OpenCV DrawMatchesFlags - no keypoint option?
我正在将SURF点从图像匹配到视频供稿。我正在尝试在不同的分辨率下进行测试,但是我遇到了一个令人烦恼的问题:当以较小的分辨率绘制匹配的关键点时,由于有色的关键点,我无法再看到视频源中发生了什么。有没有一种方法可以停止OpenCV在视频上绘制这些图像并仅显示单应性?
我已经尝试查看
我正在创建使用
在其上绘制关键点的
1 | drawMatches( img_object, keypoints_object, frame, keypoints_scene, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS ); |
然后我使用OpenCV
如何删除视频供稿上匹配的特征点并仅显示单应性?
编辑:
检测和绘图功能:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | //-- Step 1: Detect the keypoints using SURF Detector int minHessian = 400; SurfFeatureDetector detector( minHessian ); std::vector<cv::KeyPoint> keypoints_object, keypoints_scene; detector.detect( img_object, keypoints_object ); detector.detect( frame, keypoints_scene ); //-- Step 2: Calculate descriptors (feature vectors) SurfDescriptorExtractor extractor; Mat descriptors_object, descriptors_scene; extractor.compute( img_object, keypoints_object, descriptors_object ); extractor.compute( frame, keypoints_scene, descriptors_scene ); //-- Step 3: Matching descriptor vectors using FLANN matcher FlannBasedMatcher matcher; std::vector< DMatch > matches; matcher.match( descriptors_object, descriptors_scene, matches ); double max_dist = 0; double min_dist = 100; //-- Quick calculation of max and min distances between keypoints for( int i = 0; i < descriptors_object.rows; i++ ) { double dist = matches[i].distance; if( dist < min_dist ) min_dist = dist; if( dist > max_dist ) max_dist = dist; } printf("-- Max dist : %f \ ", max_dist ); printf("-- Min dist : %f \ ", min_dist ); //-- Draw only"good" matches (i.e. whose distance is less than 3*min_dist ) std::vector< DMatch > good_matches; for( int i = 0; i < descriptors_object.rows; i++ ) { if( matches[i].distance < 3*min_dist ) { good_matches.push_back( matches[i]); } } Mat img_matches; drawMatches( img_object, keypoints_object, frame, keypoints_scene, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS ); //-- Localize the object std::vector<Point2f> obj; std::vector<Point2f> scene; for( int i = 0; i < good_matches.size(); i++ ) { //-- Get the keypoints from the good matches obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt ); scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt ); } Mat H = findHomography( obj, scene, CV_RANSAC ); //-- 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( img_object.cols, 0 ); obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.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( img_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 ); line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 ); line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 ); line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 ); |
将工程图零件更改为此:
1 2 3 4 5 | Mat img_matches; std::vector< DMatch > emptyVec; //Make a empty match vector so it won't be drawn. drawMatches( img_1, keypoints_1, img_2, keypoints_2, emptyVec, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS ); |