285 lines
7.7 KiB
C++
285 lines
7.7 KiB
C++
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/*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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namespace opencv_test { namespace {
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// HistEven
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PARAM_TEST_CASE(HistEven, cv::cuda::DeviceInfo, cv::Size)
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{
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cv::cuda::DeviceInfo devInfo;
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cv::Size size;
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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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cv::cuda::setDevice(devInfo.deviceID());
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}
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};
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CUDA_TEST_P(HistEven, Accuracy)
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{
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cv::Mat src = randomMat(size, CV_8UC1);
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int hbins = 30;
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float hranges[] = {50.0f, 200.0f};
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cv::cuda::GpuMat hist;
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cv::cuda::histEven(loadMat(src), hist, hbins, (int) hranges[0], (int) hranges[1]);
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cv::Mat hist_gold;
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int histSize[] = {hbins};
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const float* ranges[] = {hranges};
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int channels[] = {0};
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cv::calcHist(&src, 1, channels, cv::Mat(), hist_gold, 1, histSize, ranges);
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hist_gold = hist_gold.t();
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hist_gold.convertTo(hist_gold, CV_32S);
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EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, HistEven, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES));
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// CalcHist
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PARAM_TEST_CASE(CalcHist, cv::cuda::DeviceInfo, cv::Size)
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{
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cv::cuda::DeviceInfo devInfo;
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cv::Size size;
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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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cv::cuda::setDevice(devInfo.deviceID());
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}
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};
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CUDA_TEST_P(CalcHist, Accuracy)
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{
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cv::Mat src = randomMat(size, CV_8UC1);
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cv::cuda::GpuMat hist;
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cv::cuda::calcHist(loadMat(src), hist);
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cv::Mat hist_gold;
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const int hbins = 256;
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const float hranges[] = {0.0f, 256.0f};
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const int histSize[] = {hbins};
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const float* ranges[] = {hranges};
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const int channels[] = {0};
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cv::calcHist(&src, 1, channels, cv::Mat(), hist_gold, 1, histSize, ranges);
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hist_gold = hist_gold.reshape(1, 1);
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hist_gold.convertTo(hist_gold, CV_32S);
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EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CalcHist, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES));
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PARAM_TEST_CASE(CalcHistWithMask, cv::cuda::DeviceInfo, cv::Size)
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{
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cv::cuda::DeviceInfo devInfo;
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cv::Size size;
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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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cv::cuda::setDevice(devInfo.deviceID());
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}
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};
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CUDA_TEST_P(CalcHistWithMask, Accuracy)
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{
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cv::Mat src = randomMat(size, CV_8UC1);
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cv::Mat mask = randomMat(size, CV_8UC1);
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cv::Mat(mask, cv::Rect(0, 0, size.width / 2, size.height / 2)).setTo(0);
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cv::cuda::GpuMat hist;
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cv::cuda::calcHist(loadMat(src), loadMat(mask), hist);
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cv::Mat hist_gold;
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const int hbins = 256;
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const float hranges[] = {0.0f, 256.0f};
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const int histSize[] = {hbins};
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const float* ranges[] = {hranges};
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const int channels[] = {0};
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cv::calcHist(&src, 1, channels, mask, hist_gold, 1, histSize, ranges);
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hist_gold = hist_gold.reshape(1, 1);
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hist_gold.convertTo(hist_gold, CV_32S);
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EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CalcHistWithMask, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES));
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// EqualizeHist
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PARAM_TEST_CASE(EqualizeHist, cv::cuda::DeviceInfo, cv::Size)
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{
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cv::cuda::DeviceInfo devInfo;
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cv::Size size;
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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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cv::cuda::setDevice(devInfo.deviceID());
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}
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};
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CUDA_TEST_P(EqualizeHist, Async)
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{
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cv::Mat src = randomMat(size, CV_8UC1);
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cv::cuda::Stream stream;
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cv::cuda::GpuMat dst;
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cv::cuda::equalizeHist(loadMat(src), dst, stream);
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stream.waitForCompletion();
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cv::Mat dst_gold;
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cv::equalizeHist(src, dst_gold);
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EXPECT_MAT_NEAR(dst_gold, dst, 3.0);
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}
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CUDA_TEST_P(EqualizeHist, Accuracy)
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{
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cv::Mat src = randomMat(size, CV_8UC1);
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cv::cuda::GpuMat dst;
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cv::cuda::equalizeHist(loadMat(src), dst);
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cv::Mat dst_gold;
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cv::equalizeHist(src, dst_gold);
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EXPECT_MAT_NEAR(dst_gold, dst, 3.0);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, EqualizeHist, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES));
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// CLAHE
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namespace
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{
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IMPLEMENT_PARAM_CLASS(ClipLimit, double)
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}
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PARAM_TEST_CASE(CLAHE, cv::cuda::DeviceInfo, cv::Size, ClipLimit, MatType)
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{
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cv::cuda::DeviceInfo devInfo;
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cv::Size size;
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double clipLimit;
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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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clipLimit = GET_PARAM(2);
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type = GET_PARAM(3);
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cv::cuda::setDevice(devInfo.deviceID());
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}
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};
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CUDA_TEST_P(CLAHE, Accuracy)
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{
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cv::Mat src;
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if (type == CV_8UC1)
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src = randomMat(size, type);
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else if (type == CV_16UC1)
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src = randomMat(size, type, 0, 65535);
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cv::Ptr<cv::cuda::CLAHE> clahe = cv::cuda::createCLAHE(clipLimit);
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cv::cuda::GpuMat dst;
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clahe->apply(loadMat(src), dst);
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cv::Ptr<cv::CLAHE> clahe_gold = cv::createCLAHE(clipLimit);
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cv::Mat dst_gold;
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clahe_gold->apply(src, dst_gold);
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ASSERT_MAT_NEAR(dst_gold, dst, 1.0);
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CLAHE, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(0.0, 5.0, 10.0, 20.0, 40.0),
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testing::Values(MatType(CV_8UC1), MatType(CV_16UC1))));
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}} // namespace
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#endif // HAVE_CUDA
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