added c++ interface for cvPyrMeanShiftFiltering; added sample on meanshift segmentation
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@ -333,7 +333,7 @@ void RandomizedTree::train(std::vector<BaseKeypoint> const& base_set,
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Size patchSize(PATCH_SIZE, PATCH_SIZE);
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for (keypt_it = base_set.begin(); keypt_it != base_set.end(); ++keypt_it, ++class_id) {
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for (int i = 0; i < views; ++i) {
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make_patch( Mat(keypt_it->image), Point(keypt_it->y, keypt_it->x ), patch, patchSize, rng );
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make_patch( Mat(keypt_it->image), Point(keypt_it->x, keypt_it->y ), patch, patchSize, rng );
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IplImage iplPatch = patch;
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addExample(class_id, getData(&iplPatch));
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}
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@ -653,6 +653,11 @@ CV_EXPORTS void equalizeHist( const Mat& src, Mat& dst );
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//! segments the image using watershed algorithm
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CV_EXPORTS void watershed( const Mat& image, Mat& markers );
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//! filters image using meanshift algorithm
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CV_EXPORTS void pyrMeanShiftFiltering( const Mat& src, Mat& dst,
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double sp, double sr, int maxLevel=1,
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TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) );
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//! class of the pixel in GrabCut algorithm
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enum { GC_BGD = 0, //!< background
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GC_FGD = 1, //!< foreground
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@ -526,3 +526,14 @@ cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
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}
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}
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void cv::pyrMeanShiftFiltering( const Mat& src, Mat& dst,
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double sp, double sr, int maxLevel,
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TermCriteria termcrit )
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{
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if( src.empty() )
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return;
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dst.create( src.size(), src.type() );
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CvMat _src = src, _dst = dst;
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cvPyrMeanShiftFiltering( &_src, &_dst, sp, sr, maxLevel, termcrit );
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}
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66
samples/cpp/meanshift_segmentation.cpp
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66
samples/cpp/meanshift_segmentation.cpp
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@ -0,0 +1,66 @@
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#include <highgui.h>
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#include "opencv2/core/core.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include <iostream>
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using namespace cv;
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using namespace std;
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void floodFillPostprocess( Mat& img, const Scalar& colorDiff=Scalar::all(1) )
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{
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CV_Assert( !img.empty() );
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RNG rng = theRNG();
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Mat mask( img.rows+2, img.cols+2, CV_8UC1, Scalar::all(0) );
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for( int y = 0; y < img.rows; y++ )
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{
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for( int x = 0; x < img.cols; x++ )
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{
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if( mask.at<uchar>(y+1, x+1) == 0 )
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{
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Scalar newVal( rng(256), rng(256), rng(256) );
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floodFill( img, mask, Point(x,y), newVal, 0, colorDiff, colorDiff );
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}
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}
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}
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}
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string winName = "meanshift";
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int spatialRad, colorRad, maxPyrLevel;
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Mat img, res;
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void meanShiftSegmentation( int, void* )
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{
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cout << "spatialRad=" << spatialRad << "; "
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<< "colorRad=" << colorRad << "; "
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<< "maxPyrLevel=" << maxPyrLevel << endl;
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pyrMeanShiftFiltering( img, res, spatialRad, colorRad, maxPyrLevel );
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floodFillPostprocess( res, Scalar::all(2) );
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imshow( winName, res );
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}
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int main(int argc, char** argv)
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{
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if( argc !=2 )
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{
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cout << "Format:" << endl << argv[0] << " image" << endl;
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return -1;
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}
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img = imread( argv[1] );
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if( img.empty() )
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return -1;
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spatialRad = 10;
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colorRad = 10;
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maxPyrLevel = 1;
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namedWindow( winName, CV_WINDOW_AUTOSIZE );
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createTrackbar( "spatialRad", winName, &spatialRad, 80, meanShiftSegmentation );
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createTrackbar( "colorRad", winName, &colorRad, 60, meanShiftSegmentation );
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createTrackbar( "maxPyrLevel", winName, &maxPyrLevel, 5, meanShiftSegmentation );
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meanShiftSegmentation(0, 0);
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waitKey();
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return 0;
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}
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