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Merge pull request #2346 from ilya-lavrenov:umat_tests_cleanup

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This commit is contained in:
Andrey Pavlenko 2014-02-17 17:53:05 +04:00 committed by OpenCV Buildbot
commit 9885a671ee
6 changed files with 258 additions and 254 deletions
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123
modules/core/test/test_precomp.hpp
View File

@ -15,127 +15,4 @@
#include "opencv2/core/private.hpp"
#define MWIDTH 256
#define MHEIGHT 256
#define MIN_VALUE 171
#define MAX_VALUE 357
#define RNG_SEED 123456
template <typename T>
struct TSTestWithParam : public ::testing::TestWithParam<T>
{
cv::RNG rng;
TSTestWithParam()
{
rng = cv::RNG(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;
}
cv::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
}
cv::Size randomSize(int minValX, int maxValX, int minValY, int maxValY)
{
#if 1
return cv::Size(randomDoubleLog(minValX, maxValX), randomDoubleLog(minValY, maxValY));
#else
return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
#endif
}
cv::Scalar randomScalar(double minVal, double maxVal)
{
return cv::Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
}
cv::Mat randomMat(cv::Size size, int type, double minVal, double maxVal, bool useRoi = false)
{
cv::RNG dataRng(rng.next());
return cvtest::randomMat(dataRng, size, type, minVal, maxVal, useRoi);
}
};
#define PARAM_TEST_CASE(name, ...) struct name : public TSTestWithParam< std::tr1::tuple< __VA_ARGS__ > >
#define GET_PARAM(k) std::tr1::get< k >(GetParam())
#define UMAT_TEST_CHANNELS testing::Values(1, 2, 3, 4)
#define UMAT_TEST_SIZES testing::Values(cv::Size(1,1), cv::Size(1,128), cv::Size(128,1), cv::Size(128, 128), cv::Size(640,480), cv::Size(751,373), cv::Size(1200, 1200))
#define UMAT_TEST_DEPTH testing::Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F)
# define CORE_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(); \
void CoreTestBody(); \
private: \
static int AddToRegistry() \
{ \
::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
GetTestCasePatternHolder<test_case_name>(\
#test_case_name, __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_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 \
{ \
CoreTestBody(); \
} \
catch (...) \
{ \
std::cout << "Something wrong in CoreTestBody running" << std::endl; \
throw; \
} \
} \
\
void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::CoreTestBody()
#endif

257
modules/core/test/test_umat.cpp
View File

@ -40,20 +40,19 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/core/ocl.hpp"
#include "opencv2/ts/ocl_test.hpp"
using namespace cvtest;
using namespace testing;
using namespace cv;
#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(cv::norm(mat1, mat2), eps); \
}\
namespace cvtest {
namespace ocl {
////////////////////////////////////////////////////////////// Basic Tests /////////////////////////////////////////////////////////////////////
#define UMAT_TEST_SIZES testing::Values(cv::Size(1, 1), cv::Size(1,128), cv::Size(128, 1), \
cv::Size(128, 128), cv::Size(640, 480), cv::Size(751, 373), cv::Size(1200, 1200))
/////////////////////////////// Basic Tests ////////////////////////////////
PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
{
@ -66,6 +65,7 @@ PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
bool useRoi;
Size roi_size;
Rect roi;
virtual void SetUp()
{
depth = GET_PARAM(0);
@ -82,7 +82,7 @@ PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
}
};
CORE_TEST_P(UMatBasicTests, createUMat)
TEST_P(UMatBasicTests, createUMat)
{
if(useRoi)
{
@ -112,7 +112,7 @@ CORE_TEST_P(UMatBasicTests, createUMat)
ASSERT_EQ( ua.dims, 2);
}
CORE_TEST_P(UMatBasicTests, swap)
TEST_P(UMatBasicTests, swap)
{
Mat b = randomMat(size, type, -100, 100);
UMat ub;
@ -128,7 +128,7 @@ CORE_TEST_P(UMatBasicTests, swap)
EXPECT_MAT_NEAR(ud, ua, 0);
}
CORE_TEST_P(UMatBasicTests, base)
TEST_P(UMatBasicTests, base)
{
if(useRoi)
{
@ -167,7 +167,7 @@ CORE_TEST_P(UMatBasicTests, base)
ASSERT_EQ(ub.total(), total);
}
CORE_TEST_P(UMatBasicTests, copyTo)
TEST_P(UMatBasicTests, DISABLED_copyTo)
{
UMat roi_ua;
Mat roi_a;
@ -224,7 +224,7 @@ CORE_TEST_P(UMatBasicTests, copyTo)
}
}
CORE_TEST_P(UMatBasicTests, DISABLED_GetUMat)
TEST_P(UMatBasicTests, DISABLED_GetUMat)
{
if(useRoi)
{
@ -254,7 +254,7 @@ CORE_TEST_P(UMatBasicTests, DISABLED_GetUMat)
}
INSTANTIATE_TEST_CASE_P(UMat, UMatBasicTests, Combine(testing::Values(CV_8U), testing::Values(1, 2),
testing::Values(cv::Size(1,1), cv::Size(1,128), cv::Size(128,1), cv::Size(128, 128), cv::Size(640,480)), Bool() ) );
testing::Values(cv::Size(1, 1), cv::Size(1, 128), cv::Size(128, 1), cv::Size(128, 128), cv::Size(640, 480)), Bool()));
//////////////////////////////////////////////////////////////// Reshape ////////////////////////////////////////////////////////////////////////
@ -278,7 +278,7 @@ PARAM_TEST_CASE(UMatTestReshape, int, int, Size, bool)
}
};
CORE_TEST_P(UMatTestReshape, reshape)
TEST_P(UMatTestReshape, DISABLED_reshape)
{
a = randomMat(size,type, -100, 100);
a.copyTo(ua);
@ -342,7 +342,7 @@ CORE_TEST_P(UMatTestReshape, reshape)
}
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestReshape, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ));
INSTANTIATE_TEST_CASE_P(UMat, UMatTestReshape, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));
////////////////////////////////////////////////////////////////// ROI testing ///////////////////////////////////////////////////////////////
@ -364,7 +364,7 @@ PARAM_TEST_CASE(UMatTestRoi, int, int, Size)
}
};
CORE_TEST_P(UMatTestRoi, createRoi)
TEST_P(UMatTestRoi, createRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
@ -378,7 +378,7 @@ CORE_TEST_P(UMatTestRoi, createRoi)
EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
}
CORE_TEST_P(UMatTestRoi, locateRoi)
TEST_P(UMatTestRoi, locateRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
@ -396,7 +396,7 @@ CORE_TEST_P(UMatTestRoi, locateRoi)
ASSERT_EQ(p, up);
}
CORE_TEST_P(UMatTestRoi, adjustRoi)
TEST_P(UMatTestRoi, adjustRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
@ -410,14 +410,14 @@ CORE_TEST_P(UMatTestRoi, adjustRoi)
int adjTop = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
int adjBot = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
roi_ua.adjustROI(adjTop, adjBot, adjLeft, adjRight);
roi_shift_x = max(0, roi.x-adjLeft);
roi_shift_y = max(0, roi.y-adjTop);
Rect new_roi( roi_shift_x, roi_shift_y, min(roi.width+adjRight+adjLeft, size.width-roi_shift_x), min(roi.height+adjBot+adjTop, size.height-roi_shift_y) );
roi_shift_x = std::max(0, roi.x-adjLeft);
roi_shift_y = std::max(0, roi.y-adjTop);
Rect new_roi( roi_shift_x, roi_shift_y, std::min(roi.width+adjRight+adjLeft, size.width-roi_shift_x), std::min(roi.height+adjBot+adjTop, size.height-roi_shift_y) );
UMat test_roi = UMat(ua, new_roi);
EXPECT_MAT_NEAR(roi_ua, test_roi, 0);
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestRoi, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES ));
INSTANTIATE_TEST_CASE_P(UMat, UMatTestRoi, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES ));
/////////////////////////////////////////////////////////////// Size ////////////////////////////////////////////////////////////////////
@ -441,7 +441,7 @@ PARAM_TEST_CASE(UMatTestSizeOperations, int, int, Size, bool)
}
};
CORE_TEST_P(UMatTestSizeOperations, copySize)
TEST_P(UMatTestSizeOperations, copySize)
{
Size s = randomSize(1,300);
a = randomMat(size, type, -100, 100);
@ -466,7 +466,7 @@ CORE_TEST_P(UMatTestSizeOperations, copySize)
ASSERT_EQ(ua.size, ub.size);
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestSizeOperations, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ));
INSTANTIATE_TEST_CASE_P(UMat, UMatTestSizeOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));
///////////////////////////////////////////////////////////////// UMat operations ////////////////////////////////////////////////////////////////////////////
@ -490,7 +490,7 @@ PARAM_TEST_CASE(UMatTestUMatOperations, int, int, Size, bool)
}
};
CORE_TEST_P(UMatTestUMatOperations, diag)
TEST_P(UMatTestUMatOperations, diag)
{
a = randomMat(size, type, -100, 100);
a.copyTo(ua);
@ -514,7 +514,7 @@ CORE_TEST_P(UMatTestUMatOperations, diag)
EXPECT_MAT_NEAR(ua.diag(), new_diag.t(), 0);
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestUMatOperations, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ));
INSTANTIATE_TEST_CASE_P(UMat, UMatTestUMatOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool()));
///////////////////////////////////////////////////////////////// OpenCL ////////////////////////////////////////////////////////////////////////////
@ -541,9 +541,208 @@ TEST(UMat, BufferPoolGrowing)
c->freeAllReservedBuffers();
}
else
{
std::cout << "Skipped, no OpenCL" << std::endl;
}
class CV_UMatTest :
public cvtest::BaseTest
{
public:
CV_UMatTest() {}
~CV_UMatTest() {}
protected:
void run(int);
struct test_excep
{
test_excep(const string& _s=string("")) : s(_s) { }
string s;
};
bool TestUMat();
void checkDiff(const Mat& m1, const Mat& m2, const string& s)
{
if (norm(m1, m2, NORM_INF) != 0)
throw test_excep(s);
}
void checkDiffF(const Mat& m1, const Mat& m2, const string& s)
{
if (norm(m1, m2, NORM_INF) > 1e-5)
throw test_excep(s);
}
};
#define STR(a) STR2(a)
#define STR2(a) #a
#define CHECK_DIFF(a, b) checkDiff(a, b, "(" #a ") != (" #b ") at l." STR(__LINE__))
#define CHECK_DIFF_FLT(a, b) checkDiffF(a, b, "(" #a ") !=(eps) (" #b ") at l." STR(__LINE__))
bool CV_UMatTest::TestUMat()
{
try
{
Mat a(100, 100, CV_16SC2), b, c;
randu(a, Scalar::all(-100), Scalar::all(100));
Rect roi(1, 3, 5, 4);
Mat ra(a, roi), rb, rc, rc0;
UMat ua, ura, ub, urb, uc, urc;
a.copyTo(ua);
ua.copyTo(b);
CHECK_DIFF(a, b);
ura = ua(roi);
ura.copyTo(rb);
CHECK_DIFF(ra, rb);
ra += Scalar::all(1.f);
{
Mat temp = ura.getMat(ACCESS_RW);
temp += Scalar::all(1.f);
}
ra.copyTo(rb);
CHECK_DIFF(ra, rb);
b = a.clone();
ra = a(roi);
rb = b(roi);
randu(b, Scalar::all(-100), Scalar::all(100));
b.copyTo(ub);
urb = ub(roi);
/*std::cout << "==============================================\nbefore op (CPU):\n";
std::cout << "ra: " << ra << std::endl;
std::cout << "rb: " << rb << std::endl;*/
ra.copyTo(ura);
rb.copyTo(urb);
ra.release();
rb.release();
ura.copyTo(ra);
urb.copyTo(rb);
/*std::cout << "==============================================\nbefore op (GPU):\n";
std::cout << "ra: " << ra << std::endl;
std::cout << "rb: " << rb << std::endl;*/
cv::max(ra, rb, rc);
cv::max(ura, urb, urc);
urc.copyTo(rc0);
/*std::cout << "==============================================\nafter op:\n";
std::cout << "rc: " << rc << std::endl;
std::cout << "rc0: " << rc0 << std::endl;*/
CHECK_DIFF(rc0, rc);
{
UMat tmp = rc0.getUMat(ACCESS_WRITE);
cv::max(ura, urb, tmp);
}
CHECK_DIFF(rc0, rc);
ura.copyTo(urc);
cv::max(urc, urb, urc);
urc.copyTo(rc0);
CHECK_DIFF(rc0, rc);
rc = ra ^ rb;
cv::bitwise_xor(ura, urb, urc);
urc.copyTo(rc0);
/*std::cout << "==============================================\nafter op:\n";
std::cout << "ra: " << rc0 << std::endl;
std::cout << "rc: " << rc << std::endl;*/
CHECK_DIFF(rc0, rc);
rc = ra + rb;
cv::add(ura, urb, urc);
urc.copyTo(rc0);
CHECK_DIFF(rc0, rc);
cv::subtract(ra, Scalar::all(5), rc);
cv::subtract(ura, Scalar::all(5), urc);
urc.copyTo(rc0);
CHECK_DIFF(rc0, rc);
}
catch (const test_excep& e)
{
ts->printf(cvtest::TS::LOG, "%s\n", e.s.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return false;
}
return true;
}
void CV_UMatTest::run( int /* start_from */)
{
printf("Use OpenCL: %s\nHave OpenCL: %s\n",
cv::ocl::useOpenCL() ? "TRUE" : "FALSE",
cv::ocl::haveOpenCL() ? "TRUE" : "FALSE" );
if (!TestUMat())
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Core_UMat, base) { CV_UMatTest test; test.safe_run(); }
TEST(Core_UMat, getUMat)
{
{
int a[3] = { 1, 2, 3 };
Mat m = Mat(1, 1, CV_32SC3, a);
UMat u = m.getUMat(ACCESS_READ);
EXPECT_NE((void*)NULL, u.u);
}
{
Mat m(10, 10, CV_8UC1), ref;
for (int y = 0; y < m.rows; ++y)
{
uchar * const ptr = m.ptr<uchar>(y);
for (int x = 0; x < m.cols; ++x)
ptr[x] = (uchar)(x + y * 2);
}
ref = m.clone();
Rect r(1, 1, 8, 8);
ref(r).setTo(17);
{
UMat um = m(r).getUMat(ACCESS_WRITE);
um.setTo(17);
}
double err = norm(m, ref, NORM_INF);
if (err > 0)
{
std::cout << "m: " << std::endl << m << std::endl;
std::cout << "ref: " << std::endl << ref << std::endl;
}
EXPECT_EQ(0., err);
}
}
TEST(UMat, Sync)
{
UMat um(10, 10, CV_8UC1);
{
Mat m = um.getMat(ACCESS_WRITE);
m.setTo(cv::Scalar::all(17));
}
um.setTo(cv::Scalar::all(19));
EXPECT_EQ(0, cv::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
}
TEST(UMat, setOpenCL)
@ -586,3 +785,5 @@ TEST(UMat, setOpenCL)
// reset state to the previous one
cv::ocl::setUseOpenCL(useOCL);
}
} } // namespace cvtest::ocl

4
modules/ts/include/opencv2/ts/ocl_perf.hpp
View File

@ -45,8 +45,6 @@
#include "ocl_test.hpp"
#include "ts_perf.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
@ -130,6 +128,4 @@ using namespace perf;
} // namespace cvtest::ocl
} // namespace cvtest
#endif // HAVE_OPENCL
#endif // __OPENCV_TS_OCL_PERF_HPP__

88
modules/ts/include/opencv2/ts/ocl_test.hpp
View File

@ -42,11 +42,8 @@
#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"
@ -60,45 +57,20 @@ 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) \
EXPECT_LE(TestUtils::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) \
EXPECT_LE(TestUtils::checkNorm(mat1, mat2), eps) \
<< "Size: " << mat1.size() << std::endl; \
}
@ -106,7 +78,7 @@ extern int test_loop_times;
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkNormRelative(mat1, mat2), eps) \
EXPECT_LE(TestUtils::checkNormRelative(mat1, mat2), eps) \
<< "Size: " << mat1.size() << std::endl; \
}
@ -227,54 +199,22 @@ struct CV_EXPORTS TestUtils
// 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);
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 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)
static double checkNorm(InputArray m);
static double checkNorm(InputArray m1, InputArray m2);
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)
{
return cv::norm(m1, m2, cv::NORM_INF) /
return cv::norm(m1.getMat(), m2.getMat(), 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);
(double)std::max(cv::norm(m1.getMat(), cv::NORM_INF), norm(m2.getMat(), cv::NORM_INF)));
}
};
@ -334,8 +274,6 @@ CV_ENUM(BorderType, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT, BORDER_WR
#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
} } // namespace cvtest::ocl
#endif // __OPENCV_TS_OCL_TEST_HPP__

6
modules/ts/src/ocl_perf.cpp
View File

@ -43,8 +43,6 @@
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
@ -82,6 +80,4 @@ void randu(InputOutputArray dst)
} // namespace perf
}} // namespace cvtest::ocl
#endif // HAVE_OPENCL
} } // namespace cvtest::ocl

34
modules/ts/src/ocl_test.cpp
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@ -43,8 +43,6 @@
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
@ -197,41 +195,39 @@ Mat TestUtils::readImageType(const String &fname, int type)
return src;
}
double TestUtils::checkNorm(const Mat &m)
double TestUtils::checkNorm(InputArray m)
{
return norm(m, NORM_INF);
return norm(m.getMat(), NORM_INF);
}
double TestUtils::checkNorm(const Mat &m1, const Mat &m2)
double TestUtils::checkNorm(InputArray m1, InputArray m2)
{
return norm(m1, m2, NORM_INF);
return norm(m1.getMat(), m2.getMat(), NORM_INF);
}
double TestUtils::checkSimilarity(const Mat &m1, const Mat &m2)
double TestUtils::checkSimilarity(InputArray m1, InputArray m2)
{
Mat diff;
matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
matchTemplate(m1.getMat(), m2.getMat(), diff, CV_TM_CCORR_NORMED);
return std::abs(diff.at<float>(0, 0) - 1.f);
}
double TestUtils::checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
double TestUtils::checkRectSimilarity(const Size & sz, std::vector<Rect>& ob1, std::vector<Rect>& ob2)
{
double final_test_result = 0.0;
size_t sz1 = ob1.size();
size_t sz2 = ob2.size();
if(sz1 != sz2)
{
if (sz1 != sz2)
return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1);
}
else
{
if(sz1==0 && sz2==0)
if (sz1 == 0 && sz2 == 0)
return 0;
cv::Mat cpu_result(sz, CV_8UC1);
cpu_result.setTo(0);
for(vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
for (vector<Rect>::const_iterator r = ob1.begin(); r != ob1.end(); r++)
{
cv::Mat cpu_result_roi(cpu_result, *r);
cpu_result_roi.setTo(1);
@ -251,7 +247,7 @@ double TestUtils::checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vect
cv::Mat result_;
multiply(cpu_result, gpu_result, result_);
int result = cv::countNonZero(result_ > 0);
if(cpu_area!=0 && result!=0)
if (cpu_area!=0 && result!=0)
final_test_result = 1.0 - (double)result/(double)cpu_area;
else if(cpu_area==0 && result!=0)
final_test_result = -1;
@ -259,8 +255,10 @@ double TestUtils::checkRectSimilarity(Size sz, std::vector<Rect>& ob1, std::vect
return final_test_result;
}
void TestUtils::showDiff(const Mat& src, const Mat& gold, const Mat& actual, double eps, bool alwaysShow)
void TestUtils::showDiff(InputArray _src, InputArray _gold, InputArray _actual, double eps, bool alwaysShow)
{
Mat src = _src.getMat(), actual = _actual.getMat(), gold = _gold.getMat();
Mat diff, diff_thresh;
absdiff(gold, actual, diff);
diff.convertTo(diff, CV_32F);
@ -288,6 +286,4 @@ void TestUtils::showDiff(const Mat& src, const Mat& gold, const Mat& actual, dou
}
}
}} // namespace cvtest::ocl
#endif // HAVE_OPENCL
} } // namespace cvtest::ocl