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- /*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),
- 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
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