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