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148 lines
4.7 KiB
148 lines
4.7 KiB
/*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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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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_HoughLinesTest : public cvtest::BaseTest |
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{ |
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public: |
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enum {STANDART = 0, PROBABILISTIC}; |
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CV_HoughLinesTest() {} |
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~CV_HoughLinesTest() {} |
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protected: |
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void run_test(int type); |
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}; |
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class CV_StandartHoughLinesTest : public CV_HoughLinesTest |
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{ |
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public: |
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CV_StandartHoughLinesTest() {} |
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~CV_StandartHoughLinesTest() {} |
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virtual void run(int); |
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}; |
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class CV_ProbabilisticHoughLinesTest : public CV_HoughLinesTest |
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{ |
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public: |
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CV_ProbabilisticHoughLinesTest() {} |
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~CV_ProbabilisticHoughLinesTest() {} |
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virtual void run(int); |
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}; |
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void CV_StandartHoughLinesTest::run(int) |
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{ |
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run_test(STANDART); |
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} |
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void CV_ProbabilisticHoughLinesTest::run(int) |
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{ |
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run_test(PROBABILISTIC); |
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} |
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void CV_HoughLinesTest::run_test(int type) |
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{ |
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Mat src = imread(string(ts->get_data_path()) + "shared/pic1.png"); |
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if (src.empty()) |
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{ |
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); |
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return; |
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} |
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string xml; |
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if (type == STANDART) |
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xml = string(ts->get_data_path()) + "imgproc/HoughLines.xml"; |
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else if (type == PROBABILISTIC) |
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xml = string(ts->get_data_path()) + "imgproc/HoughLinesP.xml"; |
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else |
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{ |
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ts->printf(cvtest::TS::LOG, "Error: unknown HoughLines algorithm type.\n"); |
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ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC); |
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return; |
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} |
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Mat dst; |
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Canny(src, dst, 50, 200, 3); |
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Mat lines; |
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if (type == STANDART) |
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HoughLines(dst, lines, 1, CV_PI/180, 100, 0, 0); |
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else if (type == PROBABILISTIC) |
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HoughLinesP(dst, lines, 1, CV_PI/180, 100, 0, 0); |
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FileStorage fs(xml, FileStorage::READ); |
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if (!fs.isOpened()) |
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{ |
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fs.open(xml, FileStorage::WRITE); |
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if (!fs.isOpened()) |
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{ |
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); |
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return; |
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} |
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fs << "exp_lines" << lines; |
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fs.release(); |
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fs.open(xml, FileStorage::READ); |
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if (!fs.isOpened()) |
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{ |
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); |
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return; |
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} |
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} |
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Mat exp_lines; |
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read( fs["exp_lines"], exp_lines, Mat() ); |
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fs.release(); |
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if ( exp_lines.size != lines.size || norm(exp_lines, lines, NORM_INF) > 1e-4 ) |
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{ |
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
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return; |
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} |
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ts->set_failed_test_info(cvtest::TS::OK); |
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} |
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TEST(Imgproc_HoughLines, regression) { CV_StandartHoughLinesTest test; test.safe_run(); } |
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TEST(Imgproc_HoughLinesP, regression) { CV_ProbabilisticHoughLinesTest test; test.safe_run(); }
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