Open Source Computer Vision Library https://opencv.org/
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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.
#include "test_precomp.hpp"
namespace opencv_test { namespace {
TEST(Core_OutputArrayCreate, _1997)
{
struct local {
static void create(OutputArray arr, Size submatSize, int type)
{
int sizes[] = {submatSize.width, submatSize.height};
arr.create(sizeof(sizes)/sizeof(sizes[0]), sizes, type);
}
};
Mat mat(Size(512, 512), CV_8U);
Size submatSize = Size(256, 256);
ASSERT_NO_THROW(local::create( mat(Rect(Point(), submatSize)), submatSize, mat.type() ));
}
TEST(Core_SaturateCast, NegativeNotClipped)
{
double d = -1.0;
unsigned int val = cv::saturate_cast<unsigned int>(d);
ASSERT_EQ(0xffffffff, val);
}
template<typename T, typename U>
static double maxAbsDiff(const T &t, const U &u)
{
Mat_<double> d;
absdiff(t, u, d);
double ret;
minMaxLoc(d, NULL, &ret);
return ret;
}
TEST(Core_OutputArrayAssign, _Matxd_Matd)
{
Mat expected = (Mat_<double>(2,3) << 1, 2, 3, .1, .2, .3);
Matx23d actualx;
{
OutputArray oa(actualx);
oa.assign(expected);
}
Mat actual = (Mat) actualx;
EXPECT_LE(maxAbsDiff(expected, actual), 0.0);
}
TEST(Core_OutputArrayAssign, _Matxd_Matf)
{
Mat expected = (Mat_<float>(2,3) << 1, 2, 3, .1, .2, .3);
Matx23d actualx;
{
OutputArray oa(actualx);
oa.assign(expected);
}
Mat actual = (Mat) actualx;
EXPECT_LE(maxAbsDiff(expected, actual), FLT_EPSILON);
}
TEST(Core_OutputArrayAssign, _Matxf_Matd)
{
Mat expected = (Mat_<double>(2,3) << 1, 2, 3, .1, .2, .3);
Matx23f actualx;
{
OutputArray oa(actualx);
oa.assign(expected);
}
Mat actual = (Mat) actualx;
EXPECT_LE(maxAbsDiff(expected, actual), FLT_EPSILON);
}
TEST(Core_OutputArrayAssign, _Matxd_UMatd)
{
Mat expected = (Mat_<double>(2,3) << 1, 2, 3, .1, .2, .3);
UMat uexpected = expected.getUMat(ACCESS_READ);
Matx23d actualx;
{
OutputArray oa(actualx);
oa.assign(uexpected);
}
Mat actual = (Mat) actualx;
EXPECT_LE(maxAbsDiff(expected, actual), 0.0);
}
TEST(Core_OutputArrayAssign, _Matxd_UMatf)
{
Mat expected = (Mat_<float>(2,3) << 1, 2, 3, .1, .2, .3);
UMat uexpected = expected.getUMat(ACCESS_READ);
Matx23d actualx;
{
OutputArray oa(actualx);
oa.assign(uexpected);
}
Mat actual = (Mat) actualx;
EXPECT_LE(maxAbsDiff(expected, actual), FLT_EPSILON);
}
TEST(Core_OutputArrayAssign, _Matxf_UMatd)
{
Mat expected = (Mat_<double>(2,3) << 1, 2, 3, .1, .2, .3);
UMat uexpected = expected.getUMat(ACCESS_READ);
Matx23f actualx;
{
OutputArray oa(actualx);
oa.assign(uexpected);
}
Mat actual = (Mat) actualx;
EXPECT_LE(maxAbsDiff(expected, actual), FLT_EPSILON);
}
TEST(Core_String, find_last_of__with__empty_string)
{
cv::String s;
size_t p = s.find_last_of("q", 0);
// npos is not exported: EXPECT_EQ(cv::String::npos, p);
EXPECT_EQ(std::string::npos, p);
}
TEST(Core_String, end_method_regression)
{
cv::String old_string = "012345";
cv::String new_string(old_string.begin(), old_string.end());
EXPECT_EQ(6u, new_string.size());
}
TEST(Core_Copy, repeat_regression_8972)
{
Mat src = (Mat_<int>(1, 4) << 1, 2, 3, 4);
ASSERT_ANY_THROW({
repeat(src, 5, 1, src);
});
}
}} // namespace