2013-03-15 18:09:39 +08:00
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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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2013-03-21 17:31:51 +08:00
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// License Agreement
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2013-03-15 18:09:39 +08:00
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// For Open Source Computer Vision Library
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//
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2013-03-21 17:31:51 +08:00
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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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2013-03-15 18:09:39 +08:00
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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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2013-03-21 17:31:51 +08:00
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// * The name of the copyright holders may not be used to endorse or promote products
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2013-03-15 18:09:39 +08:00
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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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2013-03-18 20:14:37 +08:00
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#if defined(HAVE_OPENCV_GPU) && defined(HAVE_CUDA)
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2013-03-15 18:09:39 +08:00
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using namespace cvtest;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// SURF
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namespace
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{
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IMPLEMENT_PARAM_CLASS(SURF_HessianThreshold, double)
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IMPLEMENT_PARAM_CLASS(SURF_Octaves, int)
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IMPLEMENT_PARAM_CLASS(SURF_OctaveLayers, int)
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IMPLEMENT_PARAM_CLASS(SURF_Extended, bool)
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IMPLEMENT_PARAM_CLASS(SURF_Upright, bool)
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}
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PARAM_TEST_CASE(SURF, cv::gpu::DeviceInfo, SURF_HessianThreshold, SURF_Octaves, SURF_OctaveLayers, SURF_Extended, SURF_Upright)
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{
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cv::gpu::DeviceInfo devInfo;
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double hessianThreshold;
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int nOctaves;
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int nOctaveLayers;
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bool extended;
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bool upright;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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hessianThreshold = GET_PARAM(1);
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nOctaves = GET_PARAM(2);
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nOctaveLayers = GET_PARAM(3);
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extended = GET_PARAM(4);
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upright = GET_PARAM(5);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(SURF, Detector)
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{
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2013-03-18 20:14:37 +08:00
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cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image.empty());
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cv::gpu::SURF_GPU surf;
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surf.hessianThreshold = hessianThreshold;
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surf.nOctaves = nOctaves;
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surf.nOctaveLayers = nOctaveLayers;
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surf.extended = extended;
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surf.upright = upright;
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surf.keypointsRatio = 0.05f;
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if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
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{
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try
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(CV_StsNotImplemented, e.code);
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}
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}
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else
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints);
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cv::SURF surf_gold;
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surf_gold.hessianThreshold = hessianThreshold;
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surf_gold.nOctaves = nOctaves;
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surf_gold.nOctaveLayers = nOctaveLayers;
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surf_gold.extended = extended;
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surf_gold.upright = upright;
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std::vector<cv::KeyPoint> keypoints_gold;
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surf_gold(image, cv::noArray(), keypoints_gold);
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ASSERT_EQ(keypoints_gold.size(), keypoints.size());
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int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
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double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();
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EXPECT_GT(matchedRatio, 0.95);
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}
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}
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GPU_TEST_P(SURF, Detector_Masked)
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{
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2013-03-18 20:14:37 +08:00
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cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE);
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2013-03-15 18:09:39 +08:00
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ASSERT_FALSE(image.empty());
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cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
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mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
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cv::gpu::SURF_GPU surf;
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surf.hessianThreshold = hessianThreshold;
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surf.nOctaves = nOctaves;
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surf.nOctaveLayers = nOctaveLayers;
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surf.extended = extended;
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surf.upright = upright;
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surf.keypointsRatio = 0.05f;
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if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
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{
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try
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), loadMat(mask), keypoints);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(CV_StsNotImplemented, e.code);
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}
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}
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else
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), loadMat(mask), keypoints);
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cv::SURF surf_gold;
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surf_gold.hessianThreshold = hessianThreshold;
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surf_gold.nOctaves = nOctaves;
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surf_gold.nOctaveLayers = nOctaveLayers;
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surf_gold.extended = extended;
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surf_gold.upright = upright;
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std::vector<cv::KeyPoint> keypoints_gold;
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surf_gold(image, mask, keypoints_gold);
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ASSERT_EQ(keypoints_gold.size(), keypoints.size());
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int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
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double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();
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EXPECT_GT(matchedRatio, 0.95);
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}
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}
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GPU_TEST_P(SURF, Descriptor)
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{
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2013-03-18 20:14:37 +08:00
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cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE);
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2013-03-15 18:09:39 +08:00
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ASSERT_FALSE(image.empty());
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cv::gpu::SURF_GPU surf;
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surf.hessianThreshold = hessianThreshold;
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surf.nOctaves = nOctaves;
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surf.nOctaveLayers = nOctaveLayers;
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surf.extended = extended;
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surf.upright = upright;
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surf.keypointsRatio = 0.05f;
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cv::SURF surf_gold;
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surf_gold.hessianThreshold = hessianThreshold;
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surf_gold.nOctaves = nOctaves;
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surf_gold.nOctaveLayers = nOctaveLayers;
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surf_gold.extended = extended;
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surf_gold.upright = upright;
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if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
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{
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try
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{
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std::vector<cv::KeyPoint> keypoints;
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cv::gpu::GpuMat descriptors;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints, descriptors);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(CV_StsNotImplemented, e.code);
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}
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}
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else
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{
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std::vector<cv::KeyPoint> keypoints;
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surf_gold(image, cv::noArray(), keypoints);
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cv::gpu::GpuMat descriptors;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints, descriptors, true);
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cv::Mat descriptors_gold;
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surf_gold(image, cv::noArray(), keypoints, descriptors_gold, true);
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cv::BFMatcher matcher(cv::NORM_L2);
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std::vector<cv::DMatch> matches;
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matcher.match(descriptors_gold, cv::Mat(descriptors), matches);
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int matchedCount = getMatchedPointsCount(keypoints, keypoints, matches);
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double matchedRatio = static_cast<double>(matchedCount) / keypoints.size();
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EXPECT_GT(matchedRatio, 0.6);
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Features2D, SURF, testing::Combine(
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ALL_DEVICES,
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testing::Values(SURF_HessianThreshold(100.0), SURF_HessianThreshold(500.0), SURF_HessianThreshold(1000.0)),
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testing::Values(SURF_Octaves(3), SURF_Octaves(4)),
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testing::Values(SURF_OctaveLayers(2), SURF_OctaveLayers(3)),
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testing::Values(SURF_Extended(false), SURF_Extended(true)),
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testing::Values(SURF_Upright(false), SURF_Upright(true))));
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//////////////////////////////////////////////////////
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// VIBE
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PARAM_TEST_CASE(VIBE, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
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{
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};
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GPU_TEST_P(VIBE, Accuracy)
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{
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const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
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cv::gpu::setDevice(devInfo.deviceID());
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const cv::Size size = GET_PARAM(1);
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const int type = GET_PARAM(2);
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const bool useRoi = GET_PARAM(3);
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const cv::Mat fullfg(size, CV_8UC1, cv::Scalar::all(255));
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cv::Mat frame = randomMat(size, type, 0.0, 100);
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cv::gpu::GpuMat d_frame = loadMat(frame, useRoi);
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cv::gpu::VIBE_GPU vibe;
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cv::gpu::GpuMat d_fgmask = createMat(size, CV_8UC1, useRoi);
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vibe.initialize(d_frame);
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for (int i = 0; i < 20; ++i)
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vibe(d_frame, d_fgmask);
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frame = randomMat(size, type, 160, 255);
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d_frame = loadMat(frame, useRoi);
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vibe(d_frame, d_fgmask);
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// now fgmask should be entirely foreground
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ASSERT_MAT_NEAR(fullfg, d_fgmask, 0);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Video, VIBE, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4)),
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WHOLE_SUBMAT));
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2013-03-18 20:14:37 +08:00
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#endif
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