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C++

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// License Agreement
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//
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#ifndef __OPENCV_TS_OCL_TEST_HPP__
#define __OPENCV_TS_OCL_TEST_HPP__
#include "cvconfig.h" // to get definition of HAVE_OPENCL
#include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCL
#include "opencv2/ts.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/types_c.h"
#include "opencv2/core/ocl.hpp"
namespace cvtest {
namespace ocl {
using namespace cv;
using namespace testing;
namespace traits {
template <typename T>
struct GetMatForRead
{
};
template <>
struct GetMatForRead<Mat>
{
static const Mat get(const Mat& m) { return m; }
};
template <>
struct GetMatForRead<UMat>
{
static const Mat get(const UMat& m) { return m.getMat(ACCESS_READ); }
};
} // namespace traits
template <typename T>
const Mat getMatForRead(const T& mat)
{
return traits::GetMatForRead<T>::get(mat);
}
extern int test_loop_times;
#define MAX_VALUE 357
#define EXPECT_MAT_NORM(mat, eps) \
{ \
EXPECT_LE(checkNorm(mat), eps) \
}
#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) \
<< cv::format("Size: %d x %d", mat1.size().width, mat1.size().height) << std::endl; \
}
#define EXPECT_MAT_NEAR_RELATIVE(mat1, mat2, eps) \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkNormRelative(mat1, mat2), eps) \
<< cv::format("Size: %d x %d", mat1.size().width, mat1.size().height) << std::endl; \
}
#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); \
<< cv::format("Size: %d x %d", mat1.size().width, mat1.size().height) << std::endl; \
}
using perf::MatDepth;
using perf::MatType;
#define OCL_RNG_SEED 123456
struct CV_EXPORTS 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(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 checkNorm(const cv::Mat &m);
static double checkNorm(const cv::Mat &m1, const cv::Mat &m2);
static double checkSimilarity(const cv::Mat &m1, const cv::Mat &m2);
static inline double checkNormRelative(const Mat &m1, const Mat &m2)
{
return cv::norm(m1, m2, cv::NORM_INF) /
std::max((double)std::numeric_limits<float>::epsilon(),
(double)std::max(cv::norm(m1, cv::NORM_INF), norm(m2, cv::NORM_INF)));
}
static void showDiff(const Mat& src, const Mat& gold, const Mat& actual, double eps, bool alwaysShow = false);
template <typename T1>
static double checkNorm(const T1& m)
{
return checkNorm(getMatForRead(m));
}
template <typename T1, typename T2>
static double checkNorm(const T1& m1, const T2& m2)
{
return checkNorm(getMatForRead(m1), getMatForRead(m2));
}
template <typename T1, typename T2>
static double checkSimilarity(const T1& m1, const T2& m2)
{
return checkSimilarity(getMatForRead(m1), getMatForRead(m2));
}
template <typename T1, typename T2>
static inline double checkNormRelative(const T1& m1, const T2& m2)
{
const Mat _m1 = getMatForRead(m1);
const Mat _m2 = getMatForRead(m2);
return checkNormRelative(_m1, _m2);
}
template <typename T1, typename T2, typename T3>
static void showDiff(const T1& src, const T2& gold, const T3& actual, double eps, bool alwaysShow = false)
{
const Mat _src = getMatForRead(src);
const Mat _gold = getMatForRead(gold);
const Mat _actual = getMatForRead(actual);
showDiff(_src, _gold, _actual, eps, alwaysShow);
}
};
#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) \
{ \
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)); \
}
#define UMAT_UPLOAD_OUTPUT_PARAMETER(name) UMAT_UPLOAD_INPUT_PARAMETER(name)
template <typename T>
struct CV_EXPORTS TSTestWithParam : public TestUtils, public ::testing::TestWithParam<T>
{
};
#define PARAM_TEST_CASE(name, ...) struct name : public TSTestWithParam< std::tr1::tuple< __VA_ARGS__ > >
#define GET_PARAM(k) std::tr1::get< k >(GetParam())
#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_OFF(fn) cv::ocl::setUseOpenCL(false); fn
#define OCL_ON(fn) cv::ocl::setUseOpenCL(true); fn
#define OCL_ALL_DEPTHS Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F)
#define OCL_ALL_CHANNELS Values(1, 2, 3, 4)
CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
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
#endif // HAVE_OPENCL
#endif // __OPENCV_TS_OCL_TEST_HPP__