#include "opencv2/highgui/highgui.hpp" #include "opencv2/features2d/features2d.hpp" #include "opencv2/contrib/contrib.hpp" #include #include using namespace cv; using namespace std; const string defaultDetectorType = "SURF"; const string defaultDescriptorType = "SURF"; const string defaultMatcherType = "FlannBased"; const string defaultQueryImageName = "../../opencv/samples/cpp/matching_to_many_images/query.png"; const string defaultFileWithTrainImages = "../../opencv/samples/cpp/matching_to_many_images/train/trainImages.txt"; const string defaultDirToSaveResImages = "../../opencv/samples/cpp/matching_to_many_images/results"; static void printPrompt( const string& applName ) { cout << "/*\n" << " * This is a sample on matching descriptors detected on one image to descriptors detected in image set.\n" << " * So we have one query image and several train images. For each keypoint descriptor of query image\n" << " * the one nearest train descriptor is found the entire collection of train images. To visualize the result\n" << " * of matching we save images, each of which combines query and train image with matches between them (if they exist).\n" << " * Match is drawn as line between corresponding points. Count of all matches is equel to count of\n" << " * query keypoints, so we have the same count of lines in all set of result images (but not for each result\n" << " * (train) image).\n" << " */\n" << endl; cout << endl << "Format:\n" << endl; cout << "./" << applName << " [detectorType] [descriptorType] [matcherType] [queryImage] [fileWithTrainImages] [dirToSaveResImages]" << endl; cout << endl; cout << "\nExample:" << endl << "./" << applName << " " << defaultDetectorType << " " << defaultDescriptorType << " " << defaultMatcherType << " " << defaultQueryImageName << " " << defaultFileWithTrainImages << " " << defaultDirToSaveResImages << endl; } static void maskMatchesByTrainImgIdx( const vector& matches, int trainImgIdx, vector& mask ) { mask.resize( matches.size() ); fill( mask.begin(), mask.end(), 0 ); for( size_t i = 0; i < matches.size(); i++ ) { if( matches[i].imgIdx == trainImgIdx ) mask[i] = 1; } } static void readTrainFilenames( const string& filename, string& dirName, vector& trainFilenames ) { trainFilenames.clear(); ifstream file( filename.c_str() ); if ( !file.is_open() ) return; size_t pos = filename.rfind('\\'); char dlmtr = '\\'; if (pos == String::npos) { pos = filename.rfind('/'); dlmtr = '/'; } dirName = pos == string::npos ? "" : filename.substr(0, pos) + dlmtr; while( !file.eof() ) { string str; getline( file, str ); if( str.empty() ) break; trainFilenames.push_back(str); } file.close(); } static bool createDetectorDescriptorMatcher( const string& detectorType, const string& descriptorType, const string& matcherType, Ptr& featureDetector, Ptr& descriptorExtractor, Ptr& descriptorMatcher ) { cout << "< Creating feature detector, descriptor extractor and descriptor matcher ..." << endl; featureDetector = FeatureDetector::create( detectorType ); descriptorExtractor = DescriptorExtractor::create( descriptorType ); descriptorMatcher = DescriptorMatcher::create( matcherType ); cout << ">" << endl; bool isCreated = !( featureDetector.empty() || descriptorExtractor.empty() || descriptorMatcher.empty() ); if( !isCreated ) cout << "Can not create feature detector or descriptor extractor or descriptor matcher of given types." << endl << ">" << endl; return isCreated; } static bool readImages( const string& queryImageName, const string& trainFilename, Mat& queryImage, vector & trainImages, vector& trainImageNames ) { cout << "< Reading the images..." << endl; queryImage = imread( queryImageName, CV_LOAD_IMAGE_GRAYSCALE); if( queryImage.empty() ) { cout << "Query image can not be read." << endl << ">" << endl; return false; } string trainDirName; readTrainFilenames( trainFilename, trainDirName, trainImageNames ); if( trainImageNames.empty() ) { cout << "Train image filenames can not be read." << endl << ">" << endl; return false; } int readImageCount = 0; for( size_t i = 0; i < trainImageNames.size(); i++ ) { string filename = trainDirName + trainImageNames[i]; Mat img = imread( filename, CV_LOAD_IMAGE_GRAYSCALE ); if( img.empty() ) cout << "Train image " << filename << " can not be read." << endl; else readImageCount++; trainImages.push_back( img ); } if( !readImageCount ) { cout << "All train images can not be read." << endl << ">" << endl; return false; } else cout << readImageCount << " train images were read." << endl; cout << ">" << endl; return true; } static void detectKeypoints( const Mat& queryImage, vector& queryKeypoints, const vector& trainImages, vector >& trainKeypoints, Ptr& featureDetector ) { cout << endl << "< Extracting keypoints from images..." << endl; featureDetector->detect( queryImage, queryKeypoints ); featureDetector->detect( trainImages, trainKeypoints ); cout << ">" << endl; } static void computeDescriptors( const Mat& queryImage, vector& queryKeypoints, Mat& queryDescriptors, const vector& trainImages, vector >& trainKeypoints, vector& trainDescriptors, Ptr& descriptorExtractor ) { cout << "< Computing descriptors for keypoints..." << endl; descriptorExtractor->compute( queryImage, queryKeypoints, queryDescriptors ); descriptorExtractor->compute( trainImages, trainKeypoints, trainDescriptors ); int totalTrainDesc = 0; for( vector::const_iterator tdIter = trainDescriptors.begin(); tdIter != trainDescriptors.end(); tdIter++ ) totalTrainDesc += tdIter->rows; cout << "Query descriptors count: " << queryDescriptors.rows << "; Total train descriptors count: " << totalTrainDesc << endl; cout << ">" << endl; } static void matchDescriptors( const Mat& queryDescriptors, const vector& trainDescriptors, vector& matches, Ptr& descriptorMatcher ) { cout << "< Set train descriptors collection in the matcher and match query descriptors to them..." << endl; TickMeter tm; tm.start(); descriptorMatcher->add( trainDescriptors ); descriptorMatcher->train(); tm.stop(); double buildTime = tm.getTimeMilli(); tm.start(); descriptorMatcher->match( queryDescriptors, matches ); tm.stop(); double matchTime = tm.getTimeMilli(); CV_Assert( queryDescriptors.rows == (int)matches.size() || matches.empty() ); cout << "Number of matches: " << matches.size() << endl; cout << "Build time: " << buildTime << " ms; Match time: " << matchTime << " ms" << endl; cout << ">" << endl; } static void saveResultImages( const Mat& queryImage, const vector& queryKeypoints, const vector& trainImages, const vector >& trainKeypoints, const vector& matches, const vector& trainImagesNames, const string& resultDir ) { cout << "< Save results..." << endl; Mat drawImg; vector mask; for( size_t i = 0; i < trainImages.size(); i++ ) { if( !trainImages[i].empty() ) { maskMatchesByTrainImgIdx( matches, (int)i, mask ); drawMatches( queryImage, queryKeypoints, trainImages[i], trainKeypoints[i], matches, drawImg, Scalar(255, 0, 0), Scalar(0, 255, 255), mask ); string filename = resultDir + "/res_" + trainImagesNames[i]; if( !imwrite( filename, drawImg ) ) cout << "Image " << filename << " can not be saved (may be because directory " << resultDir << " does not exist)." << endl; } } cout << ">" << endl; } int main(int argc, char** argv) { string detectorType = defaultDetectorType; string descriptorType = defaultDescriptorType; string matcherType = defaultMatcherType; string queryImageName = defaultQueryImageName; string fileWithTrainImages = defaultFileWithTrainImages; string dirToSaveResImages = defaultDirToSaveResImages; if( argc != 7 && argc != 1 ) { printPrompt( argv[0] ); return -1; } if( argc != 1 ) { detectorType = argv[1]; descriptorType = argv[2]; matcherType = argv[3]; queryImageName = argv[4]; fileWithTrainImages = argv[5]; dirToSaveResImages = argv[6]; } Ptr featureDetector; Ptr descriptorExtractor; Ptr descriptorMatcher; if( !createDetectorDescriptorMatcher( detectorType, descriptorType, matcherType, featureDetector, descriptorExtractor, descriptorMatcher ) ) { printPrompt( argv[0] ); return -1; } Mat queryImage; vector trainImages; vector trainImagesNames; if( !readImages( queryImageName, fileWithTrainImages, queryImage, trainImages, trainImagesNames ) ) { printPrompt( argv[0] ); return -1; } vector queryKeypoints; vector > trainKeypoints; detectKeypoints( queryImage, queryKeypoints, trainImages, trainKeypoints, featureDetector ); Mat queryDescriptors; vector trainDescriptors; computeDescriptors( queryImage, queryKeypoints, queryDescriptors, trainImages, trainKeypoints, trainDescriptors, descriptorExtractor ); vector matches; matchDescriptors( queryDescriptors, trainDescriptors, matches, descriptorMatcher ); saveResultImages( queryImage, queryKeypoints, trainImages, trainKeypoints, matches, trainImagesNames, dirToSaveResImages ); return 0; }