222 lines
8.2 KiB
C++
222 lines
8.2 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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// 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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// Copyright (C) 2014, Itseez, 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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template<typename T>
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struct SimilarWith
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{
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T value;
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float theta_eps;
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float rho_eps;
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SimilarWith<T>(T val, float e, float r_e): value(val), theta_eps(e), rho_eps(r_e) { };
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bool operator()(T other);
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};
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template<>
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bool SimilarWith<Vec2f>::operator()(Vec2f other)
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{
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return abs(other[0] - value[0]) < rho_eps && abs(other[1] - value[1]) < theta_eps;
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}
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template<>
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bool SimilarWith<Vec4i>::operator()(Vec4i other)
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{
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return norm(value, other) < theta_eps;
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}
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template <typename T>
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int countMatIntersection(Mat expect, Mat actual, float eps, float rho_eps)
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{
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int count = 0;
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if (!expect.empty() && !actual.empty())
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{
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for (MatIterator_<T> it=expect.begin<T>(); it!=expect.end<T>(); it++)
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{
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MatIterator_<T> f = std::find_if(actual.begin<T>(), actual.end<T>(), SimilarWith<T>(*it, eps, rho_eps));
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if (f != actual.end<T>())
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count++;
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}
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}
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return count;
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}
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String getTestCaseName(String filename)
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{
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string temp(filename);
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size_t pos = temp.find_first_of("\\/.");
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while ( pos != string::npos ) {
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temp.replace( pos, 1, "_" );
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pos = temp.find_first_of("\\/.");
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}
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return String(temp);
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}
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class BaseHoughLineTest
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{
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public:
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enum {STANDART = 0, PROBABILISTIC};
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protected:
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void run_test(int type);
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string picture_name;
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double rhoStep;
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double thetaStep;
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int threshold;
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int minLineLength;
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int maxGap;
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};
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typedef std::tr1::tuple<string, double, double, int> Image_RhoStep_ThetaStep_Threshold_t;
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class StandartHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_t>
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{
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public:
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StandartHoughLinesTest()
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{
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picture_name = std::tr1::get<0>(GetParam());
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rhoStep = std::tr1::get<1>(GetParam());
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thetaStep = std::tr1::get<2>(GetParam());
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threshold = std::tr1::get<3>(GetParam());
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minLineLength = 0;
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maxGap = 0;
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}
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};
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typedef std::tr1::tuple<string, double, double, int, int, int> Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t;
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class ProbabilisticHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t>
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{
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public:
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ProbabilisticHoughLinesTest()
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{
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picture_name = std::tr1::get<0>(GetParam());
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rhoStep = std::tr1::get<1>(GetParam());
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thetaStep = std::tr1::get<2>(GetParam());
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threshold = std::tr1::get<3>(GetParam());
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minLineLength = std::tr1::get<4>(GetParam());
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maxGap = std::tr1::get<5>(GetParam());
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}
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};
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void BaseHoughLineTest::run_test(int type)
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{
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string filename = cvtest::TS::ptr()->get_data_path() + picture_name;
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Mat src = imread(filename, IMREAD_GRAYSCALE);
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EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename;
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string xml;
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if (type == STANDART)
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xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLines.xml";
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else if (type == PROBABILISTIC)
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xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLinesP.xml";
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Mat dst;
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Canny(src, dst, 100, 150, 3);
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EXPECT_FALSE(dst.empty()) << "Failed Canny edge detector";
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Mat lines;
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if (type == STANDART)
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HoughLines(dst, lines, rhoStep, thetaStep, threshold, 0, 0);
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else if (type == PROBABILISTIC)
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HoughLinesP(dst, lines, rhoStep, thetaStep, threshold, minLineLength, maxGap);
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String test_case_name = format("lines_%s_%.0f_%.2f_%d_%d_%d", picture_name.c_str(), rhoStep, thetaStep,
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threshold, minLineLength, maxGap);
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test_case_name = getTestCaseName(test_case_name);
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FileStorage fs(xml, FileStorage::READ);
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FileNode node = fs[test_case_name];
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if (node.empty())
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{
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fs.release();
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fs.open(xml, FileStorage::APPEND);
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EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml;
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fs << test_case_name << lines;
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fs.release();
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fs.open(xml, FileStorage::READ);
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EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml;
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}
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Mat exp_lines;
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read( fs[test_case_name], exp_lines, Mat() );
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fs.release();
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int count = -1;
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if (type == STANDART)
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count = countMatIntersection<Vec2f>(exp_lines, lines, (float) thetaStep + FLT_EPSILON, (float) rhoStep + FLT_EPSILON);
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else if (type == PROBABILISTIC)
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count = countMatIntersection<Vec4i>(exp_lines, lines, 1e-4f, 0.f);
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#if (0 && defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801)
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EXPECT_GE( count, (int) (exp_lines.total() * 0.8) );
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#else
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EXPECT_EQ( count, (int) exp_lines.total());
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#endif
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}
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TEST_P(StandartHoughLinesTest, regression)
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{
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run_test(STANDART);
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}
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TEST_P(ProbabilisticHoughLinesTest, regression)
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{
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run_test(PROBABILISTIC);
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}
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INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ),
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testing::Values( 1, 10 ),
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testing::Values( 0.05, 0.1 ),
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testing::Values( 80, 150 )
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));
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INSTANTIATE_TEST_CASE_P( ImgProc, ProbabilisticHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "shared/pic1.png" ),
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testing::Values( 5, 10 ),
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testing::Values( 0.05, 0.1 ),
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testing::Values( 75, 150 ),
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testing::Values( 0, 10 ),
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testing::Values( 0, 4 )
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));
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