200 lines
7.7 KiB
C++
200 lines
7.7 KiB
C++
#include <highgui.h>
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#include "opencv2/core/core.hpp"
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#include "opencv2/calib3d/calib3d.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/features2d/features2d.hpp"
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#include <iostream>
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using namespace cv;
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using namespace std;
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#define DRAW_RICH_KEYPOINTS_MODE 0
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#define DRAW_OUTLIERS_MODE 0
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void warpPerspectiveRand( const Mat& src, Mat& dst, Mat& H, RNG& rng )
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{
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H.create(3, 3, CV_32FC1);
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H.at<float>(0,0) = rng.uniform( 0.8f, 1.2f);
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H.at<float>(0,1) = rng.uniform(-0.1f, 0.1f);
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H.at<float>(0,2) = rng.uniform(-0.1f, 0.1f)*src.cols;
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H.at<float>(1,0) = rng.uniform(-0.1f, 0.1f);
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H.at<float>(1,1) = rng.uniform( 0.8f, 1.2f);
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H.at<float>(1,2) = rng.uniform(-0.1f, 0.1f)*src.rows;
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H.at<float>(2,0) = rng.uniform( -1e-4f, 1e-4f);
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H.at<float>(2,1) = rng.uniform( -1e-4f, 1e-4f);
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H.at<float>(2,2) = rng.uniform( 0.8f, 1.2f);
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warpPerspective( src, dst, H, src.size() );
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}
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const string winName = "correspondences";
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void doIteration( const Mat& img1, Mat& img2, bool isWarpPerspective,
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vector<KeyPoint>& keypoints1, const Mat& descriptors1,
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Ptr<FeatureDetector>& detector, Ptr<DescriptorExtractor>& descriptorExtractor,
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Ptr<DescriptorMatcher>& descriptorMatcher,
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double ransacReprojThreshold, RNG& rng )
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{
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assert( !img1.empty() );
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Mat H12;
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if( isWarpPerspective )
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warpPerspectiveRand(img1, img2, H12, rng );
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else
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assert( !img2.empty()/* && img2.cols==img1.cols && img2.rows==img1.rows*/ );
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cout << endl << "< Extracting keypoints from second image..." << endl;
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vector<KeyPoint> keypoints2;
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detector->detect( img2, keypoints2 );
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cout << keypoints2.size() << " points" << endl << ">" << endl;
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if( !H12.empty() )
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{
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cout << "< Evaluate feature detector..." << endl;
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float repeatability;
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int correspCount;
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evaluateFeatureDetector( img1, img2, H12, &keypoints1, &keypoints2, repeatability, correspCount );
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cout << "repeatability = " << repeatability << endl;
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cout << "correspCount = " << correspCount << endl;
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cout << ">" << endl;
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}
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cout << "< Computing descriptors for keypoints from second image..." << endl;
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Mat descriptors2;
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descriptorExtractor->compute( img2, keypoints2, descriptors2 );
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cout << ">" << endl;
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cout << "< Matching descriptors..." << endl;
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vector<DMatch> matches;
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descriptorMatcher->match( descriptors1, descriptors2, matches, Mat() );
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cout << ">" << endl;
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if( !H12.empty() )
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{
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cout << "< Evaluate descriptor match..." << endl;
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vector<Point2f> curve;
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Ptr<GenericDescriptorMatch> gdm = new VectorDescriptorMatch( descriptorExtractor, descriptorMatcher );
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evaluateDescriptorMatch( img1, img2, H12, keypoints1, keypoints2, 0, 0, curve, gdm );
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for( float l_p = 0; l_p < 1 - FLT_EPSILON; l_p+=0.1 )
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cout << "1-precision = " << l_p << "; recall = " << getRecall( curve, l_p ) << endl;
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cout << ">" << endl;
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}
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vector<int> trainIdxs( matches.size() );
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for( size_t i = 0; i < matches.size(); i++ )
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trainIdxs[i] = matches[i].indexTrain;
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if( !isWarpPerspective && ransacReprojThreshold >= 0 )
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{
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cout << "< Computing homography (RANSAC)..." << endl;
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vector<Point2f> points1; KeyPoint::convert(keypoints1, points1);
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vector<Point2f> points2; KeyPoint::convert(keypoints2, points2, trainIdxs);
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H12 = findHomography( Mat(points1), Mat(points2), CV_RANSAC, ransacReprojThreshold );
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cout << ">" << endl;
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}
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Mat drawImg;
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if( !H12.empty() ) // filter outliers
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{
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vector<char> matchesMask( matches.size(), 0 );
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vector<Point2f> points1; KeyPoint::convert(keypoints1, points1);
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vector<Point2f> points2; KeyPoint::convert(keypoints2, points2, trainIdxs);
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Mat points1t; perspectiveTransform(Mat(points1), points1t, H12);
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for( size_t i1 = 0; i1 < points1.size(); i1++ )
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{
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if( norm(points2[i1] - points1t.at<Point2f>(i1,0)) < 4 ) // inlier
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matchesMask[i1] = 1;
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}
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// draw inliers
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drawMatches( img1, keypoints1, img2, keypoints2, matches, drawImg, CV_RGB(0, 255, 0), CV_RGB(0, 0, 255), matchesMask
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#if DRAW_RICH_KEYPOINTS_MODE
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, DrawMatchesFlags::DRAW_RICH_KEYPOINTS
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#endif
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);
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#if DRAW_OUTLIERS_MODE
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// draw outliers
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for( size_t i1 = 0; i1 < matchesMask.size(); i1++ )
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matchesMask[i1] = !matchesMask[i1];
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drawMatches( img1, keypoints1, img2, keypoints2, matches, drawImg, CV_RGB(0, 0, 255), CV_RGB(255, 0, 0), matchesMask,
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DrawMatchesFlags::DRAW_OVER_OUTIMG | DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
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#endif
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}
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else
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drawMatches( img1, keypoints1, img2, keypoints2, matches, drawImg );
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imshow( winName, drawImg );
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}
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int main(int argc, char** argv)
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{
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if( argc != 4 && argc != 6 )
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{
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cout << "Format:" << endl;
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cout << "case1: second image is obtained from the first (given) image using random generated homography matrix" << endl;
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cout << argv[0] << " [detectorType] [descriptorType] [image1]" << endl;
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cout << "case2: both images are given. If ransacReprojThreshold>=0 then homography matrix are calculated" << endl;
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cout << argv[0] << " [detectorType] [descriptorType] [image1] [image2] [ransacReprojThreshold]" << endl;
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cout << endl << "Mathes are filtered using homography matrix in case1 and case2 (if ransacReprojThreshold>=0)" << endl;
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return -1;
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}
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bool isWarpPerspective = argc == 4;
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double ransacReprojThreshold = -1;
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if( !isWarpPerspective )
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ransacReprojThreshold = atof(argv[5]);
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cout << "< Creating detector, descriptor extractor and descriptor matcher ..." << endl;
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Ptr<FeatureDetector> detector = createFeatureDetector( argv[1] );
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Ptr<DescriptorExtractor> descriptorExtractor = createDescriptorExtractor( argv[2] );
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Ptr<DescriptorMatcher> descriptorMatcher = createDescriptorMatcher( "BruteForce" );
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cout << ">" << endl;
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if( detector.empty() || descriptorExtractor.empty() || descriptorMatcher.empty() )
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{
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cout << "Can not create detector or descriptor exstractor or descriptor matcher of given types" << endl;
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return -1;
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}
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cout << "< Reading the images..." << endl;
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Mat img1 = imread( argv[3], CV_LOAD_IMAGE_GRAYSCALE), img2;
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if( !isWarpPerspective )
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img2 = imread( argv[4], CV_LOAD_IMAGE_GRAYSCALE);
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cout << ">" << endl;
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if( img1.empty() || (!isWarpPerspective && img2.empty()) )
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{
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cout << "Can not read images" << endl;
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return -1;
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}
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cout << endl << "< Extracting keypoints from first image..." << endl;
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vector<KeyPoint> keypoints1;
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detector->detect( img1, keypoints1 );
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cout << keypoints1.size() << " points" << endl << ">" << endl;
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cout << "< Computing descriptors for keypoints from first image..." << endl;
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Mat descriptors1;
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descriptorExtractor->compute( img1, keypoints1, descriptors1 );
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cout << ">" << endl;
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namedWindow(winName, 1);
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RNG rng = theRNG();
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doIteration( img1, img2, isWarpPerspective, keypoints1, descriptors1,
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detector, descriptorExtractor, descriptorMatcher,
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ransacReprojThreshold, rng );
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for(;;)
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{
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char c = (char)cvWaitKey(0);
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if( c == '\x1b' ) // esc
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{
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cout << "Exiting ..." << endl;
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return 0;
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}
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else if( isWarpPerspective )
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{
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doIteration( img1, img2, isWarpPerspective, keypoints1, descriptors1,
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detector, descriptorExtractor, descriptorMatcher,
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ransacReprojThreshold, rng );
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}
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}
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waitKey(0);
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return 0;
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}
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