132 lines
4.2 KiB
C++
132 lines
4.2 KiB
C++
/*
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* matching_test.cpp
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*
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* Created on: Oct 17, 2010
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* Author: ethan
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*/
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#include "opencv2/core/core.hpp"
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#include "opencv2/calib3d/calib3d.hpp"
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#include "opencv2/features2d/features2d.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include <vector>
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#include <iostream>
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using namespace cv;
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using namespace std;
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//Copy (x,y) location of descriptor matches found from KeyPoint data structures into Point2f vectors
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static void matches2points(const vector<DMatch>& matches, const vector<KeyPoint>& kpts_train,
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const vector<KeyPoint>& kpts_query, vector<Point2f>& pts_train, vector<Point2f>& pts_query)
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{
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pts_train.clear();
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pts_query.clear();
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pts_train.reserve(matches.size());
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pts_query.reserve(matches.size());
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for (size_t i = 0; i < matches.size(); i++)
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{
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const DMatch& match = matches[i];
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pts_query.push_back(kpts_query[match.queryIdx].pt);
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pts_train.push_back(kpts_train[match.trainIdx].pt);
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}
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}
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static double match(const vector<KeyPoint>& /*kpts_train*/, const vector<KeyPoint>& /*kpts_query*/, DescriptorMatcher& matcher,
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const Mat& train, const Mat& query, vector<DMatch>& matches)
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{
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double t = (double)getTickCount();
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matcher.match(query, train, matches); //Using features2d
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return ((double)getTickCount() - t) / getTickFrequency();
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}
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static void help()
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{
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cout << "This program shows how to use BRIEF descriptor to match points in features2d" << endl <<
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"It takes in two images, finds keypoints and matches them displaying matches and final homography warped results" << endl <<
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"Usage: " << endl <<
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"image1 image2 " << endl <<
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"Example: " << endl <<
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"box.png box_in_scene.png " << endl;
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}
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const char* keys =
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{
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"{1| |box.png |the first image}"
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"{2| |box_in_scene.png|the second image}"
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};
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int main(int argc, const char ** argv)
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{
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help();
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CommandLineParser parser(argc, argv, keys);
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string im1_name = parser.get<string>("1");
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string im2_name = parser.get<string>("2");
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Mat im1 = imread(im1_name, CV_LOAD_IMAGE_GRAYSCALE);
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Mat im2 = imread(im2_name, CV_LOAD_IMAGE_GRAYSCALE);
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if (im1.empty() || im2.empty())
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{
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cout << "could not open one of the images..." << endl;
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cout << "the cmd parameters have next current value: " << endl;
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parser.printParams();
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return 1;
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}
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double t = (double)getTickCount();
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FastFeatureDetector detector(50);
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BriefDescriptorExtractor extractor(32); //this is really 32 x 8 matches since they are binary matches packed into bytes
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vector<KeyPoint> kpts_1, kpts_2;
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detector.detect(im1, kpts_1);
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detector.detect(im2, kpts_2);
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t = ((double)getTickCount() - t) / getTickFrequency();
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cout << "found " << kpts_1.size() << " keypoints in " << im1_name << endl << "fount " << kpts_2.size()
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<< " keypoints in " << im2_name << endl << "took " << t << " seconds." << endl;
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Mat desc_1, desc_2;
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cout << "computing descriptors..." << endl;
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t = (double)getTickCount();
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extractor.compute(im1, kpts_1, desc_1);
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extractor.compute(im2, kpts_2, desc_2);
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t = ((double)getTickCount() - t) / getTickFrequency();
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cout << "done computing descriptors... took " << t << " seconds" << endl;
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//Do matching using features2d
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cout << "matching with BruteForceMatcher<Hamming>" << endl;
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BFMatcher matcher_popcount(NORM_HAMMING);
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vector<DMatch> matches_popcount;
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double pop_time = match(kpts_1, kpts_2, matcher_popcount, desc_1, desc_2, matches_popcount);
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cout << "done BruteForceMatcher<Hamming> matching. took " << pop_time << " seconds" << endl;
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vector<Point2f> mpts_1, mpts_2;
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matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2); //Extract a list of the (x,y) location of the matches
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vector<uchar> outlier_mask;
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Mat H = findHomography(mpts_2, mpts_1, RANSAC, 1, outlier_mask);
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Mat outimg;
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drawMatches(im2, kpts_2, im1, kpts_1, matches_popcount, outimg, Scalar::all(-1), Scalar::all(-1),
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*(const vector<char>*)(void*)(&outlier_mask));
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imshow("matches - popcount - outliers removed", outimg);
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Mat warped;
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Mat diff;
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warpPerspective(im2, warped, H, im1.size());
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imshow("warped", warped);
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absdiff(im1,warped,diff);
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imshow("diff", diff);
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waitKey();
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return 0;
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}
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