+++ /dev/null
-#include <cv.h>
-#include <cvaux.h>
-#include <highgui.h>
-#include <iostream>
-
-using namespace cv;
-using namespace std;
-
-inline Point2f applyHomography( const Mat_<double>& H, const Point2f& pt )
-{
- double w = 1./(H(2,0)*pt.x + H(2,1)*pt.y + H(2,2));
- return Point2f( (float)((H(0,0)*pt.x + H(0,1)*pt.y + H(0,2))*w), (float)((H(1,0)*pt.x + H(1,1)*pt.y + H(1,2))*w) );
-}
-
-void drawCorrespondences( const Mat& img1, const Mat& img2, const Mat& transfMtr,
- const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints2,
- const vector<int>& matches, float maxDist, Mat& drawImg )
-{
- Scalar RED = CV_RGB(255, 0, 0);
- Scalar PINK = CV_RGB(255,130,230);
- Scalar GREEN = CV_RGB(0, 255, 0);
- Scalar BLUE = CV_RGB(0, 0, 255);
-
- /* Output:
- red point - point without corresponding point;
- grean point - point having correct corresponding point;
- pink point - point having incorrect corresponding point, but excised by threshold of distance;
- blue point - point having incorrect corresponding point;
- */
- Size size(img1.cols + img2.cols, MAX(img1.rows, img2.rows));
- drawImg.create(size, CV_MAKETYPE(img1.depth(), 3));
- Mat drawImg1 = drawImg(Rect(0, 0, img1.cols, img1.rows));
- cvtColor(img1, drawImg1, CV_GRAY2RGB);
- Mat drawImg2 = drawImg(Rect(img1.cols, 0, img2.cols, img2.rows));
- cvtColor(img2, drawImg2, CV_GRAY2RGB);
-
- for(vector<KeyPoint>::const_iterator it = keypoints1.begin(); it < keypoints1.end(); ++it )
- {
- circle(drawImg, it->pt, 3, RED);
- }
-
- for(vector<KeyPoint>::const_iterator it = keypoints2.begin(); it < keypoints2.end(); ++it )
- {
- Point p = it->pt;
- circle(drawImg, Point2f(p.x+img1.cols, p.y), 3, RED);
- }
-
- Mat vec1(3, 1, CV_32FC1), vec2;
- float err = 3;
- vector<int>::const_iterator mit = matches.begin();
- assert( matches.size() == keypoints1.size() );
- for( int i1 = 0; mit < matches.end(); ++mit, i1++ )
- {
- Point2f pt1 = keypoints1[i1].pt, pt2 = keypoints2[*mit].pt;
- Point2f diff = applyHomography(transfMtr, pt1) - pt2;
- if( norm(diff) < err )
- {
- circle(drawImg, pt1, 3, GREEN);
- circle(drawImg, Point2f(pt2.x+img1.cols, pt2.y), 3, GREEN);
- line(drawImg, pt1, Point2f(pt2.x+img1.cols, pt2.y), GREEN);
- }
- else
- {
- /*if( *dit > maxDist )
- {
- circle(drawImg, pt1, 3, PINK);
- circle(drawImg, Point2f(pt2.x+img1.cols, pt2.y), 3, PINK);
- }
- // TODO add key point filter
- else*/
- {
- circle(drawImg, pt1, 3, BLUE);
- circle(drawImg, Point2f(pt2.x+img1.cols, pt2.y), 3, BLUE);
- line(drawImg, pt1, Point2f(pt2.x+img1.cols, pt2.y), BLUE);
- }
- }
- }
-}
-
-FeatureDetector* createDetector( const string& detectorType )
-{
- FeatureDetector* fd = 0;
- if( !detectorType.compare( "FAST" ) )
- {
- fd = new FastFeatureDetector( 1/*threshold*/, true/*nonmax_suppression*/ );
- }
- else if( !detectorType.compare( "STAR" ) )
- {
- fd = new StarFeatureDetector( 16/*max_size*/, 30/*response_threshold*/, 10/*line_threshold_projected*/,
- 8/*line_threshold_binarized*/, 5/*suppress_nonmax_size*/ );
- }
- else if( !detectorType.compare( "SIFT" ) )
- {
- fd = new SiftFeatureDetector(SIFT::DetectorParams::GET_DEFAULT_THRESHOLD(),
- SIFT::DetectorParams::GET_DEFAULT_EDGE_THRESHOLD());
- }
- else if( !detectorType.compare( "SURF" ) )
- {
- fd = new SurfFeatureDetector( 400./*hessian_threshold*/, 3 /*octaves*/, 4/*octave_layers*/ );
- }
- else if( !detectorType.compare( "MSER" ) )
- {
- fd = new MserFeatureDetector( 5/*delta*/, 60/*min_area*/, 14400/*_max_area*/, 0.25f/*max_variation*/,
- 0.2/*min_diversity*/, 200/*max_evolution*/, 1.01/*area_threshold*/, 0.003/*min_margin*/,
- 5/*edge_blur_size*/ );
- }
- else if( !detectorType.compare( "GFTT" ) )
- {
- fd = new GoodFeaturesToTrackDetector( 1000/*maxCorners*/, 0.01/*qualityLevel*/, 1./*minDistance*/,
- 3/*int _blockSize*/, true/*useHarrisDetector*/, 0.04/*k*/ );
- }
- else
- fd = 0;
-
- return fd;
-}
-
-DescriptorExtractor* createDescExtractor( const string& descriptorType )
-{
- DescriptorExtractor* de = 0;
- if( !descriptorType.compare( "CALONDER" ) )
- {
- assert(0);
- //de = new CalonderDescriptorExtractor<float>("");
- }
- else if( !descriptorType.compare( "SURF" ) )
- {
- de = new SurfDescriptorExtractor( 3/*octaves*/, 4/*octave_layers*/, false/*extended*/ );
- }
- else
- de = 0;
- return de;
-}
-
-DescriptorMatcher* createDescMatcher( const string& matherType = string() )
-{
- return new BruteForceMatcher<L2<float> >();
-}
-
-const string DETECTOR_TYPE_STR = "detector_type";
-const string DESCRIPTOR_TYPE_STR = "descriptor_type";
-
-const string winName = "correspondences";
-
-void iter( Ptr<FeatureDetector> detector, Ptr<DescriptorExtractor> descriptor,
- const Mat& img1, float maxDist, Mat& transfMtr, RNG* rng = 0 )
-{
- if( transfMtr.empty() )
- transfMtr = Mat::eye(3, 3, CV_32FC1);
- if( rng )
- {
- transfMtr.at<float>(0,0) = rng->uniform( 0.7f, 1.3f);
- transfMtr.at<float>(0,1) = rng->uniform(-0.2f, 0.2f);
- transfMtr.at<float>(0,2) = rng->uniform(-0.1f, 0.1f)*img1.cols;
- transfMtr.at<float>(1,0) = rng->uniform(-0.2f, 0.2f);
- transfMtr.at<float>(1,1) = rng->uniform( 0.7f, 1.3f);
- transfMtr.at<float>(1,2) = rng->uniform(-0.1f, 0.3f)*img1.rows;
- transfMtr.at<float>(2,0) = rng->uniform( -1e-4f, 1e-4f);
- transfMtr.at<float>(2,1) = rng->uniform( -1e-4f, 1e-4f);
- transfMtr.at<float>(2,2) = rng->uniform( 0.7f, 1.3f);
- }
-
- Mat img2; warpPerspective( img1, img2, transfMtr, img1.size() );
-
-
- cout << endl << "< Extracting keypoints... ";
- vector<KeyPoint> keypoints1, keypoints2;
- detector->detect( img1, keypoints1 );
- detector->detect( img2, keypoints2 );
- cout << keypoints1.size() << " from first image and " << keypoints2.size() << " from second image >" << endl;
- if( keypoints1.empty() || keypoints2.empty() )
- cout << "end" << endl;
-
- cout << "< Computing descriptors... ";
- Mat descs1, descs2;
- if( keypoints1.size()>0 && keypoints2.size()>0 )
- {
- descriptor->compute( img1, keypoints1, descs1 );
- descriptor->compute( img2, keypoints2, descs2 );
- }
- cout << ">" << endl;
-
- cout << "< Matching keypoints by descriptors... ";
- vector<int> matches;
- Ptr<DescriptorMatcher> matcher = createDescMatcher();
- matcher->add( descs2 );
- matcher->match( descs1, matches );
- cout << ">" << endl;
-
- // TODO time
-
- Mat drawImg;
- drawCorrespondences( img1, img2, transfMtr, keypoints1, keypoints2,
- matches, maxDist, drawImg );
- imshow( winName, drawImg);
-}
-
-Ptr<FeatureDetector> detector;
-Ptr<DescriptorExtractor> descriptor;
-Mat img1;
-Mat transfMtr;
-RNG rng;
-const float maxDistScale = 0.01f;
-int maxDist;
-
-void onMaxDistChange( int maxDist, void* )
-{
- float realMaxDist = maxDist*maxDistScale;
- cout << "maxDist " << realMaxDist << endl;
- iter( detector, descriptor, img1, realMaxDist, transfMtr );
-}
-
-int main(int argc, char** argv)
-{
- if( argc != 4 )
- {
- cout << "Format:" << endl;
- cout << "./" << argv[0] << " [detector_type] [descriptor_type] [image]" << endl;
- return 0;
- }
-
- cout << "< Creating detector, descriptor and matcher... ";
- detector = createDetector(argv[1]);
- descriptor = createDescExtractor(argv[2]);
- //Ptr<DescriptorMatcher> matcher = createDescMatcher(argv[3]);
- cout << ">" << endl;
- if( detector.empty() || descriptor.empty()/* || matcher.empty() */ )
- {
- cout << "Can not create detector or descriptor or matcher of given types" << endl;
- return 0;
- }
-
- cout << "< Reading the image... ";
- img1 = imread( argv[3], CV_LOAD_IMAGE_GRAYSCALE);
- cout << ">" << endl;
- if( img1.empty() )
- {
- cout << "Can not read image" << endl;
- return 0;
- }
-
- namedWindow(winName, 1);
- maxDist = 12;
- createTrackbar( "maxDist", winName, &maxDist, 100, onMaxDistChange );
-
- onMaxDistChange(maxDist, 0);
- for(;;)
- {
- char c = (char)cvWaitKey(0);
- if( c == '\x1b' ) // esc
- {
- cout << "Exiting ..." << endl;
- return 0;
- }
- else if( c == 'n' )
- iter(detector, descriptor, img1, maxDist*maxDistScale, transfMtr, &rng);
- }
- waitKey(0);
-}
--- /dev/null
+#include <cv.h>
+#include <cvaux.h>
+#include <highgui.h>
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+inline Point2f applyHomography( const Mat_<double>& H, const Point2f& pt )
+{
+ double z = H(2,0)*pt.x + H(2,1)*pt.y + H(2,2);
+ if( z )
+ {
+ double w = 1./z;
+ return Point2f( (H(0,0)*pt.x + H(0,1)*pt.y + H(0,2))*w, (H(1,0)*pt.x + H(1,1)*pt.y + H(1,2))*w );
+ }
+ return Point2f( numeric_limits<double>::max(), numeric_limits<double>::max() );
+}
+
+Mat warpPerspectiveRand( const Mat& src, Mat& dst, RNG* rng )
+{
+ Mat H(3, 3, CV_32FC1);
+ H.at<float>(0,0) = rng->uniform( 0.8f, 1.2f);
+ H.at<float>(0,1) = rng->uniform(-0.1f, 0.1f);
+ H.at<float>(0,2) = rng->uniform(-0.1f, 0.1f)*src.cols;
+ H.at<float>(1,0) = rng->uniform(-0.1f, 0.1f);
+ H.at<float>(1,1) = rng->uniform( 0.8f, 1.2f);
+ H.at<float>(1,2) = rng->uniform(-0.1f, 0.3f)*src.rows;
+ H.at<float>(2,0) = rng->uniform( -1e-4f, 1e-4f);
+ H.at<float>(2,1) = rng->uniform( -1e-4f, 1e-4f);
+ H.at<float>(2,2) = rng->uniform( 0.8f, 1.1f);
+
+ warpPerspective( src, dst, H, src.size() );
+ return H;
+}
+
+FeatureDetector* createDetector( const string& detectorType )
+{
+ FeatureDetector* fd = 0;
+ if( !detectorType.compare( "FAST" ) )
+ {
+ fd = new FastFeatureDetector( 10/*threshold*/, true/*nonmax_suppression*/ );
+ }
+ else if( !detectorType.compare( "STAR" ) )
+ {
+ fd = new StarFeatureDetector( 16/*max_size*/, 5/*response_threshold*/, 10/*line_threshold_projected*/,
+ 8/*line_threshold_binarized*/, 5/*suppress_nonmax_size*/ );
+ }
+ else if( !detectorType.compare( "SIFT" ) )
+ {
+ fd = new SiftFeatureDetector(SIFT::DetectorParams::GET_DEFAULT_THRESHOLD(),
+ SIFT::DetectorParams::GET_DEFAULT_EDGE_THRESHOLD());
+ }
+ else if( !detectorType.compare( "SURF" ) )
+ {
+ fd = new SurfFeatureDetector( 100./*hessian_threshold*/, 3 /*octaves*/, 4/*octave_layers*/ );
+ }
+ else if( !detectorType.compare( "MSER" ) )
+ {
+ fd = new MserFeatureDetector( 5/*delta*/, 60/*min_area*/, 14400/*_max_area*/, 0.25f/*max_variation*/,
+ 0.2/*min_diversity*/, 200/*max_evolution*/, 1.01/*area_threshold*/, 0.003/*min_margin*/,
+ 5/*edge_blur_size*/ );
+ }
+ else if( !detectorType.compare( "GFTT" ) )
+ {
+ fd = new GoodFeaturesToTrackDetector( 1000/*maxCorners*/, 0.01/*qualityLevel*/, 1./*minDistance*/,
+ 3/*int _blockSize*/, true/*useHarrisDetector*/, 0.04/*k*/ );
+ }
+ else
+ assert(0);
+ return fd;
+}
+
+GenericDescriptorMatch* createDescriptorMatch( const string& descriptorType )
+{
+ GenericDescriptorMatch* de = 0;
+ if( !descriptorType.compare( "SIFT" ) )
+ {
+ SiftDescriptorExtractor extractor/*( double magnification=SIFT::DescriptorParams::GET_DEFAULT_MAGNIFICATION(),
+ bool isNormalize=true, bool recalculateAngles=true,
+ int nOctaves=SIFT::CommonParams::DEFAULT_NOCTAVES,
+ int nOctaveLayers=SIFT::CommonParams::DEFAULT_NOCTAVE_LAYERS,
+ int firstOctave=SIFT::CommonParams::DEFAULT_FIRST_OCTAVE,
+ int angleMode=SIFT::CommonParams::FIRST_ANGLE )*/;
+ BruteForceMatcher<L2<float> > matcher;
+ de = new VectorDescriptorMatch<SiftDescriptorExtractor, BruteForceMatcher<L2<float> > >(extractor, matcher);
+
+ }
+ else if( !descriptorType.compare( "SURF" ) )
+ {
+ SurfDescriptorExtractor extractor/*( int nOctaves=4,
+ int nOctaveLayers=2, bool extended=false )*/;
+ BruteForceMatcher<L2<float> > matcher;
+ de = new VectorDescriptorMatch<SurfDescriptorExtractor, BruteForceMatcher<L2<float> > >(extractor, matcher);
+ }
+ else
+ assert(0);
+ return de;
+}
+
+void drawCorrespondences( const Mat& img1, const Mat& img2,
+ const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints2,
+ const vector<int>& matches, Mat& drawImg, const Mat& H12 = Mat() )
+{
+ Scalar RED = CV_RGB(255, 0, 0); // red keypoint - point without corresponding point
+ Scalar GREEN = CV_RGB(0, 255, 0); // green keypoint - point having correct corresponding point
+ Scalar BLUE = CV_RGB(0, 0, 255); // blue keypoint - point having incorrect corresponding point
+
+ Size size(img1.cols + img2.cols, MAX(img1.rows, img2.rows));
+ drawImg.create(size, CV_MAKETYPE(img1.depth(), 3));
+ Mat drawImg1 = drawImg(Rect(0, 0, img1.cols, img1.rows));
+ cvtColor(img1, drawImg1, CV_GRAY2RGB);
+ Mat drawImg2 = drawImg(Rect(img1.cols, 0, img2.cols, img2.rows));
+ cvtColor(img2, drawImg2, CV_GRAY2RGB);
+
+ // draw keypoints
+ for(vector<KeyPoint>::const_iterator it = keypoints1.begin(); it < keypoints1.end(); ++it )
+ {
+ circle(drawImg, it->pt, 3, RED);
+ }
+ for(vector<KeyPoint>::const_iterator it = keypoints2.begin(); it < keypoints2.end(); ++it )
+ {
+ Point p = it->pt;
+ circle(drawImg, Point2f(p.x+img1.cols, p.y), 3, RED);
+ }
+
+ // draw matches
+ vector<int>::const_iterator mit = matches.begin();
+ assert( matches.size() == keypoints1.size() );
+ for( int i1 = 0; mit != matches.end(); ++mit, i1++ )
+ {
+ Point2f pt1 = keypoints1[i1].pt,
+ pt2 = keypoints2[*mit].pt,
+ dpt2 = Point2f( std::min(pt2.x+img1.cols, float(drawImg.cols-1)), pt2.y);
+ if( !H12.empty() )
+ {
+ if( norm(pt2 - applyHomography(H12, pt1)) > 3 )
+ {
+ circle(drawImg, pt1, 3, BLUE);
+ circle(drawImg, dpt2, 3, BLUE);
+ continue;
+ }
+ }
+ circle(drawImg, pt1, 3, GREEN);
+ circle(drawImg, dpt2, 3, GREEN);
+ line(drawImg, pt1, dpt2, GREEN);
+ }
+}
+
+const string winName = "correspondences";
+
+void doIteration( const Mat& img1, Mat& img2, bool isWarpPerspective, vector<KeyPoint>& keypoints1,
+ Ptr<FeatureDetector>& detector, Ptr<GenericDescriptorMatch>& descriptor,
+ double ransacReprojThreshold = -1, RNG* rng = 0 )
+{
+ assert( !img1.empty() );
+ Mat H12;
+ if( isWarpPerspective )
+ {
+ assert( rng );
+ H12 = warpPerspectiveRand(img1, img2, rng);
+ }
+ else
+ assert( !img2.empty() && img2.cols==img1.cols && img2.rows== img1.rows );
+
+ cout << endl << "< Extracting keypoints from second image..." << endl;
+ vector<KeyPoint> keypoints2;
+ detector->detect( img2, keypoints2 );
+ cout << keypoints2.size() << " >" << endl;
+
+ cout << "< Computing and matching descriptors..." << endl;
+ vector<int> matches;
+ //if( keypoints1.size()>0 && keypoints2.size()>0 )
+ {
+ descriptor->clear();
+ descriptor->add( img2, keypoints2 );
+ descriptor->match( img1, keypoints1, matches );
+ }
+ cout << ">" << endl;
+
+ if( !isWarpPerspective && ransacReprojThreshold >= 0 )
+ {
+ cout << "< Computing homography (RANSAC)..." << endl;
+ vector<Point2f> points1(matches.size()), points2(matches.size());
+ for( int i = 0; i < matches.size(); i++ )
+ {
+ points1[i] = keypoints1[i].pt;
+ points2[i] = keypoints2[matches[i]].pt;
+ }
+ H12 = findHomography( Mat(points1), Mat(points2), CV_RANSAC, ransacReprojThreshold );
+ cout << ">" << endl;
+ }
+
+ Mat drawImg;
+ drawCorrespondences( img1, img2, keypoints1, keypoints2, matches, drawImg, H12 );
+ imshow( winName, drawImg );
+}
+
+int main(int argc, char** argv)
+{
+ if( argc != 4 && argc != 6 )
+ {
+ cout << "Format:" << endl;
+ cout << "case1: second image is obtained from the first (given) image using random generated homography matrix" << endl;
+ cout << argv[0] << " [detectorType] [descriptorType] [image1]" << endl;
+ cout << "case2: both images are given. If ransacReprojThreshold>=0 then homography matrix are calculated" << endl;
+ cout << argv[0] << " [detectorType] [descriptorType] [image1] [image2] [ransacReprojThreshold]" << endl;
+ cout << endl << "Mathes are filtered using homography matrix in case1 and case2 (if ransacReprojThreshold>=0)" << endl;
+ return 0;
+ }
+ bool isWarpPerspective = argc == 4;
+ double ransacReprojThreshold = -1;
+ if( !isWarpPerspective )
+ ransacReprojThreshold = atof(argv[5]);
+
+ cout << "< Creating detector, descriptor..." << endl;
+ Ptr<FeatureDetector> detector = createDetector(argv[1]);
+ Ptr<GenericDescriptorMatch> descriptor = createDescriptorMatch(argv[2]);
+ cout << ">" << endl;
+ if( detector.empty() || descriptor.empty() )
+ {
+ cout << "Can not create detector or descriptor or matcher of given types" << endl;
+ return 0;
+ }
+
+ cout << "< Reading the images..." << endl;
+ Mat img1 = imread( argv[3], CV_LOAD_IMAGE_GRAYSCALE), img2;
+ if( !isWarpPerspective )
+ img2 = imread( argv[4], CV_LOAD_IMAGE_GRAYSCALE);
+ cout << ">" << endl;
+ if( img1.empty() || (!isWarpPerspective && img2.empty()) )
+ {
+ cout << "Can not read images" << endl;
+ return 0;
+ }
+
+ cout << endl << "< Extracting keypoints from first image..." << endl;
+ vector<KeyPoint> keypoints1;
+ detector->detect( img1, keypoints1 );
+ cout << keypoints1.size() << " >" << endl;
+
+ namedWindow(winName, 1);
+ RNG rng;
+ doIteration( img1, img2, isWarpPerspective, keypoints1, detector, descriptor, ransacReprojThreshold, &rng );
+ for(;;)
+ {
+ char c = (char)cvWaitKey(0);
+ if( c == '\x1b' ) // esc
+ {
+ cout << "Exiting ..." << endl;
+ return 0;
+ }
+ else if( isWarpPerspective )
+ {
+ doIteration( img1, img2, isWarpPerspective, keypoints1, detector, descriptor, ransacReprojThreshold, &rng );
+ }
+ }
+ waitKey(0);
+}
projects / profile / ivi / opencv.git / commitdiff