220 lines
7.7 KiB
C++
220 lines
7.7 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware 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 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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namespace {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// BruteForceMatcher
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CV_ENUM(DistType, cv::ocl::BruteForceMatcher_OCL_base::L1Dist, cv::ocl::BruteForceMatcher_OCL_base::L2Dist, cv::ocl::BruteForceMatcher_OCL_base::HammingDist)
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IMPLEMENT_PARAM_CLASS(DescriptorSize, int)
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PARAM_TEST_CASE(BruteForceMatcher/*, NormCode*/, DistType, DescriptorSize)
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{
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//std::vector<cv::ocl::Info> oclinfo;
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cv::ocl::BruteForceMatcher_OCL_base::DistType distType;
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int normCode;
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int dim;
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int queryDescCount;
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int countFactor;
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cv::Mat query, train;
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virtual void SetUp()
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{
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//normCode = GET_PARAM(0);
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distType = (cv::ocl::BruteForceMatcher_OCL_base::DistType)(int)GET_PARAM(0);
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dim = GET_PARAM(1);
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//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
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//CV_Assert(devnums > 0);
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queryDescCount = 300; // must be even number because we split train data in some cases in two
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countFactor = 4; // do not change it
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cv::RNG& rng = cvtest::TS::ptr()->get_rng();
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cv::Mat queryBuf, trainBuf;
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// Generate query descriptors randomly.
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// Descriptor vector elements are integer values.
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queryBuf.create(queryDescCount, dim, CV_32SC1);
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rng.fill(queryBuf, cv::RNG::UNIFORM, cv::Scalar::all(0), cv::Scalar::all(3));
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queryBuf.convertTo(queryBuf, CV_32FC1);
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// Generate train decriptors as follows:
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// copy each query descriptor to train set countFactor times
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// and perturb some one element of the copied descriptors in
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// in ascending order. General boundaries of the perturbation
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// are (0.f, 1.f).
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trainBuf.create(queryDescCount * countFactor, dim, CV_32FC1);
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float step = 1.f / countFactor;
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for (int qIdx = 0; qIdx < queryDescCount; qIdx++)
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{
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cv::Mat queryDescriptor = queryBuf.row(qIdx);
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for (int c = 0; c < countFactor; c++)
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{
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int tIdx = qIdx * countFactor + c;
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cv::Mat trainDescriptor = trainBuf.row(tIdx);
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queryDescriptor.copyTo(trainDescriptor);
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int elem = rng(dim);
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float diff = rng.uniform(step * c, step * (c + 1));
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trainDescriptor.at<float>(0, elem) += diff;
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}
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}
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queryBuf.convertTo(query, CV_32F);
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trainBuf.convertTo(train, CV_32F);
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}
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};
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TEST_P(BruteForceMatcher, Match_Single)
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{
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cv::ocl::BruteForceMatcher_OCL_base matcher(distType);
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std::vector<cv::DMatch> matches;
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matcher.match(cv::ocl::oclMat(query), cv::ocl::oclMat(train), matches);
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ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
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int badCount = 0;
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for (size_t i = 0; i < matches.size(); i++)
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{
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cv::DMatch match = matches[i];
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if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor) || (match.imgIdx != 0))
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badCount++;
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}
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ASSERT_EQ(0, badCount);
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}
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TEST_P(BruteForceMatcher, KnnMatch_2_Single)
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{
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const int knn = 2;
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cv::ocl::BruteForceMatcher_OCL_base matcher(distType);
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std::vector< std::vector<cv::DMatch> > matches;
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matcher.knnMatch(cv::ocl::oclMat(query), cv::ocl::oclMat(train), matches, knn);
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ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
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int badCount = 0;
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for (size_t i = 0; i < matches.size(); i++)
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{
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if ((int)matches[i].size() != knn)
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badCount++;
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else
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{
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int localBadCount = 0;
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for (int k = 0; k < knn; k++)
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{
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cv::DMatch match = matches[i][k];
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if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k) || (match.imgIdx != 0))
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localBadCount++;
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}
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badCount += localBadCount > 0 ? 1 : 0;
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}
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}
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ASSERT_EQ(0, badCount);
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}
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TEST_P(BruteForceMatcher, RadiusMatch_Single)
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{
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float radius;
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if(distType == cv::ocl::BruteForceMatcher_OCL_base::L2Dist)
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radius = 1.f / countFactor /countFactor;
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else
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radius = 1.f / countFactor;
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cv::ocl::BruteForceMatcher_OCL_base matcher(distType);
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// assume support atomic.
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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< std::vector<cv::DMatch> > matches;
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// matcher.radiusMatch(loadMat(query), loadMat(train), matches, radius);
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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< std::vector<cv::DMatch> > matches;
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matcher.radiusMatch(cv::ocl::oclMat(query), cv::ocl::oclMat(train), matches, radius);
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ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
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int badCount = 0;
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for (size_t i = 0; i < matches.size(); i++)
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{
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if ((int)matches[i].size() != 1)
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{
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badCount++;
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}
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else
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{
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cv::DMatch match = matches[i][0];
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if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0))
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badCount++;
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}
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}
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ASSERT_EQ(0, badCount);
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Features2D, BruteForceMatcher, testing::Combine(
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//ALL_DEVICES,
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testing::Values(DistType(cv::ocl::BruteForceMatcher_OCL_base::L1Dist), DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist)),
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testing::Values(DescriptorSize(57), DescriptorSize(64), DescriptorSize(83), DescriptorSize(128), DescriptorSize(179), DescriptorSize(256), DescriptorSize(304))));
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} // namespace
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