPunts::iterator itEdges, itEdgesSeguent;
- CvPoint edgeactual;
- bool dinsBlob;
-
- // agafem tots els punts amb la mateixa y que l'actual
- cvStartReadSeq(blob.Edges(), &reader);
-
- for (int i = 0; i < blob.Edges()->total; i++)
- {
- CV_READ_SEQ_ELEM(edgeactual, reader);
- if (edgeactual.y == m_p.y)
- vectorEdges.push_back(edgeactual);
- }
-
- if (vectorEdges.empty()) return 0.0;
-
- // ordenem el vector per les Y's i les X's d'esquerra a dreta
- std::sort(vectorEdges.begin(), vectorEdges.end(), CBlob::comparaCvPoint());
-
- // recorrem el punts del blob de la mateixa fila que el punt d'entrada
- // i mirem si la X del punt d'entrada est� entre dos coordenades "plenes"
- // del blob
- itEdges = vectorEdges.begin();
- itEdgesSeguent = vectorEdges.begin() + 1;
- dinsBlob = true;
-
- while (itEdges != (vectorEdges.end() - 1))
- {
- if ((*itEdges).x <= m_p.x && (*itEdgesSeguent).x >= m_p.x && dinsBlob)
- {
- vectorEdges.clear();
- return 1.0;
- }
-
- ++itEdges;
- ++itEdgesSeguent;
- dinsBlob = !dinsBlob;
- }
-
- vectorEdges.clear();
- return 0.0;
- }
-
-#ifdef BLOB_OBJECT_FACTORY
-
- /**
- - FUNCI�: RegistraTotsOperadors
- - FUNCIONALITAT: Registrar tots els operadors definits a blob.h
- - PAR�METRES:
- - fabricaOperadorsBlob: f�brica on es registraran els operadors
- - RESULTAT:
- - Modifica l'objecte fabricaOperadorsBlob
- - RESTRICCIONS:
- - Nom�s es registraran els operadors de blob.h. Si se'n volen afegir, cal afegir-los amb
- el m�tode Register de la f�brica.
- - AUTOR: rborras
- - DATA DE CREACI�: 2006/05/18
- - MODIFICACI�: Data. Autor. Descripci�.
- */
- void RegistraTotsOperadors( t_OperadorBlobFactory &fabricaOperadorsBlob )
- {
- // blob shape
- fabricaOperadorsBlob.Register( CBlobGetArea().GetNom(), Type2Type<CBlobGetArea>());
- fabricaOperadorsBlob.Register( CBlobGetBreadth().GetNom(), Type2Type<CBlobGetBreadth>());
- fabricaOperadorsBlob.Register( CBlobGetCompactness().GetNom(), Type2Type<CBlobGetCompactness>());
- fabricaOperadorsBlob.Register( CBlobGetElongation().GetNom(), Type2Type<CBlobGetElongation>());
- fabricaOperadorsBlob.Register( CBlobGetExterior().GetNom(), Type2Type<CBlobGetExterior>());
- fabricaOperadorsBlob.Register( CBlobGetLength().GetNom(), Type2Type<CBlobGetLength>());
- fabricaOperadorsBlob.Register( CBlobGetPerimeter().GetNom(), Type2Type<CBlobGetPerimeter>());
- fabricaOperadorsBlob.Register( CBlobGetRoughness().GetNom(), Type2Type<CBlobGetRoughness>());
-
- // extern pixels
- fabricaOperadorsBlob.Register( CBlobGetExternPerimeterRatio().GetNom(), Type2Type<CBlobGetExternPerimeterRatio>());
- fabricaOperadorsBlob.Register( CBlobGetExternHullPerimeterRatio().GetNom(), Type2Type<CBlobGetExternHullPerimeterRatio>());
- fabricaOperadorsBlob.Register( CBlobGetExternPerimeter().GetNom(), Type2Type<CBlobGetExternPerimeter>());
-
-
- // hull
- fabricaOperadorsBlob.Register( CBlobGetHullPerimeter().GetNom(), Type2Type<CBlobGetHullPerimeter>());
- fabricaOperadorsBlob.Register( CBlobGetHullArea().GetNom(), Type2Type<CBlobGetHullArea>());
-
-
- // elipse info
- fabricaOperadorsBlob.Register( CBlobGetMajorAxisLength().GetNom(), Type2Type<CBlobGetMajorAxisLength>());
- fabricaOperadorsBlob.Register( CBlobGetMinorAxisLength().GetNom(), Type2Type<CBlobGetMinorAxisLength>());
- fabricaOperadorsBlob.Register( CBlobGetAxisRatio().GetNom(), Type2Type<CBlobGetAxisRatio>());
- fabricaOperadorsBlob.Register( CBlobGetOrientation().GetNom(), Type2Type<CBlobGetOrientation>());
- fabricaOperadorsBlob.Register( CBlobGetOrientationCos().GetNom(), Type2Type<CBlobGetOrientationCos>());
- fabricaOperadorsBlob.Register( CBlobGetAreaElipseRatio().GetNom(), Type2Type<CBlobGetAreaElipseRatio>());
-
- // min an max
- fabricaOperadorsBlob.Register( CBlobGetMaxX().GetNom(), Type2Type<CBlobGetMaxX>());
- fabricaOperadorsBlob.Register( CBlobGetMaxY().GetNom(), Type2Type<CBlobGetMaxY>());
- fabricaOperadorsBlob.Register( CBlobGetMinX().GetNom(), Type2Type<CBlobGetMinX>());
- fabricaOperadorsBlob.Register( CBlobGetMinY().GetNom(), Type2Type<CBlobGetMinY>());
-
- fabricaOperadorsBlob.Register( CBlobGetMaxXatMaxY().GetNom(), Type2Type<CBlobGetMaxXatMaxY>());
- fabricaOperadorsBlob.Register( CBlobGetMaxYatMinX().GetNom(), Type2Type<CBlobGetMaxYatMinX>());
- fabricaOperadorsBlob.Register( CBlobGetMinXatMinY().GetNom(), Type2Type<CBlobGetMinXatMinY>());
- fabricaOperadorsBlob.Register( CBlobGetMinYatMaxX().GetNom(), Type2Type<CBlobGetMinYatMaxX>());
-
- // grey level stats
- fabricaOperadorsBlob.Register( CBlobGetMean().GetNom(), Type2Type<CBlobGetMean>());
- fabricaOperadorsBlob.Register( CBlobGetStdDev().GetNom(), Type2Type<CBlobGetStdDev>());
-
- // coordinate info
- fabricaOperadorsBlob.Register( CBlobGetXYInside().GetNom(), Type2Type<CBlobGetXYInside>());
- fabricaOperadorsBlob.Register( CBlobGetDiffY().GetNom(), Type2Type<CBlobGetDiffY>());
- fabricaOperadorsBlob.Register( CBlobGetDiffX().GetNom(), Type2Type<CBlobGetDiffX>());
- fabricaOperadorsBlob.Register( CBlobGetXCenter().GetNom(), Type2Type<CBlobGetXCenter>());
- fabricaOperadorsBlob.Register( CBlobGetYCenter().GetNom(), Type2Type<CBlobGetYCenter>());
- fabricaOperadorsBlob.Register( CBlobGetDistanceFromPoint().GetNom(), Type2Type<CBlobGetDistanceFromPoint>());
-
- // moments
- fabricaOperadorsBlob.Register( CBlobGetMoment().GetNom(), Type2Type<CBlobGetMoment>());
-
- }
-
-#endif
-
-}
-
diff --git a/package_bgs/lb/BGModel.cpp b/package_bgs/lb/BGModel.cpp
index c42bec7..3c73b53 100644
--- a/package_bgs/lb/BGModel.cpp
+++ b/package_bgs/lb/BGModel.cpp
@@ -14,9 +14,9 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModel.cpp
-
+
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
This program is free software; you can redistribute it and/or modify
@@ -38,11 +38,11 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
namespace lb_library
{
- BGModel::BGModel(int width, int height): m_width(width), m_height(height)
+ BGModel::BGModel(int width, int height) : m_width(width), m_height(height)
{
- m_SrcImage = cvCreateImage(cvSize(m_width,m_height), IPL_DEPTH_8U, 3);
- m_BGImage = cvCreateImage(cvSize(m_width,m_height), IPL_DEPTH_8U, 3);
- m_FGImage = cvCreateImage(cvSize(m_width,m_height), IPL_DEPTH_8U, 3);
+ m_SrcImage = cvCreateImage(cvSize(m_width, m_height), IPL_DEPTH_8U, 3);
+ m_BGImage = cvCreateImage(cvSize(m_width, m_height), IPL_DEPTH_8U, 3);
+ m_FGImage = cvCreateImage(cvSize(m_width, m_height), IPL_DEPTH_8U, 3);
cvZero(m_SrcImage);
cvZero(m_BGImage);
@@ -51,9 +51,9 @@ namespace lb_library
BGModel::~BGModel()
{
- if (m_SrcImage!=NULL) cvReleaseImage(&m_SrcImage);
- if (m_BGImage!=NULL) cvReleaseImage(&m_BGImage);
- if (m_FGImage!=NULL) cvReleaseImage(&m_FGImage);
+ if (m_SrcImage != NULL) cvReleaseImage(&m_SrcImage);
+ if (m_BGImage != NULL) cvReleaseImage(&m_BGImage);
+ if (m_FGImage != NULL) cvReleaseImage(&m_FGImage);
}
IplImage* BGModel::GetSrc()
@@ -73,15 +73,15 @@ namespace lb_library
void BGModel::InitModel(IplImage* image)
{
- cvCopy(image,m_SrcImage);
+ cvCopy(image, m_SrcImage);
Init();
return;
}
void BGModel::UpdateModel(IplImage* image)
{
- cvCopy(image,m_SrcImage);
+ cvCopy(image, m_SrcImage);
Update();
return;
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/BGModel.h b/package_bgs/lb/BGModel.h
index 77f0490..d47ad62 100644
--- a/package_bgs/lb/BGModel.h
+++ b/package_bgs/lb/BGModel.h
@@ -14,9 +14,9 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModel.h
-
+
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
This program is free software; you can redistribute it and/or modify
@@ -33,9 +33,7 @@ along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef BGMODEL_H
-#define BGMODEL_H
+#pragma once
#include <opencv2/opencv.hpp>
#include <math.h>
@@ -54,7 +52,7 @@ namespace lb_library
void InitModel(IplImage* image);
void UpdateModel(IplImage* image);
-
+
virtual void setBGModelParameter(int id, int value) {};
virtual IplImage* GetSrc();
@@ -62,17 +60,15 @@ namespace lb_library
virtual IplImage* GetBG();
protected:
-
+
IplImage* m_SrcImage;
IplImage* m_BGImage;
IplImage* m_FGImage;
const int m_width;
const int m_height;
-
+
virtual void Init() = 0;
virtual void Update() = 0;
};
}
-
-#endif
diff --git a/package_bgs/lb/BGModelFuzzyGauss.cpp b/package_bgs/lb/BGModelFuzzyGauss.cpp
index 8706b13..b249052 100644
--- a/package_bgs/lb/BGModelFuzzyGauss.cpp
+++ b/package_bgs/lb/BGModelFuzzyGauss.cpp
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelFuzzyGauss.cpp
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -40,7 +40,7 @@ namespace lb_library
{
namespace FuzzyGaussian
{
- BGModelFuzzyGauss::BGModelFuzzyGauss(int width, int height) : BGModel(width,height)
+ BGModelFuzzyGauss::BGModelFuzzyGauss(int width, int height) : BGModel(width, height)
{
m_alphamax = ALPHAFUZZYGAUSS;
m_threshold = THRESHOLDFUZZYGAUSS * THRESHOLDFUZZYGAUSS;
@@ -53,7 +53,7 @@ namespace lb_library
DBLRGB *pMu = m_pMu;
DBLRGB *pVar = m_pVar;
- for(int k = 0; k < (m_width * m_height); k++)
+ for (int k = 0; k < (m_width * m_height); k++)
{
pMu->Red = 0.0;
pMu->Green = 0.0;
@@ -70,15 +70,15 @@ namespace lb_library
BGModelFuzzyGauss::~BGModelFuzzyGauss()
{
- delete [] m_pMu;
- delete [] m_pVar;
+ delete[] m_pMu;
+ delete[] m_pVar;
}
void BGModelFuzzyGauss::setBGModelParameter(int id, int value)
{
- double dvalue = (double)value/255.0;
+ double dvalue = (double)value / 255.0;
- switch(id)
+ switch (id)
{
case 0:
m_threshold = 100.0*dvalue*dvalue;
@@ -107,9 +107,9 @@ namespace lb_library
Image<BYTERGB> prgbSrc(m_SrcImage);
- for(int i = 0; i < m_height; i++)
+ for (int i = 0; i < m_height; i++)
{
- for(int j = 0; j < m_width; j++)
+ for (int j = 0; j < m_width; j++)
{
pMu->Red = prgbSrc[i][j].Red;
pMu->Green = prgbSrc[i][j].Green;
@@ -136,13 +136,13 @@ namespace lb_library
Image<BYTERGB> prgbBG(m_BGImage);
Image<BYTERGB> prgbFG(m_FGImage);
- for(int i = 0; i < m_height; i++)
+ for (int i = 0; i < m_height; i++)
{
- for(int j = 0; j < m_width; j++)
+ for (int j = 0; j < m_width; j++)
{
- double srcR = (double) prgbSrc[i][j].Red;
- double srcG = (double) prgbSrc[i][j].Green;
- double srcB = (double) prgbSrc[i][j].Blue;
+ double srcR = (double)prgbSrc[i][j].Red;
+ double srcG = (double)prgbSrc[i][j].Green;
+ double srcB = (double)prgbSrc[i][j].Blue;
// Fuzzy background subtraction (Mahalanobis distance)
@@ -150,53 +150,53 @@ namespace lb_library
double dg = srcG - pMu->Green;
double db = srcB - pMu->Blue;
- double d2 = dr*dr/pVar->Red + dg*dg/pVar->Green + db*db/pVar->Blue;
+ double d2 = dr*dr / pVar->Red + dg*dg / pVar->Green + db*db / pVar->Blue;
double fuzzyBG = 1.0;
- if(d2 < m_threshold)
- fuzzyBG = d2/m_threshold;
+ if (d2 < m_threshold)
+ fuzzyBG = d2 / m_threshold;
// Fuzzy running average
double alpha = m_alphamax*exp(FUZZYEXP*fuzzyBG);
- if(dr*dr > DBL_MIN)
+ if (dr*dr > DBL_MIN)
pMu->Red += alpha*dr;
- if(dg*dg > DBL_MIN)
+ if (dg*dg > DBL_MIN)
pMu->Green += alpha*dg;
- if(db*db > DBL_MIN)
+ if (db*db > DBL_MIN)
pMu->Blue += alpha*db;
double d;
d = (srcR - pMu->Red)*(srcR - pMu->Red) - pVar->Red;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pVar->Red += alpha*d;
d = (srcG - pMu->Green)*(srcG - pMu->Green) - pVar->Green;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pVar->Green += alpha*d;
d = (srcB - pMu->Blue)*(srcB - pMu->Blue) - pVar->Blue;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pVar->Blue += alpha*d;
- pVar->Red = (std::max)(pVar->Red,m_noise);
- pVar->Green = (std::max)(pVar->Green,m_noise);
- pVar->Blue = (std::max)(pVar->Blue,m_noise);
+ pVar->Red = (std::max)(pVar->Red, m_noise);
+ pVar->Green = (std::max)(pVar->Green, m_noise);
+ pVar->Blue = (std::max)(pVar->Blue, m_noise);
// Set foreground and background
- if(fuzzyBG >= m_threshBG)
+ if (fuzzyBG >= m_threshBG)
prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 255;
else
prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 0;
- prgbBG[i][j].Red = (unsigned char)pMu->Red;
- prgbBG[i][j].Green = (unsigned char)pMu->Green;
+ prgbBG[i][j].Red = (unsigned char)pMu->Red;
+ prgbBG[i][j].Green = (unsigned char)pMu->Green;
prgbBG[i][j].Blue = (unsigned char)pMu->Blue;
pMu++;
@@ -207,4 +207,4 @@ namespace lb_library
return;
}
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/BGModelFuzzyGauss.h b/package_bgs/lb/BGModelFuzzyGauss.h
index 98a92e5..a73b716 100644
--- a/package_bgs/lb/BGModelFuzzyGauss.h
+++ b/package_bgs/lb/BGModelFuzzyGauss.h
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelFuzzyGauss.h
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -33,9 +33,7 @@ You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef BGMODELFUZZYGAUSS_H
-#define BGMODELFUZZYGAUSS_H
+#pragma once
#include "BGModel.h"
@@ -71,5 +69,3 @@ namespace lb_library
};
}
}
-
-#endif
diff --git a/package_bgs/lb/BGModelFuzzySom.cpp b/package_bgs/lb/BGModelFuzzySom.cpp
index 189cb1a..e7e59dd 100644
--- a/package_bgs/lb/BGModelFuzzySom.cpp
+++ b/package_bgs/lb/BGModelFuzzySom.cpp
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelFuzzySom.cpp
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -40,27 +40,27 @@ namespace lb_library
{
namespace FuzzyAdaptiveSOM
{
- BGModelFuzzySom::BGModelFuzzySom(int width, int height) : BGModel(width,height)
+ BGModelFuzzySom::BGModelFuzzySom(int width, int height) : BGModel(width, height)
{
- m_offset = (KERNEL - 1)/2;
+ m_offset = (KERNEL - 1) / 2;
- if(SPAN_NEIGHBORS)
- m_pad = 0;
+ if (SPAN_NEIGHBORS)
+ m_pad = 0;
else
m_pad = m_offset;
// SOM models
- m_widthSOM = m_width*M + 2*m_offset + (m_width-1)*m_pad;
- m_heightSOM = m_height*N + 2*m_offset + (m_height-1)*m_pad;
+ m_widthSOM = m_width*M + 2 * m_offset + (m_width - 1)*m_pad;
+ m_heightSOM = m_height*N + 2 * m_offset + (m_height - 1)*m_pad;
- m_ppSOM = new DBLRGB*[m_heightSOM];
- for(int n = 0; n < m_heightSOM; n++)
+ m_ppSOM = new DBLRGB*[m_heightSOM];
+ for (int n = 0; n < m_heightSOM; n++)
m_ppSOM[n] = new DBLRGB[m_widthSOM];
- for(int j = 0; j < m_heightSOM; j++)
+ for (int j = 0; j < m_heightSOM; j++)
{
- for(int i = 0; i < m_widthSOM; i++)
+ for (int i = 0; i < m_widthSOM; i++)
{
m_ppSOM[j][i].Red = 0.0;
m_ppSOM[j][i].Green = 0.0;
@@ -71,7 +71,7 @@ namespace lb_library
// Create weights
m_ppW = new double*[KERNEL];
- for(int n = 0; n < KERNEL; n++)
+ for (int n = 0; n < KERNEL; n++)
m_ppW[n] = new double[KERNEL];
// Construct Gaussian kernel using Pascal's triangle
@@ -81,15 +81,15 @@ namespace lb_library
m_Wmax = DBL_MIN;
cN = 1;
- for(int j = 0; j < KERNEL; j++)
+ for (int j = 0; j < KERNEL; j++)
{
- cM = 1;
+ cM = 1;
- for(int i = 0; i < KERNEL; i++)
+ for (int i = 0; i < KERNEL; i++)
{
m_ppW[j][i] = cN*cM;
- if(m_ppW[j][i] > m_Wmax)
+ if (m_ppW[j][i] > m_Wmax)
m_Wmax = m_ppW[j][i];
cM = cM * (KERNEL - 1 - i) / (i + 1);
@@ -103,8 +103,8 @@ namespace lb_library
m_epsilon1 = EPS1*EPS1;
m_epsilon2 = EPS2*EPS2;
- m_alpha1 = C1/m_Wmax;
- m_alpha2 = C2/m_Wmax;
+ m_alpha1 = C1 / m_Wmax;
+ m_alpha2 = C2 / m_Wmax;
m_K = 0;
m_TSteps = TRAINING_STEPS;
@@ -112,22 +112,22 @@ namespace lb_library
BGModelFuzzySom::~BGModelFuzzySom()
{
- for(int n = 0; n < m_heightSOM; n++)
- delete [] m_ppSOM[n];
+ for (int n = 0; n < m_heightSOM; n++)
+ delete[] m_ppSOM[n];
- delete [] m_ppSOM;
+ delete[] m_ppSOM;
- for(int n = 0; n < KERNEL; n++)
- delete [] m_ppW[n];
+ for (int n = 0; n < KERNEL; n++)
+ delete[] m_ppW[n];
- delete [] m_ppW;
+ delete[] m_ppW;
}
void BGModelFuzzySom::setBGModelParameter(int id, int value)
{
- double dvalue = (double)value/255.0;
+ double dvalue = (double)value / 255.0;
- switch(id)
+ switch (id)
{
case 0:
m_epsilon2 = 255.0*255.0*dvalue*dvalue*dvalue*dvalue;
@@ -138,11 +138,11 @@ namespace lb_library
break;
case 2:
- m_alpha2 = dvalue*dvalue*dvalue/m_Wmax;
+ m_alpha2 = dvalue*dvalue*dvalue / m_Wmax;
break;
case 3:
- m_alpha1 = dvalue*dvalue*dvalue/m_Wmax;
+ m_alpha1 = dvalue*dvalue*dvalue / m_Wmax;
break;
case 5:
@@ -157,21 +157,21 @@ namespace lb_library
{
Image<BYTERGB> prgbSrc(m_SrcImage);
- for(int j = 0; j < m_height; j++)
+ for (int j = 0; j < m_height; j++)
{
int jj = m_offset + j*(N + m_pad);
- for(int i = 0; i < m_width; i++)
+ for (int i = 0; i < m_width; i++)
{
- int ii = m_offset + i*(M + m_pad);
+ int ii = m_offset + i*(M + m_pad);
- for(int l = 0; l < N; l++)
+ for (int l = 0; l < N; l++)
{
- for(int k = 0; k < M; k++)
+ for (int k = 0; k < M; k++)
{
- m_ppSOM[jj+l][ii+k].Red = (double)prgbSrc[j][i].Red;
- m_ppSOM[jj+l][ii+k].Green = (double)prgbSrc[j][i].Green;
- m_ppSOM[jj+l][ii+k].Blue = (double)prgbSrc[j][i].Blue;
+ m_ppSOM[jj + l][ii + k].Red = (double)prgbSrc[j][i].Red;
+ m_ppSOM[jj + l][ii + k].Green = (double)prgbSrc[j][i].Green;
+ m_ppSOM[jj + l][ii + k].Blue = (double)prgbSrc[j][i].Blue;
}
}
}
@@ -184,11 +184,11 @@ namespace lb_library
void BGModelFuzzySom::Update()
{
- double alpha,a;
+ double alpha, a;
double epsilon;
// calibration phase
- if(m_K <= m_TSteps)
+ if (m_K <= m_TSteps)
{
epsilon = m_epsilon1;
alpha = (m_alpha1 - m_K * (m_alpha1 - m_alpha2) / m_TSteps);
@@ -204,11 +204,11 @@ namespace lb_library
Image<BYTERGB> prgbBG(m_BGImage);
Image<BYTERGB> prgbFG(m_FGImage);
- for(int j = 0; j < m_height; j++)
+ for (int j = 0; j < m_height; j++)
{
int jj = m_offset + j*(N + m_pad);
- for(int i = 0; i < m_width; i++)
+ for (int i = 0; i < m_width; i++)
{
int ii = m_offset + i*(M + m_pad);
@@ -222,17 +222,17 @@ namespace lb_library
int iiHit = ii;
int jjHit = jj;
- for(int l = 0; l < N; l++)
+ for (int l = 0; l < N; l++)
{
- for(int k = 0; k < M; k++)
+ for (int k = 0; k < M; k++)
{
- double dr = srcR - m_ppSOM[jj+l][ii+k].Red;
- double dg = srcG - m_ppSOM[jj+l][ii+k].Green;
- double db = srcB - m_ppSOM[jj+l][ii+k].Blue;
+ double dr = srcR - m_ppSOM[jj + l][ii + k].Red;
+ double dg = srcG - m_ppSOM[jj + l][ii + k].Green;
+ double db = srcB - m_ppSOM[jj + l][ii + k].Blue;
double d2 = dr*dr + dg*dg + db*db;
- if(d2 < d2min)
+ if (d2 < d2min)
{
d2min = d2;
iiHit = ii + k;
@@ -243,16 +243,16 @@ namespace lb_library
double fuzzyBG = 1.0;
- if(d2min < epsilon)
- fuzzyBG = d2min/epsilon;
+ if (d2min < epsilon)
+ fuzzyBG = d2min / epsilon;
// Update SOM
double alphamax = alpha*exp(FUZZYEXP*fuzzyBG);
- for(int l = (jjHit - m_offset); l <= (jjHit + m_offset); l++)
+ for (int l = (jjHit - m_offset); l <= (jjHit + m_offset); l++)
{
- for(int k = (iiHit - m_offset); k <= (iiHit + m_offset); k++)
+ for (int k = (iiHit - m_offset); k <= (iiHit + m_offset); k++)
{
a = alphamax * m_ppW[l - jjHit + m_offset][k - iiHit + m_offset];
@@ -261,20 +261,20 @@ namespace lb_library
double d;
d = srcR - m_ppSOM[l][k].Red;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
m_ppSOM[l][k].Red += a*d;
d = srcG - m_ppSOM[l][k].Green;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
m_ppSOM[l][k].Green += a*d;
d = srcB - m_ppSOM[l][k].Blue;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
m_ppSOM[l][k].Blue += a*d;
}
}
- if(fuzzyBG >= FUZZYTHRESH)
+ if (fuzzyBG >= FUZZYTHRESH)
{
// Set foreground image
prgbFG[j][i].Red = prgbFG[j][i].Green = prgbFG[j][i].Blue = 255;
@@ -284,7 +284,7 @@ namespace lb_library
// Set background image
prgbBG[j][i].Red = m_ppSOM[jjHit][iiHit].Red;
prgbBG[j][i].Green = m_ppSOM[jjHit][iiHit].Green;
- prgbBG[j][i].Blue = m_ppSOM[jjHit][iiHit].Blue;
+ prgbBG[j][i].Blue = m_ppSOM[jjHit][iiHit].Blue;
// Set foreground image
prgbFG[j][i].Red = prgbFG[j][i].Green = prgbFG[j][i].Blue = 0;
@@ -295,4 +295,4 @@ namespace lb_library
return;
}
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/BGModelFuzzySom.h b/package_bgs/lb/BGModelFuzzySom.h
index 2f21d3e..ed0bf21 100644
--- a/package_bgs/lb/BGModelFuzzySom.h
+++ b/package_bgs/lb/BGModelFuzzySom.h
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelFuzzySom.h
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -33,9 +33,7 @@ You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef BGMODELFUZZYSOM_H
-#define BGMODELFUZZYSOM_H
+#pragma once
#include "BGModel.h"
@@ -47,9 +45,9 @@ namespace lb_library
const int M = 3; // width SOM (per pixel)
const int N = 3; // height SOM (per pixel)
- const int KERNEL = 3; // size Gaussian kernel
+ const int KERNEL = 3; // size Gaussian kernel
- const bool SPAN_NEIGHBORS = false; // true if update neighborhood spans different pixels //
+ const bool SPAN_NEIGHBORS = false; // true if update neighborhood spans different pixels //
const int TRAINING_STEPS = 100; // number of training steps
const double EPS1 = 100.0; // model match distance during training
@@ -84,12 +82,10 @@ namespace lb_library
double m_alpha2;
DBLRGB** m_ppSOM; // SOM grid
- double** m_ppW; // Weights
+ double** m_ppW; // Weights
void Init();
void Update();
};
}
}
-
-#endif
diff --git a/package_bgs/lb/BGModelGauss.cpp b/package_bgs/lb/BGModelGauss.cpp
index 6892d13..28a8b93 100644
--- a/package_bgs/lb/BGModelGauss.cpp
+++ b/package_bgs/lb/BGModelGauss.cpp
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelGauss.cpp
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -40,7 +40,7 @@ namespace lb_library
{
namespace SimpleGaussian
{
- BGModelGauss::BGModelGauss(int width, int height) : BGModel(width,height)
+ BGModelGauss::BGModelGauss(int width, int height) : BGModel(width, height)
{
m_alpha = ALPHAGAUSS;
m_threshold = THRESHGAUSS*THRESHGAUSS;
@@ -52,7 +52,7 @@ namespace lb_library
DBLRGB *pMu = m_pMu;
DBLRGB *pVar = m_pVar;
- for(int k = 0; k < (m_width * m_height); k++)
+ for (int k = 0; k < (m_width * m_height); k++)
{
pMu->Red = 0.0;
pMu->Green = 0.0;
@@ -69,15 +69,15 @@ namespace lb_library
BGModelGauss::~BGModelGauss()
{
- delete [] m_pMu;
- delete [] m_pVar;
+ delete[] m_pMu;
+ delete[] m_pVar;
}
void BGModelGauss::setBGModelParameter(int id, int value)
{
- double dvalue = (double)value/255.0;
+ double dvalue = (double)value / 255.0;
- switch(id)
+ switch (id)
{
case 0:
m_threshold = 100.0*dvalue*dvalue;
@@ -87,7 +87,7 @@ namespace lb_library
m_noise = 100.0*dvalue;
break;
- case 2:
+ case 2:
m_alpha = dvalue*dvalue*dvalue;
break;
}
@@ -102,9 +102,9 @@ namespace lb_library
Image<BYTERGB> prgbSrc(m_SrcImage);
- for(int i = 0; i < m_height; i++)
+ for (int i = 0; i < m_height; i++)
{
- for(int j = 0; j < m_width; j++)
+ for (int j = 0; j < m_width; j++)
{
pMu->Red = prgbSrc[i][j].Red;
pMu->Green = prgbSrc[i][j].Green;
@@ -131,62 +131,62 @@ namespace lb_library
Image<BYTERGB> prgbBG(m_BGImage);
Image<BYTERGB> prgbFG(m_FGImage);
- for(int i = 0; i < m_height; i++)
+ for (int i = 0; i < m_height; i++)
{
- for(int j = 0; j < m_width; j++)
+ for (int j = 0; j < m_width; j++)
{
- double srcR = (double) prgbSrc[i][j].Red;
- double srcG = (double) prgbSrc[i][j].Green;
- double srcB = (double) prgbSrc[i][j].Blue;
+ double srcR = (double)prgbSrc[i][j].Red;
+ double srcG = (double)prgbSrc[i][j].Green;
+ double srcB = (double)prgbSrc[i][j].Blue;
- // Mahalanobis distance
+ // Mahalanobis distance
double dr = srcR - pMu->Red;
double dg = srcG - pMu->Green;
double db = srcB - pMu->Blue;
- double d2 = dr*dr/pVar->Red + dg*dg/pVar->Green + db*db/pVar->Blue;
+ double d2 = dr*dr / pVar->Red + dg*dg / pVar->Green + db*db / pVar->Blue;
// Classify
- if(d2 < m_threshold)
- prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 0;
+ if (d2 < m_threshold)
+ prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 0;
else
- prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 255;
+ prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 255;
// Update parameters
- if(dr*dr > DBL_MIN)
+ if (dr*dr > DBL_MIN)
pMu->Red += m_alpha*dr;
- if(dg*dg > DBL_MIN)
+ if (dg*dg > DBL_MIN)
pMu->Green += m_alpha*dg;
- if(db*db > DBL_MIN)
+ if (db*db > DBL_MIN)
pMu->Blue += m_alpha*db;
double d;
d = (srcR - pMu->Red)*(srcR - pMu->Red) - pVar->Red;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pVar->Red += m_alpha*d;
d = (srcG - pMu->Green)*(srcG - pMu->Green) - pVar->Green;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pVar->Green += m_alpha*d;
d = (srcB - pMu->Blue)*(srcB - pMu->Blue) - pVar->Blue;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pVar->Blue += m_alpha*d;
- pVar->Red = (std::min)(pVar->Red,m_noise);
- pVar->Green = (std::min)(pVar->Green,m_noise);
- pVar->Blue = (std::min)(pVar->Blue,m_noise);
+ pVar->Red = (std::min)(pVar->Red, m_noise);
+ pVar->Green = (std::min)(pVar->Green, m_noise);
+ pVar->Blue = (std::min)(pVar->Blue, m_noise);
// Set background
- prgbBG[i][j].Red = (unsigned char)pMu->Red;
- prgbBG[i][j].Green = (unsigned char)pMu->Green;
+ prgbBG[i][j].Red = (unsigned char)pMu->Red;
+ prgbBG[i][j].Green = (unsigned char)pMu->Green;
prgbBG[i][j].Blue = (unsigned char)pMu->Blue;
pMu++;
@@ -197,4 +197,4 @@ namespace lb_library
return;
}
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/BGModelGauss.h b/package_bgs/lb/BGModelGauss.h
index d36a716..0af6efe 100644
--- a/package_bgs/lb/BGModelGauss.h
+++ b/package_bgs/lb/BGModelGauss.h
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelGauss.h
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -33,9 +33,7 @@ You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef BGMODELGAUSS_H
-#define BGMODELGAUSS_H
+#pragma once
#include "BGModel.h"
@@ -69,5 +67,3 @@ namespace lb_library
};
}
}
-
-#endif
diff --git a/package_bgs/lb/BGModelMog.cpp b/package_bgs/lb/BGModelMog.cpp
index df6986c..036feab 100644
--- a/package_bgs/lb/BGModelMog.cpp
+++ b/package_bgs/lb/BGModelMog.cpp
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelMog.cpp
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -54,9 +54,9 @@ namespace lb_library
MOGDATA *pMOG = m_pMOG;
int *pK = m_pK;
- for(int i = 0; i < (m_width * m_height); i++)
+ for (int i = 0; i < (m_width * m_height); i++)
{
- for(int k = 0; k < NUMBERGAUSSIANS; k++)
+ for (int k = 0; k < NUMBERGAUSSIANS; k++)
{
pMOG->mu.Red = 0.0;
pMOG->mu.Green = 0.0;
@@ -72,27 +72,27 @@ namespace lb_library
pMOG++;
}
- pK[i] = 0;
+ pK[i] = 0;
}
}
BGModelMog::~BGModelMog()
{
- delete [] m_pMOG;
- delete [] m_pK;
+ delete[] m_pMOG;
+ delete[] m_pK;
}
void BGModelMog::setBGModelParameter(int id, int value)
{
- double dvalue = (double)value/255.0;
+ double dvalue = (double)value / 255.0;
- switch(id)
+ switch (id)
{
case 0:
m_threshold = 100.0*dvalue*dvalue;
break;
- case 1:
+ case 1:
m_T = dvalue;
break;
@@ -100,7 +100,7 @@ namespace lb_library
m_alpha = dvalue*dvalue*dvalue;
break;
- case 3:
+ case 3:
m_noise = 100.0*dvalue;;
break;
}
@@ -116,9 +116,9 @@ namespace lb_library
Image<BYTERGB> prgbSrc(m_SrcImage);
int n = 0;
- for(int i = 0; i < m_height; i++)
+ for (int i = 0; i < m_height; i++)
{
- for(int j = 0; j < m_width; j++)
+ for (int j = 0; j < m_width; j++)
{
pMOG[0].mu.Red = prgbSrc[i][j].Red;
pMOG[0].mu.Green = prgbSrc[i][j].Green;
@@ -129,7 +129,7 @@ namespace lb_library
pMOG[0].var.Blue = m_noise;
pMOG[0].w = 1.0;
- pMOG[0].sortKey = pMOG[0].w/sqrt(pMOG[0].var.Red+pMOG[0].var.Green+pMOG[0].var.Blue);
+ pMOG[0].sortKey = pMOG[0].w / sqrt(pMOG[0].var.Red + pMOG[0].var.Green + pMOG[0].var.Blue);
pK[n] = 1;
n++;
@@ -153,27 +153,27 @@ namespace lb_library
Image<BYTERGB> prgbFG(m_FGImage);
int n = 0;
- for(int i = 0; i < m_height; i++)
+ for (int i = 0; i < m_height; i++)
{
- for(int j = 0; j < m_width; j++)
+ for (int j = 0; j < m_width; j++)
{
- double srcR = (double) prgbSrc[i][j].Red;
- double srcG = (double) prgbSrc[i][j].Green;
- double srcB = (double) prgbSrc[i][j].Blue;
+ double srcR = (double)prgbSrc[i][j].Red;
+ double srcG = (double)prgbSrc[i][j].Green;
+ double srcB = (double)prgbSrc[i][j].Blue;
// Find matching distribution
int kHit = -1;
- for(int k = 0; k < pK[n]; k++)
+ for (int k = 0; k < pK[n]; k++)
{
// Mahalanobis distance
double dr = srcR - pMOG[k].mu.Red;
double dg = srcG - pMOG[k].mu.Green;
double db = srcB - pMOG[k].mu.Blue;
- double d2 = dr*dr/pMOG[k].var.Red + dg*dg/pMOG[k].var.Green + db*db/pMOG[k].var.Blue;
+ double d2 = dr*dr / pMOG[k].var.Red + dg*dg / pMOG[k].var.Green + db*db / pMOG[k].var.Blue;
- if(d2 < m_threshold)
+ if (d2 < m_threshold)
{
kHit = k;
break;
@@ -183,43 +183,43 @@ namespace lb_library
// Adjust parameters
// matching distribution found
- if(kHit != -1)
+ if (kHit != -1)
{
- for(int k = 0; k < pK[n]; k++)
+ for (int k = 0; k < pK[n]; k++)
{
- if(k == kHit)
+ if (k == kHit)
{
pMOG[k].w = pMOG[k].w + m_alpha*(1.0f - pMOG[k].w);
double d;
d = srcR - pMOG[k].mu.Red;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pMOG[k].mu.Red += m_alpha*d;
d = srcG - pMOG[k].mu.Green;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pMOG[k].mu.Green += m_alpha*d;
d = srcB - pMOG[k].mu.Blue;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pMOG[k].mu.Blue += m_alpha*d;
d = (srcR - pMOG[k].mu.Red)*(srcR - pMOG[k].mu.Red) - pMOG[k].var.Red;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pMOG[k].var.Red += m_alpha*d;
d = (srcG - pMOG[k].mu.Green)*(srcG - pMOG[k].mu.Green) - pMOG[k].var.Green;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pMOG[k].var.Green += m_alpha*d;
d = (srcB - pMOG[k].mu.Blue)*(srcB - pMOG[k].mu.Blue) - pMOG[k].var.Blue;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
pMOG[k].var.Blue += m_alpha*d;
- pMOG[k].var.Red = (std::max)(pMOG[k].var.Red,m_noise);
- pMOG[k].var.Green = (std::max)(pMOG[k].var.Green,m_noise);
- pMOG[k].var.Blue = (std::max)(pMOG[k].var.Blue,m_noise);
+ pMOG[k].var.Red = (std::max)(pMOG[k].var.Red, m_noise);
+ pMOG[k].var.Green = (std::max)(pMOG[k].var.Green, m_noise);
+ pMOG[k].var.Blue = (std::max)(pMOG[k].var.Blue, m_noise);
}
else
pMOG[k].w = (1.0 - m_alpha)*pMOG[k].w;
@@ -228,12 +228,12 @@ namespace lb_library
// no match found... create new one
else
{
- if(pK[n] < NUMBERGAUSSIANS)
+ if (pK[n] < NUMBERGAUSSIANS)
pK[n]++;
kHit = pK[n] - 1;
- if(pK[n] == 1)
+ if (pK[n] == 1)
pMOG[kHit].w = 1.0;
else
pMOG[kHit].w = LEARNINGRATEMOG;
@@ -251,24 +251,24 @@ namespace lb_library
double wsum = 0.0;
- for(int k = 0; k < pK[n]; k++)
+ for (int k = 0; k < pK[n]; k++)
wsum += pMOG[k].w;
- double wfactor = 1.0/wsum;
+ double wfactor = 1.0 / wsum;
- for(int k = 0; k < pK[n]; k++)
+ for (int k = 0; k < pK[n]; k++)
{
pMOG[k].w *= wfactor;
- pMOG[k].sortKey = pMOG[k].w/sqrt(pMOG[k].var.Red+pMOG[k].var.Green+pMOG[k].var.Blue);
+ pMOG[k].sortKey = pMOG[k].w / sqrt(pMOG[k].var.Red + pMOG[k].var.Green + pMOG[k].var.Blue);
}
// Sort distributions
for (int k = 0; k < kHit; k++)
{
- if(pMOG[kHit].sortKey > pMOG[k].sortKey)
+ if (pMOG[kHit].sortKey > pMOG[k].sortKey)
{
- std::swap(pMOG[kHit],pMOG[k]);
+ std::swap(pMOG[kHit], pMOG[k]);
break;
}
}
@@ -277,21 +277,21 @@ namespace lb_library
wsum = 0.0;
- for(int k = 0; k < pK[n]; k++)
+ for (int k = 0; k < pK[n]; k++)
{
wsum += pMOG[k].w;
- if(wsum > m_T)
+ if (wsum > m_T)
{
kBG = k;
break;
}
}
- if(kHit > kBG)
- prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 255;
+ if (kHit > kBG)
+ prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 255;
else
- prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 0;
+ prgbFG[i][j].Red = prgbFG[i][j].Green = prgbFG[i][j].Blue = 0;
prgbBG[i][j].Red = (unsigned char)pMOG[0].mu.Red;
prgbBG[i][j].Green = (unsigned char)pMOG[0].mu.Green;
@@ -306,4 +306,4 @@ namespace lb_library
return;
}
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/BGModelMog.h b/package_bgs/lb/BGModelMog.h
index c4e51a4..c75d1fd 100644
--- a/package_bgs/lb/BGModelMog.h
+++ b/package_bgs/lb/BGModelMog.h
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelMog.h
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -33,9 +33,7 @@ You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef BGMODELMOGRGB_H
-#define BGMODELMOGRGB_H
+#pragma once
#include "BGModel.h"
@@ -79,5 +77,3 @@ namespace lb_library
};
}
}
-
-#endif
diff --git a/package_bgs/lb/BGModelSom.cpp b/package_bgs/lb/BGModelSom.cpp
index 256d485..735af6e 100644
--- a/package_bgs/lb/BGModelSom.cpp
+++ b/package_bgs/lb/BGModelSom.cpp
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelSom.cpp
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -40,28 +40,28 @@ namespace lb_library
{
namespace AdaptiveSOM
{
- BGModelSom::BGModelSom(int width, int height) : BGModel(width,height)
+ BGModelSom::BGModelSom(int width, int height) : BGModel(width, height)
{
- m_offset = (KERNEL - 1)/2;
+ m_offset = (KERNEL - 1) / 2;
- if(SPAN_NEIGHBORS)
- m_pad = 0;
+ if (SPAN_NEIGHBORS)
+ m_pad = 0;
else
m_pad = m_offset;
// SOM models
- m_widthSOM = m_width*M + 2*m_offset + (m_width-1)*m_pad;
- m_heightSOM = m_height*N + 2*m_offset + (m_height-1)*m_pad;
+ m_widthSOM = m_width*M + 2 * m_offset + (m_width - 1)*m_pad;
+ m_heightSOM = m_height*N + 2 * m_offset + (m_height - 1)*m_pad;
- m_ppSOM = new DBLRGB*[m_heightSOM];
- for(int n = 0; n < m_heightSOM; n++)
+ m_ppSOM = new DBLRGB*[m_heightSOM];
+ for (int n = 0; n < m_heightSOM; n++)
m_ppSOM[n] = new DBLRGB[m_widthSOM];
- for(int j = 0; j < m_heightSOM; j++)
+ for (int j = 0; j < m_heightSOM; j++)
{
- for(int i = 0; i < m_widthSOM; i++)
- {
+ for (int i = 0; i < m_widthSOM; i++)
+ {
m_ppSOM[j][i].Red = 0.0;
m_ppSOM[j][i].Green = 0.0;
m_ppSOM[j][i].Blue = 0.0;
@@ -71,7 +71,7 @@ namespace lb_library
// Create weights
m_ppW = new double*[KERNEL];
- for(int n = 0; n < KERNEL; n++)
+ for (int n = 0; n < KERNEL; n++)
m_ppW[n] = new double[KERNEL];
// Construct Gaussian kernel using Pascal's triangle
@@ -81,16 +81,16 @@ namespace lb_library
m_Wmax = DBL_MIN;
cN = 1;
- for(int j = 0; j < KERNEL; j++)
+ for (int j = 0; j < KERNEL; j++)
{
- cM = 1;
+ cM = 1;
- for(int i = 0; i < KERNEL; i++)
+ for (int i = 0; i < KERNEL; i++)
{
m_ppW[j][i] = cN*cM;
- if(m_ppW[j][i] > m_Wmax)
- m_Wmax = m_ppW[j][i];
+ if (m_ppW[j][i] > m_Wmax)
+ m_Wmax = m_ppW[j][i];
cM = cM * (KERNEL - 1 - i) / (i + 1);
}
@@ -103,8 +103,8 @@ namespace lb_library
m_epsilon1 = EPS1*EPS1;
m_epsilon2 = EPS2*EPS2;
- m_alpha1 = C1/m_Wmax;
- m_alpha2 = C2/m_Wmax;
+ m_alpha1 = C1 / m_Wmax;
+ m_alpha2 = C2 / m_Wmax;
m_K = 0;
m_TSteps = TRAINING_STEPS;
@@ -112,22 +112,22 @@ namespace lb_library
BGModelSom::~BGModelSom()
{
- for(int n = 0; n < m_heightSOM; n++)
- delete [] m_ppSOM[n];
+ for (int n = 0; n < m_heightSOM; n++)
+ delete[] m_ppSOM[n];
- delete [] m_ppSOM;
+ delete[] m_ppSOM;
- for(int n = 0; n < KERNEL; n++)
- delete [] m_ppW[n];
+ for (int n = 0; n < KERNEL; n++)
+ delete[] m_ppW[n];
- delete [] m_ppW;
+ delete[] m_ppW;
}
void BGModelSom::setBGModelParameter(int id, int value)
{
- double dvalue = (double)value/255.0;
+ double dvalue = (double)value / 255.0;
- switch(id)
+ switch (id)
{
case 0:
m_epsilon2 = 255.0*255.0*dvalue*dvalue*dvalue*dvalue;
@@ -138,11 +138,11 @@ namespace lb_library
break;
case 2:
- m_alpha2 = dvalue*dvalue*dvalue/m_Wmax;
+ m_alpha2 = dvalue*dvalue*dvalue / m_Wmax;
break;
case 3:
- m_alpha1 = dvalue*dvalue*dvalue/m_Wmax;
+ m_alpha1 = dvalue*dvalue*dvalue / m_Wmax;
break;
case 5:
@@ -157,21 +157,21 @@ namespace lb_library
{
Image<BYTERGB> prgbSrc(m_SrcImage);
- for(int j = 0; j < m_height; j++)
+ for (int j = 0; j < m_height; j++)
{
int jj = m_offset + j*(N + m_pad);
- for(int i = 0; i < m_width; i++)
+ for (int i = 0; i < m_width; i++)
{
- int ii = m_offset + i*(M + m_pad);
+ int ii = m_offset + i*(M + m_pad);
- for(int l = 0; l < N; l++)
+ for (int l = 0; l < N; l++)
{
- for(int k = 0; k < M; k++)
+ for (int k = 0; k < M; k++)
{
- m_ppSOM[jj+l][ii+k].Red = (double)prgbSrc[j][i].Red;
- m_ppSOM[jj+l][ii+k].Green = (double)prgbSrc[j][i].Green;
- m_ppSOM[jj+l][ii+k].Blue = (double)prgbSrc[j][i].Blue;
+ m_ppSOM[jj + l][ii + k].Red = (double)prgbSrc[j][i].Red;
+ m_ppSOM[jj + l][ii + k].Green = (double)prgbSrc[j][i].Green;
+ m_ppSOM[jj + l][ii + k].Blue = (double)prgbSrc[j][i].Blue;
}
}
}
@@ -184,18 +184,18 @@ namespace lb_library
void BGModelSom::Update()
{
- double alpha,a;
+ double alpha, a;
double epsilon;
// calibration phase
- if(m_K <= m_TSteps)
- {
+ if (m_K <= m_TSteps)
+ {
epsilon = m_epsilon1;
- alpha = (m_alpha1-m_K*(m_alpha1-m_alpha2)/m_TSteps);
+ alpha = (m_alpha1 - m_K*(m_alpha1 - m_alpha2) / m_TSteps);
m_K++;
}
else // online phase
- {
+ {
epsilon = m_epsilon2;
alpha = m_alpha2;
}
@@ -204,11 +204,11 @@ namespace lb_library
Image<BYTERGB> prgbBG(m_BGImage);
Image<BYTERGB> prgbFG(m_FGImage);
- for(int j = 0; j < m_height; j++)
+ for (int j = 0; j < m_height; j++)
{
int jj = m_offset + j*(N + m_pad);
- for(int i = 0; i < m_width; i++)
+ for (int i = 0; i < m_width; i++)
{
int ii = m_offset + i*(M + m_pad);
@@ -222,17 +222,17 @@ namespace lb_library
int iiHit = ii;
int jjHit = jj;
- for(int l = 0; l < N; l++)
+ for (int l = 0; l < N; l++)
{
- for(int k = 0; k < M; k++)
+ for (int k = 0; k < M; k++)
{
- double dr = srcR - m_ppSOM[jj+l][ii+k].Red;
- double dg = srcG - m_ppSOM[jj+l][ii+k].Green;
- double db = srcB - m_ppSOM[jj+l][ii+k].Blue;
+ double dr = srcR - m_ppSOM[jj + l][ii + k].Red;
+ double dg = srcG - m_ppSOM[jj + l][ii + k].Green;
+ double db = srcB - m_ppSOM[jj + l][ii + k].Blue;
double d2 = dr*dr + dg*dg + db*db;
- if(d2 < d2min)
+ if (d2 < d2min)
{
d2min = d2;
iiHit = ii + k;
@@ -243,28 +243,28 @@ namespace lb_library
// Update SOM
- if(d2min <= epsilon) // matching model found
+ if (d2min <= epsilon) // matching model found
{
- for(int l = (jjHit - m_offset); l <= (jjHit + m_offset); l++)
+ for (int l = (jjHit - m_offset); l <= (jjHit + m_offset); l++)
{
- for(int k = (iiHit - m_offset); k <= (iiHit + m_offset); k++)
+ for (int k = (iiHit - m_offset); k <= (iiHit + m_offset); k++)
{
- a = alpha*m_ppW[l-jjHit+m_offset][k-iiHit+m_offset];
+ a = alpha*m_ppW[l - jjHit + m_offset][k - iiHit + m_offset];
// speed hack.. avoid very small increment values. abs() is sloooow.
double d;
d = srcR - m_ppSOM[l][k].Red;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
m_ppSOM[l][k].Red += a*d;
d = srcG - m_ppSOM[l][k].Green;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
m_ppSOM[l][k].Green += a*d;
d = srcB - m_ppSOM[l][k].Blue;
- if(d*d > DBL_MIN)
+ if (d*d > DBL_MIN)
m_ppSOM[l][k].Blue += a*d;
}
}
@@ -272,7 +272,7 @@ namespace lb_library
// Set background image
prgbBG[j][i].Red = m_ppSOM[jjHit][iiHit].Red;
prgbBG[j][i].Green = m_ppSOM[jjHit][iiHit].Green;
- prgbBG[j][i].Blue = m_ppSOM[jjHit][iiHit].Blue;
+ prgbBG[j][i].Blue = m_ppSOM[jjHit][iiHit].Blue;
// Set foreground image
prgbFG[j][i].Red = prgbFG[j][i].Green = prgbFG[j][i].Blue = 0;
@@ -288,4 +288,4 @@ namespace lb_library
return;
}
}
-}
\ No newline at end of file
+}
diff --git a/package_bgs/lb/BGModelSom.h b/package_bgs/lb/BGModelSom.h
index dcd7158..0975b0b 100644
--- a/package_bgs/lb/BGModelSom.h
+++ b/package_bgs/lb/BGModelSom.h
@@ -14,7 +14,7 @@ GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
-/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
+/* Scene 1.0.1 -- Background subtraction and object tracking for complex environments
BGModelSom.h
Copyright (C) 2011 Laurence Bender <lbender@untref.edu.ar>
@@ -33,9 +33,7 @@ You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef BGMODELSOM_H
-#define BGMODELSOM_H
+#pragma once
#include "BGModel.h"
@@ -47,9 +45,9 @@ namespace lb_library
const int M = 3; // width SOM (per pixel)
const int N = 3; // height SOM (per pixel)
- const int KERNEL = 3; // size Gaussian kernel
+ const int KERNEL = 3; // size Gaussian kernel
- const bool SPAN_NEIGHBORS = false; // true if update neighborhood spans different pixels //
+ const bool SPAN_NEIGHBORS = false; // true if update neighborhood spans different pixels //
const int TRAINING_STEPS = 100; // number of training steps
const float EPS1 = 100.0; // model match distance during training
@@ -81,12 +79,10 @@ namespace lb_library
double m_alpha2;
DBLRGB** m_ppSOM; // SOM grid
- double** m_ppW; // Weights
+ double** m_ppW; // Weights
void Init();
void Update();
};
}
}
-
-#endif
diff --git a/package_bgs/lb/Types.h b/package_bgs/lb/Types.h
index cb318a2..bd59c41 100644
--- a/package_bgs/lb/Types.h
+++ b/package_bgs/lb/Types.h
@@ -33,57 +33,55 @@ You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
-
-#ifndef TYPES_H
-#define TYPES_H
+#pragma once
#include <opencv2/opencv.hpp>
namespace lb_library
{
- template<class T> class Image
- {
- private:
- IplImage* imgp;
+template<class T> class Image
+{
+private:
+ IplImage* imgp;
- public:
- Image(IplImage* img=0) {imgp=img;}
- ~Image(){imgp=0;}
+public:
+ Image(IplImage* img=0) {imgp=img;}
+ ~Image(){imgp=0;}
- void operator=(IplImage* img) {imgp=img;}
+ void operator=(IplImage* img) {imgp=img;}
- inline T* operator[](const int rowIndx)
- {
- return ((T *)(imgp->imageData + rowIndx*imgp->widthStep));
- }
- };
-
- typedef struct{
- unsigned char b,g,r;
- } RgbPixel;
-
- typedef struct{
- unsigned char Blue,Green,Red;
- } BYTERGB;
-
- typedef struct{
- unsigned int Blue,Green,Red;
- } INTRGB;
-
- typedef struct{
- float b,g,r;
- }RgbPixelFloat;
-
- typedef struct{
- double Blue,Green,Red;
- } DBLRGB;
-
- typedef Image<RgbPixel> RgbImage;
- typedef Image<RgbPixelFloat> RgbImageFloat;
- typedef Image<unsigned char> BwImage;
- typedef Image<float> BwImageFloat;
-
- /*
+ inline T* operator[](const int rowIndx)
+ {
+ return ((T *)(imgp->imageData + rowIndx*imgp->widthStep));
+ }
+};
+
+typedef struct{
+ unsigned char b,g,r;
+} RgbPixel;
+
+typedef struct{
+ unsigned char Blue,Green,Red;
+} BYTERGB;
+
+typedef struct{
+ unsigned int Blue,Green,Red;
+} INTRGB;
+
+typedef struct{
+ float b,g,r;
+}RgbPixelFloat;
+
+typedef struct{
+ double Blue,Green,Red;
+} DBLRGB;
+
+typedef Image<RgbPixel> RgbImage;
+typedef Image<RgbPixelFloat> RgbImageFloat;
+typedef Image<unsigned char> BwImage;
+typedef Image<float> BwImageFloat;
+
+/*
IplImage* img = cvCreateImage(cvSize(640,480), IPL_DEPTH_32F, 3);
RgbImageFloat imgA(img);
for(int i = 0; i < m_height; i++)
@@ -93,7 +91,3 @@ namespace lb_library
imgA[i][j].r = 111;
*/
}
-
-//---------------------------------------------
-
-#endif
diff --git a/package_bgs/my/MyBGS.cpp b/package_bgs/my/MyBGS.cpp
deleted file mode 100644
index 07b51cd..0000000
--- a/package_bgs/my/MyBGS.cpp
+++ /dev/null
@@ -1,26 +0,0 @@
-#include "MyBGS.h"
-
-MyBGS::MyBGS(){}
-MyBGS::~MyBGS(){}
-
-void MyBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
-{
- if(img_input.empty())
- return;
-
- if(img_previous.empty())
- img_input.copyTo(img_previous);
-
- cv::Mat img_foreground;
- cv::absdiff(img_previous, img_input, img_foreground);
-
- if(img_foreground.channels() == 3)
- cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
-
- cv::threshold(img_foreground, img_foreground, 15, 255, cv::THRESH_BINARY);
-
- img_foreground.copyTo(img_output);
- img_previous.copyTo(img_bgmodel);
-
- img_input.copyTo(img_previous);
-}
diff --git a/package_bgs/my/MyBGS.h b/package_bgs/my/MyBGS.h
deleted file mode 100644
index fa27484..0000000
--- a/package_bgs/my/MyBGS.h
+++ /dev/null
@@ -1,22 +0,0 @@
-#pragma once
-
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-
-class MyBGS : public IBGS
-{
-private:
- cv::Mat img_previous;
-
-public:
- MyBGS();
- ~MyBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig(){}
- void loadConfig(){}
-};
\ No newline at end of file
diff --git a/package_bgs/pl/BackgroundSubtractorLBSP.cpp b/package_bgs/pl/BackgroundSubtractorLBSP.cpp
deleted file mode 100644
index 6752f76..0000000
--- a/package_bgs/pl/BackgroundSubtractorLBSP.cpp
+++ /dev/null
@@ -1,69 +0,0 @@
-#include "BackgroundSubtractorLBSP.h"
-#include "DistanceUtils.h"
-#include "RandUtils.h"
-#include <iostream>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/highgui/highgui.hpp>
-#include <iomanip>
-#include <exception>
-
-#ifndef SIZE_MAX
-# if __WORDSIZE == 64
-# define SIZE_MAX (18446744073709551615UL)
-# else
-# define SIZE_MAX (4294967295U)
-# endif
-#endif
-
-// local define used to determine the default median blur kernel size
-#define DEFAULT_MEDIAN_BLUR_KERNEL_SIZE (9)
-
-BackgroundSubtractorLBSP::BackgroundSubtractorLBSP(float fRelLBSPThreshold, size_t nLBSPThresholdOffset)
- : m_nImgChannels(0)
- ,m_nImgType(0)
- ,m_nLBSPThresholdOffset(nLBSPThresholdOffset)
- ,m_fRelLBSPThreshold(fRelLBSPThreshold)
- ,m_nTotPxCount(0)
- ,m_nTotRelevantPxCount(0)
- ,m_nFrameIndex(SIZE_MAX)
- ,m_nFramesSinceLastReset(0)
- ,m_nModelResetCooldown(0)
- ,m_aPxIdxLUT(nullptr)
- ,m_aPxInfoLUT(nullptr)
- ,m_nDefaultMedianBlurKernelSize(DEFAULT_MEDIAN_BLUR_KERNEL_SIZE)
- ,m_bInitialized(false)
- ,m_bAutoModelResetEnabled(true)
- ,m_bUsingMovingCamera(false)
- ,nDebugCoordX(0),nDebugCoordY(0) {
- CV_Assert(m_fRelLBSPThreshold>=0);
-}
-
-BackgroundSubtractorLBSP::~BackgroundSubtractorLBSP() {}
-
-void BackgroundSubtractorLBSP::initialize(const cv::Mat& oInitImg) {
- this->initialize(oInitImg,cv::Mat());
-}
-
-/*cv::AlgorithmInfo* BackgroundSubtractorLBSP::info() const {
- return nullptr;
-}*/
-
-cv::Mat BackgroundSubtractorLBSP::getROICopy() const {
- return m_oROI.clone();
-}
-
-void BackgroundSubtractorLBSP::setROI(cv::Mat& oROI) {
- LBSP::validateROI(oROI);
- CV_Assert(cv::countNonZero(oROI)>0);
- if(m_bInitialized) {
- cv::Mat oLatestBackgroundImage;
- getBackgroundImage(oLatestBackgroundImage);
- initialize(oLatestBackgroundImage,oROI);
- }
- else
- m_oROI = oROI.clone();
-}
-
-void BackgroundSubtractorLBSP::setAutomaticModelReset(bool bVal) {
- m_bAutoModelResetEnabled = bVal;
-}
diff --git a/package_bgs/pl/BackgroundSubtractorLBSP.h b/package_bgs/pl/BackgroundSubtractorLBSP.h
deleted file mode 100644
index 5602d34..0000000
--- a/package_bgs/pl/BackgroundSubtractorLBSP.h
+++ /dev/null
@@ -1,85 +0,0 @@
-#pragma once
-
-#include <opencv2/features2d/features2d.hpp>
-#include <opencv2/video/background_segm.hpp>
-#include "LBSP.h"
-
-/*!
- Local Binary Similarity Pattern (LBSP)-based change detection algorithm (abstract version/base class).
-
- For more details on the different parameters, see P.-L. St-Charles and G.-A. Bilodeau, "Improving Background
- Subtraction using Local Binary Similarity Patterns", in WACV 2014, or G.-A. Bilodeau et al, "Change Detection
- in Feature Space Using Local Binary Similarity Patterns", in CRV 2013.
-
- This algorithm is currently NOT thread-safe.
- */
-class BackgroundSubtractorLBSP : public cv::BackgroundSubtractor {
-public:
- //! full constructor
- BackgroundSubtractorLBSP(float fRelLBSPThreshold, size_t nLBSPThresholdOffset=0);
- //! default destructor
- virtual ~BackgroundSubtractorLBSP();
- //! (re)initiaization method; needs to be called before starting background subtraction
- virtual void initialize(const cv::Mat& oInitImg);
- //! (re)initiaization method; needs to be called before starting background subtraction
- virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI)=0;
- //! primary model update function; the learning param is used to override the internal learning speed (ignored when <= 0)
- virtual void operator()(cv::InputArray image, cv::OutputArray fgmask, double learningRate=0)=0;
- //! unused, always returns nullptr
- //virtual cv::AlgorithmInfo* info() const;
- //! returns a copy of the ROI used for descriptor extraction
- virtual cv::Mat getROICopy() const;
- //! sets the ROI to be used for descriptor extraction (note: this function will reinit the model and return the usable ROI)
- virtual void setROI(cv::Mat& oROI);
- //! turns automatic model reset on or off
- void setAutomaticModelReset(bool);
-
-protected:
- struct PxInfoBase {
- int nImgCoord_Y;
- int nImgCoord_X;
- size_t nModelIdx;
- };
- //! background model ROI used for LBSP descriptor extraction (specific to the input image size)
- cv::Mat m_oROI;
- //! input image size
- cv::Size m_oImgSize;
- //! input image channel size
- size_t m_nImgChannels;
- //! input image type
- int m_nImgType;
- //! LBSP internal threshold offset value, used to reduce texture noise in dark regions
- const size_t m_nLBSPThresholdOffset;
- //! LBSP relative internal threshold (kept here since we don't keep an LBSP object)
- const float m_fRelLBSPThreshold;
- //! total number of pixels (depends on the input frame size) & total number of relevant pixels
- size_t m_nTotPxCount, m_nTotRelevantPxCount;
- //! current frame index, frame count since last model reset & model reset cooldown counters
- size_t m_nFrameIndex, m_nFramesSinceLastReset, m_nModelResetCooldown;
- //! pre-allocated internal LBSP threshold values LUT for all possible 8-bit intensities
- size_t m_anLBSPThreshold_8bitLUT[UCHAR_MAX+1];
- //! internal pixel index LUT for all relevant analysis regions (based on the provided ROI)
- size_t* m_aPxIdxLUT;
- //! internal pixel info LUT for all possible pixel indexes
- PxInfoBase* m_aPxInfoLUT;
- //! default kernel size for median blur post-proc filtering
- const int m_nDefaultMedianBlurKernelSize;
- //! specifies whether the algorithm is fully initialized or not
- bool m_bInitialized;
- //! specifies whether automatic model resets are enabled or not
- bool m_bAutoModelResetEnabled;
- //! specifies whether the camera is considered moving or not
- bool m_bUsingMovingCamera;
- //! copy of latest pixel intensities (used when refreshing model)
- cv::Mat m_oLastColorFrame;
- //! copy of latest descriptors (used when refreshing model)
- cv::Mat m_oLastDescFrame;
- //! the foreground mask generated by the method at [t-1]
- cv::Mat m_oLastFGMask;
-
-public:
- // ######## DEBUG PURPOSES ONLY ##########
- int nDebugCoordX, nDebugCoordY;
- std::string sDebugName;
-};
-
diff --git a/package_bgs/pl/BackgroundSubtractorLOBSTER.cpp b/package_bgs/pl/BackgroundSubtractorLOBSTER.cpp
deleted file mode 100644
index 78938ad..0000000
--- a/package_bgs/pl/BackgroundSubtractorLOBSTER.cpp
+++ /dev/null
@@ -1,326 +0,0 @@
-#include "BackgroundSubtractorLOBSTER.h"
-#include "DistanceUtils.h"
-#include "RandUtils.h"
-#include <iostream>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/highgui/highgui.hpp>
-#include <iomanip>
-
-BackgroundSubtractorLOBSTER::BackgroundSubtractorLOBSTER( float fRelLBSPThreshold
- ,size_t nLBSPThresholdOffset
- ,size_t nDescDistThreshold
- ,size_t nColorDistThreshold
- ,size_t nBGSamples
- ,size_t nRequiredBGSamples)
- : BackgroundSubtractorLBSP(fRelLBSPThreshold,nLBSPThresholdOffset)
- ,m_nColorDistThreshold(nColorDistThreshold)
- ,m_nDescDistThreshold(nDescDistThreshold)
- ,m_nBGSamples(nBGSamples)
- ,m_nRequiredBGSamples(nRequiredBGSamples) {
- CV_Assert(m_nRequiredBGSamples<=m_nBGSamples);
- m_bAutoModelResetEnabled = false; // @@@@@@ not supported here for now
-}
-
-BackgroundSubtractorLOBSTER::~BackgroundSubtractorLOBSTER() {
- if(m_aPxIdxLUT)
- delete[] m_aPxIdxLUT;
- if(m_aPxInfoLUT)
- delete[] m_aPxInfoLUT;
-}
-
-void BackgroundSubtractorLOBSTER::initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) {
- CV_Assert(!oInitImg.empty() && oInitImg.cols>0 && oInitImg.rows>0);
- CV_Assert(oInitImg.isContinuous());
- CV_Assert(oInitImg.type()==CV_8UC1 || oInitImg.type()==CV_8UC3);
- if(oInitImg.type()==CV_8UC3) {
- std::vector<cv::Mat> voInitImgChannels;
- cv::split(oInitImg,voInitImgChannels);
- if(!cv::countNonZero((voInitImgChannels[0]!=voInitImgChannels[1])|(voInitImgChannels[2]!=voInitImgChannels[1])))
- std::cout << std::endl << "\tBackgroundSubtractorLOBSTER : Warning, grayscale images should always be passed in CV_8UC1 format for optimal performance." << std::endl;
- }
- cv::Mat oNewBGROI;
- if(oROI.empty() && (m_oROI.empty() || oROI.size()!=oInitImg.size())) {
- oNewBGROI.create(oInitImg.size(),CV_8UC1);
- oNewBGROI = cv::Scalar_<uchar>(UCHAR_MAX);
- }
- else if(oROI.empty())
- oNewBGROI = m_oROI;
- else {
- CV_Assert(oROI.size()==oInitImg.size() && oROI.type()==CV_8UC1);
- CV_Assert(cv::countNonZero((oROI<UCHAR_MAX)&(oROI>0))==0);
- oNewBGROI = oROI.clone();
- }
- LBSP::validateROI(oNewBGROI);
- const size_t nROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
- CV_Assert(nROIPxCount>0);
- m_oROI = oNewBGROI;
- m_oImgSize = oInitImg.size();
- m_nImgType = oInitImg.type();
- m_nImgChannels = oInitImg.channels();
- m_nTotPxCount = m_oImgSize.area();
- m_nTotRelevantPxCount = nROIPxCount;
- m_nFrameIndex = 0;
- m_nFramesSinceLastReset = 0;
- m_nModelResetCooldown = 0;
- m_oLastFGMask.create(m_oImgSize,CV_8UC1);
- m_oLastFGMask = cv::Scalar_<uchar>(0);
- m_oLastColorFrame.create(m_oImgSize,CV_8UC((int)m_nImgChannels));
- m_oLastColorFrame = cv::Scalar_<uchar>::all(0);
- m_oLastDescFrame.create(m_oImgSize,CV_16UC((int)m_nImgChannels));
- m_oLastDescFrame = cv::Scalar_<ushort>::all(0);
- m_voBGColorSamples.resize(m_nBGSamples);
- m_voBGDescSamples.resize(m_nBGSamples);
- for(size_t s=0; s<m_nBGSamples; ++s) {
- m_voBGColorSamples[s].create(m_oImgSize,CV_8UC((int)m_nImgChannels));
- m_voBGColorSamples[s] = cv::Scalar_<uchar>::all(0);
- m_voBGDescSamples[s].create(m_oImgSize,CV_16UC((int)m_nImgChannels));
- m_voBGDescSamples[s] = cv::Scalar_<ushort>::all(0);
- }
- if(m_aPxIdxLUT)
- delete[] m_aPxIdxLUT;
- if(m_aPxInfoLUT)
- delete[] m_aPxInfoLUT;
- m_aPxIdxLUT = new size_t[m_nTotRelevantPxCount];
- m_aPxInfoLUT = new PxInfoBase[m_nTotPxCount];
- if(m_nImgChannels==1) {
- CV_Assert(m_oLastColorFrame.step.p[0]==(size_t)m_oImgSize.width && m_oLastColorFrame.step.p[1]==1);
- CV_Assert(m_oLastDescFrame.step.p[0]==m_oLastColorFrame.step.p[0]*2 && m_oLastDescFrame.step.p[1]==m_oLastColorFrame.step.p[1]*2);
- for(size_t t=0; t<=UCHAR_MAX; ++t)
- m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>((t*m_fRelLBSPThreshold+m_nLBSPThresholdOffset)/2);
- for(size_t nPxIter=0, nModelIter=0; nPxIter<m_nTotPxCount; ++nPxIter) {
- if(m_oROI.data[nPxIter]) {
- m_aPxIdxLUT[nModelIter] = nPxIter;
- m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter/m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
- m_oLastColorFrame.data[nPxIter] = oInitImg.data[nPxIter];
- const size_t nDescIter = nPxIter*2;
- LBSP::computeGrayscaleDescriptor(oInitImg,oInitImg.data[nPxIter],m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxIter]],*((ushort*)(m_oLastDescFrame.data+nDescIter)));
- ++nModelIter;
- }
- }
- }
- else { //m_nImgChannels==3
- CV_Assert(m_oLastColorFrame.step.p[0]==(size_t)m_oImgSize.width*3 && m_oLastColorFrame.step.p[1]==3);
- CV_Assert(m_oLastDescFrame.step.p[0]==m_oLastColorFrame.step.p[0]*2 && m_oLastDescFrame.step.p[1]==m_oLastColorFrame.step.p[1]*2);
- for(size_t t=0; t<=UCHAR_MAX; ++t)
- m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>(t*m_fRelLBSPThreshold+m_nLBSPThresholdOffset);
- for(size_t nPxIter=0, nModelIter=0; nPxIter<m_nTotPxCount; ++nPxIter) {
- if(m_oROI.data[nPxIter]) {
- m_aPxIdxLUT[nModelIter] = nPxIter;
- m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter/m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
- const size_t nPxRGBIter = nPxIter*3;
- const size_t nDescRGBIter = nPxRGBIter*2;
- for(size_t c=0; c<3; ++c) {
- m_oLastColorFrame.data[nPxRGBIter+c] = oInitImg.data[nPxRGBIter+c];
- LBSP::computeSingleRGBDescriptor(oInitImg,oInitImg.data[nPxRGBIter+c],m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,c,m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxRGBIter+c]],((ushort*)(m_oLastDescFrame.data+nDescRGBIter))[c]);
- }
- ++nModelIter;
- }
- }
- }
- m_bInitialized = true;
- refreshModel(1.0f);
-}
-
-void BackgroundSubtractorLOBSTER::refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate) {
- // == refresh
- CV_Assert(m_bInitialized);
- CV_Assert(fSamplesRefreshFrac>0.0f && fSamplesRefreshFrac<=1.0f);
- const size_t nModelsToRefresh = fSamplesRefreshFrac<1.0f?(size_t)(fSamplesRefreshFrac*m_nBGSamples):m_nBGSamples;
- const size_t nRefreshStartPos = fSamplesRefreshFrac<1.0f?rand()%m_nBGSamples:0;
- if(m_nImgChannels==1) {
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- if(bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
- for(size_t nCurrModelIdx=nRefreshStartPos; nCurrModelIdx<nRefreshStartPos+nModelsToRefresh; ++nCurrModelIdx) {
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- getRandSamplePosition(nSampleImgCoord_X,nSampleImgCoord_Y,m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
- if(bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
- const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
- m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter] = m_oLastColorFrame.data[nSamplePxIdx];
- *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data+nPxIter*2)) = *((ushort*)(m_oLastDescFrame.data+nSamplePxIdx*2));
- }
- }
- }
- }
- }
- else { //m_nImgChannels==3
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- if(bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
- for(size_t nCurrModelIdx=nRefreshStartPos; nCurrModelIdx<nRefreshStartPos+nModelsToRefresh; ++nCurrModelIdx) {
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- getRandSamplePosition(nSampleImgCoord_X,nSampleImgCoord_Y,m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
- if(bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
- const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
- for(size_t c=0; c<3; ++c) {
- m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter*3+c] = m_oLastColorFrame.data[nSamplePxIdx*3+c];
- *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data+(nPxIter*3+c)*2)) = *((ushort*)(m_oLastDescFrame.data+(nSamplePxIdx*3+c)*2));
- }
- }
- }
- }
- }
- }
-}
-
-void BackgroundSubtractorLOBSTER::operator()(cv::InputArray _image, cv::OutputArray _fgmask, double learningRate) {
- CV_Assert(m_bInitialized);
- CV_Assert(learningRate>0);
- cv::Mat oInputImg = _image.getMat();
- CV_Assert(oInputImg.type()==m_nImgType && oInputImg.size()==m_oImgSize);
- CV_Assert(oInputImg.isContinuous());
- _fgmask.create(m_oImgSize,CV_8UC1);
- cv::Mat oCurrFGMask = _fgmask.getMat();
- oCurrFGMask = cv::Scalar_<uchar>(0);
- const size_t nLearningRate = (size_t)ceil(learningRate);
- if(m_nImgChannels==1) {
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- const size_t nDescIter = nPxIter*2;
- const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
- const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
- const uchar nCurrColor = oInputImg.data[nPxIter];
- size_t nGoodSamplesCount=0, nModelIdx=0;
- ushort nCurrInputDesc;
- while(nGoodSamplesCount<m_nRequiredBGSamples && nModelIdx<m_nBGSamples) {
- const uchar nBGColor = m_voBGColorSamples[nModelIdx].data[nPxIter];
- {
- const size_t nColorDist = L1dist(nCurrColor,nBGColor);
- if(nColorDist>m_nColorDistThreshold/2)
- goto failedcheck1ch;
- LBSP::computeGrayscaleDescriptor(oInputImg,nBGColor,nCurrImgCoord_X,nCurrImgCoord_Y,m_anLBSPThreshold_8bitLUT[nBGColor],nCurrInputDesc);
- const size_t nDescDist = hdist(nCurrInputDesc,*((ushort*)(m_voBGDescSamples[nModelIdx].data+nDescIter)));
- if(nDescDist>m_nDescDistThreshold)
- goto failedcheck1ch;
- nGoodSamplesCount++;
- }
- failedcheck1ch:
- nModelIdx++;
- }
- if(nGoodSamplesCount<m_nRequiredBGSamples)
- oCurrFGMask.data[nPxIter] = UCHAR_MAX;
- else {
- if((rand()%nLearningRate)==0) {
- const size_t nSampleModelIdx = rand()%m_nBGSamples;
- ushort& nRandInputDesc = *((ushort*)(m_voBGDescSamples[nSampleModelIdx].data+nDescIter));
- LBSP::computeGrayscaleDescriptor(oInputImg,nCurrColor,nCurrImgCoord_X,nCurrImgCoord_Y,m_anLBSPThreshold_8bitLUT[nCurrColor],nRandInputDesc);
- m_voBGColorSamples[nSampleModelIdx].data[nPxIter] = nCurrColor;
- }
- if((rand()%nLearningRate)==0) {
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- getRandNeighborPosition_3x3(nSampleImgCoord_X,nSampleImgCoord_Y,nCurrImgCoord_X,nCurrImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t nSampleModelIdx = rand()%m_nBGSamples;
- ushort& nRandInputDesc = m_voBGDescSamples[nSampleModelIdx].at<ushort>(nSampleImgCoord_Y,nSampleImgCoord_X);
- LBSP::computeGrayscaleDescriptor(oInputImg,nCurrColor,nCurrImgCoord_X,nCurrImgCoord_Y,m_anLBSPThreshold_8bitLUT[nCurrColor],nRandInputDesc);
- m_voBGColorSamples[nSampleModelIdx].at<uchar>(nSampleImgCoord_Y,nSampleImgCoord_X) = nCurrColor;
- }
- }
- }
- }
- else { //m_nImgChannels==3
- const size_t nCurrDescDistThreshold = m_nDescDistThreshold*3;
- const size_t nCurrColorDistThreshold = m_nColorDistThreshold*3;
- const size_t nCurrSCDescDistThreshold = nCurrDescDistThreshold/2;
- const size_t nCurrSCColorDistThreshold = nCurrColorDistThreshold/2;
- const size_t desc_row_step = m_voBGDescSamples[0].step.p[0];
- const size_t img_row_step = m_voBGColorSamples[0].step.p[0];
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
- const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
- const size_t nPxIterRGB = nPxIter*3;
- const size_t nDescIterRGB = nPxIterRGB*2;
- const uchar* const anCurrColor = oInputImg.data+nPxIterRGB;
- size_t nGoodSamplesCount=0, nModelIdx=0;
- ushort anCurrInputDesc[3];
- while(nGoodSamplesCount<m_nRequiredBGSamples && nModelIdx<m_nBGSamples) {
- const ushort* const anBGDesc = (ushort*)(m_voBGDescSamples[nModelIdx].data+nDescIterRGB);
- const uchar* const anBGColor = m_voBGColorSamples[nModelIdx].data+nPxIterRGB;
- size_t nTotColorDist = 0;
- size_t nTotDescDist = 0;
- for(size_t c=0;c<3; ++c) {
- const size_t nColorDist = L1dist(anCurrColor[c],anBGColor[c]);
- if(nColorDist>nCurrSCColorDistThreshold)
- goto failedcheck3ch;
- LBSP::computeSingleRGBDescriptor(oInputImg,anBGColor[c],nCurrImgCoord_X,nCurrImgCoord_Y,c,m_anLBSPThreshold_8bitLUT[anBGColor[c]],anCurrInputDesc[c]);
- const size_t nDescDist = hdist(anCurrInputDesc[c],anBGDesc[c]);
- if(nDescDist>nCurrSCDescDistThreshold)
- goto failedcheck3ch;
- nTotColorDist += nColorDist;
- nTotDescDist += nDescDist;
- }
- if(nTotDescDist<=nCurrDescDistThreshold && nTotColorDist<=nCurrColorDistThreshold)
- nGoodSamplesCount++;
- failedcheck3ch:
- nModelIdx++;
- }
- if(nGoodSamplesCount<m_nRequiredBGSamples)
- oCurrFGMask.data[nPxIter] = UCHAR_MAX;
- else {
- if((rand()%nLearningRate)==0) {
- const size_t nSampleModelIdx = rand()%m_nBGSamples;
- ushort* anRandInputDesc = ((ushort*)(m_voBGDescSamples[nSampleModelIdx].data+nDescIterRGB));
- const size_t anCurrIntraLBSPThresholds[3] = {m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]]};
- LBSP::computeRGBDescriptor(oInputImg,anCurrColor,nCurrImgCoord_X,nCurrImgCoord_Y,anCurrIntraLBSPThresholds,anRandInputDesc);
- for(size_t c=0; c<3; ++c)
- *(m_voBGColorSamples[nSampleModelIdx].data+nPxIterRGB+c) = anCurrColor[c];
- }
- if((rand()%nLearningRate)==0) {
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- getRandNeighborPosition_3x3(nSampleImgCoord_X,nSampleImgCoord_Y,nCurrImgCoord_X,nCurrImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t nSampleModelIdx = rand()%m_nBGSamples;
- ushort* anRandInputDesc = ((ushort*)(m_voBGDescSamples[nSampleModelIdx].data + desc_row_step*nSampleImgCoord_Y + 6*nSampleImgCoord_X));
- const size_t anCurrIntraLBSPThresholds[3] = {m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]]};
- LBSP::computeRGBDescriptor(oInputImg,anCurrColor,nCurrImgCoord_X,nCurrImgCoord_Y,anCurrIntraLBSPThresholds,anRandInputDesc);
- for(size_t c=0; c<3; ++c)
- *(m_voBGColorSamples[nSampleModelIdx].data + img_row_step*nSampleImgCoord_Y + 3*nSampleImgCoord_X + c) = anCurrColor[c];
- }
- }
- }
- }
- cv::medianBlur(oCurrFGMask,m_oLastFGMask,m_nDefaultMedianBlurKernelSize);
- m_oLastFGMask.copyTo(oCurrFGMask);
-}
-
-void BackgroundSubtractorLOBSTER::getBackgroundImage(cv::OutputArray backgroundImage) const {
- CV_DbgAssert(m_bInitialized);
- cv::Mat oAvgBGImg = cv::Mat::zeros(m_oImgSize,CV_32FC((int)m_nImgChannels));
- for(size_t s=0; s<m_nBGSamples; ++s) {
- for(int y=0; y<m_oImgSize.height; ++y) {
- for(int x=0; x<m_oImgSize.width; ++x) {
- const size_t idx_nimg = m_voBGColorSamples[s].step.p[0]*y + m_voBGColorSamples[s].step.p[1]*x;
- const size_t idx_flt32 = idx_nimg*4;
- float* oAvgBgImgPtr = (float*)(oAvgBGImg.data+idx_flt32);
- const uchar* const oBGImgPtr = m_voBGColorSamples[s].data+idx_nimg;
- for(size_t c=0; c<m_nImgChannels; ++c)
- oAvgBgImgPtr[c] += ((float)oBGImgPtr[c])/m_nBGSamples;
- }
- }
- }
- oAvgBGImg.convertTo(backgroundImage,CV_8U);
-}
-
-void BackgroundSubtractorLOBSTER::getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const {
- CV_Assert(LBSP::DESC_SIZE==2);
- CV_Assert(m_bInitialized);
- cv::Mat oAvgBGDesc = cv::Mat::zeros(m_oImgSize,CV_32FC((int)m_nImgChannels));
- for(size_t n=0; n<m_voBGDescSamples.size(); ++n) {
- for(int y=0; y<m_oImgSize.height; ++y) {
- for(int x=0; x<m_oImgSize.width; ++x) {
- const size_t idx_ndesc = m_voBGDescSamples[n].step.p[0]*y + m_voBGDescSamples[n].step.p[1]*x;
- const size_t idx_flt32 = idx_ndesc*2;
- float* oAvgBgDescPtr = (float*)(oAvgBGDesc.data+idx_flt32);
- const ushort* const oBGDescPtr = (ushort*)(m_voBGDescSamples[n].data+idx_ndesc);
- for(size_t c=0; c<m_nImgChannels; ++c)
- oAvgBgDescPtr[c] += ((float)oBGDescPtr[c])/m_voBGDescSamples.size();
- }
- }
- }
- oAvgBGDesc.convertTo(backgroundDescImage,CV_16U);
-}
diff --git a/package_bgs/pl/BackgroundSubtractorLOBSTER.h b/package_bgs/pl/BackgroundSubtractorLOBSTER.h
deleted file mode 100644
index bedc55d..0000000
--- a/package_bgs/pl/BackgroundSubtractorLOBSTER.h
+++ /dev/null
@@ -1,67 +0,0 @@
-#pragma once
-
-#include "BackgroundSubtractorLBSP.h"
-
-//! defines the default value for BackgroundSubtractorLBSP::m_fRelLBSPThreshold
-#define BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD (0.365f)
-//! defines the default value for BackgroundSubtractorLBSP::m_nLBSPThresholdOffset
-#define BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD (0)
-//! defines the default value for BackgroundSubtractorLOBSTER::m_nDescDistThreshold
-#define BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD (4)
-//! defines the default value for BackgroundSubtractorLOBSTER::m_nColorDistThreshold
-#define BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD (30)
-//! defines the default value for BackgroundSubtractorLOBSTER::m_nBGSamples
-#define BGSLOBSTER_DEFAULT_NB_BG_SAMPLES (35)
-//! defines the default value for BackgroundSubtractorLOBSTER::m_nRequiredBGSamples
-#define BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES (2)
-//! defines the default value for the learning rate passed to BackgroundSubtractorLOBSTER::operator()
-#define BGSLOBSTER_DEFAULT_LEARNING_RATE (16)
-
-/*!
- LOcal Binary Similarity segmenTER (LOBSTER) change detection algorithm.
-
- Note: both grayscale and RGB/BGR images may be used with this extractor (parameters are adjusted automatically).
- For optimal grayscale results, use CV_8UC1 frames instead of CV_8UC3.
-
- For more details on the different parameters or on the algorithm itself, see P.-L. St-Charles and
- G.-A. Bilodeau, "Improving Background Subtraction using Local Binary Similarity Patterns", in WACV 2014.
-
- This algorithm is currently NOT thread-safe.
- */
-class BackgroundSubtractorLOBSTER : public BackgroundSubtractorLBSP {
-public:
- //! full constructor
- BackgroundSubtractorLOBSTER(float fRelLBSPThreshold=BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD,
- size_t nLBSPThresholdOffset=BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD,
- size_t nDescDistThreshold=BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD,
- size_t nColorDistThreshold=BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD,
- size_t nBGSamples=BGSLOBSTER_DEFAULT_NB_BG_SAMPLES,
- size_t nRequiredBGSamples=BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES);
- //! default destructor
- virtual ~BackgroundSubtractorLOBSTER();
- //! (re)initiaization method; needs to be called before starting background subtraction
- virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI);
- //! refreshes all samples based on the last analyzed frame
- virtual void refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate=false);
- //! primary model update function; the learning param is reinterpreted as an integer and should be > 0 (smaller values == faster adaptation)
- virtual void operator()(cv::InputArray image, cv::OutputArray fgmask, double learningRate=BGSLOBSTER_DEFAULT_LEARNING_RATE);
- //! returns a copy of the latest reconstructed background image
- void getBackgroundImage(cv::OutputArray backgroundImage) const;
- //! returns a copy of the latest reconstructed background descriptors image
- virtual void getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const;
-
-protected:
- //! absolute color distance threshold
- const size_t m_nColorDistThreshold;
- //! absolute descriptor distance threshold
- const size_t m_nDescDistThreshold;
- //! number of different samples per pixel/block to be taken from input frames to build the background model
- const size_t m_nBGSamples;
- //! number of similar samples needed to consider the current pixel/block as 'background'
- const size_t m_nRequiredBGSamples;
- //! background model pixel intensity samples
- std::vector<cv::Mat> m_voBGColorSamples;
- //! background model descriptors samples
- std::vector<cv::Mat> m_voBGDescSamples;
-};
-
diff --git a/package_bgs/pl/BackgroundSubtractorSuBSENSE.cpp b/package_bgs/pl/BackgroundSubtractorSuBSENSE.cpp
deleted file mode 100644
index c7d5dac..0000000
--- a/package_bgs/pl/BackgroundSubtractorSuBSENSE.cpp
+++ /dev/null
@@ -1,737 +0,0 @@
-#include "BackgroundSubtractorSuBSENSE.h"
-#include "DistanceUtils.h"
-#include "RandUtils.h"
-#include <iostream>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/highgui/highgui.hpp>
-#include <iomanip>
-
-/*
- *
- * Intrinsic parameters for our method are defined here; tuning these for better
- * performance should not be required in most cases -- although improvements in
- * very specific scenarios are always possible.
- *
- */
-//! defines the threshold value(s) used to detect long-term ghosting and trigger the fast edge-based absorption heuristic
-#define GHOSTDET_D_MAX (0.010f) // defines 'negligible' change here
-#define GHOSTDET_S_MIN (0.995f) // defines the required minimum local foreground saturation value
-//! parameter used to scale dynamic distance threshold adjustments ('R(x)')
-#define FEEDBACK_R_VAR (0.01f)
-//! parameters used to adjust the variation step size of 'v(x)'
-#define FEEDBACK_V_INCR (1.000f)
-#define FEEDBACK_V_DECR (0.100f)
-//! parameters used to scale dynamic learning rate adjustments ('T(x)')
-#define FEEDBACK_T_DECR (0.2500f)
-#define FEEDBACK_T_INCR (0.5000f)
-#define FEEDBACK_T_LOWER (2.0000f)
-#define FEEDBACK_T_UPPER (256.00f)
-//! parameters used to define 'unstable' regions, based on segm noise/bg dynamics and local dist threshold values
-#define UNSTABLE_REG_RATIO_MIN (0.100f)
-#define UNSTABLE_REG_RDIST_MIN (3.000f)
-//! parameters used to scale the relative LBSP intensity threshold used for internal comparisons
-#define LBSPDESC_NONZERO_RATIO_MIN (0.100f)
-#define LBSPDESC_NONZERO_RATIO_MAX (0.500f)
-//! parameters used to define model reset/learning rate boosts in our frame-level component
-#define FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD (m_nMinColorDistThreshold/2)
-#define FRAMELEVEL_ANALYSIS_DOWNSAMPLE_RATIO (8)
-
-// local define used to display debug information
-#define DISPLAY_SUBSENSE_DEBUG_INFO 0
-// local define used to specify the default frame size (320x240 = QVGA)
-#define DEFAULT_FRAME_SIZE cv::Size(320,240)
-// local define used to specify the color dist threshold offset used for unstable regions
-#define STAB_COLOR_DIST_OFFSET (m_nMinColorDistThreshold/5)
-// local define used to specify the desc dist threshold offset used for unstable regions
-#define UNSTAB_DESC_DIST_OFFSET (m_nDescDistThresholdOffset)
-
-static const size_t s_nColorMaxDataRange_1ch = UCHAR_MAX;
-static const size_t s_nDescMaxDataRange_1ch = LBSP::DESC_SIZE*8;
-static const size_t s_nColorMaxDataRange_3ch = s_nColorMaxDataRange_1ch*3;
-static const size_t s_nDescMaxDataRange_3ch = s_nDescMaxDataRange_1ch*3;
-
-BackgroundSubtractorSuBSENSE::BackgroundSubtractorSuBSENSE( float fRelLBSPThreshold
- ,size_t nDescDistThresholdOffset
- ,size_t nMinColorDistThreshold
- ,size_t nBGSamples
- ,size_t nRequiredBGSamples
- ,size_t nSamplesForMovingAvgs)
- : BackgroundSubtractorLBSP(fRelLBSPThreshold)
- ,m_nMinColorDistThreshold(nMinColorDistThreshold)
- ,m_nDescDistThresholdOffset(nDescDistThresholdOffset)
- ,m_nBGSamples(nBGSamples)
- ,m_nRequiredBGSamples(nRequiredBGSamples)
- ,m_nSamplesForMovingAvgs(nSamplesForMovingAvgs)
- ,m_fLastNonZeroDescRatio(0.0f)
- ,m_bLearningRateScalingEnabled(true)
- ,m_fCurrLearningRateLowerCap(FEEDBACK_T_LOWER)
- ,m_fCurrLearningRateUpperCap(FEEDBACK_T_UPPER)
- ,m_nMedianBlurKernelSize(m_nDefaultMedianBlurKernelSize)
- ,m_bUse3x3Spread(true) {
- CV_Assert(m_nBGSamples>0 && m_nRequiredBGSamples<=m_nBGSamples);
- CV_Assert(m_nMinColorDistThreshold>=STAB_COLOR_DIST_OFFSET);
-}
-
-BackgroundSubtractorSuBSENSE::~BackgroundSubtractorSuBSENSE() {
- if(m_aPxIdxLUT)
- delete[] m_aPxIdxLUT;
- if(m_aPxInfoLUT)
- delete[] m_aPxInfoLUT;
-}
-
-void BackgroundSubtractorSuBSENSE::initialize(const cv::Mat& oInitImg, const cv::Mat& oROI) {
- // == init
- CV_Assert(!oInitImg.empty() && oInitImg.cols>0 && oInitImg.rows>0);
- CV_Assert(oInitImg.isContinuous());
- CV_Assert(oInitImg.type()==CV_8UC3 || oInitImg.type()==CV_8UC1);
- if(oInitImg.type()==CV_8UC3) {
- std::vector<cv::Mat> voInitImgChannels;
- cv::split(oInitImg,voInitImgChannels);
- if(!cv::countNonZero((voInitImgChannels[0]!=voInitImgChannels[1])|(voInitImgChannels[2]!=voInitImgChannels[1])))
- std::cout << std::endl << "\tBackgroundSubtractorSuBSENSE : Warning, grayscale images should always be passed in CV_8UC1 format for optimal performance." << std::endl;
- }
- cv::Mat oNewBGROI;
- if(oROI.empty() && (m_oROI.empty() || oROI.size()!=oInitImg.size())) {
- oNewBGROI.create(oInitImg.size(),CV_8UC1);
- oNewBGROI = cv::Scalar_<uchar>(UCHAR_MAX);
- }
- else if(oROI.empty())
- oNewBGROI = m_oROI;
- else {
- CV_Assert(oROI.size()==oInitImg.size() && oROI.type()==CV_8UC1);
- CV_Assert(cv::countNonZero((oROI<UCHAR_MAX)&(oROI>0))==0);
- oNewBGROI = oROI.clone();
- cv::Mat oTempROI;
- cv::dilate(oNewBGROI,oTempROI,cv::Mat(),cv::Point(-1,-1),LBSP::PATCH_SIZE/2);
- cv::bitwise_or(oNewBGROI,oTempROI/2,oNewBGROI);
- }
- const size_t nOrigROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
- CV_Assert(nOrigROIPxCount>0);
- LBSP::validateROI(oNewBGROI);
- const size_t nFinalROIPxCount = (size_t)cv::countNonZero(oNewBGROI);
- CV_Assert(nFinalROIPxCount>0);
- m_oROI = oNewBGROI;
- m_oImgSize = oInitImg.size();
- m_nImgType = oInitImg.type();
- m_nImgChannels = oInitImg.channels();
- m_nTotPxCount = m_oImgSize.area();
- m_nTotRelevantPxCount = nFinalROIPxCount;
- m_nFrameIndex = 0;
- m_nFramesSinceLastReset = 0;
- m_nModelResetCooldown = 0;
- m_fLastNonZeroDescRatio = 0.0f;
- const int nTotImgPixels = m_oImgSize.height*m_oImgSize.width;
- if(nOrigROIPxCount>=m_nTotPxCount/2 && (int)m_nTotPxCount>=DEFAULT_FRAME_SIZE.area()) {
- m_bLearningRateScalingEnabled = true;
- m_bAutoModelResetEnabled = true;
- m_bUse3x3Spread = !(nTotImgPixels>DEFAULT_FRAME_SIZE.area()*2);
- const int nRawMedianBlurKernelSize = std::min((int)floor((float)nTotImgPixels/DEFAULT_FRAME_SIZE.area()+0.5f)+m_nDefaultMedianBlurKernelSize,14);
- m_nMedianBlurKernelSize = (nRawMedianBlurKernelSize%2)?nRawMedianBlurKernelSize:nRawMedianBlurKernelSize-1;
- m_fCurrLearningRateLowerCap = FEEDBACK_T_LOWER;
- m_fCurrLearningRateUpperCap = FEEDBACK_T_UPPER;
- }
- else {
- m_bLearningRateScalingEnabled = false;
- m_bAutoModelResetEnabled = false;
- m_bUse3x3Spread = true;
- m_nMedianBlurKernelSize = m_nDefaultMedianBlurKernelSize;
- m_fCurrLearningRateLowerCap = FEEDBACK_T_LOWER*2;
- m_fCurrLearningRateUpperCap = FEEDBACK_T_UPPER*2;
- }
- m_oUpdateRateFrame.create(m_oImgSize,CV_32FC1);
- m_oUpdateRateFrame = cv::Scalar(m_fCurrLearningRateLowerCap);
- m_oDistThresholdFrame.create(m_oImgSize,CV_32FC1);
- m_oDistThresholdFrame = cv::Scalar(1.0f);
- m_oVariationModulatorFrame.create(m_oImgSize,CV_32FC1);
- m_oVariationModulatorFrame = cv::Scalar(10.0f); // should always be >= FEEDBACK_V_DECR
- m_oMeanLastDistFrame.create(m_oImgSize,CV_32FC1);
- m_oMeanLastDistFrame = cv::Scalar(0.0f);
- m_oMeanMinDistFrame_LT.create(m_oImgSize,CV_32FC1);
- m_oMeanMinDistFrame_LT = cv::Scalar(0.0f);
- m_oMeanMinDistFrame_ST.create(m_oImgSize,CV_32FC1);
- m_oMeanMinDistFrame_ST = cv::Scalar(0.0f);
- m_oDownSampledFrameSize = cv::Size(m_oImgSize.width/FRAMELEVEL_ANALYSIS_DOWNSAMPLE_RATIO,m_oImgSize.height/FRAMELEVEL_ANALYSIS_DOWNSAMPLE_RATIO);
- m_oMeanDownSampledLastDistFrame_LT.create(m_oDownSampledFrameSize,CV_32FC((int)m_nImgChannels));
- m_oMeanDownSampledLastDistFrame_LT = cv::Scalar(0.0f);
- m_oMeanDownSampledLastDistFrame_ST.create(m_oDownSampledFrameSize,CV_32FC((int)m_nImgChannels));
- m_oMeanDownSampledLastDistFrame_ST = cv::Scalar(0.0f);
- m_oMeanRawSegmResFrame_LT.create(m_oImgSize,CV_32FC1);
- m_oMeanRawSegmResFrame_LT = cv::Scalar(0.0f);
- m_oMeanRawSegmResFrame_ST.create(m_oImgSize,CV_32FC1);
- m_oMeanRawSegmResFrame_ST = cv::Scalar(0.0f);
- m_oMeanFinalSegmResFrame_LT.create(m_oImgSize,CV_32FC1);
- m_oMeanFinalSegmResFrame_LT = cv::Scalar(0.0f);
- m_oMeanFinalSegmResFrame_ST.create(m_oImgSize,CV_32FC1);
- m_oMeanFinalSegmResFrame_ST = cv::Scalar(0.0f);
- m_oUnstableRegionMask.create(m_oImgSize,CV_8UC1);
- m_oUnstableRegionMask = cv::Scalar_<uchar>(0);
- m_oBlinksFrame.create(m_oImgSize,CV_8UC1);
- m_oBlinksFrame = cv::Scalar_<uchar>(0);
- m_oDownSampledFrame_MotionAnalysis.create(m_oDownSampledFrameSize,CV_8UC((int)m_nImgChannels));
- m_oDownSampledFrame_MotionAnalysis = cv::Scalar_<uchar>::all(0);
- m_oLastColorFrame.create(m_oImgSize,CV_8UC((int)m_nImgChannels));
- m_oLastColorFrame = cv::Scalar_<uchar>::all(0);
- m_oLastDescFrame.create(m_oImgSize,CV_16UC((int)m_nImgChannels));
- m_oLastDescFrame = cv::Scalar_<ushort>::all(0);
- m_oLastRawFGMask.create(m_oImgSize,CV_8UC1);
- m_oLastRawFGMask = cv::Scalar_<uchar>(0);
- m_oLastFGMask.create(m_oImgSize,CV_8UC1);
- m_oLastFGMask = cv::Scalar_<uchar>(0);
- m_oLastFGMask_dilated.create(m_oImgSize,CV_8UC1);
- m_oLastFGMask_dilated = cv::Scalar_<uchar>(0);
- m_oLastFGMask_dilated_inverted.create(m_oImgSize,CV_8UC1);
- m_oLastFGMask_dilated_inverted = cv::Scalar_<uchar>(0);
- m_oFGMask_FloodedHoles.create(m_oImgSize,CV_8UC1);
- m_oFGMask_FloodedHoles = cv::Scalar_<uchar>(0);
- m_oFGMask_PreFlood.create(m_oImgSize,CV_8UC1);
- m_oFGMask_PreFlood = cv::Scalar_<uchar>(0);
- m_oCurrRawFGBlinkMask.create(m_oImgSize,CV_8UC1);
- m_oCurrRawFGBlinkMask = cv::Scalar_<uchar>(0);
- m_oLastRawFGBlinkMask.create(m_oImgSize,CV_8UC1);
- m_oLastRawFGBlinkMask = cv::Scalar_<uchar>(0);
- m_voBGColorSamples.resize(m_nBGSamples);
- m_voBGDescSamples.resize(m_nBGSamples);
- for(size_t s=0; s<m_nBGSamples; ++s) {
- m_voBGColorSamples[s].create(m_oImgSize,CV_8UC((int)m_nImgChannels));
- m_voBGColorSamples[s] = cv::Scalar_<uchar>::all(0);
- m_voBGDescSamples[s].create(m_oImgSize,CV_16UC((int)m_nImgChannels));
- m_voBGDescSamples[s] = cv::Scalar_<ushort>::all(0);
- }
- if(m_aPxIdxLUT)
- delete[] m_aPxIdxLUT;
- if(m_aPxInfoLUT)
- delete[] m_aPxInfoLUT;
- m_aPxIdxLUT = new size_t[m_nTotRelevantPxCount];
- m_aPxInfoLUT = new PxInfoBase[m_nTotPxCount];
- if(m_nImgChannels==1) {
- CV_Assert(m_oLastColorFrame.step.p[0]==(size_t)m_oImgSize.width && m_oLastColorFrame.step.p[1]==1);
- CV_Assert(m_oLastDescFrame.step.p[0]==m_oLastColorFrame.step.p[0]*2 && m_oLastDescFrame.step.p[1]==m_oLastColorFrame.step.p[1]*2);
- for(size_t t=0; t<=UCHAR_MAX; ++t)
- m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>((m_nLBSPThresholdOffset+t*m_fRelLBSPThreshold)/3);
- for(size_t nPxIter=0, nModelIter=0; nPxIter<m_nTotPxCount; ++nPxIter) {
- if(m_oROI.data[nPxIter]) {
- m_aPxIdxLUT[nModelIter] = nPxIter;
- m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter/m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
- m_oLastColorFrame.data[nPxIter] = oInitImg.data[nPxIter];
- const size_t nDescIter = nPxIter*2;
- LBSP::computeGrayscaleDescriptor(oInitImg,oInitImg.data[nPxIter],m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxIter]],*((ushort*)(m_oLastDescFrame.data+nDescIter)));
- ++nModelIter;
- }
- }
- }
- else { //m_nImgChannels==3
- CV_Assert(m_oLastColorFrame.step.p[0]==(size_t)m_oImgSize.width*3 && m_oLastColorFrame.step.p[1]==3);
- CV_Assert(m_oLastDescFrame.step.p[0]==m_oLastColorFrame.step.p[0]*2 && m_oLastDescFrame.step.p[1]==m_oLastColorFrame.step.p[1]*2);
- for(size_t t=0; t<=UCHAR_MAX; ++t)
- m_anLBSPThreshold_8bitLUT[t] = cv::saturate_cast<uchar>(m_nLBSPThresholdOffset+t*m_fRelLBSPThreshold);
- for(size_t nPxIter=0, nModelIter=0; nPxIter<m_nTotPxCount; ++nPxIter) {
- if(m_oROI.data[nPxIter]) {
- m_aPxIdxLUT[nModelIter] = nPxIter;
- m_aPxInfoLUT[nPxIter].nImgCoord_Y = (int)nPxIter/m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nImgCoord_X = (int)nPxIter%m_oImgSize.width;
- m_aPxInfoLUT[nPxIter].nModelIdx = nModelIter;
- const size_t nPxRGBIter = nPxIter*3;
- const size_t nDescRGBIter = nPxRGBIter*2;
- for(size_t c=0; c<3; ++c) {
- m_oLastColorFrame.data[nPxRGBIter+c] = oInitImg.data[nPxRGBIter+c];
- LBSP::computeSingleRGBDescriptor(oInitImg,oInitImg.data[nPxRGBIter+c],m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,c,m_anLBSPThreshold_8bitLUT[oInitImg.data[nPxRGBIter+c]],((ushort*)(m_oLastDescFrame.data+nDescRGBIter))[c]);
- }
- ++nModelIter;
- }
- }
- }
- m_bInitialized = true;
- refreshModel(1.0f);
-}
-
-void BackgroundSubtractorSuBSENSE::refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate) {
- // == refresh
- CV_Assert(m_bInitialized);
- CV_Assert(fSamplesRefreshFrac>0.0f && fSamplesRefreshFrac<=1.0f);
- const size_t nModelsToRefresh = fSamplesRefreshFrac<1.0f?(size_t)(fSamplesRefreshFrac*m_nBGSamples):m_nBGSamples;
- const size_t nRefreshStartPos = fSamplesRefreshFrac<1.0f?rand()%m_nBGSamples:0;
- if(m_nImgChannels==1) {
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- if(bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
- for(size_t nCurrModelIdx=nRefreshStartPos; nCurrModelIdx<nRefreshStartPos+nModelsToRefresh; ++nCurrModelIdx) {
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- getRandSamplePosition(nSampleImgCoord_X,nSampleImgCoord_Y,m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
- if(bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
- const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
- m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter] = m_oLastColorFrame.data[nSamplePxIdx];
- *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data+nPxIter*2)) = *((ushort*)(m_oLastDescFrame.data+nSamplePxIdx*2));
- }
- }
- }
- }
- }
- else { //m_nImgChannels==3
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- if(bForceFGUpdate || !m_oLastFGMask.data[nPxIter]) {
- for(size_t nCurrModelIdx=nRefreshStartPos; nCurrModelIdx<nRefreshStartPos+nModelsToRefresh; ++nCurrModelIdx) {
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- getRandSamplePosition(nSampleImgCoord_X,nSampleImgCoord_Y,m_aPxInfoLUT[nPxIter].nImgCoord_X,m_aPxInfoLUT[nPxIter].nImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t nSamplePxIdx = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
- if(bForceFGUpdate || !m_oLastFGMask.data[nSamplePxIdx]) {
- const size_t nCurrRealModelIdx = nCurrModelIdx%m_nBGSamples;
- for(size_t c=0; c<3; ++c) {
- m_voBGColorSamples[nCurrRealModelIdx].data[nPxIter*3+c] = m_oLastColorFrame.data[nSamplePxIdx*3+c];
- *((ushort*)(m_voBGDescSamples[nCurrRealModelIdx].data+(nPxIter*3+c)*2)) = *((ushort*)(m_oLastDescFrame.data+(nSamplePxIdx*3+c)*2));
- }
- }
- }
- }
- }
- }
-}
-
-void BackgroundSubtractorSuBSENSE::operator()(cv::InputArray _image, cv::OutputArray _fgmask, double learningRateOverride) {
- // == process
- CV_Assert(m_bInitialized);
- cv::Mat oInputImg = _image.getMat();
- CV_Assert(oInputImg.type()==m_nImgType && oInputImg.size()==m_oImgSize);
- CV_Assert(oInputImg.isContinuous());
- _fgmask.create(m_oImgSize,CV_8UC1);
- cv::Mat oCurrFGMask = _fgmask.getMat();
- memset(oCurrFGMask.data,0,oCurrFGMask.cols*oCurrFGMask.rows);
- size_t nNonZeroDescCount = 0;
- const float fRollAvgFactor_LT = 1.0f/std::min(++m_nFrameIndex,m_nSamplesForMovingAvgs);
- const float fRollAvgFactor_ST = 1.0f/std::min(m_nFrameIndex,m_nSamplesForMovingAvgs/4);
- if(m_nImgChannels==1) {
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- const size_t nDescIter = nPxIter*2;
- const size_t nFloatIter = nPxIter*4;
- const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
- const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
- const uchar nCurrColor = oInputImg.data[nPxIter];
- size_t nMinDescDist = s_nDescMaxDataRange_1ch;
- size_t nMinSumDist = s_nColorMaxDataRange_1ch;
- float* pfCurrDistThresholdFactor = (float*)(m_oDistThresholdFrame.data+nFloatIter);
- float* pfCurrVariationFactor = (float*)(m_oVariationModulatorFrame.data+nFloatIter);
- float* pfCurrLearningRate = ((float*)(m_oUpdateRateFrame.data+nFloatIter));
- float* pfCurrMeanLastDist = ((float*)(m_oMeanLastDistFrame.data+nFloatIter));
- float* pfCurrMeanMinDist_LT = ((float*)(m_oMeanMinDistFrame_LT.data+nFloatIter));
- float* pfCurrMeanMinDist_ST = ((float*)(m_oMeanMinDistFrame_ST.data+nFloatIter));
- float* pfCurrMeanRawSegmRes_LT = ((float*)(m_oMeanRawSegmResFrame_LT.data+nFloatIter));
- float* pfCurrMeanRawSegmRes_ST = ((float*)(m_oMeanRawSegmResFrame_ST.data+nFloatIter));
- float* pfCurrMeanFinalSegmRes_LT = ((float*)(m_oMeanFinalSegmResFrame_LT.data+nFloatIter));
- float* pfCurrMeanFinalSegmRes_ST = ((float*)(m_oMeanFinalSegmResFrame_ST.data+nFloatIter));
- ushort& nLastIntraDesc = *((ushort*)(m_oLastDescFrame.data+nDescIter));
- uchar& nLastColor = m_oLastColorFrame.data[nPxIter];
- const size_t nCurrColorDistThreshold = (size_t)(((*pfCurrDistThresholdFactor)*m_nMinColorDistThreshold)-((!m_oUnstableRegionMask.data[nPxIter])*STAB_COLOR_DIST_OFFSET))/2;
- const size_t nCurrDescDistThreshold = ((size_t)1<<((size_t)floor(*pfCurrDistThresholdFactor+0.5f)))+m_nDescDistThresholdOffset+(m_oUnstableRegionMask.data[nPxIter]*UNSTAB_DESC_DIST_OFFSET);
- ushort nCurrInterDesc, nCurrIntraDesc;
- LBSP::computeGrayscaleDescriptor(oInputImg,nCurrColor,nCurrImgCoord_X,nCurrImgCoord_Y,m_anLBSPThreshold_8bitLUT[nCurrColor],nCurrIntraDesc);
- m_oUnstableRegionMask.data[nPxIter] = ((*pfCurrDistThresholdFactor)>UNSTABLE_REG_RDIST_MIN || (*pfCurrMeanRawSegmRes_LT-*pfCurrMeanFinalSegmRes_LT)>UNSTABLE_REG_RATIO_MIN || (*pfCurrMeanRawSegmRes_ST-*pfCurrMeanFinalSegmRes_ST)>UNSTABLE_REG_RATIO_MIN)?1:0;
- size_t nGoodSamplesCount=0, nSampleIdx=0;
- while(nGoodSamplesCount<m_nRequiredBGSamples && nSampleIdx<m_nBGSamples) {
- const uchar& nBGColor = m_voBGColorSamples[nSampleIdx].data[nPxIter];
- {
- const size_t nColorDist = L1dist(nCurrColor,nBGColor);
- if(nColorDist>nCurrColorDistThreshold)
- goto failedcheck1ch;
- const ushort& nBGIntraDesc = *((ushort*)(m_voBGDescSamples[nSampleIdx].data+nDescIter));
- const size_t nIntraDescDist = hdist(nCurrIntraDesc,nBGIntraDesc);
- LBSP::computeGrayscaleDescriptor(oInputImg,nBGColor,nCurrImgCoord_X,nCurrImgCoord_Y,m_anLBSPThreshold_8bitLUT[nBGColor],nCurrInterDesc);
- const size_t nInterDescDist = hdist(nCurrInterDesc,nBGIntraDesc);
- const size_t nDescDist = (nIntraDescDist+nInterDescDist)/2;
- if(nDescDist>nCurrDescDistThreshold)
- goto failedcheck1ch;
- const size_t nSumDist = std::min((nDescDist/4)*(s_nColorMaxDataRange_1ch/s_nDescMaxDataRange_1ch)+nColorDist,s_nColorMaxDataRange_1ch);
- if(nSumDist>nCurrColorDistThreshold)
- goto failedcheck1ch;
- if(nMinDescDist>nDescDist)
- nMinDescDist = nDescDist;
- if(nMinSumDist>nSumDist)
- nMinSumDist = nSumDist;
- nGoodSamplesCount++;
- }
- failedcheck1ch:
- nSampleIdx++;
- }
- const float fNormalizedLastDist = ((float)L1dist(nLastColor,nCurrColor)/s_nColorMaxDataRange_1ch+(float)hdist(nLastIntraDesc,nCurrIntraDesc)/s_nDescMaxDataRange_1ch)/2;
- *pfCurrMeanLastDist = (*pfCurrMeanLastDist)*(1.0f-fRollAvgFactor_ST) + fNormalizedLastDist*fRollAvgFactor_ST;
- if(nGoodSamplesCount<m_nRequiredBGSamples) {
- // == foreground
- const float fNormalizedMinDist = std::min(1.0f,((float)nMinSumDist/s_nColorMaxDataRange_1ch+(float)nMinDescDist/s_nDescMaxDataRange_1ch)/2 + (float)(m_nRequiredBGSamples-nGoodSamplesCount)/m_nRequiredBGSamples);
- *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f-fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
- *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f-fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
- *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f-fRollAvgFactor_LT) + fRollAvgFactor_LT;
- *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f-fRollAvgFactor_ST) + fRollAvgFactor_ST;
- oCurrFGMask.data[nPxIter] = UCHAR_MAX;
- if(m_nModelResetCooldown && (rand()%(size_t)FEEDBACK_T_LOWER)==0) {
- const size_t s_rand = rand()%m_nBGSamples;
- *((ushort*)(m_voBGDescSamples[s_rand].data+nDescIter)) = nCurrIntraDesc;
- m_voBGColorSamples[s_rand].data[nPxIter] = nCurrColor;
- }
- }
- else {
- // == background
- const float fNormalizedMinDist = ((float)nMinSumDist/s_nColorMaxDataRange_1ch+(float)nMinDescDist/s_nDescMaxDataRange_1ch)/2;
- *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f-fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
- *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f-fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
- *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f-fRollAvgFactor_LT);
- *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f-fRollAvgFactor_ST);
- const size_t nLearningRate = learningRateOverride>0?(size_t)ceil(learningRateOverride):(size_t)ceil(*pfCurrLearningRate);
- if((rand()%nLearningRate)==0) {
- const size_t s_rand = rand()%m_nBGSamples;
- *((ushort*)(m_voBGDescSamples[s_rand].data+nDescIter)) = nCurrIntraDesc;
- m_voBGColorSamples[s_rand].data[nPxIter] = nCurrColor;
- }
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- const bool bCurrUsing3x3Spread = m_bUse3x3Spread && !m_oUnstableRegionMask.data[nPxIter];
- if(bCurrUsing3x3Spread)
- getRandNeighborPosition_3x3(nSampleImgCoord_X,nSampleImgCoord_Y,nCurrImgCoord_X,nCurrImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- else
- getRandNeighborPosition_5x5(nSampleImgCoord_X,nSampleImgCoord_Y,nCurrImgCoord_X,nCurrImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t n_rand = rand();
- const size_t idx_rand_uchar = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
- const size_t idx_rand_flt32 = idx_rand_uchar*4;
- const float fRandMeanLastDist = *((float*)(m_oMeanLastDistFrame.data+idx_rand_flt32));
- const float fRandMeanRawSegmRes = *((float*)(m_oMeanRawSegmResFrame_ST.data+idx_rand_flt32));
- if((n_rand%(bCurrUsing3x3Spread?nLearningRate:(nLearningRate/2+1)))==0
- || (fRandMeanRawSegmRes>GHOSTDET_S_MIN && fRandMeanLastDist<GHOSTDET_D_MAX && (n_rand%((size_t)m_fCurrLearningRateLowerCap))==0)) {
- const size_t idx_rand_ushrt = idx_rand_uchar*2;
- const size_t s_rand = rand()%m_nBGSamples;
- *((ushort*)(m_voBGDescSamples[s_rand].data+idx_rand_ushrt)) = nCurrIntraDesc;
- m_voBGColorSamples[s_rand].data[idx_rand_uchar] = nCurrColor;
- }
- }
- if(m_oLastFGMask.data[nPxIter] || (std::min(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)<UNSTABLE_REG_RATIO_MIN && oCurrFGMask.data[nPxIter])) {
- if((*pfCurrLearningRate)<m_fCurrLearningRateUpperCap)
- *pfCurrLearningRate += FEEDBACK_T_INCR/(std::max(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)*(*pfCurrVariationFactor));
- }
- else if((*pfCurrLearningRate)>m_fCurrLearningRateLowerCap)
- *pfCurrLearningRate -= FEEDBACK_T_DECR*(*pfCurrVariationFactor)/std::max(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST);
- if((*pfCurrLearningRate)<m_fCurrLearningRateLowerCap)
- *pfCurrLearningRate = m_fCurrLearningRateLowerCap;
- else if((*pfCurrLearningRate)>m_fCurrLearningRateUpperCap)
- *pfCurrLearningRate = m_fCurrLearningRateUpperCap;
- if(std::max(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)>UNSTABLE_REG_RATIO_MIN && m_oBlinksFrame.data[nPxIter])
- (*pfCurrVariationFactor) += FEEDBACK_V_INCR;
- else if((*pfCurrVariationFactor)>FEEDBACK_V_DECR) {
- (*pfCurrVariationFactor) -= m_oLastFGMask.data[nPxIter]?FEEDBACK_V_DECR/4:m_oUnstableRegionMask.data[nPxIter]?FEEDBACK_V_DECR/2:FEEDBACK_V_DECR;
- if((*pfCurrVariationFactor)<FEEDBACK_V_DECR)
- (*pfCurrVariationFactor) = FEEDBACK_V_DECR;
- }
- if((*pfCurrDistThresholdFactor)<std::pow(1.0f+std::min(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)*2,2))
- (*pfCurrDistThresholdFactor) += FEEDBACK_R_VAR*(*pfCurrVariationFactor-FEEDBACK_V_DECR);
- else {
- (*pfCurrDistThresholdFactor) -= FEEDBACK_R_VAR/(*pfCurrVariationFactor);
- if((*pfCurrDistThresholdFactor)<1.0f)
- (*pfCurrDistThresholdFactor) = 1.0f;
- }
- if(popcount(nCurrIntraDesc)>=2)
- ++nNonZeroDescCount;
- nLastIntraDesc = nCurrIntraDesc;
- nLastColor = nCurrColor;
- }
- }
- else { //m_nImgChannels==3
- for(size_t nModelIter=0; nModelIter<m_nTotRelevantPxCount; ++nModelIter) {
- const size_t nPxIter = m_aPxIdxLUT[nModelIter];
- const int nCurrImgCoord_X = m_aPxInfoLUT[nPxIter].nImgCoord_X;
- const int nCurrImgCoord_Y = m_aPxInfoLUT[nPxIter].nImgCoord_Y;
- const size_t nPxIterRGB = nPxIter*3;
- const size_t nDescIterRGB = nPxIterRGB*2;
- const size_t nFloatIter = nPxIter*4;
- const uchar* const anCurrColor = oInputImg.data+nPxIterRGB;
- size_t nMinTotDescDist=s_nDescMaxDataRange_3ch;
- size_t nMinTotSumDist=s_nColorMaxDataRange_3ch;
- float* pfCurrDistThresholdFactor = (float*)(m_oDistThresholdFrame.data+nFloatIter);
- float* pfCurrVariationFactor = (float*)(m_oVariationModulatorFrame.data+nFloatIter);
- float* pfCurrLearningRate = ((float*)(m_oUpdateRateFrame.data+nFloatIter));
- float* pfCurrMeanLastDist = ((float*)(m_oMeanLastDistFrame.data+nFloatIter));
- float* pfCurrMeanMinDist_LT = ((float*)(m_oMeanMinDistFrame_LT.data+nFloatIter));
- float* pfCurrMeanMinDist_ST = ((float*)(m_oMeanMinDistFrame_ST.data+nFloatIter));
- float* pfCurrMeanRawSegmRes_LT = ((float*)(m_oMeanRawSegmResFrame_LT.data+nFloatIter));
- float* pfCurrMeanRawSegmRes_ST = ((float*)(m_oMeanRawSegmResFrame_ST.data+nFloatIter));
- float* pfCurrMeanFinalSegmRes_LT = ((float*)(m_oMeanFinalSegmResFrame_LT.data+nFloatIter));
- float* pfCurrMeanFinalSegmRes_ST = ((float*)(m_oMeanFinalSegmResFrame_ST.data+nFloatIter));
- ushort* anLastIntraDesc = ((ushort*)(m_oLastDescFrame.data+nDescIterRGB));
- uchar* anLastColor = m_oLastColorFrame.data+nPxIterRGB;
- const size_t nCurrColorDistThreshold = (size_t)(((*pfCurrDistThresholdFactor)*m_nMinColorDistThreshold)-((!m_oUnstableRegionMask.data[nPxIter])*STAB_COLOR_DIST_OFFSET));
- const size_t nCurrDescDistThreshold = ((size_t)1<<((size_t)floor(*pfCurrDistThresholdFactor+0.5f)))+m_nDescDistThresholdOffset+(m_oUnstableRegionMask.data[nPxIter]*UNSTAB_DESC_DIST_OFFSET);
- const size_t nCurrTotColorDistThreshold = nCurrColorDistThreshold*3;
- const size_t nCurrTotDescDistThreshold = nCurrDescDistThreshold*3;
- const size_t nCurrSCColorDistThreshold = nCurrTotColorDistThreshold/2;
- ushort anCurrInterDesc[3], anCurrIntraDesc[3];
- const size_t anCurrIntraLBSPThresholds[3] = {m_anLBSPThreshold_8bitLUT[anCurrColor[0]],m_anLBSPThreshold_8bitLUT[anCurrColor[1]],m_anLBSPThreshold_8bitLUT[anCurrColor[2]]};
- LBSP::computeRGBDescriptor(oInputImg,anCurrColor,nCurrImgCoord_X,nCurrImgCoord_Y,anCurrIntraLBSPThresholds,anCurrIntraDesc);
- m_oUnstableRegionMask.data[nPxIter] = ((*pfCurrDistThresholdFactor)>UNSTABLE_REG_RDIST_MIN || (*pfCurrMeanRawSegmRes_LT-*pfCurrMeanFinalSegmRes_LT)>UNSTABLE_REG_RATIO_MIN || (*pfCurrMeanRawSegmRes_ST-*pfCurrMeanFinalSegmRes_ST)>UNSTABLE_REG_RATIO_MIN)?1:0;
- size_t nGoodSamplesCount=0, nSampleIdx=0;
- while(nGoodSamplesCount<m_nRequiredBGSamples && nSampleIdx<m_nBGSamples) {
- const ushort* const anBGIntraDesc = (ushort*)(m_voBGDescSamples[nSampleIdx].data+nDescIterRGB);
- const uchar* const anBGColor = m_voBGColorSamples[nSampleIdx].data+nPxIterRGB;
- size_t nTotDescDist = 0;
- size_t nTotSumDist = 0;
- for(size_t c=0;c<3; ++c) {
- const size_t nColorDist = L1dist(anCurrColor[c],anBGColor[c]);
- if(nColorDist>nCurrSCColorDistThreshold)
- goto failedcheck3ch;
- const size_t nIntraDescDist = hdist(anCurrIntraDesc[c],anBGIntraDesc[c]);
- LBSP::computeSingleRGBDescriptor(oInputImg,anBGColor[c],nCurrImgCoord_X,nCurrImgCoord_Y,c,m_anLBSPThreshold_8bitLUT[anBGColor[c]],anCurrInterDesc[c]);
- const size_t nInterDescDist = hdist(anCurrInterDesc[c],anBGIntraDesc[c]);
- const size_t nDescDist = (nIntraDescDist+nInterDescDist)/2;
- const size_t nSumDist = std::min((nDescDist/2)*(s_nColorMaxDataRange_1ch/s_nDescMaxDataRange_1ch)+nColorDist,s_nColorMaxDataRange_1ch);
- if(nSumDist>nCurrSCColorDistThreshold)
- goto failedcheck3ch;
- nTotDescDist += nDescDist;
- nTotSumDist += nSumDist;
- }
- if(nTotDescDist>nCurrTotDescDistThreshold || nTotSumDist>nCurrTotColorDistThreshold)
- goto failedcheck3ch;
- if(nMinTotDescDist>nTotDescDist)
- nMinTotDescDist = nTotDescDist;
- if(nMinTotSumDist>nTotSumDist)
- nMinTotSumDist = nTotSumDist;
- nGoodSamplesCount++;
- failedcheck3ch:
- nSampleIdx++;
- }
- const float fNormalizedLastDist = ((float)L1dist<3>(anLastColor,anCurrColor)/s_nColorMaxDataRange_3ch+(float)hdist<3>(anLastIntraDesc,anCurrIntraDesc)/s_nDescMaxDataRange_3ch)/2;
- *pfCurrMeanLastDist = (*pfCurrMeanLastDist)*(1.0f-fRollAvgFactor_ST) + fNormalizedLastDist*fRollAvgFactor_ST;
- if(nGoodSamplesCount<m_nRequiredBGSamples) {
- // == foreground
- const float fNormalizedMinDist = std::min(1.0f,((float)nMinTotSumDist/s_nColorMaxDataRange_3ch+(float)nMinTotDescDist/s_nDescMaxDataRange_3ch)/2 + (float)(m_nRequiredBGSamples-nGoodSamplesCount)/m_nRequiredBGSamples);
- *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f-fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
- *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f-fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
- *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f-fRollAvgFactor_LT) + fRollAvgFactor_LT;
- *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f-fRollAvgFactor_ST) + fRollAvgFactor_ST;
- oCurrFGMask.data[nPxIter] = UCHAR_MAX;
- if(m_nModelResetCooldown && (rand()%(size_t)FEEDBACK_T_LOWER)==0) {
- const size_t s_rand = rand()%m_nBGSamples;
- for(size_t c=0; c<3; ++c) {
- *((ushort*)(m_voBGDescSamples[s_rand].data+nDescIterRGB+2*c)) = anCurrIntraDesc[c];
- *(m_voBGColorSamples[s_rand].data+nPxIterRGB+c) = anCurrColor[c];
- }
- }
- }
- else {
- // == background
- const float fNormalizedMinDist = ((float)nMinTotSumDist/s_nColorMaxDataRange_3ch+(float)nMinTotDescDist/s_nDescMaxDataRange_3ch)/2;
- *pfCurrMeanMinDist_LT = (*pfCurrMeanMinDist_LT)*(1.0f-fRollAvgFactor_LT) + fNormalizedMinDist*fRollAvgFactor_LT;
- *pfCurrMeanMinDist_ST = (*pfCurrMeanMinDist_ST)*(1.0f-fRollAvgFactor_ST) + fNormalizedMinDist*fRollAvgFactor_ST;
- *pfCurrMeanRawSegmRes_LT = (*pfCurrMeanRawSegmRes_LT)*(1.0f-fRollAvgFactor_LT);
- *pfCurrMeanRawSegmRes_ST = (*pfCurrMeanRawSegmRes_ST)*(1.0f-fRollAvgFactor_ST);
- const size_t nLearningRate = learningRateOverride>0?(size_t)ceil(learningRateOverride):(size_t)ceil(*pfCurrLearningRate);
- if((rand()%nLearningRate)==0) {
- const size_t s_rand = rand()%m_nBGSamples;
- for(size_t c=0; c<3; ++c) {
- *((ushort*)(m_voBGDescSamples[s_rand].data+nDescIterRGB+2*c)) = anCurrIntraDesc[c];
- *(m_voBGColorSamples[s_rand].data+nPxIterRGB+c) = anCurrColor[c];
- }
- }
- int nSampleImgCoord_Y, nSampleImgCoord_X;
- const bool bCurrUsing3x3Spread = m_bUse3x3Spread && !m_oUnstableRegionMask.data[nPxIter];
- if(bCurrUsing3x3Spread)
- getRandNeighborPosition_3x3(nSampleImgCoord_X,nSampleImgCoord_Y,nCurrImgCoord_X,nCurrImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- else
- getRandNeighborPosition_5x5(nSampleImgCoord_X,nSampleImgCoord_Y,nCurrImgCoord_X,nCurrImgCoord_Y,LBSP::PATCH_SIZE/2,m_oImgSize);
- const size_t n_rand = rand();
- const size_t idx_rand_uchar = m_oImgSize.width*nSampleImgCoord_Y + nSampleImgCoord_X;
- const size_t idx_rand_flt32 = idx_rand_uchar*4;
- const float fRandMeanLastDist = *((float*)(m_oMeanLastDistFrame.data+idx_rand_flt32));
- const float fRandMeanRawSegmRes = *((float*)(m_oMeanRawSegmResFrame_ST.data+idx_rand_flt32));
- if((n_rand%(bCurrUsing3x3Spread?nLearningRate:(nLearningRate/2+1)))==0
- || (fRandMeanRawSegmRes>GHOSTDET_S_MIN && fRandMeanLastDist<GHOSTDET_D_MAX && (n_rand%((size_t)m_fCurrLearningRateLowerCap))==0)) {
- const size_t idx_rand_uchar_rgb = idx_rand_uchar*3;
- const size_t idx_rand_ushrt_rgb = idx_rand_uchar_rgb*2;
- const size_t s_rand = rand()%m_nBGSamples;
- for(size_t c=0; c<3; ++c) {
- *((ushort*)(m_voBGDescSamples[s_rand].data+idx_rand_ushrt_rgb+2*c)) = anCurrIntraDesc[c];
- *(m_voBGColorSamples[s_rand].data+idx_rand_uchar_rgb+c) = anCurrColor[c];
- }
- }
- }
- if(m_oLastFGMask.data[nPxIter] || (std::min(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)<UNSTABLE_REG_RATIO_MIN && oCurrFGMask.data[nPxIter])) {
- if((*pfCurrLearningRate)<m_fCurrLearningRateUpperCap)
- *pfCurrLearningRate += FEEDBACK_T_INCR/(std::max(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)*(*pfCurrVariationFactor));
- }
- else if((*pfCurrLearningRate)>m_fCurrLearningRateLowerCap)
- *pfCurrLearningRate -= FEEDBACK_T_DECR*(*pfCurrVariationFactor)/std::max(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST);
- if((*pfCurrLearningRate)<m_fCurrLearningRateLowerCap)
- *pfCurrLearningRate = m_fCurrLearningRateLowerCap;
- else if((*pfCurrLearningRate)>m_fCurrLearningRateUpperCap)
- *pfCurrLearningRate = m_fCurrLearningRateUpperCap;
- if(std::max(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)>UNSTABLE_REG_RATIO_MIN && m_oBlinksFrame.data[nPxIter])
- (*pfCurrVariationFactor) += FEEDBACK_V_INCR;
- else if((*pfCurrVariationFactor)>FEEDBACK_V_DECR) {
- (*pfCurrVariationFactor) -= m_oLastFGMask.data[nPxIter]?FEEDBACK_V_DECR/4:m_oUnstableRegionMask.data[nPxIter]?FEEDBACK_V_DECR/2:FEEDBACK_V_DECR;
- if((*pfCurrVariationFactor)<FEEDBACK_V_DECR)
- (*pfCurrVariationFactor) = FEEDBACK_V_DECR;
- }
- if((*pfCurrDistThresholdFactor)<std::pow(1.0f+std::min(*pfCurrMeanMinDist_LT,*pfCurrMeanMinDist_ST)*2,2))
- (*pfCurrDistThresholdFactor) += FEEDBACK_R_VAR*(*pfCurrVariationFactor-FEEDBACK_V_DECR);
- else {
- (*pfCurrDistThresholdFactor) -= FEEDBACK_R_VAR/(*pfCurrVariationFactor);
- if((*pfCurrDistThresholdFactor)<1.0f)
- (*pfCurrDistThresholdFactor) = 1.0f;
- }
- if(popcount<3>(anCurrIntraDesc)>=4)
- ++nNonZeroDescCount;
- for(size_t c=0; c<3; ++c) {
- anLastIntraDesc[c] = anCurrIntraDesc[c];
- anLastColor[c] = anCurrColor[c];
- }
- }
- }
-#if DISPLAY_SUBSENSE_DEBUG_INFO
- std::cout << std::endl;
- cv::Point dbgpt(nDebugCoordX,nDebugCoordY);
- cv::Mat oMeanMinDistFrameNormalized; m_oMeanMinDistFrame_ST.copyTo(oMeanMinDistFrameNormalized);
- cv::circle(oMeanMinDistFrameNormalized,dbgpt,5,cv::Scalar(1.0f));
- cv::resize(oMeanMinDistFrameNormalized,oMeanMinDistFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("d_min(x)",oMeanMinDistFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " d_min(" << dbgpt << ") = " << m_oMeanMinDistFrame_ST.at<float>(dbgpt) << std::endl;
- cv::Mat oMeanLastDistFrameNormalized; m_oMeanLastDistFrame.copyTo(oMeanLastDistFrameNormalized);
- cv::circle(oMeanLastDistFrameNormalized,dbgpt,5,cv::Scalar(1.0f));
- cv::resize(oMeanLastDistFrameNormalized,oMeanLastDistFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("d_last(x)",oMeanLastDistFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " d_last(" << dbgpt << ") = " << m_oMeanLastDistFrame.at<float>(dbgpt) << std::endl;
- cv::Mat oMeanRawSegmResFrameNormalized; m_oMeanRawSegmResFrame_ST.copyTo(oMeanRawSegmResFrameNormalized);
- cv::circle(oMeanRawSegmResFrameNormalized,dbgpt,5,cv::Scalar(1.0f));
- cv::resize(oMeanRawSegmResFrameNormalized,oMeanRawSegmResFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("s_avg(x)",oMeanRawSegmResFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " s_avg(" << dbgpt << ") = " << m_oMeanRawSegmResFrame_ST.at<float>(dbgpt) << std::endl;
- cv::Mat oMeanFinalSegmResFrameNormalized; m_oMeanFinalSegmResFrame_ST.copyTo(oMeanFinalSegmResFrameNormalized);
- cv::circle(oMeanFinalSegmResFrameNormalized,dbgpt,5,cv::Scalar(1.0f));
- cv::resize(oMeanFinalSegmResFrameNormalized,oMeanFinalSegmResFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("z_avg(x)",oMeanFinalSegmResFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " z_avg(" << dbgpt << ") = " << m_oMeanFinalSegmResFrame_ST.at<float>(dbgpt) << std::endl;
- cv::Mat oDistThresholdFrameNormalized; m_oDistThresholdFrame.convertTo(oDistThresholdFrameNormalized,CV_32FC1,0.25f,-0.25f);
- cv::circle(oDistThresholdFrameNormalized,dbgpt,5,cv::Scalar(1.0f));
- cv::resize(oDistThresholdFrameNormalized,oDistThresholdFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("r(x)",oDistThresholdFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " r(" << dbgpt << ") = " << m_oDistThresholdFrame.at<float>(dbgpt) << std::endl;
- cv::Mat oVariationModulatorFrameNormalized; cv::normalize(m_oVariationModulatorFrame,oVariationModulatorFrameNormalized,0,255,cv::NORM_MINMAX,CV_8UC1);
- cv::circle(oVariationModulatorFrameNormalized,dbgpt,5,cv::Scalar(255));
- cv::resize(oVariationModulatorFrameNormalized,oVariationModulatorFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("v(x)",oVariationModulatorFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " v(" << dbgpt << ") = " << m_oVariationModulatorFrame.at<float>(dbgpt) << std::endl;
- cv::Mat oUpdateRateFrameNormalized; m_oUpdateRateFrame.convertTo(oUpdateRateFrameNormalized,CV_32FC1,1.0f/FEEDBACK_T_UPPER,-FEEDBACK_T_LOWER/FEEDBACK_T_UPPER);
- cv::circle(oUpdateRateFrameNormalized,dbgpt,5,cv::Scalar(1.0f));
- cv::resize(oUpdateRateFrameNormalized,oUpdateRateFrameNormalized,DEFAULT_FRAME_SIZE);
- cv::imshow("t(x)",oUpdateRateFrameNormalized);
- std::cout << std::fixed << std::setprecision(5) << " t(" << dbgpt << ") = " << m_oUpdateRateFrame.at<float>(dbgpt) << std::endl;
-#endif //DISPLAY_SUBSENSE_DEBUG_INFO
- cv::bitwise_xor(oCurrFGMask,m_oLastRawFGMask,m_oCurrRawFGBlinkMask);
- cv::bitwise_or(m_oCurrRawFGBlinkMask,m_oLastRawFGBlinkMask,m_oBlinksFrame);
- m_oCurrRawFGBlinkMask.copyTo(m_oLastRawFGBlinkMask);
- oCurrFGMask.copyTo(m_oLastRawFGMask);
- cv::morphologyEx(oCurrFGMask,m_oFGMask_PreFlood,cv::MORPH_CLOSE,cv::Mat());
- m_oFGMask_PreFlood.copyTo(m_oFGMask_FloodedHoles);
- cv::floodFill(m_oFGMask_FloodedHoles,cv::Point(0,0),UCHAR_MAX);
- cv::bitwise_not(m_oFGMask_FloodedHoles,m_oFGMask_FloodedHoles);
- cv::erode(m_oFGMask_PreFlood,m_oFGMask_PreFlood,cv::Mat(),cv::Point(-1,-1),3);
- cv::bitwise_or(oCurrFGMask,m_oFGMask_FloodedHoles,oCurrFGMask);
- cv::bitwise_or(oCurrFGMask,m_oFGMask_PreFlood,oCurrFGMask);
- cv::medianBlur(oCurrFGMask,m_oLastFGMask,m_nMedianBlurKernelSize);
- cv::dilate(m_oLastFGMask,m_oLastFGMask_dilated,cv::Mat(),cv::Point(-1,-1),3);
- cv::bitwise_and(m_oBlinksFrame,m_oLastFGMask_dilated_inverted,m_oBlinksFrame);
- cv::bitwise_not(m_oLastFGMask_dilated,m_oLastFGMask_dilated_inverted);
- cv::bitwise_and(m_oBlinksFrame,m_oLastFGMask_dilated_inverted,m_oBlinksFrame);
- m_oLastFGMask.copyTo(oCurrFGMask);
- cv::addWeighted(m_oMeanFinalSegmResFrame_LT,(1.0f-fRollAvgFactor_LT),m_oLastFGMask,(1.0/UCHAR_MAX)*fRollAvgFactor_LT,0,m_oMeanFinalSegmResFrame_LT,CV_32F);
- cv::addWeighted(m_oMeanFinalSegmResFrame_ST,(1.0f-fRollAvgFactor_ST),m_oLastFGMask,(1.0/UCHAR_MAX)*fRollAvgFactor_ST,0,m_oMeanFinalSegmResFrame_ST,CV_32F);
- const float fCurrNonZeroDescRatio = (float)nNonZeroDescCount/m_nTotRelevantPxCount;
- if(fCurrNonZeroDescRatio<LBSPDESC_NONZERO_RATIO_MIN && m_fLastNonZeroDescRatio<LBSPDESC_NONZERO_RATIO_MIN) {
- for(size_t t=0; t<=UCHAR_MAX; ++t)
- if(m_anLBSPThreshold_8bitLUT[t]>cv::saturate_cast<uchar>(m_nLBSPThresholdOffset+ceil(t*m_fRelLBSPThreshold/4)))
- --m_anLBSPThreshold_8bitLUT[t];
- }
- else if(fCurrNonZeroDescRatio>LBSPDESC_NONZERO_RATIO_MAX && m_fLastNonZeroDescRatio>LBSPDESC_NONZERO_RATIO_MAX) {
- for(size_t t=0; t<=UCHAR_MAX; ++t)
- if(m_anLBSPThreshold_8bitLUT[t]<cv::saturate_cast<uchar>(m_nLBSPThresholdOffset+UCHAR_MAX*m_fRelLBSPThreshold))
- ++m_anLBSPThreshold_8bitLUT[t];
- }
- m_fLastNonZeroDescRatio = fCurrNonZeroDescRatio;
- if(m_bLearningRateScalingEnabled) {
- cv::resize(oInputImg,m_oDownSampledFrame_MotionAnalysis,m_oDownSampledFrameSize,0,0,cv::INTER_AREA);
- cv::accumulateWeighted(m_oDownSampledFrame_MotionAnalysis,m_oMeanDownSampledLastDistFrame_LT,fRollAvgFactor_LT);
- cv::accumulateWeighted(m_oDownSampledFrame_MotionAnalysis,m_oMeanDownSampledLastDistFrame_ST,fRollAvgFactor_ST);
- size_t nTotColorDiff = 0;
- for(int i=0; i<m_oMeanDownSampledLastDistFrame_ST.rows; ++i) {
- const size_t idx1 = m_oMeanDownSampledLastDistFrame_ST.step.p[0]*i;
- for(int j=0; j<m_oMeanDownSampledLastDistFrame_ST.cols; ++j) {
- const size_t idx2 = idx1+m_oMeanDownSampledLastDistFrame_ST.step.p[1]*j;
- nTotColorDiff += (m_nImgChannels==1)?
- (size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data+idx2))-(*(float*)(m_oMeanDownSampledLastDistFrame_LT.data+idx2)))/2
- : //(m_nImgChannels==3)
- std::max((size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data+idx2))-(*(float*)(m_oMeanDownSampledLastDistFrame_LT.data+idx2))),
- std::max((size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data+idx2+4))-(*(float*)(m_oMeanDownSampledLastDistFrame_LT.data+idx2+4))),
- (size_t)fabs((*(float*)(m_oMeanDownSampledLastDistFrame_ST.data+idx2+8))-(*(float*)(m_oMeanDownSampledLastDistFrame_LT.data+idx2+8)))));
- }
- }
- const float fCurrColorDiffRatio = (float)nTotColorDiff/(m_oMeanDownSampledLastDistFrame_ST.rows*m_oMeanDownSampledLastDistFrame_ST.cols);
- if(m_bAutoModelResetEnabled) {
- if(m_nFramesSinceLastReset>1000)
- m_bAutoModelResetEnabled = false;
- else if(fCurrColorDiffRatio>=FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD && m_nModelResetCooldown==0) {
- m_nFramesSinceLastReset = 0;
- refreshModel(0.1f); // reset 10% of the bg model
- m_nModelResetCooldown = m_nSamplesForMovingAvgs/4;
- m_oUpdateRateFrame = cv::Scalar(1.0f);
- }
- else
- ++m_nFramesSinceLastReset;
- }
- else if(fCurrColorDiffRatio>=FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD*2) {
- m_nFramesSinceLastReset = 0;
- m_bAutoModelResetEnabled = true;
- }
- if(fCurrColorDiffRatio>=FRAMELEVEL_MIN_COLOR_DIFF_THRESHOLD/2) {
- m_fCurrLearningRateLowerCap = (float)std::max((int)FEEDBACK_T_LOWER>>(int)(fCurrColorDiffRatio/2),1);
- m_fCurrLearningRateUpperCap = (float)std::max((int)FEEDBACK_T_UPPER>>(int)(fCurrColorDiffRatio/2),1);
- }
- else {
- m_fCurrLearningRateLowerCap = FEEDBACK_T_LOWER;
- m_fCurrLearningRateUpperCap = FEEDBACK_T_UPPER;
- }
- if(m_nModelResetCooldown>0)
- --m_nModelResetCooldown;
- }
-}
-
-void BackgroundSubtractorSuBSENSE::getBackgroundImage(cv::OutputArray backgroundImage) const {
- CV_Assert(m_bInitialized);
- cv::Mat oAvgBGImg = cv::Mat::zeros(m_oImgSize,CV_32FC((int)m_nImgChannels));
- for(size_t s=0; s<m_nBGSamples; ++s) {
- for(int y=0; y<m_oImgSize.height; ++y) {
- for(int x=0; x<m_oImgSize.width; ++x) {
- const size_t idx_nimg = m_voBGColorSamples[s].step.p[0]*y + m_voBGColorSamples[s].step.p[1]*x;
- const size_t nFloatIter = idx_nimg*4;
- float* oAvgBgImgPtr = (float*)(oAvgBGImg.data+nFloatIter);
- const uchar* const oBGImgPtr = m_voBGColorSamples[s].data+idx_nimg;
- for(size_t c=0; c<m_nImgChannels; ++c)
- oAvgBgImgPtr[c] += ((float)oBGImgPtr[c])/m_nBGSamples;
- }
- }
- }
- oAvgBGImg.convertTo(backgroundImage,CV_8U);
-}
-
-void BackgroundSubtractorSuBSENSE::getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const {
- CV_Assert(LBSP::DESC_SIZE==2);
- CV_Assert(m_bInitialized);
- cv::Mat oAvgBGDesc = cv::Mat::zeros(m_oImgSize,CV_32FC((int)m_nImgChannels));
- for(size_t n=0; n<m_voBGDescSamples.size(); ++n) {
- for(int y=0; y<m_oImgSize.height; ++y) {
- for(int x=0; x<m_oImgSize.width; ++x) {
- const size_t idx_ndesc = m_voBGDescSamples[n].step.p[0]*y + m_voBGDescSamples[n].step.p[1]*x;
- const size_t nFloatIter = idx_ndesc*2;
- float* oAvgBgDescPtr = (float*)(oAvgBGDesc.data+nFloatIter);
- const ushort* const oBGDescPtr = (ushort*)(m_voBGDescSamples[n].data+idx_ndesc);
- for(size_t c=0; c<m_nImgChannels; ++c)
- oAvgBgDescPtr[c] += ((float)oBGDescPtr[c])/m_voBGDescSamples.size();
- }
- }
- }
- oAvgBGDesc.convertTo(backgroundDescImage,CV_16U);
-}
diff --git a/package_bgs/pl/BackgroundSubtractorSuBSENSE.h b/package_bgs/pl/BackgroundSubtractorSuBSENSE.h
deleted file mode 100644
index f8424ad..0000000
--- a/package_bgs/pl/BackgroundSubtractorSuBSENSE.h
+++ /dev/null
@@ -1,113 +0,0 @@
-#pragma once
-
-#include "BackgroundSubtractorLBSP.h"
-
-//! defines the default value for BackgroundSubtractorLBSP::m_fRelLBSPThreshold
-#define BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD (0.333f)
-//! defines the default value for BackgroundSubtractorSuBSENSE::m_nDescDistThresholdOffset
-#define BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET (3)
-//! defines the default value for BackgroundSubtractorSuBSENSE::m_nMinColorDistThreshold
-#define BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD (30)
-//! defines the default value for BackgroundSubtractorSuBSENSE::m_nBGSamples
-#define BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES (50)
-//! defines the default value for BackgroundSubtractorSuBSENSE::m_nRequiredBGSamples
-#define BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES (2)
-//! defines the default value for BackgroundSubtractorSuBSENSE::m_nSamplesForMovingAvgs
-#define BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS (100)
-
-/*!
- Self-Balanced Sensitivity segmenTER (SuBSENSE) change detection algorithm.
-
- Note: both grayscale and RGB/BGR images may be used with this extractor (parameters are adjusted automatically).
- For optimal grayscale results, use CV_8UC1 frames instead of CV_8UC3.
-
- For more details on the different parameters or on the algorithm itself, see P.-L. St-Charles et al.,
- "Flexible Background Subtraction With Self-Balanced Local Sensitivity", in CVPRW 2014.
-
- This algorithm is currently NOT thread-safe.
- */
-class BackgroundSubtractorSuBSENSE : public BackgroundSubtractorLBSP {
-public:
- //! full constructor
- BackgroundSubtractorSuBSENSE( float fRelLBSPThreshold=BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD,
- size_t nDescDistThresholdOffset=BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET,
- size_t nMinColorDistThreshold=BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD,
- size_t nBGSamples=BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES,
- size_t nRequiredBGSamples=BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES,
- size_t nSamplesForMovingAvgs=BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS);
- //! default destructor
- virtual ~BackgroundSubtractorSuBSENSE();
- //! (re)initiaization method; needs to be called before starting background subtraction
- virtual void initialize(const cv::Mat& oInitImg, const cv::Mat& oROI);
- //! refreshes all samples based on the last analyzed frame
- virtual void refreshModel(float fSamplesRefreshFrac, bool bForceFGUpdate=false);
- //! primary model update function; the learning param is used to override the internal learning thresholds (ignored when <= 0)
- virtual void operator()(cv::InputArray image, cv::OutputArray fgmask, double learningRateOverride=0);
- //! returns a copy of the latest reconstructed background image
- void getBackgroundImage(cv::OutputArray backgroundImage) const;
- //! returns a copy of the latest reconstructed background descriptors image
- void getBackgroundDescriptorsImage(cv::OutputArray backgroundDescImage) const;
-
-protected:
- //! absolute minimal color distance threshold ('R' or 'radius' in the original ViBe paper, used as the default/initial 'R(x)' value here)
- const size_t m_nMinColorDistThreshold;
- //! absolute descriptor distance threshold offset
- const size_t m_nDescDistThresholdOffset;
- //! number of different samples per pixel/block to be taken from input frames to build the background model (same as 'N' in ViBe/PBAS)
- const size_t m_nBGSamples;
- //! number of similar samples needed to consider the current pixel/block as 'background' (same as '#_min' in ViBe/PBAS)
- const size_t m_nRequiredBGSamples;
- //! number of samples to use to compute the learning rate of moving averages
- const size_t m_nSamplesForMovingAvgs;
- //! last calculated non-zero desc ratio
- float m_fLastNonZeroDescRatio;
- //! specifies whether Tmin/Tmax scaling is enabled or not
- bool m_bLearningRateScalingEnabled;
- //! current learning rate caps
- float m_fCurrLearningRateLowerCap, m_fCurrLearningRateUpperCap;
- //! current kernel size for median blur post-proc filtering
- int m_nMedianBlurKernelSize;
- //! specifies the px update spread range
- bool m_bUse3x3Spread;
- //! specifies the downsampled frame size used for cam motion analysis
- cv::Size m_oDownSampledFrameSize;
-
- //! background model pixel color intensity samples (equivalent to 'B(x)' in PBAS)
- std::vector<cv::Mat> m_voBGColorSamples;
- //! background model descriptors samples
- std::vector<cv::Mat> m_voBGDescSamples;
-
- //! per-pixel update rates ('T(x)' in PBAS, which contains pixel-level 'sigmas', as referred to in ViBe)
- cv::Mat m_oUpdateRateFrame;
- //! per-pixel distance thresholds (equivalent to 'R(x)' in PBAS, but used as a relative value to determine both intensity and descriptor variation thresholds)
- cv::Mat m_oDistThresholdFrame;
- //! per-pixel distance variation modulators ('v(x)', relative value used to modulate 'R(x)' and 'T(x)' variations)
- cv::Mat m_oVariationModulatorFrame;
- //! per-pixel mean distances between consecutive frames ('D_last(x)', used to detect ghosts and high variation regions in the sequence)
- cv::Mat m_oMeanLastDistFrame;
- //! per-pixel mean minimal distances from the model ('D_min(x)' in PBAS, used to control variation magnitude and direction of 'T(x)' and 'R(x)')
- cv::Mat m_oMeanMinDistFrame_LT, m_oMeanMinDistFrame_ST;
- //! per-pixel mean downsampled distances between consecutive frames (used to analyze camera movement and control max learning rates globally)
- cv::Mat m_oMeanDownSampledLastDistFrame_LT, m_oMeanDownSampledLastDistFrame_ST;
- //! per-pixel mean raw segmentation results (used to detect unstable segmentation regions)
- cv::Mat m_oMeanRawSegmResFrame_LT, m_oMeanRawSegmResFrame_ST;
- //! per-pixel mean raw segmentation results (used to detect unstable segmentation regions)
- cv::Mat m_oMeanFinalSegmResFrame_LT, m_oMeanFinalSegmResFrame_ST;
- //! a lookup map used to keep track of unstable regions (based on segm. noise & local dist. thresholds)
- cv::Mat m_oUnstableRegionMask;
- //! per-pixel blink detection map ('Z(x)')
- cv::Mat m_oBlinksFrame;
- //! pre-allocated matrix used to downsample the input frame when needed
- cv::Mat m_oDownSampledFrame_MotionAnalysis;
- //! the foreground mask generated by the method at [t-1] (without post-proc, used for blinking px detection)
- cv::Mat m_oLastRawFGMask;
-
- //! pre-allocated CV_8UC1 matrices used to speed up morph ops
- cv::Mat m_oFGMask_PreFlood;
- cv::Mat m_oFGMask_FloodedHoles;
- cv::Mat m_oLastFGMask_dilated;
- cv::Mat m_oLastFGMask_dilated_inverted;
- cv::Mat m_oCurrRawFGBlinkMask;
- cv::Mat m_oLastRawFGBlinkMask;
-};
-
diff --git a/package_bgs/pl/DistanceUtils.h b/package_bgs/pl/DistanceUtils.h
deleted file mode 100644
index 54d1cec..0000000
--- a/package_bgs/pl/DistanceUtils.h
+++ /dev/null
@@ -1,316 +0,0 @@
-#pragma once
-
-#include <opencv2/core/types_c.h>
-
-//! computes the L1 distance between two integer values
-template<typename T> static inline typename std::enable_if<std::is_integral<T>::value,size_t>::type L1dist(T a, T b) {
- return (size_t)abs((int)a-b);
-}
-
-//! computes the L1 distance between two float values
-template<typename T> static inline typename std::enable_if<std::is_floating_point<T>::value,float>::type L1dist(T a, T b) {
- return fabs((float)a-(float)b);
-}
-
-//! computes the L1 distance between two generic arrays
-template<size_t nChannels, typename T> static inline auto L1dist(const T* a, const T* b) -> decltype(L1dist(*a,*b)) {
- decltype(L1dist(*a,*b)) oResult = 0;
- for(size_t c=0; c<nChannels; ++c)
- oResult += L1dist(a[c],b[c]);
- return oResult;
-}
-
-//! computes the L1 distance between two generic arrays
-template<size_t nChannels, typename T> static inline auto L1dist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) -> decltype(L1dist<nChannels>(a,b)) {
- decltype(L1dist<nChannels>(a,b)) oResult = 0;
- size_t nTotElements = nElements*nChannels;
- if(m) {
- for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
- if(m[i])
- oResult += L1dist<nChannels>(a+n,b+n);
- }
- else {
- for(size_t n=0; n<nTotElements; n+=nChannels)
- oResult += L1dist<nChannels>(a+n,b+n);
- }
- return oResult;
-}
-
-//! computes the L1 distance between two generic arrays
-template<typename T> static inline auto L1dist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) -> decltype(L1dist<3>(a,b,nElements,m)) {
- CV_Assert(nChannels>0 && nChannels<=4);
- switch(nChannels) {
- case 1: return L1dist<1>(a,b,nElements,m);
- case 2: return L1dist<2>(a,b,nElements,m);
- case 3: return L1dist<3>(a,b,nElements,m);
- case 4: return L1dist<4>(a,b,nElements,m);
- default: return 0;
- }
-}
-
-//! computes the L1 distance between two opencv vectors
-template<size_t nChannels, typename T> static inline auto L1dist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) -> decltype(L1dist<nChannels,T>((T*)(0),(T*)(0))) {
- T a_array[nChannels], b_array[nChannels];
- for(size_t c=0; c<nChannels; ++c) {
- a_array[c] = a[(int)c];
- b_array[c] = b[(int)c];
- }
- return L1dist<nChannels>(a_array,b_array);
-}
-
-///////////////////////////////////////////////////////////////////////////////////////////////////
-
-//! computes the squared L2 distance between two generic variables
-template<typename T> static inline auto L2sqrdist(T a, T b) -> decltype(L1dist(a,b)) {
- auto oResult = L1dist(a,b);
- return oResult*oResult;
-}
-
-//! computes the squared L2 distance between two generic arrays
-template<size_t nChannels, typename T> static inline auto L2sqrdist(const T* a, const T* b) -> decltype(L2sqrdist(*a,*b)) {
- decltype(L2sqrdist(*a,*b)) oResult = 0;
- for(size_t c=0; c<nChannels; ++c)
- oResult += L2sqrdist(a[c],b[c]);
- return oResult;
-}
-
-//! computes the squared L2 distance between two generic arrays
-template<size_t nChannels, typename T> static inline auto L2sqrdist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) -> decltype(L2sqrdist<nChannels>(a,b)) {
- decltype(L2sqrdist<nChannels>(a,b)) oResult = 0;
- size_t nTotElements = nElements*nChannels;
- if(m) {
- for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
- if(m[i])
- oResult += L2sqrdist<nChannels>(a+n,b+n);
- }
- else {
- for(size_t n=0; n<nTotElements; n+=nChannels)
- oResult += L2sqrdist<nChannels>(a+n,b+n);
- }
- return oResult;
-}
-
-//! computes the squared L2 distance between two generic arrays
-template<typename T> static inline auto L2sqrdist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) -> decltype(L2sqrdist<3>(a,b,nElements,m)) {
- CV_Assert(nChannels>0 && nChannels<=4);
- switch(nChannels) {
- case 1: return L2sqrdist<1>(a,b,nElements,m);
- case 2: return L2sqrdist<2>(a,b,nElements,m);
- case 3: return L2sqrdist<3>(a,b,nElements,m);
- case 4: return L2sqrdist<4>(a,b,nElements,m);
- default: return 0;
- }
-}
-
-//! computes the squared L2 distance between two opencv vectors
-template<size_t nChannels, typename T> static inline auto L2sqrdist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) -> decltype(L2sqrdist<nChannels,T>((T*)(0),(T*)(0))) {
- T a_array[nChannels], b_array[nChannels];
- for(size_t c=0; c<nChannels; ++c) {
- a_array[c] = a[(int)c];
- b_array[c] = b[(int)c];
- }
- return L2sqrdist<nChannels>(a_array,b_array);
-}
-
-//! computes the L2 distance between two generic arrays
-template<size_t nChannels, typename T> static inline float L2dist(const T* a, const T* b) {
- decltype(L2sqrdist(*a,*b)) oResult = 0;
- for(size_t c=0; c<nChannels; ++c)
- oResult += L2sqrdist(a[c],b[c]);
- return sqrt((float)oResult);
-}
-
-//! computes the L2 distance between two generic arrays
-template<size_t nChannels, typename T> static inline float L2dist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) {
- decltype(L2sqrdist<nChannels>(a,b)) oResult = 0;
- size_t nTotElements = nElements*nChannels;
- if(m) {
- for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
- if(m[i])
- oResult += L2sqrdist<nChannels>(a+n,b+n);
- }
- else {
- for(size_t n=0; n<nTotElements; n+=nChannels)
- oResult += L2sqrdist<nChannels>(a+n,b+n);
- }
- return sqrt((float)oResult);
-}
-
-//! computes the squared L2 distance between two generic arrays
-template<typename T> static inline float L2dist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) {
- CV_Assert(nChannels>0 && nChannels<=4);
- switch(nChannels) {
- case 1: return L2dist<1>(a,b,nElements,m);
- case 2: return L2dist<2>(a,b,nElements,m);
- case 3: return L2dist<3>(a,b,nElements,m);
- case 4: return L2dist<4>(a,b,nElements,m);
- default: return 0;
- }
-}
-
-//! computes the L2 distance between two opencv vectors
-template<size_t nChannels, typename T> static inline float L2dist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) {
- T a_array[nChannels], b_array[nChannels];
- for(size_t c=0; c<nChannels; ++c) {
- a_array[c] = a[(int)c];
- b_array[c] = b[(int)c];
- }
- return L2dist<nChannels>(a_array,b_array);
-}
-
-///////////////////////////////////////////////////////////////////////////////////////////////////
-
-//! computes the color distortion between two integer arrays
-template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_integral<T>::value,size_t>::type cdist(const T* curr, const T* bg) {
- static_assert(nChannels>1,"cdist: requires more than one channel");
- size_t curr_sqr = 0;
- bool bSkip = true;
- for(size_t c=0; c<nChannels; ++c) {
- curr_sqr += curr[c]*curr[c];
- bSkip = bSkip&(bg[c]<=0);
- }
- if(bSkip)
- return (size_t)sqrt((float)curr_sqr);
- size_t bg_sqr = 0;
- size_t mix = 0;
- for(size_t c=0; c<nChannels; ++c) {
- bg_sqr += bg[c]*bg[c];
- mix += curr[c]*bg[c];
- }
- return (size_t)sqrt(curr_sqr-((float)(mix*mix)/bg_sqr));
-}
-
-//! computes the color distortion between two float arrays
-template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_floating_point<T>::value,float>::type cdist(const T* curr, const T* bg) {
- static_assert(nChannels>1,"cdist: requires more than one channel");
- float curr_sqr = 0;
- bool bSkip = true;
- for(size_t c=0; c<nChannels; ++c) {
- curr_sqr += (float)curr[c]*curr[c];
- bSkip = bSkip&(bg[c]<=0);
- }
- if(bSkip)
- return sqrt(curr_sqr);
- float bg_sqr = 0;
- float mix = 0;
- for(size_t c=0; c<nChannels; ++c) {
- bg_sqr += (float)bg[c]*bg[c];
- mix += (float)curr[c]*bg[c];
- }
- return sqrt(curr_sqr-((mix*mix)/bg_sqr));
-}
-
-//! computes the color distortion between two generic arrays
-template<size_t nChannels, typename T> static inline auto cdist(const T* a, const T* b, size_t nElements, const uchar* m=NULL) -> decltype(cdist<nChannels>(a,b)) {
- decltype(cdist<nChannels>(a,b)) oResult = 0;
- size_t nTotElements = nElements*nChannels;
- if(m) {
- for(size_t n=0,i=0; n<nTotElements; n+=nChannels,++i)
- if(m[i])
- oResult += cdist<nChannels>(a+n,b+n);
- }
- else {
- for(size_t n=0; n<nTotElements; n+=nChannels)
- oResult += cdist<nChannels>(a+n,b+n);
- }
- return oResult;
-}
-
-//! computes the color distortion between two generic arrays
-template<typename T> static inline auto cdist(const T* a, const T* b, size_t nElements, size_t nChannels, const uchar* m=NULL) -> decltype(cdist<3>(a,b,nElements,m)) {
- CV_Assert(nChannels>1 && nChannels<=4);
- switch(nChannels) {
- case 2: return cdist<2>(a,b,nElements,m);
- case 3: return cdist<3>(a,b,nElements,m);
- case 4: return cdist<4>(a,b,nElements,m);
- default: return 0;
- }
-}
-
-//! computes the color distortion between two opencv vectors
-template<size_t nChannels, typename T> static inline auto cdist_(const cv::Vec<T,nChannels>& a, const cv::Vec<T,nChannels>& b) -> decltype(cdist<nChannels,T>((T*)(0),(T*)(0))) {
- T a_array[nChannels], b_array[nChannels];
- for(size_t c=0; c<nChannels; ++c) {
- a_array[c] = a[(int)c];
- b_array[c] = b[(int)c];
- }
- return cdist<nChannels>(a_array,b_array);
-}
-
-//! computes a color distortion-distance mix using two generic distances
-template<typename T> static inline T cmixdist(T oL1Distance, T oCDistortion) {
- return (oL1Distance/2+oCDistortion*4);
-}
-
-//! computes a color distoirtion-distance mix using two generic arrays
-template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_integral<T>::value,size_t>::type cmixdist(const T* curr, const T* bg) {
- return cmixdist(L1dist<nChannels>(curr,bg),cdist<nChannels>(curr,bg));
-}
-
-template<size_t nChannels, typename T> static inline typename std::enable_if<std::is_floating_point<T>::value,float>::type cmixdist(const T* curr, const T* bg) {
- return cmixdist(L1dist<nChannels>(curr,bg),cdist<nChannels>(curr,bg));
-}
-
-///////////////////////////////////////////////////////////////////////////////////////////////////
-
-//! popcount LUT for 8-bit vectors
-static const uchar popcount_LUT8[256] = {
- 0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
- 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
- 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
- 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
- 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
- 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
- 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
- 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
- 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
- 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
- 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
- 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
- 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
- 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
- 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
- 4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8,
-};
-
-//! computes the population count of an N-byte vector using an 8-bit popcount LUT
-template<typename T> static inline size_t popcount(T x) {
- size_t nBytes = sizeof(T);
- size_t nResult = 0;
- for(size_t l=0; l<nBytes; ++l)
- nResult += popcount_LUT8[(uchar)(x>>l*8)];
- return nResult;
-}
-
-//! computes the hamming distance between two N-byte vectors using an 8-bit popcount LUT
-template<typename T> static inline size_t hdist(T a, T b) {
- return popcount(a^b);
-}
-
-//! computes the gradient magnitude distance between two N-byte vectors using an 8-bit popcount LUT
-template<typename T> static inline size_t gdist(T a, T b) {
- return L1dist(popcount(a),popcount(b));
-}
-
-//! computes the population count of a (nChannels*N)-byte vector using an 8-bit popcount LUT
-template<size_t nChannels, typename T> static inline size_t popcount(const T* x) {
- size_t nBytes = sizeof(T);
- size_t nResult = 0;
- for(size_t c=0; c<nChannels; ++c)
- for(size_t l=0; l<nBytes; ++l)
- nResult += popcount_LUT8[(uchar)(*(x+c)>>l*8)];
- return nResult;
-}
-
-//! computes the hamming distance between two (nChannels*N)-byte vectors using an 8-bit popcount LUT
-template<size_t nChannels, typename T> static inline size_t hdist(const T* a, const T* b) {
- T xor_array[nChannels];
- for(size_t c=0; c<nChannels; ++c)
- xor_array[c] = a[c]^b[c];
- return popcount<nChannels>(xor_array);
-}
-
-//! computes the gradient magnitude distance between two (nChannels*N)-byte vectors using an 8-bit popcount LUT
-template<size_t nChannels, typename T> static inline size_t gdist(const T* a, const T* b) {
- return L1dist(popcount<nChannels>(a),popcount<nChannels>(b));
-}
diff --git a/package_bgs/pl/LBSP.cpp b/package_bgs/pl/LBSP.cpp
deleted file mode 100644
index de35f1a..0000000
--- a/package_bgs/pl/LBSP.cpp
+++ /dev/null
@@ -1,318 +0,0 @@
-#include "LBSP.h"
-
-LBSP::LBSP(size_t nThreshold)
- : m_bOnlyUsingAbsThreshold(true)
- ,m_fRelThreshold(0) // unused
- ,m_nThreshold(nThreshold)
- ,m_oRefImage() {}
-
-LBSP::LBSP(float fRelThreshold, size_t nThresholdOffset)
- : m_bOnlyUsingAbsThreshold(false)
- ,m_fRelThreshold(fRelThreshold)
- ,m_nThreshold(nThresholdOffset)
- ,m_oRefImage() {
- CV_Assert(m_fRelThreshold>=0);
-}
-
-LBSP::~LBSP() {}
-
-void LBSP::read(const cv::FileNode& /*fn*/) {
- // ... = fn["..."];
-}
-
-void LBSP::write(cv::FileStorage& /*fs*/) const {
- //fs << "..." << ...;
-}
-
-void LBSP::setReference(const cv::Mat& img) {
- CV_DbgAssert(img.empty() || img.type()==CV_8UC1 || img.type()==CV_8UC3);
- m_oRefImage = img;
-}
-
-int LBSP::descriptorSize() const {
- return DESC_SIZE;
-}
-
-int LBSP::descriptorType() const {
- return CV_16U;
-}
-
-bool LBSP::isUsingRelThreshold() const {
- return !m_bOnlyUsingAbsThreshold;
-}
-
-float LBSP::getRelThreshold() const {
- return m_fRelThreshold;
-}
-
-size_t LBSP::getAbsThreshold() const {
- return m_nThreshold;
-}
-
-static inline void lbsp_computeImpl( const cv::Mat& oInputImg,
- const cv::Mat& oRefImg,
- const std::vector<cv::KeyPoint>& voKeyPoints,
- cv::Mat& oDesc,
- size_t _t) {
- CV_DbgAssert(oRefImg.empty() || (oRefImg.size==oInputImg.size && oRefImg.type()==oInputImg.type()));
- CV_DbgAssert(oInputImg.type()==CV_8UC1 || oInputImg.type()==CV_8UC3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- const size_t nChannels = (size_t)oInputImg.channels();
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* _data = oInputImg.data;
- const uchar* _refdata = oRefImg.empty()?oInputImg.data:oRefImg.data;
- const size_t nKeyPoints = voKeyPoints.size();
- if(nChannels==1) {
- oDesc.create((int)nKeyPoints,1,CV_16UC1);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar _ref = _refdata[_step_row*(_y)+_x];
- ushort& _res = oDesc.at<ushort>((int)k);
- #include "LBSP_16bits_dbcross_1ch.i"
- }
- }
- else { //nChannels==3
- oDesc.create((int)nKeyPoints,1,CV_16UC3);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar* _ref = _refdata+_step_row*(_y)+3*(_x);
- ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0]*k));
- #include "LBSP_16bits_dbcross_3ch1t.i"
- }
- }
-}
-
-static inline void lbsp_computeImpl( const cv::Mat& oInputImg,
- const cv::Mat& oRefImg,
- const std::vector<cv::KeyPoint>& voKeyPoints,
- cv::Mat& oDesc,
- float fThreshold,
- size_t nThresholdOffset) {
- CV_DbgAssert(oRefImg.empty() || (oRefImg.size==oInputImg.size && oRefImg.type()==oInputImg.type()));
- CV_DbgAssert(oInputImg.type()==CV_8UC1 || oInputImg.type()==CV_8UC3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(fThreshold>=0);
- const size_t nChannels = (size_t)oInputImg.channels();
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* _data = oInputImg.data;
- const uchar* _refdata = oRefImg.empty()?oInputImg.data:oRefImg.data;
- const size_t nKeyPoints = voKeyPoints.size();
- if(nChannels==1) {
- oDesc.create((int)nKeyPoints,1,CV_16UC1);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar _ref = _refdata[_step_row*(_y)+_x];
- ushort& _res = oDesc.at<ushort>((int)k);
- const size_t _t = (size_t)(_ref*fThreshold)+nThresholdOffset;
- #include "LBSP_16bits_dbcross_1ch.i"
- }
- }
- else { //nChannels==3
- oDesc.create((int)nKeyPoints,1,CV_16UC3);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar* _ref = _refdata+_step_row*(_y)+3*(_x);
- ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0]*k));
- const size_t _t[3] = {(size_t)(_ref[0]*fThreshold)+nThresholdOffset,(size_t)(_ref[1]*fThreshold)+nThresholdOffset,(size_t)(_ref[2]*fThreshold)+nThresholdOffset};
- #include "LBSP_16bits_dbcross_3ch3t.i"
- }
- }
-}
-
-static inline void lbsp_computeImpl2( const cv::Mat& oInputImg,
- const cv::Mat& oRefImg,
- const std::vector<cv::KeyPoint>& voKeyPoints,
- cv::Mat& oDesc,
- size_t _t) {
- CV_DbgAssert(oRefImg.empty() || (oRefImg.size==oInputImg.size && oRefImg.type()==oInputImg.type()));
- CV_DbgAssert(oInputImg.type()==CV_8UC1 || oInputImg.type()==CV_8UC3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- const size_t nChannels = (size_t)oInputImg.channels();
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* _data = oInputImg.data;
- const uchar* _refdata = oRefImg.empty()?oInputImg.data:oRefImg.data;
- const size_t nKeyPoints = voKeyPoints.size();
- if(nChannels==1) {
- oDesc.create(oInputImg.size(),CV_16UC1);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar _ref = _refdata[_step_row*(_y)+_x];
- ushort& _res = oDesc.at<ushort>(_y,_x);
- #include "LBSP_16bits_dbcross_1ch.i"
- }
- }
- else { //nChannels==3
- oDesc.create(oInputImg.size(),CV_16UC3);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar* _ref = _refdata+_step_row*(_y)+3*(_x);
- ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0]*_y + oDesc.step.p[1]*_x));
- #include "LBSP_16bits_dbcross_3ch1t.i"
- }
- }
-}
-
-static inline void lbsp_computeImpl2( const cv::Mat& oInputImg,
- const cv::Mat& oRefImg,
- const std::vector<cv::KeyPoint>& voKeyPoints,
- cv::Mat& oDesc,
- float fThreshold,
- size_t nThresholdOffset) {
- CV_DbgAssert(oRefImg.empty() || (oRefImg.size==oInputImg.size && oRefImg.type()==oInputImg.type()));
- CV_DbgAssert(oInputImg.type()==CV_8UC1 || oInputImg.type()==CV_8UC3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(fThreshold>=0);
- const size_t nChannels = (size_t)oInputImg.channels();
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* _data = oInputImg.data;
- const uchar* _refdata = oRefImg.empty()?oInputImg.data:oRefImg.data;
- const size_t nKeyPoints = voKeyPoints.size();
- if(nChannels==1) {
- oDesc.create(oInputImg.size(),CV_16UC1);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar _ref = _refdata[_step_row*(_y)+_x];
- ushort& _res = oDesc.at<ushort>(_y,_x);
- const size_t _t = (size_t)(_ref*fThreshold)+nThresholdOffset;
- #include "LBSP_16bits_dbcross_1ch.i"
- }
- }
- else { //nChannels==3
- oDesc.create(oInputImg.size(),CV_16UC3);
- for(size_t k=0; k<nKeyPoints; ++k) {
- const int _x = (int)voKeyPoints[k].pt.x;
- const int _y = (int)voKeyPoints[k].pt.y;
- const uchar* _ref = _refdata+_step_row*(_y)+3*(_x);
- ushort* _res = ((ushort*)(oDesc.data + oDesc.step.p[0]*_y + oDesc.step.p[1]*_x));
- const size_t _t[3] = {(size_t)(_ref[0]*fThreshold)+nThresholdOffset,(size_t)(_ref[1]*fThreshold)+nThresholdOffset,(size_t)(_ref[2]*fThreshold)+nThresholdOffset};
- #include "LBSP_16bits_dbcross_3ch3t.i"
- }
- }
-}
-
-void LBSP::compute2(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const {
- CV_Assert(!oImage.empty());
- cv::KeyPointsFilter::runByImageBorder(voKeypoints,oImage.size(),PATCH_SIZE/2);
- cv::KeyPointsFilter::runByKeypointSize(voKeypoints,std::numeric_limits<float>::epsilon());
- if(voKeypoints.empty()) {
- oDescriptors.release();
- return;
- }
- if(m_bOnlyUsingAbsThreshold)
- lbsp_computeImpl2(oImage,m_oRefImage,voKeypoints,oDescriptors,m_nThreshold);
- else
- lbsp_computeImpl2(oImage,m_oRefImage,voKeypoints,oDescriptors,m_fRelThreshold,m_nThreshold);
-}
-
-void LBSP::compute2(const std::vector<cv::Mat>& voImageCollection, std::vector<std::vector<cv::KeyPoint> >& vvoPointCollection, std::vector<cv::Mat>& voDescCollection) const {
- CV_Assert(voImageCollection.size() == vvoPointCollection.size());
- voDescCollection.resize(voImageCollection.size());
- for(size_t i=0; i<voImageCollection.size(); i++)
- compute2(voImageCollection[i], vvoPointCollection[i], voDescCollection[i]);
-}
-
-void LBSP::computeImpl(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const {
- CV_Assert(!oImage.empty());
- cv::KeyPointsFilter::runByImageBorder(voKeypoints,oImage.size(),PATCH_SIZE/2);
- cv::KeyPointsFilter::runByKeypointSize(voKeypoints,std::numeric_limits<float>::epsilon());
- if(voKeypoints.empty()) {
- oDescriptors.release();
- return;
- }
- if(m_bOnlyUsingAbsThreshold)
- lbsp_computeImpl(oImage,m_oRefImage,voKeypoints,oDescriptors,m_nThreshold);
- else
- lbsp_computeImpl(oImage,m_oRefImage,voKeypoints,oDescriptors,m_fRelThreshold,m_nThreshold);
-}
-
-void LBSP::reshapeDesc(cv::Size oSize, const std::vector<cv::KeyPoint>& voKeypoints, const cv::Mat& oDescriptors, cv::Mat& oOutput) {
- CV_DbgAssert(!voKeypoints.empty());
- CV_DbgAssert(!oDescriptors.empty() && oDescriptors.cols==1);
- CV_DbgAssert(oSize.width>0 && oSize.height>0);
- CV_DbgAssert(DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(oDescriptors.type()==CV_16UC1 || oDescriptors.type()==CV_16UC3);
- const size_t nChannels = (size_t)oDescriptors.channels();
- const size_t nKeyPoints = voKeypoints.size();
- if(nChannels==1) {
- oOutput.create(oSize,CV_16UC1);
- oOutput = cv::Scalar_<ushort>(0);
- for(size_t k=0; k<nKeyPoints; ++k)
- oOutput.at<ushort>(voKeypoints[k].pt) = oDescriptors.at<ushort>((int)k);
- }
- else { //nChannels==3
- oOutput.create(oSize,CV_16UC3);
- oOutput = cv::Scalar_<ushort>(0,0,0);
- for(size_t k=0; k<nKeyPoints; ++k) {
- ushort* output_ptr = (ushort*)(oOutput.data + oOutput.step.p[0]*(int)voKeypoints[k].pt.y);
- const ushort* const desc_ptr = (ushort*)(oDescriptors.data + oDescriptors.step.p[0]*k);
- const size_t idx = 3*(int)voKeypoints[k].pt.x;
- for(size_t n=0; n<3; ++n)
- output_ptr[idx+n] = desc_ptr[n];
- }
- }
-}
-
-void LBSP::calcDescImgDiff(const cv::Mat& oDesc1, const cv::Mat& oDesc2, cv::Mat& oOutput, bool bForceMergeChannels) {
- CV_DbgAssert(oDesc1.size()==oDesc2.size() && oDesc1.type()==oDesc2.type());
- CV_DbgAssert(DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(oDesc1.type()==CV_16UC1 || oDesc1.type()==CV_16UC3);
- CV_DbgAssert(CV_MAT_DEPTH(oDesc1.type())==CV_16U);
- CV_DbgAssert(DESC_SIZE*8<=UCHAR_MAX);
- CV_DbgAssert(oDesc1.step.p[0]==oDesc2.step.p[0] && oDesc1.step.p[1]==oDesc2.step.p[1]);
- const float fScaleFactor = (float)UCHAR_MAX/(DESC_SIZE*8);
- const size_t nChannels = CV_MAT_CN(oDesc1.type());
- const size_t _step_row = oDesc1.step.p[0];
- if(nChannels==1) {
- oOutput.create(oDesc1.size(),CV_8UC1);
- oOutput = cv::Scalar(0);
- for(int i=0; i<oDesc1.rows; ++i) {
- const size_t idx = _step_row*i;
- const ushort* const desc1_ptr = (ushort*)(oDesc1.data+idx);
- const ushort* const desc2_ptr = (ushort*)(oDesc2.data+idx);
- for(int j=0; j<oDesc1.cols; ++j)
- oOutput.at<uchar>(i,j) = (uchar)(fScaleFactor*hdist(desc1_ptr[j],desc2_ptr[j]));
- }
- }
- else { //nChannels==3
- if(bForceMergeChannels)
- oOutput.create(oDesc1.size(),CV_8UC1);
- else
- oOutput.create(oDesc1.size(),CV_8UC3);
- oOutput = cv::Scalar::all(0);
- for(int i=0; i<oDesc1.rows; ++i) {
- const size_t idx = _step_row*i;
- const ushort* const desc1_ptr = (ushort*)(oDesc1.data+idx);
- const ushort* const desc2_ptr = (ushort*)(oDesc2.data+idx);
- uchar* output_ptr = oOutput.data + oOutput.step.p[0]*i;
- for(int j=0; j<oDesc1.cols; ++j) {
- for(size_t n=0;n<3; ++n) {
- const size_t idx2 = 3*j+n;
- if(bForceMergeChannels)
- output_ptr[j] += (uchar)((fScaleFactor*hdist(desc1_ptr[idx2],desc2_ptr[idx2]))/3);
- else
- output_ptr[idx2] = (uchar)(fScaleFactor*hdist(desc1_ptr[idx2],desc2_ptr[idx2]));
- }
- }
- }
- }
-}
-
-void LBSP::validateKeyPoints(std::vector<cv::KeyPoint>& voKeypoints, cv::Size oImgSize) {
- cv::KeyPointsFilter::runByImageBorder(voKeypoints,oImgSize,PATCH_SIZE/2);
-}
-
-void LBSP::validateROI(cv::Mat& oROI) {
- CV_Assert(!oROI.empty() && oROI.type()==CV_8UC1);
- cv::Mat oROI_new(oROI.size(),CV_8UC1,cv::Scalar_<uchar>(0));
- const size_t nBorderSize = PATCH_SIZE/2;
- const cv::Rect nROI_inner(nBorderSize,nBorderSize,oROI.cols-nBorderSize*2,oROI.rows-nBorderSize*2);
- cv::Mat(oROI,nROI_inner).copyTo(cv::Mat(oROI_new,nROI_inner));
- oROI = oROI_new;
-}
diff --git a/package_bgs/pl/LBSP.h b/package_bgs/pl/LBSP.h
deleted file mode 100644
index 1ca17a0..0000000
--- a/package_bgs/pl/LBSP.h
+++ /dev/null
@@ -1,118 +0,0 @@
-#pragma once
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/features2d/features2d.hpp>
-#include "DistanceUtils.h"
-
-/*!
- Local Binary Similarity Pattern (LBSP) feature extractor
-
- Note 1: both grayscale and RGB/BGR images may be used with this extractor.
- Note 2: using LBSP::compute2(...) is logically equivalent to using LBSP::compute(...) followed by LBSP::reshapeDesc(...).
-
- For more details on the different parameters, see G.-A. Bilodeau et al, "Change Detection in Feature Space Using Local
- Binary Similarity Patterns", in CRV 2013.
-
- This algorithm is currently NOT thread-safe.
- */
-class LBSP : public cv::DescriptorExtractor {
-public:
- //! constructor 1, threshold = absolute intensity 'similarity' threshold used when computing comparisons
- LBSP(size_t nThreshold);
- //! constructor 2, threshold = relative intensity 'similarity' threshold used when computing comparisons
- LBSP(float fRelThreshold, size_t nThresholdOffset=0);
- //! default destructor
- virtual ~LBSP();
- //! loads extractor params from the specified file node @@@@ not impl
- virtual void read(const cv::FileNode&);
- //! writes extractor params to the specified file storage @@@@ not impl
- virtual void write(cv::FileStorage&) const;
- //! sets the 'reference' image to be used for inter-frame comparisons (note: if no image is set or if the image is empty, the algorithm will default back to intra-frame comparisons)
- virtual void setReference(const cv::Mat&);
- //! returns the current descriptor size, in bytes
- virtual int descriptorSize() const;
- //! returns the current descriptor data type
- virtual int descriptorType() const;
- //! returns whether this extractor is using a relative threshold or not
- virtual bool isUsingRelThreshold() const;
- //! returns the current relative threshold used for comparisons (-1 = invalid/not used)
- virtual float getRelThreshold() const;
- //! returns the current absolute threshold used for comparisons (-1 = invalid/not used)
- virtual size_t getAbsThreshold() const;
-
- //! similar to DescriptorExtractor::compute(const cv::Mat& image, ...), but in this case, the descriptors matrix has the same shape as the input matrix (possibly slower, but the result can be displayed)
- void compute2(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const;
- //! batch version of LBSP::compute2(const cv::Mat& image, ...), also similar to DescriptorExtractor::compute(const std::vector<cv::Mat>& imageCollection, ...)
- void compute2(const std::vector<cv::Mat>& voImageCollection, std::vector<std::vector<cv::KeyPoint> >& vvoPointCollection, std::vector<cv::Mat>& voDescCollection) const;
-
- //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (1-channel version)
- inline static void computeGrayscaleDescriptor(const cv::Mat& oInputImg, const uchar _ref, const int _x, const int _y, const size_t _t, ushort& _res) {
- CV_DbgAssert(!oInputImg.empty());
- CV_DbgAssert(oInputImg.type()==CV_8UC1);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(_x>=(int)LBSP::PATCH_SIZE/2 && _y>=(int)LBSP::PATCH_SIZE/2);
- CV_DbgAssert(_x<oInputImg.cols-(int)LBSP::PATCH_SIZE/2 && _y<oInputImg.rows-(int)LBSP::PATCH_SIZE/2);
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* const _data = oInputImg.data;
- #include "LBSP_16bits_dbcross_1ch.i"
- }
-
- //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (3-channels version)
- inline static void computeRGBDescriptor(const cv::Mat& oInputImg, const uchar* const _ref, const int _x, const int _y, const size_t* const _t, ushort* _res) {
- CV_DbgAssert(!oInputImg.empty());
- CV_DbgAssert(oInputImg.type()==CV_8UC3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(_x>=(int)LBSP::PATCH_SIZE/2 && _y>=(int)LBSP::PATCH_SIZE/2);
- CV_DbgAssert(_x<oInputImg.cols-(int)LBSP::PATCH_SIZE/2 && _y<oInputImg.rows-(int)LBSP::PATCH_SIZE/2);
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* const _data = oInputImg.data;
- #include "LBSP_16bits_dbcross_3ch3t.i"
- }
-
- //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (3-channels version)
- inline static void computeRGBDescriptor(const cv::Mat& oInputImg, const uchar* const _ref, const int _x, const int _y, const size_t _t, ushort* _res) {
- CV_DbgAssert(!oInputImg.empty());
- CV_DbgAssert(oInputImg.type()==CV_8UC3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(_x>=(int)LBSP::PATCH_SIZE/2 && _y>=(int)LBSP::PATCH_SIZE/2);
- CV_DbgAssert(_x<oInputImg.cols-(int)LBSP::PATCH_SIZE/2 && _y<oInputImg.rows-(int)LBSP::PATCH_SIZE/2);
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* const _data = oInputImg.data;
- #include "LBSP_16bits_dbcross_3ch1t.i"
- }
-
- //! utility function, shortcut/lightweight/direct single-point LBSP computation function for extra flexibility (1-channel-RGB version)
- inline static void computeSingleRGBDescriptor(const cv::Mat& oInputImg, const uchar _ref, const int _x, const int _y, const size_t _c, const size_t _t, ushort& _res) {
- CV_DbgAssert(!oInputImg.empty());
- CV_DbgAssert(oInputImg.type()==CV_8UC3 && _c<3);
- CV_DbgAssert(LBSP::DESC_SIZE==2); // @@@ also relies on a constant desc size
- CV_DbgAssert(_x>=(int)LBSP::PATCH_SIZE/2 && _y>=(int)LBSP::PATCH_SIZE/2);
- CV_DbgAssert(_x<oInputImg.cols-(int)LBSP::PATCH_SIZE/2 && _y<oInputImg.rows-(int)LBSP::PATCH_SIZE/2);
- const size_t _step_row = oInputImg.step.p[0];
- const uchar* const _data = oInputImg.data;
- #include "LBSP_16bits_dbcross_s3ch.i"
- }
-
- //! utility function, used to reshape a descriptors matrix to its input image size via their keypoint locations
- static void reshapeDesc(cv::Size oSize, const std::vector<cv::KeyPoint>& voKeypoints, const cv::Mat& oDescriptors, cv::Mat& oOutput);
- //! utility function, used to illustrate the difference between two descriptor images
- static void calcDescImgDiff(const cv::Mat& oDesc1, const cv::Mat& oDesc2, cv::Mat& oOutput, bool bForceMergeChannels=false);
- //! utility function, used to filter out bad keypoints that would trigger out of bounds error because they're too close to the image border
- static void validateKeyPoints(std::vector<cv::KeyPoint>& voKeypoints, cv::Size oImgSize);
- //! utility function, used to filter out bad pixels in a ROI that would trigger out of bounds error because they're too close to the image border
- static void validateROI(cv::Mat& oROI);
- //! utility, specifies the pixel size of the pattern used (width and height)
- static const size_t PATCH_SIZE = 5;
- //! utility, specifies the number of bytes per descriptor (should be the same as calling 'descriptorSize()')
- static const size_t DESC_SIZE = 2;
-
-protected:
- //! classic 'compute' implementation, based on the regular DescriptorExtractor::computeImpl arguments & expected output
- virtual void computeImpl(const cv::Mat& oImage, std::vector<cv::KeyPoint>& voKeypoints, cv::Mat& oDescriptors) const;
-
- const bool m_bOnlyUsingAbsThreshold;
- const float m_fRelThreshold;
- const size_t m_nThreshold;
- cv::Mat m_oRefImage;
-};
diff --git a/package_bgs/pl/LOBSTER.cpp b/package_bgs/pl/LOBSTER.cpp
deleted file mode 100644
index f4e9bf6..0000000
--- a/package_bgs/pl/LOBSTER.cpp
+++ /dev/null
@@ -1,75 +0,0 @@
-#include "LOBSTER.h"
-#include "BackgroundSubtractorLOBSTER.h"
-
-
-LOBSTERBGS::LOBSTERBGS() :
-pLOBSTER(0), firstTime(true), showOutput(true),
-fRelLBSPThreshold (BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD),
-nLBSPThresholdOffset (BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD),
-nDescDistThreshold (BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD),
-nColorDistThreshold (BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD),
-nBGSamples (BGSLOBSTER_DEFAULT_NB_BG_SAMPLES),
-nRequiredBGSamples (BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES)
-{
-}
-
-LOBSTERBGS::~LOBSTERBGS() {
- if (pLOBSTER)
- delete pLOBSTER;
-}
-
-void LOBSTERBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
-{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if (firstTime) {
- saveConfig();
- pLOBSTER = new BackgroundSubtractorLOBSTER(
- fRelLBSPThreshold, nLBSPThresholdOffset, nDescDistThreshold,
- nColorDistThreshold, nBGSamples, nRequiredBGSamples);
-
- pLOBSTER->initialize(img_input, cv::Mat (img_input.size(), CV_8UC1, cv::Scalar_<uchar>(255)));
- firstTime = false;
- }
-
- (*pLOBSTER)(img_input, img_output);
- pLOBSTER->getBackgroundImage(img_bgmodel);
-
- if(showOutput) {
- imshow("LOBSTER FG", img_output);
- imshow("LOBSTER BG", img_bgmodel);
- }
-}
-
-void LOBSTERBGS::saveConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/LOBSTERBGS.xml", 0, CV_STORAGE_WRITE);
-
- cvWriteReal(fs, "fRelLBSPThreshold", fRelLBSPThreshold);
- cvWriteInt(fs, "nLBSPThresholdOffset", nLBSPThresholdOffset);
- cvWriteInt(fs, "nDescDistThreshold", nDescDistThreshold);
- cvWriteInt(fs, "nColorDistThreshold", nColorDistThreshold);
- cvWriteInt(fs, "nBGSamples", nBGSamples);
- cvWriteInt(fs, "nRequiredBGSamples", nRequiredBGSamples);
- cvWriteInt(fs, "showOutput", showOutput);
-
- cvReleaseFileStorage(&fs);
-}
-
-void LOBSTERBGS::loadConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/LOBSTERBGS.xml", 0, CV_STORAGE_READ);
-
- fRelLBSPThreshold = cvReadRealByName(fs, 0, "fRelLBSPThreshold", BGSLOBSTER_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD);
- nLBSPThresholdOffset = cvReadIntByName(fs, 0, "nLBSPThresholdOffset", BGSLOBSTER_DEFAULT_LBSP_OFFSET_SIMILARITY_THRESHOLD);
- nDescDistThreshold = cvReadIntByName(fs, 0, "nDescDistThreshold", BGSLOBSTER_DEFAULT_DESC_DIST_THRESHOLD);
- nColorDistThreshold = cvReadIntByName(fs, 0, "nColorDistThreshold", BGSLOBSTER_DEFAULT_COLOR_DIST_THRESHOLD);
- nBGSamples = cvReadIntByName(fs, 0, "nBGSamples", BGSLOBSTER_DEFAULT_NB_BG_SAMPLES);
- nRequiredBGSamples = cvReadIntByName(fs, 0, "nRequiredBGSamples", BGSLOBSTER_DEFAULT_REQUIRED_NB_BG_SAMPLES);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
- cvReleaseFileStorage(&fs);
-}
diff --git a/package_bgs/pl/LOBSTER.h b/package_bgs/pl/LOBSTER.h
deleted file mode 100644
index f5954ca..0000000
--- a/package_bgs/pl/LOBSTER.h
+++ /dev/null
@@ -1,33 +0,0 @@
-#pragma once
-
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-
-class BackgroundSubtractorLOBSTER;
-
-class LOBSTERBGS : public IBGS
-{
-private:
- BackgroundSubtractorLOBSTER* pLOBSTER;
- bool firstTime;
- bool showOutput;
-
- float fRelLBSPThreshold;
- size_t nLBSPThresholdOffset;
- size_t nDescDistThreshold;
- size_t nColorDistThreshold;
- size_t nBGSamples;
- size_t nRequiredBGSamples;
-
-public:
- LOBSTERBGS();
- ~LOBSTERBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/pl/RandUtils.h b/package_bgs/pl/RandUtils.h
deleted file mode 100644
index 24ca5f6..0000000
--- a/package_bgs/pl/RandUtils.h
+++ /dev/null
@@ -1,96 +0,0 @@
-#pragma once
-
-/*// gaussian 3x3 pattern, based on 'floor(fspecial('gaussian', 3, 1)*256)'
-static const int s_nSamplesInitPatternWidth = 3;
-static const int s_nSamplesInitPatternHeight = 3;
-static const int s_nSamplesInitPatternTot = 256;
-static const int s_anSamplesInitPattern[s_nSamplesInitPatternHeight][s_nSamplesInitPatternWidth] = {
- {19, 32, 19,},
- {32, 52, 32,},
- {19, 32, 19,},
-};*/
-
-// gaussian 7x7 pattern, based on 'floor(fspecial('gaussian',7,2)*512)'
-static const int s_nSamplesInitPatternWidth = 7;
-static const int s_nSamplesInitPatternHeight = 7;
-static const int s_nSamplesInitPatternTot = 512;
-static const int s_anSamplesInitPattern[s_nSamplesInitPatternHeight][s_nSamplesInitPatternWidth] = {
- {2, 4, 6, 7, 6, 4, 2,},
- {4, 8, 12, 14, 12, 8, 4,},
- {6, 12, 21, 25, 21, 12, 6,},
- {7, 14, 25, 28, 25, 14, 7,},
- {6, 12, 21, 25, 21, 12, 6,},
- {4, 8, 12, 14, 12, 8, 4,},
- {2, 4, 6, 7, 6, 4, 2,},
-};
-
-//! returns a random init/sampling position for the specified pixel position; also guards against out-of-bounds values via image/border size check.
-static inline void getRandSamplePosition(int& x_sample, int& y_sample, const int x_orig, const int y_orig, const int border, const cv::Size& imgsize) {
- int r = 1+rand()%s_nSamplesInitPatternTot;
- for(x_sample=0; x_sample<s_nSamplesInitPatternWidth; ++x_sample) {
- for(y_sample=0; y_sample<s_nSamplesInitPatternHeight; ++y_sample) {
- r -= s_anSamplesInitPattern[y_sample][x_sample];
- if(r<=0)
- goto stop;
- }
- }
- stop:
- x_sample += x_orig-s_nSamplesInitPatternWidth/2;
- y_sample += y_orig-s_nSamplesInitPatternHeight/2;
- if(x_sample<border)
- x_sample = border;
- else if(x_sample>=imgsize.width-border)
- x_sample = imgsize.width-border-1;
- if(y_sample<border)
- y_sample = border;
- else if(y_sample>=imgsize.height-border)
- y_sample = imgsize.height-border-1;
-}
-
-// simple 8-connected (3x3) neighbors pattern
-static const int s_anNeighborPatternSize_3x3 = 8;
-static const int s_anNeighborPattern_3x3[8][2] = {
- {-1, 1}, { 0, 1}, { 1, 1},
- {-1, 0}, { 1, 0},
- {-1,-1}, { 0,-1}, { 1,-1},
-};
-
-//! returns a random neighbor position for the specified pixel position; also guards against out-of-bounds values via image/border size check.
-static inline void getRandNeighborPosition_3x3(int& x_neighbor, int& y_neighbor, const int x_orig, const int y_orig, const int border, const cv::Size& imgsize) {
- int r = rand()%s_anNeighborPatternSize_3x3;
- x_neighbor = x_orig+s_anNeighborPattern_3x3[r][0];
- y_neighbor = y_orig+s_anNeighborPattern_3x3[r][1];
- if(x_neighbor<border)
- x_neighbor = border;
- else if(x_neighbor>=imgsize.width-border)
- x_neighbor = imgsize.width-border-1;
- if(y_neighbor<border)
- y_neighbor = border;
- else if(y_neighbor>=imgsize.height-border)
- y_neighbor = imgsize.height-border-1;
-}
-
-// 5x5 neighbors pattern
-static const int s_anNeighborPatternSize_5x5 = 24;
-static const int s_anNeighborPattern_5x5[24][2] = {
- {-2, 2}, {-1, 2}, { 0, 2}, { 1, 2}, { 2, 2},
- {-2, 1}, {-1, 1}, { 0, 1}, { 1, 1}, { 2, 1},
- {-2, 0}, {-1, 0}, { 1, 0}, { 2, 0},
- {-2,-1}, {-1,-1}, { 0,-1}, { 1,-1}, { 2,-1},
- {-2,-2}, {-1,-2}, { 0,-2}, { 1,-2}, { 2,-2},
-};
-
-//! returns a random neighbor position for the specified pixel position; also guards against out-of-bounds values via image/border size check.
-static inline void getRandNeighborPosition_5x5(int& x_neighbor, int& y_neighbor, const int x_orig, const int y_orig, const int border, const cv::Size& imgsize) {
- int r = rand()%s_anNeighborPatternSize_5x5;
- x_neighbor = x_orig+s_anNeighborPattern_5x5[r][0];
- y_neighbor = y_orig+s_anNeighborPattern_5x5[r][1];
- if(x_neighbor<border)
- x_neighbor = border;
- else if(x_neighbor>=imgsize.width-border)
- x_neighbor = imgsize.width-border-1;
- if(y_neighbor<border)
- y_neighbor = border;
- else if(y_neighbor>=imgsize.height-border)
- y_neighbor = imgsize.height-border-1;
-}
diff --git a/package_bgs/pl/SuBSENSE.cpp b/package_bgs/pl/SuBSENSE.cpp
deleted file mode 100644
index a4aab0c..0000000
--- a/package_bgs/pl/SuBSENSE.cpp
+++ /dev/null
@@ -1,75 +0,0 @@
-#include "SuBSENSE.h"
-#include "BackgroundSubtractorSuBSENSE.h"
-
-
-SuBSENSEBGS::SuBSENSEBGS() :
-pSubsense(0), firstTime(true), showOutput(true),
-fRelLBSPThreshold (BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD),
-nDescDistThresholdOffset (BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET),
-nMinColorDistThreshold (BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD),
-nBGSamples (BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES),
-nRequiredBGSamples (BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES),
-nSamplesForMovingAvgs (BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS)
-{
-}
-
-SuBSENSEBGS::~SuBSENSEBGS() {
- if (pSubsense)
- delete pSubsense;
-}
-
-void SuBSENSEBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
-{
- if(img_input.empty())
- return;
-
- loadConfig();
-
- if (firstTime) {
- saveConfig();
- pSubsense = new BackgroundSubtractorSuBSENSE(
- fRelLBSPThreshold, nDescDistThresholdOffset, nMinColorDistThreshold,
- nBGSamples, nRequiredBGSamples, nSamplesForMovingAvgs);
-
- pSubsense->initialize(img_input, cv::Mat (img_input.size(), CV_8UC1, cv::Scalar_<uchar>(255)));
- firstTime = false;
- }
-
- (*pSubsense)(img_input, img_output);
- pSubsense->getBackgroundImage(img_bgmodel);
-
- if(showOutput) {
- imshow("SuBSENSE FG", img_output);
- imshow("SuBSENSE BG", img_bgmodel);
- }
-}
-
-void SuBSENSEBGS::saveConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/SuBSENSEBGS.xml", 0, CV_STORAGE_WRITE);
-
- cvWriteReal(fs, "fRelLBSPThreshold", fRelLBSPThreshold);
- cvWriteInt(fs, "nDescDistThresholdOffset", nDescDistThresholdOffset);
- cvWriteInt(fs, "nMinColorDistThreshold", nMinColorDistThreshold);
- cvWriteInt(fs, "nBGSamples", nBGSamples);
- cvWriteInt(fs, "nRequiredBGSamples", nRequiredBGSamples);
- cvWriteInt(fs, "nSamplesForMovingAvgs", nSamplesForMovingAvgs);
- cvWriteInt(fs, "showOutput", showOutput);
-
- cvReleaseFileStorage(&fs);
-}
-
-void SuBSENSEBGS::loadConfig()
-{
- CvFileStorage* fs = cvOpenFileStorage("./config/SuBSENSEBGS.xml", 0, CV_STORAGE_READ);
-
- fRelLBSPThreshold = cvReadRealByName(fs, 0, "fRelLBSPThreshold", BGSSUBSENSE_DEFAULT_LBSP_REL_SIMILARITY_THRESHOLD);
- nDescDistThresholdOffset = cvReadIntByName(fs, 0, "nDescDistThresholdOffset", BGSSUBSENSE_DEFAULT_DESC_DIST_THRESHOLD_OFFSET);
- nMinColorDistThreshold = cvReadIntByName(fs, 0, "nMinColorDistThreshold", BGSSUBSENSE_DEFAULT_MIN_COLOR_DIST_THRESHOLD);
- nBGSamples = cvReadIntByName(fs, 0, "nBGSamples", BGSSUBSENSE_DEFAULT_NB_BG_SAMPLES);
- nRequiredBGSamples = cvReadIntByName(fs, 0, "nRequiredBGSamples", BGSSUBSENSE_DEFAULT_REQUIRED_NB_BG_SAMPLES);
- nSamplesForMovingAvgs = cvReadIntByName(fs, 0, "nSamplesForMovingAvgs", BGSSUBSENSE_DEFAULT_N_SAMPLES_FOR_MV_AVGS);
- showOutput = cvReadIntByName(fs, 0, "showOutput", true);
-
- cvReleaseFileStorage(&fs);
-}
diff --git a/package_bgs/pl/SuBSENSE.h b/package_bgs/pl/SuBSENSE.h
deleted file mode 100644
index b527c27..0000000
--- a/package_bgs/pl/SuBSENSE.h
+++ /dev/null
@@ -1,32 +0,0 @@
-#pragma once
-
-#include <opencv2/opencv.hpp>
-
-#include "../IBGS.h"
-
-class BackgroundSubtractorSuBSENSE;
-
-class SuBSENSEBGS: public IBGS {
-private:
- BackgroundSubtractorSuBSENSE* pSubsense;
- bool firstTime;
- bool showOutput;
-
- float fRelLBSPThreshold;
- size_t nDescDistThresholdOffset;
- size_t nMinColorDistThreshold;
- size_t nBGSamples;
- size_t nRequiredBGSamples;
- size_t nSamplesForMovingAvgs;
-
-public:
- SuBSENSEBGS();
- ~SuBSENSEBGS();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output,
- cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/sjn/SJN_MultiCueBGS.h b/package_bgs/sjn/SJN_MultiCueBGS.h
deleted file mode 100644
index 0891c08..0000000
--- a/package_bgs/sjn/SJN_MultiCueBGS.h
+++ /dev/null
@@ -1,248 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#define MIN3(x,y,z) ((y) <= (z) ? ((x) <= (y) ? (x) : (y)) : ((x) <= (z) ? (x) : (z)))
-#define MAX3(x,y,z) ((y) >= (z) ? ((x) >= (y) ? (x) : (y)) : ((x) >= (z) ? (x) : (z)))
-
-#ifndef PI
- #define PI 3.14159
-#endif
-
-typedef int BOOL;
-
-#ifndef FALSE
- #define FALSE 0
-#endif
-
-#ifndef TRUE
- #define TRUE 1
-#endif
-
-#if !defined(__APPLE__)
-#include <malloc.h>
-#endif
-#include "math.h"
-
-#include <vector>
-using std::vector;
-
-#include <algorithm>
-using std::sort;
-
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-
-//------------------------------------Structure Lists-------------------------------------//
-struct point{
- short m_nX;
- short m_nY;
-};
-
-struct neighbor_pos{
- short m_nX;
- short m_nY;
-};
-//1) Bounding Box Structure
-struct BoundingBoxInfo{
- int m_iBoundBoxNum; //# of bounding boxes for all foreground and false-positive blobs
- int m_iArraySize; //the size of the below arrays to store bounding box information
-
- short *m_aLeft, *m_aRight, *m_aUpper, *m_aBottom; //arrays to store bounding box information for (the original frame size)
- short *m_aRLeft, *m_aRRight, *m_aRUpper, *m_aRBottom; //arrays to store bounding box information for (the reduced frame size)
- BOOL* m_ValidBox; //If this value is true, the corresponding bounding box is for a foreground blob.
- //Else, it is for a false-positive blob
-};
-
-//2) Texture Model Structure
-struct TextureCodeword{
- int m_iMNRL; //the maximum negative run-length
- int m_iT_first_time; //the first access time
- int m_iT_last_time; //the last access time
-
- //��� MTLBP��
- float m_fLowThre; //a low threshold for the matching
- float m_fHighThre; //a high threshold for the matching
- float m_fMean; //mean of the codeword
-};
-
-struct TextureModel{
- TextureCodeword** m_Codewords; //the texture-codeword Array
-
- int m_iTotal; //# of learned samples after the last clear process
- int m_iElementArraySize; //the array size of m_Codewords
- int m_iNumEntries; //# of codewords
-
- BOOL m_bID; //id=1 --> background model, id=0 --> cachebook
-};
-
-//3) Color Model Structure
-struct ColorCodeword{
- int m_iMNRL; //the maximum negative run-length
- int m_iT_first_time; //the first access time
- int m_iT_last_time; //the last access time
-
- double m_dMean[3]; //mean vector of the codeword
-
-};
-
-struct ColorModel{
- ColorCodeword** m_Codewords; //the color-codeword Array
-
- int m_iTotal; //# of learned samples after the last clear process
- int m_iElementArraySize; //the array size of m_Codewords
- int m_iNumEntries; //# of codewords
-
- BOOL m_bID; //id=1 --> background model, id=0 --> cachebookk
-};
-
-
-class SJN_MultiCueBGS : public IBGS
-{
-private:
- bool firstTime;
- bool showOutput;
- void saveConfig();
- void loadConfig();
-
-public:
- SJN_MultiCueBGS();
- ~SJN_MultiCueBGS(void);
-
-public:
- //----------------------------------------------------
- // APIs and User-Adjustable Parameters
- //----------------------------------------------------
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel); //the main function to background modeling and subtraction
-
- void GetForegroundMap(IplImage* return_image, IplImage* input_frame=NULL); //the function returning a foreground binary-map
- void Destroy(); //the function to release allocated memories
-
- int g_iTrainingPeriod; //the training period (The parameter t in the paper)
- int g_iT_ModelThreshold; //the threshold for texture-model based BGS. (The parameter tau_T in the paper)
- int g_iC_ModelThreshold; //the threshold for appearance based verification. (The parameter tau_A in the paper)
-
- float g_fLearningRate; //the learning rate for background models. (The parameter alpha in the paper)
-
- short g_nTextureTrainVolRange; //the codebook size factor for texture models. (The parameter k in the paper)
- short g_nColorTrainVolRange; //the codebook size factor for color models. (The parameter eta_1 in the paper)
-
-public:
- //----------------------------------------------------
- // Implemented Function Lists
- //----------------------------------------------------
-
- //--1) General Functions
- void Initialize(IplImage* frame);
-
- void PreProcessing(IplImage* frame);
- void ReduceImageSize(IplImage* SrcImage, IplImage* DstImage);
- void GaussianFiltering(IplImage* frame, uchar*** aFilteredFrame);
- void BGR2HSVxyz_Par(uchar*** aBGR, uchar*** aXYZ);
-
- void BackgroundModeling_Par(IplImage* frame);
- void ForegroundExtraction(IplImage* frame);
- void CreateLandmarkArray_Par(float fConfThre, short nTrainVolRange, float**aConfMap, int iNehborNum, uchar*** aXYZ,
- point*** aNeiDir, TextureModel**** TModel, ColorModel*** CModel, uchar**aLandmarkArr);
-
- void PostProcessing(IplImage* frame);
- void MorphologicalOpearions(uchar** aInput, uchar** aOutput, double dThresholdRatio, int iMaskSize, int iWidth, int iHeight);
- void Labeling(uchar** aBinaryArray, int* pLabelCount, int** aLabelTable);
- void SetBoundingBox(int iLabelCount, int** aLabelTable);
- void BoundBoxVerification(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo);
- void EvaluateBoxSize( BoundingBoxInfo* BoundBoxInfo);
- void EvaluateOverlapRegionSize(BoundingBoxInfo* SrcBoxInfo);
- void EvaluateGhostRegion(IplImage* frame, uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo);
- double CalculateHausdorffDist(IplImage* input_image, IplImage* model_image);
- void RemovingInvalidForeRegions(uchar** aResForeMap, BoundingBoxInfo* BoundBoxInfo);
-
- void UpdateModel_Par();
- void GetEnlargedMap(float** aOriginMap, float** aEnlargedMap);
-
- //--2) Texture Model Related Functions
- void T_AllocateTextureModelRelatedMemory();
- void T_ReleaseTextureModelRelatedMemory();
- void T_SetNeighborDirection(point*** aNeighborPos);
- void T_ModelConstruction(short nTrainVolRange,float fLearningRate, uchar*** aXYZ,point center, point* aNei, TextureModel** aModel);
- void T_ClearNonEssentialEntries(short nClearNum, TextureModel** aModel);
- void T_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short* nReferredIdxArr, short nClearNum, TextureModel** pCachebook);
- void T_GetConfidenceMap_Par(uchar*** aXYZ, float** aTextureMap, point*** aNeiDirArr, TextureModel**** aModel);
- void T_Absorption(int iAbsorbCnt, point pos, short*** aContinuCnt, short*** aRefferedIndex, TextureModel** pModel, TextureModel** pCache);
-
- //--3) Color Model Related Functions
- void C_AllocateColorModelRelatedMemory();
- void C_ReleaseColorModelRelatedMemory();
- void C_CodebookConstruction(uchar* aP,int iPosX, int iPosY, short nTrainVolRange, float fLearningRate, ColorModel* pC);
- void C_ClearNonEssentialEntries(short nClearNum, ColorModel* pModel);
- void C_ClearNonEssentialEntriesForCachebook(uchar bLandmark, short nReferredIdx, short nClearNum, ColorModel* pCachebook);
- void C_Absorption(int iAbsorbCnt, point pos , short** aContinuCnt, short** aRefferedIndex, ColorModel* pModel, ColorModel* pCache);
-public:
- //----------------------------------------------------
- // Implemented Variable Lists
- //----------------------------------------------------
-
- //--1) General Variables
- int g_iFrameCount; //the counter of processed frames
-
- int g_iBackClearPeriod; //the period to clear background models
- int g_iCacheClearPeriod; //the period to clear cache-book models
-
- int g_iAbsortionPeriod; //the period to absorb static ghost regions
- BOOL g_bAbsorptionEnable; //If True, procedures for ghost region absorption are activated.
-
- BOOL g_bModelMemAllocated; //To handle memory..
- BOOL g_bNonModelMemAllocated; //To handle memory..
-
- float g_fConfidenceThre; //the final decision threshold
-
- int g_iWidth, g_iHeight; //width and height of input frames
- int g_iRWidth, g_iRHeight; //width and height of reduced frames (For efficiency, the reduced size of frames are processed)
- int g_iForegroundNum; //# of detected foreground regions
- BOOL g_bForegroundMapEnable; //TRUE only when BGS is successful
-
- IplImage* g_ResizedFrame; //reduced size of frame (For efficiency, the reduced size of frames are processed)
- uchar*** g_aGaussFilteredFrame;
- uchar*** g_aXYZFrame;
- uchar** g_aLandmarkArray; //the landmark map
- uchar** g_aResizedForeMap; //the resized foreground map
- uchar** g_aForegroundMap; //the final foreground map
- BOOL** g_aUpdateMap; //the location map of update candidate pixels
-
- BoundingBoxInfo* g_BoundBoxInfo; //the array of bounding boxes of each foreground blob
-
- //--2) Texture Model Related
- TextureModel**** g_TextureModel; //the texture background model
- TextureModel**** g_TCacheBook; //the texture cache-book
- short*** g_aTReferredIndex; //To handle cache-book
- short*** g_aTContinuousCnt; //To handle cache-book
- point*** g_aNeighborDirection;
- float**g_aTextureConfMap; //the texture confidence map
-
- short g_nNeighborNum; //# of neighborhoods
- short g_nRadius;
- short g_nBoundarySize;
-
- //--3) Texture Model Related
- ColorModel*** g_ColorModel; //the color background model
- ColorModel*** g_CCacheBook; //the color cache-book
- short** g_aCReferredIndex; //To handle cache-book
- short** g_aCContinuousCnt; //To handle cache-book
-};
-
-
diff --git a/package_bgs/tb/FuzzyChoquetIntegral.h b/package_bgs/tb/FuzzyChoquetIntegral.h
deleted file mode 100644
index 76ba158..0000000
--- a/package_bgs/tb/FuzzyChoquetIntegral.h
+++ /dev/null
@@ -1,55 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-
-#include "FuzzyUtils.h"
-
-class FuzzyChoquetIntegral : public IBGS
-{
-private:
- bool firstTime;
- long frameNumber;
- bool showOutput;
-
- int framesToLearn;
- double alphaLearn;
- double alphaUpdate;
- int colorSpace;
- int option;
- bool smooth;
- double threshold;
-
- FuzzyUtils fu;
- cv::Mat img_background_f3;
-
-public:
- FuzzyChoquetIntegral();
- ~FuzzyChoquetIntegral();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
diff --git a/package_bgs/tb/FuzzySugenoIntegral.h b/package_bgs/tb/FuzzySugenoIntegral.h
deleted file mode 100644
index cfa91b7..0000000
--- a/package_bgs/tb/FuzzySugenoIntegral.h
+++ /dev/null
@@ -1,55 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-
-#include "FuzzyUtils.h"
-
-class FuzzySugenoIntegral : public IBGS
-{
-private:
- bool firstTime;
- long long frameNumber;
- bool showOutput;
-
- int framesToLearn;
- double alphaLearn;
- double alphaUpdate;
- int colorSpace;
- int option;
- bool smooth;
- double threshold;
-
- FuzzyUtils fu;
- cv::Mat img_background_f3;
-
-public:
- FuzzySugenoIntegral();
- ~FuzzySugenoIntegral();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
-
diff --git a/package_bgs/tb/FuzzyUtils.cpp b/package_bgs/tb/FuzzyUtils.cpp
deleted file mode 100644
index fcb1972..0000000
--- a/package_bgs/tb/FuzzyUtils.cpp
+++ /dev/null
@@ -1,512 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#include "FuzzyUtils.h"
-
-FuzzyUtils::FuzzyUtils(void){}
-
-FuzzyUtils::~FuzzyUtils(void){}
-
-void FuzzyUtils::LBP(IplImage* InputImage, IplImage* LBPimage)
-{
- PixelUtils p;
-
- float* neighberPixel = (float*) malloc(9*sizeof(float));
- float* BinaryValue = (float*) malloc(9*sizeof(float));
- float* CarreExp = (float*) malloc(9*sizeof(float));
- float* valLBP = (float*) malloc(1*sizeof(float));
-
- *valLBP = 0;
-
- int x = 0, y = 0;
-
- // on implemente les 8 valeurs puissance de 2 qui correspondent aux 8 elem. d'image voisins au elem. d'image central
- *(CarreExp+0)=1.0;
- *(CarreExp+1)=2.0;
- *(CarreExp+2)=4.0;
- *(CarreExp+3)=8.0;
- *(CarreExp+4)=0.0;
- *(CarreExp+5)=16.0;
- *(CarreExp+6)=32.0;
- *(CarreExp+7)=64.0;
- *(CarreExp+8)=128.0;
-
- //le calcule de LBP
- //pour les 4 coins
- /* 1.*/
- if(x==0 && y==0)
- {
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,4,0);
- *valLBP=*valLBP+((*(BinaryValue+1))*(*(CarreExp+1))+(*(BinaryValue+2))*(*(CarreExp+2))+(*(BinaryValue+3))*(*(CarreExp+3)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
-
- /* 2.*/
- if(x==0 && y==InputImage->width)
- {
- *valLBP=0;
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,4,1);
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp))+(*(BinaryValue+2))*(*(CarreExp+2))+(*(BinaryValue+3))*(*(CarreExp+3)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
-
- /* 3.*/
- if(x==InputImage->height && y==0)
- {
- *valLBP=0;
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,4,2);
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp))+(*(BinaryValue+1))*(*(CarreExp+1))+(*(BinaryValue+3))*(*(CarreExp+3)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
-
- /* 4.*/
- if(x==InputImage->height && y==InputImage->width)
- {
- *valLBP=0;
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,4,3);
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp))+(*(BinaryValue+1))*(*(CarreExp+1))+(*(BinaryValue+2))*(*(CarreExp+2)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
-
- //le calcul de LBP pour la premi�re ligne : L(0)
- if(x==0 && (y!=0 && y!=InputImage->width))
- {
- for(int y = 1; y < InputImage->width-1; y++)
- {
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,6,4);
- *valLBP=0;
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp))+(*(BinaryValue+1))*(*(CarreExp+1))+(*(BinaryValue+2))*(*(CarreExp+2))+(*(BinaryValue+3))*(*(CarreExp+3))+(*(BinaryValue+5))*(*(CarreExp+5)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
- }
-
- //le calcul de LBP pour la derni�re colonne : C(w)
- if((x!=0 && x!=InputImage->height) && y==InputImage->width)
- {
- for(int x = 1; x < InputImage->height-1; x++)
- {
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,6,4);
- *valLBP=0;
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp))+(*(BinaryValue+1))*(*(CarreExp+1))+(*(BinaryValue+2))*(*(CarreExp+2))+(*(BinaryValue+3))*(*(CarreExp+3))+(*(BinaryValue+5))*(*(CarreExp+5)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
- }
-
- //le calcul de LBP pour la derni�re ligne : L(h)
- if(x==InputImage->height && (y!=0 && y!=InputImage->width))
- {
- for(int y = 1; y < InputImage->width-1; y++)
- {
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,6,1);
- *valLBP=0;
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp))+(*(BinaryValue+2))*(*(CarreExp+2))+(*(BinaryValue+3))*(*(CarreExp+3))+(*(BinaryValue+4))*(*(CarreExp+4))+(*(BinaryValue+5))*(*(CarreExp+5)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
- }
-
- //le calcul de LBP pour la premi�re colonne : C(0)
- if((x!=0 && x!=InputImage->height) && y==0)
- {
- for(int x = 1; x <InputImage->height-1; x++)
- {
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,6,2);
- *valLBP=0;
- *valLBP=*valLBP+((*(BinaryValue))*(*(CarreExp+5))+(*(BinaryValue+1))*(*(CarreExp+6))+(*(BinaryValue+3))*(*(CarreExp+3))+(*(BinaryValue+4))*(*(CarreExp))+(*(BinaryValue+5))*(*(CarreExp+1)))/255.0;
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
- }
-
- //pour le reste des elements d'image
- for(int y = 1; y < InputImage->height-1; y++)
- {
- for(int x = 1; x < InputImage->width-1; x++)
- {
- p.getNeighberhoodGrayPixel(InputImage, x,y,neighberPixel);
- getBinValue(neighberPixel,BinaryValue,9,4);
- //le calcul de la valeur du LBP pour chaque elem. d'im.
- *valLBP=0;
- for(int l = 0; l < 9; l++)
- *valLBP = *valLBP + ((*(BinaryValue+l)) * (*(CarreExp+l))) / 255.0;
- //printf("\nvalLBP(%d,%d)=%f",x,y,*valLBP);
- p.PutGrayPixel(LBPimage,x,y,*valLBP);
- }
- }
-
- free(neighberPixel);
- free(BinaryValue);
- free(CarreExp);
- free(valLBP);
-}
-
-void FuzzyUtils::getBinValue(float* neighberGrayPixel, float* BinaryValue, int m, int n)
-{
- // la comparaison entre la valeur d'elem d'image central et les valeurs des elem. d'im. voisins
- // m = le numero des elements (4, 6 ou 9);
- // n = la position de l'element central;
-
- int h = 0;
- for(int k = 0; k < m; k++)
- {
- if(*(neighberGrayPixel+k) >= *(neighberGrayPixel+n))
- {
- *(BinaryValue+h)=1;
- h++;
- }
- else
- {
- *(BinaryValue+h)=0;
- h++;
- }
- }
-}
-
-void FuzzyUtils::SimilarityDegreesImage(IplImage* CurrentImage, IplImage* BGImage, IplImage* DeltaImage, int n, int color_space)
-{
- PixelUtils p;
- int i, j;
-
- if(n == 1)
- {
- float* CurrentGrayPixel = (float*) malloc (1*(sizeof(float)));
- float* BGGrayPixel = (float*) malloc (1*(sizeof(float)));
- float* DeltaGrayPixel = (float*) malloc (1*(sizeof(float)));
-
- for(i = 0; i < CurrentImage->width; i++)
- {
- for(j = 0; j < CurrentImage->height; j++)
- {
- p.GetGrayPixel(CurrentImage,i,j,CurrentGrayPixel);
- p.GetGrayPixel(BGImage,i,j,BGGrayPixel);
- RatioPixels(CurrentGrayPixel,BGGrayPixel,DeltaGrayPixel,1);
- p.PutGrayPixel(DeltaImage,i,j,*DeltaGrayPixel);
- }
- }
-
- free(CurrentGrayPixel);
- free(BGGrayPixel);
- free(DeltaGrayPixel);
- }
-
- if(n != 1)
- {
- IplImage* ConvertedCurrentImage = cvCreateImage(cvSize(CurrentImage->width, CurrentImage->height), IPL_DEPTH_32F, 3);
- IplImage* ConvertedBGImage = cvCreateImage(cvSize(CurrentImage->width, CurrentImage->height), IPL_DEPTH_32F, 3);
-
- float* ConvertedCurrentPixel = (float*) malloc(3*(sizeof(float)));
- float* ConvertedBGPixel = (float*) malloc(3*(sizeof(float)));
- float* DeltaConvertedPixel = (float*) malloc(3*(sizeof(float)));
-
- p.ColorConversion(CurrentImage,ConvertedCurrentImage,color_space);
- p.ColorConversion(BGImage,ConvertedBGImage,color_space);
-
- for(i = 0; i < CurrentImage->width; i++)
- {
- for(j = 0; j < CurrentImage->height; j++)
- {
- p.GetPixel(ConvertedCurrentImage,i,j,ConvertedCurrentPixel);
- p.GetPixel(ConvertedBGImage,i,j,ConvertedBGPixel);
- RatioPixels(ConvertedCurrentPixel,ConvertedBGPixel,DeltaConvertedPixel,3);
- p.PutPixel(DeltaImage,i,j,DeltaConvertedPixel);
- }
- }
-
- free(ConvertedCurrentPixel);
- free(ConvertedBGPixel);
- free(DeltaConvertedPixel);
-
- cvReleaseImage(&ConvertedCurrentImage);
- cvReleaseImage(&ConvertedBGImage);
- }
-}
-
-void FuzzyUtils::RatioPixels(float* CurrentPixel, float* BGPixel, float* DeltaPixel, int n)
-{
- if(n == 1)
- {
- if(*CurrentPixel < *BGPixel)
- *DeltaPixel = *CurrentPixel / *BGPixel;
-
- if(*CurrentPixel > *BGPixel)
- *DeltaPixel = *BGPixel / *CurrentPixel;
-
- if(*CurrentPixel == *BGPixel)
- *DeltaPixel = 1.0;
- }
-
- if(n == 3)
- for(int i = 0; i < 3; i++)
- {
- if(*(CurrentPixel+i) < *(BGPixel+i))
- *(DeltaPixel+i) = *(CurrentPixel+i) / *(BGPixel+i);
-
- if(*(CurrentPixel+i) > *(BGPixel+i))
- *(DeltaPixel+i) = *(BGPixel+i) / *(CurrentPixel+i);
-
- if(*(CurrentPixel+i) == *(BGPixel+i))
- *(DeltaPixel+i) = 1.0;
- }
-}
-
-void FuzzyUtils::getFuzzyIntegralSugeno(IplImage* H, IplImage* Delta, int n, float *MeasureG, IplImage* OutputImage)
-{
- // MeasureG : est un vecteur contenant 3 mesure g (g1,g2,g3) tel que : g1+g2+g3=1
- // n : =2 cad aggreger les 2 images "H" et "Delta"
- // =1 cad aggreger uniquement les valeurs des composantes couleurs de l'image "Delta"
-
- PixelUtils p;
-
- float* HTexturePixel = (float*) malloc(1*sizeof(float));
- float* DeltaOhtaPixel = (float*) malloc(3*(sizeof(float)));
- int *Indice = (int*) malloc(3*(sizeof(int)));
- float *HI = (float*) malloc(3*(sizeof(float)));
- float *Integral = (float*) malloc(3*(sizeof(float)));
- float* X = (float*) malloc(1*sizeof(float));
- float* XiXj = (float*) malloc(1*sizeof(float));
- float IntegralFlou;
-
- *Indice = 0;
- *(Indice+1) = 1;
- *(Indice+2) = 2;
- *X = 1.0;
-
- for(int i = 0; i < H->width; i++)
- {
- for(int j = 0; j < H->height; j++)
- {
- p.GetGrayPixel(H,i,j,HTexturePixel);
- p.GetPixel(Delta,i,j,DeltaOhtaPixel);
-
- *(HI+0) = *(HTexturePixel+0);
- *(HI+1) = *(DeltaOhtaPixel+0);
- *(HI+2) = *(DeltaOhtaPixel+1);
-
- Trier(HI,3,Indice);
-
- *XiXj = *(MeasureG + (*(Indice+1))) + (*(MeasureG + (*(Indice+2))));
-
- *(Integral+0) = min((HI + (*(Indice+0))), X);
- *(Integral+1) = min((HI + (*(Indice+1))), XiXj);
- *(Integral+2) = min((HI + (*(Indice+2))), ((MeasureG+(*(Indice+2)))));
-
- IntegralFlou = max(Integral,3);
- p.PutGrayPixel(OutputImage,i,j,IntegralFlou);
- }
- }
-
- free(HTexturePixel);
- free(DeltaOhtaPixel);
- free(Indice);
- free(HI);
- free(X);
- free(XiXj);
- free(Integral);
-}
-
-void FuzzyUtils::getFuzzyIntegralChoquet(IplImage* H, IplImage* Delta, int n, float *MeasureG, IplImage* OutputImage)
-{
- // MeasureG : est un vecteur contenant 3 mesure g (g1,g2,g3) tel que : g1+g2+g3=1
- // n : =2 cad aggreger les 2 images "H" et "Delta"
- // =1 cad aggreger uniquement les valeurs des composantes couleurs de l'image "Delta"
-
- PixelUtils p;
-
- float* HTexturePixel = (float*) malloc(1*sizeof(float));
- float* DeltaOhtaPixel = (float*) malloc(3*(sizeof(float)));
- int *Indice = (int*) malloc(3*(sizeof(int)));
- float *HI = (float*) malloc(3*(sizeof(float)));
- float *Integral = (float*) malloc(3*(sizeof(float)));
- float* X = (float*) malloc(1*sizeof(float));
- float* XiXj = (float*) malloc(1*sizeof(float));
- float IntegralFlou;
-
- *Indice = 0;
- *(Indice+1) = 1;
- *(Indice+2) = 2;
- *X = 1.0;
-
- for(int i = 0; i < Delta->width; i++)
- {
- for(int j = 0; j < Delta->height; j++)
- {
- if(n == 2)
- {
- p.GetGrayPixel(H,i,j,HTexturePixel);
- p.GetPixel(Delta,i,j,DeltaOhtaPixel);
-
- *(HI+0) = *(HTexturePixel+0);
- *(HI+1) = *(DeltaOhtaPixel+0);
- *(HI+2) = *(DeltaOhtaPixel+1);
- }
-
- if(n==1)
- {
- //remplir HI par les valeurs des 3 composantes couleurs uniquement
- p.GetPixel(Delta,i,j,DeltaOhtaPixel);
-
- *(HI+0) = *(DeltaOhtaPixel+0);
- //*(HI+0) = *(DeltaOhtaPixel+2);
- *(HI+1) = *(DeltaOhtaPixel+1);
- *(HI+2) = *(DeltaOhtaPixel+2);
- }
-
- Trier(HI,3,Indice);
- *XiXj = *(MeasureG + (*(Indice+1))) + (*(MeasureG + (*(Indice+2))));
-
- *(Integral+0) = *(HI+(*(Indice+0)))* (*X-*XiXj);
- *(Integral+1) = *(HI+(*(Indice+1)))* (*XiXj-*(MeasureG+(*(Indice+2))));
- *(Integral+2) = *(HI+(*(Indice+2)))* (*(MeasureG+(*(Indice+2))));
-
- IntegralFlou = *(Integral+0) + *(Integral+1) + *(Integral+2);
- p.PutGrayPixel(OutputImage,i,j,IntegralFlou);
- }
- }
-
- free(HTexturePixel);
- free(DeltaOhtaPixel);
- free(Indice);
- free(HI);
- free(X);
- free(XiXj);
- free(Integral);
-}
-
-void FuzzyUtils::FuzzyMeasureG(float g1, float g2, float g3, float *G)
-{
- *(G+0) = g1;
- *(G+1) = g2;
- *(G+2) = g3;
-}
-
-void FuzzyUtils::Trier(float* g,int n,int* index)
-{
- // Cette fonction trie un vecteur g par ordre croissant et
- // sort egalement l'indice des elements selon le trie dans le vecteur "index" suppos� initialis� par des valeurs de 1 a n
-
- float t;
- int r,a,b;
-
- for(a = 1; a <= n; a++)
- {
- for(b = n-1; b >= a; b--)
- if(*(g + b-1) < (*(g + b)))
- {
- // ordre croissant des �lements
- t = *(g + b-1);
- *(g + b-1) = *(g + b);
- *(g + b) = t;
-
- // ordre des indices des �lements du vecteur g
- r = *(index + b-1);
- *(index + b-1) = *(index + b);
- *(index + b) = r;
- }
- }
-}
-
-float FuzzyUtils::min(float *a,float *b)
-{
- float min = 0;
-
- if(*a >= (*b))
- min = *b;
- else
- min = *a;
-
- return min;
-}
-
-float FuzzyUtils::max(float* g , int n)
-{
- float max = 0;
-
- for(int i = 0; i < n; i++)
- {
- if(*(g+i) >= max)
- max = *(g+i);
- }
-
- return max;
-}
-
-void FuzzyUtils::gDeDeux(float* a, float* b, float* lambda)
-{
- float* c = (float*) malloc(1*sizeof(float));
- *c = *a + (*b) + (*lambda) * (*a) * (*b);
-}
-
-void FuzzyUtils::getLambda(float* g)
-{
- float a,b;
- float* lambda = (float*) malloc(1*sizeof(float));
-
- a = (*(g+0) * (*(g+1)) + (*(g+1)) * (*(g+2)) + (*(g+0)) * (*(g+2)));
- *lambda = -(*(g+0) * (*(g+1)) + (*(g+1)) * (*(g+2)) + (*(g+0)) * (*(g+2))) / (*(g+0) * (*(g+1)) * (*(g+2)));
- b = (*(g+0) * (*(g+1)) * (*(g+2)));
-
- //printf("\na:%f",a);
- //printf("\nb:%f",b);
- //printf("\nlambda:%f", *lambda);
-
- free(lambda);
-}
-
-void FuzzyUtils::AdaptativeSelectiveBackgroundModelUpdate(IplImage* CurrentImage, IplImage* BGImage, IplImage* OutputImage, IplImage* Integral, float seuil, float alpha)
-{
- PixelUtils p;
-
- float beta = 0.0;
- float* CurentImagePixel = (float*) malloc(3*sizeof(float));
- float* BGImagePixel = (float*) malloc(3*sizeof(float));
- float* OutputImagePixel = (float*) malloc(3*sizeof(float));
- float* IntegralImagePixel = (float*) malloc(1*sizeof(float));
- float *Maximum = (float*) malloc(1*sizeof(float));
- float *Minimum = (float*) malloc(1*sizeof(float));
-
- p.ForegroundMaximum(Integral, Maximum, 1);
- p.ForegroundMinimum(Integral, Minimum, 1);
-
- for(int i = 0; i < CurrentImage->width; i++)
- {
- for(int j = 0; j < CurrentImage->height; j++)
- {
- p.GetPixel(CurrentImage, i, j, CurentImagePixel);
- p.GetPixel(BGImage, i, j, BGImagePixel);
- p.GetGrayPixel(Integral, i, j, IntegralImagePixel);
-
- beta = 1 - ((*IntegralImagePixel) - ((*Minimum / (*Minimum - *Maximum)) * (*IntegralImagePixel) - (*Minimum * (*Maximum) / (*Minimum - *Maximum))));
-
- for(int k = 0; k < 3; k++)
- *(OutputImagePixel + k) = beta * (*(BGImagePixel + k)) + (1 - beta) * (alpha * (*(CurentImagePixel+k)) + (1-alpha) * (*(BGImagePixel+k)));
-
- p.PutPixel(OutputImage, i, j, OutputImagePixel);
- }
- }
-
- free(CurentImagePixel);
- free(BGImagePixel);
- free(OutputImagePixel);
- free(IntegralImagePixel);
- free(Maximum);
- free(Minimum);
-}
diff --git a/package_bgs/tb/PixelUtils.cpp b/package_bgs/tb/PixelUtils.cpp
deleted file mode 100644
index d647e05..0000000
--- a/package_bgs/tb/PixelUtils.cpp
+++ /dev/null
@@ -1,351 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#include "PixelUtils.h"
-
-PixelUtils::PixelUtils(void){}
-PixelUtils::~PixelUtils(void){}
-
-void PixelUtils::ColorConversion(IplImage* RGBImage, IplImage* ConvertedImage, int color_space)
-{
- // Space Color RGB - Nothing to do!
- if(color_space == 1)
- cvCopy(RGBImage, ConvertedImage);
-
- // Space Color Ohta
- if(color_space == 2)
- cvttoOTHA(RGBImage, ConvertedImage);
-
- // Space Color HSV - V Intensity - (H,S) Chromaticity
- if(color_space == 3)
- cvCvtColor(RGBImage, ConvertedImage, CV_BGR2HSV);
-
- // Space Color YCrCb - Y Intensity - (Cr,Cb) Chromaticity
- if(color_space == 4)
- cvCvtColor(RGBImage,ConvertedImage,CV_BGR2YCrCb);
-}
-
-void PixelUtils::cvttoOTHA(IplImage* RGBImage, IplImage* OthaImage)
-{
- float* OhtaPixel = (float*) malloc(3*(sizeof(float)));
- float* RGBPixel = (float*) malloc(3*(sizeof(float)));
-
- for(int i = 0; i < RGBImage->width; i++)
- {
- for(int j = 0;j < RGBImage->height; j++)
- {
- GetPixel(RGBImage, i, j, RGBPixel);
-
- // I1 = (R + G + B) / 3
- *OhtaPixel = (*(RGBPixel) + (*(RGBPixel + 1)) + (*(RGBPixel + 2))) / 3.0;
-
- // I2 = (R - B) / 2
- *(OhtaPixel+1) = (*RGBPixel - (*(RGBPixel + 2))) / 2.0;
-
- // I3 = (2G - R - B) / 4
- *(OhtaPixel+2) = (2 * (*(RGBPixel + 1)) - (*RGBPixel) - (*(RGBPixel + 2))) / 4.0;
-
- PutPixel(OthaImage, i, j, OhtaPixel);
- }
- }
-
- free(OhtaPixel);
- free(RGBPixel);
-}
-
-void PixelUtils::PostProcessing(IplImage *InputImage)
-{
- IplImage *ResultImage = cvCreateImage(cvSize(InputImage->width, InputImage->height), IPL_DEPTH_32F, 3);
-
- cvErode(InputImage, ResultImage, NULL, 1);
- cvDilate(ResultImage, InputImage, NULL, 0);
-
- cvReleaseImage(&ResultImage);
-}
-
-void PixelUtils::GetPixel(IplImage *image, int m, int n, unsigned char *pixelcourant)
-{
- for(int k = 0; k < 3; k++)
- pixelcourant[k] = ((unsigned char*)(image->imageData + image->widthStep*n))[m*3 + k];
-}
-
-void PixelUtils::GetGrayPixel(IplImage *image, int m, int n, unsigned char *pixelcourant)
-{
- *pixelcourant = ((unsigned char*)(image->imageData + image->widthStep*n))[m];
-}
-
-void PixelUtils::PutPixel(IplImage *image,int p,int q,unsigned char *pixelcourant)
-{
- for(int r = 0; r < 3; r++)
- ((unsigned char*)(image->imageData + image->widthStep*q))[p*3 + r] = pixelcourant[r];
-}
-
-void PixelUtils::PutGrayPixel(IplImage *image, int p, int q, unsigned char pixelcourant)
-{
- ((unsigned char*)(image->imageData + image->widthStep*q))[p] = pixelcourant;
-}
-
-void PixelUtils::GetPixel(IplImage *image, int m, int n, float *pixelcourant)
-{
- for(int k = 0; k < 3; k++)
- pixelcourant[k] = ((float*)(image->imageData + image->widthStep*n))[m*3 + k];
-}
-
-void PixelUtils::GetGrayPixel(IplImage *image, int m, int n, float *pixelcourant)
-{
- *pixelcourant = ((float*)(image->imageData + image->widthStep*n))[m];
-}
-
-void PixelUtils::PutPixel(IplImage *image, int p, int q, float *pixelcourant)
-{
- for(int r = 0; r < 3; r++)
- ((float*)(image->imageData + image->widthStep*q))[p*3 + r] = pixelcourant[r];
-}
-
-void PixelUtils::PutGrayPixel(IplImage *image,int p,int q,float pixelcourant)
-{
- ((float*)(image->imageData + image->widthStep*q))[p] = pixelcourant;
-}
-
-void PixelUtils::getNeighberhoodGrayPixel(IplImage* InputImage, int x, int y, float* neighberPixel)
-{
- int i,j,k;
-
- float* pixelCourant = (float*) malloc(1*(sizeof(float)));
-
- //le calcul de voisinage pour les 4 coins;
- /* 1.*/
- if(x==0 && y==0)
- {
- k = 0;
- for(i = x; i < x+2; i++)
- for(j = y; j < y+2; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- /* 2.*/
- if(x==0 && y==InputImage->width)
- {
- k = 0;
- for(i = x; i < x+2; i++)
- for(j = y-1; j < y+1; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- /* 3.*/
- if(x==InputImage->height && y==0)
- {
- k = 0;
- for(i = x-1; i < x+1; i++)
- for(j = y; j < y+2; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- /* 4.*/
- if(x==InputImage->height && y==InputImage->width)
- {
- k = 0;
- for(i = x-1; i <x+1; i++)
- for(j = y-1; j < y+1; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- // Voisinage de la premiere ligne : L(0)
- if(x==0 && (y!=0 && y!=InputImage->width))
- {
- k = 0;
- for(i = x+1; i >= x; i--)
- for(j = y-1; j < y+2; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- // Voisinage de la derni�re colonne : C(w)
- if((x!=0 && x!=InputImage->height) && y==InputImage->width)
- {
- k = 0;
- for(i = x+1; i > x-2; i--)
- for(j = y-1; j < y+1; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- // Voisinage de la derni�re ligne : L(h)
- if(x==InputImage->height && (y!=0 && y!=InputImage->width))
- {
- k = 0;
- for(i = x; i > x-2; i--)
- for(j = y-1; j < y+2; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- // Voisinage de la premiere colonne : C(0)
- if((x!=0 && x!=InputImage->height) && y==0)
- {
- k = 0;
- for(i = x-1; i < x+2; i++)
- for(j = y; j < y+2; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- //le calcul du voisinage pour le reste des elementes d'image
- if((x!=0 && x!=InputImage->height)&&(y!=0 && y!=InputImage->width))
- {
- k = 0;
- for(i = x+1;i > x-2; i--)
- for(j = y-1; j < y+2; j++)
- {
- GetGrayPixel(InputImage,i,j,pixelCourant);
- *(neighberPixel+k) = *pixelCourant;
- k++;
- }
- }
-
- free(pixelCourant);
-}
-
-void PixelUtils::ForegroundMinimum(IplImage *Foreground, float *Minimum, int n)
-{
- int i,j,k;
- float *pixelcourant;
-
- pixelcourant = (float *) malloc(n*sizeof(float));
-
- for(k = 0; k < n; k++)
- *(Minimum + k) = 255;
-
- for(i = 0; i < Foreground->width; i++)
- for(j = 0; j < Foreground->height; j++)
- {
- if(n == 3)
- {
- GetPixel(Foreground,i,j,pixelcourant);
-
- for(k = 0; k < n; k++)
- if(*(pixelcourant + k) < *(Minimum + k))
- *(Minimum + k) = *(pixelcourant + k);
- }
-
- if(n==1)
- {
- GetGrayPixel(Foreground,i,j,pixelcourant);
-
- if(*pixelcourant < *Minimum)
- *Minimum = *pixelcourant;
- }
- }
-
- free(pixelcourant);
-}
-
-void PixelUtils::ForegroundMaximum(IplImage *Foreground, float *Maximum, int n)
-{
- int i,j,k;
- float *pixelcourant;
-
- pixelcourant = (float *) malloc(n*sizeof(float));
-
- for(k = 0; k < n; k++)
- *(Maximum + k) = 0;
-
- for(i = 0; i < Foreground->width; i++)
- for(j = 0; j < Foreground->height; j++)
- {
- if(n == 3)
- {
- GetPixel(Foreground,i,j,pixelcourant);
-
- for(k = 0; k < n; k++)
- if(*(pixelcourant + k) > *(Maximum + k))
- *(Maximum + k) = *(pixelcourant + k);
- }
-
- if(n == 1)
- {
- GetGrayPixel(Foreground,i,j,pixelcourant);
-
- if(*pixelcourant > *Maximum)
- *Maximum = *pixelcourant;
- }
- }
-
- free(pixelcourant);
-}
-
-void PixelUtils::ComplementaryAlphaImageCreation(IplImage *AlphaImage, IplImage *ComplementaryAlphaImage, int n)
-{
- int i,j,k;
- float *pixelcourant, *pixelcourant1;
-
- pixelcourant = (float *) malloc(n * sizeof(float));
- pixelcourant1 = (float *) malloc(n * sizeof(float));
-
- for(i = 0; i < AlphaImage->width; i++)
- for(j = 0; j < AlphaImage->height; j++)
- {
- if(n == 1)
- {
- GetGrayPixel(AlphaImage,i,j,pixelcourant);
- *pixelcourant1 = 1 - *(pixelcourant);
- PutGrayPixel(ComplementaryAlphaImage,i,j,*pixelcourant1);
- }
-
- if(n == 3)
- {
- GetPixel(AlphaImage,i,j,pixelcourant);
- for(k = 0; k < 3; k++)
- {
- *pixelcourant1 = 1.0 - *(pixelcourant);
- *(pixelcourant1+1) = 1.0 - *(pixelcourant+1);
- *(pixelcourant1+2) = 1.0 - *(pixelcourant+2);
- }
- PutPixel(ComplementaryAlphaImage,i,j,pixelcourant1);
- }
- }
-
- free(pixelcourant);
- free(pixelcourant1);
-}
diff --git a/package_bgs/tb/T2FMRF_UM.h b/package_bgs/tb/T2FMRF_UM.h
deleted file mode 100644
index fd0da7b..0000000
--- a/package_bgs/tb/T2FMRF_UM.h
+++ /dev/null
@@ -1,64 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "MRF.h"
-
-using namespace Algorithms::BackgroundSubtraction;
-
-class T2FMRF_UM : public IBGS
-{
-private:
- bool firstTime;
- long frameNumber;
- IplImage *frame;
- RgbImage frame_data;
-
- IplImage *old_labeling;
- IplImage *old;
-
- T2FMRFParams params;
- T2FMRF bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- float km;
- float kv;
- int gaussians;
- bool showOutput;
-
- MRF_TC mrf;
- GMM *gmm;
- HMM *hmm;
-
-public:
- T2FMRF_UM();
- ~T2FMRF_UM();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/package_bgs/tb/T2FMRF_UV.h b/package_bgs/tb/T2FMRF_UV.h
deleted file mode 100644
index 28fcb67..0000000
--- a/package_bgs/tb/T2FMRF_UV.h
+++ /dev/null
@@ -1,64 +0,0 @@
-/*
-This file is part of BGSLibrary.
-
-BGSLibrary is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-BGSLibrary is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
-*/
-#pragma once
-
-#include <iostream>
-#include <opencv2/opencv.hpp>
-
-
-#include "../IBGS.h"
-#include "MRF.h"
-
-using namespace Algorithms::BackgroundSubtraction;
-
-class T2FMRF_UV : public IBGS
-{
-private:
- bool firstTime;
- long frameNumber;
- IplImage *frame;
- RgbImage frame_data;
-
- IplImage *old_labeling;
- IplImage *old;
-
- T2FMRFParams params;
- T2FMRF bgs;
- BwImage lowThresholdMask;
- BwImage highThresholdMask;
-
- double threshold;
- double alpha;
- float km;
- float kv;
- int gaussians;
- bool showOutput;
-
- MRF_TC mrf;
- GMM *gmm;
- HMM *hmm;
-
-public:
- T2FMRF_UV();
- ~T2FMRF_UV();
-
- void process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel);
-
-private:
- void saveConfig();
- void loadConfig();
-};
diff --git a/vs2010/.gitignore b/vs2010/.gitignore
deleted file mode 100644
index affde92..0000000
--- a/vs2010/.gitignore
+++ /dev/null
@@ -1,16 +0,0 @@
-# Ignore everything in this directory
-*
-# Except these files
-!.gitignore
-!README.txt
-!bgslibrary.sln
-!bgslibrary.suo
-!bgslibrary.vcxproj
-!bgslibrary.vcxproj.filters
-!bgslibrary.vcxproj.user
-!bgslibrary_demo.vcxproj
-!bgslibrary_demo.vcxproj.filters
-!bgslibrary_demo.vcxproj.user
-!bgslibrary_demo2.vcxproj
-!bgslibrary_demo2.vcxproj.filters
-!bgslibrary_demo2.vcxproj.user
diff --git a/vs2010/README.txt b/vs2010/README.txt
deleted file mode 100644
index 7b0a5cf..0000000
--- a/vs2010/README.txt
+++ /dev/null
@@ -1,15 +0,0 @@
-VISUAL STUDIO 2010 TEMPLATE PROJECT
------------------------------------
-Change to [Release][Win32]
-
-Tested with:
- VISUAL STUDIO 2010
- VISUAL STUDIO 2012
- VISUAL STUDIO 2013
- VISUAL STUDIO 2015
-
-You need to install OpenCV at:
- C:\OpenCV2.4.10
-or change the project settings.
-
-Build and run! ;)
\ No newline at end of file
diff --git a/vs2010/bgslibrary.sln b/vs2010/bgslibrary.sln
deleted file mode 100644
index ab59be3..0000000
--- a/vs2010/bgslibrary.sln
+++ /dev/null
@@ -1,27 +0,0 @@
-
-Microsoft Visual Studio Solution File, Format Version 12.00
-# Visual Studio 14
-VisualStudioVersion = 14.0.24720.0
-MinimumVisualStudioVersion = 10.0.40219.1
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "bgslibrary", "bgslibrary.vcxproj", "{3B6BF763-9CDE-4859-ADD9-8EB7B282659F}"
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "bgslibrary_demo", "bgslibrary_demo.vcxproj", "{EBE7FE0E-9FE6-41D2-B744-D43E7446D50C}"
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "bgslibrary_demo2", "bgslibrary_demo2.vcxproj", "{EAA15CCC-270A-460B-A61C-2DB864D67718}"
-EndProject
-Global
- GlobalSection(SolutionConfigurationPlatforms) = preSolution
- Release|Win32 = Release|Win32
- EndGlobalSection
- GlobalSection(ProjectConfigurationPlatforms) = postSolution
- {3B6BF763-9CDE-4859-ADD9-8EB7B282659F}.Release|Win32.ActiveCfg = Release|Win32
- {3B6BF763-9CDE-4859-ADD9-8EB7B282659F}.Release|Win32.Build.0 = Release|Win32
- {EBE7FE0E-9FE6-41D2-B744-D43E7446D50C}.Release|Win32.ActiveCfg = Release|Win32
- {EBE7FE0E-9FE6-41D2-B744-D43E7446D50C}.Release|Win32.Build.0 = Release|Win32
- {EAA15CCC-270A-460B-A61C-2DB864D67718}.Release|Win32.ActiveCfg = Release|Win32
- {EAA15CCC-270A-460B-A61C-2DB864D67718}.Release|Win32.Build.0 = Release|Win32
- EndGlobalSection
- GlobalSection(SolutionProperties) = preSolution
- HideSolutionNode = FALSE
- EndGlobalSection
-EndGlobal
diff --git a/vs2010/bgslibrary.suo b/vs2010/bgslibrary.suo
deleted file mode 100644
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-</Project>
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diff --git a/vs2010/bgslibrary_demo2.vcxproj.user b/vs2010/bgslibrary_demo2.vcxproj.user
deleted file mode 100644
index abe8dd8..0000000
--- a/vs2010/bgslibrary_demo2.vcxproj.user
+++ /dev/null
@@ -1,4 +0,0 @@
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-<Project ToolsVersion="14.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
- <PropertyGroup />
-</Project>
\ No newline at end of file
diff --git a/vs2010mfc/outputs/background/KEEP_THIS_FOLDER b/vs2010mfc/outputs/background/KEEP_THIS_FOLDER
deleted file mode 100644
index e69de29..0000000
diff --git a/vs2010mfc/outputs/foreground/KEEP_THIS_FOLDER b/vs2010mfc/outputs/foreground/KEEP_THIS_FOLDER
deleted file mode 100644
index e69de29..0000000
diff --git a/vs2010mfc/outputs/input/KEEP_THIS_FOLDER b/vs2010mfc/outputs/input/KEEP_THIS_FOLDER
deleted file mode 100644
index e69de29..0000000
diff --git a/vs2010mfc/src/ReadMe.txt b/vs2010mfc/src/ReadMe.txt
deleted file mode 100644
index 6c7fde0..0000000
--- a/vs2010mfc/src/ReadMe.txt
+++ /dev/null
@@ -1,100 +0,0 @@
-================================================================================
- MICROSOFT FOUNDATION CLASS LIBRARY : bgslibrary_vs2010_mfc Project Overview
-===============================================================================
-
-The application wizard has created this bgslibrary_vs2010_mfc application for
-you. This application not only demonstrates the basics of using the Microsoft
-Foundation Classes but is also a starting point for writing your application.
-
-This file contains a summary of what you will find in each of the files that
-make up your bgslibrary_vs2010_mfc application.
-
-bgslibrary_vs2010_mfc.vcxproj
- This is the main project file for VC++ projects generated using an application wizard.
- It contains information about the version of Visual C++ that generated the file, and
- information about the platforms, configurations, and project features selected with the
- application wizard.
-
-bgslibrary_vs2010_mfc.vcxproj.filters
- This is the filters file for VC++ projects generated using an Application Wizard.
- It contains information about the association between the files in your project
- and the filters. This association is used in the IDE to show grouping of files with
- similar extensions under a specific node (for e.g. ".cpp" files are associated with the
- "Source Files" filter).
-
-bgslibrary_vs2010_mfc.h
- This is the main header file for the application. It includes other
- project specific headers (including Resource.h) and declares the
- CApp application class.
-
-bgslibrary_vs2010_mfc.cpp
- This is the main application source file that contains the application
- class CApp.
-
-bgslibrary_vs2010_mfc.rc
- This is a listing of all of the Microsoft Windows resources that the
- program uses. It includes the icons, bitmaps, and cursors that are stored
- in the RES subdirectory. This file can be directly edited in Microsoft
- Visual C++. Your project resources are in 1033.
-
-res\bgslibrary_vs2010_mfc.ico
- This is an icon file, which is used as the application's icon. This
- icon is included by the main resource file bgslibrary_vs2010_mfc.rc.
-
-res\bgslibrary_vs2010_mfc.rc2
- This file contains resources that are not edited by Microsoft
- Visual C++. You should place all resources not editable by
- the resource editor in this file.
-
-
-/////////////////////////////////////////////////////////////////////////////
-
-The application wizard creates one dialog class:
-
-Dlg.h, Dlg.cpp - the dialog
- These files contain your CDlg class. This class defines
- the behavior of your application's main dialog. The dialog's template is
- in bgslibrary_vs2010_mfc.rc, which can be edited in Microsoft Visual C++.
-
-
-/////////////////////////////////////////////////////////////////////////////
-
-Other Features:
-
-ActiveX Controls
- The application includes support to use ActiveX controls.
-
-/////////////////////////////////////////////////////////////////////////////
-
-Other standard files:
-
-StdAfx.h, StdAfx.cpp
- These files are used to build a precompiled header (PCH) file
- named bgslibrary_vs2010_mfc.pch and a precompiled types file named StdAfx.obj.
-
-Resource.h
- This is the standard header file, which defines new resource IDs.
- Microsoft Visual C++ reads and updates this file.
-
-bgslibrary_vs2010_mfc.manifest
- Application manifest files are used by Windows XP to describe an applications
- dependency on specific versions of Side-by-Side assemblies. The loader uses this
- information to load the appropriate assembly from the assembly cache or private
- from the application. The Application manifest maybe included for redistribution
- as an external .manifest file that is installed in the same folder as the application
- executable or it may be included in the executable in the form of a resource.
-/////////////////////////////////////////////////////////////////////////////
-
-Other notes:
-
-The application wizard uses "TODO:" to indicate parts of the source code you
-should add to or customize.
-
-If your application uses MFC in a shared DLL, you will need
-to redistribute the MFC DLLs. If your application is in a language
-other than the operating system's locale, you will also have to
-redistribute the corresponding localized resources MFC100XXX.DLL.
-For more information on both of these topics, please see the section on
-redistributing Visual C++ applications in MSDN documentation.
-
-/////////////////////////////////////////////////////////////////////////////
diff --git a/vs2010mfc/src/bgslibrary_vs2010_mfc.rc b/vs2010mfc/src/bgslibrary_vs2010_mfc.rc
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diff --git a/vs2013/.gitignore b/vs2013/.gitignore
deleted file mode 100644
index e289c95..0000000
--- a/vs2013/.gitignore
+++ /dev/null
@@ -1,10 +0,0 @@
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-*
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diff --git a/vs2013/README.txt b/vs2013/README.txt
deleted file mode 100644
index e090e33..0000000
--- a/vs2013/README.txt
+++ /dev/null
@@ -1,8 +0,0 @@
-VISUAL STUDIO 2013 TEMPLATE PROJECT
------------------------------------
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-
-YOU NEEDS TO INSTALL OPENCV AT:
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-
-BUILD AND RUN!
\ No newline at end of file
diff --git a/vs2013/bgslibrary.sln b/vs2013/bgslibrary.sln
deleted file mode 100644
index 8013b8e..0000000
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+++ /dev/null
@@ -1,40 +0,0 @@
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- EndGlobalSection
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- HideSolutionNode = FALSE
- EndGlobalSection
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diff --git a/vs2013/bgslibrary.suo b/vs2013/bgslibrary.suo
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- <Filter>Header Files\package_bgs\pl</Filter>
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- <Filter>Header Files\package_bgs\pl</Filter>
- </ClInclude>
- </ItemGroup>
- <ItemGroup>
- <None Include="..\package_bgs\pl\LBSP_16bits_dbcross_1ch.i">
- <Filter>Header Files\package_bgs\pl</Filter>
- </None>
- <None Include="..\package_bgs\pl\LBSP_16bits_dbcross_3ch1t.i">
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- <Filter>Header Files\package_bgs\pl</Filter>
- </None>
- </ItemGroup>
-</Project>
\ No newline at end of file
diff --git a/vs2013/bgslibrary.vcxproj.user b/vs2013/bgslibrary.vcxproj.user
deleted file mode 100644
index 02146ba..0000000
--- a/vs2013/bgslibrary.vcxproj.user
+++ /dev/null
@@ -1,34 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
- <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
- <LocalDebuggerWorkingDirectory>../</LocalDebuggerWorkingDirectory>
- <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
- <LocalDebuggerCommandArguments>-uf=true -fn=dataset/video.avi</LocalDebuggerCommandArguments>
- </PropertyGroup>
- <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
- <LocalDebuggerWorkingDirectory>../</LocalDebuggerWorkingDirectory>
- <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
- <LocalDebuggerCommandArguments>-uf=true -fn=dataset/video.avi</LocalDebuggerCommandArguments>
- </PropertyGroup>
- <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='ReleaseDemo|Win32'">
- <LocalDebuggerWorkingDirectory>../</LocalDebuggerWorkingDirectory>
- <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
- <LocalDebuggerCommandArguments>
- </LocalDebuggerCommandArguments>
- </PropertyGroup>
- <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='ReleaseDemo|x64'">
- <LocalDebuggerWorkingDirectory>../</LocalDebuggerWorkingDirectory>
- <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
- <LocalDebuggerCommandArguments />
- </PropertyGroup>
- <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='ReleaseDemo2|Win32'">
- <LocalDebuggerWorkingDirectory>../</LocalDebuggerWorkingDirectory>
- <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
- <LocalDebuggerCommandArguments />
- </PropertyGroup>
- <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='ReleaseDemo2|x64'">
- <LocalDebuggerWorkingDirectory>../</LocalDebuggerWorkingDirectory>
- <DebuggerFlavor>WindowsLocalDebugger</DebuggerFlavor>
- <LocalDebuggerCommandArguments />
- </PropertyGroup>
-</Project>
\ No newline at end of file
diff --git a/vs2013mfc/.gitignore b/vs2013mfc/.gitignore
deleted file mode 100644
index fc99052..0000000
--- a/vs2013mfc/.gitignore
+++ /dev/null
@@ -1,3 +0,0 @@
-*.exe
-*.pdb
-*.dll
\ No newline at end of file
diff --git a/vs2013mfc/config/AdaptiveBackgroundLearning.xml b/vs2013mfc/config/AdaptiveBackgroundLearning.xml
deleted file mode 100644
index 313e1d4..0000000
--- a/vs2013mfc/config/AdaptiveBackgroundLearning.xml
+++ /dev/null
@@ -1,9 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<alpha>5.0000000000000003e-002</alpha>
-<limit>-1</limit>
-<enableThreshold>1</enableThreshold>
-<threshold>15</threshold>
-<showForeground>0</showForeground>
-<showBackground>0</showBackground>
-</opencv_storage>
diff --git a/vs2013mfc/config/AdaptiveSelectiveBackgroundLearning.xml b/vs2013mfc/config/AdaptiveSelectiveBackgroundLearning.xml
deleted file mode 100644
index f175558..0000000
--- a/vs2013mfc/config/AdaptiveSelectiveBackgroundLearning.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<learningFrames>90</learningFrames>
-<alphaLearn>5.0000000000000003e-002</alphaLearn>
-<alphaDetection>5.0000000000000003e-002</alphaDetection>
-<threshold>25</threshold>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPAdaptiveMedianBGS.xml b/vs2013mfc/config/DPAdaptiveMedianBGS.xml
deleted file mode 100644
index 8d09e85..0000000
--- a/vs2013mfc/config/DPAdaptiveMedianBGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>40</threshold>
-<samplingRate>7</samplingRate>
-<learningFrames>30</learningFrames>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPEigenbackgroundBGS.xml b/vs2013mfc/config/DPEigenbackgroundBGS.xml
deleted file mode 100644
index d610426..0000000
--- a/vs2013mfc/config/DPEigenbackgroundBGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>225</threshold>
-<historySize>20</historySize>
-<embeddedDim>10</embeddedDim>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPGrimsonGMMBGS.xml b/vs2013mfc/config/DPGrimsonGMMBGS.xml
deleted file mode 100644
index 8ade44f..0000000
--- a/vs2013mfc/config/DPGrimsonGMMBGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>9.</threshold>
-<alpha>1.0000000000000000e-002</alpha>
-<gaussians>3</gaussians>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPMeanBGS.xml b/vs2013mfc/config/DPMeanBGS.xml
deleted file mode 100644
index 9bd59a8..0000000
--- a/vs2013mfc/config/DPMeanBGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>2700</threshold>
-<alpha>9.9999999747524271e-007</alpha>
-<learningFrames>30</learningFrames>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPPratiMediodBGS.xml b/vs2013mfc/config/DPPratiMediodBGS.xml
deleted file mode 100644
index fdf20b4..0000000
--- a/vs2013mfc/config/DPPratiMediodBGS.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>30</threshold>
-<samplingRate>5</samplingRate>
-<historySize>16</historySize>
-<weight>5</weight>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPTextureBGS.xml b/vs2013mfc/config/DPTextureBGS.xml
deleted file mode 100644
index 0d63e78..0000000
--- a/vs2013mfc/config/DPTextureBGS.xml
+++ /dev/null
@@ -1,4 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPWrenGABGS.xml b/vs2013mfc/config/DPWrenGABGS.xml
deleted file mode 100644
index 7eaa78b..0000000
--- a/vs2013mfc/config/DPWrenGABGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>1.2250000000000000e+001</threshold>
-<alpha>4.9999998882412910e-003</alpha>
-<learningFrames>30</learningFrames>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/DPZivkovicAGMMBGS.xml b/vs2013mfc/config/DPZivkovicAGMMBGS.xml
deleted file mode 100644
index 98ee82a..0000000
--- a/vs2013mfc/config/DPZivkovicAGMMBGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<threshold>25.</threshold>
-<alpha>1.0000000474974513e-003</alpha>
-<gaussians>3</gaussians>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/FrameDifferenceBGS.xml b/vs2013mfc/config/FrameDifferenceBGS.xml
deleted file mode 100644
index 943a6c9..0000000
--- a/vs2013mfc/config/FrameDifferenceBGS.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<enableThreshold>1</enableThreshold>
-<threshold>15</threshold>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/FuzzyChoquetIntegral.xml b/vs2013mfc/config/FuzzyChoquetIntegral.xml
deleted file mode 100644
index 22074aa..0000000
--- a/vs2013mfc/config/FuzzyChoquetIntegral.xml
+++ /dev/null
@@ -1,11 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
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-<alphaLearn>1.0000000000000001e-001</alphaLearn>
-<alphaUpdate>1.0000000000000000e-002</alphaUpdate>
-<colorSpace>1</colorSpace>
-<option>2</option>
-<smooth>1</smooth>
-<threshold>6.7000000000000004e-001</threshold>
-</opencv_storage>
diff --git a/vs2013mfc/config/FuzzySugenoIntegral.xml b/vs2013mfc/config/FuzzySugenoIntegral.xml
deleted file mode 100644
index 22074aa..0000000
--- a/vs2013mfc/config/FuzzySugenoIntegral.xml
+++ /dev/null
@@ -1,11 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
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-<smooth>1</smooth>
-<threshold>6.7000000000000004e-001</threshold>
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diff --git a/vs2013mfc/config/GMG.xml b/vs2013mfc/config/GMG.xml
deleted file mode 100644
index e3ebdc7..0000000
--- a/vs2013mfc/config/GMG.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<initializationFrames>20</initializationFrames>
-<decisionThreshold>6.9999999999999996e-001</decisionThreshold>
-<showOutput>0</showOutput>
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diff --git a/vs2013mfc/config/IndependentMultimodalBGS.xml b/vs2013mfc/config/IndependentMultimodalBGS.xml
deleted file mode 100644
index 0d63e78..0000000
--- a/vs2013mfc/config/IndependentMultimodalBGS.xml
+++ /dev/null
@@ -1,4 +0,0 @@
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-<opencv_storage>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/KDE.xml b/vs2013mfc/config/KDE.xml
deleted file mode 100644
index c9b7402..0000000
--- a/vs2013mfc/config/KDE.xml
+++ /dev/null
@@ -1,11 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<framesToLearn>10</framesToLearn>
-<SequenceLength>50</SequenceLength>
-<TimeWindowSize>100</TimeWindowSize>
-<SDEstimationFlag>1</SDEstimationFlag>
-<lUseColorRatiosFlag>1</lUseColorRatiosFlag>
-<th>9.9999999999999995e-008</th>
-<alpha>2.9999999999999999e-001</alpha>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/LBAdaptiveSOM.xml b/vs2013mfc/config/LBAdaptiveSOM.xml
deleted file mode 100644
index 94b2570..0000000
--- a/vs2013mfc/config/LBAdaptiveSOM.xml
+++ /dev/null
@@ -1,9 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
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-<showOutput>0</showOutput>
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diff --git a/vs2013mfc/config/LBFuzzyAdaptiveSOM.xml b/vs2013mfc/config/LBFuzzyAdaptiveSOM.xml
deleted file mode 100644
index 7168563..0000000
--- a/vs2013mfc/config/LBFuzzyAdaptiveSOM.xml
+++ /dev/null
@@ -1,9 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
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-<trainingLearningRate>255</trainingLearningRate>
-<trainingSteps>81</trainingSteps>
-<showOutput>0</showOutput>
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diff --git a/vs2013mfc/config/LBFuzzyGaussian.xml b/vs2013mfc/config/LBFuzzyGaussian.xml
deleted file mode 100644
index 18635a1..0000000
--- a/vs2013mfc/config/LBFuzzyGaussian.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<sensitivity>72</sensitivity>
-<bgThreshold>162</bgThreshold>
-<learningRate>49</learningRate>
-<noiseVariance>195</noiseVariance>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/LBMixtureOfGaussians.xml b/vs2013mfc/config/LBMixtureOfGaussians.xml
deleted file mode 100644
index 2273720..0000000
--- a/vs2013mfc/config/LBMixtureOfGaussians.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
-<sensitivity>81</sensitivity>
-<bgThreshold>83</bgThreshold>
-<learningRate>59</learningRate>
-<noiseVariance>206</noiseVariance>
-<showOutput>0</showOutput>
-</opencv_storage>
diff --git a/vs2013mfc/config/LBSimpleGaussian.xml b/vs2013mfc/config/LBSimpleGaussian.xml
deleted file mode 100644
index a803f3f..0000000
--- a/vs2013mfc/config/LBSimpleGaussian.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
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-<noiseVariance>162</noiseVariance>
-<learningRate>18</learningRate>
-<showOutput>0</showOutput>
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diff --git a/vs2013mfc/config/LOBSTERBGS.xml b/vs2013mfc/config/LOBSTERBGS.xml
deleted file mode 100644
index c17b551..0000000
--- a/vs2013mfc/config/LOBSTERBGS.xml
+++ /dev/null
@@ -1,10 +0,0 @@
-<?xml version="1.0"?>
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-<showOutput>0</showOutput>
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diff --git a/vs2013mfc/config/MixtureOfGaussianV1BGS.xml b/vs2013mfc/config/MixtureOfGaussianV1BGS.xml
deleted file mode 100644
index 1e09ceb..0000000
--- a/vs2013mfc/config/MixtureOfGaussianV1BGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
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-<threshold>15</threshold>
-<showOutput>0</showOutput>
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diff --git a/vs2013mfc/config/MixtureOfGaussianV2BGS.xml b/vs2013mfc/config/MixtureOfGaussianV2BGS.xml
deleted file mode 100644
index 1e09ceb..0000000
--- a/vs2013mfc/config/MixtureOfGaussianV2BGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0"?>
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diff --git a/vs2013mfc/config/MultiCueBGS.xml b/vs2013mfc/config/MultiCueBGS.xml
deleted file mode 100644
index 0d63e78..0000000
--- a/vs2013mfc/config/MultiCueBGS.xml
+++ /dev/null
@@ -1,4 +0,0 @@
-<?xml version="1.0"?>
-<opencv_storage>
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diff --git a/vs2013mfc/config/MultiLayerBGS.xml b/vs2013mfc/config/MultiLayerBGS.xml
deleted file mode 100644
index 9b803db..0000000
--- a/vs2013mfc/config/MultiLayerBGS.xml
+++ /dev/null
@@ -1,31 +0,0 @@
-<?xml version="1.0"?>
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diff --git a/vs2013mfc/config/SigmaDeltaBGS.xml b/vs2013mfc/config/SigmaDeltaBGS.xml
deleted file mode 100644
index f1b2b2f..0000000
--- a/vs2013mfc/config/SigmaDeltaBGS.xml
+++ /dev/null
@@ -1,7 +0,0 @@
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-<opencv_storage>
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diff --git a/vs2013mfc/config/StaticFrameDifferenceBGS.xml b/vs2013mfc/config/StaticFrameDifferenceBGS.xml
deleted file mode 100644
index 943a6c9..0000000
--- a/vs2013mfc/config/StaticFrameDifferenceBGS.xml
+++ /dev/null
@@ -1,6 +0,0 @@
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diff --git a/vs2013mfc/config/SuBSENSEBGS.xml b/vs2013mfc/config/SuBSENSEBGS.xml
deleted file mode 100644
index 05509c1..0000000
--- a/vs2013mfc/config/SuBSENSEBGS.xml
+++ /dev/null
@@ -1,10 +0,0 @@
-<?xml version="1.0"?>
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diff --git a/vs2013mfc/config/T2FGMM_UM.xml b/vs2013mfc/config/T2FGMM_UM.xml
deleted file mode 100644
index d2f1054..0000000
--- a/vs2013mfc/config/T2FGMM_UM.xml
+++ /dev/null
@@ -1,9 +0,0 @@
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diff --git a/vs2013mfc/config/T2FGMM_UV.xml b/vs2013mfc/config/T2FGMM_UV.xml
deleted file mode 100644
index d2f1054..0000000
--- a/vs2013mfc/config/T2FGMM_UV.xml
+++ /dev/null
@@ -1,9 +0,0 @@
-<?xml version="1.0"?>
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diff --git a/vs2013mfc/config/T2FMRF_UM.xml b/vs2013mfc/config/T2FMRF_UM.xml
deleted file mode 100644
index 9a65c57..0000000
--- a/vs2013mfc/config/T2FMRF_UM.xml
+++ /dev/null
@@ -1,9 +0,0 @@
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diff --git a/vs2013mfc/config/T2FMRF_UV.xml b/vs2013mfc/config/T2FMRF_UV.xml
deleted file mode 100644
index 9a65c57..0000000
--- a/vs2013mfc/config/T2FMRF_UV.xml
+++ /dev/null
@@ -1,9 +0,0 @@
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diff --git a/vs2013mfc/config/VuMeter.xml b/vs2013mfc/config/VuMeter.xml
deleted file mode 100644
index d28fda7..0000000
--- a/vs2013mfc/config/VuMeter.xml
+++ /dev/null
@@ -1,8 +0,0 @@
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diff --git a/vs2013mfc/config/WeightedMovingMeanBGS.xml b/vs2013mfc/config/WeightedMovingMeanBGS.xml
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diff --git a/vs2013mfc/config/WeightedMovingVarianceBGS.xml b/vs2013mfc/config/WeightedMovingVarianceBGS.xml
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index d9de1d4..0000000
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diff --git a/vs2013mfc/src/.gitignore b/vs2013mfc/src/.gitignore
deleted file mode 100644
index 4ad092e..0000000
--- a/vs2013mfc/src/.gitignore
+++ /dev/null
@@ -1,6 +0,0 @@
-Release/
-ipch/
-*.exe
-*.pdb
-*.sdf
-*.opensdf
\ No newline at end of file
diff --git a/vs2013mfc/src/App.cpp b/vs2013mfc/src/App.cpp
deleted file mode 100644
index a6f45c7..0000000
--- a/vs2013mfc/src/App.cpp
+++ /dev/null
@@ -1,94 +0,0 @@
-
-// App.cpp : Defines the class behaviors for the application.
-//
-
-#include "stdafx.h"
-#include "App.h"
-#include "Dlg.h"
-
-#ifdef _DEBUG
-#define new DEBUG_NEW
-#endif
-
-
-// CApp
-
-BEGIN_MESSAGE_MAP(CApp, CWinApp)
- ON_COMMAND(ID_HELP, &CWinApp::OnHelp)
-END_MESSAGE_MAP()
-
-
-// CApp construction
-
-CApp::CApp()
-{
- // support Restart Manager
- m_dwRestartManagerSupportFlags = AFX_RESTART_MANAGER_SUPPORT_RESTART;
-
- // TODO: add construction code here,
- // Place all significant initialization in InitInstance
-}
-
-
-// The one and only CApp object
-
-CApp theApp;
-
-
-// CApp initialization
-
-BOOL CApp::InitInstance()
-{
- // InitCommonControlsEx() is required on Windows XP if an application
- // manifest specifies use of ComCtl32.dll version 6 or later to enable
- // visual styles. Otherwise, any window creation will fail.
- INITCOMMONCONTROLSEX InitCtrls;
- InitCtrls.dwSize = sizeof(InitCtrls);
- // Set this to include all the common control classes you want to use
- // in your application.
- InitCtrls.dwICC = ICC_WIN95_CLASSES;
- InitCommonControlsEx(&InitCtrls);
-
- CWinApp::InitInstance();
-
-
- AfxEnableControlContainer();
-
- // Create the shell manager, in case the dialog contains
- // any shell tree view or shell list view controls.
- CShellManager *pShellManager = new CShellManager;
-
- // Standard initialization
- // If you are not using these features and wish to reduce the size
- // of your final executable, you should remove from the following
- // the specific initialization routines you do not need
- // Change the registry key under which our settings are stored
- // TODO: You should modify this string to be something appropriate
- // such as the name of your company or organization
- SetRegistryKey(_T("Local AppWizard-Generated Applications"));
-
- CDlg dlg;
- m_pMainWnd = &dlg;
- INT_PTR nResponse = dlg.DoModal();
- if (nResponse == IDOK)
- {
- // TODO: Place code here to handle when the dialog is
- // dismissed with OK
- }
- else if (nResponse == IDCANCEL)
- {
- // TODO: Place code here to handle when the dialog is
- // dismissed with Cancel
- }
-
- // Delete the shell manager created above.
- if (pShellManager != NULL)
- {
- delete pShellManager;
- }
-
- // Since the dialog has been closed, return FALSE so that we exit the
- // application, rather than start the application's message pump.
- return FALSE;
-}
-
diff --git a/vs2013mfc/src/App.h b/vs2013mfc/src/App.h
deleted file mode 100644
index 5ef9764..0000000
--- a/vs2013mfc/src/App.h
+++ /dev/null
@@ -1,32 +0,0 @@
-
-// App.h : main header file for the application
-//
-
-#pragma once
-
-#ifndef __AFXWIN_H__
- #error "include 'stdafx.h' before including this file for PCH"
-#endif
-
-#include "resource.h" // main symbols
-
-
-// CApp:
-// See App.cpp for the implementation of this class
-//
-
-class CApp : public CWinApp
-{
-public:
- CApp();
-
-// Overrides
-public:
- virtual BOOL InitInstance();
-
-// Implementation
-
- DECLARE_MESSAGE_MAP()
-};
-
-extern CApp theApp;
\ No newline at end of file
diff --git a/vs2013mfc/src/Dlg.cpp b/vs2013mfc/src/Dlg.cpp
deleted file mode 100644
index f39249e..0000000
--- a/vs2013mfc/src/Dlg.cpp
+++ /dev/null
@@ -1,709 +0,0 @@
-
-// Dlg.cpp : implementation file
-//
-
-#include "stdafx.h"
-#include "App.h"
-#include "Dlg.h"
-#include "afxdialogex.h"
-
-#ifdef _DEBUG
-#define new DEBUG_NEW
-#endif
-
-
-// CAboutDlg dialog used for App About
-
-class CAboutDlg : public CDialogEx
-{
-public:
- CAboutDlg();
-
-// Dialog Data
- enum { IDD = IDD_ABOUTBOX };
-
- protected:
- virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV support
-
-// Implementation
-protected:
- DECLARE_MESSAGE_MAP()
-};
-
-CAboutDlg::CAboutDlg() : CDialogEx(CAboutDlg::IDD)
-{
-}
-
-void CAboutDlg::DoDataExchange(CDataExchange* pDX)
-{
- CDialogEx::DoDataExchange(pDX);
-}
-
-BEGIN_MESSAGE_MAP(CAboutDlg, CDialogEx)
-END_MESSAGE_MAP()
-
-
-// CDlg dialog
-
-
-
-
-CDlg::CDlg(CWnd* pParent /*=NULL*/)
- : CDialogEx(CDlg::IDD, pParent)
-{
- m_hIcon = AfxGetApp()->LoadIcon(IDR_MAINFRAME);
-}
-
-void CDlg::DoDataExchange(CDataExchange* pDX)
-{
- CDialogEx::DoDataExchange(pDX);
- DDX_Control(pDX, IDC_COMBO_BGSLIST, m_bgslist);
- DDX_Control(pDX, IDC_LOG, m_log);
- DDX_Control(pDX, IDC_INPUT_VIDEO, m_inputVideo);
- DDX_Control(pDX, IDC_USE_WEBCAM, m_useWebCam);
- DDX_Control(pDX, IDC_SPIN_WEBCAM_INDEX, m_spinWebCamIndex);
- DDX_Control(pDX, IDC_EDIT_WEBCAM_INDEX, m_webCamIndex);
- DDX_Control(pDX, IDC_FRAME_NUMBER, m_frameNumber);
- DDX_Control(pDX, IDC_SAVE_FRAME, m_saveFrame);
- DDX_Control(pDX, IDC_SAVE_MASK, m_saveMask);
- DDX_Control(pDX, IDC_SAVE_BKG, m_saveBkg);
- DDX_Control(pDX, IDC_IMG_SEQ, m_isImgSeq);
- DDX_Control(pDX, IDC_EDIT_START_IDX, m_startIdx);
- DDX_Control(pDX, IDC_EDIT_STOP_IDX, m_stopIdx);
- DDX_Control(pDX, IDC_COMBO_FILE_TYPE, m_fileTypeList);
- DDX_Control(pDX, IDC_SPIN_START_IDX, m_spinStartIdx);
- DDX_Control(pDX, IDC_SPIN_STOP_IDX, m_spinStopIdx);
- DDX_Control(pDX, IDC_EDIT_DELAY, m_delay);
- DDX_Control(pDX, IDC_EXEC_TIME, m_execTime);
- DDX_Control(pDX, IDC_MEDIAN_FILTER, m_medianFilter);
-}
-
-BEGIN_MESSAGE_MAP(CDlg, CDialogEx)
- ON_WM_SYSCOMMAND()
- ON_WM_PAINT()
- ON_WM_QUERYDRAGICON()
- ON_BN_CLICKED(IDSTART, &CDlg::OnBnClickedStart)
- ON_BN_CLICKED(IDSTOP, &CDlg::OnBnClickedStop)
- ON_BN_CLICKED(IDC_USE_WEBCAM, &CDlg::OnBnClickedUseWebcam)
- ON_BN_CLICKED(IDC_IMG_SEQ, &CDlg::OnBnClickedImgSeq)
- ON_BN_CLICKED(IDSAVE, &CDlg::OnBnClickedSave)
-END_MESSAGE_MAP()
-
-
-// CDlg message handlers
-
-BOOL CDlg::OnInitDialog()
-{
- CDialogEx::OnInitDialog();
-
- // Add "About..." menu item to system menu.
-
- // IDM_ABOUTBOX must be in the system command range.
- ASSERT((IDM_ABOUTBOX & 0xFFF0) == IDM_ABOUTBOX);
- ASSERT(IDM_ABOUTBOX < 0xF000);
-
- CMenu* pSysMenu = GetSystemMenu(FALSE);
- if (pSysMenu != NULL)
- {
- BOOL bNameValid;
- CString strAboutMenu;
- bNameValid = strAboutMenu.LoadString(IDS_ABOUTBOX);
- ASSERT(bNameValid);
- if (!strAboutMenu.IsEmpty())
- {
- pSysMenu->AppendMenu(MF_SEPARATOR);
- pSysMenu->AppendMenu(MF_STRING, IDM_ABOUTBOX, strAboutMenu);
- }
- }
-
- // Set the icon for this dialog. The framework does this automatically
- // when the application's main window is not a dialog
- SetIcon(m_hIcon, TRUE); // Set big icon
- SetIcon(m_hIcon, FALSE); // Set small icon
-
- // TODO: Add extra initialization here
- methodName = L"";
- useWebCam = false;
- useImgSeq = false;
- filePath = L"";
- bgs = NULL;
- webCamIndex = 0;
- m_spinWebCamIndex.SetRange(0, 9);
- m_spinStartIdx.SetRange(0, 999999);
- m_spinStopIdx.SetRange(0, 999999);
- m_frameNumber.SetWindowTextW(L"0");
-
- addBgsList();
- m_fileTypeList.AddString(L"PNG");
- m_fileTypeList.AddString(L"JPG");
- m_fileTypeList.AddString(L"JPEG");
- m_fileTypeList.AddString(L"JPE");
- m_fileTypeList.AddString(L"JP2");
- m_fileTypeList.AddString(L"BMP");
- m_fileTypeList.AddString(L"DIB");
- m_fileTypeList.AddString(L"PBM");
- m_fileTypeList.AddString(L"PGM");
- m_fileTypeList.AddString(L"PPM");
- m_fileTypeList.AddString(L"SR");
- m_fileTypeList.AddString(L"RAS");
- m_fileTypeList.AddString(L"TIFF");
- m_fileTypeList.AddString(L"TIF");
- m_fileTypeList.SelectString(0,L"PNG");
- m_inputVideo.SetWindowTextW(L"dataset/video.avi");
- m_delay.SetWindowTextW(L"1");
- m_execTime.SetWindowTextW(L"0");
-
- started = false;
- if(started == false)
- {
- cv::namedWindow("INPUT", 1);
- HWND hWnd = (HWND) cvGetWindowHandle("INPUT");
- HWND hParent = ::GetParent(hWnd);
- ::SetParent(hWnd, GetDlgItem(IDC_FRAME_INPUT)->m_hWnd);
- ::ShowWindow(hParent, SW_HIDE);
- }
-
- if(started == false)
- {
- cv::namedWindow("MASK", 1);
- HWND hWnd = (HWND) cvGetWindowHandle("MASK");
- HWND hParent = ::GetParent(hWnd);
- ::SetParent(hWnd, GetDlgItem(IDC_FRAME_MASK)->m_hWnd);
- ::ShowWindow(hParent, SW_HIDE);
- }
-
- if(started == false)
- {
- cv::namedWindow("BKG", 1);
- HWND hWnd = (HWND) cvGetWindowHandle("BKG");
- HWND hParent = ::GetParent(hWnd);
- ::SetParent(hWnd, GetDlgItem(IDC_FRAME_BKG)->m_hWnd);
- ::ShowWindow(hParent, SW_HIDE);
- }
-
- return TRUE; // return TRUE unless you set the focus to a control
-}
-
-void CDlg::OnSysCommand(UINT nID, LPARAM lParam)
-{
- if ((nID & 0xFFF0) == IDM_ABOUTBOX)
- {
- CAboutDlg dlgAbout;
- dlgAbout.DoModal();
- }
- else
- {
- CDialogEx::OnSysCommand(nID, lParam);
- }
-}
-
-// If you add a minimize button to your dialog, you will need the code below
-// to draw the icon. For MFC applications using the document/view model,
-// this is automatically done for you by the framework.
-
-void CDlg::OnPaint()
-{
- if (IsIconic())
- {
- CPaintDC dc(this); // device context for painting
-
- SendMessage(WM_ICONERASEBKGND, reinterpret_cast<WPARAM>(dc.GetSafeHdc()), 0);
-
- // Center icon in client rectangle
- int cxIcon = GetSystemMetrics(SM_CXICON);
- int cyIcon = GetSystemMetrics(SM_CYICON);
- CRect rect;
- GetClientRect(&rect);
- int x = (rect.Width() - cxIcon + 1) / 2;
- int y = (rect.Height() - cyIcon + 1) / 2;
-
- // Draw the icon
- dc.DrawIcon(x, y, m_hIcon);
- }
- else
- {
- CDialogEx::OnPaint();
- }
-}
-
-// The system calls this function to obtain the cursor to display while the user drags
-// the minimized window.
-HCURSOR CDlg::OnQueryDragIcon()
-{
- return static_cast<HCURSOR>(m_hIcon);
-}
-
-void CDlg::addBgsList()
-{
- // 37 algorithms
- m_bgslist.AddString(L"FrameDifferenceBGS");
- m_bgslist.AddString(L"StaticFrameDifferenceBGS");
- m_bgslist.AddString(L"WeightedMovingMeanBGS");
- m_bgslist.AddString(L"WeightedMovingVarianceBGS");
- m_bgslist.AddString(L"MixtureOfGaussianV1BGS");
- m_bgslist.AddString(L"MixtureOfGaussianV2BGS");
- m_bgslist.AddString(L"AdaptiveBackgroundLearning");
- m_bgslist.AddString(L"AdaptiveSelectiveBackgroundLearning");
- m_bgslist.AddString(L"GMG");
- m_bgslist.AddString(L"DPAdaptiveMedianBGS");
- m_bgslist.AddString(L"DPGrimsonGMMBGS");
- m_bgslist.AddString(L"DPZivkovicAGMMBGS");
- m_bgslist.AddString(L"DPMeanBGS");
- m_bgslist.AddString(L"DPWrenGABGS");
- m_bgslist.AddString(L"DPPratiMediodBGS");
- m_bgslist.AddString(L"DPEigenbackgroundBGS");
- m_bgslist.AddString(L"DPTextureBGS");
- m_bgslist.AddString(L"T2FGMM_UM");
- m_bgslist.AddString(L"T2FGMM_UV");
- m_bgslist.AddString(L"T2FMRF_UM");
- m_bgslist.AddString(L"T2FMRF_UV");
- m_bgslist.AddString(L"FuzzySugenoIntegral");
- m_bgslist.AddString(L"FuzzyChoquetIntegral");
- m_bgslist.AddString(L"LBSimpleGaussian");
- m_bgslist.AddString(L"LBFuzzyGaussian");
- m_bgslist.AddString(L"LBMixtureOfGaussians");
- m_bgslist.AddString(L"LBAdaptiveSOM");
- m_bgslist.AddString(L"LBFuzzyAdaptiveSOM");
- m_bgslist.AddString(L"MultiLayerBGS");
- //m_bgslist.AddString(L"PBAS");
- m_bgslist.AddString(L"VuMeter");
- m_bgslist.AddString(L"KDE");
- m_bgslist.AddString(L"IndependentMultimodalBGS");
- m_bgslist.AddString(L"SJN_MultiCueBGS");
- m_bgslist.AddString(L"SigmaDeltaBGS");
- m_bgslist.AddString(L"SuBSENSEBGS");
- m_bgslist.AddString(L"LOBSTERBGS");
-}
-
-bool CDlg::getBgsMethodName()
-{
- int nIndex = m_bgslist.GetCurSel();
- if(nIndex != CB_ERR)
- {
- m_bgslist.GetLBText(nIndex, methodName);
- return true;
- }
- else
- {
- AfxMessageBox(L"Please, select one background subtraction method!");
- return false;
- }
-}
-
-bool CDlg::getFileType()
-{
- int nIndex = m_fileTypeList.GetCurSel();
- if(nIndex != CB_ERR)
- {
- m_fileTypeList.GetLBText(nIndex, fileType);
- return true;
- }
- else
- {
- AfxMessageBox(L"Please, select one file type or extension!");
- return false;
- }
-}
-
-bool CDlg::getInputVideoFilePath()
-{
- m_inputVideo.GetWindowTextW(filePath);
-
- if(filePath.GetLength() > 0)
- return true;
- else
- {
- AfxMessageBox(L"Please, select one video file or image sequence folder!");
- return false;
- }
-}
-
-void CDlg::OnBnClickedStart()
-{
- if(started == false)
- {
- m_log.SetWindowTextW(L"Checking...");
-
- if(!getBgsMethodName())
- {
- m_log.SetWindowTextW(L"Stopped...");
- return;
- }
-
- useWebCam = false;
- if(m_useWebCam.GetCheck() == BST_CHECKED)
- useWebCam = true;
-
- useImgSeq = false;
- if(m_isImgSeq.GetCheck() == BST_CHECKED)
- {
- useImgSeq = true;
-
- if(!getFileType())
- {
- m_log.SetWindowTextW(L"Stopped...");
- return;
- }
- }
-
- if(useWebCam == false)
- if(!getInputVideoFilePath())
- {
- m_log.SetWindowTextW(L"Stopped...");
- return;
- }
-
- m_log.SetWindowTextW(L"Starting...");
- thread = AfxBeginThread((AFX_THREADPROC) CDlg::Thread, (LPVOID) this);
- }
- else
- {
- AfxMessageBox(L"Thread is already initialized!");
- return;
- }
-}
-
-DWORD CDlg::Thread(LPVOID *lpvParam)
-{
- CDlg *thr = (CDlg*) lpvParam;
- thr->ThreadProcess();
- return NULL;
-}
-
-void CDlg::ThreadProcess()
-{
- CString csStartIdx;
- m_startIdx.GetWindowTextW(csStartIdx);
- startIdx = _tstoi(csStartIdx);
-
- CString csStopIdx;
- m_stopIdx.GetWindowTextW(csStopIdx);
- stopIdx = _tstoi(csStopIdx);
-
- if(useImgSeq == false)
- {
- if(useWebCam)
- {
- CString strIndex;
- m_webCamIndex.GetWindowTextW(strIndex);
- webCamIndex = _tstoi(strIndex);
- capture = cvCaptureFromCAM(webCamIndex);
- }
- else
- {
- CStringA file_path_aux(filePath);
- capture = cvCaptureFromFile((const char *) file_path_aux);
- }
-
- if(!capture)
- {
- AfxMessageBox(L"ERROR: Cannot initialize video!");
- m_log.SetWindowTextW(L"Stopped...");
- return;
- }
- }
- else
- {
- if(stopIdx == 0)
- {
- AfxMessageBox(L"Stop index not defined!");
- return;
- }
-
- if(startIdx > stopIdx)
- {
- AfxMessageBox(L"Start index is higher than stop index!");
- return;
- }
- }
-
- /* Background Subtraction Methods */
-
- if(methodName == "FrameDifferenceBGS")
- bgs = new FrameDifferenceBGS;
- if(methodName == "StaticFrameDifferenceBGS")
- bgs = new StaticFrameDifferenceBGS;
- if(methodName == "WeightedMovingMeanBGS")
- bgs = new WeightedMovingMeanBGS;
- if(methodName == "WeightedMovingVarianceBGS")
- bgs = new WeightedMovingVarianceBGS;
- if(methodName == "MixtureOfGaussianV1BGS")
- bgs = new MixtureOfGaussianV1BGS;
- if(methodName == "MixtureOfGaussianV2BGS")
- bgs = new MixtureOfGaussianV2BGS;
- if(methodName == "AdaptiveBackgroundLearning")
- bgs = new AdaptiveBackgroundLearning;
- if(methodName == "AdaptiveSelectiveBackgroundLearning")
- bgs = new AdaptiveSelectiveBackgroundLearning;
- if(methodName == "GMG")
- bgs = new GMG;
-
- if(methodName == "DPAdaptiveMedianBGS")
- bgs = new DPAdaptiveMedianBGS;
- if(methodName == "DPGrimsonGMMBGS")
- bgs = new DPGrimsonGMMBGS;
- if(methodName == "DPZivkovicAGMMBGS")
- bgs = new DPZivkovicAGMMBGS;
- if(methodName == "DPMeanBGS")
- bgs = new DPMeanBGS;
- if(methodName == "DPWrenGABGS")
- bgs = new DPWrenGABGS;
- if(methodName == "DPPratiMediodBGS")
- bgs = new DPPratiMediodBGS;
- if(methodName == "DPEigenbackgroundBGS")
- bgs = new DPEigenbackgroundBGS;
- if(methodName == "DPTextureBGS")
- bgs = new DPTextureBGS;
-
- if(methodName == "T2FGMM_UM")
- bgs = new T2FGMM_UM;
- if(methodName == "T2FGMM_UV")
- bgs = new T2FGMM_UV;
- if(methodName == "T2FMRF_UM")
- bgs = new T2FMRF_UM;
- if(methodName == "T2FMRF_UV")
- bgs = new T2FMRF_UV;
- if(methodName == "FuzzySugenoIntegral")
- bgs = new FuzzySugenoIntegral;
- if(methodName == "FuzzyChoquetIntegral")
- bgs = new FuzzyChoquetIntegral;
-
- if(methodName == "LBSimpleGaussian")
- bgs = new LBSimpleGaussian;
- if(methodName == "LBFuzzyGaussian")
- bgs = new LBFuzzyGaussian;
- if(methodName == "LBMixtureOfGaussians")
- bgs = new LBMixtureOfGaussians;
- if(methodName == "LBAdaptiveSOM")
- bgs = new LBAdaptiveSOM;
- if(methodName == "LBFuzzyAdaptiveSOM")
- bgs = new LBFuzzyAdaptiveSOM;
- if(methodName == "MultiLayerBGS")
- bgs = new MultiLayerBGS;
- //if(methodName == "PBAS")
- //bgs = new PixelBasedAdaptiveSegmenter;
- if(methodName == "VuMeter")
- bgs = new VuMeter;
- if(methodName == "KDE")
- bgs = new KDE;
- if(methodName == "IndependentMultimodalBGS")
- bgs = new IndependentMultimodalBGS;
- if(methodName == "SJN_MultiCueBGS")
- bgs = new SJN_MultiCueBGS;
- if (methodName == "SigmaDeltaBGS")
- bgs = new SigmaDeltaBGS;
- if (methodName == "SuBSENSEBGS")
- bgs = new SuBSENSEBGS;
- if (methodName == "LOBSTERBGS")
- bgs = new LOBSTERBGS;
-
- if(bgs == NULL)
- {
- AfxMessageBox(L"BGS object not defined!");
- return;
- }
-
- started = true;
- int i = 0;
- if(useImgSeq == true && startIdx > 0)
- i = startIdx - 1;
- CString strFrameNumber;
- CString strExecTime;
- cv::Size default_size;
- default_size.width = 235;
- default_size.height = 189;
- IplImage* frame;
- std::string input_filename;
- cv::Mat img_input;
- // Convert a TCHAR string to a LPCSTR
- CT2CA fileType2(fileType);
- CT2CA filePath2(filePath);
- // construct a std::string using the LPCSTR input
- std::string str_fileType(fileType2);
- std::string str_filePath(filePath2);
- // delay
- CString csDelay;
- m_delay.GetWindowTextW(csDelay);
- int delay = _tstoi(csDelay);
-
- do
- {
- m_log.SetWindowTextW(L"Running...");
-
- i++;
- //::Sleep(1);
-
- if(useImgSeq == true && i == (stopIdx + 1))
- break;
-
- if(useImgSeq)
- {
- input_filename = str_filePath + "\\" + boost::lexical_cast<std::string>(i) + "." + str_fileType;
- img_input = cv::imread(input_filename);
-
- CString input_filename2(input_filename.c_str());
- m_log.SetWindowTextW(input_filename2);
-
- strFrameNumber.Format(L"%d",i);
- m_frameNumber.SetWindowTextW(strFrameNumber);
-
- if(img_input.data == NULL)
- {
- AfxMessageBox(L"File can not be read!");
- break;
- }
- }
- else
- {
- if(useWebCam == false && stopIdx >= 2 && i > stopIdx)
- break;
-
- frame = cvQueryFrame(capture);
- if(!frame)
- break;
-
- if(useWebCam == false && startIdx >= 2 && i < startIdx)
- continue;
-
- img_input = cv::Mat(frame,true);
- }
-
- cv::Mat img_mask;
- cv::Mat img_bkg;
- Clock::time_point t0 = Clock::now();
- bgs->process(img_input, img_mask, img_bkg);
- Clock::time_point t1 = Clock::now();
- auto d = boost::chrono::duration_cast<milliseconds>(t1 - t0);
- //std::cout << "\nElapsed time: " << d.count() << "ms" << std::endl;
-
- cv::Mat img_input_aux;
- cv::resize(img_input, img_input_aux, default_size);
-
- cv::Mat img_mask_aux;
- if(img_mask.empty())
- img_mask = cv::Mat::zeros(cv::Size(img_input.size().width, img_input.size().height), img_input.type());
- if(m_medianFilter.GetCheck() == BST_CHECKED)
- cv::medianBlur(img_mask, img_mask, 5);
- cv::resize(img_mask, img_mask_aux, default_size);
-
- cv::Mat img_bgk_aux;
- if(img_bkg.empty())
- img_bkg = cv::Mat::zeros(cv::Size(img_input.size().width, img_input.size().height), img_input.type());
- cv::resize(img_bkg, img_bgk_aux, default_size);
-
- cv::imshow("INPUT", img_input_aux);
- cv::imshow("MASK", img_mask_aux);
- cv::imshow("BKG", img_bgk_aux);
-
- extern_input_filename = "outputs/input/" + boost::lexical_cast<std::string>(i)+".png";
- img_input.copyTo(extern_input_img);
- if(m_saveFrame.GetCheck() == BST_CHECKED)
- cv::imwrite(extern_input_filename, img_input);
-
- extern_fg_filename = "outputs/foreground/" + boost::lexical_cast<std::string>(i)+".png";
- img_mask.copyTo(extern_fg_img);
- if(m_saveMask.GetCheck() == BST_CHECKED)
- cv::imwrite(extern_fg_filename, img_mask);
-
- extern_bg_filename = "outputs/background/" + boost::lexical_cast<std::string>(i)+".png";
- img_bkg.copyTo(extern_bg_img);
- if(m_saveBkg.GetCheck() == BST_CHECKED)
- cv::imwrite(extern_bg_filename, img_bkg);
-
- strFrameNumber.Format(L"%d",i);
- m_frameNumber.SetWindowTextW(strFrameNumber);
-
- //strExecTime.Format(_T("%.2f"), d.count());
- strExecTime.Format(_T("%d"), d.count());
- m_execTime.SetWindowTextW(strExecTime);
-
- ::Sleep(delay);
-
- }while(1);
-
- delete bgs;
-
- if(!useImgSeq)
- cvReleaseCapture(&capture);
-
- //AfxMessageBox(L"Thread is finished!");
- m_log.SetWindowTextW(L"Finished!");
- started = false;
-}
-
-
-void CDlg::OnBnClickedStop()
-{
- if(started)
- {
- m_log.SetWindowTextW(L"Stopping...");
-
- StopThread();
-
- if(!useImgSeq)
- if(capture)
- cvReleaseCapture(&capture);
-
- delete bgs;
- bgs = NULL;
-
- m_log.SetWindowTextW(L"Stopped!");
- started = false;
- }
-}
-
-void CDlg::StopThread()
-{
- DWORD exit_code = NULL;
-
- if(thread != NULL)
- {
- GetExitCodeThread(thread->m_hThread, &exit_code);
-
- if(exit_code == STILL_ACTIVE)
- {
- ::TerminateThread(thread->m_hThread, 0);
- CloseHandle(thread->m_hThread);
- }
-
- thread->m_hThread = NULL;
- thread = NULL;
- }
-}
-
-void CDlg::OnBnClickedUseWebcam()
-{
- if(m_useWebCam.GetCheck() == BST_CHECKED)
- m_isImgSeq.SetCheck(BST_UNCHECKED);
-
- m_inputVideo.EnableFileBrowseButton();
-}
-
-void CDlg::OnBnClickedImgSeq()
-{
- if(m_isImgSeq.GetCheck() == BST_CHECKED)
- {
- m_inputVideo.EnableFolderBrowseButton();
- m_useWebCam.SetCheck(BST_UNCHECKED);
- }
- else
- {
- m_startIdx.SetWindowTextW(L"0");
- m_stopIdx.SetWindowTextW(L"0");
- m_inputVideo.EnableFileBrowseButton();
- }
-}
-
-void CDlg::OnBnClickedSave()
-{
- if(m_saveFrame.GetCheck() == BST_CHECKED)
- cv::imwrite(extern_input_filename, extern_input_img);
-
- if(m_saveMask.GetCheck() == BST_CHECKED)
- cv::imwrite(extern_fg_filename, extern_fg_img);
-
- if(m_saveBkg.GetCheck() == BST_CHECKED)
- cv::imwrite(extern_bg_filename, extern_bg_img);
-
- m_log.SetWindowTextW(L"OK! Saved!");
-}
diff --git a/vs2013mfc/src/Dlg.h b/vs2013mfc/src/Dlg.h
deleted file mode 100644
index 479d727..0000000
--- a/vs2013mfc/src/Dlg.h
+++ /dev/null
@@ -1,92 +0,0 @@
-
-// Dlg.h : header file
-//
-
-#pragma once
-#include "stdafx.h"
-#include "afxwin.h"
-#include "afxcmn.h"
-
-// CDlg dialog
-class CDlg : public CDialogEx
-{
-// Construction
-public:
- CDlg(CWnd* pParent = NULL); // standard constructor
-
-// Dialog Data
- enum { IDD = IDD_APP };
-
- protected:
- virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV support
-
-
-// Implementation
-protected:
- HICON m_hIcon;
-
- // Generated message map functions
- virtual BOOL OnInitDialog();
- afx_msg void OnSysCommand(UINT nID, LPARAM lParam);
- afx_msg void OnPaint();
- afx_msg HCURSOR OnQueryDragIcon();
- DECLARE_MESSAGE_MAP()
-
-private:
- bool started;
- CWinThread* thread;
- CvCapture* capture;
- IBGS* bgs;
- CString methodName;
- CString fileType;
- bool useWebCam;
- bool useImgSeq;
- int webCamIndex;
- int startIdx;
- int stopIdx;
- int extern_i;
- std::string extern_input_filename;
- cv::Mat extern_input_img;
- std::string extern_fg_filename;
- cv::Mat extern_fg_img;
- std::string extern_bg_filename;
- cv::Mat extern_bg_img;
-
- CString filePath;
-
-public:
- afx_msg void ThreadProcess();
- static DWORD Thread(LPVOID *x);
- afx_msg void StopThread();
- afx_msg bool ipDraw(HDC hdc, IplImage* img, int xoffset=0, int yoffset=0);
-
-public:
- void addBgsList();
- bool getBgsMethodName();
- CComboBox m_bgslist;
- afx_msg void OnBnClickedStart();
- CStatic m_log;
- CMFCEditBrowseCtrl m_inputVideo;
- bool getInputVideoFilePath();
- CButton m_useWebCam;
- afx_msg void OnBnClickedStop();
- CSpinButtonCtrl m_spinWebCamIndex;
- CEdit m_webCamIndex;
- CStatic m_frameNumber;
- CButton m_saveFrame;
- CButton m_saveMask;
- CButton m_saveBkg;
- CButton m_isImgSeq;
- CEdit m_startIdx;
- CEdit m_stopIdx;
- CComboBox m_fileTypeList;
- bool getFileType();
- CSpinButtonCtrl m_spinStartIdx;
- CSpinButtonCtrl m_spinStopIdx;
- afx_msg void OnBnClickedUseWebcam();
- afx_msg void OnBnClickedImgSeq();
- CEdit m_delay;
- CStatic m_execTime;
- CButton m_medianFilter;
- afx_msg void OnBnClickedSave();
-};
diff --git a/vs2013mfc/src/resource.h b/vs2013mfc/src/resource.h
deleted file mode 100644
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diff --git a/vs2013mfc/src/stdafx.cpp b/vs2013mfc/src/stdafx.cpp
deleted file mode 100644
index 9e260e7..0000000
--- a/vs2013mfc/src/stdafx.cpp
+++ /dev/null
@@ -1,8 +0,0 @@
-
-// stdafx.cpp : source file that includes just the standard includes
-// bgslibrary_vs2010_mfc.pch will be the pre-compiled header
-// stdafx.obj will contain the pre-compiled type information
-
-#include "stdafx.h"
-
-
diff --git a/vs2013mfc/src/stdafx.h b/vs2013mfc/src/stdafx.h
deleted file mode 100644
index 4d734a9..0000000
--- a/vs2013mfc/src/stdafx.h
+++ /dev/null
@@ -1,104 +0,0 @@
-
-// stdafx.h : include file for standard system include files,
-// or project specific include files that are used frequently,
-// but are changed infrequently
-
-#pragma once
-
-#ifndef _SECURE_ATL
-#define _SECURE_ATL 1
-#endif
-
-#ifndef VC_EXTRALEAN
-#define VC_EXTRALEAN // Exclude rarely-used stuff from Windows headers
-#endif
-
-#include "targetver.h"
-
-#define _ATL_CSTRING_EXPLICIT_CONSTRUCTORS // some CString constructors will be explicit
-
-// turns off MFC's hiding of some common and often safely ignored warning messages
-#define _AFX_ALL_WARNINGS
-
-#include <afxwin.h> // MFC core and standard components
-#include <afxext.h> // MFC extensions
-
-
-#include <afxdisp.h> // MFC Automation classes
-
-
-
-#ifndef _AFX_NO_OLE_SUPPORT
-#include <afxdtctl.h> // MFC support for Internet Explorer 4 Common Controls
-#endif
-#ifndef _AFX_NO_AFXCMN_SUPPORT
-#include <afxcmn.h> // MFC support for Windows Common Controls
-#endif // _AFX_NO_AFXCMN_SUPPORT
-
-#include <afxcontrolbars.h> // MFC support for ribbons and control bars
-
-#ifdef _UNICODE
-#if defined _M_IX86
-#pragma comment(linker,"/manifestdependency:\"type='win32' name='Microsoft.Windows.Common-Controls' version='6.0.0.0' processorArchitecture='x86' publicKeyToken='6595b64144ccf1df' language='*'\"")
-#elif defined _M_X64
-#pragma comment(linker,"/manifestdependency:\"type='win32' name='Microsoft.Windows.Common-Controls' version='6.0.0.0' processorArchitecture='amd64' publicKeyToken='6595b64144ccf1df' language='*'\"")
-#else
-#pragma comment(linker,"/manifestdependency:\"type='win32' name='Microsoft.Windows.Common-Controls' version='6.0.0.0' processorArchitecture='*' publicKeyToken='6595b64144ccf1df' language='*'\"")
-#endif
-#endif
-
-#include <boost/lexical_cast.hpp>
-#include <boost/chrono.hpp>
-typedef boost::chrono::high_resolution_clock Clock;
-typedef boost::chrono::milliseconds milliseconds;
-typedef boost::chrono::microseconds microseconds;
-
-#include <iostream>
-
-#include <cv.h>
-#include <highgui.h>
-
-// BGSLibrary algorithms
-
-#include "../../package_bgs/FrameDifferenceBGS.h"
-#include "../../package_bgs/StaticFrameDifferenceBGS.h"
-#include "../../package_bgs/WeightedMovingMeanBGS.h"
-#include "../../package_bgs/WeightedMovingVarianceBGS.h"
-#include "../../package_bgs/MixtureOfGaussianV1BGS.h"
-#include "../../package_bgs/MixtureOfGaussianV2BGS.h"
-#include "../../package_bgs/AdaptiveBackgroundLearning.h"
-#include "../../package_bgs/AdaptiveSelectiveBackgroundLearning.h"
-#include "../../package_bgs/GMG.h"
-
-#include "../../package_bgs/dp/DPAdaptiveMedianBGS.h"
-#include "../../package_bgs/dp/DPGrimsonGMMBGS.h"
-#include "../../package_bgs/dp/DPZivkovicAGMMBGS.h"
-#include "../../package_bgs/dp/DPMeanBGS.h"
-#include "../../package_bgs/dp/DPWrenGABGS.h"
-#include "../../package_bgs/dp/DPPratiMediodBGS.h"
-#include "../../package_bgs/dp/DPEigenbackgroundBGS.h"
-#include "../../package_bgs/dp/DPTextureBGS.h"
-
-#include "../../package_bgs/tb/T2FGMM_UM.h"
-#include "../../package_bgs/tb/T2FGMM_UV.h"
-#include "../../package_bgs/tb/T2FMRF_UM.h"
-#include "../../package_bgs/tb/T2FMRF_UV.h"
-#include "../../package_bgs/tb/FuzzySugenoIntegral.h"
-#include "../../package_bgs/tb/FuzzyChoquetIntegral.h"
-
-#include "../../package_bgs/lb/LBSimpleGaussian.h"
-#include "../../package_bgs/lb/LBFuzzyGaussian.h"
-#include "../../package_bgs/lb/LBMixtureOfGaussians.h"
-#include "../../package_bgs/lb/LBAdaptiveSOM.h"
-#include "../../package_bgs/lb/LBFuzzyAdaptiveSOM.h"
-
-#include "../../package_bgs/jmo/MultiLayerBGS.h"
-//#include "../../package_bgs/pt/PixelBasedAdaptiveSegmenter.h"
-#include "../../package_bgs/av/VuMeter.h"
-#include "../../package_bgs/ae/KDE.h"
-#include "../../package_bgs/db/IndependentMultimodalBGS.h"
-#include "../../package_bgs/sjn/SJN_MultiCueBGS.h"
-#include "../../package_bgs/bl/SigmaDeltaBGS.h"
-
-#include "../../package_bgs/pl/SuBSENSE.h"
-#include "../../package_bgs/pl/LOBSTER.h"
diff --git a/vs2013mfc/src/targetver.h b/vs2013mfc/src/targetver.h
deleted file mode 100644
index 87c0086..0000000
--- a/vs2013mfc/src/targetver.h
+++ /dev/null
@@ -1,8 +0,0 @@
-#pragma once
-
-// Including SDKDDKVer.h defines the highest available Windows platform.
-
-// If you wish to build your application for a previous Windows platform, include WinSDKVer.h and
-// set the _WIN32_WINNT macro to the platform you wish to support before including SDKDDKVer.h.
-
-#include <SDKDDKVer.h>
diff --git a/wrapper_matlab/.gitignore b/wrapper_matlab/.gitignore
new file mode 100644
index 0000000..1c363bf
--- /dev/null
+++ b/wrapper_matlab/.gitignore
@@ -0,0 +1 @@
+*.mex*
diff --git a/wrapper_matlab/backgroundSubtractor.m b/wrapper_matlab/backgroundSubtractor.m
new file mode 100644
index 0000000..e431766
--- /dev/null
+++ b/wrapper_matlab/backgroundSubtractor.m
@@ -0,0 +1,81 @@
+%{
+/*
+ * This file is part of BGSLibrary.
+ *
+ * BGSLibrary is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * BGSLibrary is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+ */
+%}
+classdef backgroundSubtractor
+ %backgroundSubtractor Wrapper class for BGSLibrary
+ % obj = backgroundSubtractor(algorithm)
+ % creates an object with properties
+ %
+ % Properties:
+ % algorithm - Algorithm name (e.g. "FrameDifference").
+ %
+ % fgMask = getForegroundMask(obj, img) computes foreground mask on
+ % input image, img, for the object defined by obj.
+ %
+ % reset(obj) resets object.
+ %
+ % release(obj) releases object memory.
+
+ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ % Properties
+ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ properties
+ % See the full list of available algorithms in the BGSLibrary website.
+ algorithm = 'FrameDifference';
+ end
+
+ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ % Public methods
+ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+ methods
+ % Constructor
+ function obj = backgroundSubtractor(algorithm)
+ if(nargin > 0)
+ obj.algorithm = algorithm;
+ else
+ obj.algorithm = 'FrameDifference';
+ end
+ disp(['Selected algorithm: ' obj.algorithm]);
+ params = struct('algorithm', obj.algorithm);
+ backgroundSubtractor_wrapper('construct', params);
+ end
+
+ % Get foreground mask and background model
+ function [fgMask, bgModel] = getForegroundMask(~, img)
+ [fgMask, bgModel] = backgroundSubtractor_wrapper('compute', img);
+ end
+
+ % Reset object states
+ function reset(obj)
+ % Reset the background model with default parameters
+ % This is done in two steps. First free the persistent
+ % memory and then reconstruct the model with original
+ % parameters
+ backgroundSubtractor_wrapper('destroy');
+ params = struct('algorithm', obj.algorithm);
+ backgroundSubtractor_wrapper('construct', params);
+ end
+
+ % Release object memory
+ function release(~)
+ % free persistent memory for model
+ backgroundSubtractor_wrapper('destroy');
+ end
+
+ end
+end
\ No newline at end of file
diff --git a/wrapper_matlab/backgroundSubtractor_wrapper.cpp b/wrapper_matlab/backgroundSubtractor_wrapper.cpp
new file mode 100644
index 0000000..5470120
--- /dev/null
+++ b/wrapper_matlab/backgroundSubtractor_wrapper.cpp
@@ -0,0 +1,395 @@
+/*
+ * This file is part of BGSLibrary.
+ *
+ * BGSLibrary is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * BGSLibrary is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+ */
+
+#include "opencvmex.hpp"
+ // On some platforms, the following include is needed for "placement new".
+ // For more information see: http://en.wikipedia.org/wiki/Placement_syntax
+#include <memory>
+
+#include <typeinfo>
+#include "mxarray.h"
+
+#include "IBGS.h"
+#include "FrameDifference.h"
+#include "StaticFrameDifference.h"
+#include "WeightedMovingMean.h"
+#include "WeightedMovingVariance.h"
+#include "MixtureOfGaussianV1.h"
+#include "MixtureOfGaussianV2.h"
+#include "AdaptiveBackgroundLearning.h"
+#include "AdaptiveSelectiveBackgroundLearning.h"
+#include "GMG.h"
+#include "KNN.h"
+#include "DPAdaptiveMedian.h"
+#include "DPGrimsonGMM.h"
+#include "DPZivkovicAGMM.h"
+#include "DPMean.h"
+#include "DPWrenGA.h"
+#include "DPPratiMediod.h"
+#include "DPEigenbackground.h"
+#include "DPTexture.h"
+#include "T2FGMM_UM.h"
+#include "T2FGMM_UV.h"
+#include "T2FMRF_UM.h"
+#include "T2FMRF_UV.h"
+#include "FuzzySugenoIntegral.h"
+#include "FuzzyChoquetIntegral.h"
+#include "LBSimpleGaussian.h"
+#include "LBFuzzyGaussian.h"
+#include "LBMixtureOfGaussians.h"
+#include "LBAdaptiveSOM.h"
+#include "LBFuzzyAdaptiveSOM.h"
+#include "LBP_MRF.h"
+#include "MultiLayer.h"
+#include "PixelBasedAdaptiveSegmenter.h"
+#include "VuMeter.h"
+#include "KDE.h"
+#include "IndependentMultimodal.h"
+#include "MultiCue.h"
+#include "SigmaDelta.h"
+#include "SuBSENSE.h"
+#include "LOBSTER.h"
+#include "PAWCS.h"
+#include "TwoPoints.h"
+#include "ViBe.h"
+
+using namespace bgslibrary::algorithms;
+
+static IBGS *ptrBGS = NULL;
+
+namespace bgslibrary
+{
+ IBGS* init_alg(std::string alg_name)
+ {
+ if (alg_name.compare("FrameDifference") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(FrameDifference));
+ if (alg_name.compare("StaticFrameDifference") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(StaticFrameDifference));
+ if (alg_name.compare("WeightedMovingMean") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(WeightedMovingMean));
+ if (alg_name.compare("WeightedMovingVariance") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(WeightedMovingVariance));
+#if CV_MAJOR_VERSION == 2
+ if (alg_name.compare("MixtureOfGaussianV1") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(MixtureOfGaussianV1)); // only for OpenCV 2.x
+#endif
+ if (alg_name.compare("MixtureOfGaussianV2") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(MixtureOfGaussianV2));
+ if (alg_name.compare("AdaptiveBackgroundLearning") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(AdaptiveBackgroundLearning));
+ if (alg_name.compare("AdaptiveSelectiveBackgroundLearning") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(AdaptiveSelectiveBackgroundLearning));
+#if CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
+ if (alg_name.compare("GMG") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(GMG)); // only for OpenCV >= 2.4.3
+#endif
+#if CV_MAJOR_VERSION == 3
+ if (alg_name.compare("KNN") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(KNN)); // only for OpenCV 3.x
+#endif
+ if (alg_name.compare("DPAdaptiveMedian") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPAdaptiveMedian));
+ if (alg_name.compare("DPGrimsonGMM") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPGrimsonGMM));
+ if (alg_name.compare("DPZivkovicAGMM") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPZivkovicAGMM));
+ if (alg_name.compare("DPMean") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPMean));
+ if (alg_name.compare("DPWrenGA") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPWrenGA));
+ if (alg_name.compare("DPPratiMediod") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPPratiMediod));
+ if (alg_name.compare("DPEigenbackground") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPEigenbackground));
+ if (alg_name.compare("DPTexture") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(DPTexture));
+ if (alg_name.compare("T2FGMM_UM") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(T2FGMM_UM));
+ if (alg_name.compare("T2FGMM_UV") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(T2FGMM_UV));
+ if (alg_name.compare("T2FMRF_UM") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(T2FMRF_UM));
+ if (alg_name.compare("T2FMRF_UV") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(T2FMRF_UV));
+ if (alg_name.compare("FuzzySugenoIntegral") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(FuzzySugenoIntegral));
+ if (alg_name.compare("FuzzyChoquetIntegral") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(FuzzyChoquetIntegral));
+ if (alg_name.compare("LBSimpleGaussian") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LBSimpleGaussian));
+ if (alg_name.compare("LBFuzzyGaussian") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LBFuzzyGaussian));
+ if (alg_name.compare("LBMixtureOfGaussians") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LBMixtureOfGaussians));
+ if (alg_name.compare("LBAdaptiveSOM") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LBAdaptiveSOM));
+ if (alg_name.compare("LBFuzzyAdaptiveSOM") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LBFuzzyAdaptiveSOM));
+ if (alg_name.compare("LBP_MRF") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LBP_MRF));
+ if (alg_name.compare("MultiLayer") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(MultiLayer));
+ if (alg_name.compare("PixelBasedAdaptiveSegmenter") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(PixelBasedAdaptiveSegmenter));
+ if (alg_name.compare("VuMeter") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(VuMeter));
+ if (alg_name.compare("KDE") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(KDE));
+ if (alg_name.compare("IndependentMultimodal") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(IndependentMultimodal));
+ if (alg_name.compare("MultiCue") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(MultiCue));
+ if (alg_name.compare("SigmaDelta") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(SigmaDelta));
+ if (alg_name.compare("SuBSENSE") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(SuBSENSE));
+ if (alg_name.compare("LOBSTER") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(LOBSTER));
+ if (alg_name.compare("PAWCS") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(PAWCS));
+ if (alg_name.compare("TwoPoints") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(TwoPoints));
+ if (alg_name.compare("ViBe") == 0)
+ return (IBGS *)mxCalloc(1, sizeof(ViBe));
+ return NULL;
+ }
+
+ IBGS* get_alg(std::string alg_name)
+ {
+ if (alg_name.compare("FrameDifference") == 0)
+ return new (ptrBGS) FrameDifference();
+ if (alg_name.compare("StaticFrameDifference") == 0)
+ return new (ptrBGS) StaticFrameDifference();
+ if (alg_name.compare("WeightedMovingMean") == 0)
+ return new (ptrBGS) WeightedMovingMean();
+ if (alg_name.compare("WeightedMovingVariance") == 0)
+ return new (ptrBGS) WeightedMovingVariance();
+#if CV_MAJOR_VERSION == 2
+ if (alg_name.compare("MixtureOfGaussianV1") == 0)
+ return new (ptrBGS) MixtureOfGaussianV1(); // only for OpenCV 2.x
+#endif
+ if (alg_name.compare("MixtureOfGaussianV2") == 0)
+ return new (ptrBGS) MixtureOfGaussianV2();
+ if (alg_name.compare("AdaptiveBackgroundLearning") == 0)
+ return new (ptrBGS) AdaptiveBackgroundLearning();
+ if (alg_name.compare("AdaptiveSelectiveBackgroundLearning") == 0)
+ return new (ptrBGS) AdaptiveSelectiveBackgroundLearning();
+#if CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >= 4 && CV_SUBMINOR_VERSION >= 3
+ if (alg_name.compare("GMG") == 0)
+ return new (ptrBGS) GMG(); // only for OpenCV >= 2.4.3
+#endif
+#if CV_MAJOR_VERSION == 3
+ if (alg_name.compare("KNN") == 0)
+ return new (ptrBGS) KNN(); // only on OpenCV 3.x
+#endif
+ if (alg_name.compare("DPAdaptiveMedian") == 0)
+ return new (ptrBGS) DPAdaptiveMedian();
+ if (alg_name.compare("DPGrimsonGMM") == 0)
+ return new (ptrBGS) DPGrimsonGMM();
+ if (alg_name.compare("DPZivkovicAGMM") == 0)
+ return new (ptrBGS) DPZivkovicAGMM();
+ if (alg_name.compare("DPMean") == 0)
+ return new (ptrBGS) DPMean();
+ if (alg_name.compare("DPWrenGA") == 0)
+ return new (ptrBGS) DPWrenGA();
+ if (alg_name.compare("DPPratiMediod") == 0)
+ return new (ptrBGS) DPPratiMediod();
+ if (alg_name.compare("DPEigenbackground") == 0)
+ return new (ptrBGS) DPEigenbackground();
+ if (alg_name.compare("DPTexture") == 0)
+ return new (ptrBGS) DPTexture();
+ if (alg_name.compare("T2FGMM_UM") == 0)
+ return new (ptrBGS) T2FGMM_UM();
+ if (alg_name.compare("T2FGMM_UV") == 0)
+ return new (ptrBGS) T2FGMM_UV();
+ if (alg_name.compare("T2FMRF_UM") == 0)
+ return new (ptrBGS) T2FMRF_UM();
+ if (alg_name.compare("T2FMRF_UV") == 0)
+ return new (ptrBGS) T2FMRF_UV();
+ if (alg_name.compare("FuzzySugenoIntegral") == 0)
+ return new (ptrBGS) FuzzySugenoIntegral();
+ if (alg_name.compare("FuzzyChoquetIntegral") == 0)
+ return new (ptrBGS) FuzzyChoquetIntegral();
+ if (alg_name.compare("LBSimpleGaussian") == 0)
+ return new (ptrBGS) LBSimpleGaussian();
+ if (alg_name.compare("LBFuzzyGaussian") == 0)
+ return new (ptrBGS) LBFuzzyGaussian();
+ if (alg_name.compare("LBMixtureOfGaussians") == 0)
+ return new (ptrBGS) LBMixtureOfGaussians();
+ if (alg_name.compare("LBAdaptiveSOM") == 0)
+ return new (ptrBGS) LBAdaptiveSOM();
+ if (alg_name.compare("LBFuzzyAdaptiveSOM") == 0)
+ return new (ptrBGS) LBFuzzyAdaptiveSOM();
+ if (alg_name.compare("LBP_MRF") == 0)
+ return new (ptrBGS) LBP_MRF();
+ if (alg_name.compare("MultiLayer") == 0)
+ return new (ptrBGS) MultiLayer();
+ if (alg_name.compare("PixelBasedAdaptiveSegmenter") == 0)
+ return new (ptrBGS) PixelBasedAdaptiveSegmenter();
+ if (alg_name.compare("VuMeter") == 0)
+ return new (ptrBGS) VuMeter();
+ if (alg_name.compare("KDE") == 0)
+ return new (ptrBGS) KDE();
+ if (alg_name.compare("IndependentMultimodal") == 0)
+ return new (ptrBGS) IndependentMultimodal();
+ if (alg_name.compare("MultiCue") == 0)
+ return new (ptrBGS) MultiCue();
+ if (alg_name.compare("SigmaDelta") == 0)
+ return new (ptrBGS) SigmaDelta();
+ if (alg_name.compare("SuBSENSE") == 0)
+ return new (ptrBGS) SuBSENSE();
+ if (alg_name.compare("LOBSTER") == 0)
+ return new (ptrBGS) LOBSTER();
+ if (alg_name.compare("PAWCS") == 0)
+ return new (ptrBGS) PAWCS();
+ if (alg_name.compare("TwoPoints") == 0)
+ return new (ptrBGS) TwoPoints();
+ if (alg_name.compare("ViBe") == 0)
+ return new (ptrBGS) ViBe();
+ return NULL;
+ }
+}
+
+//////////////////////////////////////////////////////////////////////////////
+// Check inputs
+//////////////////////////////////////////////////////////////////////////////
+void checkInputs(int nrhs, const mxArray *prhs[])
+{
+ //mexPrintf("checkInputs()\n");
+ if ((nrhs < 1) || (nrhs > 2))
+ mexErrMsgTxt("Incorrect number of inputs. Function expects 1 or 2 inputs.");
+}
+
+//////////////////////////////////////////////////////////////////////////////
+// Get MEX function inputs
+//////////////////////////////////////////////////////////////////////////////
+void getParams(std::string &algorithm, const mxArray* mxParams)
+{
+ //mexPrintf("getParams()\n");
+ const mxArray* mxfield;
+ mxfield = mxGetField(mxParams, 0, "algorithm");
+ algorithm = mexplus::MxArray::to<std::string>(mxfield);
+ //mexPrintf(algorithm.c_str());
+ //mexPrintf("\n");
+}
+
+//////////////////////////////////////////////////////////////////////////////
+// Exit function for freeing persistent memory
+//////////////////////////////////////////////////////////////////////////////
+void exitFcn()
+{
+ //mexPrintf("exitFcn()\n");
+ if (ptrBGS != NULL)
+ {
+ // explicitly call destructor for "placement new"
+ ptrBGS->~IBGS();
+ mxFree(ptrBGS);
+ ptrBGS = NULL;
+ }
+}
+
+//////////////////////////////////////////////////////////////////////////////
+// Construct object
+//////////////////////////////////////////////////////////////////////////////
+void constructObject(const mxArray *prhs[])
+{
+ //mexPrintf("constructObject()\n");
+ std::string algorithm;
+
+ // second input must be struct
+ if (mxIsStruct(prhs[1]))
+ getParams(algorithm, prhs[1]);
+
+ if (ptrBGS != NULL) exitFcn();
+
+ // Allocate memory for background subtractor model
+ //ptrBGS = (IBGS *)mxCalloc(1, sizeof(IBGS));
+ ptrBGS = bgslibrary::init_alg(algorithm);
+ if (ptrBGS != NULL)
+ {
+ // Make memory allocated by MATLAB software persist after MEX-function completes.
+ // This lets us use the updated background subtractor model for the next frame.
+ mexMakeMemoryPersistent(ptrBGS);
+
+ // Use "placement new" to construct an object on memory that was
+ // already allocated using mxCalloc
+ ptrBGS = bgslibrary::get_alg(algorithm);
+ if (ptrBGS == NULL)
+ mexErrMsgTxt("Failed to construct an object on memory. Algorithm not initialized.");
+ }
+ else
+ mexErrMsgTxt("Failed to allocate memory. Algorithm not found?");
+
+ // Register a function that gets called when the MEX-function is cleared.
+ // This function is responsible for freeing persistent memory
+ mexAtExit(exitFcn);
+}
+
+//////////////////////////////////////////////////////////////////////////////
+// Compute foreground mask
+//////////////////////////////////////////////////////////////////////////////
+void computeForegroundMask(mxArray *plhs[], const mxArray *prhs[])
+{
+ //mexPrintf("computeForegroundMask()\n");
+ if (ptrBGS != NULL)
+ {
+ cv::Ptr<cv::Mat> img = ocvMxArrayToImage_uint8(prhs[1], true);
+ cv::Mat fgmask, bgmodel;
+
+ ptrBGS->process(*img, fgmask, bgmodel);
+
+ if (fgmask.empty())
+ fgmask = cv::Mat::zeros((*img).size(), CV_8UC1);
+ if (bgmodel.empty())
+ bgmodel = cv::Mat::zeros((*img).size(), CV_8UC3); // (*img).type()
+
+ // https://fr.mathworks.com/help/vision/ref/ocvmxarrayfromimage_datatype.html
+ plhs[0] = ocvMxArrayFromImage_uint8(fgmask);
+ plhs[1] = ocvMxArrayFromImage_uint8(bgmodel);
+
+ //if(!fgmask.empty())
+ fgmask.release();
+ //if(!bgmodel.empty())
+ bgmodel.release();
+ }
+ else
+ mexErrMsgTxt("Algorithm not initialized.");
+}
+
+//////////////////////////////////////////////////////////////////////////////
+// The main MEX function entry point
+//////////////////////////////////////////////////////////////////////////////
+void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
+{
+ //mexPrintf("mexFunction()\n");
+ checkInputs(nrhs, prhs);
+ const char *str = mxIsChar(prhs[0]) ? mxArrayToString(prhs[0]) : NULL;
+
+ if (str != NULL)
+ {
+ //mexPrintf("%s\n",str);
+ if (strcmp(str, "construct") == 0)
+ constructObject(prhs);
+ else if (strcmp(str, "compute") == 0)
+ computeForegroundMask(plhs, prhs);
+ else if (strcmp(str, "destroy") == 0)
+ exitFcn();
+
+ // Free memory allocated by mxArrayToString
+ mxFree((void *)str);
+ }
+}
diff --git a/wrapper_matlab/compile.m b/wrapper_matlab/compile.m
new file mode 100644
index 0000000..314ada1
--- /dev/null
+++ b/wrapper_matlab/compile.m
@@ -0,0 +1,94 @@
+%% Compile
+clc;
+mexOpenCV -v -DMEX_COMPILE_FLAG -I"..\package_bgs" backgroundSubtractor_wrapper.cpp ...
+ "..\package_bgs\FrameDifference.cpp" ...
+ "..\package_bgs\StaticFrameDifference.cpp" ...
+ "..\package_bgs\WeightedMovingMean.cpp" ...
+ "..\package_bgs\WeightedMovingVariance.cpp" ...
+ "..\package_bgs\MixtureOfGaussianV1.cpp" ...
+ "..\package_bgs\MixtureOfGaussianV2.cpp" ...
+ "..\package_bgs\AdaptiveBackgroundLearning.cpp" ...
+ "..\package_bgs\AdaptiveSelectiveBackgroundLearning.cpp" ...
+ "..\package_bgs\GMG.cpp" ...
+ "..\package_bgs\KNN.cpp" ...
+ "..\package_bgs\DPAdaptiveMedian.cpp" ...
+ "..\package_bgs\DPGrimsonGMM.cpp" ...
+ "..\package_bgs\DPZivkovicAGMM.cpp" ...
+ "..\package_bgs\DPMean.cpp" ...
+ "..\package_bgs\DPWrenGA.cpp" ...
+ "..\package_bgs\DPPratiMediod.cpp" ...
+ "..\package_bgs\DPEigenbackground.cpp" ...
+ "..\package_bgs\DPTexture.cpp" ...
+ "..\package_bgs\dp\AdaptiveMedianBGS.cpp" ...
+ "..\package_bgs\dp\Image.cpp" ...
+ "..\package_bgs\dp\Error.cpp" ...
+ "..\package_bgs\dp\GrimsonGMM.cpp" ...
+ "..\package_bgs\dp\ZivkovicAGMM.cpp" ...
+ "..\package_bgs\dp\MeanBGS.cpp" ...
+ "..\package_bgs\dp\WrenGA.cpp" ...
+ "..\package_bgs\dp\PratiMediodBGS.cpp" ...
+ "..\package_bgs\dp\Eigenbackground.cpp" ...
+ "..\package_bgs\dp\TextureBGS.cpp" ...
+ "..\package_bgs\T2FGMM_UM.cpp" ...
+ "..\package_bgs\T2FGMM_UV.cpp" ...
+ "..\package_bgs\T2FMRF_UM.cpp" ...
+ "..\package_bgs\T2FMRF_UV.cpp" ...
+ "..\package_bgs\FuzzyChoquetIntegral.cpp" ...
+ "..\package_bgs\FuzzySugenoIntegral.cpp" ...
+ "..\package_bgs\T2F\T2FGMM.cpp" ...
+ "..\package_bgs\T2F\T2FMRF.cpp" ...
+ "..\package_bgs\T2F\MRF.cpp" ...
+ "..\package_bgs\T2F\FuzzyUtils.cpp" ...
+ "..\package_analysis\PixelUtils.cpp" ...
+ "..\package_bgs\MultiLayer.cpp" ...
+ "..\package_bgs\MultiLayer\CMultiLayerBGS.cpp" ...
+ "..\package_bgs\MultiLayer\LocalBinaryPattern.cpp" ...
+ "..\package_bgs\MultiLayer\BlobResult.cpp" ...
+ "..\package_bgs\MultiLayer\BlobExtraction.cpp" ...
+ "..\package_bgs\MultiLayer\blob.cpp" ...
+ "..\package_bgs\LBSimpleGaussian.cpp" ...
+ "..\package_bgs\LBFuzzyGaussian.cpp" ...
+ "..\package_bgs\LBMixtureOfGaussians.cpp" ...
+ "..\package_bgs\LBAdaptiveSOM.cpp" ...
+ "..\package_bgs\LBFuzzyAdaptiveSOM.cpp" ...
+ "..\package_bgs\lb\BGModel.cpp" ...
+ "..\package_bgs\lb\BGModelFuzzyGauss.cpp" ...
+ "..\package_bgs\lb\BGModelFuzzySom.cpp" ...
+ "..\package_bgs\lb\BGModelGauss.cpp" ...
+ "..\package_bgs\lb\BGModelMog.cpp" ...
+ "..\package_bgs\lb\BGModelSom.cpp" ...
+ "..\package_bgs\LBP_MRF.cpp" ...
+ "..\package_bgs\LBP_MRF\MotionDetection.cpp" ...
+ "..\package_bgs\LBP_MRF\MEImage.cpp" ...
+ "..\package_bgs\LBP_MRF\MEHistogram.cpp" ...
+ "..\package_bgs\LBP_MRF\MEDefs.cpp" ...
+ "..\package_bgs\LBP_MRF\maxflow.cpp" ...
+ "..\package_bgs\LBP_MRF\graph.cpp" ...
+ "..\package_bgs\PixelBasedAdaptiveSegmenter.cpp" ...
+ "..\package_bgs\PBAS\PBAS.cpp" ...
+ "..\package_bgs\VuMeter.cpp" ...
+ "..\package_bgs\VuMeter\TBackgroundVuMeter.cpp" ...
+ "..\package_bgs\VuMeter\TBackground.cpp" ...
+ "..\package_bgs\KDE.cpp" ...
+ "..\package_bgs\KDE\NPBGSubtractor.cpp" ...
+ "..\package_bgs\KDE\NPBGmodel.cpp" ...
+ "..\package_bgs\KDE\KernelTable.cpp" ...
+ "..\package_bgs\IndependentMultimodal.cpp" ...
+ "..\package_bgs\IMBS\IMBS.cpp" ...
+ "..\package_bgs\MultiCue.cpp" ...
+ "..\package_bgs\SigmaDelta.cpp" ...
+ "..\package_bgs\SigmaDelta\sdLaMa091.cpp" ...
+ "..\package_bgs\SuBSENSE.cpp" ...
+ "..\package_bgs\LOBSTER.cpp" ...
+ "..\package_bgs\PAWCS.cpp" ...
+ "..\package_bgs\LBSP\LBSP.cpp" ...
+ "..\package_bgs\LBSP\LBSP_.cpp" ...
+ "..\package_bgs\LBSP\BackgroundSubtractorLBSP.cpp" ...
+ "..\package_bgs\LBSP\BackgroundSubtractorLBSP_.cpp" ...
+ "..\package_bgs\LBSP\BackgroundSubtractorLOBSTER.cpp" ...
+ "..\package_bgs\LBSP\BackgroundSubtractorPAWCS.cpp" ...
+ "..\package_bgs\LBSP\BackgroundSubtractorSuBSENSE.cpp" ...
+ "..\package_bgs\ViBe.cpp" ...
+ "..\package_bgs\ViBe\vibe-background-sequential.cpp" ...
+ "..\package_bgs\TwoPoints.cpp" ...
+ "..\package_bgs\TwoPoints\two_points.cpp"
diff --git a/wrapper_matlab/config/.gitignore b/wrapper_matlab/config/.gitignore
new file mode 100644
index 0000000..4e2a98b
--- /dev/null
+++ b/wrapper_matlab/config/.gitignore
@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except these files
+!.gitignore
diff --git a/wrapper_matlab/demo.m b/wrapper_matlab/demo.m
new file mode 100644
index 0000000..942e457
--- /dev/null
+++ b/wrapper_matlab/demo.m
@@ -0,0 +1,65 @@
+%{
+/*
+ * This file is part of BGSLibrary.
+ *
+ * BGSLibrary is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * BGSLibrary is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+ */
+%}
+% Example:
+% demo('FrameDifference')
+% demo('StaticFrameDifference')
+% See the full list of available algorithms in the BGSLibrary website.
+function demo(algorithm)
+if(nargin < 1)
+ algorithm = 'FrameDifference';
+end
+
+% Create video reader object
+%filename = 'visiontraffic.avi';
+filename = '../dataset/demo.avi';
+hsrc = vision.VideoFileReader(filename, ...
+ 'ImageColorSpace', 'RGB', ...
+ 'VideoOutputDataType', 'uint8');
+
+% Create background/foreground segmentation object
+hfg = backgroundSubtractor(algorithm);
+
+disp('Starting...');
+frameCnt = 1;
+while ~isDone(hsrc), %disp(frameCnt)
+ % Read frame
+ frame = step(hsrc);
+
+ % Compute foreground mask and background model
+ [fgMask, bgModel] = getForegroundMask(hfg, frame);
+
+ % View results
+ subplot(1,3,1), imshow(frame,'InitialMagnification','fit');
+ subplot(1,3,2), imshow(fgMask,'InitialMagnification','fit');
+ subplot(1,3,3), imshow(bgModel,'InitialMagnification','fit');
+ pause(0.01);
+
+ % Reset background model
+ % This step just demonstrates how to use reset method
+ if (frameCnt==15)
+ %reset(hfg);
+ %break;
+ end
+
+ frameCnt = frameCnt + 1;
+end
+disp('Finished!');
+
+release(hfg);
+release(hsrc);
diff --git a/wrapper_matlab/mxarray.h b/wrapper_matlab/mxarray.h
new file mode 100644
index 0000000..6a9afe9
--- /dev/null
+++ b/wrapper_matlab/mxarray.h
@@ -0,0 +1,1555 @@
+/** MxArray data conversion library.
+ *
+ * Copyright 2014 Kota Yamaguchi.
+ *
+ * The library provides mexplus::MxArray class for data conversion between
+ * mxArray* and C++ types. The static API's are the core of the high-level
+ * conversions.
+ *
+ * int value = MxArray::to<int>(prhs[0]);
+ * string value = MxArray::to<string>(prhs[0]);
+ * vector<double> value = MxArray::to<vector<double> >(prhs[0]);
+ *
+ * plhs[0] = MxArray::from(20);
+ * plhs[0] = MxArray::from("text value.");
+ * plhs[0] = MxArray::from(vector<double>(20, 0));
+ *
+ * Additionally, object API's are there to wrap around a complicated data
+ * access.
+ *
+ * ### Read access
+ *
+ * MxArray cell(prhs[0]); // Assumes cell array in prhs[0].
+ * int x = cell.at<int>(0);
+ * vector<double> y = cell.at<vector<double> >(1);
+ *
+ * MxArray numeric(prhs[0]); // Assumes numeric array in prhs[0].
+ * double x = numeric.at<double>(0);
+ * int y = numeric.at<int>(1);
+ *
+ * ### Write access
+ *
+ * MxArray cell(MxArray::Cell(1, 3));
+ * cell.set(0, 12);
+ * cell.set(1, "text value.");
+ * cell.set(2, vector<double>(4, 0));
+ * plhs[0] = cell.release();
+ *
+ * MxArray numeric(MxArray::Numeric<double>(2, 2));
+ * numeric.set(0, 0, 1);
+ * numeric.set(0, 1, 2);
+ * numeric.set(1, 0, 3);
+ * numeric.set(1, 1, 4);
+ * plhs[0] = numeric.release();
+ *
+ * To add your own data conversion, define in namespace mexplus a template
+ * specialization of MxArray::from() and MxArray::to().
+ *
+ */
+
+#ifndef INCLUDE_MEXPLUS_MXARRAY_H_
+#define INCLUDE_MEXPLUS_MXARRAY_H_
+
+#include <mex.h>
+#include <algorithm>
+#include <cstdint>
+#include <set>
+#include <string>
+#include <typeinfo>
+#include <vector>
+#include "mxtypes.h"
+
+#pragma warning(once : 4244)
+
+/** Macro definitions.
+ */
+#define MEXPLUS_CHECK_NOTNULL(pointer) \
+ if (!(pointer)) \
+ mexErrMsgIdAndTxt("mexplus:error", \
+ "Null pointer exception: %s:%d:%s `" #pointer "`.", \
+ __FILE__, \
+ __LINE__, \
+ __FUNCTION__)
+
+#define MEXPLUS_ERROR(...) mexErrMsgIdAndTxt("mexplus:error", __VA_ARGS__)
+#define MEXPLUS_WARNING(...) mexWarnMsgIdAndTxt("mexplus:warning", __VA_ARGS__)
+#define MEXPLUS_ASSERT(condition, ...) \
+ if (!(condition)) mexErrMsgIdAndTxt("mexplus:error", __VA_ARGS__)
+
+namespace mexplus {
+
+/** mxArray object wrapper for data conversion and manipulation.
+ *
+ * The class is similar to a combination of unique_ptr and wrapper around
+ * Matlab's matrix API. An MxArray object created from a mutable mxArray*
+ * pointer automatically frees its internal memory unless explicitly
+ * released. When MxArray is created from a const mxArray*, the object does not
+ * manage memory but still provides the same matrix API.
+ */
+class MxArray {
+ public:
+ /** Empty MxArray constructor. Use reset() to set a pointer.
+ */
+ MxArray() : array_(NULL), owner_(false) {}
+ /** NULL assignment.
+ */
+ MxArray& operator= (std::nullptr_t) {
+ reset();
+ return *this;
+ }
+ /** Move constructor.
+ */
+ MxArray(MxArray&& array) : array_(NULL), owner_(false) {
+ *this = std::move(array);
+ }
+ /** Move assignment.
+ */
+ MxArray& operator= (MxArray&& rhs) {
+ if (this != &rhs) {
+ array_ = rhs.array_;
+ owner_ = rhs.owner_;
+ rhs.array_ = NULL;
+ rhs.owner_ = false;
+ }
+ return *this;
+ }
+ /** MxArray constructor from const mxArray*. MxArray will not manage memory.
+ * @param array mxArray pointer given by mexFunction.
+ */
+ explicit MxArray(const mxArray* array) :
+ array_(const_cast<mxArray*>(array)),
+ owner_(false) {}
+ /** MxArray constructor from mutable mxArray*. MxArray will manage memory.
+ * @param array mxArray pointer.
+ */
+ explicit MxArray(mxArray* array) : array_(array), owner_(array != NULL) {}
+ /** Assignment from const mxArray*. MxArray will not manage memory.
+ */
+ MxArray& operator= (const mxArray* rhs) {
+ reset(rhs);
+ return *this;
+ }
+ /** Assignment from mutable mxArray*. MxArray will manage memory.
+ */
+ MxArray& operator= (mxArray* rhs) {
+ reset(rhs);
+ return *this;
+ }
+ /** MxArray constructor from scalar.
+ */
+ template <typename T>
+ explicit MxArray(const T& value) : array_(from(value)), owner_(true) {}
+ /** Destructor. Unreleased pointers will be destroyed.
+ */
+ virtual ~MxArray() {
+ if (array_ && owner_)
+ mxDestroyArray(array_);
+ }
+ /** Swap operation.
+ */
+ void swap(MxArray& rhs) {
+ if (this != &rhs) {
+ mxArray* array = rhs.array_;
+ bool owner = rhs.owner_;
+ rhs.array_ = array_;
+ rhs.owner_ = owner_;
+ array_ = array;
+ owner_ = owner;
+ }
+ }
+ /** Reset an mxArray to a const mxArray*.
+ *
+ * Caller must be VERY careful with this, as the behavior is undefined when
+ * the original mxArray* is destroyed. For example, the following will crash.
+ * @code
+ * MxArray foo;
+ * {
+ * MxArray bar(1);
+ * foo.reset(bar.get());
+ * }
+ * foo.toInt(); // Error!
+ * @endcode
+ */
+ void reset(const mxArray* array = NULL) {
+ if (array_ && owner_)
+ mxDestroyArray(array_);
+ array_ = const_cast<mxArray*>(array);
+ owner_ = false;
+ }
+ /** Reset an mxArray.
+ */
+ void reset(mxArray* array) {
+ if (array_ && owner_)
+ mxDestroyArray(array_);
+ array_ = array;
+ owner_ = (array != NULL);
+ }
+ /** Release managed mxArray* pointer, or clone if not owner.
+ * @return Unmanaged mxArray*. Always caller must destroy.
+ */
+ mxArray* release() {
+ MEXPLUS_CHECK_NOTNULL(array_);
+ mxArray* array = (owner_) ? array_ : clone();
+ array_ = NULL;
+ owner_ = false;
+ return array;
+ }
+ /** Clone mxArray. This always allocates new mxArray*.
+ * @return Unmanaged mxArray*. Always caller must destroy.
+ */
+ mxArray* clone() const {
+ MEXPLUS_CHECK_NOTNULL(array_);
+ mxArray* array = mxDuplicateArray(array_);
+ MEXPLUS_CHECK_NOTNULL(array);
+ return array;
+ }
+ /** Conversion to const mxArray*.
+ * @return const mxArray* pointer.
+ */
+ inline const mxArray* get() const { return array_; }
+ /** Get raw mxArray*.
+ * @return mxArray* pointer.
+ */
+ inline mxArray* getMutable() { return array_; }
+ /** Return true if the array is not NULL.
+ */
+ operator bool() const { return array_ != NULL; }
+ /** Return true if owner.
+ */
+ inline bool isOwner() const { return owner_; }
+ /** Create a new numeric (real or complex) matrix.
+ * @param rows Number of rows.
+ * @param columns Number of cols.
+ */
+ template <typename T>
+ static mxArray* Numeric(int rows = 1, int columns = 1);
+ /** Create a new numeric (real or complex) matrix.
+ * @param ndim Number of dimensions.
+ * @param dims Dimensions array. Each element in the dimensions array
+ * contains the size of the array in that dimension.
+ */
+ template <typename T>
+ static mxArray* Numeric(std::vector<std::size_t> dims);
+ /** Create a new logical matrix.
+ * @param rows Number of rows.
+ * @param columns Number of cols.
+ */
+ static mxArray* Logical(int rows = 1, int columns = 1) {
+ mxArray* logical_array = mxCreateLogicalMatrix(rows, columns);
+ MEXPLUS_CHECK_NOTNULL(logical_array);
+ return logical_array;
+ }
+ /** Create a new cell matrix.
+ * @param rows Number of rows.
+ * @param columns Number of cols.
+ *
+ * Example:
+ * @code
+ * MxArray cell_array = MxArray::Cell(1, 2);
+ * cell_array.set(0, 1);
+ * cell_array.set(1, "another value");
+ * plhs[0] = cell_array.release();
+ * @endcode
+ */
+ static mxArray* Cell(int rows = 1, int columns = 1) {
+ mxArray* cell_array = mxCreateCellMatrix(rows, columns);
+ MEXPLUS_CHECK_NOTNULL(cell_array);
+ return cell_array;
+ }
+ /** Generic constructor for a struct matrix.
+ * @param fields field names.
+ * @param nfields number of field names.
+ * @param rows size of the first dimension.
+ * @param columns size of the second dimension.
+ *
+ * Example:
+ * @code
+ * const char* fields[] = {"field1", "field2"};
+ * MxArray struct_array(MxArray::Struct(2, fields));
+ * struct_array.set("field1", 1);
+ * struct_array.set("field2", "field2 value");
+ * plhs[0] = struct_array.release();
+ * @endcode
+ */
+ static mxArray* Struct(int nfields = 0,
+ const char** fields = NULL,
+ int rows = 1,
+ int columns = 1) {
+ mxArray* struct_array = mxCreateStructMatrix(rows,
+ columns,
+ nfields,
+ fields);
+ MEXPLUS_CHECK_NOTNULL(struct_array);
+ return struct_array;
+ }
+ /** mxArray* importer methods.
+ */
+ template <typename T>
+ static mxArray* from(const T& value) { return fromInternal<T>(value); }
+ static mxArray* from(const char* value) {
+ mxArray* array = mxCreateString(value);
+ MEXPLUS_CHECK_NOTNULL(array);
+ return array;
+ }
+ static mxArray* from(int32_t value) {
+ mxArray* array = mxCreateNumericMatrix(1, 1, mxINT32_CLASS, mxREAL);
+ MEXPLUS_CHECK_NOTNULL(array);
+ *reinterpret_cast<int32_t*>(mxGetData(array)) = value;
+ return array;
+ }
+ /** mxArray* exporter methods.
+ */
+ template <typename T>
+ static void to(const mxArray* array, T* value) {
+ toInternal<T>(array, value);
+ }
+ template <typename T>
+ static T to(const mxArray* array) {
+ T value;
+ toInternal<T>(array, &value);
+ return value;
+ }
+ /** mxArray* element reader methods.
+ */
+ template <typename T>
+ static T at(const mxArray* array, mwIndex index) {
+ T value;
+ atInternal<T>(array, index, &value);
+ return value;
+ }
+ template <typename T>
+ static void at(const mxArray* array, mwIndex index, T* value) {
+ atInternal<T>(array, index, value);
+ }
+ static const mxArray* at(const mxArray* array, mwIndex index) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_ASSERT(mxIsCell(array), "Expected a cell array.");
+ return mxGetCell(array, index);
+ }
+ template <typename T>
+ static void at(const mxArray* array,
+ const std::string& field,
+ T* value,
+ mwIndex index = 0) {
+ atInternal<T>(array, field, index, value);
+ }
+ static const mxArray* at(const mxArray* array,
+ const std::string& field,
+ mwIndex index = 0) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_ASSERT(mxIsStruct(array), "Expected a struct array.");
+ return mxGetField(array, index, field.c_str());
+ }
+ /** mxArray* element writer methods.
+ */
+ template <typename T>
+ static void set(mxArray* array, mwIndex index, const T& value) {
+ setInternal<T>(array, index, value);
+ }
+ static void set(mxArray* array, mwIndex index, mxArray* value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_CHECK_NOTNULL(value);
+ MEXPLUS_ASSERT(mxIsCell(array), "Expected a cell array.");
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ mxDestroyArray(mxGetCell(array, index));
+ mxSetCell(array, index, value);
+ }
+ template <typename T>
+ static void set(mxArray* array,
+ const std::string& field,
+ const T& value,
+ mwIndex index = 0) {
+ setInternal<T>(array, field, index, value);
+ }
+ static void set(mxArray* array,
+ const std::string& field,
+ mxArray* value,
+ mwIndex index = 0) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_CHECK_NOTNULL(value);
+ MEXPLUS_ASSERT(mxIsStruct(array), "Expected a struct array.");
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ int field_number = mxGetFieldNumber(array, field.c_str());
+ if (field_number < 0) {
+ field_number = mxAddField(array, field.c_str());
+ MEXPLUS_ASSERT(field_number >= 0,
+ "Failed to create a field '%s'",
+ field.c_str());
+ }
+ mxDestroyArray(mxGetFieldByNumber(array, index, field_number));
+ mxSetFieldByNumber(array, index, field_number, value);
+ }
+
+ /** Convert MxArray to a specified type.
+ */
+ template <typename T>
+ T to() const {
+ T value;
+ toInternal<T>(array_, &value);
+ return value;
+ }
+ template <typename T>
+ void to(T* value) const { toInternal<T>(array_, value); }
+ /** Template for element accessor.
+ * @param index index of the array element.
+ * @return value of the element at index.
+ *
+ *
+ * Example:
+ * @code
+ * MxArray array(prhs[0]);
+ * double value = array.at<double>(0);
+ * @endcode
+ */
+ template <typename T>
+ T at(mwIndex index) const {
+ T value;
+ atInternal<T>(array_, index, &value);
+ return value;
+ }
+ template <typename T>
+ void at(mwIndex index, T* value) const {
+ atInternal<T>(array_, index, value);
+ }
+ const mxArray* at(mwIndex index) const {
+ return at(array_, index);
+ }
+ /** Template for element accessor.
+ * @param row index of the first dimension.
+ * @param column index of the second dimension.
+ * @return value of the element at (row, column).
+ */
+ template <typename T>
+ T at(mwIndex row, mwIndex column) const;
+ /** Template for element accessor.
+ * @param subscripts subscript indexes of elements.
+ * @return value of the element at subscript index.
+ */
+ template <typename T>
+ T at(const std::vector<mwIndex>& subscripts) const;
+ /** Struct element accessor.
+ * @param field field name of the struct array.
+ * @param index index of the struct array.
+ * @return value of the element at the specified field.
+ */
+ template <typename T>
+ T at(const std::string& field, mwIndex index = 0) const {
+ T value;
+ atInternal<T>(array_, field, index, &value);
+ return value;
+ }
+ template <typename T>
+ void at(const std::string& field, T* value, mwIndex index = 0) const {
+ atInternal<T>(array_, field, index, value);
+ }
+ const mxArray* at(const std::string& field, mwIndex index = 0) const {
+ return at(array_, field, index);
+ }
+
+ /** Template for element write accessor.
+ * @param index offset of the array element.
+ * @param value value of the field.
+ */
+ template <typename T>
+ void set(mwIndex index, const T& value) {
+ setInternal<T>(array_, index, value);
+ }
+ /** Template for element write accessor.
+ * @param row index of the first dimension of the array element.
+ * @param column index of the first dimension of the array element.
+ * @param value value of the field.
+ */
+ template <typename T>
+ void set(mwIndex row, mwIndex column, const T& value);
+ /** Template for element write accessor.
+ * @param subscripts subscript index of the element.
+ * @param value value of the field.
+ */
+ template <typename T>
+ void set(const std::vector<mwIndex>& subscripts, const T& value);
+ /** Cell element write accessor.
+ * @param index index of the element.
+ * @param value cell element to be inserted.
+ */
+ void set(mwIndex index, mxArray* value) {
+ MEXPLUS_ASSERT(isOwner(), "Must be an owner to set.");
+ set(array_, index, value);
+ }
+ /** Cell element write accessor.
+ * @param row index of the first dimension of the array element.
+ * @param column index of the first dimension of the array element.
+ * @param value cell element to be inserted.
+ */
+ void set(mwIndex row, mwIndex column, mxArray* value) {
+ MEXPLUS_ASSERT(isOwner(), "Must be an owner to set.");
+ set(array_, subscriptIndex(row, column), value);
+ }
+ /** Cell element write accessor.
+ * @param subscripts subscript index of the element.
+ * @param value value of the field.
+ */
+ void set(const std::vector<mwIndex>& subscripts, mxArray* value) {
+ MEXPLUS_ASSERT(isOwner(), "Must be an owner to set.");
+ set(array_, subscriptIndex(subscripts), value);
+ }
+ /** Struct element write accessor.
+ * @param field field name of the struct array.
+ * @param value value of the field.
+ * @param index linear index of the struct array element.
+ */
+ template <typename T>
+ void set(const std::string& field, const T& value, mwIndex index = 0) {
+ MEXPLUS_ASSERT(isOwner(), "Must be an owner to set.");
+ setInternal<T>(array_, field, index, value);
+ }
+ /** Struct element write accessor.
+ * @param field field name of the struct array.
+ * @param value value of the field to be inserted.
+ * @param index linear index of the struct array element.
+ */
+ void set(const std::string& field, mxArray* value, mwIndex index = 0) {
+ MEXPLUS_ASSERT(isOwner(), "Must be an owner to set.");
+ set(array_, field, value, index);
+ }
+ /** Get raw data pointer.
+ * @return pointer T*. If MxArray is not compatible, return NULL.
+ */
+ template <typename T>
+ T* getData() const;
+ /** Get raw data pointer to imaginary part.
+ * @return pointer T*. If MxArray is not compatible, return NULL.
+ */
+ template <typename T>
+ T* getImagData() const;
+ mxLogical* getLogicals() const {
+ MEXPLUS_CHECK_NOTNULL(array_);
+ MEXPLUS_ASSERT(isLogical(),
+ "Expected a logical array but %s.",
+ className().c_str());
+ return mxGetLogicals(array_);
+ }
+ mxChar* getChars() const {
+ MEXPLUS_CHECK_NOTNULL(array_);
+ MEXPLUS_ASSERT(isChar(),
+ "Expected a char array but %s.",
+ className().c_str());
+ return mxGetChars(array_);
+ }
+ /** Class ID of mxArray.
+ */
+ inline mxClassID classID() const { return mxGetClassID(array_); }
+ /** Class name of mxArray.
+ */
+ inline const std::string className() const {
+ return std::string(mxGetClassName(array_));
+ }
+ /** Number of elements in an array.
+ */
+ inline mwSize size() const {
+ return static_cast<mwSize>(mxGetNumberOfElements(array_));
+ }
+ /** Number of dimensions.
+ */
+ inline mwSize dimensionSize() const {
+ return mxGetNumberOfDimensions(array_);
+ }
+ /** Array of each dimension.
+ */
+ inline std::vector<mwSize> dimensions() const {
+ const mwSize* dimensions = mxGetDimensions(array_);
+ return std::vector<mwSize>(dimensions, dimensions + dimensionSize());
+ }
+ /** Number of rows in an array.
+ */
+ inline mwSize rows() const { return static_cast<mwSize>(mxGetM(array_)); }
+ /** Number of columns in an array.
+ */
+ inline mwSize cols() const { return static_cast<mwSize>(mxGetN(array_)); }
+ /** Number of fields in a struct array.
+ */
+ inline int fieldSize() const { return mxGetNumberOfFields(array_); }
+ /** Get field name of a struct array.
+ * @param index index of the struct array.
+ * @return std::string.
+ */
+ std::string fieldName(int index) const {
+ const char* field = mxGetFieldNameByNumber(array_, index);
+ MEXPLUS_ASSERT(field, "Failed to get field name at %d.", index);
+ return std::string(field);
+ }
+ /** Get field names of a struct array.
+ * @return std::vector<std::string> of struct field names.
+ */
+ std::vector<std::string> fieldNames() const {
+ MEXPLUS_ASSERT(isStruct(), "Expected a struct array.");
+ std::vector<std::string> fields(fieldSize());
+ for (size_t i = 0; i < fields.size(); ++i)
+ fields[i] = fieldName(i);
+ return fields;
+ }
+ /** Number of elements in IR, PR, and PI arrays.
+ */
+ inline mwSize nonZeroMax() const { return mxGetNzmax(array_); }
+ /** Offset from first element to desired element.
+ * @param row index of the first dimension of the array.
+ * @param column index of the second dimension of the array.
+ * @return linear offset of the specified subscript index.
+ */
+ mwIndex subscriptIndex(mwIndex row, mwIndex column) const {
+ MEXPLUS_ASSERT(row < rows() && column < cols(),
+ "Subscript is out of range.");
+ mwIndex subscripts[] = {row, column};
+ return mxCalcSingleSubscript(array_, 2, subscripts);
+ }
+ /** Offset from first element to desired element.
+ * @param subscripts subscript indexes of the array.
+ * @return linear offset of the specified subscript index.
+ */
+ mwIndex subscriptIndex(const std::vector<mwIndex>& subscripts) const {
+ return mxCalcSingleSubscript(array_,
+ static_cast<mwSize>(subscripts.size()),
+ const_cast<mwIndex*>(&subscripts[0]));
+ }
+ /** Determine whether input is cell array.
+ */
+ inline bool isCell() const { return mxIsCell(array_); }
+ /** Determine whether input is string array.
+ */
+ inline bool isChar() const { return mxIsChar(array_); }
+ /** Determine whether input is vector array.
+ */
+ inline bool isVector() const {
+ return mxGetNumberOfDimensions(array_) == 2 &&
+ (mxGetM(array_) == 1 || mxGetN(array_) == 1);
+ }
+ /** Determine whether array is integral type.
+ */
+ inline bool isIntegral(const char* name) const {
+ return mxIsNumeric(array_) && !mxIsDouble(array_);
+ }
+ /** Determine whether array is member of specified class.
+ */
+ inline bool isClass(const char* name) const {
+ return mxIsClass(array_, name);
+ }
+ /** Determine whether data is complex.
+ */
+ inline bool isComplex() const { return mxIsComplex(array_); }
+ /** Determine whether mxArray represents data as double-precision,
+ * floating-point numbers.
+ */
+ inline bool isDouble() const { return mxIsDouble(array_); }
+ /** Determine whether array is empty.
+ */
+ inline bool isEmpty() const { return mxIsEmpty(array_); }
+ /** Determine whether input is finite.
+ */
+ static inline bool IsFinite(double value) { return mxIsFinite(value); }
+ /** Determine whether array was copied from MATLAB global workspace.
+ */
+ inline bool isFromGlobalWS() const { return mxIsFromGlobalWS(array_); }
+ /** Determine whether input is infinite.
+ */
+ static inline bool IsInf(double value) { return mxIsInf(value); }
+ /** Determine whether array represents data as signed 8-bit integers.
+ */
+ inline bool isInt8() const { return mxIsInt8(array_); }
+ /** Determine whether array represents data as signed 16-bit integers.
+ */
+ inline bool isInt16() const { return mxIsInt16(array_); }
+ /** Determine whether array represents data as signed 32-bit integers.
+ */
+ inline bool isInt32() const { return mxIsInt32(array_); }
+ /** Determine whether array represents data as signed 64-bit integers.
+ */
+ inline bool isInt64() const { return mxIsInt64(array_); }
+ /** Determine whether array is of type mxLogical.
+ */
+ inline bool isLogical() const { return mxIsLogical(array_); }
+ /** Determine whether scalar array is of type mxLogical.
+ */
+ inline bool isLogicalScalar() const { return mxIsLogicalScalar(array_); }
+ /** Determine whether scalar array of type mxLogical is true.
+ */
+ inline bool isLogicalScalarTrue() const {
+ return mxIsLogicalScalarTrue(array_);
+ }
+ /** Determine whether array is numeric.
+ */
+ inline bool isNumeric() const { return mxIsNumeric(array_); }
+ /** Determine whether array represents data as single-precision,
+ * floating-point numbers.
+ */
+ inline bool isSingle() const { return mxIsSingle(array_); }
+ /** Determine whether input is sparse array.
+ */
+ inline bool isSparse() const { return mxIsSparse(array_); }
+ /** Determine whether input is structure array.
+ */
+ inline bool isStruct() const { return mxIsStruct(array_); }
+ /** Determine whether array represents data as unsigned 8-bit integers.
+ */
+ inline bool isUint8() const { return mxIsUint8(array_); }
+ /** Determine whether array represents data as unsigned 16-bit integers.
+ */
+ inline bool isUint16() const { return mxIsUint16(array_); }
+ /** Determine whether array represents data as unsigned 32-bit integers.
+ */
+ inline bool isUint32() const { return mxIsUint32(array_); }
+ /** Determine whether array represents data as unsigned 64-bit integers.
+ */
+ inline bool isUint64() const { return mxIsUint64(array_); }
+ /** Determine whether a struct array has a specified field.
+ */
+ bool hasField(const std::string& field_name, mwIndex index = 0) const {
+ return isStruct() &&
+ mxGetField(array_, index, field_name.c_str()) != NULL;
+ }
+ /** Element size.
+ */
+ int elementSize() const {
+ return static_cast<int>(mxGetElementSize(array_));
+ }
+ /** Determine whether input is NaN (Not-a-Number).
+ */
+ static inline bool IsNaN(double value) { return mxIsNaN(value); }
+ /** Value of infinity.
+ */
+ static inline double Inf() { return mxGetInf(); }
+ /** Value of NaN (Not-a-Number).
+ */
+ static inline double NaN() { return mxGetNaN(); }
+ /** Value of EPS.
+ */
+ static inline double Eps() { return mxGetEps(); }
+
+ private:
+ /** Copy constructor is prohibited except internally.
+ */
+ MxArray(const MxArray& array);
+ // MxArray(const MxArray& array) = delete;
+ /** Copy assignment operator is prohibited.
+ */
+ MxArray& operator=(const MxArray& rhs);
+ // MxArray& operator=(const MxArray& rhs) = delete;
+
+ /*************************************************************/
+ /** Templated mxArray importers **/
+ /*************************************************************/
+
+ /** Fundamental numerics.
+ */
+ template <typename T>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxArithmeticType<T>::value, T>::type& value);
+ /** Complex types, complex<float> or complex<double>.
+ */
+ template <typename T>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxComplexType<T>::value, T>::type& value);
+ /** Container with fundamental numerics, i.e. vector<double>.
+ */
+ template <typename Container>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxArithmeticCompound<Container>::value,
+ Container>::type& value);
+ /** Container with complex numbers, i.e. vector<complex<double>>.
+ */
+ template <typename Container>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxComplexCompound<Container>::value, Container>::type& value);
+ /** Char type */
+ template <typename T>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxCharType<T>::value, T>::type& value);
+ /** Containter with signed char.
+ */
+ template <typename Container>
+ static mxArray* fromInternal(const typename std::enable_if<
+ (MxCharCompound<Container>::value) &&
+ (std::is_signed<typename Container::value_type>::value),
+ Container>::type& value);
+ /** Container with unsigned char.
+ */
+ template <typename Container>
+ static mxArray* fromInternal(const typename std::enable_if<
+ (MxCharCompound<Container>::value) &&
+ !(std::is_signed<typename Container::value_type>::value),
+ Container>::type& value);
+ /** Logicals.
+ */
+ template <typename T>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxLogicalType<T>::value, T>::type& value);
+ /** Container with logicals.
+ */
+ template <typename Container>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxLogicalCompound<Container>::value, Container>::type& value);
+ /** Container with cell type content.
+ */
+ template <typename Container>
+ static mxArray* fromInternal(const typename std::enable_if<
+ MxCellCompound<Container>::value, Container>::type& value);
+
+ /*************************************************************/
+ /** Templated mxArray exporters **/
+ /*************************************************************/
+
+ /** Singleton types.
+ */
+ template <typename T>
+ static void toInternal(const mxArray* array,
+ typename std::enable_if<
+ MxArithmeticType<T>::value ||
+ MxComplexType<T>::value ||
+ MxLogicalType<T>::value ||
+ MxCharType<T>::value,
+ T
+ >::type* value) {
+ atInternal<T>(array, 0, value);
+ }
+ /** Vector types.
+ */
+ template <typename T>
+ static void toInternal(const mxArray* array,
+ typename std::enable_if<
+ MxComplexOrArithmeticCompound<T>::value ||
+ MxLogicalCompound<T>::value ||
+ MxCharCompound<T>::value,
+ T
+ >::type* value);
+ /** Nested types (leads into recursive deduction).
+ */
+ template <typename T>
+ static void toInternal(const mxArray* array,
+ typename std::enable_if<
+ MxCellType<T>::value &&
+ (!std::is_compound<T>::value ||
+ MxCellType<typename T::value_type>::value),
+ T
+ >::type* value);
+
+ /*************************************************************/
+ /** Templated mxArray getters **/
+ /*************************************************************/
+
+ /** Fundamental numeric types.
+ */
+ template <typename T>
+ static void atInternal(const mxArray* array, mwIndex index,
+ typename std::enable_if<
+ MxComplexOrArithmeticType<T>::value ||
+ MxLogicalType<T>::value ||
+ MxCharType<T>::value,
+ T>::type* value);
+ /** Converter for nested types.
+ */
+ template <typename T>
+ static void atInternal(const mxArray* array, mwIndex index,
+ typename std::enable_if<
+ std::is_compound<T>::value &&
+ !MxComplexType<T>::value,
+ T
+ >::type* value);
+ /** Structure access.
+ */
+ template <typename T>
+ static void atInternal(const mxArray* array,
+ const std::string& field,
+ mwIndex index, T* value);
+
+ /*************************************************************/
+ /** Templated mxArray element setters **/
+ /*************************************************************/
+
+ /** Fundamental numeric and complex types.
+ */
+ template <typename T>
+ static void setInternal(mxArray* array, mwIndex index,
+ const typename std::enable_if<
+ !std::is_compound<T>::value ||
+ MxComplexType<T>::value,
+ T
+ >::type& value);
+ /** Container types.
+ */
+ template <typename T>
+ static void setInternal(mxArray* array, mwIndex index,
+ const typename std::enable_if<
+ MxCellType<T>::value,
+ T
+ >::type& value);
+ /** Structure access.
+ */
+ template <typename T>
+ static void setInternal(mxArray* array, const std::string& field,
+ mwIndex index, const T& value);
+
+ /*************************************************************/
+ /** Assignment helpers (for MxArray.to<type>(value)) **/
+ /*************************************************************/
+
+ /** Explicit integer element assignment.
+ */
+ template <typename T, typename R>
+ static void assignTo(const mxArray* array,
+ mwIndex index, typename std::enable_if<
+ std::is_integral<R>::value,
+ R
+ >::type* value) {
+ MEXPLUS_ASSERT(!mxIsComplex(array), "Non-complex array expected!");
+ *value = (R)*(reinterpret_cast<T*>(mxGetData(array)) + index);
+ }
+ /** Explicit floating point element assignment.
+ */
+ template <typename T, typename R>
+ static void assignTo(const mxArray* array,
+ mwIndex index,
+ typename std::enable_if<
+ std::is_floating_point<R>::value,
+ R
+ >::type* value) {
+ if (mxIsComplex(array)) {
+ T real_part = *(reinterpret_cast<T*>(mxGetPr(array)) + index);
+ T imag_part = *(reinterpret_cast<T*>(mxGetPi(array)) + index);
+ *value = std::abs(std::complex<R>(real_part, imag_part));
+ } else {
+ *value = *(reinterpret_cast<T*>(mxGetData(array)) + index);
+ }
+ }
+ /** Explicit complex element assignment.
+ */
+ template <typename T, typename R>
+ static void assignTo(const mxArray* array,
+ mwIndex index,
+ typename std::enable_if<
+ MxComplexType<R>::value,
+ R
+ >::type* value) {
+ typename R::value_type real_part, imag_part;
+ if (mxIsComplex(array)) {
+ real_part = *(reinterpret_cast<T*>(mxGetPr(array)) + index);
+ imag_part = *(reinterpret_cast<T*>(mxGetPi(array)) + index);
+ } else {
+ real_part = *(reinterpret_cast<T*>(mxGetData(array)) + index);
+ imag_part = 0.0;
+ }
+ *value = std::complex<typename R::value_type>(real_part, imag_part);
+ }
+ /** Explicit char (signed) element assignment.
+ */
+ template <typename R>
+ static void assignCharTo(const mxArray* array,
+ mwIndex index,
+ typename std::enable_if<
+ std::is_signed<R>::value,
+ R
+ >::type* value) {
+ typedef typename std::make_signed<mxChar>::type SignedMxChar;
+ *value = *(reinterpret_cast<SignedMxChar*>(mxGetChars(array)) + index);
+ }
+ /** Explicit char (unsigned) element assignment.
+ */
+ template <typename R>
+ static void assignCharTo(const mxArray* array,
+ mwIndex index,
+ typename std::enable_if<
+ !std::is_signed<R>::value,
+ R
+ >::type* value) {
+ *value = *(mxGetChars(array) + index);
+ }
+ /** Explicit cell element assignment.
+ */
+ template <typename T>
+ static void assignCellTo(const mxArray* array, mwIndex index, T* value) {
+ const mxArray* element = mxGetCell(array, index);
+ MEXPLUS_CHECK_NOTNULL(element);
+ toInternal<T>(element, value); // Recursion for nested types.
+ }
+ /** Explicit numeric array assignment.
+ */
+ template <typename T, typename R>
+ static void assignTo(const mxArray* array,
+ typename std::enable_if<
+ MxArithmeticCompound<R>::value ||
+ MxLogicalCompound<R>::value ||
+ MxCharCompound<R>::value,
+ R
+ >::type* value) {
+ mwSize array_size = static_cast<mwSize>(mxGetNumberOfElements(array));
+ if (!mxIsComplex(array)) {
+ T* data_pointer = reinterpret_cast<T*>(mxGetData(array));
+ value->assign(data_pointer, data_pointer + array_size);
+ } else {
+ T* real_part = reinterpret_cast<T*>(mxGetPr(array));
+ T* imag_part = reinterpret_cast<T*>(mxGetPi(array));
+ value->resize(array_size);
+ for (mwSize i = 0; i < array_size; ++i) {
+ double mag = std::abs(std::complex<double>(
+ static_cast<double>(*(real_part++)),
+ static_cast<double>(*(imag_part++))));
+ (*value)[i] = static_cast<T>(mag);
+ }
+ }
+ }
+ /** Explicit complex array assigment.
+ */
+ template <typename T, typename R>
+ static void assignTo(const mxArray* array,
+ typename std::enable_if<
+ MxComplexCompound<R>::value,
+ R
+ >::type* value) {
+ mwSize array_size = mxGetNumberOfElements(array);
+ value->resize(array_size);
+ if (!mxIsComplex(array)) {
+ T* data_pointer = reinterpret_cast<T*>(mxGetData(array));
+ for (mwSize i = 0; i < array_size; ++i) {
+ (*value)[i] = typename R::value_type(*(data_pointer++), 0.0f);
+ }
+ } else {
+ T* real_part = reinterpret_cast<T*>(mxGetPr(array));
+ T* imag_part = reinterpret_cast<T*>(mxGetPi(array));
+ for (mwSize i = 0; i < array_size; ++i) {
+ (*value)[i] = typename R::value_type(*(real_part++), *(imag_part++));
+ }
+ }
+ }
+ /** Explicit char (signed) array assignment.
+ */
+ template <typename R>
+ static void assignStringTo(const mxArray* array,
+ typename std::enable_if<
+ std::is_signed<typename R::value_type>::value,
+ R
+ >::type* value) {
+ typedef typename std::make_signed<mxChar>::type SignedMxChar;
+ SignedMxChar* data_pointer = reinterpret_cast<SignedMxChar*>(
+ mxGetChars(array));
+ value->assign(data_pointer, data_pointer + mxGetNumberOfElements(array));
+ }
+ /** Explicit char (unsigned) array assignment.
+ */
+ template <typename R>
+ static void assignStringTo(const mxArray* array,
+ typename std::enable_if<
+ !std::is_signed<typename R::value_type>::value,
+ R>::type* value) {
+ mxChar* data_pointer = mxGetChars(array);
+ value->assign(data_pointer, data_pointer + mxGetNumberOfElements(array));
+ }
+ /** Explicit cell array assignment.
+ */
+ template <typename T>
+ static void assignCellTo(const mxArray* array, T* value) {
+ mwSize array_size = static_cast<mwSize>(mxGetNumberOfElements(array));
+ value->resize(array_size);
+ for (size_t i = 0; i < array_size; ++i) {
+ const mxArray* element = mxGetCell(array, i);
+ MEXPLUS_CHECK_NOTNULL(element);
+ (*value)[i] = to<typename T::value_type>(element);
+ }
+ }
+
+ /*************************************************************/
+ /** Assignment helpers (for MxArray.set<type>(i, value)) **/
+ /*************************************************************/
+
+ /** Explicit numeric element assignment.
+ */
+ template <typename R, typename T>
+ static void assignFrom(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ MxArithmeticType<T>::value || MxCharType<T>::value,
+ T
+ >::type& value) {
+ if (mxIsComplex(array)) {
+ *(reinterpret_cast<R*>(mxGetPr(array)) + index) = value;
+ *(reinterpret_cast<R*>(mxGetPi(array)) + index) = 0.0;
+ } else {
+ *(reinterpret_cast<R*>(mxGetData(array)) + index) = value;
+ }
+ }
+ /** Explicit complex element assignment.
+ */
+ template <typename R, typename T>
+ static void assignFrom(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ MxComplexType<T>::value,
+ T
+ >::type& value) {
+ if (mxIsComplex(array)) {
+ *(reinterpret_cast<R*>(mxGetPr(array)) + index) = value.real();
+ *(reinterpret_cast<R*>(mxGetPi(array)) + index) = value.imag();
+ } else {
+ *(reinterpret_cast<R*>(mxGetData(array)) + index) = std::abs(value);
+ }
+ }
+ template <typename T>
+ static void assignCharFrom(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ std::is_floating_point<T>::value,
+ T
+ >::type& value) {
+ *(mxGetChars(array) + index) = value; // whoever needs this...
+ }
+ template <typename T>
+ static void assignCharFrom(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ std::is_integral<T>::value &&
+ std::is_signed<T>::value,
+ T
+ >::type& value) {
+ *(mxGetChars(array) + index) = reinterpret_cast<const typename
+ std::make_unsigned<T>::type&>(value);
+ }
+ template <typename T>
+ static void assignCharFrom(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ std::is_integral<T>::value &&
+ !std::is_signed<T>::value,
+ T
+ >::type& value) {
+ *(mxGetChars(array) + index) = value;
+ }
+
+ template <typename T>
+ static void assignCharFrom(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ MxComplexType<T>::value,
+ T
+ >::type& value) {
+ *(mxGetChars(array) + index) = std::abs(value); // whoever needs it...
+ }
+
+ /** Pointer to the mxArray C object.
+ */
+ mxArray* array_;
+ /** Flag to enable resource management.
+ */
+ bool owner_;
+};
+
+/*************************************************************/
+/** Templated mxArray importers **/
+/*************************************************************/
+
+/** Fundamental numeric type.
+ */
+template <typename T>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxArithmeticType<T>::value, T>::type& value) {
+ mxArray* array = mxCreateNumericMatrix(1,
+ 1,
+ MxTypes<T>::class_id,
+ MxTypes<T>::complexity);
+ MEXPLUS_CHECK_NOTNULL(array);
+ *reinterpret_cast<T*>(mxGetData(array)) = value;
+ return array;
+}
+
+/** Complex type, complex<float> or complex<double>.
+ */
+template <typename T>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxComplexType<T>::value, T>::type& value) {
+ mxArray* array = mxCreateNumericMatrix(1, 1,
+ MxTypes<T>::class_id,
+ MxTypes<T>::complexity);
+ MEXPLUS_CHECK_NOTNULL(array);
+ *reinterpret_cast<typename T::value_type*>(mxGetPr(array)) = value.real();
+ *reinterpret_cast<typename T::value_type*>(mxGetPi(array)) = value.imag();
+
+ return array;
+}
+
+/** Container with fundamental numerics, i.e. vector<double>.
+ */
+template <typename Container>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxArithmeticCompound<Container>::value, Container>::type& value) {
+ typedef typename Container::value_type ValueType;
+ mxArray* array = mxCreateNumericMatrix(1,
+ value.size(),
+ MxTypes<ValueType>::class_id,
+ MxTypes<ValueType>::complexity);
+ MEXPLUS_CHECK_NOTNULL(array);
+ std::copy(value.begin(),
+ value.end(),
+ reinterpret_cast<ValueType*>(mxGetData(array)));
+ return array;
+}
+
+/** Container with complex numbers, i.e. vector<complex<double>>.
+ */
+template <typename Container>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxComplexCompound<Container>::value, Container>::type& value) {
+ typedef typename Container::value_type ContainerValueType;
+ typedef typename ContainerValueType::value_type ValueType;
+ mxArray* array = mxCreateNumericMatrix(1,
+ value.size(),
+ MxTypes<ContainerValueType>::class_id,
+ mxCOMPLEX);
+ MEXPLUS_CHECK_NOTNULL(array);
+ ValueType* real = reinterpret_cast<ValueType*>(mxGetPr(array));
+ ValueType* imag = reinterpret_cast<ValueType*>(mxGetPi(array));
+ typename Container::const_iterator it;
+ for (it = value.begin(); it != value.end(); it++) {
+ *real++ = (*it).real();
+ *imag++ = (*it).imag();
+ }
+ return array;
+}
+
+template <typename T>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxCharType<T>::value, T>::type& value) {
+ const char char_array[] = {static_cast<char>(value), 0};
+ mxArray* array = mxCreateString(char_array);
+ MEXPLUS_CHECK_NOTNULL(array);
+ return array;
+}
+
+template <typename Container>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ (MxCharCompound<Container>::value) &&
+ (std::is_signed<typename Container::value_type>::value),
+ Container>::type& value) {
+ typedef typename std::make_unsigned<typename Container::value_type>::type
+ UnsignedValue;
+ const mwSize dimensions[] = {1, static_cast<mwSize>(value.size())};
+ mxArray* array = mxCreateCharArray(2, dimensions);
+ MEXPLUS_CHECK_NOTNULL(array);
+ mxChar* array_data = mxGetChars(array);
+ for (typename Container::const_iterator it = value.begin();
+ it != value.end();
+ ++it) {
+ *(array_data++) = reinterpret_cast<const UnsignedValue&>(*it);
+ }
+ return array;
+}
+
+template <typename Container>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ (MxCharCompound<Container>::value) &&
+ !(std::is_signed<typename Container::value_type>::value),
+ Container>::type& value) {
+ const mwSize dimensions[] = {1, static_cast<mwSize>(value.size())};
+ mxArray* array = mxCreateCharArray(2, dimensions);
+ MEXPLUS_CHECK_NOTNULL(array);
+ std::copy(value.begin(), value.end(), mxGetChars(array));
+ return array;
+}
+
+template <typename T>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxLogicalType<T>::value, T>::type& value) {
+ mxArray* array = mxCreateLogicalScalar(value);
+ MEXPLUS_CHECK_NOTNULL(array);
+ return array;
+}
+
+template <typename Container>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxLogicalCompound<Container>::value, Container>::type& value) {
+ mxArray* array = mxCreateLogicalMatrix(1, value.size());
+ MEXPLUS_CHECK_NOTNULL(array);
+ std::copy(value.begin(), value.end(), mxGetLogicals(array));
+ return array;
+}
+
+template <typename Container>
+mxArray* MxArray::fromInternal(const typename std::enable_if<
+ MxCellCompound<Container>::value, Container>::type& value) {
+ mxArray* array = mxCreateCellMatrix(1, value.size());
+ MEXPLUS_CHECK_NOTNULL(array);
+ mwIndex index = 0;
+ for (typename Container::const_iterator it = value.begin();
+ it != value.end();
+ ++it) {
+ mxArray* new_item = from(*it); // Safe in case if from() fails.
+ mxDestroyArray(mxGetCell(array, index));
+ mxSetCell(array, index++, new_item);
+ }
+ return array;
+}
+
+/*************************************************************/
+/** Templated mxArray exporters **/
+/*************************************************************/
+
+/** Converter from numeric matrix to container.
+ */
+template <typename T>
+void MxArray::toInternal(const mxArray* array, typename std::enable_if<
+ MxComplexOrArithmeticCompound<T>::value ||
+ MxLogicalCompound<T>::value ||
+ MxCharCompound<T>::value, T>::type* value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_CHECK_NOTNULL(value);
+ switch (mxGetClassID(array)) {
+ case mxINT8_CLASS: assignTo<int8_t, T>(array, value); break;
+ case mxUINT8_CLASS: assignTo<uint8_t, T>(array, value); break;
+ case mxINT16_CLASS: assignTo<int16_t, T>(array, value); break;
+ case mxUINT16_CLASS: assignTo<uint16_t, T>(array, value); break;
+ case mxINT32_CLASS: assignTo<int32_t, T>(array, value); break;
+ case mxUINT32_CLASS: assignTo<uint32_t, T>(array, value); break;
+ case mxINT64_CLASS: assignTo<int64_t, T>(array, value); break;
+ case mxUINT64_CLASS: assignTo<uint64_t, T>(array, value); break;
+ case mxSINGLE_CLASS: assignTo<float, T>(array, value); break;
+ case mxDOUBLE_CLASS: assignTo<double, T>(array, value); break;
+ case mxLOGICAL_CLASS: assignTo<mxLogical, T>(array, value); break;
+ case mxCHAR_CLASS: assignStringTo<T>(array, value); break;
+ case mxCELL_CLASS: assignCellTo<T>(array, value); break;
+ // case mxSPARSE_CLASS:
+ default:
+ MEXPLUS_ERROR("Cannot convert %s.", mxGetClassName(array));
+ }
+}
+
+/** Converter from nested types to container.
+ */
+template <typename T>
+void MxArray::toInternal(const mxArray* array,
+ typename std::enable_if<
+ MxCellType<T>::value &&
+ (!std::is_compound<T>::value ||
+ MxCellType<typename T::value_type>::value),
+ T
+ >::type* value) {
+ MEXPLUS_CHECK_NOTNULL(value);
+ MEXPLUS_ASSERT(mxIsCell(array), "Expected a cell array.");
+ mwSize array_size = mxGetNumberOfElements(array);
+ value->resize(array_size);
+ for (size_t i = 0; i < array_size; ++i) {
+ const mxArray* element = mxGetCell(array, i);
+ (*value)[i] = to<typename T::value_type>(element);
+ }
+}
+
+/*************************************************************/
+/** Templated mxArray getters **/
+/*************************************************************/
+
+/** Converter from fundamental numeric or complex types.
+ */
+template <typename T>
+void MxArray::atInternal(const mxArray* array, mwIndex index,
+ typename std::enable_if<
+ MxComplexOrArithmeticType<T>::value ||
+ MxLogicalType<T>::value ||
+ MxCharType<T>::value, T>::type* value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_CHECK_NOTNULL(value);
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ switch (mxGetClassID(array)) {
+ case mxINT8_CLASS: assignTo<int8_t, T>(array, index, value); break;
+ case mxUINT8_CLASS: assignTo<uint8_t, T>(array, index, value); break;
+ case mxINT16_CLASS: assignTo<int16_t, T>(array, index, value); break;
+ case mxUINT16_CLASS: assignTo<uint16_t, T>(array, index, value); break;
+ case mxINT32_CLASS: assignTo<int32_t, T>(array, index, value); break;
+ case mxUINT32_CLASS: assignTo<uint32_t, T>(array, index, value); break;
+ case mxINT64_CLASS: assignTo<int64_t, T>(array, index, value); break;
+ case mxUINT64_CLASS: assignTo<uint64_t, T>(array, index, value); break;
+ case mxSINGLE_CLASS: assignTo<float, T>(array, index, value); break;
+ case mxDOUBLE_CLASS: assignTo<double, T>(array, index, value); break;
+ case mxLOGICAL_CLASS: assignTo<mxLogical, T>(array, index, value); break;
+ case mxCHAR_CLASS: assignCharTo<T>(array, index, value); break;
+ case mxCELL_CLASS: assignCellTo<T>(array, index, value); break;
+ // case mxSPARSE_CLASS:
+ default:
+ MEXPLUS_ASSERT(true, "Cannot convert %s", mxGetClassName(array));
+ }
+}
+
+template <typename T>
+void MxArray::atInternal(const mxArray* array, mwIndex index,
+ typename std::enable_if<
+ std::is_compound<T>::value &&
+ !MxComplexType<T>::value, T>::type* value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_CHECK_NOTNULL(value);
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ MEXPLUS_ASSERT(mxIsCell(array), "Expected a cell array.");
+ const mxArray* element = mxGetCell(array, index);
+ to<T>(element, value);
+}
+
+template <typename T>
+void MxArray::atInternal(const mxArray* array,
+ const std::string& field,
+ mwIndex index,
+ T* value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_CHECK_NOTNULL(value);
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ MEXPLUS_ASSERT(mxIsStruct(array), "Expected a struct array.");
+ const mxArray* element = mxGetField(array, index, field.c_str());
+ MEXPLUS_ASSERT(element, "Invalid field name %s.", field.c_str());
+ to<T>(element, value);
+}
+
+/*************************************************************/
+/** Templated mxArray setters **/
+/*************************************************************/
+
+/** Converter from fundamental numeric or complex types.
+ */
+template <typename T>
+void MxArray::setInternal(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ !std::is_compound<T>::value ||
+ MxComplexType<T>::value, T>::type& value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ switch (mxGetClassID(array)) {
+ case mxINT8_CLASS: assignFrom<int8_t, T>(array, index, value); break;
+ case mxUINT8_CLASS: assignFrom<uint8_t, T>(array, index, value); break;
+ case mxINT16_CLASS: assignFrom<int16_t, T>(array, index, value); break;
+ case mxUINT16_CLASS: assignFrom<uint16_t, T>(array, index, value); break;
+ case mxINT32_CLASS: assignFrom<int32_t, T>(array, index, value); break;
+ case mxUINT32_CLASS: assignFrom<uint32_t, T>(array, index, value); break;
+ case mxINT64_CLASS: assignFrom<int64_t, T>(array, index, value); break;
+ case mxUINT64_CLASS: assignFrom<uint64_t, T>(array, index, value); break;
+ case mxSINGLE_CLASS: assignFrom<float, T>(array, index, value); break;
+ case mxDOUBLE_CLASS: assignFrom<double, T>(array, index, value); break;
+ case mxCHAR_CLASS: assignCharFrom<T>(array, index, value); break;
+ case mxLOGICAL_CLASS: assignFrom<mxLogical, T>(array, index, value); break;
+ case mxCELL_CLASS: {
+ mxArray* new_item = from(value); // Safe in case if from() fails.
+
+ mxDestroyArray(mxGetCell(array, index));
+ mxSetCell(array, index, new_item);
+ break;
+ }
+ default:
+ MEXPLUS_ERROR("Cannot assign to %s array.", mxGetClassName(array));
+ }
+}
+
+/** Converter from fundamental numeric or complex types.
+ */
+template <typename T>
+void MxArray::setInternal(mxArray* array,
+ mwIndex index,
+ const typename std::enable_if<
+ MxCellType<T>::value, T>::type& value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ MEXPLUS_ASSERT(mxIsCell(array), "Expected a cell array.");
+ mxArray* new_item = from(value); // Safe in case if from() fails.
+ mxDestroyArray(mxGetCell(array, index));
+ mxSetCell(array, index, new_item);
+}
+
+template <typename T>
+void MxArray::setInternal(mxArray* array,
+ const std::string& field,
+ mwIndex index,
+ const T& value) {
+ MEXPLUS_CHECK_NOTNULL(array);
+ MEXPLUS_ASSERT(static_cast<size_t>(index) < mxGetNumberOfElements(array),
+ "Index out of range: %u.",
+ index);
+ MEXPLUS_ASSERT(mxIsStruct(array), "Expected a struct array.");
+ int field_number = mxGetFieldNumber(array, field.c_str());
+ if (field_number < 0) {
+ field_number = mxAddField(array, field.c_str());
+ MEXPLUS_ASSERT(field_number >= 0,
+ "Failed to create a field '%s'",
+ field.c_str());
+ }
+ mxArray* new_item = from(value);
+ mxDestroyArray(mxGetFieldByNumber(array, index, field_number));
+ mxSetFieldByNumber(array, index, field_number, new_item);
+}
+
+template <typename T>
+mxArray* MxArray::Numeric(int rows, int columns) {
+ typedef typename std::enable_if<
+ MxComplexOrArithmeticType<T>::value, T>::type Scalar;
+ mxArray* numeric = mxCreateNumericMatrix(rows,
+ columns,
+ MxTypes<Scalar>::class_id,
+ MxTypes<Scalar>::complexity);
+ MEXPLUS_CHECK_NOTNULL(numeric);
+ return numeric;
+}
+
+template <typename T>
+mxArray* MxArray::Numeric(std::vector<std::size_t> dims) {
+ typedef typename std::enable_if<
+ MxComplexOrArithmeticType<T>::value, T>::type Scalar;
+ mxArray* numeric = mxCreateNumericArray(dims.size(),
+ &dims[0],
+ MxTypes<Scalar>::class_id,
+ MxTypes<Scalar>::complexity);
+ MEXPLUS_CHECK_NOTNULL(numeric);
+ return numeric;
+}
+
+template <typename T>
+T* MxArray::getData() const {
+ MEXPLUS_CHECK_NOTNULL(array_);
+ MEXPLUS_ASSERT(MxTypes<T>::class_id == classID(),
+ "Expected a %s array.",
+ typeid(T).name());
+ return reinterpret_cast<T*>(mxGetData(array_));
+}
+
+template <typename T>
+T* MxArray::getImagData() const {
+ MEXPLUS_CHECK_NOTNULL(array_);
+ MEXPLUS_ASSERT(MxTypes<T>::class_id == classID(),
+ "Expected a %s array.",
+ typeid(T).name());
+ return reinterpret_cast<T*>(mxGetPi(array_));
+}
+
+template <typename T>
+T MxArray::at(mwIndex row, mwIndex column) const {
+ return at<T>(subscriptIndex(row, column));
+}
+
+template <typename T>
+T MxArray::at(const std::vector<mwIndex>& subscripts) const {
+ return at<T>(subscriptIndex(subscripts));
+}
+
+template <typename T>
+void MxArray::set(mwIndex row, mwIndex column, const T& value) {
+ set<T>(subscriptIndex(row, column), value);
+}
+
+template <typename T>
+void MxArray::set(const std::vector<mwIndex>& subscripts, const T& value) {
+ set<T>(subscriptIndex(subscripts), value);
+}
+
+} // namespace mexplus
+
+#endif // INCLUDE_MEXPLUS_MXARRAY_H_
diff --git a/wrapper_matlab/mxtypes.h b/wrapper_matlab/mxtypes.h
new file mode 100644
index 0000000..bc8c1aa
--- /dev/null
+++ b/wrapper_matlab/mxtypes.h
@@ -0,0 +1,345 @@
+/** MxTypes and other type traits for template.
+ *
+ * Copyright 2014 Kota Yamaguchi.
+ */
+
+#ifndef INCLUDE_MEXPLUS_MXTYPES_H_
+#define INCLUDE_MEXPLUS_MXTYPES_H_
+
+#include <mex.h>
+#include <complex>
+#include <type_traits>
+
+namespace mexplus {
+
+/************************************************************/
+/* Traits for fundamental datatypes.
+ Don't use with function templates due to type promotion!
+ (Ignore it and get PITA!) */
+/************************************************************/
+
+/** Traits for mxLogical-convertibles.
+ */
+template <typename T, typename U = T>
+struct MxLogicalTy : std::false_type {};
+
+template <typename T>
+struct MxLogicalTy<T, typename std::enable_if<
+ std::is_same<typename std::remove_cv<T>::type, bool>::value ||
+ std::is_same<typename std::remove_cv<T>::type, mxLogical>::value,
+ T>::type> : std::true_type {};
+
+/** Traits for mxChar-convertibles.
+ *
+ * Treat them as an integer types when they are specified signed or unsigned,
+ * because uint8_t is exactly unsigned char and there is no way to tell them
+ * apart.
+ */
+template <typename T, typename U = T>
+struct MxCharTy : std::false_type {};
+
+template <typename T>
+struct MxCharTy<T, typename std::enable_if<
+ std::is_same<typename std::remove_cv<T>::type, char>::value ||
+ // Visual Studio cannot distinguish these from uint.
+ // std::is_same<typename std::remove_cv<T>::type, char16_t>::value ||
+ // std::is_same<typename std::remove_cv<T>::type, char32_t>::value ||
+ std::is_same<typename std::remove_cv<T>::type, mxChar>::value ||
+ std::is_same<typename std::remove_cv<T>::type, wchar_t>::value,
+ T>::type> : std::true_type {};
+
+/** Traits for integer numerics.
+ */
+template <typename T, typename U = T>
+struct MxIntTy : std::false_type {};
+template <typename T>
+struct MxIntTy<T, typename std::enable_if<
+ std::is_integral<T>::value &&
+ !MxLogicalTy<T>::value &&
+ !MxCharTy<T>::value,
+ T>::type> : std::true_type {};
+/** Traits for arithmetic types.
+ */
+template <typename T, typename U = T>
+struct MxArithmeticTy : std::false_type {};
+template <typename T>
+struct MxArithmeticTy<T, typename std::enable_if<
+ (std::is_floating_point<T>::value) || (MxIntTy<T>::value),
+ T>::type> : std::true_type {};
+
+/**********************************************/
+/* Introducing traits for MATLAB array types. */
+/**********************************************/
+
+typedef struct mxNumeric_tag {} mxNumeric;
+typedef struct mxCell_tag {} mxCell;
+typedef struct mxComplex_tag {} mxComplex;
+// mxLogical already defined in MATLAB (matrix.h).
+
+/** Traits for mxArray.
+ */
+template <typename T, typename U = T>
+struct MxTypes {
+ typedef T type;
+ typedef mxCell array_type;
+ static const mxClassID class_id = mxUNKNOWN_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<MxCharTy<T>::value, T>::type> {
+ typedef T type;
+ typedef mxChar array_type;
+ static const mxClassID class_id = mxCHAR_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<MxLogicalTy<T>::value, T>::type> {
+ typedef T type;
+ typedef mxLogical array_type;
+ static const mxClassID class_id = mxLOGICAL_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_signed<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 1, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxINT8_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_unsigned<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 1, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxUINT8_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_signed<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 2, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxINT16_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_unsigned<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 2, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxUINT16_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_signed<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 4, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxINT32_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_unsigned<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 4, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxUINT32_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_signed<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 8, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxINT64_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_unsigned<T>::value &&
+ MxIntTy<T>::value &&
+ sizeof(T) == 8, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxUINT64_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_floating_point<T>::value &&
+ sizeof(T) == 4, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxSINGLE_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<std::is_floating_point<T>::value &&
+ sizeof(T) == 8, T>::type> {
+ typedef T type;
+ typedef mxNumeric array_type;
+ static const mxClassID class_id = mxDOUBLE_CLASS;
+ static const mxComplexity complexity = mxREAL;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<
+ std::is_same<typename std::remove_cv<T>::type,
+ std::complex<float>>::value,
+ T>::type> {
+ typedef T type;
+ typedef mxComplex array_type;
+ static const mxClassID class_id = mxSINGLE_CLASS;
+ static const mxComplexity complexity = mxCOMPLEX;
+};
+
+template <typename T>
+struct MxTypes<T, typename std::enable_if<
+ std::is_same<typename std::remove_cv<T>::type,
+ std::complex<double>>::value,
+ T>::type> {
+ typedef T type;
+ typedef mxComplex array_type;
+ static const mxClassID class_id = mxDOUBLE_CLASS;
+ static const mxComplexity complexity = mxCOMPLEX;
+};
+
+/********************************************/
+/* Type traits for function template usage. */
+/********************************************/
+
+/* Traits for logical types.
+ */
+template <typename T, typename U = T>
+struct MxLogicalType : std::false_type {};
+template<typename T>
+struct MxLogicalType<T, typename std::enable_if<
+ std::is_same<typename MxTypes<T>::array_type, mxLogical>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for char types.
+ */
+template <typename T, typename U = T>
+struct MxCharType : std::false_type {};
+template<typename T>
+struct MxCharType<T, typename std::enable_if<
+ std::is_same<typename MxTypes<T>::array_type, mxChar>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for arithmetic types.
+ */
+template <typename T, typename U = T>
+struct MxArithmeticType : std::false_type {};
+template<typename T>
+struct MxArithmeticType<T, typename std::enable_if<
+ std::is_same<typename MxTypes<T>::array_type, mxNumeric>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for complex types.
+ */
+template <typename T, typename U = T>
+struct MxComplexType : std::false_type {};
+template<typename T>
+struct MxComplexType<T, typename std::enable_if<
+ std::is_same<typename MxTypes<T>::array_type, mxComplex>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for complex or arithmetic types.
+ */
+template <typename T, typename U = T>
+struct MxComplexOrArithmeticType : std::false_type {};
+template <typename T>
+struct MxComplexOrArithmeticType<T, typename std::enable_if<
+ MxComplexType<T>::value,
+ T>::type> : std::true_type {};
+template <typename T>
+struct MxComplexOrArithmeticType<T, typename std::enable_if<
+ MxArithmeticTy<T>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for cell types.
+ */
+template <typename T, typename U = T>
+struct MxCellType : std::false_type {};
+template <typename T>
+struct MxCellType<T, typename std::enable_if<
+ std::is_same<typename MxTypes<T>::array_type, mxCell>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for logical type compounds.
+ */
+template <typename T, typename U = T>
+struct MxLogicalCompound : std::false_type {};
+template <typename T>
+struct MxLogicalCompound<T, typename std::enable_if<
+ MxLogicalType<typename T::value_type>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for char type compounds.
+ */
+template <typename T, typename U = T>
+struct MxCharCompound : std::false_type {};
+template <typename T>
+struct MxCharCompound<T, typename std::enable_if<
+ MxCharType<typename T::value_type>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for arithmetic type compounds.
+ */
+template <typename T, typename U = T>
+struct MxArithmeticCompound : std::false_type {};
+template <typename T>
+struct MxArithmeticCompound<T, typename std::enable_if<
+ (MxArithmeticType<typename T::value_type>::value) &&
+ !(MxComplexType<T>::value),
+ T>::type> : std::true_type {};
+
+/* Traits for complex type compounds.
+ */
+template <typename T, typename U = T>
+struct MxComplexCompound : std::false_type {};
+template <typename T>
+struct MxComplexCompound<T, typename std::enable_if<
+ MxComplexType<typename T::value_type>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for complex or arithmetic type compounds.
+ */
+template <typename T, typename U = T>
+struct MxComplexOrArithmeticCompound : std::false_type {};
+template <typename T>
+struct MxComplexOrArithmeticCompound<T, typename std::enable_if<
+ MxComplexCompound<T>::value ||
+ MxArithmeticCompound<T>::value,
+ T>::type> : std::true_type {};
+
+/* Traits for cell compounds.
+ */
+template <typename T, typename U = T>
+struct MxCellCompound : std::false_type {};
+template <typename T>
+struct MxCellCompound<T, typename std::enable_if<
+ MxCellType<typename T::value_type>::value,
+ T>::type> : std::true_type {};
+
+} // namespace mexplus
+
+#endif // INCLUDE_MEXPLUS_MXTYPES_H_
diff --git a/wrapper_matlab/run_demo.m b/wrapper_matlab/run_demo.m
new file mode 100644
index 0000000..e27174d
--- /dev/null
+++ b/wrapper_matlab/run_demo.m
@@ -0,0 +1,49 @@
+%% Compile the BGSLibrary wrapper
+compile;
+
+%% Run demo
+demo;
+
+%% Run a specific algorithm
+demo('FrameDifference')
+% demo('StaticFrameDifference')
+% demo('WeightedMovingMean')
+% demo('WeightedMovingVariance')
+% demo('MixtureOfGaussianV1') % only for OpenCV 2.x
+% demo('MixtureOfGaussianV2')
+% demo('AdaptiveBackgroundLearning')
+% demo('AdaptiveSelectiveBackgroundLearning')
+% demo('GMG') % only on OpenCV >= 2.4.3
+% demo('KNN') % only on OpenCV 3.x
+% demo('DPAdaptiveMedian')
+% demo('DPGrimsonGMM')
+% demo('DPZivkovicAGMM')
+% demo('DPMean')
+% demo('DPWrenGA')
+% demo('DPPratiMediod')
+% demo('DPEigenbackground')
+% demo('DPTexture')
+% demo('T2FGMM_UM')
+% demo('T2FGMM_UV')
+% demo('T2FMRF_UM')
+% demo('T2FMRF_UV')
+% demo('FuzzySugenoIntegral')
+% demo('FuzzyChoquetIntegral')
+% demo('LBSimpleGaussian')
+% demo('LBFuzzyGaussian')
+% demo('LBMixtureOfGaussians')
+% demo('LBAdaptiveSOM')
+% demo('LBFuzzyAdaptiveSOM')
+% demo('LBP_MRF')
+% demo('MultiLayer')
+% demo('PixelBasedAdaptiveSegmenter')
+% demo('VuMeter')
+% demo('KDE')
+% demo('IndependentMultimodal')
+% demo('MultiCue')
+% demo('SigmaDelta')
+% demo('SuBSENSE')
+% demo('LOBSTER')
+% demo('PAWCS')
+% demo('TwoPoints')
+% demo('ViBe')
\ No newline at end of file
diff --git a/wrapper_python/bgslibrary_module.cpp b/wrapper_python/bgslibrary_module.cpp
new file mode 100644
index 0000000..edb75a8
--- /dev/null
+++ b/wrapper_python/bgslibrary_module.cpp
@@ -0,0 +1,265 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include <boost/python.hpp>
+#include <boost/python/suite/indexing/vector_indexing_suite.hpp>
+#include <exception>
+
+#include <opencv2/opencv.hpp>
+#include "np_opencv_converter.h"
+
+#include "../package_bgs/bgslibrary.h"
+
+namespace py = boost::python;
+
+cv::Mat test_transpose(const cv::Mat& in)
+{
+ std::cerr << "Input size: " << in.size() << std::endl;
+ std::cerr << "Returning transpose" << std::endl;
+ return in.t();
+}
+
+namespace fs
+{
+ namespace python
+ {
+ BOOST_PYTHON_MODULE(libbgs)
+ {
+ // Main types export
+ fs::python::init_and_export_converters();
+ py::scope scope = py::scope();
+
+ // Basic test
+ py::def("test_transpose", &test_transpose);
+
+ py::class_<FrameDifference>("FrameDifference")
+ .def("apply", &FrameDifference::apply)
+ .def("getBackgroundModel", &FrameDifference::getBackgroundModel)
+ ;
+
+ py::class_<StaticFrameDifference>("StaticFrameDifference")
+ .def("apply", &StaticFrameDifference::apply)
+ .def("getBackgroundModel", &StaticFrameDifference::getBackgroundModel)
+ ;
+
+ py::class_<AdaptiveBackgroundLearning>("AdaptiveBackgroundLearning")
+ .def("apply", &AdaptiveBackgroundLearning::apply)
+ .def("getBackgroundModel", &AdaptiveBackgroundLearning::getBackgroundModel)
+ ;
+
+ py::class_<AdaptiveSelectiveBackgroundLearning>("AdaptiveSelectiveBackgroundLearning")
+ .def("apply", &AdaptiveSelectiveBackgroundLearning::apply)
+ .def("getBackgroundModel", &AdaptiveSelectiveBackgroundLearning::getBackgroundModel)
+ ;
+
+ py::class_<DPAdaptiveMedian>("DPAdaptiveMedian")
+ .def("apply", &DPAdaptiveMedian::apply)
+ .def("getBackgroundModel", &DPAdaptiveMedian::getBackgroundModel)
+ ;
+
+ py::class_<DPEigenbackground>("DPEigenbackground")
+ .def("apply", &DPEigenbackground::apply)
+ .def("getBackgroundModel", &DPEigenbackground::getBackgroundModel)
+ ;
+
+ py::class_<DPGrimsonGMM>("DPGrimsonGMM")
+ .def("apply", &DPGrimsonGMM::apply)
+ .def("getBackgroundModel", &DPGrimsonGMM::getBackgroundModel)
+ ;
+
+ py::class_<DPMean>("DPMean")
+ .def("apply", &DPMean::apply)
+ .def("getBackgroundModel", &DPMean::getBackgroundModel)
+ ;
+
+ py::class_<DPPratiMediod>("DPPratiMediod")
+ .def("apply", &DPPratiMediod::apply)
+ .def("getBackgroundModel", &DPPratiMediod::getBackgroundModel)
+ ;
+
+ py::class_<DPTexture>("DPTexture")
+ .def("apply", &DPTexture::apply)
+ .def("getBackgroundModel", &DPTexture::getBackgroundModel)
+ ;
+
+ py::class_<DPWrenGA>("DPWrenGA")
+ .def("apply", &DPWrenGA::apply)
+ .def("getBackgroundModel", &DPWrenGA::getBackgroundModel)
+ ;
+
+ py::class_<DPZivkovicAGMM>("DPZivkovicAGMM")
+ .def("apply", &DPZivkovicAGMM::apply)
+ .def("getBackgroundModel", &DPZivkovicAGMM::getBackgroundModel)
+ ;
+
+ py::class_<FuzzyChoquetIntegral>("FuzzyChoquetIntegral")
+ .def("apply", &FuzzyChoquetIntegral::apply)
+ .def("getBackgroundModel", &FuzzyChoquetIntegral::getBackgroundModel)
+ ;
+
+ py::class_<FuzzySugenoIntegral>("FuzzySugenoIntegral")
+ .def("apply", &FuzzySugenoIntegral::apply)
+ .def("getBackgroundModel", &FuzzySugenoIntegral::getBackgroundModel)
+ ;
+
+#if CV_MAJOR_VERSION == 2
+ py::class_<GMG>("GMG")
+ .def("apply", &GMG::apply)
+ .def("getBackgroundModel", &GMG::getBackgroundModel)
+ ;
+#endif
+
+ py::class_<IndependentMultimodal>("IndependentMultimodal")
+ .def("apply", &IndependentMultimodal::apply)
+ .def("getBackgroundModel", &IndependentMultimodal::getBackgroundModel)
+ ;
+
+ py::class_<KDE>("KDE")
+ .def("apply", &KDE::apply)
+ .def("getBackgroundModel", &KDE::getBackgroundModel)
+ ;
+
+#if CV_MAJOR_VERSION == 3
+ py::class_<KNN>("KNN")
+ .def("apply", &KNN::apply)
+ .def("getBackgroundModel", &KNN::getBackgroundModel)
+ ;
+#endif
+
+ py::class_<LBAdaptiveSOM>("LBAdaptiveSOM")
+ .def("apply", &LBAdaptiveSOM::apply)
+ .def("getBackgroundModel", &LBAdaptiveSOM::getBackgroundModel)
+ ;
+
+ py::class_<LBFuzzyAdaptiveSOM>("LBFuzzyAdaptiveSOM")
+ .def("apply", &LBFuzzyAdaptiveSOM::apply)
+ .def("getBackgroundModel", &LBFuzzyAdaptiveSOM::getBackgroundModel)
+ ;
+
+ py::class_<LBFuzzyGaussian>("LBFuzzyGaussian")
+ .def("apply", &LBFuzzyGaussian::apply)
+ .def("getBackgroundModel", &LBFuzzyGaussian::getBackgroundModel)
+ ;
+
+ py::class_<LBMixtureOfGaussians>("LBMixtureOfGaussians")
+ .def("apply", &LBMixtureOfGaussians::apply)
+ .def("getBackgroundModel", &LBMixtureOfGaussians::getBackgroundModel)
+ ;
+
+ py::class_<LBSimpleGaussian>("LBSimpleGaussian")
+ .def("apply", &LBSimpleGaussian::apply)
+ .def("getBackgroundModel", &LBSimpleGaussian::getBackgroundModel)
+ ;
+
+ py::class_<LBP_MRF>("LBP_MRF")
+ .def("apply", &LBP_MRF::apply)
+ .def("getBackgroundModel", &LBP_MRF::getBackgroundModel)
+ ;
+
+ py::class_<LOBSTER>("LOBSTER")
+ .def("apply", &LOBSTER::apply)
+ .def("getBackgroundModel", &LOBSTER::getBackgroundModel)
+ ;
+
+#if CV_MAJOR_VERSION == 2
+ py::class_<MixtureOfGaussianV1>("MixtureOfGaussianV1")
+ .def("apply", &MixtureOfGaussianV1::apply)
+ .def("getBackgroundModel", &MixtureOfGaussianV1::getBackgroundModel)
+ ;
+#endif
+
+ py::class_<MixtureOfGaussianV2>("MixtureOfGaussianV2")
+ .def("apply", &MixtureOfGaussianV2::apply)
+ .def("getBackgroundModel", &MixtureOfGaussianV2::getBackgroundModel)
+ ;
+
+ py::class_<MultiCue>("MultiCue")
+ .def("apply", &MultiCue::apply)
+ .def("getBackgroundModel", &MultiCue::getBackgroundModel)
+ ;
+
+ py::class_<MultiLayer>("MultiLayer")
+ .def("apply", &MultiLayer::apply)
+ .def("getBackgroundModel", &MultiLayer::getBackgroundModel)
+ ;
+
+ py::class_<PAWCS>("PAWCS")
+ .def("apply", &PAWCS::apply)
+ .def("getBackgroundModel", &PAWCS::getBackgroundModel)
+ ;
+
+ py::class_<PixelBasedAdaptiveSegmenter>("PixelBasedAdaptiveSegmenter")
+ .def("apply", &PixelBasedAdaptiveSegmenter::apply)
+ .def("getBackgroundModel", &PixelBasedAdaptiveSegmenter::getBackgroundModel)
+ ;
+
+ py::class_<SigmaDelta>("SigmaDelta")
+ .def("apply", &SigmaDelta::apply)
+ .def("getBackgroundModel", &SigmaDelta::getBackgroundModel)
+ ;
+
+ py::class_<SuBSENSE>("SuBSENSE")
+ .def("apply", &SuBSENSE::apply)
+ .def("getBackgroundModel", &SuBSENSE::getBackgroundModel)
+ ;
+
+ py::class_<T2FGMM_UM>("T2FGMM_UM")
+ .def("apply", &T2FGMM_UM::apply)
+ .def("getBackgroundModel", &T2FGMM_UM::getBackgroundModel)
+ ;
+
+ py::class_<T2FGMM_UV>("T2FGMM_UV")
+ .def("apply", &T2FGMM_UV::apply)
+ .def("getBackgroundModel", &T2FGMM_UV::getBackgroundModel)
+ ;
+
+ py::class_<T2FMRF_UM>("T2FMRF_UM")
+ .def("apply", &T2FMRF_UM::apply)
+ .def("getBackgroundModel", &T2FMRF_UM::getBackgroundModel)
+ ;
+
+ py::class_<T2FMRF_UV>("T2FMRF_UV")
+ .def("apply", &T2FMRF_UV::apply)
+ .def("getBackgroundModel", &T2FMRF_UV::getBackgroundModel)
+ ;
+
+ py::class_<VuMeter>("VuMeter")
+ .def("apply", &VuMeter::apply)
+ .def("getBackgroundModel", &VuMeter::getBackgroundModel)
+ ;
+
+ py::class_<WeightedMovingMean>("WeightedMovingMean")
+ .def("apply", &WeightedMovingMean::apply)
+ .def("getBackgroundModel", &WeightedMovingMean::getBackgroundModel)
+ ;
+
+ py::class_<WeightedMovingVariance>("WeightedMovingVariance")
+ .def("apply", &WeightedMovingVariance::apply)
+ .def("getBackgroundModel", &WeightedMovingVariance::getBackgroundModel)
+ ;
+
+ py::class_<TwoPoints>("TwoPoints")
+ .def("apply", &TwoPoints::apply)
+ .def("getBackgroundModel", &TwoPoints::getBackgroundModel)
+ ;
+
+ py::class_<ViBe>("ViBe")
+ .def("apply", &ViBe::apply)
+ .def("getBackgroundModel", &ViBe::getBackgroundModel)
+ ;
+ }
+ } // namespace fs
+} // namespace python
diff --git a/wrapper_python/np_opencv_converter.cpp b/wrapper_python/np_opencv_converter.cpp
new file mode 100644
index 0000000..6050f6b
--- /dev/null
+++ b/wrapper_python/np_opencv_converter.cpp
@@ -0,0 +1,103 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#include "np_opencv_converter.h"
+
+namespace fs { namespace python {
+
+// Static PyInit
+static void py_init() {
+ Py_Initialize();
+ import_array();
+}
+
+// Singleton init and export converters
+static bool export_type_conversions_once = false;
+bool init_and_export_converters() {
+
+ if (export_type_conversions_once)
+ return false;
+
+ std::cerr << "PYTHON TYPE CONVERTERS exported" << std::endl;
+ export_type_conversions_once = true;
+
+ // Py_Init and array import
+ py_init();
+
+ // => py::list
+ expose_template_type<int>();
+ expose_template_type<float>();
+ expose_template_type<double>();
+
+ // std::vector => py::list
+ expose_template_type< std::vector<int> >();
+ expose_template_type< std::vector<float> >();
+ expose_template_type< std::vector<double> >();
+
+ expose_template_type< std::vector<cv::Point> >();
+ expose_template_type< std::vector<cv::Point2f> >();
+ expose_template_type< std::vector<cv::KeyPoint> >();
+
+ expose_template_type< std::vector<cv::Mat> >();
+ expose_template_type< std::vector<cv::Mat1b > >();
+ expose_template_type< std::vector<cv::Mat1f > >();
+
+ // std::map => py::dict
+ expose_template_type<std::map<int, std::vector<int> > >();
+ expose_template_type<std::map<int, std::vector<float> > >();
+ expose_template_type<std::map<std::string, float> >();
+
+ // various converters to cv::Mat
+ py::to_python_converter<cv::Point, Point_to_mat>();
+ py::to_python_converter<cv::Point2f, Point2f_to_mat>();
+ py::to_python_converter<cv::Point3f, Point3f_to_mat>();
+ py::to_python_converter<cv::Vec3f, Vec3f_to_mat>();
+
+ // register the to-from-python converter for each of the types
+ Mat_PyObject_converter< cv::Mat >();
+
+ // 1-channel
+ Mat_PyObject_converter< cv::Mat1b >();
+ Mat_PyObject_converter< cv::Mat1s >();
+ Mat_PyObject_converter< cv::Mat1w >();
+ Mat_PyObject_converter< cv::Mat1i >();
+ Mat_PyObject_converter< cv::Mat1f >();
+ Mat_PyObject_converter< cv::Mat1d >();
+
+ // 2-channel
+ Mat_PyObject_converter< cv::Mat2b >();
+ Mat_PyObject_converter< cv::Mat2s >();
+ Mat_PyObject_converter< cv::Mat2w >();
+ Mat_PyObject_converter< cv::Mat2i >();
+ Mat_PyObject_converter< cv::Mat2f >();
+ Mat_PyObject_converter< cv::Mat2d >();
+
+ // 3-channel
+ Mat_PyObject_converter< cv::Mat3b >();
+ Mat_PyObject_converter< cv::Mat3s >();
+ Mat_PyObject_converter< cv::Mat3w >();
+ Mat_PyObject_converter< cv::Mat3i >();
+ Mat_PyObject_converter< cv::Mat3f >();
+ Mat_PyObject_converter< cv::Mat3d >();
+
+ // add more if needed
+
+ return true;
+}
+
+} // namespace python
+} // namespace fs
+
diff --git a/wrapper_python/np_opencv_converter.h b/wrapper_python/np_opencv_converter.h
new file mode 100644
index 0000000..68386f0
--- /dev/null
+++ b/wrapper_python/np_opencv_converter.h
@@ -0,0 +1,122 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+#pragma once
+
+#include <boost/python.hpp>
+#include <boost/python/suite/indexing/vector_indexing_suite.hpp>
+
+#include "utils/template.h"
+#include "utils/container.h"
+#include "utils/conversion.h"
+
+#include <opencv2/opencv.hpp>
+
+namespace fs { namespace python {
+
+// TODO: Template these
+// Vec3f => cv::Mat
+struct Vec3f_to_mat {
+ static PyObject* convert(const cv::Vec3f& v){
+ NDArrayConverter cvt;
+ PyObject* ret = cvt.toNDArray(cv::Mat(v));
+ return ret;
+ }
+};
+
+// cv::Point => cv::Mat
+struct Point_to_mat {
+ static PyObject* convert(const cv::Point& v){
+ NDArrayConverter cvt;
+ PyObject* ret = cvt.toNDArray(cv::Mat(v));
+ return ret;
+ }
+};
+
+// cv::Point2f => cv::Mat
+struct Point2f_to_mat {
+ static PyObject* convert(const cv::Point2f& v){
+ NDArrayConverter cvt;
+ PyObject* ret = cvt.toNDArray(cv::Mat(v));
+ return ret;
+ }
+};
+
+// cv::Point3f => cv::Mat
+struct Point3f_to_mat {
+ static PyObject* convert(const cv::Point3f& v){
+ NDArrayConverter cvt;
+ PyObject* ret = cvt.toNDArray(cv::Mat(v));
+ return ret;
+ }
+};
+
+// cv::Mat_<T> => Numpy PyObject
+template <typename T>
+struct Mat_to_PyObject {
+ static PyObject* convert(const T& mat){
+ NDArrayConverter cvt;
+ PyObject* ret = cvt.toNDArray(mat);
+ return ret;
+ }
+};
+
+// Generic templated cv::Mat <=> Numpy PyObject converter
+template <typename T>
+struct Mat_PyObject_converter
+{
+ // Register from converter
+ Mat_PyObject_converter() {
+ boost::python::converter::registry::push_back(
+ &convertible,
+ &construct,
+ boost::python::type_id<T>());
+
+ // Register to converter
+ py::to_python_converter<T, Mat_to_PyObject<T> >();
+ }
+
+ // Convert from type T to PyObject (numpy array)
+ // Assume obj_ptr can be converted in a cv::Mat
+ static void* convertible(PyObject* obj_ptr)
+ {
+ // Check validity?
+ assert(obj_ptr != 0);
+ return obj_ptr;
+ }
+
+ // Convert obj_ptr into a cv::Mat
+ static void construct(PyObject* obj_ptr,
+ boost::python::converter::rvalue_from_python_stage1_data* data)
+ {
+ using namespace boost::python;
+ typedef converter::rvalue_from_python_storage< T > storage_t;
+
+ storage_t* the_storage = reinterpret_cast<storage_t*>( data );
+ void* memory_chunk = the_storage->storage.bytes;
+
+ NDArrayConverter cvt;
+ T* newvec = new (memory_chunk) T(cvt.toMat(obj_ptr));
+ data->convertible = memory_chunk;
+
+ return;
+ }
+};
+
+bool init_and_export_converters();
+
+} // namespace python
+} // namespace fs
diff --git a/wrapper_python/utils/container.h b/wrapper_python/utils/container.h
new file mode 100644
index 0000000..3db5613
--- /dev/null
+++ b/wrapper_python/utils/container.h
@@ -0,0 +1,208 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+// Author: Sudeep Pillai (spillai@csail.mit.edu)
+// Note: Stripped from pyxx project
+
+#pragma once
+
+#include <boost/python.hpp>
+#include <boost/python/class.hpp>
+#include <boost/python/module.hpp>
+#include <boost/foreach.hpp>
+
+#include <vector>
+#include <string>
+#include <stdexcept>
+#include <iostream>
+#include <map>
+#include <list>
+
+namespace py = boost::python;
+
+template<typename T>
+struct expose_template_type< std::vector<T> > :
+ public expose_template_type_base< std::vector<T> >
+{
+ typedef expose_template_type_base< std::vector<T> > base_type;
+ typedef expose_template_type< std::vector<T> > this_type;
+ typedef std::vector<T> wrapped_type;
+
+ expose_template_type()
+ {
+ ::expose_template_type<T>();
+ if( !base_type::wrapped() )
+ {
+ py::to_python_converter< wrapped_type, this_type >();
+ py::converter::registry::push_back(
+ this_type::convertible,
+ this_type::construct,
+ py::type_id< wrapped_type >() );
+
+ }
+ }
+
+ static PyObject * convert( const wrapped_type & container)
+ {
+ py::list l;
+ for(typename wrapped_type::const_iterator iter = container.begin(); iter != container.end(); iter++)
+ {
+ l.append( py::object( *iter ) );
+ }
+ Py_INCREF( l.ptr() );
+ return l.ptr();
+ }
+
+ static void * convertible( PyObject * py_obj)
+ {
+ // we are supposed to indicate whether or not we can convert this
+ // we don't really know, but we'll try any sequence
+ if( PySequence_Check(py_obj) )
+ return py_obj;
+ return 0;
+ }
+
+ static void construct( PyObject * py_obj, py::converter::rvalue_from_python_stage1_data* data)
+ {
+ using namespace boost::python;
+ typedef converter::rvalue_from_python_storage< wrapped_type > storage_t;
+
+ storage_t* the_storage = reinterpret_cast<storage_t*>( data );
+ void* memory_chunk = the_storage->storage.bytes;
+ wrapped_type * newvec = new (memory_chunk) wrapped_type;
+ data->convertible = memory_chunk;
+
+ object sequence(handle<>( borrowed( py_obj ) ) );
+
+ for(int idx = 0; idx < len(sequence);idx++)
+ {
+ newvec->push_back( extract<T>( sequence[idx] )() );
+ }
+
+ }
+
+};
+
+template<typename Key, typename Value>
+ struct expose_template_type< std::map<Key, Value> > :
+ public expose_template_type_base< std::map<Key, Value> >
+{
+ typedef std::map<Key, Value> wrapped_type;
+ typedef expose_template_type_base< wrapped_type > base_type;
+ typedef expose_template_type< wrapped_type > this_type;
+
+ expose_template_type()
+ {
+ if( !base_type::wrapped() )
+ {
+ py::to_python_converter< wrapped_type, this_type >();
+ py::converter::registry::push_back(
+ this_type::convertible,
+ this_type::construct,
+ py::type_id< wrapped_type >() );
+
+ }
+ }
+
+ static PyObject * convert( const wrapped_type & container)
+ {
+ py::dict d;
+ for(typename wrapped_type::const_iterator iter = container.begin(); iter != container.end(); iter++)
+ {
+ d[iter->first] = py::object(iter->second);
+ }
+ Py_INCREF( d.ptr() );
+ return d.ptr();
+ }
+
+ static void * convertible( PyObject * py_obj)
+ {
+ // we are supposed to indicate whether or not we can convert this
+ // we don't really know, but we'll try any sequence
+ if( PyMapping_Check(py_obj) )
+ return py_obj;
+ return 0;
+ }
+
+ static void construct( PyObject * py_obj, py::converter::rvalue_from_python_stage1_data* data)
+ {
+ using namespace boost::python;
+ typedef converter::rvalue_from_python_storage< wrapped_type > storage_t;
+
+ storage_t* the_storage = reinterpret_cast<storage_t*>( data );
+ void* memory_chunk = the_storage->storage.bytes;
+ wrapped_type * newvec = new (memory_chunk) wrapped_type;
+ data->convertible = memory_chunk;
+
+ object sequence(handle<>( borrowed( py_obj ) ) );
+ sequence = sequence.attr("items")();
+
+ for(int idx = 0; idx < len(sequence);idx++)
+ {
+ Key key = py::extract<Key>(sequence[idx][0])();
+ Value value = py::extract<Value>(sequence[idx][1])();
+ (*newvec)[key] = value;
+ }
+
+ }
+
+};
+
+template<typename Key, typename Value>
+ struct expose_template_type< typename std::pair<Key, Value> > :
+ public expose_template_type_base< std::pair<Key, Value> >
+{
+ typedef std::pair<Key, Value> wrapped_type;
+ typedef expose_template_type_base< wrapped_type > base_type;
+ typedef expose_template_type< wrapped_type > this_type;
+
+ expose_template_type()
+ {
+ if( !base_type::wrapped() )
+ {
+ py::converter::registry::push_back(
+ this_type::convertible,
+ this_type::construct,
+ py::type_id< wrapped_type >() );
+
+ }
+ }
+
+ static void * convertible( PyObject * py_obj)
+ {
+ // we are supposed to indicate whether or not we can convert this
+ // we don't really know, but we'll try any sequence
+ if( PyTuple_Check(py_obj) && PyTuple_Size(py_obj) == 2)
+ return py_obj;
+ return 0;
+ }
+
+ static void construct( PyObject * py_obj, py::converter::rvalue_from_python_stage1_data* data)
+ {
+ using namespace boost::python;
+ typedef converter::rvalue_from_python_storage< wrapped_type > storage_t;
+
+ storage_t* the_storage = reinterpret_cast<storage_t*>( data );
+ void* memory_chunk = the_storage->storage.bytes;
+ wrapped_type * newvec = new (memory_chunk) wrapped_type;
+ data->convertible = memory_chunk;
+
+ object sequence(handle<>( borrowed( py_obj ) ) );
+ newvec->first = extract<Key>(sequence[0])();
+ newvec->second = extract<Value>(sequence[1])();
+ }
+
+};
diff --git a/wrapper_python/utils/conversion.cpp b/wrapper_python/utils/conversion.cpp
new file mode 100644
index 0000000..7ca21dd
--- /dev/null
+++ b/wrapper_python/utils/conversion.cpp
@@ -0,0 +1,349 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+// Author: Sudeep Pillai (spillai@csail.mit.edu)
+// Note: Stripped from Opencv (opencv/modules/python/src2/cv2.cpp)
+
+# include "conversion.h"
+/*
+ * The following conversion functions are taken/adapted from OpenCV's cv2.cpp file
+ * inside modules/python/src2 folder.
+ */
+
+static void init()
+{
+ import_array();
+}
+
+static int failmsg(const char *fmt, ...)
+{
+ char str[1000];
+
+ va_list ap;
+ va_start(ap, fmt);
+ vsnprintf(str, sizeof(str), fmt, ap);
+ va_end(ap);
+
+ PyErr_SetString(PyExc_TypeError, str);
+ return 0;
+}
+
+class PyAllowThreads
+{
+public:
+ PyAllowThreads() : _state(PyEval_SaveThread()) {}
+ ~PyAllowThreads()
+ {
+ PyEval_RestoreThread(_state);
+ }
+private:
+ PyThreadState* _state;
+};
+
+class PyEnsureGIL
+{
+public:
+ PyEnsureGIL() : _state(PyGILState_Ensure()) {}
+ ~PyEnsureGIL()
+ {
+ PyGILState_Release(_state);
+ }
+private:
+ PyGILState_STATE _state;
+};
+
+using namespace cv;
+static PyObject* failmsgp(const char *fmt, ...)
+{
+ char str[1000];
+
+ va_list ap;
+ va_start(ap, fmt);
+ vsnprintf(str, sizeof(str), fmt, ap);
+ va_end(ap);
+
+ PyErr_SetString(PyExc_TypeError, str);
+ return 0;
+}
+
+#define OPENCV_3 0
+#if OPENCV_3
+class NumpyAllocator : public MatAllocator
+{
+public:
+ NumpyAllocator() { stdAllocator = Mat::getStdAllocator(); }
+ ~NumpyAllocator() {}
+
+ UMatData* allocate(PyObject* o, int dims, const int* sizes, int type, size_t* step) const
+ {
+ UMatData* u = new UMatData(this);
+ u->data = u->origdata = (uchar*)PyArray_DATA((PyArrayObject*) o);
+ npy_intp* _strides = PyArray_STRIDES((PyArrayObject*) o);
+ for( int i = 0; i < dims - 1; i++ )
+ step[i] = (size_t)_strides[i];
+ step[dims-1] = CV_ELEM_SIZE(type);
+ u->size = sizes[0]*step[0];
+ u->userdata = o;
+ return u;
+ }
+
+ UMatData* allocate(int dims0, const int* sizes, int type, void* data, size_t* step, int flags) const
+ {
+ if( data != 0 )
+ {
+ CV_Error(Error::StsAssert, "The data should normally be NULL!");
+ // probably this is safe to do in such extreme case
+ return stdAllocator->allocate(dims0, sizes, type, data, step, flags);
+ }
+ PyEnsureGIL gil;
+
+ int depth = CV_MAT_DEPTH(type);
+ int cn = CV_MAT_CN(type);
+ const int f = (int)(sizeof(size_t)/8);
+ int typenum = depth == CV_8U ? NPY_UBYTE : depth == CV_8S ? NPY_BYTE :
+ depth == CV_16U ? NPY_USHORT : depth == CV_16S ? NPY_SHORT :
+ depth == CV_32S ? NPY_INT : depth == CV_32F ? NPY_FLOAT :
+ depth == CV_64F ? NPY_DOUBLE : f*NPY_ULONGLONG + (f^1)*NPY_UINT;
+ int i, dims = dims0;
+ cv::AutoBuffer<npy_intp> _sizes(dims + 1);
+ for( i = 0; i < dims; i++ )
+ _sizes[i] = sizes[i];
+ if( cn > 1 )
+ _sizes[dims++] = cn;
+ PyObject* o = PyArray_SimpleNew(dims, _sizes, typenum);
+ if(!o)
+ CV_Error_(Error::StsError, ("The numpy array of typenum=%d, ndims=%d can not be created", typenum, dims));
+ return allocate(o, dims0, sizes, type, step);
+ }
+
+ bool allocate(UMatData* u, int accessFlags) const
+ {
+ return stdAllocator->allocate(u, accessFlags);
+ }
+
+ void deallocate(UMatData* u) const
+ {
+ if(u)
+ {
+ PyEnsureGIL gil;
+ PyObject* o = (PyObject*)u->userdata;
+ Py_XDECREF(o);
+ delete u;
+ }
+ }
+
+ const MatAllocator* stdAllocator;
+};
+#else
+class NumpyAllocator : public MatAllocator
+{
+public:
+ NumpyAllocator() {}
+ ~NumpyAllocator() {}
+
+ void allocate(int dims, const int* sizes, int type, int*& refcount,
+ uchar*& datastart, uchar*& data, size_t* step)
+ {
+ PyEnsureGIL gil;
+
+ int depth = CV_MAT_DEPTH(type);
+ int cn = CV_MAT_CN(type);
+ const int f = (int)(sizeof(size_t)/8);
+ int typenum = depth == CV_8U ? NPY_UBYTE : depth == CV_8S ? NPY_BYTE :
+ depth == CV_16U ? NPY_USHORT : depth == CV_16S ? NPY_SHORT :
+ depth == CV_32S ? NPY_INT : depth == CV_32F ? NPY_FLOAT :
+ depth == CV_64F ? NPY_DOUBLE : f*NPY_ULONGLONG + (f^1)*NPY_UINT;
+ int i;
+ npy_intp _sizes[CV_MAX_DIM+1];
+ for( i = 0; i < dims; i++ )
+ _sizes[i] = sizes[i];
+ if( cn > 1 )
+ {
+ /*if( _sizes[dims-1] == 1 )
+ _sizes[dims-1] = cn;
+ else*/
+ _sizes[dims++] = cn;
+ }
+ PyObject* o = PyArray_SimpleNew(dims, _sizes, typenum);
+ if(!o)
+ CV_Error_(CV_StsError, ("The numpy array of typenum=%d, ndims=%d can not be created", typenum, dims));
+ refcount = refcountFromPyObject(o);
+ npy_intp* _strides = PyArray_STRIDES((PyArrayObject*) o);
+ for( i = 0; i < dims - (cn > 1); i++ )
+ step[i] = (size_t)_strides[i];
+ datastart = data = (uchar*)PyArray_DATA((PyArrayObject*) o);
+ }
+
+ void deallocate(int* refcount, uchar*, uchar*)
+ {
+ PyEnsureGIL gil;
+ if( !refcount )
+ return;
+ PyObject* o = pyObjectFromRefcount(refcount);
+ Py_INCREF(o);
+ Py_DECREF(o);
+ }
+};
+#endif
+
+
+
+NumpyAllocator g_numpyAllocator;
+
+NDArrayConverter::NDArrayConverter() { init(); }
+
+void NDArrayConverter::init()
+{
+ import_array();
+}
+
+cv::Mat NDArrayConverter::toMat(const PyObject *o)
+{
+ cv::Mat m;
+
+ if(!o || o == Py_None)
+ {
+ if( !m.data )
+ m.allocator = &g_numpyAllocator;
+ }
+
+ if( !PyArray_Check(o) )
+ {
+ failmsg("toMat: Object is not a numpy array");
+ }
+
+ int typenum = PyArray_TYPE(o);
+ int type = typenum == NPY_UBYTE ? CV_8U : typenum == NPY_BYTE ? CV_8S :
+ typenum == NPY_USHORT ? CV_16U : typenum == NPY_SHORT ? CV_16S :
+ typenum == NPY_INT || typenum == NPY_LONG ? CV_32S :
+ typenum == NPY_FLOAT ? CV_32F :
+ typenum == NPY_DOUBLE ? CV_64F : -1;
+
+ if( type < 0 )
+ {
+ failmsg("toMat: Data type = %d is not supported", typenum);
+ }
+
+ int ndims = PyArray_NDIM(o);
+
+ if(ndims >= CV_MAX_DIM)
+ {
+ failmsg("toMat: Dimensionality (=%d) is too high", ndims);
+ }
+
+ int size[CV_MAX_DIM+1];
+ size_t step[CV_MAX_DIM+1], elemsize = CV_ELEM_SIZE1(type);
+ const npy_intp* _sizes = PyArray_DIMS(o);
+ const npy_intp* _strides = PyArray_STRIDES(o);
+ bool transposed = false;
+
+ for(int i = 0; i < ndims; i++)
+ {
+ size[i] = (int)_sizes[i];
+ step[i] = (size_t)_strides[i];
+ }
+
+ if( ndims == 0 || step[ndims-1] > elemsize ) {
+ size[ndims] = 1;
+ step[ndims] = elemsize;
+ ndims++;
+ }
+
+ if( ndims >= 2 && step[0] < step[1] )
+ {
+ std::swap(size[0], size[1]);
+ std::swap(step[0], step[1]);
+ transposed = true;
+ }
+
+ // std::cerr << " ndims: " << ndims
+ // << " size: " << size
+ // << " type: " << type
+ // << " step: " << step
+ // << " size: " << size[2] << std::endl;
+
+ // TODO: Possible bug in multi-dimensional matrices
+#if 1
+ if( ndims == 3 && size[2] <= CV_CN_MAX && step[1] == elemsize*size[2] )
+ {
+ ndims--;
+ type |= CV_MAKETYPE(0, size[2]);
+ }
+#endif
+
+ if( ndims > 2)
+ {
+ failmsg("toMat: Object has more than 2 dimensions");
+ }
+
+ m = Mat(ndims, size, type, PyArray_DATA(o), step);
+ // m.u = g_numpyAllocator.allocate(o, ndims, size, type, step);
+
+ if( m.data )
+ {
+#if OPENCV_3
+ m.addref();
+ Py_INCREF(o);
+#else
+ m.refcount = refcountFromPyObject(o);
+ m.addref(); // protect the original numpy array from deallocation
+ // (since Mat destructor will decrement the reference counter)
+#endif
+ };
+ m.allocator = &g_numpyAllocator;
+
+ if( transposed )
+ {
+ Mat tmp;
+ tmp.allocator = &g_numpyAllocator;
+ transpose(m, tmp);
+ m = tmp;
+ }
+ return m;
+}
+
+PyObject* NDArrayConverter::toNDArray(const cv::Mat& m)
+{
+#if OPENCV_3
+ if( !m.data )
+ Py_RETURN_NONE;
+ Mat temp, *p = (Mat*)&m;
+ if(!p->u || p->allocator != &g_numpyAllocator)
+ {
+ temp.allocator = &g_numpyAllocator;
+ m.copyTo(temp);
+ p = &temp;
+ }
+ PyObject* o = (PyObject*)p->u->userdata;
+ Py_INCREF(o);
+ // p->addref();
+ // pyObjectFromRefcount(p->refcount);
+ return o;
+#else
+ if( !m.data )
+ Py_RETURN_NONE;
+ Mat temp, *p = (Mat*)&m;
+ if(!p->refcount || p->allocator != &g_numpyAllocator)
+ {
+ temp.allocator = &g_numpyAllocator;
+ ERRWRAP2(m.copyTo(temp));
+ p = &temp;
+ }
+ p->addref();
+ return pyObjectFromRefcount(p->refcount);
+#endif
+
+}
diff --git a/wrapper_python/utils/conversion.h b/wrapper_python/utils/conversion.h
new file mode 100644
index 0000000..8ce616d
--- /dev/null
+++ b/wrapper_python/utils/conversion.h
@@ -0,0 +1,75 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+// Author: Sudeep Pillai (spillai@csail.mit.edu)
+// Note: Stripped from Opencv (opencv/modules/python/src2/cv2.cpp)
+
+#pragma once
+
+#include <Python.h>
+#include <opencv2/opencv.hpp>
+#include <opencv2/core/core.hpp>
+#include <numpy/ndarrayobject.h>
+
+static PyObject* opencv_error = 0;
+
+static int failmsg(const char *fmt, ...);
+
+class PyAllowThreads;
+
+class PyEnsureGIL;
+
+#define ERRWRAP2(expr) \
+try \
+{ \
+ PyAllowThreads allowThreads; \
+ expr; \
+} \
+catch (const cv::Exception &e) \
+{ \
+ PyErr_SetString(opencv_error, e.what()); \
+ return 0; \
+}
+
+static PyObject* failmsgp(const char *fmt, ...);
+
+static size_t REFCOUNT_OFFSET = (size_t)&(((PyObject*)0)->ob_refcnt) +
+ (0x12345678 != *(const size_t*)"\x78\x56\x34\x12\0\0\0\0\0")*sizeof(int);
+
+static inline PyObject* pyObjectFromRefcount(const int* refcount)
+{
+ return (PyObject*)((size_t)refcount - REFCOUNT_OFFSET);
+}
+
+static inline int* refcountFromPyObject(const PyObject* obj)
+{
+ return (int*)((size_t)obj + REFCOUNT_OFFSET);
+}
+
+
+class NumpyAllocator;
+
+enum { ARG_NONE = 0, ARG_MAT = 1, ARG_SCALAR = 2 };
+
+class NDArrayConverter
+{
+private:
+ void init();
+public:
+ NDArrayConverter();
+ cv::Mat toMat(const PyObject* o);
+ PyObject* toNDArray(const cv::Mat& mat);
+};
diff --git a/wrapper_python/utils/template.h b/wrapper_python/utils/template.h
new file mode 100644
index 0000000..3f0b535
--- /dev/null
+++ b/wrapper_python/utils/template.h
@@ -0,0 +1,44 @@
+/*
+This file is part of BGSLibrary.
+
+BGSLibrary is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+BGSLibrary is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
+*/
+// Author: Sudeep Pillai (spillai@csail.mit.edu)
+// Note: Stripped from pyxx project
+
+#pragma once
+
+#include <boost/python.hpp>
+/*
+ * Provides template support
+ */
+
+template<typename TemplateType>
+struct expose_template_type
+{
+ // do nothing!
+};
+
+template<typename TemplateType>
+struct expose_template_type_base
+{
+ bool wrapped()
+ {
+ using namespace boost::python::converter;
+ using namespace boost::python;
+ registration const * p = registry::query( type_id<TemplateType>() );
+ return p && (p->m_class_object || p->m_to_python);
+ }
+
+};
--
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