// vector of keypoints std::vector<cv::KeyPoint> keypoints; // Construction of the Good Feature to Track detector cv::GoodFeaturesToTrackDetector gftt( 500, // maximum number of corners to be returned 0.01, // quality level 10); // minimum allowed distance between points // point detectio...
cv::KeyPoint::KeyPoint ( Point2f _pt, float _size, float _angle = -1, float _response = 0, int _octave = 0, int _class_id = -1 ) 1. 2. 3. 4. 5. 6. 7. 8. Parameters (397.0, 384.0) (398.0, 384.0) (399.0, 384.0) (461.0, 384.0) (369.0, 385.0) (370.0, 385.0) (3...
{ /*Shi-Tomas角点检测*/ string path = "Lena.png"; Mat img = imread(path, 1); Mat img_gray; cvtColor(img, img_gray, COLOR_BGR2GRAY); vector<Point2f> corners; //Shi-Tomas角点检测 goodFeaturesToTrack(img_gray, corners, 100, 0.01, 0.1); //绘制角点 vector<KeyPoint> keyPoints; for ...
std::vector<cv::KeyPoint>& keypoints1, std::vector<cv::KeyPoint>& keypoints2); cv::Mat ransacTest( const std::vector<cv::DMatch>& matches, const std::vector<cv::KeyPoint>& keypoints1, const std::vector<cv::KeyPoint>& keypoints2, std::vector<cv::DMatch>& outMatches); void ...
回到顶部(go to top) KeyPoints classCV_EXPORTS_W_SIMPLE KeyPoint {public://! the default constructorCV_WRAP KeyPoint() : pt(0,0), size(0), angle(-1), response(0), octave(0), class_id(-1) {}//! the full constructorKeyPoint(Point2f _pt,float_size,float_angle=-1,float_response...
参数五:std::vector类型的matchers1to2,从第一个图像匹配到第二个图像,这意味着keypoints1[i]在keypoints2中有一个对应的点[matches[i]]。 参数六:InputOutputArray类型的outImg,为空时,默认并排绘制输出图像以及连接关键点;若不为空,则在图像上绘制关系点。
pointIndexes2.push_back(it->trainIdx); }//将KeyPoint类型转换为Point2f类型//根据pointIndexes来筛选需要转换的点,相当于掩膜(Mask)vector<Point2f> selPoints1, selPoints2; KeyPoint::convert(keypoints1,selPoints1,pointIndexes1); KeyPoint::convert(keypoints2,selPoints2,pointIndexes2);//在筛选出的...
//提取特征点SurfFeatureDetectorDetector(2000);vector<KeyPoint>keyPoint1,keyPoint2;Detector.detect(image1,keyPoint1);Detector.detect(image2,keyPoint2);//特征点描述,为下边的特征点匹配做准备SurfDescriptorExtractor Descriptor;Mat imageDesc1,imageDesc2;Descriptor.compute(image1,keyPoint1,imageDesc1);Descr...
drawMatches(im1,keypoints1,im2,keypoints2,matches,imMatches); imwrite("matches.jpg",imMatches); //存储好的匹配点 std::vector<Point2f>points1,points2; for(size_ti=0;i<matches.size;i++) { points1.push_back(keypoints1[matches[i].queryIdx].pt); ...
vector < KeyPoint > keypoints_1 , keypoints_2 ; detector -> setHessianThreshold ( minHessian ); detector -> detect ( box , keypoints_1 ); detector -> detect ( box_scene , keypoints_2 ); 3.描述子生成(DLCO) Ptr < VGG > vgg_deor = VGG :: create ; ...