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Hi there,

I making logo detection program that uses the SIFT method to detect a logo on image. The source code is here. The folder with source images and logos("references" folder) is here. When I scrolling results of drawmatches(), program falling on image "13380-sony.jpg".

What could be the problem? And how a source code could be optimized?

P.S. Sorry my English.
P.P.S. I am beginner in OpenCV.

Hi there,

I making logo detection program that uses the SIFT method to detect a logo on image. The source code is here. The folder with source images and logos("references" folder) is here. When I scrolling results of drawmatches(), program falling on image "13380-sony.jpg"."13380-sony.jpg" with text in console: "OpenCV Error: Assertion failed (scn + 1 == m.cols) in perspectiveTransform, file "my_opencv_dir"\sources\modules\core\src\matmul.cpp, line 2125
terminate called after throwing an instance of 'cv::Exception'
what(): "opencv_dir"...\matmul.cpp:2125: error: (-215) scn + 1 == m.cols in function perspectiveTransform".

What could be the problem? And how a source code could be optimized?

P.S. Sorry my English.
P.P.S. I am beginner in OpenCV.

Hi there,

I making logo detection program that uses the SIFT method to detect a logo on image. The source latest code version is here.

#include <core.hpp>
#include <highgui.hpp>
#include <imgproc.hpp>
#include <cv.hpp>
#include <imgcodecs.hpp>
#include <xfeatures2d.hpp>
#include <vector>

using namespace cv;
using namespace cv::xfeatures2d;
using std::vector;

vector<Mat> images, templates;

Mat temf = imread("C://DataSet_pic//reference//LEGO_logo.jpg"),
    teml = imread("C://DataSet_pic//reference//logo-blend-a-med.png");

Mat detectLogo(const Mat &source, const Mat &template_)
{
    Ptr<Feature2D> sift = SIFT::create();
    vector<KeyPoint> keypoints_s, keypoints_t;
    Mat descriptors_s, descriptors_t;

    sift->detect(source, keypoints_s);
    sift->detect(template_, keypoints_t);

    sift->compute(source, keypoints_s, descriptors_s);
    sift->compute(template_, keypoints_t, descriptors_t);

    BFMatcher matcher;
    vector<vector<DMatch>> matches;
    matcher.knnMatch(descriptors_t, descriptors_s, matches, 2);
    vector<DMatch> good_matches;
    for(vector<DMatch> vdm : matches)
        for(DMatch dm : vdm)
            if(vdm.data()->distance < dm.distance / 2)
                good_matches.push_back(*(vdm.data()));

    Mat img_matches;

    if(good_matches.empty())
        return img_matches;

    drawMatches(template_, keypoints_t, source, keypoints_s,
                good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    vector<Point2f> templt, scene;

    for(unsigned int i = 0; i < good_matches.size(); i++)
    {
        templt.push_back( keypoints_t[ good_matches[i].queryIdx ].pt );
        scene.push_back( keypoints_s[ good_matches[i].trainIdx ].pt );
    }

    if(templt.size() < 4 || scene.size() < 4)
    {
        img_matches.release();
        return img_matches;
    }

    Mat homogr = findHomography(templt, scene, CV_RANSAC);
    vector<Point2f> templ_corners(4);

    templ_corners[0] = cvPoint(0,0);
    templ_corners[1] = cvPoint(template_.cols, 0);
    templ_corners[2] = cvPoint(template_.cols, template_.rows);
    templ_corners[3] = cvPoint(0, template_.rows);

    vector<Point2f> scene_corners(4);
    perspectiveTransform(templ_corners, scene_corners, homogr);

    Point p1 = scene_corners[0] + Point2f( template_.cols, 0),
          p2 = scene_corners[1] + Point2f( template_.cols, 0),
          p3 = scene_corners[2] + Point2f( template_.cols, 0),
          p4 = scene_corners[3] + Point2f( template_.cols, 0);

    line( img_matches, p1, p2, Scalar(0, 255, 0), 4 );
    line( img_matches, p2, p3, Scalar( 0, 255, 0), 4 );
    line( img_matches, p3, p4, Scalar( 0, 255, 0), 4 );
    line( img_matches, p4, p1, Scalar( 0, 255, 0), 4 );

    return img_matches;
}

void showFirstLogoMatch()
{
    imshow("Logo detection", detectLogo(images[0], temf));
}

void showLastLogoMatch()
{
    imshow("Logo detection", detectLogo(images[images.size()-1], teml));
}

void showLogoMatch(unsigned short int index)
{
    Mat image = images[index];
    Mat img = image.clone();

    if(img.size().width == 1280 && img.size().height == 720)
    {
        Rect roi(Point(img.size().width / 2 - img.size().width / 4 + 50, img.size().height),
                 Point(img.size().width / 2 + img.size().width / 4 + 50, 0));
        Mat image_(img, roi);
        img = image_;
    }
    else if(img.size().width >= 500 && img.size().height >= 370)
        resize(img, img, Size(), 0.5, 0.5);

    for(Mat mat : templates)
    {
        if( (mat.size().width >= 1280 || mat.size().width >= 324) && mat.size().height >= 324)
            resize(mat, mat, Size(), 0.5, 0.5);

        Mat logo = detectLogo(img, mat);

        if(logo.empty())
            continue;
        else
        {
            imshow("Logo detection", logo);
            waitKey(0);
        }
    }
}

int main()
{
    vector<String> paths, paths_t;
    String folder = "C://DataSet_pic//", folder_t = "C://DataSet_pic//reference//";

    glob(folder, paths);
    glob(folder_t, paths_t);

    for(String str : paths)
        images.push_back(imread(str));

    for(String str : paths_t)
        templates.push_back(imread(str));

    unsigned int index = 0;

    resize(temf, temf, Size(), 0.1667, 0.1667);
    resize(images[0], images[0], Size(), 3, 3);

    showFirstLogoMatch();

    resize(teml, teml, Size(), 0.5, 0.5);
    resize(images[images.size()-1], images[images.size()-1], Size(), 0.333, 0.333);

    //imshow("image", images[0]);

    while(1)
    {
        char key = waitKey(0);

        if(key == '1')
            showFirstLogoMatch();

        if(key == '/')
            showLastLogoMatch();

        if(key == '+')
        {
            index++;
            showLogoMatch(index);
            //imshow("image", images[index]);
        }

        if(key == '-')
        {
            index--;
            showLogoMatch(index);
            //imshow("image", images[index]);
        }

        if(index == 0)
        {
            showFirstLogoMatch();
            index++;
        }

        if(index == images.size()-1)
        {
            showLastLogoMatch();
            index--;
        }

        if(key == 27)
            break;
    }
    destroyAllWindows();
    return 0;
}

The folder with source images and logos("references" folder) is here. When I scrolling results of drawmatches(), program falling on image "13380-sony.jpg" with text in console: "OpenCV Error: Assertion failed (scn + 1 == m.cols) in perspectiveTransform, file "my_opencv_dir"\sources\modules\core\src\matmul.cpp, line 2125
terminate called after throwing an instance of 'cv::Exception'
what(): "opencv_dir"...\matmul.cpp:2125: error: (-215) scn + 1 == m.cols in function perspectiveTransform".

What could be the problem? And how a source code could be optimized?

P.S. Sorry my English.
P.P.S. I am beginner in OpenCV.

Hi there,

I making logo detection program that uses the SIFT method to detect a logo on image. The latest version of code version is

#include <core.hpp>
#include <highgui.hpp>
#include <imgproc.hpp>
#include <cv.hpp>
#include <imgcodecs.hpp>
#include <xfeatures2d.hpp>
#include <vector>

using namespace cv;
using namespace cv::xfeatures2d;
using std::vector;

vector<Mat> images, templates;

Mat temf = imread("C://DataSet_pic//reference//LEGO_logo.jpg"),
    teml = imread("C://DataSet_pic//reference//logo-blend-a-med.png");

Mat detectLogo(const Mat &source, const Mat &template_)
{
    Ptr<Feature2D> sift = SIFT::create();
    vector<KeyPoint> keypoints_s, keypoints_t;
    Mat descriptors_s, descriptors_t;

    sift->detect(source, keypoints_s);
    sift->detect(template_, keypoints_t);

    sift->compute(source, keypoints_s, descriptors_s);
    sift->compute(template_, keypoints_t, descriptors_t);

    BFMatcher matcher;
    vector<vector<DMatch>> matches;
    matcher.knnMatch(descriptors_t, descriptors_s, matches, 2);
    vector<DMatch> good_matches;
    for(vector<DMatch> vdm : matches)
        for(DMatch dm : vdm)
            if(vdm.data()->distance < dm.distance / 2)
                good_matches.push_back(*(vdm.data()));

    Mat img_matches;

    if(good_matches.empty())
        return img_matches;

    drawMatches(template_, keypoints_t, source, keypoints_s,
                good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    vector<Point2f> templt, scene;

    for(unsigned int i = 0; i < good_matches.size(); i++)
    {
        templt.push_back( keypoints_t[ good_matches[i].queryIdx ].pt );
        scene.push_back( keypoints_s[ good_matches[i].trainIdx ].pt );
    }

    if(templt.size() < 4 || scene.size() < 4)
    {
        img_matches.release();
        return img_matches;
    }

    Mat homogr = findHomography(templt, scene, CV_RANSAC);
    vector<Point2f> templ_corners(4);

    templ_corners[0] = cvPoint(0,0);
    templ_corners[1] = cvPoint(template_.cols, 0);
    templ_corners[2] = cvPoint(template_.cols, template_.rows);
    templ_corners[3] = cvPoint(0, template_.rows);

    vector<Point2f> scene_corners(4);
    perspectiveTransform(templ_corners, scene_corners, homogr);

    Point p1 = scene_corners[0] + Point2f( template_.cols, 0),
          p2 = scene_corners[1] + Point2f( template_.cols, 0),
          p3 = scene_corners[2] + Point2f( template_.cols, 0),
          p4 = scene_corners[3] + Point2f( template_.cols, 0);

    line( img_matches, p1, p2, Scalar(0, 255, 0), 4 );
    line( img_matches, p2, p3, Scalar( 0, 255, 0), 4 );
    line( img_matches, p3, p4, Scalar( 0, 255, 0), 4 );
    line( img_matches, p4, p1, Scalar( 0, 255, 0), 4 );

    return img_matches;
}

void showFirstLogoMatch()
{
    imshow("Logo detection", detectLogo(images[0], temf));
}

void showLastLogoMatch()
{
    imshow("Logo detection", detectLogo(images[images.size()-1], teml));
}

void showLogoMatch(unsigned short int index)
{
    Mat image = images[index];
    Mat img = image.clone();

    if(img.size().width == 1280 && img.size().height == 720)
    {
        Rect roi(Point(img.size().width / 2 - img.size().width / 4 + 50, img.size().height),
                 Point(img.size().width / 2 + img.size().width / 4 + 50, 0));
        Mat image_(img, roi);
        img = image_;
    }
    else if(img.size().width >= 500 && img.size().height >= 370)
        resize(img, img, Size(), 0.5, 0.5);

    for(Mat mat : templates)
    {
        if( (mat.size().width >= 1280 || mat.size().width >= 324) && mat.size().height >= 324)
            resize(mat, mat, Size(), 0.5, 0.5);

        Mat logo = detectLogo(img, mat);

        if(logo.empty())
            continue;
        else
        {
            imshow("Logo detection", logo);
            waitKey(0);
        }
    }
}

int main()
{
    vector<String> paths, paths_t;
    String folder = "C://DataSet_pic//", folder_t = "C://DataSet_pic//reference//";

    glob(folder, paths);
    glob(folder_t, paths_t);

    for(String str : paths)
        images.push_back(imread(str));

    for(String str : paths_t)
        templates.push_back(imread(str));

    unsigned int index = 0;

    resize(temf, temf, Size(), 0.1667, 0.1667);
    resize(images[0], images[0], Size(), 3, 3);

    showFirstLogoMatch();

    resize(teml, teml, Size(), 0.5, 0.5);
    resize(images[images.size()-1], images[images.size()-1], Size(), 0.333, 0.333);

    //imshow("image", images[0]);

    while(1)
    {
        char key = waitKey(0);

        if(key == '1')
            showFirstLogoMatch();

        if(key == '/')
            showLastLogoMatch();

        if(key == '+')
        {
            index++;
            showLogoMatch(index);
            //imshow("image", images[index]);
        }

        if(key == '-')
        {
            index--;
            showLogoMatch(index);
            //imshow("image", images[index]);
        }

        if(index == 0)
        {
            showFirstLogoMatch();
            index++;
        }

        if(index == images.size()-1)
        {
            showLastLogoMatch();
            index--;
        }

        if(key == 27)
            break;
    }
    destroyAllWindows();
    return 0;
}

The folder with source images and logos("references" folder) is here. When I scrolling results of drawmatches(), program falling on image "13380-sony.jpg" with text in console: "OpenCV Error: Assertion failed (scn + 1 == m.cols) in perspectiveTransform, file "my_opencv_dir"\sources\modules\core\src\matmul.cpp, line 2125
terminate called after throwing an instance of 'cv::Exception'
what(): "opencv_dir"...\matmul.cpp:2125: error: (-215) scn + 1 == m.cols in function perspectiveTransform".

What could be the problem? And how a source code could be optimized?

P.S. Sorry my English.
P.P.S. I am beginner in OpenCV.