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ed86bd34b1
cuda_canny : multi stream safety (#11483) * CUDA_ImgProc/Canny Asynchronous test * cuda_canny : multi stream safety (1/3) - Convert global variable canny::counter to class local variable * cuda_canny : multi stream safety (2/3) - Use texture objects rather than texture reference for cc >= 3.0, since texture reference must be declared as a static global variable which results in race condition when ran concurrently * cuda_canny : multi stream safety (3/3) - Refrain from using global variable in row_filter and column_filter (converts column_filter::c_kernel and row_filter::c_kernel to local variables) * Fixes #11193
161 lines
5.7 KiB
C++
161 lines
5.7 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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namespace opencv_test { namespace {
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////////////////////////////////////////////////////////
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// Canny
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namespace
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{
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IMPLEMENT_PARAM_CLASS(AppertureSize, int)
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IMPLEMENT_PARAM_CLASS(L2gradient, bool)
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}
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PARAM_TEST_CASE(Canny, cv::cuda::DeviceInfo, AppertureSize, L2gradient, UseRoi)
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{
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cv::cuda::DeviceInfo devInfo;
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int apperture_size;
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bool useL2gradient;
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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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apperture_size = GET_PARAM(1);
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useL2gradient = GET_PARAM(2);
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useRoi = 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(Canny, Accuracy)
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{
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cv::Mat img = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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double low_thresh = 50.0;
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double high_thresh = 100.0;
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cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
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cv::cuda::GpuMat edges;
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canny->detect(loadMat(img, useRoi), edges);
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cv::Mat edges_gold;
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cv::Canny(img, edges_gold, low_thresh, high_thresh, apperture_size, useL2gradient);
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EXPECT_MAT_SIMILAR(edges_gold, edges, 2e-2);
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}
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class CannyAsyncParallelLoopBody : public cv::ParallelLoopBody
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{
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public:
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CannyAsyncParallelLoopBody(const cv::cuda::GpuMat& d_img_, cv::cuda::GpuMat* edges_, double low_thresh_, double high_thresh_, int apperture_size_, bool useL2gradient_)
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: d_img(d_img_), edges(edges_), low_thresh(low_thresh_), high_thresh(high_thresh_), apperture_size(apperture_size_), useL2gradient(useL2gradient_) {}
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~CannyAsyncParallelLoopBody() {};
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void operator()(const cv::Range& r) const
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{
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for (int i = r.start; i < r.end; i++) {
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cv::cuda::Stream stream;
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cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
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canny->detect(d_img, edges[i], stream);
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stream.waitForCompletion();
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}
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}
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protected:
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const cv::cuda::GpuMat& d_img;
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cv::cuda::GpuMat* edges;
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double low_thresh;
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double high_thresh;
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int apperture_size;
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bool useL2gradient;
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};
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#define NUM_STREAMS 64
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CUDA_TEST_P(Canny, Async)
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{
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if (!supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_30))
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{
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throw SkipTestException("CUDA device doesn't support texture objects");
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}
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else
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{
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const cv::Mat img = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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const cv::cuda::GpuMat d_img_roi = loadMat(img, useRoi);
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double low_thresh = 50.0;
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double high_thresh = 100.0;
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// Synchronous call
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cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
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cv::cuda::GpuMat edges_gold;
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canny->detect(d_img_roi, edges_gold);
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// Asynchronous call
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cv::cuda::GpuMat edges[NUM_STREAMS];
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cv::parallel_for_(cv::Range(0, NUM_STREAMS), CannyAsyncParallelLoopBody(d_img_roi, edges, low_thresh, high_thresh, apperture_size, useL2gradient));
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// Compare the results of synchronous call and asynchronous call
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for (int i = 0; i < NUM_STREAMS; i++)
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EXPECT_MAT_NEAR(edges_gold, edges[i], 0.0);
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}
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}
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INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, Canny, testing::Combine(
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ALL_DEVICES,
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testing::Values(AppertureSize(3), AppertureSize(5), AppertureSize(7)),
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testing::Values(L2gradient(false), L2gradient(true)),
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WHOLE_SUBMAT));
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}} // namespace
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#endif // HAVE_CUDA
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