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fixed gpu::filter2D border interpolation for CV_32FC1 type

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added additional tests for gpu filters
fixed gpu features2D tests
This commit is contained in:
Vladislav Vinogradov
2012-03-21 14:38:23 +00:00
parent c1a6cb6221
commit 059cef57e6
16 changed files with 1730 additions and 1515 deletions
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263
modules/gpu/test/utility.hpp
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@@ -42,37 +42,66 @@
#ifndef __OPENCV_TEST_UTILITY_HPP__
#define __OPENCV_TEST_UTILITY_HPP__
#include <vector>
#include <string>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.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);
void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
//////////////////////////////////////////////////////////////////////
// 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::gpu::DeviceInfo& info, cv::gpu::FeatureSet feature);
//! return all devices compatible with current gpu module build.
const std::vector<cv::gpu::DeviceInfo>& devices();
//! return all devices compatible with current gpu module build which support specified feature.
std::vector<cv::gpu::DeviceInfo> 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);
#define ALL_DEVICES testing::ValuesIn(devices())
#define DEVICES(feature) testing::ValuesIn(devices(feature))
//////////////////////////////////////////////////////////////////////
// Additional assertion
cv::Mat getMat(cv::InputArray arr);
double checkNorm(cv::InputArray m1, cv::InputArray m2);
#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkNorm(mat1, mat2), eps); \
}
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) \
{ \
@@ -81,6 +110,37 @@ double checkNorm(cv::InputArray m1, cv::InputArray m2);
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);
@@ -90,94 +150,35 @@ double checkSimilarity(cv::InputArray m1, cv::InputArray m2);
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);
}}
using perf::MatDepth;
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();
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))
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))
CV_ENUM(CmpCode, cv::CMP_EQ, cv::CMP_GT, cv::CMP_GE, cv::CMP_LT, cv::CMP_LE, cv::CMP_NE)
#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))
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)
#define ALL_FLIP_CODES testing::Values(FlipCode(FLIP_BOTH), FlipCode(FLIP_X), FlipCode(FLIP_Y))
CV_ENUM(ReduceCode, CV_REDUCE_SUM, CV_REDUCE_AVG, CV_REDUCE_MAX, CV_REDUCE_MIN)
#define ALL_REDUCE_CODES testing::Values(ReduceCode(CV_REDUCE_SUM), ReduceCode(CV_REDUCE_AVG), ReduceCode(CV_REDUCE_MAX), ReduceCode(CV_REDUCE_MIN))
CV_FLAGS(GemmFlags, 0, cv::GEMM_1_T, cv::GEMM_2_T, cv::GEMM_3_T);
#define ALL_GEMM_FLAGS testing::Values(GemmFlags(0), GemmFlags(cv::GEMM_1_T), GemmFlags(cv::GEMM_2_T), GemmFlags(cv::GEMM_3_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_2_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_3_T), 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)
#define ALL_THRESH_OPS testing::Values(ThreshOp(cv::THRESH_BINARY), ThreshOp(cv::THRESH_BINARY_INV), ThreshOp(cv::THRESH_TRUNC), ThreshOp(cv::THRESH_TOZERO), ThreshOp(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))
// Depth
using perf::MatDepth;
//! return vector with depths from specified range.
std::vector<MatDepth> 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)), \
@@ -204,4 +205,88 @@ CV_FLAGS(DftFlags, cv::DFT_INVERSE, cv::DFT_SCALE, cv::DFT_ROWS, cv::DFT_COMPLEX
\
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 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 << "(" << 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_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__