309 lines
10 KiB
C++
309 lines
10 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "cxcoretest.h"
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using namespace cv;
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#define CHECK_C
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Size sz( 200, 500);
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class CV_PCATest : public CvTest
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{
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public:
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CV_PCATest() : CvTest( "pca", "PCA funcs" ) {}
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protected:
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void run( int);
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};
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#if 0
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void CV_PCATest::run( int )
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{
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int code = CvTS::OK, err;
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int maxComponents = 1;
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Mat points( 1000, 3, CV_32FC1);
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RNG rng = *ts->get_rng(); // get ts->rng seed
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rng.fill( points, RNG::NORMAL, Scalar::all(0.0), Scalar::all(1.0) );
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float mp[] = { 3.0f, 3.0f, 3.0f }, cp[] = { 0.5f, 0.0f, 0.0f,
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0.0f, 1.0f, 0.0f,
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0.0f, 0.0f, 0.3f };
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Mat mean( 1, 3, CV_32FC1, mp ),
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cov( 3, 3, CV_32FC1, cp );
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for( int i = 0; i < points.rows; i++ )
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{
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Mat r(1, points.cols, CV_32FC1, points.ptr<float>(i));
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r = r * cov + mean;
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}
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PCA pca( points, Mat(), CV_PCA_DATA_AS_ROW, maxComponents );
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// check project
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Mat prjPoints = pca.project( points );
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err = 0;
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for( int i = 0; i < prjPoints.rows; i++ )
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{
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float val = prjPoints.at<float>(i,0);
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if( val > 3.0f || val < -3.0f )
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err++;
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}
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float projectErr = 0.02f;
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if( (float)err > prjPoints.rows * projectErr )
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{
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ts->printf( CvTS::LOG, "bad accuracy of project() (real = %f, permissible = %f)",
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(float)err/(float)prjPoints.rows, projectErr );
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code = CvTS::FAIL_BAD_ACCURACY;
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}
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// check backProject
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Mat points1 = pca.backProject( prjPoints );
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err = 0;
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for( int i = 0; i < points.rows; i++ )
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{
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if( fabs(points1.at<float>(i,0) - mean.at<float>(0,0)) > 0.15 ||
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fabs(points1.at<float>(i,1) - points.at<float>(i,1)) > 0.05 ||
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fabs(points1.at<float>(i,2) - mean.at<float>(0,2)) > 0.15 )
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err++;
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}
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float backProjectErr = 0.05f;
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if( (float)err > prjPoints.rows*backProjectErr )
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{
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ts->printf( CvTS::LOG, "bad accuracy of backProject() (real = %f, permissible = %f)",
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(float)err/(float)prjPoints.rows, backProjectErr );
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code = CvTS::FAIL_BAD_ACCURACY;
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}
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CvRNG *oldRng = ts->get_rng(); // set ts->rng seed
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*oldRng = rng.state;
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ts->set_failed_test_info( code );
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}
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#else
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void CV_PCATest::run( int )
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{
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int code = CvTS::OK;
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double diffPrjEps, diffBackPrjEps,
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prjEps, backPrjEps,
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evalEps, evecEps;
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int maxComponents = 100;
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Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);
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RNG rng = *ts->get_rng();
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rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
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rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
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PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;
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// 1. check C++ PCA & ROW
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Mat rPrjTestPoints = rPCA.project( rTestPoints );
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Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
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Mat avg(1, sz.width, CV_32FC1 );
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reduce( rPoints, avg, 0, CV_REDUCE_AVG );
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Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
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Q = Qt * Q;
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Q = Q /(float)rPoints.rows;
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eigen( Q, eval, evec );
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/*SVD svd(Q);
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evec = svd.vt;
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eval = svd.w;*/
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Mat subEval( maxComponents, 1, eval.type(), eval.data ),
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subEvec( maxComponents, evec.cols, evec.type(), evec.data );
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#ifdef CHECK_C
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Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();
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CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;
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#endif
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// check eigen()
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double eigenEps = 1e-6;
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double err;
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for(int i = 0; i < Q.rows; i++ )
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{
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Mat v = evec.row(i).t();
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Mat Qv = Q * v;
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Mat lv = eval.at<float>(i,0) * v;
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err = norm( Qv, lv );
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if( err > eigenEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of eigen(); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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}
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// check pca eigenvalues
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evalEps = 1e-6, evecEps = 1;
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err = norm( rPCA.eigenvalues, subEval );
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if( err > evalEps )
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{
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ts->printf( CvTS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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// check pca eigenvectors
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err = norm( rPCA.eigenvectors, subEvec, CV_RELATIVE_L2 );
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if( err > evecEps )
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{
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ts->printf( CvTS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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prjEps = 1.265, backPrjEps = 1.265;
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for( int i = 0; i < rTestPoints.rows; i++ )
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{
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// check pca project
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Mat subEvec_t = subEvec.t();
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Mat prj = rTestPoints.row(i) - avg; prj *= subEvec_t;
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err = norm(rPrjTestPoints.row(i), prj, CV_RELATIVE_L2);
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if( err > prjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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// check pca backProject
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Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;
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err = norm( rBackPrjTestPoints.row(i), backPrj, CV_RELATIVE_L2 );
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if( err > backPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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}
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// 2. check C++ PCA & COL
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cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
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diffPrjEps = 1, diffBackPrjEps = 1;
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err = norm(cPCA.project(rTestPoints.t()), rPrjTestPoints.t(), CV_RELATIVE_L2 );
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if( err > diffPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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err = norm(cPCA.backProject(rPrjTestPoints.t()), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );
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if( err > diffBackPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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#ifdef CHECK_C
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// 3. check C PCA & ROW
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_points = rPoints;
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_testPoints = rTestPoints;
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_avg = avg;
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_eval = eval;
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_evec = evec;
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prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );
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backPrjTestPoints.create(rPoints.size(), rPoints.type() );
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_prjTestPoints = prjTestPoints;
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_backPrjTestPoints = backPrjTestPoints;
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cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
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cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
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cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
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err = norm(prjTestPoints, rPrjTestPoints, CV_RELATIVE_L2);
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if( err > diffPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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err = norm(backPrjTestPoints, rBackPrjTestPoints, CV_RELATIVE_L2);
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if( err > diffBackPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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// 3. check C PCA & COL
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_points = cPoints;
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_testPoints = cTestPoints;
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avg = avg.t(); _avg = avg;
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eval = eval.t(); _eval = eval;
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evec = evec.t(); _evec = evec;
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prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
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backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
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cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
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cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
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cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
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err = norm(prjTestPoints, rPrjTestPoints.t(), CV_RELATIVE_L2 );
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if( err > diffPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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err = norm(backPrjTestPoints, rBackPrjTestPoints.t(), CV_RELATIVE_L2);
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if( err > diffBackPrjEps )
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{
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ts->printf( CvTS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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code = CvTS::FAIL_BAD_ACCURACY;
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goto exit_func;
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}
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#endif
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exit_func:
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CvRNG* _rng = ts->get_rng();
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*_rng = rng.state;
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ts->set_failed_test_info( code );
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}
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#endif
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CV_PCATest pca_test;
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