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opencv_match_sort
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| //原文：https://blog.csdn.net/zilanpotou182/article/details/68061929 | |
| #include <iostream> | |
| #include <stdio.h> | |
| #include "opencv2/core.hpp" | |
| #include "opencv2/core/utility.hpp" | |
| #include "opencv2/core/ocl.hpp" | |
| #include "opencv2/imgcodecs.hpp" | |
| #include "opencv2/highgui.hpp" | |
| #include "opencv2/features2d.hpp" | |
| #include "opencv2/calib3d.hpp" | |
| #include "opencv2/imgproc.hpp" | |
| #include"opencv2/flann.hpp" | |
| #include"opencv2/xfeatures2d.hpp" | |
| #include"opencv2/ml.hpp" | |
| using namespace cv; | |
| using namespace std; | |
| using namespace cv::xfeatures2d; | |
| using namespace cv::ml; | |
| int main() | |
| { | |
| Mat a = imread("3.png", 0);//左右相机的图像来源于MiddleBury图片库 | |
| Mat b = imread("4.png", 0); | |
| Ptr<SURF> surf; //创建方式和OpenCV2中的不一样,并且要加上命名空间xfreatures2d | |
| surf = SURF::create(800); | |
| BFMatcher matcher; //实例化一个暴力匹配器 | |
| Mat c, d; | |
| vector<KeyPoint>key1, key2; | |
| vector<DMatch> matches; //DMatch是用来描述匹配好的一对特征点的类，包含这两个点之间的相关信息 | |
| //比如左图有个特征m，它和右图的特征点n最匹配，这个DMatch就记录它俩最匹配，并且还记录m和n的 | |
| //特征向量的距离和其他信息，这个距离在后面用来做筛选 | |
| surf->detectAndCompute(a, Mat(), key1, c);//输入图像，输入掩码，输入特征点，输出Mat，存放所有特征点的描述向量 | |
| surf->detectAndCompute(b, Mat(), key2, d);//这个Mat行数为特征点的个数，列数为每个特征向量的尺寸，SURF是64（维） | |
| matcher.match(c, d, matches); //匹配，数据来源是特征向量，结果存放在DMatch类型里面 | |
| //sort函数对数据进行升序排列 | |
| sort(matches.begin(), matches.end()); //筛选匹配点，根据match里面特征对的距离从小到大排序 | |
| vector< DMatch > good_matches; | |
| int ptsPairs = std::min(50, (int)(matches.size() * 0.15)); | |
| cout << ptsPairs << endl; | |
| for (int i = 0; i < ptsPairs; i++) | |
| { | |
| good_matches.push_back(matches[i]);//距离最小的50个压入新的DMatch | |
| } | |
| Mat outimg; //drawMatches这个函数直接画出摆在一起的图 | |
| drawMatches(a, key1, b, key2, good_matches, outimg, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS); //绘制匹配点 | |
| imshow("桌面", outimg); | |
| cvWaitKey(0); | |
| } | |
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