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modules/ts/include/opencv2/ts.hpp
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modules/ts/include/opencv2/ts/cuda_perf.hpp
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/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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_CUDA_PERF_UTILITY_HPP
#define OPENCV_CUDA_PERF_UTILITY_HPP
#include "opencv2/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
namespace perf
{
#define ALL_BORDER_MODES BorderMode::all()
#define ALL_INTERPOLATIONS Interpolation::all()
CV_ENUM(BorderMode, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, BORDER_WRAP)
CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
CV_ENUM(NormType, NORM_INF, NORM_L1, NORM_L2, NORM_HAMMING, NORM_MINMAX)
enum { Gray = 1, TwoChannel = 2, BGR = 3, BGRA = 4 };
CV_ENUM(MatCn, Gray, TwoChannel, BGR, BGRA)
#define CUDA_CHANNELS_1_3_4 testing::Values(MatCn(Gray), MatCn(BGR), MatCn(BGRA))
#define CUDA_CHANNELS_1_3 testing::Values(MatCn(Gray), MatCn(BGR))
#define GET_PARAM(k) testing::get< k >(GetParam())
#define DEF_PARAM_TEST(name, ...) typedef ::perf::TestBaseWithParam< testing::tuple< __VA_ARGS__ > > name
#define DEF_PARAM_TEST_1(name, param_type) typedef ::perf::TestBaseWithParam< param_type > name
DEF_PARAM_TEST_1(Sz, cv::Size);
typedef perf::Size_MatType Sz_Type;
DEF_PARAM_TEST(Sz_Depth, cv::Size, perf::MatDepth);
DEF_PARAM_TEST(Sz_Depth_Cn, cv::Size, perf::MatDepth, MatCn);
#define CUDA_TYPICAL_MAT_SIZES testing::Values(perf::sz720p, perf::szSXGA, perf::sz1080p)
#define FAIL_NO_CPU() FAIL() << "No such CPU implementation analogy"
#define CUDA_SANITY_CHECK(mat, ...) \
do{ \
cv::Mat gpu_##mat(mat); \
SANITY_CHECK(gpu_##mat, ## __VA_ARGS__); \
} while(0)
#define CPU_SANITY_CHECK(mat, ...) \
do{ \
cv::Mat cpu_##mat(mat); \
SANITY_CHECK(cpu_##mat, ## __VA_ARGS__); \
} while(0)
cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR);
struct CvtColorInfo
{
int scn;
int dcn;
int code;
CvtColorInfo() {}
explicit CvtColorInfo(int scn_, int dcn_, int code_) : scn(scn_), dcn(dcn_), code(code_) {}
};
void PrintTo(const CvtColorInfo& info, std::ostream* os);
void printCudaInfo();
void sortKeyPoints(std::vector<cv::KeyPoint>& keypoints, cv::InputOutputArray _descriptors = cv::noArray());
#ifdef HAVE_CUDA
#define CV_PERF_TEST_CUDA_MAIN(modulename) \
int main(int argc, char **argv)\
{\
const char * impls[] = { "cuda", "plain" };\
CV_PERF_TEST_MAIN_INTERNALS(modulename, impls, perf::printCudaInfo())\
}
#else
#define CV_PERF_TEST_CUDA_MAIN(modulename) \
int main(int argc, char **argv)\
{\
const char * plain_only[] = { "plain" };\
CV_PERF_TEST_MAIN_INTERNALS(modulename, plain_only)\
}
#endif
}
#endif // OPENCV_CUDA_PERF_UTILITY_HPP
modules/ts/include/opencv2/ts/cuda_test.hpp
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/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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_CUDA_TEST_UTILITY_HPP
#define OPENCV_CUDA_TEST_UTILITY_HPP
#include "opencv2/ts.hpp"
#include <stdexcept>
#include "opencv2/core/cuda.hpp"
namespace cvtest
{
//////////////////////////////////////////////////////////////////////
// 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::cuda::GpuMat createMat(cv::Size size, int type, bool useRoi = false);
cv::cuda::GpuMat createMat(cv::Size size, int type, cv::Size& size0, cv::Point& ofs, bool useRoi = false);
cv::cuda::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);
//////////////////////////////////////////////////////////////////////
// Gpu devices
//! return true if device supports specified feature and gpu module was built with support the feature.
bool supportFeature(const cv::cuda::DeviceInfo& info, cv::cuda::FeatureSet feature);
class DeviceManager
{
public:
static DeviceManager& instance();
void load(int i);
void loadAll();
const std::vector<cv::cuda::DeviceInfo>& values() const { return devices_; }
private:
std::vector<cv::cuda::DeviceInfo> devices_;
};
#define ALL_DEVICES testing::ValuesIn(cvtest::DeviceManager::instance().values())
//////////////////////////////////////////////////////////////////////
// Additional assertion
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());
cv::Mat getMat(cv::InputArray arr);
testing::AssertionResult assertMatNear(const char* expr1, const char* expr2, const char* eps_expr, cv::InputArray m1, cv::InputArray m2, double eps);
#undef EXPECT_MAT_NEAR
#define EXPECT_MAT_NEAR(m1, m2, eps) EXPECT_PRED_FORMAT3(cvtest::assertMatNear, m1, m2, eps)
#define ASSERT_MAT_NEAR(m1, m2, eps) ASSERT_PRED_FORMAT3(cvtest::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);
#undef EXPECT_MAT_SIMILAR
#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 CUDA_TEST_P(test_case_name, test_name) \
class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) \
: public test_case_name { \
public: \
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {} \
virtual void TestBody(); \
private: \
void UnsafeTestBody(); \
static int AddToRegistry() { \
::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
GetTestCasePatternHolder<test_case_name>(\
#test_case_name, \
::testing::internal::CodeLocation(\
__FILE__, __LINE__))->AddTestPattern(\
#test_case_name, \
#test_name, \
new ::testing::internal::TestMetaFactory< \
GTEST_TEST_CLASS_NAME_(\
test_case_name, test_name)>()); \
return 0; \
} \
static int gtest_registering_dummy_ GTEST_ATTRIBUTE_UNUSED_; \
GTEST_DISALLOW_COPY_AND_ASSIGN_(\
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)); \
}; \
int GTEST_TEST_CLASS_NAME_(test_case_name, \
test_name)::gtest_registering_dummy_ = \
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::AddToRegistry(); \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() \
{ \
try \
{ \
UnsafeTestBody(); \
} \
catch (const cvtest::details::SkipTestExceptionBase& e) \
{ \
printf("[ SKIP ] %s\n", e.what()); \
cv::cuda::resetDevice(); \
} \
catch (...) \
{ \
cv::cuda::resetDevice(); \
throw; \
} \
} \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::UnsafeTestBody()
#define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113))
#define DIFFERENT_SIZES_EXTRA testing::Values(cv::Size(13, 1), cv::Size(1, 13), cv::Size(128, 128), cv::Size(113, 113))
// Depth
using perf::MatDepth;
#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 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<MatType> 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<MatType>& 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_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, NORM_INF, NORM_L1, NORM_L2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX)
CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
CV_ENUM(BorderType, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, 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, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, WARP_INVERSE_MAP)
//////////////////////////////////////////////////////////////////////
// Features
testing::AssertionResult assertKeyPointsEquals(const char* gold_expr, const char* actual_expr, std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual);
#define ASSERT_KEYPOINTS_EQ(gold, actual) EXPECT_PRED_FORMAT2(assertKeyPointsEquals, gold, actual)
int getMatchedPointsCount(std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual);
int getMatchedPointsCount(const std::vector<cv::KeyPoint>& keypoints1, const std::vector<cv::KeyPoint>& keypoints2, const std::vector<cv::DMatch>& matches);
//////////////////////////////////////////////////////////////////////
// Other
void dumpImage(const std::string& fileName, const cv::Mat& image);
void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
void parseCudaDeviceOptions(int argc, char **argv);
void printCudaInfo();
}
namespace cv { namespace cuda
{
void PrintTo(const DeviceInfo& info, std::ostream* os);
}}
#ifdef HAVE_CUDA
#define CV_TEST_INIT0_CUDA cvtest::parseCudaDeviceOptions(argc, argv), cvtest::printCudaInfo(), cv::setUseOptimized(false)
#define CV_CUDA_TEST_MAIN(resourcesubdir, ...) \
CV_TEST_MAIN_EX(resourcesubdir, CUDA, __VA_ARGS__)
#else // HAVE_CUDA
#define CV_CUDA_TEST_MAIN(resourcesubdir) \
int main() \
{ \
printf("OpenCV was built without CUDA support\n"); \
return 0; \
}
#endif // HAVE_CUDA
#endif // OPENCV_CUDA_TEST_UTILITY_HPP
modules/ts/include/opencv2/ts/ocl_perf.hpp
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/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., 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 the copyright holders 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 OpenCV Foundation 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_TS_OCL_PERF_HPP
#define OPENCV_TS_OCL_PERF_HPP
#include "opencv2/ts.hpp"
#include "ocl_test.hpp"
#include "ts_perf.hpp"
namespace cvtest {
namespace ocl {
using namespace perf;
#define OCL_PERF_STRATEGY PERF_STRATEGY_SIMPLE
#define OCL_PERF_TEST(fixture, name) SIMPLE_PERF_TEST(fixture, name)
#define OCL_PERF_TEST_P(fixture, name, params) SIMPLE_PERF_TEST_P(fixture, name, params)
#define SIMPLE_PERF_TEST(fixture, name) \
class OCL##_##fixture##_##name : \
public ::perf::TestBase \
{ \
public: \
OCL##_##fixture##_##name() { } \
protected: \
virtual void PerfTestBody() CV_OVERRIDE; \
}; \
TEST_F(OCL##_##fixture##_##name, name) { CV_TRACE_REGION("PERF_TEST: " #fixture "_" #name); declare.strategy(OCL_PERF_STRATEGY); RunPerfTestBody(); } \
void OCL##_##fixture##_##name::PerfTestBody()
#define SIMPLE_PERF_TEST_P(fixture, name, params) \
class OCL##_##fixture##_##name : \
public fixture \
{ \
public: \
OCL##_##fixture##_##name() { } \
protected: \
virtual void PerfTestBody() CV_OVERRIDE; \
}; \
TEST_P(OCL##_##fixture##_##name, name) { CV_TRACE_REGION("PERF_TEST_P: " #fixture "_" #name); declare.strategy(OCL_PERF_STRATEGY); RunPerfTestBody(); } \
INSTANTIATE_TEST_CASE_P(/*none*/, OCL##_##fixture##_##name, params); \
void OCL##_##fixture##_##name::PerfTestBody()
#define OCL_SIZE_1 szVGA
#define OCL_SIZE_2 sz720p
#define OCL_SIZE_3 sz1080p
#define OCL_SIZE_4 sz2160p
#define OCL_TEST_SIZES ::testing::Values(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3, OCL_SIZE_4)
#define OCL_TEST_TYPES ::testing::Values(CV_8UC1, CV_32FC1, CV_8UC4, CV_32FC4)
#define OCL_TEST_TYPES_14 OCL_TEST_TYPES
#define OCL_TEST_TYPES_134 ::testing::Values(CV_8UC1, CV_32FC1, CV_8UC3, CV_32FC3, CV_8UC4, CV_32FC4)
#define OCL_PERF_ENUM ::testing::Values
//! deprecated
#define OCL_TEST_CYCLE() \
for (cvtest::ocl::perf::safeFinish(); next() && startTimer(); cvtest::ocl::perf::safeFinish(), stopTimer())
//! deprecated
#define OCL_TEST_CYCLE_N(n) \
for (declare.iterations(n), cvtest::ocl::perf::safeFinish(); next() && startTimer(); cvtest::ocl::perf::safeFinish(), stopTimer())
//! deprecated
#define OCL_TEST_CYCLE_MULTIRUN(runsNum) \
for (declare.runs(runsNum), cvtest::ocl::perf::safeFinish(); next() && startTimer(); cvtest::ocl::perf::safeFinish(), stopTimer()) \
for (int r = 0; r < runsNum; cvtest::ocl::perf::safeFinish(), ++r)
#undef PERF_SAMPLE_BEGIN
#undef PERF_SAMPLE_END
#define PERF_SAMPLE_BEGIN() \
cvtest::ocl::perf::safeFinish(); \
for(; next() && startTimer(); cvtest::ocl::perf::safeFinish(), stopTimer()) \
{ \
CV_TRACE_REGION("iteration");
#define PERF_SAMPLE_END() \
}
namespace perf {
// Check for current device limitation
void checkDeviceMaxMemoryAllocSize(const Size& size, int type, int factor = 1);
// Initialize Mat with random numbers. Range is depends on the data type.
// TODO Parameter type is actually OutputArray
void randu(InputOutputArray dst);
inline void safeFinish()
{
if (cv::ocl::useOpenCL())
cv::ocl::finish();
}
} // namespace perf
using namespace perf;
} // namespace cvtest::ocl
} // namespace cvtest
#endif // OPENCV_TS_OCL_PERF_HPP
modules/ts/include/opencv2/ts/ocl_test.hpp
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/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., 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 the copyright holders 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 OpenCV Foundation 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_TS_OCL_TEST_HPP
#define OPENCV_TS_OCL_TEST_HPP
#include "opencv2/ts.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/core/ocl.hpp"
namespace cvtest {
namespace ocl {
using namespace cv;
using namespace testing;
inline std::vector<UMat> ToUMat(const std::vector<Mat>& src)
{
std::vector<UMat> dst;
dst.resize(src.size());
for (size_t i = 0; i < src.size(); ++i)
{
src[i].copyTo(dst[i]);
}
return dst;
}
inline UMat ToUMat(const Mat& src)
{
UMat dst;
src.copyTo(dst);
return dst;
}
inline UMat ToUMat(InputArray src)
{
UMat dst;
src.getMat().copyTo(dst);
return dst;
}
extern int test_loop_times;
#define MAX_VALUE 357
#define EXPECT_MAT_NORM(mat, eps) \
do \
{ \
EXPECT_LE(cvtest::ocl::TestUtils::checkNorm1(mat), eps) \
} while ((void)0, 0)
#undef EXPECT_MAT_NEAR
#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
do \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(cvtest::ocl::TestUtils::checkNorm2(mat1, mat2), eps) \
<< "Size: " << mat1.size() << std::endl; \
} while ((void)0, 0)
#define EXPECT_MAT_NEAR_RELATIVE(mat1, mat2, eps) \
do \
{ \
ASSERT_EQ((mat1).type(), (mat2).type()); \
ASSERT_EQ((mat1).size(), (mat2).size()); \
EXPECT_LE(cvtest::ocl::TestUtils::checkNormRelative((mat1), (mat2)), eps) \
<< "Size: " << (mat1).size() << std::endl; \
} while ((void)0, 0)
#define EXPECT_MAT_N_DIFF_EPS(mat1, mat2, eps, num) \
do \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
Mat diff, mask; \
absdiff(mat1, mat2, diff); \
cv::compare(diff.reshape(1), Scalar::all(eps), mask, CMP_GT); \
EXPECT_LE(countNonZero(mask), num) \
<< "Size: " << mat1.size() << std::endl; \
} while ((void)0, 0)
#define EXPECT_MAT_N_DIFF(mat1, mat2, num) \
do \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
Mat diff; \
absdiff(mat1, mat2, diff); \
EXPECT_LE(countNonZero(diff.reshape(1)), num) \
<< "Size: " << mat1.size() << std::endl; \
} while ((void)0, 0)
#define OCL_EXPECT_MAT_N_DIFF(name, eps) \
do \
{ \
ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
Mat diff, binary, binary_8; \
absdiff(name ## _roi, u ## name ## _roi, diff); \
Mat mask(diff.size(), CV_8UC(dst.channels()), cv::Scalar::all(255)); \
if (mask.cols > 2 && mask.rows > 2) \
mask(cv::Rect(1, 1, mask.cols - 2, mask.rows - 2)).setTo(0); \
cv::threshold(diff, binary, (double)eps, 255, cv::THRESH_BINARY); \
EXPECT_LE(countNonZero(binary.reshape(1)), (int)(binary.cols*binary.rows*5/1000)) \
<< "Size: " << name ## _roi.size() << std::endl; \
binary.convertTo(binary_8, mask.type()); \
binary_8 = binary_8 & mask; \
EXPECT_LE(countNonZero(binary_8.reshape(1)), (int)((binary_8.cols+binary_8.rows)/100)) \
<< "Size: " << name ## _roi.size() << std::endl; \
} while ((void)0, 0)
#define OCL_EXPECT_MATS_NEAR(name, eps) \
do \
{ \
ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
EXPECT_LE(cvtest::ocl::TestUtils::checkNorm2(name ## _roi, u ## name ## _roi), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
Point _offset; \
Size _wholeSize; \
u ## name ## _roi.locateROI(_wholeSize, _offset); \
Mat _mask(name.size(), CV_8UC1, Scalar::all(255)); \
_mask(Rect(_offset, name ## _roi.size())).setTo(Scalar::all(0)); \
ASSERT_EQ(name.type(), u ## name.type()); \
ASSERT_EQ(name.size(), u ## name.size()); \
EXPECT_LE(cvtest::ocl::TestUtils::checkNorm2(name, u ## name, _mask), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
} while ((void)0, 0)
#define OCL_EXPECT_MATS_NEAR_RELATIVE(name, eps) \
do \
{ \
ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
EXPECT_LE(TestUtils::checkNormRelative(name ## _roi, u ## name ## _roi), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
Point _offset; \
Size _wholeSize; \
name ## _roi.locateROI(_wholeSize, _offset); \
Mat _mask(name.size(), CV_8UC1, Scalar::all(255)); \
_mask(Rect(_offset, name ## _roi.size())).setTo(Scalar::all(0)); \
ASSERT_EQ(name.type(), u ## name.type()); \
ASSERT_EQ(name.size(), u ## name.size()); \
EXPECT_LE(TestUtils::checkNormRelative(name, u ## name, _mask), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
} while ((void)0, 0)
//for sparse matrix
#define OCL_EXPECT_MATS_NEAR_RELATIVE_SPARSE(name, eps) \
do \
{ \
ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
EXPECT_LE(cvtest::ocl::TestUtils::checkNormRelativeSparse(name ## _roi, u ## name ## _roi), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
Point _offset; \
Size _wholeSize; \
name ## _roi.locateROI(_wholeSize, _offset); \
Mat _mask(name.size(), CV_8UC1, Scalar::all(255)); \
_mask(Rect(_offset, name ## _roi.size())).setTo(Scalar::all(0)); \
ASSERT_EQ(name.type(), u ## name.type()); \
ASSERT_EQ(name.size(), u ## name.size()); \
EXPECT_LE(cvtest::ocl::TestUtils::checkNormRelativeSparse(name, u ## name, _mask), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
} while ((void)0, 0)
#undef EXPECT_MAT_SIMILAR
#define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \
do \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkSimilarity(mat1, mat2), eps) \
<< "Size: " << mat1.size() << std::endl; \
} while ((void)0, 0)
using perf::MatDepth;
using perf::MatType;
#define OCL_RNG_SEED 123456
struct TestUtils
{
cv::RNG rng;
TestUtils()
{
rng = cv::RNG(OCL_RNG_SEED);
}
int randomInt(int minVal, int maxVal)
{
return rng.uniform(minVal, maxVal);
}
double randomDouble(double minVal, double maxVal)
{
return rng.uniform(minVal, maxVal);
}
double randomDoubleLog(double minVal, double maxVal)
{
double logMin = log((double)minVal + 1);
double logMax = log((double)maxVal + 1);
double pow = rng.uniform(logMin, logMax);
double v = exp(pow) - 1;
CV_Assert(v >= minVal && (v < maxVal || (v == minVal && v == maxVal)));
return v;
}
Size randomSize(int minVal, int maxVal)
{
#if 1
return cv::Size((int)randomDoubleLog(minVal, maxVal), (int)randomDoubleLog(minVal, maxVal));
#else
return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
#endif
}
Size randomSize(int minValX, int maxValX, int minValY, int maxValY)
{
#if 1
return cv::Size((int)randomDoubleLog(minValX, maxValX), (int)randomDoubleLog(minValY, maxValY));
#else
return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
#endif
}
Scalar randomScalar(double minVal, double maxVal)
{
return Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
}
Mat randomMat(Size size, int type, double minVal, double maxVal, bool useRoi = false)
{
RNG dataRng(rng.next());
return cvtest::randomMat(dataRng, size, type, minVal, maxVal, useRoi);
}
struct Border
{
int top, bot, lef, rig;
};
Border randomBorder(int minValue = 0, int maxValue = MAX_VALUE)
{
Border border = {
(int)randomDoubleLog(minValue, maxValue),
(int)randomDoubleLog(minValue, maxValue),
(int)randomDoubleLog(minValue, maxValue),
(int)randomDoubleLog(minValue, maxValue)
};
return border;
}
void randomSubMat(Mat& whole, Mat& subMat, const Size& roiSize, const Border& border, int type, double minVal, double maxVal)
{
Size wholeSize = Size(roiSize.width + border.lef + border.rig, roiSize.height + border.top + border.bot);
whole = randomMat(wholeSize, type, minVal, maxVal, false);
subMat = whole(Rect(border.lef, border.top, roiSize.width, roiSize.height));
}
// If the two vectors are not equal, it will return the difference in vector size
// Else it will return (total diff of each 1 and 2 rects covered pixels)/(total 1 rects covered pixels)
// The smaller, the better matched
static double checkRectSimilarity(const cv::Size & sz, std::vector<cv::Rect>& ob1, std::vector<cv::Rect>& ob2);
//! read image from testdata folder.
static cv::Mat readImage(const String &fileName, int flags = cv::IMREAD_COLOR);
static cv::Mat readImageType(const String &fname, int type);
static double checkNorm1(InputArray m, InputArray mask = noArray());
static double checkNorm2(InputArray m1, InputArray m2, InputArray mask = noArray());
static double checkSimilarity(InputArray m1, InputArray m2);
static void showDiff(InputArray _src, InputArray _gold, InputArray _actual, double eps, bool alwaysShow);
static inline double checkNormRelative(InputArray m1, InputArray m2, InputArray mask = noArray())
{
return cvtest::norm(m1.getMat(), m2.getMat(), cv::NORM_INF, mask) /
std::max((double)std::numeric_limits<float>::epsilon(),
(double)std::max(cvtest::norm(m1.getMat(), cv::NORM_INF), cvtest::norm(m2.getMat(), cv::NORM_INF)));
}
static inline double checkNormRelativeSparse(InputArray m1, InputArray m2, InputArray mask = noArray())
{
double norm_inf = cvtest::norm(m1.getMat(), m2.getMat(), cv::NORM_INF, mask);
double norm_rel = norm_inf /
std::max((double)std::numeric_limits<float>::epsilon(),
(double)std::max(cvtest::norm(m1.getMat(), cv::NORM_INF), cvtest::norm(m2.getMat(), cv::NORM_INF)));
return std::min(norm_inf, norm_rel);
}
};
#define TEST_DECLARE_INPUT_PARAMETER(name) Mat name, name ## _roi; UMat u ## name, u ## name ## _roi
#define TEST_DECLARE_OUTPUT_PARAMETER(name) TEST_DECLARE_INPUT_PARAMETER(name)
#define UMAT_UPLOAD_INPUT_PARAMETER(name) \
do \
{ \
name.copyTo(u ## name); \
Size _wholeSize; Point ofs; name ## _roi.locateROI(_wholeSize, ofs); \
u ## name ## _roi = u ## name(Rect(ofs.x, ofs.y, name ## _roi.size().width, name ## _roi.size().height)); \
} while ((void)0, 0)
#define UMAT_UPLOAD_OUTPUT_PARAMETER(name) UMAT_UPLOAD_INPUT_PARAMETER(name)
template <typename T>
struct TSTestWithParam : public TestUtils, public ::testing::TestWithParam<T>
{
};
#undef PARAM_TEST_CASE
#define PARAM_TEST_CASE(name, ...) struct name : public ::cvtest::ocl::TSTestWithParam< testing::tuple< __VA_ARGS__ > >
#ifndef IMPLEMENT_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)
#endif // IMPLEMENT_PARAM_CLASS
#define OCL_TEST_P TEST_P
#define OCL_TEST_F(name, ...) typedef name OCL_##name; TEST_F(OCL_##name, __VA_ARGS__)
#define OCL_TEST(name, ...) TEST(OCL_##name, __VA_ARGS__)
#define OCL_OFF(...) cv::ocl::setUseOpenCL(false); __VA_ARGS__ ;
#define OCL_ON(...) cv::ocl::setUseOpenCL(true); __VA_ARGS__ ;
#define OCL_ALL_DEPTHS Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F)
#define OCL_ABSOLUTELY_ALL_DEPTHS Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32U, CV_64S, CV_64U, CV_16F, CV_16BF, CV_32F, CV_64F, CV_Bool)
//, CV_16F, CV_16BF, CV_64U, CV_64S, CV_32U)
#define OCL_ALL_DEPTHS_16F Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F, CV_16F)
#define OCL_ALL_CHANNELS Values(1, 2, 3, 4)
CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA, INTER_LINEAR_EXACT)
CV_ENUM(ThreshOp, THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV)
CV_ENUM(BorderType, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT, BORDER_WRAP, BORDER_REFLECT_101)
#define OCL_INSTANTIATE_TEST_CASE_P(prefix, test_case_name, generator) \
INSTANTIATE_TEST_CASE_P(OCL_ ## prefix, test_case_name, generator)
} } // namespace cvtest::ocl
namespace opencv_test {
namespace ocl {
using namespace cvtest::ocl;
}} // namespace
#endif // OPENCV_TS_OCL_TEST_HPP
modules/ts/include/opencv2/ts/ts_ext.hpp
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
// Copyright (C) 2014, Intel, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
#ifndef OPENCV_TS_EXT_HPP
#define OPENCV_TS_EXT_HPP
namespace cvtest {
void checkIppStatus();
extern bool skipUnstableTests;
extern bool runBigDataTests;
extern int testThreads;
extern int debugLevel; ///< 0 - no debug, 1 - basic test debug information, >1 - extra debug information
void testSetUp();
void testTearDown();
bool checkBigDataTests();
}
// check for required "opencv_test" namespace
#if !defined(CV_TEST_SKIP_NAMESPACE_CHECK) && defined(__OPENCV_BUILD)
#define CV__TEST_NAMESPACE_CHECK required_opencv_test_namespace = true;
#else
#define CV__TEST_NAMESPACE_CHECK // nothing
#endif
#define CV__TEST_INIT \
CV__TEST_NAMESPACE_CHECK \
if (setUpSkipped) \
return; \
::cvtest::testSetUp();
#define CV__TEST_CLEANUP ::cvtest::testTearDown();
#define CV__TEST_BODY_IMPL(name) \
{ \
CV__TRACE_APP_FUNCTION_NAME(name); \
try { \
CV__TEST_INIT \
Body(); \
CV__TEST_CLEANUP \
} \
catch (const cvtest::details::SkipTestExceptionBase& e) \
{ \
printf("[ SKIP ] %s\n", e.what()); \
} \
} \
#define CV__TEST_SETUP_IMPL(parent_class) { \
setUpSkipped = false; \
try { \
parent_class::SetUp(); \
} catch (const cvtest::details::SkipTestExceptionBase& e) { \
setUpSkipped = true; \
printf("[ SKIP ] %s\n", e.what()); \
} \
} \
struct SkipThisTest : public ::testing::Test {
SkipThisTest(const std::string& msg_) : msg(msg_) {}
virtual void TestBody() CV_OVERRIDE {
printf("[ SKIP ] %s\n", msg.c_str());
}
std::string msg;
};
#undef TEST
#define TEST_(test_case_name, test_name, parent_class, bodyMethodName, BODY_ATTR, BODY_IMPL) \
class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) : public parent_class {\
public:\
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {}\
private:\
bool setUpSkipped = false; \
virtual void TestBody() CV_OVERRIDE;\
virtual void bodyMethodName() BODY_ATTR;\
virtual void SetUp() CV_OVERRIDE; \
static ::testing::TestInfo* const test_info_ GTEST_ATTRIBUTE_UNUSED_;\
GTEST_DISALLOW_COPY_AND_ASSIGN_(\
GTEST_TEST_CLASS_NAME_(test_case_name, test_name));\
};\
class test_case_name##test_name##_factory : public ::testing::internal::TestFactoryBase { \
public:\
virtual ::testing::Test* CreateTest() CV_OVERRIDE { \
try { \
return new GTEST_TEST_CLASS_NAME_(test_case_name, test_name); \
} catch (const cvtest::details::SkipTestExceptionBase& e) { \
return new SkipThisTest(e.what()); \
} \
} \
};\
\
::testing::TestInfo* const GTEST_TEST_CLASS_NAME_(test_case_name, test_name)\
::test_info_ =\
::testing::internal::MakeAndRegisterTestInfo(\
#test_case_name, #test_name, NULL, NULL, \
::testing::internal::CodeLocation(__FILE__, __LINE__), \
(::testing::internal::GetTestTypeId()), \
parent_class::SetUpTestCase, \
parent_class::TearDownTestCase, \
new test_case_name##test_name##_factory);\
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() BODY_IMPL( #test_case_name "_" #test_name ) \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::SetUp() CV__TEST_SETUP_IMPL(parent_class) \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::bodyMethodName()
#define TEST(test_case_name, test_name) TEST_(test_case_name, test_name, ::testing::Test, Body,, CV__TEST_BODY_IMPL)
#define CV__TEST_BIGDATA_BODY_IMPL(name) \
{ \
if (!cvtest::checkBigDataTests()) \
{ \
return; \
} \
CV__TRACE_APP_FUNCTION_NAME(name); \
try { \
CV__TEST_INIT \
Body(); \
CV__TEST_CLEANUP \
} \
catch (const cvtest::details::SkipTestExceptionBase& e) \
{ \
printf("[ SKIP ] %s\n", e.what()); \
} \
} \
// Special type of tests which require / use or validate processing of huge amount of data (>= 2Gb)
#if defined(_M_X64) || defined(_M_ARM64) || defined(_M_ARM64EC) || defined(__x86_64__) || defined(__aarch64__)
#define BIGDATA_TEST(test_case_name, test_name) TEST_(BigData_ ## test_case_name, test_name, ::testing::Test, Body,, CV__TEST_BIGDATA_BODY_IMPL)
#else
#define BIGDATA_TEST(test_case_name, test_name) TEST_(BigData_ ## test_case_name, DISABLED_ ## test_name, ::testing::Test, Body,, CV__TEST_BIGDATA_BODY_IMPL)
#endif
#undef TEST_F
#define TEST_F(test_fixture, test_name)\
class GTEST_TEST_CLASS_NAME_(test_fixture, test_name) : public test_fixture {\
public:\
GTEST_TEST_CLASS_NAME_(test_fixture, test_name)() {}\
private:\
bool setUpSkipped = false; \
virtual void TestBody() CV_OVERRIDE;\
virtual void Body(); \
virtual void SetUp() CV_OVERRIDE; \
static ::testing::TestInfo* const test_info_ GTEST_ATTRIBUTE_UNUSED_;\
GTEST_DISALLOW_COPY_AND_ASSIGN_(\
GTEST_TEST_CLASS_NAME_(test_fixture, test_name));\
};\
class test_fixture##test_name##_factory : public ::testing::internal::TestFactoryBase { \
public:\
virtual ::testing::Test* CreateTest() CV_OVERRIDE { \
try { \
return new GTEST_TEST_CLASS_NAME_(test_fixture, test_name); \
} catch (const cvtest::details::SkipTestExceptionBase& e) { \
return new SkipThisTest(e.what()); \
} \
} \
};\
\
::testing::TestInfo* const GTEST_TEST_CLASS_NAME_(test_fixture, test_name)\
::test_info_ =\
::testing::internal::MakeAndRegisterTestInfo(\
#test_fixture, #test_name, NULL, NULL, \
::testing::internal::CodeLocation(__FILE__, __LINE__), \
(::testing::internal::GetTypeId<test_fixture>()), \
test_fixture::SetUpTestCase, \
test_fixture::TearDownTestCase, \
new test_fixture##test_name##_factory);\
void GTEST_TEST_CLASS_NAME_(test_fixture, test_name)::TestBody() CV__TEST_BODY_IMPL( #test_fixture "_" #test_name ) \
void GTEST_TEST_CLASS_NAME_(test_fixture, test_name)::SetUp() CV__TEST_SETUP_IMPL(test_fixture) \
void GTEST_TEST_CLASS_NAME_(test_fixture, test_name)::Body()
// Don't use directly
#define CV__TEST_P(test_case_name, test_name, bodyMethodName, BODY_ATTR, BODY_IMPL/*(name_str)*/) \
class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) \
: public test_case_name { \
public: \
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {} \
private: \
bool setUpSkipped = false; \
virtual void bodyMethodName() BODY_ATTR; \
virtual void TestBody() CV_OVERRIDE; \
virtual void SetUp() CV_OVERRIDE; \
static int AddToRegistry() { \
::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
GetTestCasePatternHolder<test_case_name>(\
#test_case_name, \
::testing::internal::CodeLocation(\
__FILE__, __LINE__))->AddTestPattern(\
#test_case_name, \
#test_name, \
new ::testing::internal::TestMetaFactory< \
GTEST_TEST_CLASS_NAME_(\
test_case_name, test_name)>()); \
return 0; \
} \
static int gtest_registering_dummy_ GTEST_ATTRIBUTE_UNUSED_; \
GTEST_DISALLOW_COPY_AND_ASSIGN_(\
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)); \
}; \
int GTEST_TEST_CLASS_NAME_(test_case_name, \
test_name)::gtest_registering_dummy_ = \
GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::AddToRegistry(); \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() BODY_IMPL( #test_case_name "_" #test_name ) \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::SetUp() CV__TEST_SETUP_IMPL(test_case_name) \
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::bodyMethodName()
#undef TEST_P
#define TEST_P(test_case_name, test_name) CV__TEST_P(test_case_name, test_name, Body,, CV__TEST_BODY_IMPL)
#define CV_TEST_EXPECT_EXCEPTION_MESSAGE(statement, msg) \
GTEST_AMBIGUOUS_ELSE_BLOCKER_ \
if (::testing::internal::AlwaysTrue()) { \
const char* msg_ = msg; \
bool hasException = false; \
try { \
GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \
} \
catch (const cv::Exception& e) { \
if (NULL == strstr(e.what(), msg_)) \
ADD_FAILURE() << "Unexpected cv::Exception is raised: " << #statement << "\n Expected message substring: '" << msg_ << "'. Actual message:\n" << e.what(); \
hasException = true; \
} \
catch (const std::exception& e) { \
ADD_FAILURE() << "Unexpected std::exception is raised: " << #statement << "\n" << e.what(); \
hasException = true; \
} \
catch (...) { \
ADD_FAILURE() << "Unexpected C++ exception is raised: " << #statement; \
hasException = true; \
} \
if (!hasException) { \
goto GTEST_CONCAT_TOKEN_(gtest_label_test_, __LINE__); \
} \
} else \
GTEST_CONCAT_TOKEN_(gtest_label_test_, __LINE__): \
ADD_FAILURE() << "Failed: Expected: " #statement " throws an '" << msg << "' exception.\n" \
" Actual: it doesn't."
#endif // OPENCV_TS_EXT_HPP
modules/ts/include/opencv2/ts/ts_gtest.h
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modules/ts/include/opencv2/ts/ts_perf.hpp
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#ifndef OPENCV_TS_PERF_HPP
#define OPENCV_TS_PERF_HPP
#include "opencv2/ts.hpp"
#include "ts_ext.hpp"
#include <functional>
#if !(defined(LOGD) || defined(LOGI) || defined(LOGW) || defined(LOGE))
# if defined(__ANDROID__) && defined(USE_ANDROID_LOGGING)
# include <android/log.h>
# define PERF_TESTS_LOG_TAG "OpenCV_perf"
# define LOGD(...) ((void)__android_log_print(ANDROID_LOG_DEBUG, PERF_TESTS_LOG_TAG, __VA_ARGS__))
# define LOGI(...) ((void)__android_log_print(ANDROID_LOG_INFO, PERF_TESTS_LOG_TAG, __VA_ARGS__))
# define LOGW(...) ((void)__android_log_print(ANDROID_LOG_WARN, PERF_TESTS_LOG_TAG, __VA_ARGS__))
# define LOGE(...) ((void)__android_log_print(ANDROID_LOG_ERROR, PERF_TESTS_LOG_TAG, __VA_ARGS__))
# else
# define LOGD(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
# define LOGI(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
# define LOGW(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
# define LOGE(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
# endif
#endif
// declare major namespaces to avoid errors on unknown namespace
namespace cv { namespace cuda {} namespace ocl {} }
namespace cvtest { }
namespace perf
{
// Tuple stuff from Google Tests
using testing::get;
using testing::make_tuple;
using testing::tuple;
using testing::tuple_size;
using testing::tuple_element;
class TestBase;
/*****************************************************************************************\
* Predefined typical frame sizes and typical test parameters *
\*****************************************************************************************/
const static cv::Size szQVGA = cv::Size(320, 240);
const static cv::Size szVGA = cv::Size(640, 480);
const static cv::Size szSVGA = cv::Size(800, 600);
const static cv::Size szXGA = cv::Size(1024, 768);
const static cv::Size szSXGA = cv::Size(1280, 1024);
const static cv::Size szWQHD = cv::Size(2560, 1440);
const static cv::Size sznHD = cv::Size(640, 360);
const static cv::Size szqHD = cv::Size(960, 540);
const static cv::Size sz240p = szQVGA;
const static cv::Size sz720p = cv::Size(1280, 720);
const static cv::Size sz1080p = cv::Size(1920, 1080);
const static cv::Size sz1440p = szWQHD;
const static cv::Size sz2160p = cv::Size(3840, 2160);//UHDTV1 4K
const static cv::Size sz4320p = cv::Size(7680, 4320);//UHDTV2 8K
const static cv::Size sz3MP = cv::Size(2048, 1536);
const static cv::Size sz5MP = cv::Size(2592, 1944);
const static cv::Size sz2K = cv::Size(2048, 2048);
const static cv::Size szODD = cv::Size(127, 61);
const static cv::Size szSmall24 = cv::Size(24, 24);
const static cv::Size szSmall32 = cv::Size(32, 32);
const static cv::Size szSmall64 = cv::Size(64, 64);
const static cv::Size szSmall128 = cv::Size(128, 128);
#define SZ_ALL_VGA ::testing::Values(::perf::szQVGA, ::perf::szVGA, ::perf::szSVGA)
#define SZ_ALL_GA ::testing::Values(::perf::szQVGA, ::perf::szVGA, ::perf::szSVGA, ::perf::szXGA, ::perf::szSXGA)
#define SZ_ALL_HD ::testing::Values(::perf::sznHD, ::perf::szqHD, ::perf::sz720p, ::perf::sz1080p)
#define SZ_ALL_SMALL ::testing::Values(::perf::szSmall24, ::perf::szSmall32, ::perf::szSmall64, ::perf::szSmall128)
#define SZ_ALL ::testing::Values(::perf::szQVGA, ::perf::szVGA, ::perf::szSVGA, ::perf::szXGA, ::perf::szSXGA, ::perf::sznHD, ::perf::szqHD, ::perf::sz720p, ::perf::sz1080p)
#define SZ_TYPICAL ::testing::Values(::perf::szVGA, ::perf::szqHD, ::perf::sz720p, ::perf::szODD)
#define TYPICAL_MAT_SIZES ::perf::szVGA, ::perf::sz720p, ::perf::sz1080p, ::perf::szODD
#define TYPICAL_MAT_TYPES CV_8UC1, CV_8UC4, CV_32FC1
#define TYPICAL_MATS testing::Combine( testing::Values( TYPICAL_MAT_SIZES ), testing::Values( TYPICAL_MAT_TYPES ) )
#define TYPICAL_MATS_C1 testing::Combine( testing::Values( TYPICAL_MAT_SIZES ), testing::Values( CV_8UC1, CV_32FC1 ) )
#define TYPICAL_MATS_C4 testing::Combine( testing::Values( TYPICAL_MAT_SIZES ), testing::Values( CV_8UC4 ) )
/*****************************************************************************************\
* MatType - printable wrapper over integer 'type' of Mat *
\*****************************************************************************************/
class MatType
{
public:
MatType(int val=0) : _type(val) {}
operator int() const {return _type;}
private:
int _type;
};
/*****************************************************************************************\
* CV_ENUM and CV_FLAGS - macro to create printable wrappers for defines and enums *
\*****************************************************************************************/
#define CV_ENUM(class_name, ...) \
namespace { \
using namespace cv;using namespace cv::cuda; using namespace cv::ocl; \
struct class_name { \
class_name(int val = 0) : val_(val) {} \
operator int() const { return val_; } \
void PrintTo(std::ostream* os) const { \
const int vals[] = { __VA_ARGS__ }; \
const char* svals = #__VA_ARGS__; \
for(int i = 0, pos = 0; i < (int)(sizeof(vals)/sizeof(int)); ++i) { \
while(isspace(svals[pos]) || svals[pos] == ',') ++pos; \
int start = pos; \
while(!(isspace(svals[pos]) || svals[pos] == ',' || svals[pos] == 0)) \
++pos; \
if (val_ == vals[i]) { \
*os << std::string(svals + start, svals + pos); \
return; \
} \
} \
*os << "UNKNOWN"; \
} \
static ::testing::internal::ParamGenerator<class_name> all() { \
const class_name vals[] = { __VA_ARGS__ }; \
return ::testing::ValuesIn(vals); \
} \
private: int val_; \
}; \
static inline void PrintTo(const class_name& t, std::ostream* os) { t.PrintTo(os); } }
#define CV_FLAGS(class_name, ...) \
namespace { \
struct class_name { \
class_name(int val = 0) : val_(val) {} \
operator int() const { return val_; } \
void PrintTo(std::ostream* os) const { \
using namespace cv;using namespace cv::cuda; using namespace cv::ocl; \
const int vals[] = { __VA_ARGS__ }; \
const char* svals = #__VA_ARGS__; \
int value = val_; \
bool first = true; \
for(int i = 0, pos = 0; i < (int)(sizeof(vals)/sizeof(int)); ++i) { \
while(isspace(svals[pos]) || svals[pos] == ',') ++pos; \
int start = pos; \
while(!(isspace(svals[pos]) || svals[pos] == ',' || svals[pos] == 0)) \
++pos; \
if ((value & vals[i]) == vals[i]) { \
value &= ~vals[i]; \
if (first) first = false; else *os << "|"; \
*os << std::string(svals + start, svals + pos); \
if (!value) return; \
} \
} \
if (first) *os << "UNKNOWN"; \
} \
private: int val_; \
}; \
static inline void PrintTo(const class_name& t, std::ostream* os) { t.PrintTo(os); } }
CV_ENUM(MatDepth, CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F, CV_16F, \
CV_16BF, CV_Bool, CV_64U, CV_64S, CV_32U)
/*****************************************************************************************\
* Regression control utility for performance testing *
\*****************************************************************************************/
enum ERROR_TYPE
{
ERROR_ABSOLUTE = 0,
ERROR_RELATIVE = 1
};
class Regression
{
public:
static Regression& add(TestBase* test, const std::string& name, cv::InputArray array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
static Regression& addMoments(TestBase* test, const std::string& name, const cv::Moments & array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
static Regression& addKeypoints(TestBase* test, const std::string& name, const std::vector<cv::KeyPoint>& array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
static Regression& addMatches(TestBase* test, const std::string& name, const std::vector<cv::DMatch>& array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
static void Init(const std::string& testSuitName, const std::string& ext = ".xml");
Regression& operator() (const std::string& name, cv::InputArray array, double eps = DBL_EPSILON, ERROR_TYPE err = ERROR_ABSOLUTE);
private:
static Regression& instance();
Regression();
~Regression();
Regression(const Regression&);
Regression& operator=(const Regression&);
cv::RNG regRNG;//own random numbers generator to make collection and verification work identical
std::string storageInPath;
std::string storageOutPath;
cv::FileStorage storageIn;
cv::FileStorage storageOut;
cv::FileNode rootIn;
std::string currentTestNodeName;
std::string suiteName;
cv::FileStorage& write();
static std::string getCurrentTestNodeName();
static bool isVector(cv::InputArray a);
static double getElem(cv::Mat& m, int x, int y, int cn = 0);
void init(const std::string& testSuitName, const std::string& ext);
void write(cv::InputArray array);
void write(cv::Mat m);
void verify(cv::FileNode node, cv::InputArray array, double eps, ERROR_TYPE err);
void verify(cv::FileNode node, cv::Mat actual, double eps, std::string argname, ERROR_TYPE err);
};
#define SANITY_CHECK(array, ...) ::perf::Regression::add(this, #array, array , ## __VA_ARGS__)
#define SANITY_CHECK_MOMENTS(array, ...) ::perf::Regression::addMoments(this, #array, array , ## __VA_ARGS__)
#define SANITY_CHECK_KEYPOINTS(array, ...) ::perf::Regression::addKeypoints(this, #array, array , ## __VA_ARGS__)
#define SANITY_CHECK_MATCHES(array, ...) ::perf::Regression::addMatches(this, #array, array , ## __VA_ARGS__)
#define SANITY_CHECK_NOTHING() this->setVerified()
class GpuPerf
{
public:
static bool targetDevice();
};
#define PERF_RUN_CUDA() ::perf::GpuPerf::targetDevice()
/*****************************************************************************************\
* Container for performance metrics *
\*****************************************************************************************/
typedef struct performance_metrics
{
size_t bytesIn;
size_t bytesOut;
unsigned int samples;
unsigned int outliers;
double gmean;
double gstddev;//stddev for log(time)
double mean;
double stddev;
double median;
double min;
double frequency;
int terminationReason;
enum
{
TERM_ITERATIONS = 0,
TERM_TIME = 1,
TERM_INTERRUPT = 2,
TERM_EXCEPTION = 3,
TERM_SKIP_TEST = 4, // there are some limitations and test should be skipped
TERM_UNKNOWN = -1
};
performance_metrics();
void clear();
} performance_metrics;
/*****************************************************************************************\
* Strategy for performance measuring *
\*****************************************************************************************/
enum PERF_STRATEGY
{
PERF_STRATEGY_DEFAULT = -1,
PERF_STRATEGY_BASE = 0,
PERF_STRATEGY_SIMPLE = 1
};
/*****************************************************************************************\
* Base fixture for performance tests *
\*****************************************************************************************/
#ifdef CV_COLLECT_IMPL_DATA
// Implementation collection processing class.
// Accumulates and shapes implementation data.
typedef struct ImplData
{
bool ipp;
bool icv;
bool ipp_mt;
bool ocl;
bool plain;
std::vector<int> implCode;
std::vector<cv::String> funName;
ImplData()
{
Reset();
}
void Reset()
{
cv::setImpl(0);
ipp = icv = ocl = ipp_mt = false;
implCode.clear();
funName.clear();
}
void GetImpl()
{
flagsToVars(cv::getImpl(implCode, funName));
}
std::vector<cv::String> GetCallsForImpl(int impl)
{
std::vector<cv::String> out;
for(int i = 0; i < (int)implCode.size(); i++)
{
if(impl == implCode[i])
out.push_back(funName[i]);
}
return out;
}
// Remove duplicate entries
void ShapeUp()
{
std::vector<int> savedCode;
std::vector<cv::String> savedName;
for(int i = 0; i < (int)implCode.size(); i++)
{
bool match = false;
for(int j = 0; j < (int)savedCode.size(); j++)
{
if(implCode[i] == savedCode[j] && !funName[i].compare(savedName[j]))
{
match = true;
break;
}
}
if(!match)
{
savedCode.push_back(implCode[i]);
savedName.push_back(funName[i]);
}
}
implCode = savedCode;
funName = savedName;
}
// convert flags register to more handy variables
void flagsToVars(int flags)
{
#if defined(HAVE_IPP_ICV)
ipp = 0;
icv = ((flags&CV_IMPL_IPP) > 0);
#else
ipp = ((flags&CV_IMPL_IPP) > 0);
icv = 0;
#endif
ipp_mt = ((flags&CV_IMPL_MT) > 0);
ocl = ((flags&CV_IMPL_OCL) > 0);
plain = (flags == 0);
}
} ImplData;
#endif
#ifdef ENABLE_INSTRUMENTATION
class InstumentData
{
public:
static ::cv::String treeToString();
static void printTree();
};
#endif
class TestBase: public ::testing::Test
{
public:
TestBase();
static void Init(int argc, const char* const argv[]);
static void Init(const std::vector<std::string> & availableImpls,
int argc, const char* const argv[]);
static void RecordRunParameters();
static std::string getDataPath(const std::string& relativePath);
static std::string getSelectedImpl();
static enum PERF_STRATEGY getCurrentModulePerformanceStrategy();
static enum PERF_STRATEGY setModulePerformanceStrategy(enum PERF_STRATEGY strategy);
class PerfSkipTestException: public cvtest::SkipTestException
{
public:
int dummy; // workaround for MacOSX Xcode 7.3 bug (don't make class "empty")
PerfSkipTestException() : dummy(0) {}
};
protected:
virtual void PerfTestBody() = 0;
virtual void SetUp() CV_OVERRIDE;
virtual void TearDown() CV_OVERRIDE;
bool startTimer(); // bool is dummy for conditional loop
void stopTimer();
bool next();
PERF_STRATEGY getCurrentPerformanceStrategy() const;
enum WarmUpType
{
WARMUP_READ,
WARMUP_WRITE,
WARMUP_RNG,
WARMUP_NONE
};
void reportMetrics(bool toJUnitXML = false);
static void warmup(cv::InputOutputArray a, WarmUpType wtype = WARMUP_READ);
performance_metrics& calcMetrics();
void RunPerfTestBody();
#ifdef CV_COLLECT_IMPL_DATA
ImplData implConf;
#endif
#ifdef ENABLE_INSTRUMENTATION
InstumentData instrConf;
#endif
private:
typedef std::vector<std::pair<int, cv::Size> > SizeVector;
typedef std::vector<int64> TimeVector;
SizeVector inputData;
SizeVector outputData;
unsigned int getTotalInputSize() const;
unsigned int getTotalOutputSize() const;
enum PERF_STRATEGY testStrategy;
TimeVector times;
int64 lastTime;
int64 totalTime;
int64 timeLimit;
static int64 timeLimitDefault;
static unsigned int iterationsLimitDefault;
unsigned int minIters;
unsigned int nIters;
unsigned int currentIter;
unsigned int runsPerIteration;
unsigned int perfValidationStage;
performance_metrics metrics;
void validateMetrics();
static void warmup_impl(cv::Mat m, WarmUpType wtype);
static int getSizeInBytes(cv::InputArray a);
static cv::Size getSize(cv::InputArray a);
static void declareArray(SizeVector& sizes, cv::InputOutputArray a, WarmUpType wtype);
class _declareHelper
{
public:
_declareHelper& in(cv::InputOutputArray a1, WarmUpType wtype = WARMUP_READ);
_declareHelper& in(cv::InputOutputArray a1, cv::InputOutputArray a2, WarmUpType wtype = WARMUP_READ);
_declareHelper& in(cv::InputOutputArray a1, cv::InputOutputArray a2, cv::InputOutputArray a3, WarmUpType wtype = WARMUP_READ);
_declareHelper& in(cv::InputOutputArray a1, cv::InputOutputArray a2, cv::InputOutputArray a3, cv::InputOutputArray a4, WarmUpType wtype = WARMUP_READ);
_declareHelper& out(cv::InputOutputArray a1, WarmUpType wtype = WARMUP_WRITE);
_declareHelper& out(cv::InputOutputArray a1, cv::InputOutputArray a2, WarmUpType wtype = WARMUP_WRITE);
_declareHelper& out(cv::InputOutputArray a1, cv::InputOutputArray a2, cv::InputOutputArray a3, WarmUpType wtype = WARMUP_WRITE);
_declareHelper& out(cv::InputOutputArray a1, cv::InputOutputArray a2, cv::InputOutputArray a3, cv::InputOutputArray a4, WarmUpType wtype = WARMUP_WRITE);
_declareHelper& iterations(unsigned int n);
_declareHelper& time(double timeLimitSecs);
_declareHelper& tbb_threads(int n = -1);
_declareHelper& runs(unsigned int runsNumber);
_declareHelper& strategy(enum PERF_STRATEGY s);
private:
TestBase* test;
_declareHelper(TestBase* t);
_declareHelper(const _declareHelper&);
_declareHelper& operator=(const _declareHelper&);
friend class TestBase;
};
friend class _declareHelper;
bool verified;
public:
_declareHelper declare;
void setVerified() { this->verified = true; }
};
template<typename T> class TestBaseWithParam: public TestBase, public ::testing::WithParamInterface<T> {};
typedef tuple<cv::Size, MatType> Size_MatType_t;
typedef TestBaseWithParam<Size_MatType_t> Size_MatType;
/*****************************************************************************************\
* Print functions for googletest *
\*****************************************************************************************/
void PrintTo(const MatType& t, std::ostream* os);
} //namespace perf
namespace cv
{
void PrintTo(const String& str, ::std::ostream* os);
void PrintTo(const Size& sz, ::std::ostream* os);
} //namespace cv
/*****************************************************************************************\
* Macro definitions for performance tests *
\*****************************************************************************************/
#define CV__PERF_TEST_BODY_IMPL(name) \
{ \
CV__TEST_NAMESPACE_CHECK \
CV__TRACE_APP_FUNCTION_NAME("PERF_TEST: " name); \
try { \
::cvtest::testSetUp(); \
RunPerfTestBody(); \
} \
catch (cvtest::details::SkipTestExceptionBase& e) \
{ \
printf("[ SKIP ] %s\n", e.what()); \
} \
::cvtest::testTearDown(); \
}
#define PERF_PROXY_NAMESPACE_NAME_(test_case_name, test_name) \
test_case_name##_##test_name##_perf_namespace_proxy
// Defines a performance test.
//
// The first parameter is the name of the test case, and the second
// parameter is the name of the test within the test case.
//
// The user should put his test code between braces after using this
// macro. Example:
//
// PERF_TEST(FooTest, InitializesCorrectly) {
// Foo foo;
// EXPECT_TRUE(foo.StatusIsOK());
// }
#define PERF_TEST(test_case_name, test_name)\
TEST_(test_case_name, test_name, ::perf::TestBase, PerfTestBody, CV_OVERRIDE, CV__PERF_TEST_BODY_IMPL)
// Defines a performance test that uses a test fixture.
//
// The first parameter is the name of the test fixture class, which
// also doubles as the test case name. The second parameter is the
// name of the test within the test case.
//
// A test fixture class must be declared earlier. The user should put
// his test code between braces after using this macro. Example:
//
// class FooTest : public ::perf::TestBase {
// protected:
// virtual void SetUp() { TestBase::SetUp(); b_.AddElement(3); }
//
// Foo a_;
// Foo b_;
// };
//
// PERF_TEST_F(FooTest, InitializesCorrectly) {
// EXPECT_TRUE(a_.StatusIsOK());
// }
//
// PERF_TEST_F(FooTest, ReturnsElementCountCorrectly) {
// EXPECT_EQ(0, a_.size());
// EXPECT_EQ(1, b_.size());
// }
#define PERF_TEST_F(fixture, testname) \
namespace PERF_PROXY_NAMESPACE_NAME_(fixture, testname) {\
class TestBase {/*compile error for this class means that you are trying to use perf::TestBase as a fixture*/};\
class fixture : public ::fixture {\
public:\
fixture() {}\
protected:\
virtual void PerfTestBody() CV_OVERRIDE;\
};\
TEST_F(fixture, testname){ CV__PERF_TEST_BODY_IMPL(#fixture "_" #testname); }\
}\
void PERF_PROXY_NAMESPACE_NAME_(fixture, testname)::fixture::PerfTestBody()
// Defines a parametrized performance test.
//
// @Note PERF_TEST_P() below violates behavior of original Google Tests - there is no tests instantiation in original TEST_P()
// This macro is intended for usage with separate INSTANTIATE_TEST_CASE_P macro
#define PERF_TEST_P_(test_case_name, test_name) CV__TEST_P(test_case_name, test_name, PerfTestBody, CV_OVERRIDE, CV__PERF_TEST_BODY_IMPL)
// Defines a parametrized performance test.
//
// @Note Original TEST_P() macro doesn't instantiate tests with parameters. To keep original usage use PERF_TEST_P_() macro
//
// The first parameter is the name of the test fixture class, which
// also doubles as the test case name. The second parameter is the
// name of the test within the test case.
//
// The user should put his test code between braces after using this
// macro. Example:
//
// typedef ::perf::TestBaseWithParam<cv::Size> FooTest;
//
// PERF_TEST_P(FooTest, DoTestingRight, ::testing::Values(::perf::szVGA, ::perf::sz720p) {
// cv::Mat b(GetParam(), CV_8U, cv::Scalar(10));
// cv::Mat a(GetParam(), CV_8U, cv::Scalar(20));
// cv::Mat c(GetParam(), CV_8U, cv::Scalar(0));
//
// declare.in(a, b).out(c).time(0.5);
//
// TEST_CYCLE() cv::add(a, b, c);
//
// SANITY_CHECK(c);
// }
#define PERF_TEST_P(fixture, name, params) \
class fixture##_##name : public fixture {\
public:\
fixture##_##name() {}\
protected:\
virtual void PerfTestBody() CV_OVERRIDE;\
};\
CV__TEST_P(fixture##_##name, name, PerfTestBodyDummy,, CV__PERF_TEST_BODY_IMPL){} \
INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\
void fixture##_##name::PerfTestBody()
#ifndef __CV_TEST_EXEC_ARGS
#if defined(_MSC_VER) && (_MSC_VER <= 1400)
#define __CV_TEST_EXEC_ARGS(...) \
while (++argc >= (--argc,-1)) {__VA_ARGS__; break;} /*this ugly construction is needed for VS 2005*/
#else
#define __CV_TEST_EXEC_ARGS(...) \
__VA_ARGS__;
#endif
#endif
#define CV_PERF_TEST_MAIN_INTERNALS(modulename, impls, ...) \
CV_TRACE_FUNCTION(); \
{ CV_TRACE_REGION("INIT"); \
::perf::Regression::Init(#modulename); \
::perf::TestBase::Init(std::vector<std::string>(impls, impls + sizeof impls / sizeof *impls), \
argc, argv); \
::testing::InitGoogleTest(&argc, argv); \
::testing::UnitTest::GetInstance()->listeners().Append(new cvtest::SystemInfoCollector); \
::testing::Test::RecordProperty("cv_module_name", #modulename); \
::perf::TestBase::RecordRunParameters(); \
__CV_TEST_EXEC_ARGS(__VA_ARGS__) \
} \
return RUN_ALL_TESTS();
// impls must be an array, not a pointer; "plain" should always be one of the implementations
#define CV_PERF_TEST_MAIN_WITH_IMPLS(modulename, impls, ...) \
int main(int argc, char **argv)\
{\
CV_PERF_TEST_MAIN_INTERNALS(modulename, impls, __VA_ARGS__)\
}
#define CV_PERF_TEST_MAIN(modulename, ...) \
int main(int argc, char **argv)\
{\
const char * plain_only[] = { "plain" };\
CV_PERF_TEST_MAIN_INTERNALS(modulename, plain_only, __VA_ARGS__)\
}
//! deprecated
#define TEST_CYCLE_N(n) for(declare.iterations(n); next() && startTimer(); stopTimer())
//! deprecated
#define TEST_CYCLE() for(; next() && startTimer(); stopTimer())
//! deprecated
#define TEST_CYCLE_MULTIRUN(runsNum) for(declare.runs(runsNum); next() && startTimer(); stopTimer()) for(int r = 0; r < runsNum; ++r)
#define PERF_SAMPLE_BEGIN() \
for(; next() && startTimer(); stopTimer()) \
{ \
CV_TRACE_REGION("iteration");
#define PERF_SAMPLE_END() \
}
namespace perf
{
namespace comparators
{
template<typename T>
struct RectLess_
{
bool operator()(const cv::Rect_<T>& r1, const cv::Rect_<T>& r2) const
{
return r1.x < r2.x ||
(r1.x == r2.x && r1.y < r2.y) ||
(r1.x == r2.x && r1.y == r2.y && r1.width < r2.width) ||
(r1.x == r2.x && r1.y == r2.y && r1.width == r2.width && r1.height < r2.height);
}
};
typedef RectLess_<int> RectLess;
struct KeypointGreater
{
bool operator()(const cv::KeyPoint& kp1, const cv::KeyPoint& kp2) const
{
if (kp1.response > kp2.response) return true;
if (kp1.response < kp2.response) return false;
if (kp1.size > kp2.size) return true;
if (kp1.size < kp2.size) return false;
if (kp1.octave > kp2.octave) return true;
if (kp1.octave < kp2.octave) return false;
if (kp1.pt.y < kp2.pt.y) return false;
if (kp1.pt.y > kp2.pt.y) return true;
return kp1.pt.x < kp2.pt.x;
}
};
} //namespace comparators
void sort(std::vector<cv::KeyPoint>& pts, cv::InputOutputArray descriptors);
} //namespace perf
#endif //OPENCV_TS_PERF_HPP