+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "test_precomp.hpp"
-
-using namespace cv;
-using namespace std;
-
-const int angularBins=12;
-const int radialBins=4;
-const float minRad=0.2f;
-const float maxRad=2;
-const int NSN=5;//10;//20; //number of shapes per class
-const int NP=100; //number of points sympliying the contour
-const float CURRENT_MAX_ACCUR=95; //98% and 99% reached in several tests, 95 is fixed as minimum boundary
-
-class CV_ShapeEMDTest : public cvtest::BaseTest
-{
-public:
- CV_ShapeEMDTest();
- ~CV_ShapeEMDTest();
-protected:
- void run(int);
-
-private:
- void mpegTest();
- void listShapeNames(vector<string> &listHeaders);
- vector<Point2f> convertContourType(const Mat &, int n=0 );
- float computeShapeDistance(vector <Point2f>& queryNormal,
- vector <Point2f>& queryFlipped1,
- vector <Point2f>& queryFlipped2,
- vector<Point2f>& testq);
- void displayMPEGResults();
-};
-
-CV_ShapeEMDTest::CV_ShapeEMDTest()
-{
-}
-CV_ShapeEMDTest::~CV_ShapeEMDTest()
-{
-}
-
-vector <Point2f> CV_ShapeEMDTest::convertContourType(const Mat& currentQuery, int n)
-{
- vector<vector<Point> > _contoursQuery;
- vector <Point2f> contoursQuery;
- findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
- for (size_t border=0; border<_contoursQuery.size(); border++)
- {
- for (size_t p=0; p<_contoursQuery[border].size(); p++)
- {
- contoursQuery.push_back(Point2f((float)_contoursQuery[border][p].x,
- (float)_contoursQuery[border][p].y));
- }
- }
-
- // In case actual number of points is less than n
- int dum=0;
- for (int add=(int)contoursQuery.size()-1; add<n; add++)
- {
- contoursQuery.push_back(contoursQuery[dum++]); //adding dummy values
- }
-
- // Uniformly sampling
- random_shuffle(contoursQuery.begin(), contoursQuery.end());
- int nStart=n;
- vector<Point2f> cont;
- for (int i=0; i<nStart; i++)
- {
- cont.push_back(contoursQuery[i]);
- }
- return cont;
-}
-
-void CV_ShapeEMDTest::listShapeNames( vector<string> &listHeaders)
-{
- listHeaders.push_back("apple"); //ok
- listHeaders.push_back("children"); // ok
- listHeaders.push_back("device7"); // ok
- listHeaders.push_back("Heart"); // ok
- listHeaders.push_back("teddy"); // ok
-}
-float CV_ShapeEMDTest::computeShapeDistance(vector <Point2f>& query1, vector <Point2f>& query2,
- vector <Point2f>& query3, vector <Point2f>& testq)
-{
- //waitKey(0);
- Ptr <ShapeContextDistanceExtractor> mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad);
- //Ptr <HistogramCostExtractor> cost = createNormHistogramCostExtractor(cv::DIST_L1);
- //Ptr <HistogramCostExtractor> cost = createChiHistogramCostExtractor(30,0.15);
- //Ptr <HistogramCostExtractor> cost = createEMDHistogramCostExtractor();
- // Ptr <HistogramCostExtractor> cost = createEMDL1HistogramCostExtractor();
- mysc->setIterations(1); //(3)
- mysc->setCostExtractor( createEMDL1HistogramCostExtractor() );
- //mysc->setTransformAlgorithm(createAffineTransformer(true));
- mysc->setTransformAlgorithm( createThinPlateSplineShapeTransformer() );
- //mysc->setImageAppearanceWeight(1.6);
- //mysc->setImageAppearanceWeight(0.0);
- //mysc->setImages(im1,imtest);
- return ( std::min( mysc->computeDistance(query1, testq),
- std::min(mysc->computeDistance(query2, testq), mysc->computeDistance(query3, testq) )));
-}
-
-void CV_ShapeEMDTest::mpegTest()
-{
- string baseTestFolder="shape/mpeg_test/";
- string path = cvtest::TS::ptr()->get_data_path() + baseTestFolder;
- vector<string> namesHeaders;
- listShapeNames(namesHeaders);
-
- // distance matrix //
- Mat distanceMat=Mat::zeros(NSN*(int)namesHeaders.size(), NSN*(int)namesHeaders.size(), CV_32F);
-
- // query contours (normal v flipped, h flipped) and testing contour //
- vector<Point2f> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
-
- // reading query and computing its properties //
- int counter=0;
- const int loops=NSN*(int)namesHeaders.size()*NSN*(int)namesHeaders.size();
- for (size_t n=0; n<namesHeaders.size(); n++)
- {
- for (int i=1; i<=NSN; i++)
- {
- // read current image //
- stringstream thepathandname;
- thepathandname<<path+namesHeaders[n]<<"-"<<i<<".png";
- Mat currentQuery, flippedHQuery, flippedVQuery;
- currentQuery=imread(thepathandname.str(), IMREAD_GRAYSCALE);
- flip(currentQuery, flippedHQuery, 0);
- flip(currentQuery, flippedVQuery, 1);
- // compute border of the query and its flipped versions //
- vector<Point2f> origContour;
- contoursQuery1=convertContourType(currentQuery, NP);
- origContour=contoursQuery1;
- contoursQuery2=convertContourType(flippedHQuery, NP);
- contoursQuery3=convertContourType(flippedVQuery, NP);
-
- // compare with all the rest of the images: testing //
- for (size_t nt=0; nt<namesHeaders.size(); nt++)
- {
- for (int it=1; it<=NSN; it++)
- {
- // skip self-comparisson //
- counter++;
- if (nt==n && it==i)
- {
- distanceMat.at<float>(NSN*(int)n+i-1,
- NSN*(int)nt+it-1)=0;
- continue;
- }
- // read testing image //
- stringstream thetestpathandname;
- thetestpathandname<<path+namesHeaders[nt]<<"-"<<it<<".png";
- Mat currentTest;
- currentTest=imread(thetestpathandname.str().c_str(), 0);
- // compute border of the testing //
- contoursTesting=convertContourType(currentTest, NP);
-
- // compute shape distance //
- std::cout<<std::endl<<"Progress: "<<counter<<"/"<<loops<<": "<<100*double(counter)/loops<<"% *******"<<std::endl;
- std::cout<<"Computing shape distance between "<<namesHeaders[n]<<i<<
- " and "<<namesHeaders[nt]<<it<<": ";
- distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)=
- computeShapeDistance(contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting);
- std::cout<<distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)<<std::endl;
- }
- }
- }
- }
- // save distance matrix //
- FileStorage fs(cvtest::TS::ptr()->get_data_path() + baseTestFolder + "distanceMatrixMPEGTest.yml", FileStorage::WRITE);
- fs << "distanceMat" << distanceMat;
-}
-
-const int FIRST_MANY=2*NSN;
-void CV_ShapeEMDTest::displayMPEGResults()
-{
- string baseTestFolder="shape/mpeg_test/";
- Mat distanceMat;
- FileStorage fs(cvtest::TS::ptr()->get_data_path() + baseTestFolder + "distanceMatrixMPEGTest.yml", FileStorage::READ);
- vector<string> namesHeaders;
- listShapeNames(namesHeaders);
-
- // Read generated MAT //
- fs["distanceMat"]>>distanceMat;
-
- int corrects=0;
- int divi=0;
- for (int row=0; row<distanceMat.rows; row++)
- {
- if (row%NSN==0) //another group
- {
- divi+=NSN;
- }
- for (int col=divi-NSN; col<divi; col++)
- {
- int nsmall=0;
- for (int i=0; i<distanceMat.cols; i++)
- {
- if (distanceMat.at<float>(row,col)>distanceMat.at<float>(row,i))
- {
- nsmall++;
- }
- }
- if (nsmall<=FIRST_MANY)
- {
- corrects++;
- }
- }
- }
- float porc = 100*float(corrects)/(NSN*distanceMat.rows);
- std::cout<<"%="<<porc<<std::endl;
- if (porc >= CURRENT_MAX_ACCUR)
- ts->set_failed_test_info(cvtest::TS::OK);
- else
- ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
-
-}
-
-void CV_ShapeEMDTest::run( int /*start_from*/ )
-{
- mpegTest();
- displayMPEGResults();
-}
-
-TEST(ShapeEMD_SCD, regression) { CV_ShapeEMDTest test; test.safe_run(); }
+++ /dev/null
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-// By downloading, copying, installing or using the software you agree to this license.
-// If you do not agree to this license, do not download, install,
-// copy or use the software.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-// * Redistribution's of source code must retain the above copyright notice,
-// this list of conditions and the following disclaimer.
-//
-// * Redistribution's in binary form must reproduce the above copyright notice,
-// this list of conditions and the following disclaimer in the documentation
-// and/or other materials provided with the distribution.
-//
-// * The name of Intel Corporation may not be used to endorse or promote products
-// derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "test_precomp.hpp"
-#include <stdlib.h>
-
-using namespace cv;
-using namespace std;
-
-const int NSN=5;//10;//20; //number of shapes per class
-const float CURRENT_MAX_ACCUR=85; //90% and 91% reached in several tests, 85 is fixed as minimum boundary
-
-class CV_HaussTest : public cvtest::BaseTest
-{
-public:
- CV_HaussTest();
- ~CV_HaussTest();
-protected:
- void run(int);
-private:
- float computeShapeDistance(vector<Point> &query1, vector<Point> &query2,
- vector<Point> &query3, vector<Point> &testq);
- vector <Point> convertContourType(const Mat& currentQuery, int n=180);
- vector<Point2f> normalizeContour(const vector <Point>& contour);
- void listShapeNames( vector<string> &listHeaders);
- void mpegTest();
- void displayMPEGResults();
-};
-
-CV_HaussTest::CV_HaussTest()
-{
-}
-CV_HaussTest::~CV_HaussTest()
-{
-}
-
-vector<Point2f> CV_HaussTest::normalizeContour(const vector<Point> &contour)
-{
- vector<Point2f> output(contour.size());
- Mat disMat((int)contour.size(),(int)contour.size(),CV_32F);
- Point2f meanpt(0,0);
- float meanVal=1;
-
- for (int ii=0, end1 = (int)contour.size(); ii<end1; ii++)
- {
- for (int jj=0, end2 = (int)contour.size(); end2; jj++)
- {
- if (ii==jj) disMat.at<float>(ii,jj)=0;
- else
- {
- disMat.at<float>(ii,jj)=
- float(fabs(double(contour[ii].x*contour[jj].x)))+float(fabs(double(contour[ii].y*contour[jj].y)));
- }
- }
- meanpt.x+=contour[ii].x;
- meanpt.y+=contour[ii].y;
- }
- meanpt.x/=contour.size();
- meanpt.y/=contour.size();
- meanVal=float(cv::mean(disMat)[0]);
- for (size_t ii=0; ii<contour.size(); ii++)
- {
- output[ii].x = (contour[ii].x-meanpt.x)/meanVal;
- output[ii].y = (contour[ii].y-meanpt.y)/meanVal;
- }
- return output;
-}
-
-void CV_HaussTest::listShapeNames( vector<string> &listHeaders)
-{
- listHeaders.push_back("apple"); //ok
- listHeaders.push_back("children"); // ok
- listHeaders.push_back("device7"); // ok
- listHeaders.push_back("Heart"); // ok
- listHeaders.push_back("teddy"); // ok
-}
-
-
-vector <Point> CV_HaussTest::convertContourType(const Mat& currentQuery, int n)
-{
- vector<vector<Point> > _contoursQuery;
- vector <Point> contoursQuery;
- findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
- for (size_t border=0; border<_contoursQuery.size(); border++)
- {
- for (size_t p=0; p<_contoursQuery[border].size(); p++)
- {
- contoursQuery.push_back(_contoursQuery[border][p]);
- }
- }
-
- // In case actual number of points is less than n
- for (int add=(int)contoursQuery.size()-1; add<n; add++)
- {
- contoursQuery.push_back(contoursQuery[contoursQuery.size()-add+1]); //adding dummy values
- }
-
- // Uniformly sampling
- random_shuffle(contoursQuery.begin(), contoursQuery.end());
- int nStart=n;
- vector<Point> cont;
- for (int i=0; i<nStart; i++)
- {
- cont.push_back(contoursQuery[i]);
- }
- return cont;
-}
-
-float CV_HaussTest::computeShapeDistance(vector <Point>& query1, vector <Point>& query2,
- vector <Point>& query3, vector <Point>& testq)
-{
- Ptr <HausdorffDistanceExtractor> haus = createHausdorffDistanceExtractor();
- return std::min(haus->computeDistance(query1,testq), std::min(haus->computeDistance(query2,testq),
- haus->computeDistance(query3,testq)));
-}
-
-void CV_HaussTest::mpegTest()
-{
- string baseTestFolder="shape/mpeg_test/";
- string path = cvtest::TS::ptr()->get_data_path() + baseTestFolder;
- vector<string> namesHeaders;
- listShapeNames(namesHeaders);
-
- // distance matrix //
- Mat distanceMat=Mat::zeros(NSN*(int)namesHeaders.size(), NSN*(int)namesHeaders.size(), CV_32F);
-
- // query contours (normal v flipped, h flipped) and testing contour //
- vector<Point> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
-
- // reading query and computing its properties //
- int counter=0;
- const int loops=NSN*(int)namesHeaders.size()*NSN*(int)namesHeaders.size();
- for (size_t n=0; n<namesHeaders.size(); n++)
- {
- for (int i=1; i<=NSN; i++)
- {
- // read current image //
- stringstream thepathandname;
- thepathandname<<path+namesHeaders[n]<<"-"<<i<<".png";
- Mat currentQuery, flippedHQuery, flippedVQuery;
- currentQuery=imread(thepathandname.str(), IMREAD_GRAYSCALE);
- flip(currentQuery, flippedHQuery, 0);
- flip(currentQuery, flippedVQuery, 1);
- // compute border of the query and its flipped versions //
- vector<Point> origContour;
- contoursQuery1=convertContourType(currentQuery);
- origContour=contoursQuery1;
- contoursQuery2=convertContourType(flippedHQuery);
- contoursQuery3=convertContourType(flippedVQuery);
-
- // compare with all the rest of the images: testing //
- for (size_t nt=0; nt<namesHeaders.size(); nt++)
- {
- for (int it=1; it<=NSN; it++)
- {
- /* skip self-comparisson */
- counter++;
- if (nt==n && it==i)
- {
- distanceMat.at<float>(NSN*(int)n+i-1,
- NSN*(int)nt+it-1)=0;
- continue;
- }
- // read testing image //
- stringstream thetestpathandname;
- thetestpathandname<<path+namesHeaders[nt]<<"-"<<it<<".png";
- Mat currentTest;
- currentTest=imread(thetestpathandname.str().c_str(), 0);
-
- // compute border of the testing //
- contoursTesting=convertContourType(currentTest);
-
- // compute shape distance //
- std::cout<<std::endl<<"Progress: "<<counter<<"/"<<loops<<": "<<100*double(counter)/loops<<"% *******"<<std::endl;
- std::cout<<"Computing shape distance between "<<namesHeaders[n]<<i<<
- " and "<<namesHeaders[nt]<<it<<": ";
- distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)=
- computeShapeDistance(contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting);
- std::cout<<distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)<<std::endl;
- }
- }
- }
- }
- // save distance matrix //
- FileStorage fs(cvtest::TS::ptr()->get_data_path() + baseTestFolder + "distanceMatrixMPEGTest.yml", FileStorage::WRITE);
- fs << "distanceMat" << distanceMat;
-}
-
-const int FIRST_MANY=2*NSN;
-void CV_HaussTest::displayMPEGResults()
-{
- string baseTestFolder="shape/mpeg_test/";
- Mat distanceMat;
- FileStorage fs(cvtest::TS::ptr()->get_data_path() + baseTestFolder + "distanceMatrixMPEGTest.yml", FileStorage::READ);
- vector<string> namesHeaders;
- listShapeNames(namesHeaders);
-
- // Read generated MAT //
- fs["distanceMat"]>>distanceMat;
-
- int corrects=0;
- int divi=0;
- for (int row=0; row<distanceMat.rows; row++)
- {
- if (row%NSN==0) //another group
- {
- divi+=NSN;
- }
- for (int col=divi-NSN; col<divi; col++)
- {
- int nsmall=0;
- for (int i=0; i<distanceMat.cols; i++)
- {
- if (distanceMat.at<float>(row,col)>distanceMat.at<float>(row,i))
- {
- nsmall++;
- }
- }
- if (nsmall<=FIRST_MANY)
- {
- corrects++;
- }
- }
- }
- float porc = 100*float(corrects)/(NSN*distanceMat.rows);
- std::cout<<"%="<<porc<<std::endl;
- if (porc >= CURRENT_MAX_ACCUR)
- ts->set_failed_test_info(cvtest::TS::OK);
- else
- ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
-
-}
-
-
-void CV_HaussTest::run(int /* */)
-{
- mpegTest();
- displayMPEGResults();
- ts->set_failed_test_info(cvtest::TS::OK);
-}
-
-TEST(Hauss, regression) { CV_HaussTest test; test.safe_run(); }
+++ /dev/null
-#include "test_precomp.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/shape.hpp"
-#include "opencv2/opencv_modules.hpp"
-
#endif
using namespace cv;
using namespace std;
-const int angularBins=12;
-const int radialBins=4;
-const float minRad=0.2f;
-const float maxRad=2;
-const int NSN=5;//10;//20; //number of shapes per class
-const int NP=120; //number of points sympliying the contour
-const float CURRENT_MAX_ACCUR=95; //99% and 100% reached in several tests, 95 is fixed as minimum boundary
-
-class CV_ShapeTest : public cvtest::BaseTest
+template <typename T, typename compute>
+class ShapeBaseTest : public cvtest::BaseTest
{
public:
- CV_ShapeTest();
- ~CV_ShapeTest();
-protected:
- void run(int);
-
-private:
- void mpegTest();
- void listShapeNames(vector<string> &listHeaders);
- vector<Point2f> convertContourType(const Mat &, int n=0 );
- float computeShapeDistance(vector <Point2f>& queryNormal,
- vector <Point2f>& queryFlipped1,
- vector <Point2f>& queryFlipped2,
- vector<Point2f>& testq);
- void displayMPEGResults();
-};
-
-CV_ShapeTest::CV_ShapeTest()
-{
-}
-CV_ShapeTest::~CV_ShapeTest()
-{
-}
-
-vector <Point2f> CV_ShapeTest::convertContourType(const Mat& currentQuery, int n)
-{
- vector<vector<Point> > _contoursQuery;
- vector <Point2f> contoursQuery;
- findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
- for (size_t border=0; border<_contoursQuery.size(); border++)
+ typedef Point_<T> PointType;
+ ShapeBaseTest(int _NSN, int _NP, float _CURRENT_MAX_ACCUR)
+ : NSN(_NSN), NP(_NP), CURRENT_MAX_ACCUR(_CURRENT_MAX_ACCUR)
{
- for (size_t p=0; p<_contoursQuery[border].size(); p++)
+ // generate file list
+ vector<string> shapeNames;
+ shapeNames.push_back("apple"); //ok
+ shapeNames.push_back("children"); // ok
+ shapeNames.push_back("device7"); // ok
+ shapeNames.push_back("Heart"); // ok
+ shapeNames.push_back("teddy"); // ok
+ for (vector<string>::const_iterator i = shapeNames.begin(); i != shapeNames.end(); ++i)
{
- contoursQuery.push_back(Point2f((float)_contoursQuery[border][p].x,
- (float)_contoursQuery[border][p].y));
+ for (int j = 0; j < NSN; ++j)
+ {
+ stringstream filename;
+ filename << cvtest::TS::ptr()->get_data_path()
+ << "shape/mpeg_test/" << *i << "-" << j + 1 << ".png";
+ filenames.push_back(filename.str());
+ }
}
+ // distance matrix
+ const int totalCount = (int)filenames.size();
+ distanceMat = Mat::zeros(totalCount, totalCount, CV_32F);
}
- // In case actual number of points is less than n
- for (int add=(int)contoursQuery.size()-1; add<n; add++)
+protected:
+ void run(int)
{
- contoursQuery.push_back(contoursQuery[contoursQuery.size()-add+1]); //adding dummy values
+ mpegTest();
+ displayMPEGResults();
}
- // Uniformly sampling
- random_shuffle(contoursQuery.begin(), contoursQuery.end());
- int nStart=n;
- vector<Point2f> cont;
- for (int i=0; i<nStart; i++)
+ vector<PointType> convertContourType(const Mat& currentQuery) const
{
- cont.push_back(contoursQuery[i]);
- }
- return cont;
-}
-
-void CV_ShapeTest::listShapeNames( vector<string> &listHeaders)
-{
- listHeaders.push_back("apple"); //ok
- listHeaders.push_back("children"); // ok
- listHeaders.push_back("device7"); // ok
- listHeaders.push_back("Heart"); // ok
- listHeaders.push_back("teddy"); // ok
-}
-
-float CV_ShapeTest::computeShapeDistance(vector <Point2f>& query1, vector <Point2f>& query2,
- vector <Point2f>& query3, vector <Point2f>& testq)
-{
- //waitKey(0);
- Ptr <ShapeContextDistanceExtractor> mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad);
- //Ptr <HistogramCostExtractor> cost = createNormHistogramCostExtractor(cv::DIST_L1);
- Ptr <HistogramCostExtractor> cost = createChiHistogramCostExtractor(30,0.15f);
- //Ptr <HistogramCostExtractor> cost = createEMDHistogramCostExtractor();
- //Ptr <HistogramCostExtractor> cost = createEMDL1HistogramCostExtractor();
- mysc->setIterations(1);
- mysc->setCostExtractor( cost );
- //mysc->setTransformAlgorithm(createAffineTransformer(true));
- mysc->setTransformAlgorithm( createThinPlateSplineShapeTransformer() );
- //mysc->setImageAppearanceWeight(1.6);
- //mysc->setImageAppearanceWeight(0.0);
- //mysc->setImages(im1,imtest);
- return ( std::min( mysc->computeDistance(query1, testq),
- std::min(mysc->computeDistance(query2, testq), mysc->computeDistance(query3, testq) )));
-}
+ vector<vector<Point> > _contoursQuery;
+ findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE);
-void CV_ShapeTest::mpegTest()
-{
- string baseTestFolder="shape/mpeg_test/";
- string path = cvtest::TS::ptr()->get_data_path() + baseTestFolder;
- vector<string> namesHeaders;
- listShapeNames(namesHeaders);
+ vector <PointType> contoursQuery;
+ for (size_t border=0; border<_contoursQuery.size(); border++)
+ {
+ for (size_t p=0; p<_contoursQuery[border].size(); p++)
+ {
+ contoursQuery.push_back(PointType((T)_contoursQuery[border][p].x,
+ (T)_contoursQuery[border][p].y));
+ }
+ }
- // distance matrix //
- Mat distanceMat=Mat::zeros(NSN*(int)namesHeaders.size(), NSN*(int)namesHeaders.size(), CV_32F);
+ // In case actual number of points is less than n
+ for (int add=(int)contoursQuery.size()-1; add<NP; add++)
+ {
+ contoursQuery.push_back(contoursQuery[contoursQuery.size()-add+1]); //adding dummy values
+ }
- // query contours (normal v flipped, h flipped) and testing contour //
- vector<Point2f> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
+ // Uniformly sampling
+ random_shuffle(contoursQuery.begin(), contoursQuery.end());
+ int nStart=NP;
+ vector<PointType> cont;
+ for (int i=0; i<nStart; i++)
+ {
+ cont.push_back(contoursQuery[i]);
+ }
+ return cont;
+ }
- // reading query and computing its properties //
- int counter=0;
- const int loops=NSN*(int)namesHeaders.size()*NSN*(int)namesHeaders.size();
- for (size_t n=0; n<namesHeaders.size(); n++)
+ void mpegTest()
{
- for (int i=1; i<=NSN; i++)
+ // query contours (normal v flipped, h flipped) and testing contour
+ vector<PointType> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
+ // reading query and computing its properties
+ for (vector<string>::const_iterator a = filenames.begin(); a != filenames.end(); ++a)
{
- // read current image //
- stringstream thepathandname;
- thepathandname<<path+namesHeaders[n]<<"-"<<i<<".png";
- Mat currentQuery, flippedHQuery, flippedVQuery;
- currentQuery=imread(thepathandname.str(), IMREAD_GRAYSCALE);
- Mat currentQueryBuf=currentQuery.clone();
+ // read current image
+ int aIndex = a - filenames.begin();
+ Mat currentQuery = imread(*a, IMREAD_GRAYSCALE);
+ Mat flippedHQuery, flippedVQuery;
flip(currentQuery, flippedHQuery, 0);
flip(currentQuery, flippedVQuery, 1);
- // compute border of the query and its flipped versions //
- vector<Point2f> origContour;
- contoursQuery1=convertContourType(currentQuery, NP);
- origContour=contoursQuery1;
- contoursQuery2=convertContourType(flippedHQuery, NP);
- contoursQuery3=convertContourType(flippedVQuery, NP);
-
- // compare with all the rest of the images: testing //
- for (size_t nt=0; nt<namesHeaders.size(); nt++)
+ // compute border of the query and its flipped versions
+ contoursQuery1=convertContourType(currentQuery);
+ contoursQuery2=convertContourType(flippedHQuery);
+ contoursQuery3=convertContourType(flippedVQuery);
+ // compare with all the rest of the images: testing
+ for (vector<string>::const_iterator b = filenames.begin(); b != filenames.end(); ++b)
{
- for (int it=1; it<=NSN; it++)
+ int bIndex = b - filenames.begin();
+ float distance = 0;
+ // skip self-comparisson
+ if (a != b)
{
- // skip self-comparisson //
- counter++;
- if (nt==n && it==i)
- {
- distanceMat.at<float>(NSN*(int)n+i-1,
- NSN*(int)nt+it-1)=0;
- continue;
- }
- // read testing image //
- stringstream thetestpathandname;
- thetestpathandname<<path+namesHeaders[nt]<<"-"<<it<<".png";
- Mat currentTest;
- currentTest=imread(thetestpathandname.str().c_str(), 0);
- // compute border of the testing //
- contoursTesting=convertContourType(currentTest, NP);
-
- // compute shape distance //
- std::cout<<std::endl<<"Progress: "<<counter<<"/"<<loops<<": "<<100*double(counter)/loops<<"% *******"<<std::endl;
- std::cout<<"Computing shape distance between "<<namesHeaders[n]<<i<<
- " and "<<namesHeaders[nt]<<it<<": ";
- distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)=
- computeShapeDistance(contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting);
- std::cout<<distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)<<std::endl;
+ // read testing image
+ Mat currentTest = imread(*b, IMREAD_GRAYSCALE);
+ // compute border of the testing
+ contoursTesting=convertContourType(currentTest);
+ // compute shape distance
+ distance = cmp(contoursQuery1, contoursQuery2,
+ contoursQuery3, contoursTesting);
}
+ distanceMat.at<float>(aIndex, bIndex) = distance;
}
}
}
- // save distance matrix //
- FileStorage fs(cvtest::TS::ptr()->get_data_path() + baseTestFolder + "distanceMatrixMPEGTest.yml", FileStorage::WRITE);
- fs << "distanceMat" << distanceMat;
-}
-const int FIRST_MANY=2*NSN;
-void CV_ShapeTest::displayMPEGResults()
-{
- string baseTestFolder="shape/mpeg_test/";
- Mat distanceMat;
- FileStorage fs(cvtest::TS::ptr()->get_data_path() + baseTestFolder + "distanceMatrixMPEGTest.yml", FileStorage::READ);
- vector<string> namesHeaders;
- listShapeNames(namesHeaders);
-
- // Read generated MAT //
- fs["distanceMat"]>>distanceMat;
-
- int corrects=0;
- int divi=0;
- for (int row=0; row<distanceMat.rows; row++)
+ void displayMPEGResults()
{
- if (row%NSN==0) //another group
- {
- divi+=NSN;
- }
- for (int col=divi-NSN; col<divi; col++)
+ const int FIRST_MANY=2*NSN;
+
+ int corrects=0;
+ int divi=0;
+ for (int row=0; row<distanceMat.rows; row++)
{
- int nsmall=0;
- for (int i=0; i<distanceMat.cols; i++)
+ if (row%NSN==0) //another group
{
- if (distanceMat.at<float>(row,col)>distanceMat.at<float>(row,i))
- {
- nsmall++;
- }
+ divi+=NSN;
}
- if (nsmall<=FIRST_MANY)
+ for (int col=divi-NSN; col<divi; col++)
{
- corrects++;
+ int nsmall=0;
+ for (int i=0; i<distanceMat.cols; i++)
+ {
+ if (distanceMat.at<float>(row,col) > distanceMat.at<float>(row,i))
+ {
+ nsmall++;
+ }
+ }
+ if (nsmall<=FIRST_MANY)
+ {
+ corrects++;
+ }
}
}
+ float porc = 100*float(corrects)/(NSN*distanceMat.rows);
+ std::cout << "Test result: " << porc << "%" << std::endl;
+ if (porc >= CURRENT_MAX_ACCUR)
+ ts->set_failed_test_info(cvtest::TS::OK);
+ else
+ ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
+ }
+
+protected:
+ int NSN;
+ int NP;
+ float CURRENT_MAX_ACCUR;
+ vector<string> filenames;
+ Mat distanceMat;
+ compute cmp;
+};
+
+//------------------------------------------------------------------------
+// Test Shape_SCD.regression
+//------------------------------------------------------------------------
+
+class computeShapeDistance_Chi
+{
+ Ptr <ShapeContextDistanceExtractor> mysc;
+public:
+ computeShapeDistance_Chi()
+ {
+ const int angularBins=12;
+ const int radialBins=4;
+ const float minRad=0.2f;
+ const float maxRad=2;
+ mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad);
+ mysc->setIterations(1);
+ mysc->setCostExtractor(createChiHistogramCostExtractor(30,0.15f));
+ mysc->setTransformAlgorithm( createThinPlateSplineShapeTransformer() );
+ }
+ float operator()(vector <Point2f>& query1, vector <Point2f>& query2,
+ vector <Point2f>& query3, vector <Point2f>& testq)
+ {
+ return std::min(mysc->computeDistance(query1, testq),
+ std::min(mysc->computeDistance(query2, testq),
+ mysc->computeDistance(query3, testq)));
}
- float porc = 100*float(corrects)/(NSN*distanceMat.rows);
- std::cout<<"%="<<porc<<std::endl;
- if (porc >= CURRENT_MAX_ACCUR)
- ts->set_failed_test_info(cvtest::TS::OK);
- else
- ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
- //done
+};
+
+TEST(Shape_SCD, regression)
+{
+ const int NSN_val=5;//10;//20; //number of shapes per class
+ const int NP_val=120; //number of points simplifying the contour
+ const float CURRENT_MAX_ACCUR_val=95; //99% and 100% reached in several tests, 95 is fixed as minimum boundary
+ ShapeBaseTest<float, computeShapeDistance_Chi> test(NSN_val, NP_val, CURRENT_MAX_ACCUR_val);
+ test.safe_run();
}
-void CV_ShapeTest::run( int /*start_from*/ )
+//------------------------------------------------------------------------
+// Test ShapeEMD_SCD.regression
+//------------------------------------------------------------------------
+
+class computeShapeDistance_EMD
{
- mpegTest();
- displayMPEGResults();
- ts->set_failed_test_info(cvtest::TS::OK);
+ Ptr <ShapeContextDistanceExtractor> mysc;
+public:
+ computeShapeDistance_EMD()
+ {
+ const int angularBins=12;
+ const int radialBins=4;
+ const float minRad=0.2f;
+ const float maxRad=2;
+ mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad);
+ mysc->setIterations(1);
+ mysc->setCostExtractor( createEMDL1HistogramCostExtractor() );
+ mysc->setTransformAlgorithm( createThinPlateSplineShapeTransformer() );
+ }
+ float operator()(vector <Point2f>& query1, vector <Point2f>& query2,
+ vector <Point2f>& query3, vector <Point2f>& testq)
+ {
+ return std::min(mysc->computeDistance(query1, testq),
+ std::min(mysc->computeDistance(query2, testq),
+ mysc->computeDistance(query3, testq)));
+ }
+};
+
+TEST(ShapeEMD_SCD, regression)
+{
+ const int NSN_val=5;//10;//20; //number of shapes per class
+ const int NP_val=100; //number of points simplifying the contour
+ const float CURRENT_MAX_ACCUR_val=95; //98% and 99% reached in several tests, 95 is fixed as minimum boundary
+ ShapeBaseTest<float, computeShapeDistance_EMD> test(NSN_val, NP_val, CURRENT_MAX_ACCUR_val);
+ test.safe_run();
}
-TEST(Shape_SCD, regression) { CV_ShapeTest test; test.safe_run(); }
+//------------------------------------------------------------------------
+// Test Hauss.regression
+//------------------------------------------------------------------------
+
+class computeShapeDistance_Haussdorf
+{
+ Ptr <HausdorffDistanceExtractor> haus;
+public:
+ computeShapeDistance_Haussdorf()
+ {
+ haus = createHausdorffDistanceExtractor();
+ }
+ float operator()(vector<Point> &query1, vector<Point> &query2,
+ vector<Point> &query3, vector<Point> &testq)
+ {
+ return std::min(haus->computeDistance(query1,testq),
+ std::min(haus->computeDistance(query2,testq),
+ haus->computeDistance(query3,testq)));
+ }
+};
+
+TEST(Hauss, regression)
+{
+ const int NSN_val=5;//10;//20; //number of shapes per class
+ const int NP_val = 180; //number of points simplifying the contour
+ const float CURRENT_MAX_ACCUR_val=85; //90% and 91% reached in several tests, 85 is fixed as minimum boundary
+ ShapeBaseTest<int, computeShapeDistance_Haussdorf> test(NSN_val, NP_val, CURRENT_MAX_ACCUR_val);
+ test.safe_run();
+}
projects / platform / upstream / opencv.git / commitdiff