ade7394e77
wrote more complicated tests for them implemented own version of warpAffine and warpPerspective for different border interpolation types refactored some gpu tests
1691 lines
44 KiB
C++
1691 lines
44 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp"
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#ifdef HAVE_CUDA
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using namespace cvtest;
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using namespace testing;
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PARAM_TEST_CASE(ArithmTestBase, cv::gpu::DeviceInfo, MatType, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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int type;
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bool useRoi;
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cv::Size size;
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cv::Mat mat1;
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cv::Mat mat2;
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cv::Scalar val;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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type = GET_PARAM(1);
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useRoi = GET_PARAM(2);
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cv::gpu::setDevice(devInfo.deviceID());
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cv::RNG& rng = TS::ptr()->get_rng();
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size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
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mat1 = randomMat(rng, size, type, 5, 16, false);
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mat2 = randomMat(rng, size, type, 5, 16, false);
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val = cv::Scalar(rng.uniform(1, 3), rng.uniform(1, 3), rng.uniform(1, 3), rng.uniform(1, 3));
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// add
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struct Add : ArithmTestBase {};
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TEST_P(Add, Array)
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{
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cv::Mat dst_gold;
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cv::add(mat1, mat2, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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TEST_P(Add, Scalar)
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{
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cv::Mat dst_gold;
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cv::add(mat1, val, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::add(loadMat(mat1, useRoi), val, gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Add, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
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CV_32SC1, CV_32SC2, CV_32SC3, CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// subtract
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struct Subtract : ArithmTestBase {};
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TEST_P(Subtract, Array)
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{
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cv::Mat dst_gold;
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cv::subtract(mat1, mat2, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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TEST_P(Subtract, Scalar)
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{
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cv::Mat dst_gold;
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cv::subtract(mat1, val, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::subtract(loadMat(mat1, useRoi), val, gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Subtract, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
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CV_32SC1, CV_32SC2, CV_32SC3, CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// multiply
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struct Multiply : ArithmTestBase {};
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TEST_P(Multiply, Array)
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{
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cv::Mat dst_gold;
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cv::multiply(mat1, mat2, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::multiply(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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TEST_P(Multiply, Scalar)
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{
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cv::Mat dst_gold;
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cv::multiply(mat1, val, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::multiply(loadMat(mat1, useRoi), val, gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Multiply, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC3, CV_16SC4,
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CV_32SC1, CV_32SC3, CV_32FC1, CV_32FC3, CV_32FC4),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// divide
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struct Divide : ArithmTestBase {};
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TEST_P(Divide, Array)
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{
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cv::Mat dst_gold;
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cv::divide(mat1, mat2, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::divide(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, mat1.depth() == CV_32F ? 1e-5 : 1);
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}
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TEST_P(Divide, Scalar)
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{
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cv::Mat dst_gold;
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cv::divide(mat1, val, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::divide(loadMat(mat1, useRoi), val, gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, mat1.depth() == CV_32F ? 1e-5 : 1);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Divide, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC3, CV_16SC4,
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CV_32SC1, CV_32SC3, CV_32FC1, CV_32FC3, CV_32FC4),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// transpose
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struct Transpose : ArithmTestBase {};
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TEST_P(Transpose, Accuracy)
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{
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cv::Mat dst_gold;
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cv::transpose(mat1, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::transpose(loadMat(mat1, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Transpose, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_8UC4, CV_8SC1, CV_8SC4, CV_16UC2, CV_16SC2, CV_32SC1, CV_32SC2, CV_32FC1, CV_32FC2, CV_64FC1),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// absdiff
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struct Absdiff : ArithmTestBase {};
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TEST_P(Absdiff, Array)
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{
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cv::Mat dst_gold;
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cv::absdiff(mat1, mat2, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::absdiff(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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TEST_P(Absdiff, Scalar)
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{
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cv::Mat dst_gold;
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cv::absdiff(mat1, val, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::absdiff(loadMat(mat1, useRoi), val, gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Absdiff, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_16UC1, CV_32SC1, CV_32FC1),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// abs
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struct Abs : ArithmTestBase {};
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TEST_P(Abs, Array)
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{
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cv::Mat dst_gold = cv::abs(mat1);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::abs(loadMat(mat1, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Abs, Combine(
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ALL_DEVICES,
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Values(CV_16SC1, CV_32FC1),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// Sqr
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struct Sqr : ArithmTestBase {};
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TEST_P(Sqr, Array)
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{
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cv::Mat dst_gold;
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cv::multiply(mat1, mat1, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::sqr(loadMat(mat1, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Sqr, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_16UC1, CV_16SC1, CV_32FC1),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// Sqrt
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struct Sqrt : ArithmTestBase {};
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TEST_P(Sqrt, Array)
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{
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cv::Mat dst_gold;
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cv::sqrt(mat1, dst_gold);
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::sqrt(loadMat(mat1, useRoi), gpuRes);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Sqrt, Combine(
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ALL_DEVICES,
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Values(MatType(CV_32FC1)),
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WHOLE_SUBMAT));
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////////////////////////////////////////////////////////////////////////////////
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// compare
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PARAM_TEST_CASE(Compare, cv::gpu::DeviceInfo, MatType, CmpCode, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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int type;
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int cmp_code;
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bool useRoi;
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cv::Size size;
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cv::Mat mat1, mat2;
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cv::Mat dst_gold;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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type = GET_PARAM(1);
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cmp_code = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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cv::gpu::setDevice(devInfo.deviceID());
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cv::RNG& rng = TS::ptr()->get_rng();
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size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
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mat1 = randomMat(rng, size, type, 1, 16, false);
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mat2 = randomMat(rng, size, type, 1, 16, false);
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cv::compare(mat1, mat2, dst_gold, cmp_code);
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}
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};
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TEST_P(Compare, Accuracy)
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{
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cv::Mat dst;
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cv::gpu::GpuMat gpuRes;
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cv::gpu::compare(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuRes, cmp_code);
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gpuRes.download(dst);
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EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(Arithm, Compare, Combine(
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ALL_DEVICES,
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Values(CV_8UC1, CV_16UC1, CV_32SC1),
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Values((int) cv::CMP_EQ, (int) cv::CMP_GT, (int) cv::CMP_GE, (int) cv::CMP_LT, (int) cv::CMP_LE, (int) cv::CMP_NE),
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WHOLE_SUBMAT));
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|
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////////////////////////////////////////////////////////////////////////////////
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// meanStdDev
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PARAM_TEST_CASE(MeanStdDev, cv::gpu::DeviceInfo, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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bool useRoi;
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cv::Size size;
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cv::Mat mat;
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cv::Scalar mean_gold;
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cv::Scalar stddev_gold;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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useRoi = GET_PARAM(1);
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cv::gpu::setDevice(devInfo.deviceID());
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cv::RNG& rng = TS::ptr()->get_rng();
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size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
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mat = randomMat(rng, size, CV_8UC1, 1, 255, false);
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cv::meanStdDev(mat, mean_gold, stddev_gold);
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}
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};
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TEST_P(MeanStdDev, Accuracy)
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{
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cv::Scalar mean;
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cv::Scalar stddev;
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cv::gpu::meanStdDev(loadMat(mat, useRoi), mean, stddev);
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EXPECT_NEAR(mean_gold[0], mean[0], 1e-5);
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EXPECT_NEAR(mean_gold[1], mean[1], 1e-5);
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EXPECT_NEAR(mean_gold[2], mean[2], 1e-5);
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EXPECT_NEAR(mean_gold[3], mean[3], 1e-5);
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EXPECT_NEAR(stddev_gold[0], stddev[0], 1e-5);
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EXPECT_NEAR(stddev_gold[1], stddev[1], 1e-5);
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EXPECT_NEAR(stddev_gold[2], stddev[2], 1e-5);
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EXPECT_NEAR(stddev_gold[3], stddev[3], 1e-5);
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}
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|
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INSTANTIATE_TEST_CASE_P(Arithm, MeanStdDev, Combine(
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ALL_DEVICES,
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WHOLE_SUBMAT));
|
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|
|
////////////////////////////////////////////////////////////////////////////////
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// normDiff
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|
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PARAM_TEST_CASE(NormDiff, cv::gpu::DeviceInfo, NormCode, UseRoi)
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{
|
|
cv::gpu::DeviceInfo devInfo;
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int normCode;
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bool useRoi;
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cv::Size size;
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cv::Mat mat1, mat2;
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|
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double norm_gold;
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|
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virtual void SetUp()
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|
{
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devInfo = GET_PARAM(0);
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normCode = GET_PARAM(1);
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useRoi = GET_PARAM(2);
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cv::gpu::setDevice(devInfo.deviceID());
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cv::RNG& rng = TS::ptr()->get_rng();
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size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
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mat1 = randomMat(rng, size, CV_8UC1, 1, 255, false);
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mat2 = randomMat(rng, size, CV_8UC1, 1, 255, false);
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norm_gold = cv::norm(mat1, mat2, normCode);
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}
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};
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|
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TEST_P(NormDiff, Accuracy)
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{
|
|
double norm = cv::gpu::norm(loadMat(mat1, useRoi), loadMat(mat2, useRoi), normCode);
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EXPECT_NEAR(norm_gold, norm, 1e-6);
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}
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|
|
INSTANTIATE_TEST_CASE_P(Arithm, NormDiff, Combine(
|
|
ALL_DEVICES,
|
|
Values((int) cv::NORM_INF, (int) cv::NORM_L1, (int) cv::NORM_L2),
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// flip
|
|
|
|
PARAM_TEST_CASE(Flip, cv::gpu::DeviceInfo, MatType, FlipCode, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
int flip_code;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
flip_code = GET_PARAM(2);
|
|
useRoi = GET_PARAM(3);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, type, 1, 255, false);
|
|
|
|
cv::flip(mat, dst_gold, flip_code);
|
|
}
|
|
};
|
|
|
|
TEST_P(Flip, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::flip(loadMat(mat, useRoi), gpu_res, flip_code);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Flip, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, CV_32FC4),
|
|
Values((int)FLIP_BOTH, (int)FLIP_X, (int)FLIP_Y),
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// LUT
|
|
|
|
PARAM_TEST_CASE(LUT, cv::gpu::DeviceInfo, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
cv::Mat lut;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
useRoi = GET_PARAM(2);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, type, 1, 255, false);
|
|
lut = randomMat(rng, cv::Size(256, 1), CV_8UC1, 100, 200, false);
|
|
|
|
cv::LUT(mat, lut, dst_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(LUT, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::LUT(loadMat(mat, useRoi), lut, gpu_res);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, LUT, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8UC1, CV_8UC3),
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// exp
|
|
|
|
PARAM_TEST_CASE(Exp, cv::gpu::DeviceInfo, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
useRoi = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, CV_32FC1, -10.0, 2.0, false);
|
|
|
|
cv::exp(mat, dst_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(Exp, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::exp(loadMat(mat, useRoi), gpu_res);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Exp, Combine(
|
|
ALL_DEVICES,
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// pow
|
|
|
|
PARAM_TEST_CASE(Pow, cv::gpu::DeviceInfo, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
bool useRoi;
|
|
|
|
double power;
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
useRoi = GET_PARAM(2);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, type, 0.0, 100.0, false);
|
|
|
|
if (mat.depth() == CV_32F)
|
|
power = rng.uniform(1.2f, 3.f);
|
|
else
|
|
{
|
|
int ipower = rng.uniform(2, 8);
|
|
power = (float)ipower;
|
|
}
|
|
|
|
cv::pow(mat, power, dst_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(Pow, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::pow(loadMat(mat, useRoi), power, gpu_res);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 2);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Pow, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_32F, CV_32FC3),
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// log
|
|
|
|
PARAM_TEST_CASE(Log, cv::gpu::DeviceInfo, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
useRoi = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
|
|
|
|
cv::log(mat, dst_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(Log, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::log(loadMat(mat, useRoi), gpu_res);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Log, Combine(
|
|
ALL_DEVICES,
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// magnitude
|
|
|
|
PARAM_TEST_CASE(Magnitude, cv::gpu::DeviceInfo, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat1, mat2;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
useRoi = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat1 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
|
|
mat2 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
|
|
|
|
cv::magnitude(mat1, mat2, dst_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(Magnitude, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::magnitude(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpu_res);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 1e-4);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Magnitude, Combine(
|
|
ALL_DEVICES,
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// phase
|
|
|
|
PARAM_TEST_CASE(Phase, cv::gpu::DeviceInfo, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat1, mat2;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
useRoi = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat1 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
|
|
mat2 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
|
|
|
|
cv::phase(mat1, mat2, dst_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(Phase, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat gpu_res;
|
|
|
|
cv::gpu::phase(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpu_res);
|
|
|
|
gpu_res.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 1e-3);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Phase, Combine(
|
|
ALL_DEVICES,
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// cartToPolar
|
|
|
|
PARAM_TEST_CASE(CartToPolar, cv::gpu::DeviceInfo, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat1, mat2;
|
|
|
|
cv::Mat mag_gold;
|
|
cv::Mat angle_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
useRoi = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat1 = randomMat(rng, size, CV_32FC1, -100.0, 100.0, false);
|
|
mat2 = randomMat(rng, size, CV_32FC1, -100.0, 100.0, false);
|
|
|
|
cv::cartToPolar(mat1, mat2, mag_gold, angle_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(CartToPolar, Accuracy)
|
|
{
|
|
cv::Mat mag, angle;
|
|
|
|
cv::gpu::GpuMat gpuMag;
|
|
cv::gpu::GpuMat gpuAngle;
|
|
|
|
cv::gpu::cartToPolar(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuMag, gpuAngle);
|
|
|
|
gpuMag.download(mag);
|
|
gpuAngle.download(angle);
|
|
|
|
EXPECT_MAT_NEAR(mag_gold, mag, 1e-4);
|
|
EXPECT_MAT_NEAR(angle_gold, angle, 1e-3);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, CartToPolar, Combine(
|
|
ALL_DEVICES,
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// polarToCart
|
|
|
|
PARAM_TEST_CASE(PolarToCart, cv::gpu::DeviceInfo, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mag;
|
|
cv::Mat angle;
|
|
|
|
cv::Mat x_gold;
|
|
cv::Mat y_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
useRoi = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mag = randomMat(rng, size, CV_32FC1, -100.0, 100.0, false);
|
|
angle = randomMat(rng, size, CV_32FC1, 0.0, 2.0 * CV_PI, false);
|
|
|
|
cv::polarToCart(mag, angle, x_gold, y_gold);
|
|
}
|
|
};
|
|
|
|
TEST_P(PolarToCart, Accuracy)
|
|
{
|
|
cv::Mat x, y;
|
|
|
|
cv::gpu::GpuMat gpuX;
|
|
cv::gpu::GpuMat gpuY;
|
|
|
|
cv::gpu::polarToCart(loadMat(mag, useRoi), loadMat(angle, useRoi), gpuX, gpuY);
|
|
|
|
gpuX.download(x);
|
|
gpuY.download(y);
|
|
|
|
EXPECT_MAT_NEAR(x_gold, x, 1e-4);
|
|
EXPECT_MAT_NEAR(y_gold, y, 1e-4);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, PolarToCart, Combine(
|
|
ALL_DEVICES,
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// minMax
|
|
|
|
PARAM_TEST_CASE(MinMax, cv::gpu::DeviceInfo, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
cv::Mat mask;
|
|
|
|
double minVal_gold;
|
|
double maxVal_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
useRoi = GET_PARAM(2);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, type, 0.0, 127.0, false);
|
|
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
|
|
|
|
if (type != CV_8S)
|
|
{
|
|
cv::minMaxLoc(mat, &minVal_gold, &maxVal_gold, 0, 0, mask);
|
|
}
|
|
else
|
|
{
|
|
// OpenCV's minMaxLoc doesn't support CV_8S type
|
|
minVal_gold = std::numeric_limits<double>::max();
|
|
maxVal_gold = -std::numeric_limits<double>::max();
|
|
for (int i = 0; i < mat.rows; ++i)
|
|
{
|
|
const signed char* mat_row = mat.ptr<signed char>(i);
|
|
const unsigned char* mask_row = mask.ptr<unsigned char>(i);
|
|
for (int j = 0; j < mat.cols; ++j)
|
|
{
|
|
if (mask_row[j])
|
|
{
|
|
signed char val = mat_row[j];
|
|
if (val < minVal_gold) minVal_gold = val;
|
|
if (val > maxVal_gold) maxVal_gold = val;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
TEST_P(MinMax, Accuracy)
|
|
{
|
|
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
double minVal, maxVal;
|
|
|
|
cv::gpu::minMax(loadMat(mat, useRoi), &minVal, &maxVal, loadMat(mask, useRoi));
|
|
|
|
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
|
|
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, MinMax, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// minMaxLoc
|
|
|
|
PARAM_TEST_CASE(MinMaxLoc, cv::gpu::DeviceInfo, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
cv::Mat mask;
|
|
|
|
double minVal_gold;
|
|
double maxVal_gold;
|
|
cv::Point minLoc_gold;
|
|
cv::Point maxLoc_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
useRoi = GET_PARAM(2);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, type, 0.0, 127.0, false);
|
|
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
|
|
|
|
if (type != CV_8S)
|
|
{
|
|
cv::minMaxLoc(mat, &minVal_gold, &maxVal_gold, &minLoc_gold, &maxLoc_gold, mask);
|
|
}
|
|
else
|
|
{
|
|
// OpenCV's minMaxLoc doesn't support CV_8S type
|
|
minVal_gold = std::numeric_limits<double>::max();
|
|
maxVal_gold = -std::numeric_limits<double>::max();
|
|
for (int i = 0; i < mat.rows; ++i)
|
|
{
|
|
const signed char* mat_row = mat.ptr<signed char>(i);
|
|
const unsigned char* mask_row = mask.ptr<unsigned char>(i);
|
|
for (int j = 0; j < mat.cols; ++j)
|
|
{
|
|
if (mask_row[j])
|
|
{
|
|
signed char val = mat_row[j];
|
|
if (val < minVal_gold) { minVal_gold = val; minLoc_gold = cv::Point(j, i); }
|
|
if (val > maxVal_gold) { maxVal_gold = val; maxLoc_gold = cv::Point(j, i); }
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
};
|
|
|
|
TEST_P(MinMaxLoc, Accuracy)
|
|
{
|
|
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
double minVal, maxVal;
|
|
cv::Point minLoc, maxLoc;
|
|
|
|
cv::gpu::minMaxLoc(loadMat(mat, useRoi), &minVal, &maxVal, &minLoc, &maxLoc, loadMat(mask, useRoi));
|
|
|
|
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
|
|
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
|
|
|
|
int cmpMinVals = memcmp(mat.data + minLoc_gold.y * mat.step + minLoc_gold.x * mat.elemSize(),
|
|
mat.data + minLoc.y * mat.step + minLoc.x * mat.elemSize(),
|
|
mat.elemSize());
|
|
int cmpMaxVals = memcmp(mat.data + maxLoc_gold.y * mat.step + maxLoc_gold.x * mat.elemSize(),
|
|
mat.data + maxLoc.y * mat.step + maxLoc.x * mat.elemSize(),
|
|
mat.elemSize());
|
|
|
|
EXPECT_EQ(0, cmpMinVals);
|
|
EXPECT_EQ(0, cmpMaxVals);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, MinMaxLoc, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
|
|
WHOLE_SUBMAT));
|
|
|
|
////////////////////////////////////////////////////////////////////////////
|
|
// countNonZero
|
|
|
|
PARAM_TEST_CASE(CountNonZero, cv::gpu::DeviceInfo, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
|
|
int n_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
useRoi = GET_PARAM(2);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
cv::Mat matBase = randomMat(rng, size, CV_8U, 0.0, 1.0, false);
|
|
matBase.convertTo(mat, type);
|
|
|
|
n_gold = cv::countNonZero(mat);
|
|
}
|
|
};
|
|
|
|
TEST_P(CountNonZero, Accuracy)
|
|
{
|
|
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
int n = cv::gpu::countNonZero(loadMat(mat, useRoi));
|
|
|
|
ASSERT_EQ(n_gold, n);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, CountNonZero, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
|
|
WHOLE_SUBMAT));
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
// sum
|
|
|
|
PARAM_TEST_CASE(Sum, cv::gpu::DeviceInfo, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
useRoi = GET_PARAM(2);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat = randomMat(rng, size, CV_8U, 0.0, 10.0, false);
|
|
}
|
|
};
|
|
|
|
TEST_P(Sum, Simple)
|
|
{
|
|
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Scalar sum_gold = cv::sum(mat);
|
|
|
|
cv::Scalar sum = cv::gpu::sum(loadMat(mat, useRoi));
|
|
|
|
EXPECT_NEAR(sum[0], sum_gold[0], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[1], sum_gold[1], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[2], sum_gold[2], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[3], sum_gold[3], mat.size().area() * 1e-5);
|
|
}
|
|
|
|
TEST_P(Sum, Abs)
|
|
{
|
|
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Scalar sum_gold = cv::norm(mat, cv::NORM_L1);
|
|
|
|
cv::Scalar sum = cv::gpu::absSum(loadMat(mat, useRoi));
|
|
|
|
EXPECT_NEAR(sum[0], sum_gold[0], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[1], sum_gold[1], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[2], sum_gold[2], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[3], sum_gold[3], mat.size().area() * 1e-5);
|
|
}
|
|
|
|
TEST_P(Sum, Sqr)
|
|
{
|
|
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Mat sqrmat;
|
|
multiply(mat, mat, sqrmat);
|
|
cv::Scalar sum_gold = sum(sqrmat);
|
|
|
|
cv::Scalar sum = cv::gpu::sqrSum(loadMat(mat, useRoi));
|
|
|
|
EXPECT_NEAR(sum[0], sum_gold[0], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[1], sum_gold[1], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[2], sum_gold[2], mat.size().area() * 1e-5);
|
|
EXPECT_NEAR(sum[3], sum_gold[3], mat.size().area() * 1e-5);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Sum, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
|
|
WHOLE_SUBMAT));
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
// bitwise
|
|
|
|
PARAM_TEST_CASE(Bitwise, cv::gpu::DeviceInfo, MatType)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat1;
|
|
cv::Mat mat2;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = cvtest::TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat1.create(size, type);
|
|
mat2.create(size, type);
|
|
|
|
for (int i = 0; i < mat1.rows; ++i)
|
|
{
|
|
cv::Mat row1(1, static_cast<int>(mat1.cols * mat1.elemSize()), CV_8U, (void*)mat1.ptr(i));
|
|
rng.fill(row1, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
|
|
|
|
cv::Mat row2(1, static_cast<int>(mat2.cols * mat2.elemSize()), CV_8U, (void*)mat2.ptr(i));
|
|
rng.fill(row2, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
|
|
}
|
|
}
|
|
};
|
|
|
|
TEST_P(Bitwise, Not)
|
|
{
|
|
if (mat1.depth() == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Mat dst_gold = ~mat1;
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_not(loadMat(mat1), dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
TEST_P(Bitwise, Or)
|
|
{
|
|
if (mat1.depth() == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Mat dst_gold = mat1 | mat2;
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_or(loadMat(mat1), loadMat(mat2), dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
TEST_P(Bitwise, And)
|
|
{
|
|
if (mat1.depth() == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Mat dst_gold = mat1 & mat2;
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_and(loadMat(mat1), loadMat(mat2), dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
TEST_P(Bitwise, Xor)
|
|
{
|
|
if (mat1.depth() == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Mat dst_gold = mat1 ^ mat2;
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_xor(loadMat(mat1), loadMat(mat2), dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Bitwise, Combine(
|
|
ALL_DEVICES,
|
|
ALL_TYPES));
|
|
|
|
PARAM_TEST_CASE(BitwiseScalar, cv::gpu::DeviceInfo, MatType)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
|
|
cv::Size size;
|
|
cv::Mat mat;
|
|
cv::Scalar sc;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = cvtest::TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
mat.create(size, type);
|
|
|
|
for (int i = 0; i < mat.rows; ++i)
|
|
{
|
|
cv::Mat row(1, static_cast<int>(mat.cols * mat.elemSize()), CV_8U, (void*)mat.ptr(i));
|
|
rng.fill(row, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
|
|
}
|
|
|
|
sc = cv::Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
|
|
}
|
|
};
|
|
|
|
TEST_P(BitwiseScalar, Or)
|
|
{
|
|
cv::Mat dst_gold;
|
|
cv::bitwise_or(mat, sc, dst_gold);
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_or(loadMat(mat), sc, dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
TEST_P(BitwiseScalar, And)
|
|
{
|
|
cv::Mat dst_gold;
|
|
cv::bitwise_and(mat, sc, dst_gold);
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_and(loadMat(mat), sc, dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
TEST_P(BitwiseScalar, Xor)
|
|
{
|
|
cv::Mat dst_gold;
|
|
cv::bitwise_xor(mat, sc, dst_gold);
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::bitwise_xor(loadMat(mat), sc, dev_dst);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, BitwiseScalar, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32SC1, CV_32SC3, CV_32SC4)));
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
// addWeighted
|
|
|
|
PARAM_TEST_CASE(AddWeighted, cv::gpu::DeviceInfo, MatType, MatType, MatType, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type1;
|
|
int type2;
|
|
int dtype;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat src1;
|
|
cv::Mat src2;
|
|
double alpha;
|
|
double beta;
|
|
double gamma;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type1 = GET_PARAM(1);
|
|
type2 = GET_PARAM(2);
|
|
dtype = GET_PARAM(3);
|
|
useRoi = GET_PARAM(4);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
|
|
|
|
src1 = randomMat(rng, size, type1, 0.0, 255.0, false);
|
|
src2 = randomMat(rng, size, type2, 0.0, 255.0, false);
|
|
|
|
alpha = rng.uniform(-10.0, 10.0);
|
|
beta = rng.uniform(-10.0, 10.0);
|
|
gamma = rng.uniform(-10.0, 10.0);
|
|
|
|
cv::addWeighted(src1, alpha, src2, beta, gamma, dst_gold, dtype);
|
|
}
|
|
};
|
|
|
|
TEST_P(AddWeighted, Accuracy)
|
|
{
|
|
if ((src1.depth() == CV_64F || src2.depth() == CV_64F || dst_gold.depth() == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
|
|
return;
|
|
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::addWeighted(loadMat(src1, useRoi), alpha, loadMat(src2, useRoi), beta, gamma, dev_dst, dtype);
|
|
|
|
dev_dst.download(dst);
|
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, dtype < CV_32F ? 1.0 : 1e-12);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, AddWeighted, Combine(
|
|
ALL_DEVICES,
|
|
TYPES(CV_8U, CV_64F, 1, 1),
|
|
TYPES(CV_8U, CV_64F, 1, 1),
|
|
TYPES(CV_8U, CV_64F, 1, 1),
|
|
WHOLE_SUBMAT));
|
|
|
|
//////////////////////////////////////////////////////////////////////////////
|
|
// reduce
|
|
|
|
PARAM_TEST_CASE(Reduce, cv::gpu::DeviceInfo, MatType, int, ReduceOp, UseRoi)
|
|
{
|
|
cv::gpu::DeviceInfo devInfo;
|
|
int type;
|
|
int dim;
|
|
int reduceOp;
|
|
bool useRoi;
|
|
|
|
cv::Size size;
|
|
cv::Mat src;
|
|
|
|
cv::Mat dst_gold;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
type = GET_PARAM(1);
|
|
dim = GET_PARAM(2);
|
|
reduceOp = GET_PARAM(3);
|
|
useRoi = GET_PARAM(4);
|
|
|
|
cv::gpu::setDevice(devInfo.deviceID());
|
|
|
|
cv::RNG& rng = TS::ptr()->get_rng();
|
|
|
|
size = cv::Size(rng.uniform(100, 400), rng.uniform(100, 400));
|
|
|
|
src = randomMat(rng, size, type, 0.0, 255.0, false);
|
|
|
|
cv::reduce(src, dst_gold, dim, reduceOp, reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG ? CV_32F : CV_MAT_DEPTH(type));
|
|
|
|
if (dim == 1)
|
|
{
|
|
dst_gold.cols = dst_gold.rows;
|
|
dst_gold.rows = 1;
|
|
dst_gold.step = dst_gold.cols * dst_gold.elemSize();
|
|
}
|
|
}
|
|
};
|
|
|
|
TEST_P(Reduce, Accuracy)
|
|
{
|
|
cv::Mat dst;
|
|
|
|
cv::gpu::GpuMat dev_dst;
|
|
|
|
cv::gpu::reduce(loadMat(src, useRoi), dev_dst, dim, reduceOp, reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG ? CV_32F : CV_MAT_DEPTH(type));
|
|
|
|
dev_dst.download(dst);
|
|
|
|
double norm = reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG ? 1e-1 : 0.0;
|
|
EXPECT_MAT_NEAR(dst_gold, dst, norm);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Arithm, Reduce, Combine(
|
|
ALL_DEVICES,
|
|
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4),
|
|
Values(0, 1),
|
|
Values((int)CV_REDUCE_SUM, (int)CV_REDUCE_AVG, (int)CV_REDUCE_MAX, (int)CV_REDUCE_MIN),
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WHOLE_SUBMAT));
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//////////////////////////////////////////////////////////////////////////////
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// gemm
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PARAM_TEST_CASE(GEMM, cv::gpu::DeviceInfo, MatType, GemmFlags, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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int type;
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int flags;
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bool useRoi;
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|
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int size;
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cv::Mat src1;
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cv::Mat src2;
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cv::Mat src3;
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double alpha;
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double beta;
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|
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cv::Mat dst_gold;
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|
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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type = GET_PARAM(1);
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flags = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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cv::gpu::setDevice(devInfo.deviceID());
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cv::RNG& rng = TS::ptr()->get_rng();
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size = rng.uniform(100, 200);
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src1 = randomMat(rng, cv::Size(size, size), type, -10.0, 10.0, false);
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src2 = randomMat(rng, cv::Size(size, size), type, -10.0, 10.0, false);
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src3 = randomMat(rng, cv::Size(size, size), type, -10.0, 10.0, false);
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alpha = rng.uniform(-10.0, 10.0);
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beta = rng.uniform(-10.0, 10.0);
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|
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cv::gemm(src1, src2, alpha, src3, beta, dst_gold, flags);
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}
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|
};
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|
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TEST_P(GEMM, Accuracy)
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|
{
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|
cv::Mat dst;
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|
|
|
cv::gpu::GpuMat dev_dst;
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|
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cv::gpu::gemm(loadMat(src1, useRoi), loadMat(src2, useRoi), alpha, loadMat(src3, useRoi), beta, dev_dst, flags);
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|
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|
dev_dst.download(dst);
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|
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EXPECT_MAT_NEAR(dst_gold, dst, 1e-1);
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}
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|
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INSTANTIATE_TEST_CASE_P(Arithm, GEMM, Combine(
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|
ALL_DEVICES,
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|
Values(CV_32FC1, CV_32FC2),
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|
Values(0, (int) cv::GEMM_1_T, (int) cv::GEMM_2_T, (int) cv::GEMM_3_T),
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|
WHOLE_SUBMAT));
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|
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|
#endif // HAVE_CUDA
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