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| #include "opencv2/core/core.hpp" #include "opencv2/xfeatures2d.hpp" #include "opencv2/features2d/features2d.hpp" #include "opencv2/highgui/highgui.hpp" #include <iostream> using namespace cv; using namespace std;
int main(int argc, char **argv) { Mat img_1 = imread("box.png", 1); Mat img_2 = imread("box_in_scene.png", 1); if (!img_1.data || !img_2.data) { printf("读取图片image0错误~! \n"); return false; }
int minHessian = 300; Ptr<xfeatures2d::SURF> detector= xfeatures2d::SURF::create(minHessian); std::vector<KeyPoint> keypoints_1, keypoints_2; detector->detect(img_1, keypoints_1); detector->detect(img_2, keypoints_2);
Ptr<xfeatures2d::SURF> extractor=xfeatures2d::SURF::create(); Mat descriptors_1, descriptors_2; extractor->compute(img_1, keypoints_1, descriptors_1); extractor->compute(img_2, keypoints_2, descriptors_2);
FlannBasedMatcher matcher; std::vector<DMatch> matches; matcher.match(descriptors_1, descriptors_2, matches); double max_dist = 0; double min_dist = 100;
for (int i = 0; i < descriptors_1.rows; i++) { double dist = matches[ i ].distance; if (dist < min_dist) min_dist = dist; if (dist > max_dist) max_dist = dist; } printf("> 最大距离(Max dist) : %f \n", max_dist); printf("> 最小距离(Min dist) : %f \n", min_dist);
std::vector<DMatch> good_matches; for (int i = 0; i < descriptors_1.rows; i++) { if (matches[ i ].distance < 2 * min_dist) { good_matches.push_back(matches[ i ]); } }
Mat img_matches; drawMatches(img_1, keypoints_1, img_2, keypoints_2, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
for (int i = 0; i < good_matches.size(); i++) { printf(">符合条件的匹配点 [%d] 特征点1: %d -- 特征点2: %d \n", i, good_matches[ i ].queryIdx, good_matches[ i ].trainIdx); }
imshow("result", img_matches);
waitKey(0); return 0; }
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