diff --git a/Demo2.cpp b/Demo2.cpp
index cbb6edbda8ff6af27b740c33d0a6ae189f91f0ec..3ce643189c85c8a74096a9ab7be41d45450cdba9 100644
--- a/Demo2.cpp
+++ b/Demo2.cpp
@@ -1,106 +1,665 @@
/*
-This file is part of BGSLibrary.
+./bgs_demo -i test45/ -a 100 -o test45/results/
+based on original demo.cpp
+*/
-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.
+//cpp c
+#include <iostream>
+#include <algorithm>
+#include <cstdlib>
+#include <stdio.h> /* printf, scanf, puts, NULL */
+#include <stdlib.h> /* srand, rand */
+#include <time.h> /* time */
+#include <ctime>
-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 <iostream>
-#include <opencv2/opencv.hpp>
+#define PROCESS_CENTER_VERSION_MAJOR 0
+#define PROCESS_CENTER_VERSION_MINOR 6
+//opencv
+#include <opencv2/opencv.hpp>
+//bgslibrary
#include "package_bgs/bgslibrary.h"
+//my class
+#include "package_bgs/Tapter.h"
+#include "package_bgs/ttoolbox.h"
+
+using namespace cv;
+using namespace std;
-int main(int argc, char **argv)
+char* getCmdOption(char ** begin, char ** end, const std::string & option)
{
- std::cout << "Using OpenCV " << CV_MAJOR_VERSION << "." << CV_MINOR_VERSION << "." << CV_SUBMINOR_VERSION << std::endl;
-
- /* Background Subtraction Methods */
- IBGS *bgs;
-
- //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; // 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;
- //bgs = new MultiLayer;
- //bgs = new PixelBasedAdaptiveSegmenter;
- //bgs = new LBSimpleGaussian;
- //bgs = new LBFuzzyGaussian;
- //bgs = new LBMixtureOfGaussians;
- bgs = new LBAdaptiveSOM;
- //bgs = new LBFuzzyAdaptiveSOM;
- //bgs = new LBP_MRF;
- //bgs = new VuMeter;
- //bgs = new KDE;
- //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')
- {
- std::stringstream ss;
- ss << frameNumber;
- 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;
-
- cv::imshow("input", img_input);
-
- cv::Mat img_mask;
- cv::Mat img_bkgmodel;
- 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;
+ char ** itr = std::find(begin, end, option);
+ if (itr != end && ++itr != end)
+ {
+ return *itr;
+ }
+ return 0;
+}
+
+bool cmdOptionExists(char** begin, char** end, const std::string& option)
+{
+ return std::find(begin, end, option) != end;
+}
+
+
+int main(int argc, char * argv[])
+{
+ std::cout << "using produce bk " <<PROCESS_CENTER_VERSION_MAJOR <<"."<< PROCESS_CENTER_VERSION_MINOR << endl;
+ std::cout << "Using OpenCV " << CV_MAJOR_VERSION << "." << CV_MINOR_VERSION << "." << CV_SUBMINOR_VERSION << std::endl;
+ //!** parse programm input****************/
+ if(cmdOptionExists(argv, argv+argc, "-h"))
+ {
+ cout <<" error: please use command as\n./bgs_demo -i pathToInputDir -a amountOfJpgFiles -c exactCenterConfFile.xml -o outPutPath"<<endl;
+ return EXIT_FAILURE;
+ }
+ if(!cmdOptionExists(argv, argv+argc, "-i")||!cmdOptionExists(argv, argv+argc, "-a")||!cmdOptionExists(argv, argv+argc, "-o") )
+ {
+ cout <<" error: please use command as\n./bgs_demo -i pathToInputDir -a amountOfJpgFiles -c exactCenterConfFile.xml -o outPutPath"<<endl;
+ return EXIT_FAILURE;
+ }
+
+ char *testInputDir = getCmdOption(argv, argv + argc, "-i");
+ string inputDir(".");
+ if (testInputDir)
+ {
+ //test dir exists
+ inputDir = string(testInputDir);
+ }
+ int amountFiles = -1;
+ char *testFileAmount = getCmdOption(argv, argv + argc, "-a");
+ if (testFileAmount)
+ {
+ string s(testFileAmount);
+ stringstream foo(s);
+ foo >> amountFiles;
+ }
+
+
+ char *centerFile = getCmdOption(argv, argv + argc, "-c");
+ string centerFileString(".");
+ if (centerFile)
+ {
+ //test dir exists
+ centerFileString = string(centerFile);
+ }
+
+ char *testOutputDir = getCmdOption(argv, argv + argc, "-o");
+ string outputDir(".");
+ if (testOutputDir)
+ {
+ //test dir exists
+ outputDir = string(testOutputDir);
+ }
+
+ cout <<"args: -i "<<inputDir<<" -a "<<amountFiles << " -c" << centerFileString<<" -o " << outputDir;
+ //!**** end parse input***********/
+
+ //./program -i pathToInputDir -a amountOfJpgFiles -o outPutPath
+
+ //pathToInputDir
+ //----should have
+ // centerFile.xml
+ // -data/
+ // #which include all jpg and tt files
+ // first file mus be: 0000000000.jpg
+ // -bk.jpg
+ // #is the neutral bk file for training the bgs method
+ //
+
+
+ // VideoCapture capture;
+
+ // if (argc > 1)
+ // {
+ // std::cout << "Openning: " << argv[1] << std::endl;
+ // capture.open(argv[1]);
+ // }
+ // else
+ // capture.open(0);
+
+ // if (!capture.isOpened())
+ // {
+ // std::cerr << "Cannot initialize video!" << std::endl;
+ // return -1;
+ // }
+
+ /* Background Subtraction Methods */
+ //IBGS *bgs;
+
+ //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; // 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;
+ //bgs = new MultiLayer;
+ //bgs = new PixelBasedAdaptiveSegmenter;
+ //bgs = new LBSimpleGaussian;
+ //bgs = new LBFuzzyGaussian;
+ //bgs = new LBMixtureOfGaussians;
+ //bgs = new LBAdaptiveSOM;
+ //bgs = new LBFuzzyAdaptiveSOM;
+ //bgs = new LBP_MRF;
+ //bgs = new VuMeter;
+ //bgs = new KDE;
+ //bgs = new IndependentMultimodal;
+ //bgs = new MultiCue;
+ //bgs = new SigmaDelta;
+ //bgs = new SuBSENSE;
+ //bgs = new LOBSTER;
+ //bgs = new PAWCS;
+ //bgs = new TwoPoints;
+ //bgs = new ViBe;
+ //bgs = new Tapter;
+
+ Tapter *bgs = new Tapter;
+
+ // bgs->setPathOut(outputDir);
+ // bgs->setInitialFrameCounter(0);
+ // bgs->setFlagWrite(0);
+ // bgs->setFlagWriteDBGpic(0);
+
+
+ //see paper https://dl.acm.org/citation.cfm?id=2321600
+ //https://ieeexplore.ieee.org/document/4527178/
+ //was in benchmark on top https://www.researchgate.net/publication/259340906_A_comprehensive_review_of_background_subtraction_algorithms_evaluated_with_synthetic_and_real_videos
+ //my own adapter to use the model
+
+ int i= 0;
+ cv::Mat img_input;
+
+ //init the random number generator
+ srand (time(NULL));
+
+ clock_t beginAll = clock();
+
+ //! we read the center config file for cut out the ROI
+ //TODO merge this config with the Tapter.xml ??
+ //circle param
+ int circleCenterX = 880;
+ int circleCenterY = 750;
+ int circleRadius = 700;
+ cv::String configFileNameCenter(centerFileString);
+ //read the config
+ cout << "parameter of centerConfigFile.xml"<<endl;
+ FileStorage fsCen;
+ fsCen.open(configFileNameCenter, FileStorage::READ);
+ if (!fsCen.isOpened())
+ {
+ cout << "error during open " <<centerFileString << " will abort\n ";
+ return EXIT_FAILURE;
+ }
+
+ circleCenterX = (int) fsCen["circleCenterX"];
+ cout <<"circleCenterX: "<< circleCenterX<<endl;
+
+ circleCenterY = (int) fsCen["circleCenterY"];
+ cout <<"circleCenterY: "<< circleCenterY<<endl;
+
+ circleRadius = (int) fsCen["circleRadius"];
+ cout <<"circleRadius: "<< circleRadius<<endl;
+ fsCen.release();
+
+ // //first the static pic**********
+ // //std::string fileName = getFileName(begin);
+ // std::string staticFile = inputDir+"/bk.jpg";
+ // cout <<"a) load first static background pic :"<< staticFile<<endl;
+ // img_input = imread(staticFile.c_str(), CV_LOAD_IMAGE_COLOR);
+ // if(img_input.data )
+ // {
+ // //we cut out a smaller ROI
+ // img_input = TToolBox::cropImageCircle(img_input,circleCenterX,circleCenterY,circleRadius);
+
+ // cv::Mat img_mask;
+ // cv::Mat img_bkgmodel;
+ // bgs->process(img_input, img_mask, img_bkgmodel);
+ // }
+ // else
+ // {
+ // cout<<"error loading file: "<< staticFile<<", will abort"<<endl;
+ // return EXIT_FAILURE;
+ // }
+
+ std::string fileName;
+
+ //! we train with first x on random draws
+ //int amountTrainingSteps = 2;
+ // //we open the config file and readin
+ // cv::String configFileName("./config/Tapter.xml");
+ // {//read the config
+ // FileStorage fs;
+ // fs.open(configFileName, FileStorage::READ);
+ // if (!fs.isOpened())
+ // {
+ // cout << "error during open " << configFileName << " will abort " <<endl;
+ // return EXIT_FAILURE;
+ // }
+ // //param
+ // amountTrainingSteps = (int) fs["trainingSteps"];
+ // //cout <<"amountTrainingSteps: "<< amountTrainingSteps<< endl;
+ // fs.release();
+ // }
+
+ cout <<"a) we choose two random file "<< fileName<<endl;
+ //int j=255;
+
+ vector<Mat> picsMask;
+ vector<Mat> picsOrigin;
+ int maxTrain = 10;
+ vector<string> myRandomTrainList; //we save all draws in a list which will save to the results
+ for(i=0;i<maxTrain;i++)
+ {
+
+ //random index
+ int index = rand() % amountFiles; //TODO: double check no double draw ??
+ fileName = inputDir + TToolBox::getFileName(index);
+ myRandomTrainList.push_back(fileName);
+
+ cout <<"\t"<<i <<"\t of \t"<<maxTrain<<" rnd file :"<< fileName<<endl;
+ img_input = imread(fileName.c_str(), CV_LOAD_IMAGE_COLOR);
+
+
+ if(img_input.data )
+ {
+
+ //we cut out a smaller ROI
+ img_input = TToolBox::cropImageCircle(img_input,circleCenterX,circleCenterY,circleRadius);
+
+ //cv::imshow("input", img_input);
+ cv::Mat img_mask;
+ cv::Mat img_bkgmodel;
+
+ // //adapter learning rate
+ // if(j>62)
+ // bgs->setLearningRate(j);
+
+
+ bgs->process(img_input, img_mask, img_bkgmodel); // by default, it shows automatically the foreground mask image
+
+ if(i>=(maxTrain-2))
+ {
+ picsMask.push_back(img_mask.clone());
+ picsOrigin.push_back(img_input.clone());
+ }
+
+ // //we save the bk gmodel
+ // std::string bkTestFileName = inputDir + "bk_"+TToolBox::mNzero(i)+".jpg";
+ // imwrite(bkTestFileName.c_str(),img_bkgmodel);
+ }
+ else
+ {
+ cout<<"error loading file: "<< fileName<<", will abort"<<endl;
+ return EXIT_FAILURE;
+ }
+ }
+
+
+ cout <<"b) we calc the two polygones of the points"<< fileName<<endl;
+
+ if(picsMask.empty())
+ {
+ cout<<"error no pics loaded"<<endl;
+ return EXIT_FAILURE;
+ }
+ else
+ cout<<"pics.size(): "<<picsMask.size()<<endl;
+
+ int frameCounter = 0;
+ //vector<vector<vector<Point>>> polyGones;
+ vector<RotatedRect> rectanglesPicA;//we will save the rectangles for each polygone which was selected
+ vector<RotatedRect> rectanglesPicB;
+
+ for(frameCounter=0;frameCounter<2;frameCounter++)
+ {
+ Mat img_mask = picsMask[frameCounter];
+
+ //! step 3) we make we apply a edge detection
+ //TODO make this in a function, how many times is this listed ??
+ //TODO read from tapter config
+ //TODO all parameter from applyCannyEdgeAndCalcCountours also !!
+ double threshholdMin = 150;
+ double threshholdMax = 200;
+ int apertureSize = 3;
+ std::vector<vector<Point> > contours = TToolBox::applyCannyEdgeAndCalcCountours(img_mask,threshholdMin,threshholdMax,apertureSize);
+
+
+ // //TODO: we need to order the points to get a nice polygon, otherwise not usefull
+ // //we also try to find the aproximate polygon*****************
+ //// vector<Point> aproxiCurve;
+
+ //// // //see https://docs.opencv.org/3.4/d3/d63/classcv_1_1Mat.html#a167a8e0a3a3d86e84b70e33483af4466
+ //// // if(aproxiCurve::checkVector(10,CV_32F)==-1)
+ //// // cout<<"error wrong format of vector"<<endl;
+
+ //// //calc 0.1 percent of arc length of convex hull
+ //// double epsilon = 0.1 * cv::arcLength(hullComplete,true);
+
+ //// //see https://docs.opencv.org/2.4.13.2/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html#approxpolydp
+ //// cv::approxPolyDP(allContourPoints,aproxiCurve,epsilon,false);
+
+ ////#ifdef MC_SHOW_STEP_ANALYSE
+ //// if(aproxiCurve.size()>=2)//we only draw if we have at least a line
+ //// {
+ //// Mat imgPolyApr = Mat::zeros( img_input.size(), CV_8UC3 );
+ //// imgPolyApr = Scalar(255,255,255); //fille the picture
+ //// Scalar colorC( 0,0,255,255 );//red
+
+
+ //// //for(imgPolyApr)
+
+ //// polylines(imgPolyApr, aproxiCurve, true, colorC, 1, 8);
+
+ //// cv::String outpath3= "/homes/tb55xemi/work/bugTrainingSet/testRec/rec04379437pp/result/";
+ //// std::ostringstream convert3;
+ //// convert3 << outpath3 << frameCounter <<"_appr_poly.jpg";
+ //// cv::imwrite(convert3.str().c_str(), imgPolyApr);
+ //// }
+ //// else
+ //// cout<<"approximate poly has not enough points will skip file: "<<frameCounter<<endl;
+
+ ////#endif
+
+
+ //! step 4) we make a selection out of all counters with area sizes******************************
+ vector<vector<Point> > contourSelection;
+ //we exlcude very small one and very big ones
+
+ //we calc all min rotated rectangles for all contour from candy egde detect
+ vector<RotatedRect> minRect( contours.size() );
+
+ //calc boxes around the contours
+ for( size_t i = 0; i < contours.size(); i++ )
+ minRect[i] = minAreaRect( Mat(contours[i]) ); //may use boundingRect ?? to use fix non rotated rectangles ?
+
+ vector<Point2f> recCenterPoints;
+ float areaMinThreshold = 150;
+ float areaMaxThreshold = 15000; //TODO apply moving filter ??, an more adaptive approach
+
+ //iterate all rectangles
+ for( size_t i = 0; i< minRect.size(); i++ )
+ {
+ Point2f rect_points[4];
+ //get all points of the retange
+ minRect[i].points( rect_points );
+
+ //construct contour based on rectangle points because contour != rectangle with points
+ vector<Point> contourRect;
+ for(int j=0;j<4;j++)
+ contourRect.push_back(rect_points[j]);
+
+ //calc the area of the contour
+ double area0 = contourArea(contourRect);
+ //over stepp all small areas
+ if(area0<areaMinThreshold||area0>areaMaxThreshold)
+ {
+ cout<<i<<":area0:"<<area0<<" dismissed "<<endl;
+ //skipe if the area is too small
+ continue;
+ }
+ else
+ {
+ cout<<i<<":area0:"<<area0<<" choose "<<endl;
+ //we add the rectangles to the list
+ if(frameCounter==0)
+ rectanglesPicA.push_back(minRect[i]);
+ if(frameCounter==1)
+ rectanglesPicB.push_back(minRect[i]);
+
+ //get the center of this rectangle
+ Point2f center = minRect[i].center;
+ recCenterPoints.push_back(center);
+
+ //we also add the this contour to a selection
+ contourSelection.push_back(contours[i]);
+
+ }
+ }//end iterate all min rectangle
+
+ // //! step 5) we calc the moments from the contour selection
+ // vector<Moments> mu(contourSelection.size() );
+ // for( size_t i = 0; i < contourSelection.size(); i++ )
+ // {
+ // mu[i] = moments( contourSelection[i], false );
+ // }
+
+ // // Get the mass centers:
+ // vector<Point2f> massCenters( contourSelection.size() );
+ // for( size_t i = 0; i < contourSelection.size(); i++ )
+ // {
+ // massCenters[i] = Point2f( mu[i].m10/mu[i].m00 , mu[i].m01/mu[i].m00 );
+ // }
+
+ // //! step 6) calc convex hull of all points of the contour selection *********
+ // //TODO produce center of convex hull of all polygones
+ // //TODO double check if ne contour sharing a center point ? nearby ??
+
+ // //we merge all points
+ // vector<Point> allContourPoints;
+ // for (size_t cC = 0; cC < contourSelection.size(); ++cC)
+ // for(size_t cP =0; cP < contourSelection[cC].size(); cP++)
+ // {
+ // Point currentContourPixel = contourSelection[cC][cP];
+ // allContourPoints.push_back(currentContourPixel);
+ // }
+
+ // // calc the hull ******************
+ // vector<Point> conHull(allContourPoints.size());
+ // convexHull( Mat(allContourPoints), conHull, false );
+ // // Point roiCenter;
+ // // float roiRadius;
+
+ // //calc the min circle around
+ // //minEnclosingCircle(conHull,roiCenter,roiRadius);
+ // //we calc the mass center of the convex hull
+
+ // ///we calc the mass center of the convex hull
+ // Moments muConvexHull;
+ // Point2f muConvexHullMassCenter(0.0,0.0);
+ // if(!conHull.empty())
+ // {
+ // muConvexHull = moments(conHull, true );
+ // muConvexHullMassCenter= Point2f( muConvexHull.m10/muConvexHull.m00 , muConvexHull.m01/muConvexHull.m00 );
+ // }
+
+ //#ifdef MC_SHOW_STEP_ANALYSE
+
+ // if(!conHull.empty())//if we any elements, we process further
+ // {
+ // Mat imgConvexHull = Mat::zeros( img_input.size(), CV_8UC3 );
+ // imgConvexHull = Scalar(255,255,255); //fille the picture
+
+ // Scalar colorB( 0,0,255,255 );//red
+ // polylines(imgConvexHull, hullComplete, true, colorB, 1, 8);
+
+ // //draw circle around
+ // //circle( imgConvexHull, roiCenter, (int) roiRadius, colorB, 2, 8, 0 );
+
+ // //we draw it
+ // cv::String outpath2= outputDir;
+ // std::ostringstream convert2;
+ // convert2 << outpath2 <<TToolBox::mNzero(frameCounter) <<"_convex_hull.jpg";
+ // cv::imwrite(convert2.str().c_str(), imgConvexHull);
+ // }
+ // else
+ // cout<<"convex hull has no points will skip file: "<<i<<endl;
+
+ //#endif
+
+ // //! step 8: we write down all our results in yml file
+ // std::string nameOutPutFileData = outputDir + TToolBox::mNzero(frameCounter) + ".yml";
+
+ // FileStorage fs(nameOutPutFileData.c_str(), FileStorage::WRITE);
+ // fs << "masscenters" << massCenters;
+ // fs << "polygonselection"<< contourSelection;
+ // fs << "convexhull"<<conHull;
+ // fs << "masscenterconvexhull"<<muConvexHullMassCenter;
+ // fs.release();
+
+
+ // //! we write from time to time a dbg picture
+ // if(frameCounter%everyPic==0)
+ // {
+ // Scalar colorRed( 0,0,255,255 );//red
+ // RNG rng(4344234);
+ // Mat imgDebugPaint2 = Mat::zeros( img_input.size(), CV_8UC3 );
+ // imgDebugPaint2 = Scalar(255,255,255); //fill the picture white
+
+ // //we write all polyies of the selection and the mass centers with a random color
+ // for( size_t i = 0; i< contourSelection.size(); i++ )
+ // {
+ // //random color
+ // Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
+ // //contour
+ // drawContours( imgDebugPaint2, contourSelection, i, color, 1, LINE_AA);
+ // //draw the center
+ // circle( imgDebugPaint2, massCenters[i], 4, color, -1, 8, 0 );
+ // }
+
+ // //we write the convex hull
+ // if(!conHull.empty())
+ // {
+ // //the poly
+ // polylines(imgDebugPaint2, conHull, true, colorRed, 1, 8);
+ // //the center
+ // circle( imgDebugPaint2,muConvexHullMassCenter, 4, colorRed, -1, 8, 0 );
+ // }
+
+ // //we make a copy
+ // Mat imgOverlay2 = img_input.clone();
+ // //we add a overlay of our paitings
+ // addWeighted( imgDebugPaint2, 0.7, imgOverlay2, 0.3, 0.0, imgOverlay2);
+ // //we write the file down
+ // std::string nameOutPutFileDBGpic = outputDir + TToolBox::mNzero(frameCounter) + ".jpg";
+ // imwrite(nameOutPutFileDBGpic.c_str(),imgOverlay2);
+
+ // }
+
+ }//end for iterate frame
+
+
+ if(rectanglesPicA.empty()||rectanglesPicB.empty())
+ cout<<"error no retangles found in pics "<<endl;
+
+ Mat picA = picsOrigin[0].clone();
+ Mat picB = picsOrigin[1].clone();
+ //now we iterate all rectangles in picA and will produce pictures
+ for(size_t i=0;i<rectanglesPicA.size();i++)
+ {
+ std::string filenName = outputDir + "bk_candidate_a_" + TToolBox::mNzero(i) + ".jpg";
+ cout << "process picA i"<<i<<" name" <<filenName << endl;
+
+ //get the points
+ RotatedRect rectA= rectanglesPicA[i];
+ Point2f rectApoints[4];
+ //get all points of the retange
+ rectA.points( rectApoints );
+ //@see https://docs.opencv.org/3.4.0/db/dd6/classcv_1_1RotatedRect.html#a69d648b086f26dbce0029facae9bfb2d
+ //The points array for storing rectangle vertices.
+ //The order is bottomLeft, topLeft, topRight, bottomRight.
+ Point2f corner = rectApoints[1];
+ //we should add some offset
+ int offset = 50; //TODO double check offset
+ Point2f cornerOffset= Point2f((float)( corner.x-offset), (float) (corner.y-offset));
+
+
+ Rect rect = rectA.boundingRect();
+ //TODO check if out of our area
+ Rect rectOffset = Rect((float) (cornerOffset.x),(float) (cornerOffset.y),(float)(rect.width + offset) ,(float) (rect.height+offset )) ;
+ Mat imageRoi = picB(rectOffset);
+
+ // std::string filenNameROI = outputDir + "bk_test_a_roi_" + TToolBox::mNzero(i) + ".jpg";
+ // imwrite(filenNameROI.c_str(),imageRoi);
+
+ //imageRoi = Scalar( 255, 0, 0); //fill blue)
+
+ // std::cout << "rect size: " << rect.size() << std::endl;
+ // std::cout << "tempResult cols,rows: " << picB.cols << ", " << picB.rows << endl;
+
+ cv::Rect rectROI(cornerOffset.x,cornerOffset.y, imageRoi.cols, imageRoi.rows);
+ imageRoi.copyTo(picA(rectROI));
+
+ cout << "."<<endl;
+
+ imwrite(filenName.c_str(),picA);
+ }
+ //now we iterate all rectangles and will produce pictures
+ for(size_t i=0;i<rectanglesPicB.size();i++)
+ {
+
+ std::string filenName = outputDir + "bk_candidate_b_" + TToolBox::mNzero(i) + ".jpg";
+ cout << "process picB i"<<i<<" name" <<filenName << endl;
+
+ //get the points
+ RotatedRect rectB= rectanglesPicB[i];
+ Point2f rectBpoints[4];
+ //get all points of the retange
+ rectB.points( rectBpoints );
+ //@see https://docs.opencv.org/3.4.0/db/dd6/classcv_1_1RotatedRect.html#a69d648b086f26dbce0029facae9bfb2d
+ //The points array for storing rectangle vertices.
+ //The order is bottomLeft, topLeft, topRight, bottomRight.
+ Point2f corner = rectBpoints[1];
+ //we should add some offset
+ int offset = 50; //TODO double check offset
+ Point2f cornerOffset= Point2f((float)( corner.x-offset), (float) (corner.y-offset));
+
+ Rect rect = rectB.boundingRect();
+ //TODO check if out of our area
+ Rect rectOffset = Rect((float) (cornerOffset.x),(float)(cornerOffset.y),(float)(rect.width+offset) ,(float) (rect.height+offset)) ;
+ Mat imageRoi = picA(rectOffset);
+
+ // std::string filenNameROI = outputDir + "bk_test_a_roi_" + TToolBox::mNzero(i) + ".jpg";
+ // imwrite(filenNameROI.c_str(),imageRoi);
+
+ //imageRoi = Scalar( 255, 0, 0); //fill blue)
+
+ // std::cout << "rect size: " << rect.size() << std::endl;
+ // std::cout << "tempResult cols,rows: " << picB.cols << ", " << picB.rows << endl;
+
+ cv::Rect rectROI(cornerOffset.x,cornerOffset.y, imageRoi.cols, imageRoi.rows);
+ imageRoi.copyTo(picB(rectROI));
+
+ cout << "."<<endl;
+
+ imwrite(filenName.c_str(),picB);
+
+ }
+
+ // //we calc the time which we used for a picture
+ // clock_t end = clock();
+ // double elapsedSecs = double(end - begin) / CLOCKS_PER_SEC;
+
+
+ // //we calc the time which was used for all picture
+ // clock_t endAll = clock();
+ // double elapsedSecTotal = double(endAll - beginAll) / CLOCKS_PER_SEC;
+ // cout <<"process single pic:\t"<<elapsedSecs<<" s - \t\t"<<(int)(elapsedSecTotal/60)<<" min -\t"<<(int)(elapsedSecTotal/60/60)<<" h"<<endl;
+
+
+
+
+ delete bgs;
+
+ // capture.release();
+ cvDestroyAllWindows();
+
+ return 0;
}