/*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*/ #ifndef __OPENCV_TEST_UTILITY_HPP__ #define __OPENCV_TEST_UTILITY_HPP__ ////////////////////////////////////////////////////////////////////// // random generators int randomInt(int minVal, int maxVal); double randomDouble(double minVal, double maxVal); cv::Size randomSize(int minVal, int maxVal); cv::Scalar randomScalar(double minVal, double maxVal); cv::Mat randomMat(cv::Size size, int type, double minVal = 0.0, double maxVal = 255.0); ////////////////////////////////////////////////////////////////////// // GpuMat create cv::gpu::GpuMat createMat(cv::Size size, int type, bool useRoi = false); cv::gpu::GpuMat loadMat(const cv::Mat& m, bool useRoi = false); ////////////////////////////////////////////////////////////////////// // Image load //! read image from testdata folder cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR); //! read image from testdata folder and convert it to specified type cv::Mat readImageType(const std::string& fname, int type); ////////////////////////////////////////////////////////////////////// // Image dumping void dumpImage(const std::string& fileName, const cv::Mat& image); ////////////////////////////////////////////////////////////////////// // Gpu devices //! return true if device supports specified feature and gpu module was built with support the feature. bool supportFeature(const cv::gpu::DeviceInfo& info, cv::gpu::FeatureSet feature); class DeviceManager { public: static DeviceManager& instance(); void load(int i); void loadAll(); const std::vector& values() const { return devices_; } private: std::vector devices_; }; #define ALL_DEVICES testing::ValuesIn(DeviceManager::instance().values()) ////////////////////////////////////////////////////////////////////// // Additional assertion cv::Mat getMat(cv::InputArray arr); double checkNorm(cv::InputArray m1, cv::InputArray m2); 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()); testing::AssertionResult assertMatNear(const char* expr1, const char* expr2, const char* eps_expr, cv::InputArray m1, cv::InputArray m2, double eps); #define EXPECT_MAT_NEAR(m1, m2, eps) EXPECT_PRED_FORMAT3(assertMatNear, m1, m2, eps) #define ASSERT_MAT_NEAR(m1, m2, eps) ASSERT_PRED_FORMAT3(assertMatNear, m1, m2, eps) #define EXPECT_SCALAR_NEAR(s1, s2, eps) \ { \ EXPECT_NEAR(s1[0], s2[0], eps); \ EXPECT_NEAR(s1[1], s2[1], eps); \ EXPECT_NEAR(s1[2], s2[2], eps); \ EXPECT_NEAR(s1[3], s2[3], eps); \ } #define ASSERT_SCALAR_NEAR(s1, s2, eps) \ { \ ASSERT_NEAR(s1[0], s2[0], eps); \ ASSERT_NEAR(s1[1], s2[1], eps); \ ASSERT_NEAR(s1[2], s2[2], eps); \ ASSERT_NEAR(s1[3], s2[3], eps); \ } #define EXPECT_POINT2_NEAR(p1, p2, eps) \ { \ EXPECT_NEAR(p1.x, p2.x, eps); \ EXPECT_NEAR(p1.y, p2.y, eps); \ } #define ASSERT_POINT2_NEAR(p1, p2, eps) \ { \ ASSERT_NEAR(p1.x, p2.x, eps); \ ASSERT_NEAR(p1.y, p2.y, eps); \ } #define EXPECT_POINT3_NEAR(p1, p2, eps) \ { \ EXPECT_NEAR(p1.x, p2.x, eps); \ EXPECT_NEAR(p1.y, p2.y, eps); \ EXPECT_NEAR(p1.z, p2.z, eps); \ } #define ASSERT_POINT3_NEAR(p1, p2, eps) \ { \ ASSERT_NEAR(p1.x, p2.x, eps); \ ASSERT_NEAR(p1.y, p2.y, eps); \ ASSERT_NEAR(p1.z, p2.z, eps); \ } double checkSimilarity(cv::InputArray m1, cv::InputArray m2); #define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \ { \ ASSERT_EQ(mat1.type(), mat2.type()); \ ASSERT_EQ(mat1.size(), mat2.size()); \ EXPECT_LE(checkSimilarity(mat1, mat2), eps); \ } #define ASSERT_MAT_SIMILAR(mat1, mat2, eps) \ { \ ASSERT_EQ(mat1.type(), mat2.type()); \ ASSERT_EQ(mat1.size(), mat2.size()); \ ASSERT_LE(checkSimilarity(mat1, mat2), eps); \ } ////////////////////////////////////////////////////////////////////// // Helper structs for value-parameterized tests #define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< std::tr1::tuple< __VA_ARGS__ > > #define GET_PARAM(k) std::tr1::get< k >(GetParam()) namespace cv { namespace gpu { void PrintTo(const DeviceInfo& info, std::ostream* os); }} #define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113)) // Depth using perf::MatDepth; //! return vector with depths from specified range. std::vector depths(int depth_start, int depth_end); #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)) #define DEPTHS(depth_start, depth_end) testing::ValuesIn(depths(depth_start, depth_end)) #define DEPTH_PAIRS testing::Values(std::make_pair(MatDepth(CV_8U), MatDepth(CV_8U)), \ std::make_pair(MatDepth(CV_8U), MatDepth(CV_16U)), \ std::make_pair(MatDepth(CV_8U), MatDepth(CV_16S)), \ std::make_pair(MatDepth(CV_8U), MatDepth(CV_32S)), \ std::make_pair(MatDepth(CV_8U), MatDepth(CV_32F)), \ std::make_pair(MatDepth(CV_8U), MatDepth(CV_64F)), \ \ std::make_pair(MatDepth(CV_16U), MatDepth(CV_16U)), \ std::make_pair(MatDepth(CV_16U), MatDepth(CV_32S)), \ std::make_pair(MatDepth(CV_16U), MatDepth(CV_32F)), \ std::make_pair(MatDepth(CV_16U), MatDepth(CV_64F)), \ \ std::make_pair(MatDepth(CV_16S), MatDepth(CV_16S)), \ std::make_pair(MatDepth(CV_16S), MatDepth(CV_32S)), \ std::make_pair(MatDepth(CV_16S), MatDepth(CV_32F)), \ std::make_pair(MatDepth(CV_16S), MatDepth(CV_64F)), \ \ std::make_pair(MatDepth(CV_32S), MatDepth(CV_32S)), \ std::make_pair(MatDepth(CV_32S), MatDepth(CV_32F)), \ std::make_pair(MatDepth(CV_32S), MatDepth(CV_64F)), \ \ std::make_pair(MatDepth(CV_32F), MatDepth(CV_32F)), \ std::make_pair(MatDepth(CV_32F), MatDepth(CV_64F)), \ \ std::make_pair(MatDepth(CV_64F), MatDepth(CV_64F))) // Type using perf::MatType; //! return vector with types from specified range. std::vector types(int depth_start, int depth_end, int cn_start, int cn_end); //! return vector with all types (depth: CV_8U-CV_64F, channels: 1-4). const std::vector& all_types(); #define ALL_TYPES testing::ValuesIn(all_types()) #define TYPES(depth_start, depth_end, cn_start, cn_end) testing::ValuesIn(types(depth_start, depth_end, cn_start, cn_end)) // ROI class UseRoi { public: inline UseRoi(bool val = false) : val_(val) {} inline operator bool() const { return val_; } private: bool val_; }; void PrintTo(const UseRoi& useRoi, std::ostream* os); #define WHOLE testing::Values(UseRoi(false)) #define SUBMAT testing::Values(UseRoi(true)) #define WHOLE_SUBMAT testing::Values(UseRoi(false), UseRoi(true)) // Direct/Inverse class Inverse { public: inline Inverse(bool val = false) : val_(val) {} inline operator bool() const { return val_; } private: bool val_; }; void PrintTo(const Inverse& useRoi, std::ostream* os); #define DIRECT_INVERSE testing::Values(Inverse(false), Inverse(true)) // Param class #define IMPLEMENT_PARAM_CLASS(name, type) \ class name \ { \ public: \ name ( type arg = type ()) : val_(arg) {} \ operator type () const {return val_;} \ private: \ type val_; \ }; \ inline void PrintTo( name param, std::ostream* os) \ { \ *os << #name << "(" << testing::PrintToString(static_cast< type >(param)) << ")"; \ } IMPLEMENT_PARAM_CLASS(Channels, int) #define ALL_CHANNELS testing::Values(Channels(1), Channels(2), Channels(3), Channels(4)) #define IMAGE_CHANNELS testing::Values(Channels(1), Channels(3), Channels(4)) // Flags and enums CV_ENUM(NormCode, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_TYPE_MASK, cv::NORM_RELATIVE, cv::NORM_MINMAX) CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::INTER_AREA) CV_ENUM(BorderType, cv::BORDER_REFLECT101, cv::BORDER_REPLICATE, cv::BORDER_CONSTANT, cv::BORDER_REFLECT, cv::BORDER_WRAP) #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)) CV_FLAGS(WarpFlags, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::WARP_INVERSE_MAP) ////////////////////////////////////////////////////////////////////// // Other void showDiff(cv::InputArray gold, cv::InputArray actual, double eps); #endif // __OPENCV_TEST_UTILITY_HPP__