Added sample for GenericDescriptorMatch

pull/13383/head
Ilya Lysenkov 15 years ago
parent 809ebddefb
commit b251136e45
  1. 2
      modules/features2d/include/opencv2/features2d/features2d.hpp
  2. 32
      modules/features2d/src/descriptors.cpp
  3. 10
      samples/c/calonder_params.xml
  4. 10
      samples/c/fern_params.xml
  5. 94
      samples/c/match_sample.cpp

@ -1751,6 +1751,8 @@ public:
// Writes match object to a file storage
virtual void write( FileStorage& fs ) const {};
static GenericDescriptorMatch* CreateDescriptorMatch( const string &alg_name, const string &params_filename = string () );
protected:
KeyPointCollection collection;
};

@ -226,6 +226,38 @@ void GenericDescriptorMatch::clear()
{
collection.clear();
}
GenericDescriptorMatch* GenericDescriptorMatch::CreateDescriptorMatch( const string &alg_name, const string &params_filename )
{
GenericDescriptorMatch *descriptorMatch = 0;
if( ! alg_name.compare ("one_way") )
{
descriptorMatch = new OneWayDescriptorMatch ();
}
else if( ! alg_name.compare ("fern") )
{
FernDescriptorMatch::Params params;
params.signatureSize = INT_MAX;
descriptorMatch = new FernDescriptorMatch (params);
}
else if( ! alg_name.compare ("calonder") )
{
descriptorMatch = new CalonderDescriptorMatch ();
}
if( !params_filename.empty() && descriptorMatch != 0 )
{
FileStorage fs = FileStorage( params_filename, FileStorage::READ );
if( fs.isOpened() )
{
descriptorMatch->read( fs.root() );
fs.release();
}
}
return descriptorMatch;
}
/****************************************************************************************\
* OneWayDescriptorMatch *
\****************************************************************************************/

@ -0,0 +1,10 @@
<?xml version="1.0"?>
<opencv_storage>
<numTrees>20</numTrees>
<depth>7</depth>
<views>1000</views>
<patchSize>20</patchSize>
<reducedNumDim>30</reducedNumDim>
<numQuantBits>4</numQuantBits>
<printStatus>1</printStatus>
</opencv_storage>

@ -0,0 +1,10 @@
<?xml version="1.0"?>
<opencv_storage>
<nclasses>0</nclasses>
<patchSize>31</patchSize>
<signatureSize>INT_MAX</signatureSize>
<nstructs>50</nstructs>
<structSize>9</structSize>
<nviews>1000</nviews>
<compressionMethod>0</compressionMethod>
</opencv_storage>

@ -0,0 +1,94 @@
#include <cv.h>
#include <cvaux.h>
#include <highgui.h>
#include <string>
using namespace cv;
IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
const vector<KeyPoint>& features2, const vector<int>& desc_idx);
int main(int argc, char** argv)
{
if (argc != 5)
{
printf("Format: \n./match_sample [image1] [image2] [algorithm] [XML params]\n");
printf("For example: ./match_sample scene_l.bmp scene_r.bmp fern fern_params.xml\n");
return 0;
}
std::string img1_name = std::string(argv[1]);
std::string img2_name = std::string(argv[2]);
std::string alg_name = std::string(argv[3]);
std::string params_filename = std::string(argv[4]);
GenericDescriptorMatch *descriptorMatch = GenericDescriptorMatch::CreateDescriptorMatch (alg_name, params_filename);
if( descriptorMatch == 0 )
{
printf ("Cannot create descriptor\n");
return 0;
}
//printf("Reading the images...\n");
IplImage* img1 = cvLoadImage(img1_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
IplImage* img2 = cvLoadImage(img2_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
// extract keypoints from the first image
SURF surf_extractor(5.0e3);
vector<KeyPoint> keypoints1;
// printf("Extracting keypoints\n");
surf_extractor(img1, Mat(), keypoints1);
printf("Extracted %d keypoints from the first image\n", (int)keypoints1.size());
vector<KeyPoint> keypoints2;
surf_extractor(img2, Mat(), keypoints2);
printf("Extracted %d keypoints from the second image\n", (int)keypoints2.size());
printf("Finding nearest neighbors... \n");
// find NN for each of keypoints2 in keypoints1
descriptorMatch->add( img1, keypoints1 );
vector<int> matches2to1;
matches2to1.resize(keypoints2.size());
descriptorMatch->match( img2, keypoints2, matches2to1 );
printf("Done\n");
IplImage* img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, matches2to1);
cvNamedWindow("correspondences", 1);
cvShowImage("correspondences", img_corr);
cvWaitKey(0);
cvReleaseImage(&img1);
cvReleaseImage(&img2);
cvReleaseImage(&img_corr);
delete descriptorMatch;
}
IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
const vector<KeyPoint>& features2, const vector<int>& desc_idx)
{
IplImage* img_corr = cvCreateImage(cvSize(img1->width + img2->width, MAX(img1->height, img2->height)),
IPL_DEPTH_8U, 3);
cvSetImageROI(img_corr, cvRect(0, 0, img1->width, img1->height));
cvCvtColor(img1, img_corr, CV_GRAY2RGB);
cvSetImageROI(img_corr, cvRect(img1->width, 0, img2->width, img2->height));
cvCvtColor(img2, img_corr, CV_GRAY2RGB);
cvResetImageROI(img_corr);
for (size_t i = 0; i < features1.size(); i++)
{
cvCircle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0));
}
for (size_t i = 0; i < features2.size(); i++)
{
CvPoint pt = cvPoint(features2[i].pt.x + img1->width, features2[i].pt.y);
cvCircle(img_corr, pt, 3, CV_RGB(255, 0, 0));
cvLine(img_corr, features1[desc_idx[i]].pt, pt, CV_RGB(0, 255, 0));
}
return img_corr;
}
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