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ransacMatch.cpp
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ransacMatch.cpp
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//#include "opencv2/core/core.hpp"
//#include "highgui.h"
//#include "opencv2/imgproc/imgproc.hpp"
//#include "opencv2/features2d/features2d.hpp"
//#include "opencv2/nonfree/nonfree.hpp"
//#include "opencv2/legacy/legacy.hpp"
//#include "opencv2/stitching/detail/autocalib.hpp"
//#include "opencv2/stitching/detail/blenders.hpp"
//#include "opencv2/stitching/detail/camera.hpp"
//#include "opencv2/stitching/detail/exposure_compensate.hpp"
//#include "opencv2/stitching/detail/matchers.hpp"
//#include "opencv2/stitching/detail/motion_estimators.hpp"
//#include "opencv2/stitching/detail/seam_finders.hpp"
//#include "opencv2/stitching/detail/util.hpp"
//#include "opencv2/stitching/detail/warpers.hpp"
//#include "opencv2/stitching/warpers.hpp"
//#include <iostream>
//#include <fstream>
//#include <string>
//#include <iomanip>
//#include<vector>
//using namespace cv;
//using namespace std;
//using namespace detail;
//int main(int argc, char** argv)
//{
// vector<Mat> imgs; //表示待拼接的图像矢量队列
// Mat img = imread("E:/biyesheji/Main/imagePairs/A1.png"); //读取两幅图像，并存入队列
// imgs.push_back(img);
// img = imread("E:/biyesheji/Main/imagePairs/A2.png");
// imgs.push_back(img);
// Ptr<FeaturesFinder> finder; //特征检测
//
// clock_t feature_find_time1, feature_find_time2;
//
// /*finder = new SurfFeaturesFinder();*/
// finder = new OrbFeaturesFinder();
// vector<ImageFeatures> features(2);
//
// feature_find_time1 = clock();
//
// (*finder)(imgs[0], features[0]);
//
// //feature_find_time2 = clock();
//
// (*finder)(imgs[1], features[1]);
//
// cout << "图像1的特征点数量：" << features[0].keypoints.size() << endl;
// cout << "图像2的特征点数量：" << features[1].keypoints.size() << endl;
//
// //cout << "特征点检测耗时：" << (double)(feature_find_time2 - feature_find_time1) / CLOCKS_PER_SEC << "s" << endl;
//
// vector<Mat>img_with_features(2);
// for (int i = 0; i < 2; i++)
// {
// drawKeypoints(imgs[i], features[i].keypoints, img_with_features[i], Scalar(0, 0, 255));
// namedWindow("img" + to_string(i + 1) + "WithFeatures");
// imshow("img" + to_string(i + 1) + "WithFeatures", img_with_features[i]);
// imwrite("img" + to_string(i + 1) + "WithFeatures.png", img_with_features[i]);
// }
//
// vector<MatchesInfo> pairwise_matches; //特征匹配
// BestOf2NearestMatcher matcher(false, 0.2f); //定义特征匹配器，2NN方法
// matcher(features, pairwise_matches); //进行特征匹配
//
// feature_find_time2 = clock();
// cout << "特征点检测耗时：" << (double)(feature_find_time2 - feature_find_time1) / CLOCKS_PER_SEC << "s" << endl;
// Mat dispimg; //两幅图像合并成一幅图像显示
// dispimg.create(Size(imgs[0].cols+imgs[1].cols, max(imgs[1].rows,imgs[1].rows)), CV_8UC3);
// Mat imgROI = dispimg(Rect(0, 0, (int)(imgs[0].cols), (int)(imgs[0].rows)));
// resize(imgs[0], imgROI, Size((int)(imgs[0].cols), (int)(imgs[0].rows)));
// imgROI = dispimg(Rect((int)(imgs[0].cols), 0, (int)(imgs[1].cols), (int)(imgs[1].rows)));
// resize(imgs[1], imgROI, Size((int)(imgs[1].cols), (int)(imgs[1].rows)));
// Point2f p1, p2; //分别表示两幅图像内的匹配点对
// int j=0;
// for (size_t i = 0; i < pairwise_matches[1].matches.size(); ++i) //遍历匹配点对
// {
// if (!pairwise_matches[1].inliers_mask[i]) //不是内点，则继续下一次循环
// continue;
// const DMatch& m = pairwise_matches[1].matches[i]; //得到内点的匹配点对
// p1 = features[0].keypoints[m.queryIdx].pt;
// p2 = features[1].keypoints[m.trainIdx].pt;
// p2.x += features[0].img_size.width; //p2在合并图像上的坐标
// line(dispimg, p1, p2, Scalar(0,0,255), 1, CV_AA); //画直线
// //if(j++==10) //内点数量较多，我们只显示10个
// // break;
// } //在终端显示内点数量和单应矩阵
// cout << "内点数量：" << endl;
// cout << pairwise_matches[1].num_inliers << endl;
// cout<<"好的匹配的数量："<<endl;
// cout<<pairwise_matches[1].matches.size()<<endl<<endl;
// const double* h = reinterpret_cast<const double*>(pairwise_matches[1].H.data);
// cout<<"单应矩阵："<<endl;
// /*for (int i = 0; i < 9; i++)
// {
// cout << *(h + i) << ',';
// if ((i + 1) % 3 == 0)
// cout << endl;
// }*/
// cout<<setw(10)<<(int)(h[0]+0.5)<<setw(6)<<(int)(h[1]+0.5)<<setw(6)<<(int)(h[2]+0.5)<<endl;
// cout<<setw(10)<<(int)(h[3]+0.5)<<setw(6)<<(int)(h[4]+0.5)<<setw(6)<<(int)(h[5]+0.5)<<endl;
// cout<<setw(10)<<(int)(h[6]+0.5)<<setw(6)<<(int)(h[7]+0.5)<<setw(6)<<(int)(h[8]+0.5)<<endl;
// imshow("匹配显示", dispimg); //显示匹配图像
// imwrite("ransacMatch.png", dispimg);
// waitKey(0);
// return 0;
//}