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416 lines
11 KiB
C++
416 lines
11 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#ifdef HAVE_CUDA
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using namespace cvtest;
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////////////////////////////////////////////////////////////////////////////////
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// Merge
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PARAM_TEST_CASE(Merge, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int depth;
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int channels;
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bool useRoi;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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depth = GET_PARAM(2);
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channels = GET_PARAM(3);
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useRoi = GET_PARAM(4);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(Merge, Accuracy)
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{
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std::vector<cv::Mat> src;
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src.reserve(channels);
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for (int i = 0; i < channels; ++i)
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src.push_back(cv::Mat(size, depth, cv::Scalar::all(i)));
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std::vector<cv::gpu::GpuMat> d_src;
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for (int i = 0; i < channels; ++i)
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d_src.push_back(loadMat(src[i], useRoi));
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if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
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{
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try
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{
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cv::gpu::GpuMat dst;
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cv::gpu::merge(d_src, dst);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
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}
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}
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else
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{
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cv::gpu::GpuMat dst;
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cv::gpu::merge(d_src, dst);
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cv::Mat dst_gold;
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cv::merge(src, dst_gold);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Arithm, Merge, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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ALL_DEPTH,
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testing::Values(1, 2, 3, 4),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// Split
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PARAM_TEST_CASE(Split, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int depth;
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int channels;
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bool useRoi;
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int type;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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depth = GET_PARAM(2);
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channels = GET_PARAM(3);
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useRoi = GET_PARAM(4);
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cv::gpu::setDevice(devInfo.deviceID());
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type = CV_MAKE_TYPE(depth, channels);
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}
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};
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GPU_TEST_P(Split, Accuracy)
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{
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cv::Mat src = randomMat(size, type);
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if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
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{
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try
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{
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std::vector<cv::gpu::GpuMat> dst;
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cv::gpu::split(loadMat(src), dst);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
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}
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}
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else
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{
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std::vector<cv::gpu::GpuMat> dst;
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cv::gpu::split(loadMat(src, useRoi), dst);
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std::vector<cv::Mat> dst_gold;
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cv::split(src, dst_gold);
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ASSERT_EQ(dst_gold.size(), dst.size());
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for (size_t i = 0; i < dst_gold.size(); ++i)
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{
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EXPECT_MAT_NEAR(dst_gold[i], dst[i], 0.0);
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}
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Arithm, Split, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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ALL_DEPTH,
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testing::Values(1, 2, 3, 4),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// Transpose
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PARAM_TEST_CASE(Transpose, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int type;
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bool useRoi;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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type = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(Transpose, Accuracy)
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{
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cv::Mat src = randomMat(size, type);
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if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
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{
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try
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{
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cv::gpu::GpuMat dst;
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cv::gpu::transpose(loadMat(src), dst);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
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}
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}
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else
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{
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cv::gpu::GpuMat dst = createMat(cv::Size(size.height, size.width), type, useRoi);
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cv::gpu::transpose(loadMat(src, useRoi), dst);
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cv::Mat dst_gold;
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cv::transpose(src, dst_gold);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Arithm, Transpose, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC1),
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MatType(CV_8UC4),
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MatType(CV_16UC2),
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MatType(CV_16SC2),
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MatType(CV_32SC1),
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MatType(CV_32SC2),
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MatType(CV_64FC1)),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// Flip
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enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
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CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
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#define ALL_FLIP_CODES testing::Values(FlipCode(FLIP_BOTH), FlipCode(FLIP_X), FlipCode(FLIP_Y))
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PARAM_TEST_CASE(Flip, cv::gpu::DeviceInfo, cv::Size, MatType, FlipCode, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int type;
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int flip_code;
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bool useRoi;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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type = GET_PARAM(2);
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flip_code = GET_PARAM(3);
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useRoi = GET_PARAM(4);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(Flip, Accuracy)
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{
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cv::Mat src = randomMat(size, type);
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cv::gpu::GpuMat dst = createMat(size, type, useRoi);
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cv::gpu::flip(loadMat(src, useRoi), dst, flip_code);
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cv::Mat dst_gold;
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cv::flip(src, dst_gold, flip_code);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Arithm, Flip, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC1),
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MatType(CV_8UC3),
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MatType(CV_8UC4),
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MatType(CV_16UC1),
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MatType(CV_16UC3),
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MatType(CV_16UC4),
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MatType(CV_32SC1),
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MatType(CV_32SC3),
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MatType(CV_32SC4),
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MatType(CV_32FC1),
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MatType(CV_32FC3),
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MatType(CV_32FC4)),
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ALL_FLIP_CODES,
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// LUT
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PARAM_TEST_CASE(LUT, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int type;
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bool useRoi;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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type = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(LUT, OneChannel)
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{
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cv::Mat src = randomMat(size, type);
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cv::Mat lut = randomMat(cv::Size(256, 1), CV_8UC1);
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cv::gpu::GpuMat dst = createMat(size, CV_MAKE_TYPE(lut.depth(), src.channels()));
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cv::gpu::LUT(loadMat(src, useRoi), lut, dst);
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cv::Mat dst_gold;
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cv::LUT(src, lut, dst_gold);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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GPU_TEST_P(LUT, MultiChannel)
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{
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cv::Mat src = randomMat(size, type);
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cv::Mat lut = randomMat(cv::Size(256, 1), CV_MAKE_TYPE(CV_8U, src.channels()));
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cv::gpu::GpuMat dst = createMat(size, CV_MAKE_TYPE(lut.depth(), src.channels()), useRoi);
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cv::gpu::LUT(loadMat(src, useRoi), lut, dst);
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cv::Mat dst_gold;
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cv::LUT(src, lut, dst_gold);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Arithm, LUT, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3)),
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WHOLE_SUBMAT));
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//////////////////////////////////////////////////////////////////////////////
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// CopyMakeBorder
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namespace
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{
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IMPLEMENT_PARAM_CLASS(Border, int)
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}
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PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border, BorderType, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int type;
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int border;
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int borderType;
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bool useRoi;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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type = GET_PARAM(2);
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border = GET_PARAM(3);
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borderType = GET_PARAM(4);
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useRoi = GET_PARAM(5);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(CopyMakeBorder, Accuracy)
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{
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cv::Mat src = randomMat(size, type);
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cv::Scalar val = randomScalar(0, 255);
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cv::gpu::GpuMat dst = createMat(cv::Size(size.width + 2 * border, size.height + 2 * border), type, useRoi);
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cv::gpu::copyMakeBorder(loadMat(src, useRoi), dst, border, border, border, border, borderType, val);
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cv::Mat dst_gold;
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cv::copyMakeBorder(src, dst_gold, border, border, border, border, borderType, val);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Arithm, CopyMakeBorder, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC1),
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MatType(CV_8UC3),
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MatType(CV_8UC4),
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MatType(CV_16UC1),
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MatType(CV_16UC3),
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MatType(CV_16UC4),
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MatType(CV_32FC1),
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MatType(CV_32FC3),
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MatType(CV_32FC4)),
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testing::Values(Border(1), Border(10), Border(50)),
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ALL_BORDER_TYPES,
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WHOLE_SUBMAT));
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#endif // HAVE_CUDA
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