/*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__ 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); cv::gpu::GpuMat createMat(cv::Size size, int type, bool useRoi = false); cv::gpu::GpuMat loadMat(const cv::Mat& m, bool useRoi = false); void showDiff(cv::InputArray gold, cv::InputArray actual, double eps); //! 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); //! return all devices compatible with current gpu module build. const std::vector& devices(); //! return all devices compatible with current gpu module build which support specified feature. std::vector devices(cv::gpu::FeatureSet feature); //! read image from testdata folder. cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR); cv::Mat readImageType(const std::string& fname, int type); double checkNorm(const cv::Mat& m); double checkNorm(const cv::Mat& m1, const cv::Mat& m2); double checkSimilarity(const cv::Mat& m1, const cv::Mat& m2); #define EXPECT_MAT_NORM(mat, eps) \ { \ EXPECT_LE(checkNorm(cv::Mat(mat)), eps) \ } #define EXPECT_MAT_NEAR(mat1, mat2, eps) \ { \ ASSERT_EQ(mat1.type(), mat2.type()); \ ASSERT_EQ(mat1.size(), mat2.size()); \ EXPECT_LE(checkNorm(cv::Mat(mat1), cv::Mat(mat2)), eps); \ } #define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \ { \ ASSERT_EQ(mat1.type(), mat2.type()); \ ASSERT_EQ(mat1.size(), mat2.size()); \ EXPECT_LE(checkSimilarity(cv::Mat(mat1), cv::Mat(mat2)), eps); \ } namespace cv { namespace gpu { void PrintTo(const DeviceInfo& info, std::ostream* os); }} using perf::MatDepth; 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(); 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); 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); CV_ENUM(CmpCode, cv::CMP_EQ, cv::CMP_GT, cv::CMP_GE, cv::CMP_LT, cv::CMP_LE, cv::CMP_NE) CV_ENUM(NormCode, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_TYPE_MASK, cv::NORM_RELATIVE, cv::NORM_MINMAX) enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1}; CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y) CV_ENUM(ReduceOp, CV_REDUCE_SUM, CV_REDUCE_AVG, CV_REDUCE_MAX, CV_REDUCE_MIN) CV_FLAGS(GemmFlags, cv::GEMM_1_T, cv::GEMM_2_T, cv::GEMM_3_T); CV_ENUM(DistType, cv::gpu::BruteForceMatcher_GPU_base::L1Dist, cv::gpu::BruteForceMatcher_GPU_base::L2Dist) CV_ENUM(MorphOp, cv::MORPH_OPEN, cv::MORPH_CLOSE, cv::MORPH_GRADIENT, cv::MORPH_TOPHAT, cv::MORPH_BLACKHAT) CV_ENUM(ThreshOp, cv::THRESH_BINARY, cv::THRESH_BINARY_INV, cv::THRESH_TRUNC, cv::THRESH_TOZERO, cv::THRESH_TOZERO_INV) CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC) CV_ENUM(Border, cv::BORDER_REFLECT101, cv::BORDER_REPLICATE, cv::BORDER_CONSTANT, cv::BORDER_REFLECT, cv::BORDER_WRAP) CV_FLAGS(WarpFlags, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::WARP_INVERSE_MAP) CV_ENUM(TemplateMethod, cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED, cv::TM_CCORR, cv::TM_CCORR_NORMED, cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED) CV_FLAGS(DftFlags, cv::DFT_INVERSE, cv::DFT_SCALE, cv::DFT_ROWS, cv::DFT_COMPLEX_OUTPUT, cv::DFT_REAL_OUTPUT) #define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< std::tr1::tuple< __VA_ARGS__ > > #define GET_PARAM(k) std::tr1::get< k >(GetParam()) #define ALL_DEVICES testing::ValuesIn(devices()) #define DEVICES(feature) testing::ValuesIn(devices(feature)) #define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113)) #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 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)) #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))) #define WHOLE testing::Values(UseRoi(false)) #define SUBMAT testing::Values(UseRoi(true)) #define WHOLE_SUBMAT testing::Values(UseRoi(false), UseRoi(true)) #define DIRECT_INVERSE testing::Values(Inverse(false), Inverse(true)) #define ALL_CMP_CODES testing::Values(CmpCode(cv::CMP_EQ), CmpCode(cv::CMP_NE), CmpCode(cv::CMP_GT), CmpCode(cv::CMP_GE), CmpCode(cv::CMP_LT), CmpCode(cv::CMP_LE)) #endif // __OPENCV_TEST_UTILITY_HPP__