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/*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 )
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transpose(lines, lines);
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if ( exp_lines.size != lines.size || cvtest::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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