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opencv/modules/imgproc/test/test_contours.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
// 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.
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// This software is provided by the copyright holders and contributors "as is" and
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// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "test_precomp.hpp"
using namespace cv;
using namespace std;
class CV_FindContourTest : public cvtest::BaseTest
{
public:
enum { NUM_IMG = 4 };
CV_FindContourTest();
~CV_FindContourTest();
void clear();
protected:
int read_params( CvFileStorage* fs );
int prepare_test_case( int test_case_idx );
int validate_test_results( int test_case_idx );
void run_func();
int min_blob_size, max_blob_size;
int blob_count, max_log_blob_count;
int retr_mode, approx_method;
int min_log_img_size, max_log_img_size;
CvSize img_size;
int count, count2;
IplImage* img[NUM_IMG];
CvMemStorage* storage;
CvSeq *contours, *contours2, *chain;
};
CV_FindContourTest::CV_FindContourTest()
{
int i;
test_case_count = 300;
min_blob_size = 1;
max_blob_size = 50;
max_log_blob_count = 10;
min_log_img_size = 3;
max_log_img_size = 10;
for( i = 0; i < NUM_IMG; i++ )
img[i] = 0;
storage = 0;
}
CV_FindContourTest::~CV_FindContourTest()
{
clear();
}
void CV_FindContourTest::clear()
{
int i;
cvtest::BaseTest::clear();
for( i = 0; i < NUM_IMG; i++ )
cvReleaseImage( &img[i] );
cvReleaseMemStorage( &storage );
}
int CV_FindContourTest::read_params( CvFileStorage* fs )
{
int t;
int code = cvtest::BaseTest::read_params( fs );
if( code < 0 )
return code;
min_blob_size = cvReadInt( find_param( fs, "min_blob_size" ), min_blob_size );
max_blob_size = cvReadInt( find_param( fs, "max_blob_size" ), max_blob_size );
max_log_blob_count = cvReadInt( find_param( fs, "max_log_blob_count" ), max_log_blob_count );
min_log_img_size = cvReadInt( find_param( fs, "min_log_img_size" ), min_log_img_size );
max_log_img_size = cvReadInt( find_param( fs, "max_log_img_size" ), max_log_img_size );
min_blob_size = cvtest::clipInt( min_blob_size, 1, 100 );
max_blob_size = cvtest::clipInt( max_blob_size, 1, 100 );
if( min_blob_size > max_blob_size )
CV_SWAP( min_blob_size, max_blob_size, t );
max_log_blob_count = cvtest::clipInt( max_log_blob_count, 1, 10 );
min_log_img_size = cvtest::clipInt( min_log_img_size, 1, 10 );
max_log_img_size = cvtest::clipInt( max_log_img_size, 1, 10 );
if( min_log_img_size > max_log_img_size )
CV_SWAP( min_log_img_size, max_log_img_size, t );
return 0;
}
static void
cvTsGenerateBlobImage( IplImage* img, int min_blob_size, int max_blob_size,
int blob_count, int min_brightness, int max_brightness,
RNG& rng )
{
int i;
CvSize size;
assert( img->depth == IPL_DEPTH_8U && img->nChannels == 1 );
cvZero( img );
// keep the border clear
cvSetImageROI( img, cvRect(1,1,img->width-2,img->height-2) );
size = cvGetSize( img );
for( i = 0; i < blob_count; i++ )
{
CvPoint center;
CvSize axes;
int angle = cvtest::randInt(rng) % 180;
int brightness = cvtest::randInt(rng) %
(max_brightness - min_brightness) + min_brightness;
center.x = cvtest::randInt(rng) % size.width;
center.y = cvtest::randInt(rng) % size.height;
axes.width = (cvtest::randInt(rng) %
(max_blob_size - min_blob_size) + min_blob_size + 1)/2;
axes.height = (cvtest::randInt(rng) %
(max_blob_size - min_blob_size) + min_blob_size + 1)/2;
cvEllipse( img, center, axes, angle, 0, 360, cvScalar(brightness), CV_FILLED );
}
cvResetImageROI( img );
}
static void
cvTsMarkContours( IplImage* img, int val )
{
int i, j;
int step = img->widthStep;
assert( img->depth == IPL_DEPTH_8U && img->nChannels == 1 && (val&1) != 0);
for( i = 1; i < img->height - 1; i++ )
for( j = 1; j < img->width - 1; j++ )
{
uchar* t = (uchar*)(img->imageData + img->widthStep*i + j);
if( *t == 1 && (t[-step] == 0 || t[-1] == 0 || t[1] == 0 || t[step] == 0))
*t = (uchar)val;
}
cvThreshold( img, img, val - 2, val, CV_THRESH_BINARY );
}
int CV_FindContourTest::prepare_test_case( int test_case_idx )
{
RNG& rng = ts->get_rng();
const int min_brightness = 0, max_brightness = 2;
int i, code = cvtest::BaseTest::prepare_test_case( test_case_idx );
if( code < 0 )
return code;
clear();
blob_count = cvRound(exp(cvtest::randReal(rng)*max_log_blob_count*CV_LOG2));
img_size.width = cvRound(exp((cvtest::randReal(rng)*
(max_log_img_size - min_log_img_size) + min_log_img_size)*CV_LOG2));
img_size.height = cvRound(exp((cvtest::randReal(rng)*
(max_log_img_size - min_log_img_size) + min_log_img_size)*CV_LOG2));
approx_method = cvtest::randInt( rng ) % 4 + 1;
retr_mode = cvtest::randInt( rng ) % 4;
storage = cvCreateMemStorage( 1 << 10 );
for( i = 0; i < NUM_IMG; i++ )
img[i] = cvCreateImage( img_size, 8, 1 );
cvTsGenerateBlobImage( img[0], min_blob_size, max_blob_size,
blob_count, min_brightness, max_brightness, rng );
cvCopy( img[0], img[1] );
cvCopy( img[0], img[2] );
cvTsMarkContours( img[1], 255 );
return 1;
}
void CV_FindContourTest::run_func()
{
contours = contours2 = chain = 0;
count = cvFindContours( img[2], storage, &contours, sizeof(CvContour), retr_mode, approx_method );
cvZero( img[3] );
if( contours && retr_mode != CV_RETR_EXTERNAL && approx_method < CV_CHAIN_APPROX_TC89_L1 )
cvDrawContours( img[3], contours, cvScalar(255), cvScalar(255), INT_MAX, -1 );
cvCopy( img[0], img[2] );
count2 = cvFindContours( img[2], storage, &chain, sizeof(CvChain), retr_mode, CV_CHAIN_CODE );
if( chain )
contours2 = cvApproxChains( chain, storage, approx_method, 0, 0, 1 );
cvZero( img[2] );
if( contours && retr_mode != CV_RETR_EXTERNAL && approx_method < CV_CHAIN_APPROX_TC89_L1 )
cvDrawContours( img[2], contours2, cvScalar(255), cvScalar(255), INT_MAX );
}
// the whole testing is done here, run_func() is not utilized in this test
int CV_FindContourTest::validate_test_results( int /*test_case_idx*/ )
{
int code = cvtest::TS::OK;
cvCmpS( img[0], 0, img[0], CV_CMP_GT );
if( count != count2 )
{
ts->printf( cvtest::TS::LOG, "The number of contours retrieved with different "
"approximation methods is not the same\n"
"(%d contour(s) for method %d vs %d contour(s) for method %d)\n",
count, approx_method, count2, CV_CHAIN_CODE );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
}
if( retr_mode != CV_RETR_EXTERNAL && approx_method < CV_CHAIN_APPROX_TC89_L1 )
{
Mat _img[4];
for( int i = 0; i < 4; i++ )
_img[i] = cvarrToMat(img[i]);
code = cvtest::cmpEps2(ts, _img[0], _img[3], 0, true, "Comparing original image with the map of filled contours" );
if( code < 0 )
goto _exit_;
code = cvtest::cmpEps2( ts, _img[1], _img[2], 0, true,
"Comparing contour outline vs manually produced edge map" );
if( code < 0 )
goto _exit_;
}
if( contours )
{
CvTreeNodeIterator iterator1;
CvTreeNodeIterator iterator2;
int count3;
for(int i = 0; i < 2; i++ )
{
CvTreeNodeIterator iterator;
cvInitTreeNodeIterator( &iterator, i == 0 ? contours : contours2, INT_MAX );
for( count3 = 0; cvNextTreeNode( &iterator ) != 0; count3++ )
;
if( count3 != count )
{
ts->printf( cvtest::TS::LOG,
"The returned number of retrieved contours (using the approx_method = %d) does not match\n"
"to the actual number of contours in the tree/list (returned %d, actual %d)\n",
i == 0 ? approx_method : 0, count, count3 );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
goto _exit_;
}
}
cvInitTreeNodeIterator( &iterator1, contours, INT_MAX );
cvInitTreeNodeIterator( &iterator2, contours2, INT_MAX );
for( count3 = 0; count3 < count; count3++ )
{
CvSeq* seq1 = (CvSeq*)cvNextTreeNode( &iterator1 );
CvSeq* seq2 = (CvSeq*)cvNextTreeNode( &iterator2 );
CvSeqReader reader1;
CvSeqReader reader2;
if( !seq1 || !seq2 )
{
ts->printf( cvtest::TS::LOG,
"There are NULL pointers in the original contour tree or the "
"tree produced by cvApproxChains\n" );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
goto _exit_;
}
cvStartReadSeq( seq1, &reader1 );
cvStartReadSeq( seq2, &reader2 );
if( seq1->total != seq2->total )
{
ts->printf( cvtest::TS::LOG,
"The original contour #%d has %d points, while the corresponding contour has %d point\n",
count3, seq1->total, seq2->total );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
goto _exit_;
}
for(int i = 0; i < seq1->total; i++ )
{
CvPoint pt1;
CvPoint pt2;
CV_READ_SEQ_ELEM( pt1, reader1 );
CV_READ_SEQ_ELEM( pt2, reader2 );
if( pt1.x != pt2.x || pt1.y != pt2.y )
{
ts->printf( cvtest::TS::LOG,
"The point #%d in the contour #%d is different from the corresponding point "
"in the approximated chain ((%d,%d) vs (%d,%d)", count3, i, pt1.x, pt1.y, pt2.x, pt2.y );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
goto _exit_;
}
}
}
}
_exit_:
if( code < 0 )
{
#if 0
cvNamedWindow( "test", 0 );
cvShowImage( "test", img[0] );
cvWaitKey();
#endif
ts->set_failed_test_info( code );
}
return code;
}
TEST(Imgproc_FindContours, accuracy) { CV_FindContourTest test; test.safe_run(); }
TEST(Core_Drawing, _914)
{
const int rows = 256;
const int cols = 256;
Mat img(rows, cols, CV_8UC1, Scalar(255));
line(img, Point(0, 10), Point(255, 10), Scalar(0), 2, 4);
line(img, Point(-5, 20), Point(260, 20), Scalar(0), 2, 4);
line(img, Point(10, 0), Point(10, 255), Scalar(0), 2, 4);
double x0 = 0.0/pow(2.0, -2.0);
double x1 = 255.0/pow(2.0, -2.0);
double y = 30.5/pow(2.0, -2.0);
line(img, Point(int(x0), int(y)), Point(int(x1), int(y)), Scalar(0), 2, 4, 2);
int pixelsDrawn = rows*cols - countNonZero(img);
ASSERT_EQ( (3*rows + cols)*3 - 3*9, pixelsDrawn);
}
TEST(Core_Drawing, polylines_empty)
{
Mat img(100, 100, CV_8UC1, Scalar(0));
vector<Point> pts; // empty
polylines(img, pts, false, Scalar(255));
int cnt = countNonZero(img);
ASSERT_EQ(cnt, 0);
}
TEST(Core_Drawing, polylines)
{
Mat img(100, 100, CV_8UC1, Scalar(0));
vector<Point> pts;
pts.push_back(Point(0, 0));
pts.push_back(Point(20, 0));
polylines(img, pts, false, Scalar(255));
int cnt = countNonZero(img);
ASSERT_EQ(cnt, 21);
}
/* End of file. */
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