ttoolbox.cpp

#include "ttoolbox.h"

std::string TToolBox::mNzero(int i)
{
    std::ostringstream convert;
    convert << i ;
    std::string numberString = convert.str();
    std::string newNumberString = std::string(10 - numberString.length(), '0') + numberString;
    return newNumberString;
}
std::string TToolBox::getFileName(int i)
{
    std::string fileName =std::string ( std::string ("/data/")+  mNzero(i) + std::string (".jpg"));
    return fileName;
}

std::vector<std::vector<cv::Point>> TToolBox::applyCannyEdgeAndCalcCountours(cv::Mat imgSource, double threshholdMin, double threshholdMax, int apertureSize)
{
    cv::Mat imgCannyEdge;
    std::vector<std::vector<cv::Point> > contours;
    std::vector<cv::Vec4i> hierarchy;

    //! 2 make a copy
    cv::Mat imgBinary = imgSource.clone();
    //imgMarkBinary = Scalar(255,255,255); //fill white

    //! 3 apply binary filter not reduce noise
    //method to threshold important changes
    int binaryThreshold = 80; //TODO as parameter
    imgBinary = imgSource > binaryThreshold;


    //! 4 smooth with gaussian filter to suppress no connected lines
    //add a gaussian filter //see http://docs.opencv.org/2.4/doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.html
    cv::Mat imgSmoothed = imgBinary.clone();
    int exclusPara3 = 3; //TODO as parameter
    cv::GaussianBlur(imgBinary,imgSmoothed,cv::Size(exclusPara3,exclusPara3),0);  //0 = BORDER_CONSTANT

    //! 5 we make the canny edge detect
    // Detect edges using canny
    cv::Canny( imgSmoothed, imgCannyEdge, threshholdMin, threshholdMax, apertureSize );

    // Find contours, use RETR_EXTERNAL ignore inner child structures, TREE more usefull ?
    cv::findContours( imgCannyEdge, contours, hierarchy, cv::RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0) );

#ifdef  MC_SHOW_STEP_ANALYSE
    // Draw contours on extra mat
    Mat imgContour = Mat::zeros( imgCannyEdge.size(), CV_8UC3 );
    imgContour =  Scalar(255,255,255); //fille the picture
    RNG rng(232323);
    for( size_t i = 0; i< contours.size(); i++ )
    {
        //random color
        Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
        //contour
        drawContours( imgContour, contours, i, color, 1, LINE_AA, hierarchy, 0, Point() );
    }

    cv::String outpath=  "/homes/tb55xemi/work/bugTrainingSet/testRec/rec04379437pp/result/";
    std::ostringstream convert;
    convert << outpath << frameCounter <<"_countour_canny_edge.jpg";
    cv::imwrite(convert.str().c_str(), imgContour);

#endif

    //    return minRect;
    return contours;
}


cv::Mat TToolBox::cropImageCircle(cv::Mat image, int x, int y, int r)
{

    // Your Hough circle
    cv::Vec3f circ(x,y,r);

    // Draw the mask: white circle on black background
    cv::Mat1b mask(image.size(), uchar(0));
    cv::circle(mask, cv::Point(circ[0], circ[1]), circ[2], cv::Scalar(255), CV_FILLED);

    //NO CROP NEEDED

    // Compute the bounding box
    //Rect bbox(circ[0] - circ[2], circ[1] - circ[2], 2 * circ[2], 2 * circ[2]);

    // Create a black image
    cv::Mat res = cv::Mat::zeros( image.size(), CV_8UC3 );
    res = cv::Scalar(0,0,0); //fill with black color


    // Copy only the image under the white circle to black image
    image.copyTo(res, mask);

    // Crop according to the roi
    //res = res(bbox);

    return res;
}