opencv/modules/gpu/src/brute_force_matcher.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other GpuMaterials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or bpied warranties, including, but not limited to, the bpied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::gpu;
using namespace std;
#if !defined (HAVE_CUDA)
cv::gpu::BruteForceMatcher_GPU_base::BruteForceMatcher_GPU_base(DistType) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::add(const vector<GpuMat>&) { throw_nogpu(); }
const vector<GpuMat>& cv::gpu::BruteForceMatcher_GPU_base::getTrainDescriptors() const { throw_nogpu(); return trainDescCollection; }
void cv::gpu::BruteForceMatcher_GPU_base::clear() { throw_nogpu(); }
bool cv::gpu::BruteForceMatcher_GPU_base::empty() const { throw_nogpu(); return true; }
bool cv::gpu::BruteForceMatcher_GPU_base::isMaskSupported() const { throw_nogpu(); return true; }
void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat&, const GpuMat&, vector<DMatch>&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat&, const GpuMat&, vector<DMatch>&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::makeGpuCollection(GpuMat&, GpuMat&, const vector<GpuMat>&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat&, const GpuMat&, const GpuMat&, std::vector<DMatch>&) { throw_nogpu(); }
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void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat&, std::vector<DMatch>&, const std::vector<GpuMat>&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, int, const GpuMat&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::knnMatchDownload(const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, bool) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, int, const GpuMat&, bool) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat&, std::vector< std::vector<DMatch> >&, int, const std::vector<GpuMat>&, bool) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat&, float, const GpuMat&) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::radiusMatchDownload(const GpuMat&, const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, bool) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, const GpuMat&, std::vector< std::vector<DMatch> >&, float, const GpuMat&, bool) { throw_nogpu(); }
void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, std::vector< std::vector<DMatch> >&, float, const std::vector<GpuMat>&, bool) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace bfmatcher
{
template <typename T>
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void matchSingleL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
bool cc_12);
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template <typename T>
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void matchSingleL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
bool cc_12);
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template <typename T>
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void matchCollectionL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
const DevMem2Df& distance,
bool cc_12);
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template <typename T>
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void matchCollectionL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
const DevMem2Df& distance,
bool cc_12);
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template <typename T>
void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
template <typename T>
void knnMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
template <typename T>
void radiusMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
template <typename T>
void radiusMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
}}}
namespace
{
class ImgIdxSetter
{
public:
ImgIdxSetter(int imgIdx_) : imgIdx(imgIdx_) {}
void operator()(DMatch& m) const {m.imgIdx = imgIdx;}
private:
int imgIdx;
};
}
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cv::gpu::BruteForceMatcher_GPU_base::BruteForceMatcher_GPU_base(DistType distType_) : distType(distType_)
{
}
////////////////////////////////////////////////////////////////////
// Train collection
void cv::gpu::BruteForceMatcher_GPU_base::add(const vector<GpuMat>& descCollection)
{
trainDescCollection.insert(trainDescCollection.end(), descCollection.begin(), descCollection.end());
}
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const vector<GpuMat>& cv::gpu::BruteForceMatcher_GPU_base::getTrainDescriptors() const
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{
return trainDescCollection;
}
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void cv::gpu::BruteForceMatcher_GPU_base::clear()
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{
trainDescCollection.clear();
}
bool cv::gpu::BruteForceMatcher_GPU_base::empty() const
{
return trainDescCollection.empty();
}
bool cv::gpu::BruteForceMatcher_GPU_base::isMaskSupported() const
{
return true;
}
////////////////////////////////////////////////////////////////////
// Match
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void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs, const GpuMat& trainDescs,
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GpuMat& trainIdx, GpuMat& distance, const GpuMat& mask)
{
if (queryDescs.empty() || trainDescs.empty())
return;
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using namespace cv::gpu::bfmatcher;
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typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
bool cc_12);
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static const match_caller_t match_callers[2][8] =
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{
{
matchSingleL1_gpu<unsigned char>, matchSingleL1_gpu<signed char>,
matchSingleL1_gpu<unsigned short>, matchSingleL1_gpu<short>,
matchSingleL1_gpu<int>, matchSingleL1_gpu<float>, 0, 0
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},
{
matchSingleL2_gpu<unsigned char>, matchSingleL2_gpu<signed char>,
matchSingleL2_gpu<unsigned short>, matchSingleL2_gpu<short>,
matchSingleL2_gpu<int>, matchSingleL2_gpu<float>, 0, 0
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}
};
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CV_Assert(queryDescs.channels() == 1 && queryDescs.depth() < CV_64F);
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CV_Assert(trainDescs.cols == queryDescs.cols && trainDescs.type() == queryDescs.type());
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const int nQuery = queryDescs.rows;
trainIdx.create(1, nQuery, CV_32S);
distance.create(1, nQuery, CV_32F);
match_caller_t func = match_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
bool cc_12 = TargetArchs::builtWith(FEATURE_SET_COMPUTE_12) && DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
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// For single train there is no need to save imgIdx, so we just save imgIdx to trainIdx.
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// trainIdx store after imgIdx, so we doesn't lose it value.
func(queryDescs, trainDescs, mask, trainIdx, trainIdx, distance, cc_12);
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}
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void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat& trainIdx, const GpuMat& distance,
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vector<DMatch>& matches)
{
if (trainIdx.empty() || distance.empty())
return;
CV_Assert(trainIdx.type() == CV_32SC1 && trainIdx.isContinuous());
CV_Assert(distance.type() == CV_32FC1 && distance.isContinuous() && distance.cols == trainIdx.cols);
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const int nQuery = trainIdx.cols;
Mat trainIdxCPU = trainIdx;
Mat distanceCPU = distance;
matches.clear();
matches.reserve(nQuery);
const int* trainIdx_ptr = trainIdxCPU.ptr<int>();
const float* distance_ptr = distanceCPU.ptr<float>();
for (int queryIdx = 0; queryIdx < nQuery; ++queryIdx, ++trainIdx_ptr, ++distance_ptr)
{
int trainIdx = *trainIdx_ptr;
if (trainIdx == -1)
continue;
float distance = *distance_ptr;
DMatch m(queryIdx, trainIdx, 0, distance);
matches.push_back(m);
}
}
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void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat& queryDescs, const GpuMat& trainDescs,
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vector<DMatch>& matches, const GpuMat& mask)
{
GpuMat trainIdx, distance;
matchSingle(queryDescs, trainDescs, trainIdx, distance, mask);
matchDownload(trainIdx, distance, matches);
}
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void cv::gpu::BruteForceMatcher_GPU_base::makeGpuCollection(GpuMat& trainCollection, GpuMat& maskCollection,
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const vector<GpuMat>& masks)
{
if (empty())
return;
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if (masks.empty())
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{
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Mat trainCollectionCPU(1, trainDescCollection.size(), CV_8UC(sizeof(DevMem2D)));
for (size_t i = 0; i < trainDescCollection.size(); ++i)
{
const GpuMat& trainDescs = trainDescCollection[i];
trainCollectionCPU.ptr<DevMem2D>(0)[i] = trainDescs;
}
trainCollection.upload(trainCollectionCPU);
}
else
{
CV_Assert(masks.size() == trainDescCollection.size());
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Mat trainCollectionCPU(1, trainDescCollection.size(), CV_8UC(sizeof(DevMem2D)));
Mat maskCollectionCPU(1, trainDescCollection.size(), CV_8UC(sizeof(PtrStep)));
for (size_t i = 0; i < trainDescCollection.size(); ++i)
{
const GpuMat& trainDescs = trainDescCollection[i];
const GpuMat& mask = masks[i];
CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.cols == trainDescs.rows));
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trainCollectionCPU.ptr<DevMem2D>(0)[i] = trainDescs;
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maskCollectionCPU.ptr<PtrStep>(0)[i] = mask;
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}
trainCollection.upload(trainCollectionCPU);
maskCollection.upload(maskCollectionCPU);
}
}
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void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDescs, const GpuMat& trainCollection,
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GpuMat& trainIdx, GpuMat& imgIdx, GpuMat& distance, const GpuMat& maskCollection)
{
if (queryDescs.empty() || trainCollection.empty())
return;
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using namespace cv::gpu::bfmatcher;
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typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
const DevMem2Df& distance, bool cc_12);
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static const match_caller_t match_callers[2][8] =
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{
{
matchCollectionL1_gpu<unsigned char>, matchCollectionL1_gpu<signed char>,
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matchCollectionL1_gpu<unsigned short>, matchCollectionL1_gpu<short>,
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matchCollectionL1_gpu<int>, matchCollectionL1_gpu<float>, 0, 0
},
{
matchCollectionL2_gpu<unsigned char>, matchCollectionL2_gpu<signed char>,
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matchCollectionL2_gpu<unsigned short>, matchCollectionL2_gpu<short>,
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matchCollectionL2_gpu<int>, matchCollectionL2_gpu<float>, 0, 0
}
};
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CV_Assert(queryDescs.channels() == 1 && queryDescs.depth() < CV_64F);
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const int nQuery = queryDescs.rows;
trainIdx.create(1, nQuery, CV_32S);
imgIdx.create(1, nQuery, CV_32S);
distance.create(1, nQuery, CV_32F);
match_caller_t func = match_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
bool cc_12 = TargetArchs::builtWith(FEATURE_SET_COMPUTE_12) && DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
func(queryDescs, trainCollection, maskCollection, trainIdx, imgIdx, distance, cc_12);
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}
void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat& trainIdx, const GpuMat& imgIdx,
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const GpuMat& distance, vector<DMatch>& matches)
{
if (trainIdx.empty() || imgIdx.empty() || distance.empty())
return;
CV_Assert(trainIdx.type() == CV_32SC1 && trainIdx.isContinuous());
CV_Assert(imgIdx.type() == CV_32SC1 && imgIdx.isContinuous() && imgIdx.cols == trainIdx.cols);
CV_Assert(distance.type() == CV_32FC1 && distance.isContinuous() && imgIdx.cols == trainIdx.cols);
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const int nQuery = trainIdx.cols;
Mat trainIdxCPU = trainIdx;
Mat imgIdxCPU = imgIdx;
Mat distanceCPU = distance;
matches.clear();
matches.reserve(nQuery);
const int* trainIdx_ptr = trainIdxCPU.ptr<int>();
const int* imgIdx_ptr = imgIdxCPU.ptr<int>();
const float* distance_ptr = distanceCPU.ptr<float>();
for (int queryIdx = 0; queryIdx < nQuery; ++queryIdx, ++trainIdx_ptr, ++imgIdx_ptr, ++distance_ptr)
{
int trainIdx = *trainIdx_ptr;
if (trainIdx == -1)
continue;
int imgIdx = *imgIdx_ptr;
float distance = *distance_ptr;
DMatch m(queryIdx, trainIdx, imgIdx, distance);
matches.push_back(m);
}
}
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void cv::gpu::BruteForceMatcher_GPU_base::match(const GpuMat& queryDescs, vector<DMatch>& matches,
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const vector<GpuMat>& masks)
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{
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GpuMat trainCollection;
GpuMat maskCollection;
makeGpuCollection(trainCollection, maskCollection, masks);
GpuMat trainIdx, imgIdx, distance;
matchCollection(queryDescs, trainCollection, trainIdx, imgIdx, distance, maskCollection);
matchDownload(trainIdx, imgIdx, distance, matches);
}
////////////////////////////////////////////////////////////////////
// KnnMatch
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void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
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GpuMat& trainIdx, GpuMat& distance, GpuMat& allDist, int k, const GpuMat& mask)
{
if (queryDescs.empty() || trainDescs.empty())
return;
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using namespace cv::gpu::bfmatcher;
typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist);
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static const match_caller_t match_callers[2][8] =
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{
{
knnMatchL1_gpu<unsigned char>, knnMatchL1_gpu<signed char>, knnMatchL1_gpu<unsigned short>,
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knnMatchL1_gpu<short>, knnMatchL1_gpu<int>, knnMatchL1_gpu<float>, 0, 0
},
{
knnMatchL2_gpu<unsigned char>, knnMatchL2_gpu<signed char>, knnMatchL2_gpu<unsigned short>,
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knnMatchL2_gpu<short>, knnMatchL2_gpu<int>, knnMatchL2_gpu<float>, 0, 0
}
};
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CV_Assert(queryDescs.channels() == 1 && queryDescs.depth() < CV_64F);
CV_Assert(trainDescs.type() == queryDescs.type() && trainDescs.cols == queryDescs.cols);
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const int nQuery = queryDescs.rows;
const int nTrain = trainDescs.rows;
trainIdx.create(nQuery, k, CV_32S);
trainIdx.setTo(Scalar::all(-1));
distance.create(nQuery, k, CV_32F);
ensureSizeIsEnough(nQuery, nTrain, CV_32FC1, allDist);
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match_caller_t func = match_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
func(queryDescs, trainDescs, k, mask, trainIdx, distance, allDist);
}
void cv::gpu::BruteForceMatcher_GPU_base::knnMatchDownload(const GpuMat& trainIdx, const GpuMat& distance,
vector< vector<DMatch> >& matches, bool compactResult)
{
if (trainIdx.empty() || distance.empty())
return;
CV_Assert(trainIdx.type() == CV_32SC1);
CV_Assert(distance.type() == CV_32FC1 && distance.size() == trainIdx.size());
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const int nQuery = distance.rows;
const int k = trainIdx.cols;
Mat trainIdxCPU = trainIdx;
Mat distanceCPU = distance;
matches.clear();
matches.reserve(nQuery);
for (int queryIdx = 0; queryIdx < nQuery; ++queryIdx)
{
matches.push_back(vector<DMatch>());
vector<DMatch>& curMatches = matches.back();
curMatches.reserve(k);
int* trainIdx_ptr = trainIdxCPU.ptr<int>(queryIdx);
float* distance_ptr = distanceCPU.ptr<float>(queryIdx);
for (int i = 0; i < k; ++i, ++trainIdx_ptr, ++distance_ptr)
{
int trainIdx = *trainIdx_ptr;
if (trainIdx != -1)
{
float distance = *distance_ptr;
DMatch m(queryIdx, trainIdx, 0, distance);
curMatches.push_back(m);
}
}
if (compactResult && curMatches.empty())
matches.pop_back();
}
}
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void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
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vector< vector<DMatch> >& matches, int k, const GpuMat& mask, bool compactResult)
{
GpuMat trainIdx, distance, allDist;
knnMatch(queryDescs, trainDescs, trainIdx, distance, allDist, k, mask);
knnMatchDownload(trainIdx, distance, matches, compactResult);
}
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void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs,
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vector< vector<DMatch> >& matches, int knn, const vector<GpuMat>& masks, bool compactResult)
{
if (queryDescs.empty() || empty())
return;
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vector< vector<DMatch> > curMatches;
vector<DMatch> temp;
temp.reserve(2 * knn);
matches.resize(queryDescs.rows);
for_each(matches.begin(), matches.end(), bind2nd(mem_fun_ref(&vector<DMatch>::reserve), knn));
for (size_t imgIdx = 0; imgIdx < trainDescCollection.size(); ++imgIdx)
{
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knnMatch(queryDescs, trainDescCollection[imgIdx], curMatches, knn,
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masks.empty() ? GpuMat() : masks[imgIdx]);
for (int queryIdx = 0; queryIdx < queryDescs.rows; ++queryIdx)
{
vector<DMatch>& localMatch = curMatches[queryIdx];
vector<DMatch>& globalMatch = matches[queryIdx];
for_each(localMatch.begin(), localMatch.end(), ImgIdxSetter(imgIdx));
temp.clear();
merge(globalMatch.begin(), globalMatch.end(), localMatch.begin(), localMatch.end(), back_inserter(temp));
globalMatch.clear();
const size_t count = std::min((size_t)knn, temp.size());
copy(temp.begin(), temp.begin() + count, back_inserter(globalMatch));
}
}
if (compactResult)
{
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vector< vector<DMatch> >::iterator new_end = remove_if(matches.begin(), matches.end(),
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mem_fun_ref(&vector<DMatch>::empty));
matches.erase(new_end, matches.end());
}
}
////////////////////////////////////////////////////////////////////
// RadiusMatch
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void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
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GpuMat& trainIdx, GpuMat& nMatches, GpuMat& distance, float maxDistance, const GpuMat& mask)
{
if (queryDescs.empty() || trainDescs.empty())
return;
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using namespace cv::gpu::bfmatcher;
typedef void (*radiusMatch_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
const DevMem2D& mask, const DevMem2Di& trainIdx, unsigned int* nMatches, const DevMem2Df& distance);
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static const radiusMatch_caller_t radiusMatch_callers[2][8] =
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{
{
radiusMatchL1_gpu<unsigned char>, radiusMatchL1_gpu<signed char>, radiusMatchL1_gpu<unsigned short>,
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radiusMatchL1_gpu<short>, radiusMatchL1_gpu<int>, radiusMatchL1_gpu<float>, 0, 0
},
{
radiusMatchL2_gpu<unsigned char>, radiusMatchL2_gpu<signed char>, radiusMatchL2_gpu<unsigned short>,
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radiusMatchL2_gpu<short>, radiusMatchL2_gpu<int>, radiusMatchL2_gpu<float>, 0, 0
}
};
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CV_Assert(DeviceInfo().supports(GLOBAL_ATOMICS));
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const int nQuery = queryDescs.rows;
const int nTrain = trainDescs.rows;
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CV_Assert(queryDescs.channels() == 1 && queryDescs.depth() < CV_64F);
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CV_Assert(trainDescs.type() == queryDescs.type() && trainDescs.cols == queryDescs.cols);
CV_Assert(trainIdx.empty() || (trainIdx.rows == nQuery && trainIdx.size() == distance.size()));
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ensureSizeIsEnough(1, nQuery, CV_32SC1, nMatches);
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nMatches.setTo(Scalar::all(0));
if (trainIdx.empty())
{
trainIdx.create(nQuery, nTrain, CV_32SC1);
distance.create(nQuery, nTrain, CV_32FC1);
}
radiusMatch_caller_t func = radiusMatch_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
func(queryDescs, trainDescs, maxDistance, mask, trainIdx, nMatches.ptr<unsigned int>(), distance);
}
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void cv::gpu::BruteForceMatcher_GPU_base::radiusMatchDownload(const GpuMat& trainIdx, const GpuMat& nMatches,
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const GpuMat& distance, std::vector< std::vector<DMatch> >& matches, bool compactResult)
{
if (trainIdx.empty() || nMatches.empty() || distance.empty())
return;
CV_Assert(trainIdx.type() == CV_32SC1);
CV_Assert(nMatches.type() == CV_32SC1 && nMatches.isContinuous() && nMatches.cols >= trainIdx.rows);
CV_Assert(distance.type() == CV_32FC1 && distance.size() == trainIdx.size());
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const int nQuery = trainIdx.rows;
Mat trainIdxCPU = trainIdx;
Mat nMatchesCPU = nMatches;
Mat distanceCPU = distance;
matches.clear();
matches.reserve(nQuery);
const unsigned int* nMatches_ptr = nMatchesCPU.ptr<unsigned int>();
for (int queryIdx = 0; queryIdx < nQuery; ++queryIdx)
{
const int* trainIdx_ptr = trainIdxCPU.ptr<int>(queryIdx);
const float* distance_ptr = distanceCPU.ptr<float>(queryIdx);
const int nMatches = std::min(static_cast<int>(nMatches_ptr[queryIdx]), trainIdx.cols);
if (nMatches == 0)
{
if (!compactResult)
matches.push_back(vector<DMatch>());
continue;
}
matches.push_back(vector<DMatch>());
vector<DMatch>& curMatches = matches.back();
curMatches.reserve(nMatches);
for (int i = 0; i < nMatches; ++i, ++trainIdx_ptr, ++distance_ptr)
{
int trainIdx = *trainIdx_ptr;
float distance = *distance_ptr;
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DMatch m(queryIdx, trainIdx, 0, distance);
curMatches.push_back(m);
}
sort(curMatches.begin(), curMatches.end());
}
}
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void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs, const GpuMat& trainDescs,
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vector< vector<DMatch> >& matches, float maxDistance, const GpuMat& mask, bool compactResult)
{
GpuMat trainIdx, nMatches, distance;
radiusMatch(queryDescs, trainDescs, trainIdx, nMatches, distance, maxDistance, mask);
radiusMatchDownload(trainIdx, nMatches, distance, matches, compactResult);
}
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void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs, vector< vector<DMatch> >& matches,
float maxDistance, const vector<GpuMat>& masks, bool compactResult)
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{
if (queryDescs.empty() || empty())
return;
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matches.resize(queryDescs.rows);
vector< vector<DMatch> > curMatches;
for (size_t imgIdx = 0; imgIdx < trainDescCollection.size(); ++imgIdx)
{
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radiusMatch(queryDescs, trainDescCollection[imgIdx], curMatches, maxDistance,
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masks.empty() ? GpuMat() : masks[imgIdx]);
for (int queryIdx = 0; queryIdx < queryDescs.rows; ++queryIdx)
{
vector<DMatch>& localMatch = curMatches[queryIdx];
vector<DMatch>& globalMatch = matches[queryIdx];
for_each(localMatch.begin(), localMatch.end(), ImgIdxSetter(imgIdx));
const size_t oldSize = globalMatch.size();
copy(localMatch.begin(), localMatch.end(), back_inserter(globalMatch));
inplace_merge(globalMatch.begin(), globalMatch.begin() + oldSize, globalMatch.end());
}
}
if (compactResult)
{
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vector< vector<DMatch> >::iterator new_end = remove_if(matches.begin(), matches.end(),
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mem_fun_ref(&vector<DMatch>::empty));
matches.erase(new_end, matches.end());
}
}
#endif /* !defined (HAVE_CUDA) */