/*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" namespace opencv_test { namespace { static void Canny_reference_follow( int x, int y, float lowThreshold, const Mat& mag, Mat& dst ) { static const int ofs[][2] = {{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1},{0,1},{1,1}}; int i; dst.at(y, x) = (uchar)255; for( i = 0; i < 8; i++ ) { int x1 = x + ofs[i][0]; int y1 = y + ofs[i][1]; if( (unsigned)x1 < (unsigned)mag.cols && (unsigned)y1 < (unsigned)mag.rows && mag.at(y1, x1) > lowThreshold && !dst.at(y1, x1) ) Canny_reference_follow( x1, y1, lowThreshold, mag, dst ); } } static void Canny_reference( const Mat& src, Mat& dst, double threshold1, double threshold2, int aperture_size, bool use_true_gradient ) { dst.create(src.size(), src.type()); int m = aperture_size; Point anchor(m/2, m/2); const double tan_pi_8 = tan(CV_PI/8.); const double tan_3pi_8 = tan(CV_PI*3/8); float lowThreshold = (float)MIN(threshold1, threshold2); float highThreshold = (float)MAX(threshold1, threshold2); int x, y, width = src.cols, height = src.rows; Mat dxkernel = cvtest::calcSobelKernel2D( 1, 0, m, 0 ); Mat dykernel = cvtest::calcSobelKernel2D( 0, 1, m, 0 ); Mat dx, dy, mag(height, width, CV_32F); cvtest::filter2D(src, dx, CV_32S, dxkernel, anchor, 0, BORDER_REPLICATE); cvtest::filter2D(src, dy, CV_32S, dykernel, anchor, 0, BORDER_REPLICATE); // calc gradient magnitude for( y = 0; y < height; y++ ) { for( x = 0; x < width; x++ ) { int dxval = dx.at(y, x), dyval = dy.at(y, x); mag.at(y, x) = use_true_gradient ? (float)sqrt((double)(dxval*dxval + dyval*dyval)) : (float)(fabs((double)dxval) + fabs((double)dyval)); } } // calc gradient direction, do nonmaxima suppression for( y = 0; y < height; y++ ) { for( x = 0; x < width; x++ ) { float a = mag.at(y, x), b = 0, c = 0; int y1 = 0, y2 = 0, x1 = 0, x2 = 0; if( a <= lowThreshold ) continue; int dxval = dx.at(y, x); int dyval = dy.at(y, x); double tg = dxval ? (double)dyval/dxval : DBL_MAX*CV_SIGN(dyval); if( fabs(tg) < tan_pi_8 ) { y1 = y2 = y; x1 = x + 1; x2 = x - 1; } else if( tan_pi_8 <= tg && tg <= tan_3pi_8 ) { y1 = y + 1; y2 = y - 1; x1 = x + 1; x2 = x - 1; } else if( -tan_3pi_8 <= tg && tg <= -tan_pi_8 ) { y1 = y - 1; y2 = y + 1; x1 = x + 1; x2 = x - 1; } else { CV_Assert( fabs(tg) > tan_3pi_8 ); x1 = x2 = x; y1 = y + 1; y2 = y - 1; } if( (unsigned)y1 < (unsigned)height && (unsigned)x1 < (unsigned)width ) b = (float)fabs(mag.at(y1, x1)); if( (unsigned)y2 < (unsigned)height && (unsigned)x2 < (unsigned)width ) c = (float)fabs(mag.at(y2, x2)); if( (a > b || (a == b && ((x1 == x+1 && y1 == y) || (x1 == x && y1 == y+1)))) && a > c ) ; else mag.at(y, x) = -a; } } dst = Scalar::all(0); // hysteresis threshold for( y = 0; y < height; y++ ) { for( x = 0; x < width; x++ ) if( mag.at(y, x) > highThreshold && !dst.at(y, x) ) Canny_reference_follow( x, y, lowThreshold, mag, dst ); } } //============================================================================== // aperture, true gradient typedef testing::TestWithParam> Canny_Modes; TEST_P(Canny_Modes, accuracy) { const int aperture = get<0>(GetParam()); const bool trueGradient = get<1>(GetParam()); const double range = aperture == 3 ? 300. : 1000.; RNG & rng = TS::ptr()->get_rng(); for (int ITER = 0; ITER < 20; ++ITER) { SCOPED_TRACE(cv::format("iteration %d", ITER)); const std::string fname = cvtest::findDataFile("shared/fruits.png"); const Mat original = cv::imread(fname, IMREAD_GRAYSCALE); const double thresh1 = rng.uniform(0., range); const double thresh2 = rng.uniform(0., range * 0.3); const Size sz(rng.uniform(127, 800), rng.uniform(127, 600)); const Size osz = original.size(); // preparation Mat img; if (sz.width >= osz.width || sz.height >= osz.height) { // larger image -> scale resize(original, img, sz, 0, 0, INTER_LINEAR_EXACT); } else { // smaller image -> crop Point origin(rng.uniform(0, osz.width - sz.width), rng.uniform(0, osz.height - sz.height)); Rect roi(origin, sz); original(roi).copyTo(img); } GaussianBlur(img, img, Size(5, 5), 0); // regular function Mat result; { cv::Canny(img, result, thresh1, thresh2, aperture, trueGradient); } // custom derivatives Mat customResult; { Mat dxkernel = cvtest::calcSobelKernel2D(1, 0, aperture, 0); Mat dykernel = cvtest::calcSobelKernel2D(0, 1, aperture, 0); Point anchor(aperture / 2, aperture / 2); cv::Mat dx, dy; cvtest::filter2D(img, dx, CV_16S, dxkernel, anchor, 0, BORDER_REPLICATE); cvtest::filter2D(img, dy, CV_16S, dykernel, anchor, 0, BORDER_REPLICATE); cv::Canny(dx, dy, customResult, thresh1, thresh2, trueGradient); } Mat reference; Canny_reference(img, reference, thresh1, thresh2, aperture, trueGradient); EXPECT_MAT_NEAR(result, reference, 0); EXPECT_MAT_NEAR(customResult, reference, 0); } } INSTANTIATE_TEST_CASE_P(/**/, Canny_Modes, testing::Combine( testing::Values(3, 5), testing::Values(true, false))); }} // namespace /* End of file. */