opencv/samples/cpp/matching_to_many_images.cpp

263 lines
10 KiB
C++
Raw Normal View History

2010-11-17 00:34:27 +08:00
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/contrib/contrib.hpp"
2010-11-17 00:34:27 +08:00
#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";
2012-06-08 01:21:29 +08:00
static void printPrompt( const string& applName )
2010-11-29 15:54:10 +08:00
{
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;
2010-11-29 15:54:10 +08:00
2010-12-04 16:30:30 +08:00
cout << endl << "Format:\n" << endl;
2010-11-29 15:54:10 +08:00
cout << "./" << applName << " [detectorType] [descriptorType] [matcherType] [queryImage] [fileWithTrainImages] [dirToSaveResImages]" << endl;
cout << endl;
cout << "\nExample:" << endl
<< "./" << applName << " " << defaultDetectorType << " " << defaultDescriptorType << " " << defaultMatcherType << " "
<< defaultQueryImageName << " " << defaultFileWithTrainImages << " " << defaultDirToSaveResImages << endl;
}
2012-06-08 01:21:29 +08:00
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;
}
}
2012-06-08 01:21:29 +08:00
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();
}
2012-06-08 01:21:29 +08:00
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;
}
2012-06-08 01:21:29 +08:00
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, IMREAD_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, IMREAD_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;
}
2012-06-08 01:21:29 +08:00
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;
}
2012-06-08 01:21:29 +08:00
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 );
2012-06-08 01:21:29 +08:00
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;
}
2012-06-08 01:21:29 +08:00
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() );
2012-06-08 01:21:29 +08:00
cout << "Number of matches: " << matches.size() << endl;
cout << "Build time: " << buildTime << " ms; Match time: " << matchTime << " ms" << endl;
cout << ">" << endl;
}
2012-06-08 01:21:29 +08:00
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;
}
}
2010-11-17 00:34:27 +08:00
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;
}
2010-11-17 00:34:27 +08:00
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;
}