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