c++ - OpenCV 筛选/冲浪/Orb : drawMatch function is not working well

Question

我使用 Sift/Surf 和 ORB，但有时我会遇到 drawMatch 函数的问题。

错误在这里:

OpenCV Error: Assertion failed (i2 >= 0 && i2 < static_cast(keypoints2.size())) in drawMatches, file /home/opencv-2.4.6.1/modules/features2d/src/draw.cpp, line 208 terminate called after throwing an instance of 'cv::Exception' what(): /home/opencv-2.4.6.1/modules/features2d/src/draw.cpp:208: error: (-215) i2 >= 0 && i2 < static_cast(keypoints2.size()) in function drawMatche

代码:

drawMatchPoints(img1,keypoints_img1,img2,keypoints_img2,matches);

我试着像这样用 img2 和 keypoints_img2 反转 img 1,keypoints_img1 :

drawMatchPoints(img2,keypoints_img2,img1,keypoints_img1,matches);

对应我做单应性的函数:

void drawMatchPoints(cv::Mat image1,std::vector<KeyPoint> keypoints_img1,
                                      cv::Mat image2,std::vector<KeyPoint> keypoints_img2,std::vector<cv::DMatch> matches){

    cv::Mat img_matches;
    drawMatches( image1, keypoints_img1, image2, keypoints_img2,
                         matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                         vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
            std::cout << "Number of good matching " << (int)matches.size() << "\n" << endl;



            //-- Localize the object
            std::vector<Point2f> obj;
            std::vector<Point2f> scene;

            for( int i = 0; i < matches.size(); i++ )
            {
              //-- Get the keypoints from the good matches
              obj.push_back( keypoints_img1[ matches[i].queryIdx ].pt );
              scene.push_back( keypoints_img2[matches[i].trainIdx ].pt );
            }

            Mat H = findHomography( obj, scene, CV_RANSAC );
            std::cout << "Size of homography " << *H.size << std::endl ;

            //-- Get the corners from the image_1 ( the object to be "detected" )
            std::vector<Point2f> obj_corners(4);
            obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( image1.cols, 0 );
            obj_corners[2] = cvPoint( image1.cols, image1.rows ); obj_corners[3] = cvPoint( 0, image1.rows );
            std::vector<Point2f> scene_corners(4);


            perspectiveTransform( obj_corners, scene_corners, H);


            //-- Draw lines between the corners (the mapped object in the scene - image_2 )
            line( img_matches, scene_corners[0] + Point2f( image1.cols, 0), scene_corners[1] + Point2f( image1.cols, 0), Scalar(0, 255, 0), 4 );
            line( img_matches, scene_corners[1] + Point2f( image1.cols, 0), scene_corners[2] + Point2f( image1.cols, 0), Scalar( 0, 255, 0), 4 );
            line( img_matches, scene_corners[2] + Point2f( image1.cols, 0), scene_corners[3] + Point2f( image1.cols, 0), Scalar( 0, 255, 0), 4 );
            line( img_matches, scene_corners[3] + Point2f( image1.cols, 0), scene_corners[0] + Point2f( image1.cols, 0), Scalar( 0, 255, 0), 4 );

            //-- Show detected matches
            cv::imshow( "Good Matches & Object detection", img_matches );
            cv::waitKey(5000);

但我仍然有错误!

我注意到当我的 keypoints_img1 的大小小于我的 keypoints_img2 的大小时发生错误:

Size keyPoint1 : 244 - Size keyPoint2 : 400

因此，如果我颠倒我的两张图片的加载，那是可行的，但如果我的第一张图片比我的第二张图片有更多的关键点，我现在不能提前......

为了创建功能，我的代码(最重要的一步):

init_Sift(400,5,0.04,25,1.6);
void init_Sift(int nf,int nOctaveL,double contrastThresh, double edgeThresh,double sigma){
this->nfeatureSift=nf;
this->nOctaveLayerSift=nOctaveL;
this->contrastThresholdSift=contrastThresh;
this->edgeThresholdSift=edgeThresh;
this->sigmaSift=sigma;}



 cv::FeatureDetector* detector=new SiftFeatureDetector(nfeatureSift,nOctaveLayerSift,contrastThresholdSift,edgeThresholdSift,sigmaSift);
cv::DescriptorExtractor* extractor=new SiftDescriptorExtractor

extractor->compute( image, keypoints, descriptors );

匹配部分:

    std::cout << "Type of matcher : " << type_of_matcher << std::endl;
if (type_of_matcher=="FLANN" || type_of_matcher=="BF"){
    std::vector<KeyPoint> keypoints_img1 = keyfeatures.compute_Keypoints(img1);
    std::vector<KeyPoint> keypoints_img2 = keyfeatures.compute_Keypoints(img2);

    cv::Mat descriptor_img1 = keyfeatures.compute_Descriptors(img1);
    cv::Mat descriptor_img2 = keyfeatures.compute_Descriptors(img2);

    std::cout << "Size keyPoint1 " << keypoints_img1.size() << "\n" << std::endl;
    std::cout << "Size keyPoint2 " << keypoints_img2.size() << "\n" << std::endl;

    //Flann with sift or surf
    if (type_of_matcher=="FLANN"){
        Debug::info("USING Matcher FLANN");
        fLmatcher.match(descriptor_img1,descriptor_img2,matches);

        double max_dist = 0; double min_dist = 100;

        //-- Quick calculation of max and min distances between keypoints
        for( int i = 0; i < descriptor_img1.rows; i++ ){
            double dist = matches[i].distance;
            if( dist < min_dist ) min_dist = dist;
            if( dist > max_dist ) max_dist = dist;
         }

        std::vector< DMatch > good_matches;

          for( int i = 0; i < descriptor_img1.rows; i++ )
          { if( matches[i].distance <= max(2*min_dist, 0.02) )
            { good_matches.push_back( matches[i]); }
          }

          std::cout << "Size of good match : " <<  (int)good_matches.size() << std::endl;
          //-- Draw only "good" matches
          if (!good_matches.empty()){
              drawMatchPoints(img1,keypoints_img1,img2,keypoints_img2,good_matches);

          }
          else {
              Debug::error("Flann Matcher : Pas de match");
              cv::Mat img_matches;
              drawMatches( img1, keypoints_img1, img2, keypoints_img2,
                                matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                                vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
              cv::imshow( "No match", img_matches );
              cv::waitKey(5000);
          }

    }
    //BruteForce with sift or surf
    else if (type_of_matcher=="BF"){
        Debug::info("USING Matcher Brute Force");

        bFmatcher.match(descriptor_img1,descriptor_img2,matches);
        if (!matches.empty()){
            std::nth_element(matches.begin(),//Initial position
                             matches.begin()+24, //Position  of the sorted element
                             matches.end());//End position
            matches.erase(matches.begin()+25,matches.end());

            drawMatchPoints(img1,keypoints_img1,img2,keypoints_img2,matches);
            //drawMatchPoints(img2,keypoints_img2,img1,keypoints_img1,matches);
        }
        else {
            Debug::error("Brute Force matcher  : Pas de match");
            cv::Mat img_matches;
            drawMatches( img1, keypoints_img1, img2, keypoints_img2,
                              matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                              vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
            cv::imshow( "No match", img_matches );
            cv::waitKey(5000);

        }

}

您有什么建议或建议吗？

编辑: 我解决了我的问题。我有一个 C++ 问题，因为我有两个类。一个关于匹配，另一个关于寻找关键特征。我已经在我的 .h std::vector 上写过，对于描述符也是如此。

class keyFeatures{

public:
...   
std::vector<keyPoint> keypoints;
...

我删除了这个属性并做了一个接受参数 std::vector keypoints 的函数

cv::Mat descriptor_img1 = keyfeatures.compute_Descriptors(img1,keypoints_img1);

代替

cv::Mat descriptor_img1 = keyfeatures.compute_Descriptors(img1);

我觉得我做匹配的时候有冲突...但我不知道为什么我不应该把它写在我的 .h 上并在我的函数上做一个本地参数。

谢谢!

Answer 1

对于像我这样搜索过但找不到解决方案的人。

Assertion failed (i2 >= 0 && i2 < static_cast(keypoints2.size()))

这意味着断言由于 i2 小于 0 或 i2 小于 keypoints2 大小而失败。但什么是 i2？

来自 rbaleksandar 在评论中提供的链接

int i2 = matches1to2[m].trainIdx;

这里的 trainIdx 是 keypoints2 中的一个索引。检查 i2 < static_cast(keypoints2.size()) 确保索引小于 keypoints2.size()。

对我来说，这是因为我在调用 drawMatches 之前丢弃了一些关键点，但在计算描述符之后，即调用了 DescriptorExtractor#compute。这意味着当我更改那些关键点时，drawMatches 通过描述符引用旧的关键点。最终结果是一些关键点的 idx 很大，但关键点的大小很小，因此出现错误。