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in this post @Tetragramm clarify the documentation of the generalized HoughTransform in OpenCV a bit. As I still do not find any tutorial or further information about this implementation, i hope someone can help me to get the following crashing code to work. The images are taken from this tutorial Thank you for your help!

int main()
{
    Mat queryImage, //image where template key is located
            bigTemplateImage, //uncropped template
            templateImage; //cropped template

    queryImage = imread("b.bmp", IMREAD_GRAYSCALE);
    bigTemplateImage = imread("template_original.jpg", IMREAD_GRAYSCALE);
    // Crop template
    Rect myROI(197, 36, 80, 165);
    templateImage = bigTemplateImage(myROI);

    Ptr<GeneralizedHoughBallard> ghB;
    ghB->setTemplate(templateImage, Point(-1,-1) ); //Point as dummy just to see if it would work

    return 0;
}

b.bmp: template_original.jpg

in this post @Tetragramm clarify the documentation of the generalized HoughTransform in OpenCV a bit. bit. As I still do not find any tutorial or further information about this implementation, i hope someone can help me to get the following crashing code to work. work. update:->@berak found a sample of this function, and i was able to fix the code, so that it does not crash anymore. (Thank you very much!)

The remaining question is why the key instance is not found properly: I assume that it sicks close to the threshold which has to be set for Canny. In the documentation for setCannyHighThresh it only says: "Canny low/high threshold." I don't find templ.png from the given example and would assume that both input images are filtered with the same canny-filter, arn't they?

The images are taken from this tutorial Thank you for your help!

int main()
{
    Mat queryImage, //image where template key is located
            bigTemplateImage, //uncropped template
            templateImage; //cropped template

    queryImage = imread("b.bmp", IMREAD_GRAYSCALE);
    bigTemplateImage = imread("template_original.jpg", IMREAD_GRAYSCALE);
    // Crop template
    Rect myROI(197, 36, 80, 165);
    templateImage = bigTemplateImage(myROI);

    Ptr<GeneralizedHoughBallard> ghB;
    ghB->setTemplate(templateImage, Point(-1,-1) ); //Point as dummy just to see if it would work

Ptr<GeneralizedHoughGuil> ghB =  createGeneralizedHoughGuil();
    ghB->setTemplate(templateImage);


    vector<Vec4f> position;
    TickMeter tm;
    tm.start();
    ghB->detect(queryImage, position);
    tm.stop();

    cout << "Found : " << position.size() << " objects" << endl;
    cout << "Detection time : " << tm.getTimeMilli() << " ms" << endl;

   Mat out;
    cv::cvtColor(queryImage, out, COLOR_GRAY2BGR);

    for (size_t i = 0; i < position.size(); ++i)
    {
       Point2f pos(position[i][0], position[i][1]);
       float scale = position[i][2];
       float angle = position[i][3];

       RotatedRect rect;
       rect.center = pos;
       rect.size = Size2f(queryImage.cols * scale, queryImage.rows * scale);
       rect.angle = angle;

      Point2f pts[4];
      rect.points(pts);

      line(out, pts[0], pts[1], Scalar(0, 0, 255), 3);
      line(out, pts[1], pts[2], Scalar(0, 0, 255), 3);
      line(out, pts[2], pts[3], Scalar(0, 0, 255), 3);
      line(out, pts[3], pts[0], Scalar(0, 0, 255), 3);
    }

    imshow("out", out);
    waitKey();
    return 0;
}

b.bmp: template_original.jpg

in this post @Tetragramm clarify the documentation of the generalized HoughTransform in OpenCV a bit. As I still do not find any tutorial or further information about this implementation, i hope someone can help me to get the following crashing code to work. update:->@berak found a sample of this function, and i was able to fix the code, so that it does not crash anymore. (Thank you very much!)

The remaining question is why the key instance is not found properly: I assume that it sicks close to the threshold which has to be set for Canny. In the documentation for setCannyHighThresh it only says: "Canny low/high threshold." I don't find templ.png from the given example and would assume that both input images are filtered with the same canny-filter, arn't they?

update: I found both used images pic1.png and templ.png from the sample in this folder.

My problem is, that even with the given example settings i get wrong results: I detect 4 wrong objects shown in the output image below. Can someone try the code from the sample with this pictures as a confirmation?

The images key-images are taken from this tutorial Thank you for your help!

int main()
{
    Mat queryImage, //image where template key is located
            bigTemplateImage, //uncropped template
            templateImage; //cropped template

    queryImage = imread("b.bmp", IMREAD_GRAYSCALE);
    bigTemplateImage = imread("template_original.jpg", IMREAD_GRAYSCALE);
    // Crop template
    Rect myROI(197, 36, 80, 165);
    templateImage = bigTemplateImage(myROI);

    Ptr<GeneralizedHoughGuil> ghB =  createGeneralizedHoughGuil();
    ghB->setTemplate(templateImage);


    vector<Vec4f> position;
    TickMeter tm;
    tm.start();
    ghB->detect(queryImage, position);
    tm.stop();

    cout << "Found : " << position.size() << " objects" << endl;
    cout << "Detection time : " << tm.getTimeMilli() << " ms" << endl;

   Mat out;
    cv::cvtColor(queryImage, out, COLOR_GRAY2BGR);

    for (size_t i = 0; i < position.size(); ++i)
    {
       Point2f pos(position[i][0], position[i][1]);
       float scale = position[i][2];
       float angle = position[i][3];

       RotatedRect rect;
       rect.center = pos;
       rect.size = Size2f(queryImage.cols * scale, queryImage.rows * scale);
       rect.angle = angle;

      Point2f pts[4];
      rect.points(pts);

      line(out, pts[0], pts[1], Scalar(0, 0, 255), 3);
      line(out, pts[1], pts[2], Scalar(0, 0, 255), 3);
      line(out, pts[2], pts[3], Scalar(0, 0, 255), 3);
      line(out, pts[3], pts[0], Scalar(0, 0, 255), 3);
    }

    imshow("out", out);
    waitKey();
    return 0;
}

b.bmp: template_original.jpg

in this post @Tetragramm clarify the documentation of the generalized HoughTransform in OpenCV a bit. As I still do not find any tutorial or further information about this implementation, i hope someone can help me to get the following crashing code to work. update:->@berak found a sample of this function, and i was able to fix the code, so that it does not crash anymore. (Thank you very much!)

The remaining question is why the key instance is not found properly: I assume that it sicks close to the threshold which has to be set for Canny. In the documentation for setCannyHighThresh it only says: "Canny low/high threshold." I don't find templ.png from the given example and would assume that both input images are filtered with the same canny-filter, arn't they?

update: I found both used images pic1.png and templ.png from the sample in this folder.

My problem is, that even with the given example settings i get wrong results: I detect 4 wrong objects shown in the output image below. Can someone try the code from the sample with this pictures as a confirmation? confirmation?

The key-images are taken from this tutorial Thank you for your help!

int main()
{
    Mat queryImage, //image where template key is located
            bigTemplateImage, //uncropped template
            templateImage; //cropped template

    queryImage = imread("b.bmp", IMREAD_GRAYSCALE);
    bigTemplateImage = imread("template_original.jpg", IMREAD_GRAYSCALE);
    // Crop template
    Rect myROI(197, 36, 80, 165);
    templateImage = bigTemplateImage(myROI);

    Ptr<GeneralizedHoughGuil> ghB =  createGeneralizedHoughGuil();
    ghB->setTemplate(templateImage);


    vector<Vec4f> position;
    TickMeter tm;
    tm.start();
    ghB->detect(queryImage, position);
    tm.stop();

    cout << "Found : " << position.size() << " objects" << endl;
    cout << "Detection time : " << tm.getTimeMilli() << " ms" << endl;

   Mat out;
    cv::cvtColor(queryImage, out, COLOR_GRAY2BGR);

    for (size_t i = 0; i < position.size(); ++i)
    {
       Point2f pos(position[i][0], position[i][1]);
       float scale = position[i][2];
       float angle = position[i][3];

       RotatedRect rect;
       rect.center = pos;
       rect.size = Size2f(queryImage.cols * scale, queryImage.rows * scale);
       rect.angle = angle;

      Point2f pts[4];
      rect.points(pts);

      line(out, pts[0], pts[1], Scalar(0, 0, 255), 3);
      line(out, pts[1], pts[2], Scalar(0, 0, 255), 3);
      line(out, pts[2], pts[3], Scalar(0, 0, 255), 3);
      line(out, pts[3], pts[0], Scalar(0, 0, 255), 3);
    }

    imshow("out", out);
    waitKey();
    return 0;
}

b.bmp: template_original.jpg