1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262
|
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/contrib/contrib.hpp"
#include <iostream>
#include <fstream>
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<DMatch>& matches, int trainImgIdx, vector<char>& 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<string>& 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>& featureDetector,
Ptr<DescriptorExtractor>& descriptorExtractor,
Ptr<DescriptorMatcher>& 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 <Mat>& trainImages, vector<string>& 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<KeyPoint>& queryKeypoints,
const vector<Mat>& trainImages, vector<vector<KeyPoint> >& trainKeypoints,
Ptr<FeatureDetector>& 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<KeyPoint>& queryKeypoints, Mat& queryDescriptors,
const vector<Mat>& trainImages, vector<vector<KeyPoint> >& trainKeypoints, vector<Mat>& trainDescriptors,
Ptr<DescriptorExtractor>& descriptorExtractor )
{
cout << "< Computing descriptors for keypoints..." << endl;
descriptorExtractor->compute( queryImage, queryKeypoints, queryDescriptors );
descriptorExtractor->compute( trainImages, trainKeypoints, trainDescriptors );
int totalTrainDesc = 0;
for( vector<Mat>::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<Mat>& trainDescriptors,
vector<DMatch>& matches, Ptr<DescriptorMatcher>& 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<KeyPoint>& queryKeypoints,
const vector<Mat>& trainImages, const vector<vector<KeyPoint> >& trainKeypoints,
const vector<DMatch>& matches, const vector<string>& trainImagesNames, const string& resultDir )
{
cout << "< Save results..." << endl;
Mat drawImg;
vector<char> 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> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
Ptr<DescriptorMatcher> descriptorMatcher;
if( !createDetectorDescriptorMatcher( detectorType, descriptorType, matcherType, featureDetector, descriptorExtractor, descriptorMatcher ) )
{
printPrompt( argv[0] );
return -1;
}
Mat queryImage;
vector<Mat> trainImages;
vector<string> trainImagesNames;
if( !readImages( queryImageName, fileWithTrainImages, queryImage, trainImages, trainImagesNames ) )
{
printPrompt( argv[0] );
return -1;
}
vector<KeyPoint> queryKeypoints;
vector<vector<KeyPoint> > trainKeypoints;
detectKeypoints( queryImage, queryKeypoints, trainImages, trainKeypoints, featureDetector );
Mat queryDescriptors;
vector<Mat> trainDescriptors;
computeDescriptors( queryImage, queryKeypoints, queryDescriptors,
trainImages, trainKeypoints, trainDescriptors,
descriptorExtractor );
vector<DMatch> matches;
matchDescriptors( queryDescriptors, trainDescriptors, matches, descriptorMatcher );
saveResultImages( queryImage, queryKeypoints, trainImages, trainKeypoints,
matches, trainImagesNames, dirToSaveResImages );
return 0;
}
|