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d7ff3ad0cf
* converted it into Algorithm
136 lines
4.9 KiB
C++
136 lines
4.9 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 "perf_precomp.hpp"
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using namespace std;
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using namespace testing;
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using namespace perf;
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//////////////////////////////////////////////////////////////////////
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// CornerHarris
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DEF_PARAM_TEST(Image_Type_Border_BlockSz_ApertureSz, string, MatType, BorderMode, int, int);
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PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, CornerHarris,
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Combine(Values<string>("gpu/stereobm/aloe-L.png"),
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Values(CV_8UC1, CV_32FC1),
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Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_REFLECT)),
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Values(3, 5, 7),
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Values(0, 3, 5, 7)))
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{
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const string fileName = GET_PARAM(0);
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const int type = GET_PARAM(1);
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const int borderMode = GET_PARAM(2);
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const int blockSize = GET_PARAM(3);
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const int apertureSize = GET_PARAM(4);
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cv::Mat img = readImage(fileName, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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img.convertTo(img, type, type == CV_32F ? 1.0 / 255.0 : 1.0);
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const double k = 0.5;
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if (PERF_RUN_GPU())
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{
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const cv::gpu::GpuMat d_img(img);
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cv::gpu::GpuMat dst;
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cv::Ptr<cv::gpu::CornernessCriteria> harris = cv::gpu::createHarrisCorner(img.type(), blockSize, apertureSize, k, borderMode);
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TEST_CYCLE() harris->compute(d_img, dst);
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GPU_SANITY_CHECK(dst, 1e-4);
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}
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else
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{
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cv::Mat dst;
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TEST_CYCLE() cv::cornerHarris(img, dst, blockSize, apertureSize, k, borderMode);
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CPU_SANITY_CHECK(dst);
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}
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}
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//////////////////////////////////////////////////////////////////////
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// CornerMinEigenVal
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PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, CornerMinEigenVal,
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Combine(Values<string>("gpu/stereobm/aloe-L.png"),
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Values(CV_8UC1, CV_32FC1),
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Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_REFLECT)),
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Values(3, 5, 7),
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Values(0, 3, 5, 7)))
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{
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const string fileName = GET_PARAM(0);
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const int type = GET_PARAM(1);
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const int borderMode = GET_PARAM(2);
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const int blockSize = GET_PARAM(3);
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const int apertureSize = GET_PARAM(4);
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cv::Mat img = readImage(fileName, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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img.convertTo(img, type, type == CV_32F ? 1.0 / 255.0 : 1.0);
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if (PERF_RUN_GPU())
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{
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const cv::gpu::GpuMat d_img(img);
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cv::gpu::GpuMat dst;
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cv::Ptr<cv::gpu::CornernessCriteria> minEigenVal = cv::gpu::createMinEigenValCorner(img.type(), blockSize, apertureSize, borderMode);
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TEST_CYCLE() minEigenVal->compute(d_img, dst);
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GPU_SANITY_CHECK(dst, 1e-4);
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}
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else
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{
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cv::Mat dst;
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TEST_CYCLE() cv::cornerMinEigenVal(img, dst, blockSize, apertureSize, borderMode);
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CPU_SANITY_CHECK(dst);
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}
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}
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