288 lines
		
	
	
		
			9.3 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			288 lines
		
	
	
		
			9.3 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 "test_precomp.hpp"
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using namespace cv;
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using namespace std;
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class CV_CannyTest : public cvtest::ArrayTest
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{
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public:
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    CV_CannyTest();
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protected:
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    void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
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    double get_success_error_level( int test_case_idx, int i, int j );
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    int prepare_test_case( int test_case_idx );
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    void run_func();
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    void prepare_to_validation( int );
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    int validate_test_results( int /*test_case_idx*/ );
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    int aperture_size;
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    bool use_true_gradient;
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    double threshold1, threshold2;
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    bool test_cpp;
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};
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CV_CannyTest::CV_CannyTest()
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{
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    test_array[INPUT].push_back(NULL);
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    test_array[OUTPUT].push_back(NULL);
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    test_array[REF_OUTPUT].push_back(NULL);
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    element_wise_relative_error = true;
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    aperture_size = 0;
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    use_true_gradient = false;
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    threshold1 = threshold2 = 0;
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    test_cpp = false;
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}
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void CV_CannyTest::get_test_array_types_and_sizes( int test_case_idx,
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                                                  vector<vector<Size> >& sizes,
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                                                  vector<vector<int> >& types )
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{
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    RNG& rng = ts->get_rng();
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    double thresh_range;
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    cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
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    types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_8U;
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    aperture_size = cvtest::randInt(rng) % 2 ? 5 : 3;
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    thresh_range = aperture_size == 3 ? 300 : 1000;
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    threshold1 = cvtest::randReal(rng)*thresh_range;
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    threshold2 = cvtest::randReal(rng)*thresh_range*0.3;
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    if( cvtest::randInt(rng) % 2 )
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        CV_SWAP( threshold1, threshold2, thresh_range );
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    use_true_gradient = cvtest::randInt(rng) % 2 != 0;
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    test_cpp = (cvtest::randInt(rng) & 256) == 0;
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}
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int CV_CannyTest::prepare_test_case( int test_case_idx )
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{
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    int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
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    if( code > 0 )
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    {
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        Mat& src = test_mat[INPUT][0];
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        GaussianBlur(src, src, Size(11, 11), 5, 5);
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    }
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    return code;
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}
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double CV_CannyTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
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{
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    return 0;
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}
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void CV_CannyTest::run_func()
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{
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    if(!test_cpp)
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        cvCanny( test_array[INPUT][0], test_array[OUTPUT][0], threshold1, threshold2,
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                aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0));
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    else
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    {
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        cv::Mat _out = cv::cvarrToMat(test_array[OUTPUT][0]);
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        cv::Canny(cv::cvarrToMat(test_array[INPUT][0]), _out, threshold1, threshold2,
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                aperture_size + (use_true_gradient ? CV_CANNY_L2_GRADIENT : 0));
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    }
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}
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static void
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cannyFollow( int x, int y, float lowThreshold, const Mat& mag, Mat& dst )
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{
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    static const int ofs[][2] = {{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1},{0,1},{1,1}};
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    int i;
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    dst.at<uchar>(y, x) = (uchar)255;
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    for( i = 0; i < 8; i++ )
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    {
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        int x1 = x + ofs[i][0];
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        int y1 = y + ofs[i][1];
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        if( (unsigned)x1 < (unsigned)mag.cols &&
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            (unsigned)y1 < (unsigned)mag.rows &&
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            mag.at<float>(y1, x1) > lowThreshold &&
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            !dst.at<uchar>(y1, x1) )
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            cannyFollow( x1, y1, lowThreshold, mag, dst );
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    }
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}
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static void
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test_Canny( const Mat& src, Mat& dst,
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            double threshold1, double threshold2,
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            int aperture_size, bool use_true_gradient )
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{
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    int m = aperture_size;
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    Point anchor(m/2, m/2);
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    const double tan_pi_8 = tan(CV_PI/8.);
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    const double tan_3pi_8 = tan(CV_PI*3/8);
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    float lowThreshold = (float)MIN(threshold1, threshold2);
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    float highThreshold = (float)MAX(threshold1, threshold2);
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    int x, y, width = src.cols, height = src.rows;
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    Mat dxkernel = cvtest::calcSobelKernel2D( 1, 0, m, 0 );
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    Mat dykernel = cvtest::calcSobelKernel2D( 0, 1, m, 0 );
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    Mat dx, dy, mag(height, width, CV_32F);
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    cvtest::filter2D(src, dx, CV_16S, dxkernel, anchor, 0, BORDER_REPLICATE);
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    cvtest::filter2D(src, dy, CV_16S, dykernel, anchor, 0, BORDER_REPLICATE);
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    // calc gradient magnitude
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    for( y = 0; y < height; y++ )
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    {
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        for( x = 0; x < width; x++ )
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        {
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            int dxval = dx.at<short>(y, x), dyval = dy.at<short>(y, x);
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            mag.at<float>(y, x) = use_true_gradient ?
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                (float)sqrt((double)(dxval*dxval + dyval*dyval)) :
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                (float)(fabs((double)dxval) + fabs((double)dyval));
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        }
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    }
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    // calc gradient direction, do nonmaxima suppression
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    for( y = 0; y < height; y++ )
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    {
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        for( x = 0; x < width; x++ )
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        {
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            float a = mag.at<float>(y, x), b = 0, c = 0;
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            int y1 = 0, y2 = 0, x1 = 0, x2 = 0;
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            if( a <= lowThreshold )
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                continue;
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            int dxval = dx.at<short>(y, x);
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            int dyval = dy.at<short>(y, x);
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            double tg = dxval ? (double)dyval/dxval : DBL_MAX*CV_SIGN(dyval);
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            if( fabs(tg) < tan_pi_8 )
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            {
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                y1 = y2 = y; x1 = x + 1; x2 = x - 1;
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            }
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            else if( tan_pi_8 <= tg && tg <= tan_3pi_8 )
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            {
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                y1 = y + 1; y2 = y - 1; x1 = x + 1; x2 = x - 1;
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            }
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            else if( -tan_3pi_8 <= tg && tg <= -tan_pi_8 )
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            {
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                y1 = y - 1; y2 = y + 1; x1 = x + 1; x2 = x - 1;
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            }
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            else
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            {
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                assert( fabs(tg) > tan_3pi_8 );
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                x1 = x2 = x; y1 = y + 1; y2 = y - 1;
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            }
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            if( (unsigned)y1 < (unsigned)height && (unsigned)x1 < (unsigned)width )
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                b = (float)fabs(mag.at<float>(y1, x1));
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            if( (unsigned)y2 < (unsigned)height && (unsigned)x2 < (unsigned)width )
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                c = (float)fabs(mag.at<float>(y2, x2));
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            if( (a > b || (a == b && ((x1 == x+1 && y1 == y) || (x1 == x && y1 == y+1)))) && a > c )
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                ;
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            else
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                mag.at<float>(y, x) = -a;
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        }
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    }
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    dst = Scalar::all(0);
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    // hysteresis threshold
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    for( y = 0; y < height; y++ )
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    {
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        for( x = 0; x < width; x++ )
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            if( mag.at<float>(y, x) > highThreshold && !dst.at<uchar>(y, x) )
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                cannyFollow( x, y, lowThreshold, mag, dst );
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    }
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}
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void CV_CannyTest::prepare_to_validation( int )
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{
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    Mat src = test_mat[INPUT][0], dst = test_mat[REF_OUTPUT][0];
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    test_Canny( src, dst, threshold1, threshold2, aperture_size, use_true_gradient );
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}
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int CV_CannyTest::validate_test_results( int test_case_idx )
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{
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    int code = cvtest::TS::OK, nz0;
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    prepare_to_validation(test_case_idx);
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    double err = cvtest::norm(test_mat[OUTPUT][0], test_mat[REF_OUTPUT][0], CV_L1);
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    if( err == 0 )
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        return code;
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    if( err != cvRound(err) || cvRound(err)%255 != 0 )
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    {
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        ts->printf( cvtest::TS::LOG, "Some of the pixels, produced by Canny, are not 0's or 255's; the difference is %g\n", err );
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        ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
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        return code;
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    }
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    nz0 = cvRound(cvtest::norm(test_mat[REF_OUTPUT][0], CV_L1)/255);
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    err = (err/255/MAX(nz0,100))*100;
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    if( err > 1 )
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    {
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        ts->printf( cvtest::TS::LOG, "Too high percentage of non-matching edge pixels = %g%%\n", err);
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        ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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    }
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    return code;
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}
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TEST(Imgproc_Canny, accuracy) { CV_CannyTest test; test.safe_run(); }
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/* End of file. */
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