mirror of
https://github.com/opencv/opencv.git
synced 2024-12-15 01:39:10 +08:00
1d18aba587
* started adding support for new types (16f, 16bf, 32u, 64u, 64s) to arithmetic functions * fixed several tests; refactored and extended sum(), extended inRange(). * extended countNonZero(), mean(), meanStdDev(), minMaxIdx(), norm() and sum() to support new types (F16, BF16, U32, U64, S64) * put missing CV_DEPTH_MAX to some function dispatcher tables * extended findnonzero, hasnonzero with the new types support * extended mixChannels() to support new types * minor fix * fixed a few compile errors on Linux and a few failures in core tests * fixed a few more warnings and test failures * trying to fix the remaining warnings and test failures. The test `MulTestGPU.MathOpTest` was disabled - not clear whether to set tolerance - it's not bit-exact operation, as possibly assumed by the test, due to the use of scale and possibly limited accuracy of the intermediate floating-point calculations. * found that in the current snapshot G-API produces incorrect results in Mul, Div and AddWeighted (at least when using OpenCL on Windows x64 or MacOS x64). Disabled the respective tests.
202 lines
6.9 KiB
C++
202 lines
6.9 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
//
|
|
// By downloading, copying, installing or using the software you agree to this license.
|
|
// If you do not agree to this license, do not download, install,
|
|
// copy or use the software.
|
|
//
|
|
//
|
|
// License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
|
|
// Third party copyrights are property of their respective owners.
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without modification,
|
|
// are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistribution's of source code must retain the above copyright notice,
|
|
// this list of conditions and the following disclaimer.
|
|
//
|
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
//
|
|
// * The name of the copyright holders may not be used to endorse or promote products
|
|
// derived from this software without specific prior written permission.
|
|
//
|
|
// This software is provided by the copyright holders and contributors "as is" and
|
|
// any express or implied warranties, including, but not limited to, the implied
|
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
// indirect, incidental, special, exemplary, or consequential damages
|
|
// (including, but not limited to, procurement of substitute goods or services;
|
|
// loss of use, data, or profits; or business interruption) however caused
|
|
// and on any theory of liability, whether in contract, strict liability,
|
|
// or tort (including negligence or otherwise) arising in any way out of
|
|
// the use of this software, even if advised of the possibility of such damage.
|
|
//
|
|
//M*/
|
|
|
|
#include "test_precomp.hpp"
|
|
|
|
namespace opencv_test { namespace {
|
|
|
|
typedef testing::TestWithParam<std::tuple<int, Size> > HasNonZeroAllZeros;
|
|
|
|
TEST_P(HasNonZeroAllZeros, hasNonZeroAllZeros)
|
|
{
|
|
const int type = std::get<0>(GetParam());
|
|
const Size size = std::get<1>(GetParam());
|
|
|
|
Mat m = Mat::zeros(size, type);
|
|
EXPECT_FALSE(hasNonZero(m));
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core, HasNonZeroAllZeros,
|
|
testing::Combine(
|
|
testing::Values(CV_8UC1, CV_8SC1, CV_16UC1, CV_16SC1, CV_32SC1, CV_32FC1, CV_64FC1),
|
|
testing::Values(Size(1, 1), Size(320, 240), Size(127, 113), Size(1, 113))
|
|
)
|
|
);
|
|
|
|
typedef testing::TestWithParam<std::tuple<int, Size> > HasNonZeroNegZeros;
|
|
|
|
TEST_P(HasNonZeroNegZeros, hasNonZeroNegZeros)
|
|
{
|
|
const int type = std::get<0>(GetParam());
|
|
const Size size = std::get<1>(GetParam());
|
|
|
|
Mat m = Mat(size, type);
|
|
m.setTo(Scalar::all(-0.));
|
|
EXPECT_FALSE(hasNonZero(m));
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core, HasNonZeroNegZeros,
|
|
testing::Combine(
|
|
testing::Values(CV_32FC1, CV_64FC1, CV_16FC1, CV_16BFC1),
|
|
testing::Values(Size(1, 1), Size(320, 240), Size(127, 113), Size(1, 113))
|
|
)
|
|
);
|
|
|
|
typedef testing::TestWithParam<std::tuple<int, Size> > HasNonZeroLimitValues;
|
|
|
|
TEST_P(HasNonZeroLimitValues, hasNonZeroLimitValues)
|
|
{
|
|
const int type = std::get<0>(GetParam());
|
|
const Size size = std::get<1>(GetParam());
|
|
|
|
Mat m = Mat(size, type);
|
|
|
|
m.setTo(Scalar::all(std::numeric_limits<double>::infinity()));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
|
|
m.setTo(Scalar::all(-std::numeric_limits<double>::infinity()));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
|
|
m.setTo(Scalar::all(std::numeric_limits<double>::quiet_NaN()));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
|
|
m.setTo((CV_MAT_DEPTH(type) == CV_64F) ? Scalar::all(std::numeric_limits<double>::epsilon()) : Scalar::all(std::numeric_limits<float>::epsilon()));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
|
|
m.setTo((CV_MAT_DEPTH(type) == CV_64F) ? Scalar::all(std::numeric_limits<double>::min()) : Scalar::all(std::numeric_limits<float>::min()));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
|
|
m.setTo((CV_MAT_DEPTH(type) == CV_64F) ? Scalar::all(std::numeric_limits<double>::denorm_min()) : Scalar::all(std::numeric_limits<float>::denorm_min()));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core, HasNonZeroLimitValues,
|
|
testing::Combine(
|
|
testing::Values(CV_32FC1, CV_64FC1),
|
|
testing::Values(Size(1, 1), Size(320, 240), Size(127, 113), Size(1, 113))
|
|
)
|
|
);
|
|
|
|
typedef testing::TestWithParam<std::tuple<int, Size> > HasNonZeroRandom;
|
|
|
|
TEST_P(HasNonZeroRandom, hasNonZeroRandom)
|
|
{
|
|
const int type = std::get<0>(GetParam());
|
|
const Size size = std::get<1>(GetParam());
|
|
|
|
RNG& rng = theRNG();
|
|
|
|
const size_t N = std::min(100, size.area());
|
|
for(size_t i = 0 ; i<N ; ++i)
|
|
{
|
|
const int nz_pos_x = rng.uniform(0, size.width);
|
|
const int nz_pos_y = rng.uniform(0, size.height);
|
|
Mat m = Mat::zeros(size, type);
|
|
Mat nzROI = Mat(m, Rect(nz_pos_x, nz_pos_y, 1, 1));
|
|
nzROI.setTo(Scalar::all(1));
|
|
EXPECT_TRUE(hasNonZero(m));
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core, HasNonZeroRandom,
|
|
testing::Combine(
|
|
testing::Values(CV_8UC1, CV_8SC1, CV_16UC1, CV_16SC1, CV_32SC1, CV_32FC1, CV_64FC1),
|
|
testing::Values(Size(1, 1), Size(320, 240), Size(127, 113), Size(1, 113))
|
|
)
|
|
);
|
|
|
|
typedef testing::TestWithParam<tuple<int, int, bool> > HasNonZeroNd;
|
|
|
|
TEST_P(HasNonZeroNd, hasNonZeroNd)
|
|
{
|
|
const int type = get<0>(GetParam());
|
|
const int ndims = get<1>(GetParam());
|
|
const bool continuous = get<2>(GetParam());
|
|
|
|
RNG& rng = theRNG();
|
|
|
|
const size_t N = 10;
|
|
for(size_t i = 0 ; i<N ; ++i)
|
|
{
|
|
std::vector<size_t> steps(ndims);
|
|
std::vector<int> sizes(ndims);
|
|
size_t totalBytes = 1;
|
|
for(int dim = 0 ; dim<ndims ; ++dim)
|
|
{
|
|
const bool isFirstDim = (dim == 0);
|
|
const bool isLastDim = (dim+1 == ndims);
|
|
const int length = rng.uniform(1, 64);
|
|
steps[dim] = (isLastDim ? 1 : static_cast<size_t>(length))*CV_ELEM_SIZE(type);
|
|
sizes[dim] = (isFirstDim || continuous) ? length : rng.uniform(1, length);
|
|
totalBytes *= steps[dim]*static_cast<size_t>(sizes[dim]);
|
|
}
|
|
|
|
std::vector<unsigned char> buffer(totalBytes);
|
|
void* data = buffer.data();
|
|
|
|
Mat m = Mat(ndims, sizes.data(), type, data, steps.data());
|
|
|
|
std::vector<Range> nzRange(ndims);
|
|
for(int dim = 0 ; dim<ndims ; ++dim)
|
|
{
|
|
const int pos = rng.uniform(0, sizes[dim]);
|
|
nzRange[dim] = Range(pos, pos+1);
|
|
}
|
|
|
|
Mat nzROI = Mat(m, nzRange.data());
|
|
nzROI.setTo(Scalar::all(1));
|
|
|
|
const int nzCount = countNonZero(m);
|
|
EXPECT_EQ((nzCount>0), hasNonZero(m));
|
|
}
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Core, HasNonZeroNd,
|
|
testing::Combine(
|
|
testing::Values(CV_8UC1),
|
|
testing::Values(2, 3),
|
|
testing::Values(true, false)
|
|
)
|
|
);
|
|
|
|
}} // namespace
|