Feature Counts in a Grid

edit

Hello everyone, I am working on a feature detection project based on GridAdaptedFeatureDetector. I need to calculate the number of keypoints in each grid but I'm getting incompatible results. It returns "0" for some grids where there are keypoints and matches. I am pretty sure I'm making a mistake in the counting part. Is there a simpler way to obtain the number of features in each grid?

Entire code is below, I'd appreciate any insight.

int main()
{
    CvCapture* cap = cvCreateFileCapture(VIDEO_NAME);
    int height    = (int) cvGetCaptureProperty(cap, CV_CAP_PROP_FRAME_HEIGHT);
    int width    = (int) cvGetCaptureProperty(cap, CV_CAP_PROP_FRAME_WIDTH);

    int x = 300;
    int y = 300;

    int counts[4][4];
    int all[4][4];


    int inx = 200;


    IplImage* src1= cvQueryFrame(cap);

    Mat frame_prev(src1);

    cv::Mat imageROI1,imageROI2;
    imageROI1=frame_prev(Rect(x,y,width-x-inx,height-y));

    //ORB detector(500);
    BriefDescriptorExtractor extractor;
    //SURF extractor;

    //ORB extractor;
    vector<KeyPoint> keypoints1, keypoints2;
    Mat descriptors1, descriptors2;

    BFMatcher matcher(NORM_HAMMING);
    vector<vector<DMatch>> matches, good_matches;
    vector<DMatch>matches2,good_matches2;

    Ptr<FeatureDetector> detector = FeatureDetector::create("ORB");

    cv::GridAdaptedFeatureDetector det(detector,5000);


    IplImage* src2;
    det.detect(imageROI1,keypoints1);
    extractor.compute(imageROI1,keypoints1,descriptors1);



    while(src2 = cvQueryFrame(cap))
    {
        for(int a = 0; a<4; a++)
        {for(int b = 0; b<4; b++)
        {counts[a][b]=0;
        all[a][b]=0;
        }}

        Mat frame(src2);

        imageROI2=frame(Rect(x,y,width-x-inx,height-y));

        det.detect(imageROI2,keypoints2);
        extractor.compute(imageROI2,keypoints2,descriptors2);

        matcher.radiusMatch(descriptors2,descriptors1,matches,5);
        //matcher.match(descriptors2,descriptors1,matches2);

        for(int i=0; i<matches.size(); i++)
            {int num = matches[i].size();
            for(int k=0; k<num; k++)
             {if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(imageROI2.cols/4))
             counts[0][0]++;
            if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(imageROI2.cols/2) && keypoints2[matches[i][k].queryIdx].pt.y>(imageROI2.cols/4) )
             counts[0][1]++;
            if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(3*imageROI2.cols/4) && keypoints2[matches[i][k].queryIdx].pt.y>(imageROI2.cols/2) )
             counts[0][2]++;
            if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(imageROI2.cols) && keypoints2[matches[i][k].queryIdx].pt.y>(3*imageROI2.cols/4) )
             counts[0][3]++;

            if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/2) && keypoints2[matches[i][k].queryIdx].pt.x>(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(imageROI2.cols/4))
             counts[1][0]++;
            if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/2) && keypoints2[matches[i][k].queryIdx].pt.x>(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(imageROI2.cols/2) && keypoints2[matches[i][k].queryIdx].pt.y>(imageROI2.cols/4) )
             counts[1][1]++;
            if(keypoints2[matches[i][k].queryIdx].pt.x<=(imageROI2.rows/2) && keypoints2[matches[i][k].queryIdx].pt.x>(imageROI2.rows/4) && keypoints2[matches[i][k].queryIdx].pt.y<=(3*imageROI2.cols/4) && keypoints2[matches[i][k].queryIdx].pt ...