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/*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 "test_precomp.hpp"
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using namespace cv;
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using namespace std;
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class CV_PyrSegmentationTest : public cvtest::BaseTest
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{
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public:
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CV_PyrSegmentationTest();
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protected:
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void run(int);
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};
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#define SCAN 0
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CV_PyrSegmentationTest::CV_PyrSegmentationTest()
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{
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}
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void CV_PyrSegmentationTest::run( int /*start_from*/ )
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{
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Mat _image_f, _image, _image_s;
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const int level = 5;
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const double range = 15;
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int code = cvtest::TS::OK;
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CvPoint _cp[] ={ CvPoint(33,33), CvPoint(43,33), CvPoint(43,43), CvPoint(33,43)};
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CvPoint _cp2[] ={CvPoint(50,50), CvPoint(70,50), CvPoint(70,70), CvPoint(50,70)};
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CvPoint* cp = _cp;
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CvPoint* cp2 = _cp2;
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CvConnectedComp *dst_comp[3];
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CvRect rect[3] = {CvRect(50,50,21,21), CvRect(0,0,128,128), CvRect(33,33,11,11)};
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double a[3] = {441.0, 15822.0, 121.0};
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/* ippiPoint cp3[] ={130,130, 150,130, 150,150, 130,150}; */
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/* CvPoint cp[] ={0,0, 5,5, 5,0, 10,5, 10,0, 15,5, 15,0}; */
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int nPoints = 4;
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int block_size = 1000;
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CvMemStorage *storage; /* storage for connected component writing */
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CvSeq *comp;
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RNG& rng = ts->get_rng();
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int i, j, iter;
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IplImage *image, *image_f, *image_s;
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CvSize size(128, 128);
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const int threshold1 = 50, threshold2 = 50;
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rect[1].width = size.width;
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rect[1].height = size.height;
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a[1] = size.width*size.height - a[0] - a[2];
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OPENCV_CALL( storage = cvCreateMemStorage( block_size ) );
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for( iter = 0; iter < 2; iter++ )
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{
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int channels = iter == 0 ? 1 : 3;
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int mask[] = {0,0,0};
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image = cvCreateImage(size, 8, channels );
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image_s = cvCloneImage( image );
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image_f = cvCloneImage( image );
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if( channels == 1 )
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{
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int color1 = 30, color2 = 110, color3 = 190;
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cvSet( image, cvScalarAll(color1));
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cvFillPoly( image, &cp, &nPoints, 1, cvScalar(color2));
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cvFillPoly( image, &cp2, &nPoints, 1, cvScalar(color3));
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}
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else
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{
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CvScalar color1 = CV_RGB(30,30,30), color2 = CV_RGB(255,0,0), color3 = CV_RGB(0,255,0);
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assert( channels == 3 );
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cvSet( image, color1 );
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cvFillPoly( image, &cp, &nPoints, 1, color2);
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cvFillPoly( image, &cp2, &nPoints, 1, color3);
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}
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_image_f = cvarrToMat(image_f);
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cvtest::randUni( rng, _image_f, cvScalarAll(0), cvScalarAll(range*2) );
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cvAddWeighted( image, 1, image_f, 1, -range, image_f );
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cvPyrSegmentation( image_f, image_s,
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storage, &comp,
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level, threshold1, threshold2 );
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if(comp->total != 3)
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{
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ts->printf( cvtest::TS::LOG,
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"The segmentation function returned %d (not 3) components\n", comp->total );
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code = cvtest::TS::FAIL_INVALID_OUTPUT;
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goto _exit_;
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}
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/* read the connected components */
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dst_comp[0] = (CvConnectedComp*)CV_GET_SEQ_ELEM( CvConnectedComp, comp, 0 );
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dst_comp[1] = (CvConnectedComp*)CV_GET_SEQ_ELEM( CvConnectedComp, comp, 1 );
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dst_comp[2] = (CvConnectedComp*)CV_GET_SEQ_ELEM( CvConnectedComp, comp, 2 );
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/*{
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for( i = 0; i < 3; i++ )
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{
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CvRect r = dst_comp[i]->rect;
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cvRectangle( image_s, cvPoint(r.x,r.y), cvPoint(r.x+r.width,r.y+r.height),
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CV_RGB(255,255,255), 3, 8, 0 );
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}
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cvNamedWindow( "test", 1 );
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cvShowImage( "test", image_s );
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cvWaitKey(0);
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}*/
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_image = cvarrToMat(image);
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_image_s = cvarrToMat(image_s);
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code = cvtest::cmpEps2( ts, _image, _image_s, 10, false, "the output image" );
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if( code < 0 )
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goto _exit_;
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for( i = 0; i < 3; i++)
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{
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for( j = 0; j < 3; j++ )
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{
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if( !mask[j] && dst_comp[i]->area == a[j] &&
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dst_comp[i]->rect.x == rect[j].x &&
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dst_comp[i]->rect.y == rect[j].y &&
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dst_comp[i]->rect.width == rect[j].width &&
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dst_comp[i]->rect.height == rect[j].height )
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{
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mask[j] = 1;
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break;
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}
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}
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if( j == 3 )
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{
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ts->printf( cvtest::TS::LOG, "The component #%d is incorrect\n", i );
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code = cvtest::TS::FAIL_BAD_ACCURACY;
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goto _exit_;
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}
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}
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cvReleaseImage(&image_f);
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cvReleaseImage(&image);
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cvReleaseImage(&image_s);
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}
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_exit_:
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cvReleaseMemStorage( &storage );
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cvReleaseImage(&image_f);
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cvReleaseImage(&image);
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cvReleaseImage(&image_s);
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if( code < 0 )
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ts->set_failed_test_info( code );
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}
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TEST(Legacy_PyrSegmentation, regression) { CV_PyrSegmentationTest test; test.safe_run(); }
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/* End of file. */
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