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https://github.com/opencv/opencv.git
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370 lines
15 KiB
C++
370 lines
15 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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// 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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#ifndef OPENCV_CUDA_TEST_UTILITY_HPP
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#define OPENCV_CUDA_TEST_UTILITY_HPP
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#include "opencv2/ts.hpp"
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#include <stdexcept>
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#include "opencv2/core/cuda.hpp"
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namespace cvtest
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{
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//////////////////////////////////////////////////////////////////////
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// random generators
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int randomInt(int minVal, int maxVal);
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double randomDouble(double minVal, double maxVal);
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cv::Size randomSize(int minVal, int maxVal);
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cv::Scalar randomScalar(double minVal, double maxVal);
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cv::Mat randomMat(cv::Size size, int type, double minVal = 0.0, double maxVal = 255.0);
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//////////////////////////////////////////////////////////////////////
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// GpuMat create
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cv::cuda::GpuMat createMat(cv::Size size, int type, bool useRoi = false);
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cv::cuda::GpuMat loadMat(const cv::Mat& m, bool useRoi = false);
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//////////////////////////////////////////////////////////////////////
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// Image load
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//! read image from testdata folder
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cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR);
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//! read image from testdata folder and convert it to specified type
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cv::Mat readImageType(const std::string& fname, int type);
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//////////////////////////////////////////////////////////////////////
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// Gpu devices
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//! return true if device supports specified feature and gpu module was built with support the feature.
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bool supportFeature(const cv::cuda::DeviceInfo& info, cv::cuda::FeatureSet feature);
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class DeviceManager
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{
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public:
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static DeviceManager& instance();
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void load(int i);
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void loadAll();
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const std::vector<cv::cuda::DeviceInfo>& values() const { return devices_; }
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private:
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std::vector<cv::cuda::DeviceInfo> devices_;
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};
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#define ALL_DEVICES testing::ValuesIn(cvtest::DeviceManager::instance().values())
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//////////////////////////////////////////////////////////////////////
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// Additional assertion
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void minMaxLocGold(const cv::Mat& src, double* minVal_, double* maxVal_ = 0, cv::Point* minLoc_ = 0, cv::Point* maxLoc_ = 0, const cv::Mat& mask = cv::Mat());
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cv::Mat getMat(cv::InputArray arr);
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testing::AssertionResult assertMatNear(const char* expr1, const char* expr2, const char* eps_expr, cv::InputArray m1, cv::InputArray m2, double eps);
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#undef EXPECT_MAT_NEAR
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#define EXPECT_MAT_NEAR(m1, m2, eps) EXPECT_PRED_FORMAT3(cvtest::assertMatNear, m1, m2, eps)
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#define ASSERT_MAT_NEAR(m1, m2, eps) ASSERT_PRED_FORMAT3(cvtest::assertMatNear, m1, m2, eps)
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#define EXPECT_SCALAR_NEAR(s1, s2, eps) \
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{ \
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EXPECT_NEAR(s1[0], s2[0], eps); \
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EXPECT_NEAR(s1[1], s2[1], eps); \
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EXPECT_NEAR(s1[2], s2[2], eps); \
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EXPECT_NEAR(s1[3], s2[3], eps); \
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}
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#define ASSERT_SCALAR_NEAR(s1, s2, eps) \
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{ \
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ASSERT_NEAR(s1[0], s2[0], eps); \
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ASSERT_NEAR(s1[1], s2[1], eps); \
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ASSERT_NEAR(s1[2], s2[2], eps); \
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ASSERT_NEAR(s1[3], s2[3], eps); \
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}
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#define EXPECT_POINT2_NEAR(p1, p2, eps) \
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{ \
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EXPECT_NEAR(p1.x, p2.x, eps); \
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EXPECT_NEAR(p1.y, p2.y, eps); \
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}
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#define ASSERT_POINT2_NEAR(p1, p2, eps) \
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{ \
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ASSERT_NEAR(p1.x, p2.x, eps); \
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ASSERT_NEAR(p1.y, p2.y, eps); \
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}
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#define EXPECT_POINT3_NEAR(p1, p2, eps) \
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{ \
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EXPECT_NEAR(p1.x, p2.x, eps); \
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EXPECT_NEAR(p1.y, p2.y, eps); \
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EXPECT_NEAR(p1.z, p2.z, eps); \
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}
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#define ASSERT_POINT3_NEAR(p1, p2, eps) \
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{ \
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ASSERT_NEAR(p1.x, p2.x, eps); \
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ASSERT_NEAR(p1.y, p2.y, eps); \
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ASSERT_NEAR(p1.z, p2.z, eps); \
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}
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double checkSimilarity(cv::InputArray m1, cv::InputArray m2);
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#undef EXPECT_MAT_SIMILAR
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#define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \
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{ \
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ASSERT_EQ(mat1.type(), mat2.type()); \
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ASSERT_EQ(mat1.size(), mat2.size()); \
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EXPECT_LE(checkSimilarity(mat1, mat2), eps); \
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}
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#define ASSERT_MAT_SIMILAR(mat1, mat2, eps) \
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{ \
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ASSERT_EQ(mat1.type(), mat2.type()); \
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ASSERT_EQ(mat1.size(), mat2.size()); \
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ASSERT_LE(checkSimilarity(mat1, mat2), eps); \
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}
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//////////////////////////////////////////////////////////////////////
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// Helper structs for value-parameterized tests
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#define CUDA_TEST_P(test_case_name, test_name) \
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class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) \
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: public test_case_name { \
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public: \
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {} \
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virtual void TestBody(); \
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private: \
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void UnsafeTestBody(); \
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static int AddToRegistry() { \
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::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
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GetTestCasePatternHolder<test_case_name>(\
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#test_case_name, \
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::testing::internal::CodeLocation(\
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__FILE__, __LINE__))->AddTestPattern(\
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#test_case_name, \
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#test_name, \
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new ::testing::internal::TestMetaFactory< \
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GTEST_TEST_CLASS_NAME_(\
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test_case_name, test_name)>()); \
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return 0; \
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} \
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static int gtest_registering_dummy_ GTEST_ATTRIBUTE_UNUSED_; \
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GTEST_DISALLOW_COPY_AND_ASSIGN_(\
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)); \
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}; \
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int GTEST_TEST_CLASS_NAME_(test_case_name, \
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test_name)::gtest_registering_dummy_ = \
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::AddToRegistry(); \
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void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() \
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{ \
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try \
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{ \
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UnsafeTestBody(); \
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} \
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catch (...) \
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{ \
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cv::cuda::resetDevice(); \
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throw; \
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} \
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} \
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void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::UnsafeTestBody()
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#define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113))
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// Depth
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using perf::MatDepth;
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#define ALL_DEPTH testing::Values(MatDepth(CV_8U), MatDepth(CV_8S), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32S), MatDepth(CV_32F), MatDepth(CV_64F))
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#define DEPTH_PAIRS testing::Values(std::make_pair(MatDepth(CV_8U), MatDepth(CV_8U)), \
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std::make_pair(MatDepth(CV_8U), MatDepth(CV_16U)), \
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std::make_pair(MatDepth(CV_8U), MatDepth(CV_16S)), \
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std::make_pair(MatDepth(CV_8U), MatDepth(CV_32S)), \
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std::make_pair(MatDepth(CV_8U), MatDepth(CV_32F)), \
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std::make_pair(MatDepth(CV_8U), MatDepth(CV_64F)), \
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\
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std::make_pair(MatDepth(CV_16U), MatDepth(CV_16U)), \
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std::make_pair(MatDepth(CV_16U), MatDepth(CV_32S)), \
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std::make_pair(MatDepth(CV_16U), MatDepth(CV_32F)), \
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std::make_pair(MatDepth(CV_16U), MatDepth(CV_64F)), \
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\
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std::make_pair(MatDepth(CV_16S), MatDepth(CV_16S)), \
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std::make_pair(MatDepth(CV_16S), MatDepth(CV_32S)), \
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std::make_pair(MatDepth(CV_16S), MatDepth(CV_32F)), \
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std::make_pair(MatDepth(CV_16S), MatDepth(CV_64F)), \
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\
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std::make_pair(MatDepth(CV_32S), MatDepth(CV_32S)), \
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std::make_pair(MatDepth(CV_32S), MatDepth(CV_32F)), \
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std::make_pair(MatDepth(CV_32S), MatDepth(CV_64F)), \
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\
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std::make_pair(MatDepth(CV_32F), MatDepth(CV_32F)), \
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std::make_pair(MatDepth(CV_32F), MatDepth(CV_64F)), \
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\
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std::make_pair(MatDepth(CV_64F), MatDepth(CV_64F)))
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// Type
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using perf::MatType;
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//! return vector with types from specified range.
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std::vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end);
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//! return vector with all types (depth: CV_8U-CV_64F, channels: 1-4).
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const std::vector<MatType>& all_types();
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#define ALL_TYPES testing::ValuesIn(all_types())
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#define TYPES(depth_start, depth_end, cn_start, cn_end) testing::ValuesIn(types(depth_start, depth_end, cn_start, cn_end))
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// ROI
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class UseRoi
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{
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public:
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inline UseRoi(bool val = false) : val_(val) {}
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inline operator bool() const { return val_; }
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private:
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bool val_;
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};
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void PrintTo(const UseRoi& useRoi, std::ostream* os);
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#define WHOLE_SUBMAT testing::Values(UseRoi(false), UseRoi(true))
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// Direct/Inverse
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class Inverse
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{
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public:
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inline Inverse(bool val = false) : val_(val) {}
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inline operator bool() const { return val_; }
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private:
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bool val_;
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};
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void PrintTo(const Inverse& useRoi, std::ostream* os);
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#define DIRECT_INVERSE testing::Values(Inverse(false), Inverse(true))
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// Param class
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#define IMPLEMENT_PARAM_CLASS(name, type) \
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class name \
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{ \
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public: \
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name ( type arg = type ()) : val_(arg) {} \
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operator type () const {return val_;} \
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private: \
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type val_; \
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}; \
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inline void PrintTo( name param, std::ostream* os) \
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{ \
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*os << #name << "(" << testing::PrintToString(static_cast< type >(param)) << ")"; \
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}
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IMPLEMENT_PARAM_CLASS(Channels, int)
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#define ALL_CHANNELS testing::Values(Channels(1), Channels(2), Channels(3), Channels(4))
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#define IMAGE_CHANNELS testing::Values(Channels(1), Channels(3), Channels(4))
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// Flags and enums
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CV_ENUM(NormCode, NORM_INF, NORM_L1, NORM_L2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX)
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CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
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CV_ENUM(BorderType, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, BORDER_WRAP)
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#define ALL_BORDER_TYPES testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP))
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CV_FLAGS(WarpFlags, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, WARP_INVERSE_MAP)
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//////////////////////////////////////////////////////////////////////
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// Features2D
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testing::AssertionResult assertKeyPointsEquals(const char* gold_expr, const char* actual_expr, std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual);
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#define ASSERT_KEYPOINTS_EQ(gold, actual) EXPECT_PRED_FORMAT2(assertKeyPointsEquals, gold, actual)
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int getMatchedPointsCount(std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual);
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int getMatchedPointsCount(const std::vector<cv::KeyPoint>& keypoints1, const std::vector<cv::KeyPoint>& keypoints2, const std::vector<cv::DMatch>& matches);
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//////////////////////////////////////////////////////////////////////
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// Other
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void dumpImage(const std::string& fileName, const cv::Mat& image);
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void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
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void parseCudaDeviceOptions(int argc, char **argv);
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void printCudaInfo();
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}
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namespace cv { namespace cuda
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{
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void PrintTo(const DeviceInfo& info, std::ostream* os);
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}}
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#ifdef HAVE_CUDA
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#define CV_TEST_INIT0_CUDA cvtest::parseCudaDeviceOptions(argc, argv), cvtest::printCudaInfo(), cv::setUseOptimized(false)
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#define CV_CUDA_TEST_MAIN(resourcesubdir, ...) \
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CV_TEST_MAIN_EX(resourcesubdir, CUDA, __VA_ARGS__)
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#else // HAVE_CUDA
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#define CV_CUDA_TEST_MAIN(resourcesubdir) \
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int main() \
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{ \
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printf("OpenCV was built without CUDA support\n"); \
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return 0; \
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}
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#endif // HAVE_CUDA
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#endif // OPENCV_CUDA_TEST_UTILITY_HPP
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