提交 b5f251c8 编写于 作者: E Elena Gvozdeva

fixed test ocl_MatchTemplate for sparse matrix

上级 7dd7dd97
......@@ -454,14 +454,15 @@ static bool matchTemplate_CCOEFF(InputArray _image, InputArray _templ, OutputArr
if (cn==1)
{
float templ_sum = static_cast<float>(sum(_templ)[0]) / tsize.area();
Scalar templMean = mean(templ);
float templ_sum = (float)templMean[0];
k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols, templ_sum);
}
else
{
Vec4f templ_sum = Vec4f::all(0);
templ_sum = sum(templ) / tsize.area();
templ_sum = (Vec4f)mean(templ);
k.args(ocl::KernelArg::ReadOnlyNoSize(image_sums), ocl::KernelArg::ReadWrite(result), templ.rows, templ.cols, templ_sum); }
......
......@@ -97,9 +97,17 @@ PARAM_TEST_CASE(MatchTemplate, MatDepth, Channels, MatchTemplType, bool)
UMAT_UPLOAD_OUTPUT_PARAMETER(result);
}
void Near(double threshold = 0.0)
void Near()
{
OCL_EXPECT_MATS_NEAR(result, threshold);
bool isNormed =
method == TM_CCORR_NORMED ||
method == TM_SQDIFF_NORMED ||
method == TM_CCOEFF_NORMED;
if (isNormed)
OCL_EXPECT_MATS_NEAR(result, 3e-2);
else
OCL_EXPECT_MATS_NEAR_RELATIVE_SPARSE(result, 1.5e-2);
}
};
......@@ -112,14 +120,7 @@ OCL_TEST_P(MatchTemplate, Mat)
OCL_OFF(cv::matchTemplate(image_roi, templ_roi, result_roi, method));
OCL_ON(cv::matchTemplate(uimage_roi, utempl_roi, uresult_roi, method));
bool isNormed =
method == TM_CCORR_NORMED ||
method == TM_SQDIFF_NORMED ||
method == TM_CCOEFF_NORMED;
double eps = isNormed ? 3e-2 : 255.0 * 255.0 * templ.total() * 2e-5;
Near(eps);
Near();
}
}
......
......@@ -159,6 +159,25 @@ do \
<< "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(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(TestUtils::checkNormRelativeSparse(name, u ## name, _mask), eps) \
<< "Size: " << name ## _roi.size() << std::endl; \
} while ((void)0, 0)
#define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \
do \
{ \
......@@ -274,6 +293,16 @@ struct CV_EXPORTS TestUtils
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
......
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