Shape module added


@@ -5,7 +5,7 @@
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SET(OPENCV_CPP_SAMPLES_REQUIRED_DEPS opencv_core opencv_flann opencv_imgproc
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opencv_highgui opencv_ml opencv_video opencv_objdetect opencv_photo opencv_nonfree opencv_softcascade
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opencv_features2d opencv_calib3d opencv_legacy opencv_contrib opencv_stitching opencv_videostab opencv_bioinspired)
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opencv_features2d opencv_calib3d opencv_legacy opencv_contrib opencv_stitching opencv_videostab opencv_bioinspired opencv_shape)
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ocv_check_dependencies(${OPENCV_CPP_SAMPLES_REQUIRED_DEPS})
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111
samples/cpp/shape_example.cpp
Normal file
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/*
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* shape_context.cpp -- Shape context demo for shape matching
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*/
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#include "opencv2/shape.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include <opencv2/core/utility.hpp>
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#include <iostream>
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#include <string>
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using namespace std;
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using namespace cv;
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static void help()
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{
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printf("\n"
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"This program demonstrates a method for shape comparisson based on Shape Context\n"
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"You should run the program providing a number between 1 and 20 for selecting an image in the folder shape_sample.\n"
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"Call\n"
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"./shape_example [number between 1 and 20]\n\n");
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}
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static vector<Point> simpleContour( const Mat& currentQuery, int n=300 )
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{
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vector<vector<Point> > _contoursQuery;
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vector <Point> contoursQuery;
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findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
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for (size_t border=0; border<_contoursQuery.size(); border++)
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{
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for (size_t p=0; p<_contoursQuery[border].size(); p++)
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{
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contoursQuery.push_back( _contoursQuery[border][p] );
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}
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}
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// In case actual number of points is less than n
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int dummy=0;
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for (int add=contoursQuery.size()-1; add<n; add++)
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{
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contoursQuery.push_back(contoursQuery[dummy++]); //adding dummy values
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}
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// Uniformly sampling
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random_shuffle(contoursQuery.begin(), contoursQuery.end());
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vector<Point> cont;
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for (int i=0; i<n; i++)
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{
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cont.push_back(contoursQuery[i]);
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}
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return cont;
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}
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int main(int argc, char** argv)
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{
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help();
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string path = "./shape_sample/";
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int indexQuery = 1;
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if( argc < 2 )
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{
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std::cout<<"Using first image as query."<<std::endl;
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}
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else
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{
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sscanf( argv[1], "%i", &indexQuery );
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}
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cv::Ptr <cv::ShapeContextDistanceExtractor> mysc = cv::createShapeContextDistanceExtractor();
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Size sz2Sh(300,300);
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stringstream queryName;
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queryName<<path<<indexQuery<<".png";
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Mat query=imread(queryName.str(), IMREAD_GRAYSCALE);
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Mat queryToShow;
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resize(query, queryToShow, sz2Sh);
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imshow("QUERY", queryToShow);
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moveWindow("TEST", 0,0);
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vector<Point> contQuery = simpleContour(query);
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int bestMatch;
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float bestDis=FLT_MAX;
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for ( int ii=1; ii<=20; ii++ )
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{
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if (ii==indexQuery) continue;
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waitKey(30);
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stringstream iiname;
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iiname<<path<<ii<<".png";
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cout<<"name: "<<iiname.str()<<endl;
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Mat iiIm=imread(iiname.str(), 0);
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Mat iiToShow;
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resize(iiIm, iiToShow, sz2Sh);
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imshow("TEST", iiToShow);
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moveWindow("TEST", sz2Sh.width+50,0);
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vector<Point> contii = simpleContour(iiIm);
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float dis = mysc->computeDistance( contQuery, contii );
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if ( dis<bestDis )
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{
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bestMatch = ii;
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bestDis = dis;
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}
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std::cout<<" distance between "<<queryName.str()<<" and "<<iiname.str()<<" is: "<<dis<<std::endl;
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}
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destroyWindow("TEST");
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stringstream bestname;
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bestname<<path<<bestMatch<<".png";
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Mat iiIm=imread(bestname.str(), 0);
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Mat bestToShow;
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resize(iiIm, bestToShow, sz2Sh);
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imshow("BEST MATCH", bestToShow);
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moveWindow("BEST MATCH", sz2Sh.width+50,0);
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return 0;
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}
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BIN
samples/cpp/shape_sample/1.png
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After Width: | Height: | Size: 705 B |
BIN
samples/cpp/shape_sample/10.png
Normal file
After Width: | Height: | Size: 1.0 KiB |
BIN
samples/cpp/shape_sample/11.png
Normal file
After Width: | Height: | Size: 722 B |
BIN
samples/cpp/shape_sample/12.png
Normal file
After Width: | Height: | Size: 437 B |
BIN
samples/cpp/shape_sample/13.png
Normal file
After Width: | Height: | Size: 443 B |
BIN
samples/cpp/shape_sample/14.png
Normal file
After Width: | Height: | Size: 1.8 KiB |
BIN
samples/cpp/shape_sample/15.png
Normal file
After Width: | Height: | Size: 803 B |
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samples/cpp/shape_sample/16.png
Normal file
After Width: | Height: | Size: 830 B |
BIN
samples/cpp/shape_sample/17.png
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After Width: | Height: | Size: 3.0 KiB |
BIN
samples/cpp/shape_sample/18.png
Normal file
After Width: | Height: | Size: 3.2 KiB |
BIN
samples/cpp/shape_sample/19.png
Normal file
After Width: | Height: | Size: 1.5 KiB |
BIN
samples/cpp/shape_sample/2.png
Normal file
After Width: | Height: | Size: 813 B |
BIN
samples/cpp/shape_sample/20.png
Normal file
After Width: | Height: | Size: 1.5 KiB |
BIN
samples/cpp/shape_sample/3.png
Normal file
After Width: | Height: | Size: 2.2 KiB |
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samples/cpp/shape_sample/4.png
Normal file
After Width: | Height: | Size: 2.4 KiB |
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samples/cpp/shape_sample/5.png
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After Width: | Height: | Size: 852 B |
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samples/cpp/shape_sample/6.png
Normal file
After Width: | Height: | Size: 969 B |
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samples/cpp/shape_sample/7.png
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After Width: | Height: | Size: 874 B |
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samples/cpp/shape_sample/8.png
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After Width: | Height: | Size: 851 B |
BIN
samples/cpp/shape_sample/9.png
Normal file
After Width: | Height: | Size: 1.2 KiB |
74
samples/cpp/shape_transformation.cpp
Normal file
@@ -0,0 +1,74 @@
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/*
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* shape_context.cpp -- Shape context demo for shape matching
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*/
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#include "opencv2/shape.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/features2d/features2d.hpp"
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#include "opencv2/nonfree/nonfree.hpp"
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#include <opencv2/core/utility.hpp>
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#include <iostream>
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#include <string>
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using namespace std;
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using namespace cv;
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static void help()
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{
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printf("\nThis program demonstrates how to use common interface for shape transformers\n"
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"Call\n"
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"shape_transformation [image1] [image2]\n");
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}
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int main(int argc, char** argv)
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{
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help();
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Mat img1 = imread(argv[1], IMREAD_GRAYSCALE);
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Mat img2 = imread(argv[2], IMREAD_GRAYSCALE);
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if(img1.empty() || img2.empty() || argc<2)
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{
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printf("Can't read one of the images\n");
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return -1;
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}
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// detecting keypoints
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SurfFeatureDetector detector(5000);
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vector<KeyPoint> keypoints1, keypoints2;
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detector.detect(img1, keypoints1);
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detector.detect(img2, keypoints2);
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// computing descriptors
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SurfDescriptorExtractor extractor;
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Mat descriptors1, descriptors2;
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extractor.compute(img1, keypoints1, descriptors1);
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extractor.compute(img2, keypoints2, descriptors2);
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// matching descriptors
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BFMatcher matcher(NORM_L2);
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vector<DMatch> matches;
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matcher.match(descriptors1, descriptors2, matches);
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// drawing the results
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namedWindow("matches", 1);
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Mat img_matches;
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drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches);
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imshow("matches", img_matches);
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// extract points
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vector<Point2f> pts1, pts2;
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for (size_t ii=0; ii<keypoints1.size(); ii++)
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pts1.push_back( keypoints1[ii].pt );
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for (size_t ii=0; ii<keypoints2.size(); ii++)
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pts2.push_back( keypoints2[ii].pt );
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// Apply TPS
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Ptr<ThinPlateSplineShapeTransformer> mytps = createThinPlateSplineShapeTransformer(25000); //TPS with a relaxed constraint
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mytps->estimateTransformation(pts1, pts2, matches);
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mytps->warpImage(img2, img2);
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imshow("Tranformed", img2);
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waitKey(0);
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return 0;
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}
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