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759 lines
28 KiB
759 lines
28 KiB
/*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) 2010-2012, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// @Authors |
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// Peng Xiao, pengxiao@multicorewareinc.com |
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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 oclMaterials 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 <iomanip> |
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#include "precomp.hpp" |
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using namespace cv; |
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using namespace cv::ocl; |
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using namespace std; |
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#if !defined (HAVE_OPENCL) |
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cv::ocl::SURF_OCL::SURF_OCL() { throw_nogpu(); } |
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cv::ocl::SURF_OCL::SURF_OCL(double, int, int, bool, float, bool) { throw_nogpu(); } |
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int cv::ocl::SURF_OCL::descriptorSize() const { throw_nogpu(); return 0;} |
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void cv::ocl::SURF_OCL::uploadKeypoints(const vector<KeyPoint>&, oclMat&) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::downloadKeypoints(const oclMat&, vector<KeyPoint>&) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::downloadDescriptors(const oclMat&, vector<float>&) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::operator()(const oclMat&, const oclMat&, oclMat&) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::operator()(const oclMat&, const oclMat&, oclMat&, oclMat&, bool) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::operator()(const oclMat&, const oclMat&, vector<KeyPoint>&) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::operator()(const oclMat&, const oclMat&, vector<KeyPoint>&, oclMat&, bool) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::operator()(const oclMat&, const oclMat&, vector<KeyPoint>&, vector<float>&, bool) { throw_nogpu(); } |
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void cv::ocl::SURF_OCL::releaseMemory() { throw_nogpu(); } |
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#else /* !defined (HAVE_OPENCL) */ |
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namespace cv { namespace ocl |
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{ |
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///////////////////////////OpenCL kernel strings/////////////////////////// |
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extern const char * nonfree_surf; |
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}} |
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namespace |
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{ |
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static inline int divUp(int total, int grain) |
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{ |
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return (total + grain - 1) / grain; |
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} |
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static inline int calcSize(int octave, int layer) |
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{ |
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/* Wavelet size at first layer of first octave. */ |
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const int HAAR_SIZE0 = 9; |
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/* Wavelet size increment between layers. This should be an even number, |
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such that the wavelet sizes in an octave are either all even or all odd. |
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This ensures that when looking for the neighbours of a sample, the layers |
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above and below are aligned correctly. */ |
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const int HAAR_SIZE_INC = 6; |
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return (HAAR_SIZE0 + HAAR_SIZE_INC * layer) << octave; |
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} |
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class SURF_OCL_Invoker |
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{ |
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public: |
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// facilities |
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void bindImgTex(const oclMat& img); |
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void bindSumTex(const oclMat& sum); |
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void bindMaskSumTex(const oclMat& maskSum); |
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//void loadGlobalConstants(int maxCandidates, int maxFeatures, int img_rows, int img_cols, int nOctaveLayers, float hessianThreshold); |
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//void loadOctaveConstants(int octave, int layer_rows, int layer_cols); |
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// kernel callers declearations |
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void icvCalcLayerDetAndTrace_gpu(oclMat& det, oclMat& trace, int octave, int nOctaveLayers, int layer_rows); |
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void icvFindMaximaInLayer_gpu(const oclMat& det, const oclMat& trace, oclMat& maxPosBuffer, oclMat& maxCounter, int counterOffset, |
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int octave, bool use_mask, int nLayers, int layer_rows, int layer_cols); |
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void icvInterpolateKeypoint_gpu(const oclMat& det, const oclMat& maxPosBuffer, unsigned int maxCounter, |
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oclMat& keypoints, oclMat& counters, int octave, int layer_rows, int maxFeatures); |
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void icvCalcOrientation_gpu(const oclMat& keypoints, int nFeatures); |
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void compute_descriptors_gpu(const oclMat& descriptors, const oclMat& keypoints, int nFeatures); |
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// end of kernel callers declearations |
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SURF_OCL_Invoker(SURF_OCL& surf, const oclMat& img, const oclMat& mask) : |
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surf_(surf), |
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img_cols(img.cols), img_rows(img.rows), |
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use_mask(!mask.empty()) |
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{ |
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CV_Assert(!img.empty() && img.type() == CV_8UC1); |
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CV_Assert(mask.empty() || (mask.size() == img.size() && mask.type() == CV_8UC1)); |
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CV_Assert(surf_.nOctaves > 0 && surf_.nOctaveLayers > 0); |
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const int min_size = calcSize(surf_.nOctaves - 1, 0); |
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CV_Assert(img_rows - min_size >= 0); |
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CV_Assert(img_cols - min_size >= 0); |
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const int layer_rows = img_rows >> (surf_.nOctaves - 1); |
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const int layer_cols = img_cols >> (surf_.nOctaves - 1); |
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const int min_margin = ((calcSize((surf_.nOctaves - 1), 2) >> 1) >> (surf_.nOctaves - 1)) + 1; |
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CV_Assert(layer_rows - 2 * min_margin > 0); |
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CV_Assert(layer_cols - 2 * min_margin > 0); |
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maxFeatures = std::min(static_cast<int>(img.size().area() * surf.keypointsRatio), 65535); |
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maxCandidates = std::min(static_cast<int>(1.5 * maxFeatures), 65535); |
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CV_Assert(maxFeatures > 0); |
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counters.create(1, surf_.nOctaves + 1, CV_32SC1); |
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counters.setTo(Scalar::all(0)); |
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//loadGlobalConstants(maxCandidates, maxFeatures, img_rows, img_cols, surf_.nOctaveLayers, static_cast<float>(surf_.hessianThreshold)); |
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bindImgTex(img); |
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integral(img, surf_.sum); // the two argumented integral version is incorrect |
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bindSumTex(surf_.sum); |
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maskSumTex = 0; |
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if (use_mask) |
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{ |
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throw std::exception(); |
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//!FIXME |
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// temp fix for missing min overload |
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oclMat temp(mask.size(), mask.type()); |
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temp.setTo(Scalar::all(1.0)); |
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//cv::ocl::min(mask, temp, surf_.mask1); ///////// disable this |
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integral(surf_.mask1, surf_.maskSum); |
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bindMaskSumTex(surf_.maskSum); |
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} |
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} |
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void detectKeypoints(oclMat& keypoints) |
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{ |
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// create image pyramid buffers |
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// different layers have same sized buffers, but they are sampled from gaussin kernel. |
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surf_.det.create(img_rows * (surf_.nOctaveLayers + 2), img_cols, CV_32FC1); |
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surf_.trace.create(img_rows * (surf_.nOctaveLayers + 2), img_cols, CV_32FC1); |
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surf_.maxPosBuffer.create(1, maxCandidates, CV_32SC4); |
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keypoints.create(SURF_OCL::ROWS_COUNT, maxFeatures, CV_32FC1); |
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keypoints.setTo(Scalar::all(0)); |
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for (int octave = 0; octave < surf_.nOctaves; ++octave) |
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{ |
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const int layer_rows = img_rows >> octave; |
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const int layer_cols = img_cols >> octave; |
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//loadOctaveConstants(octave, layer_rows, layer_cols); |
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icvCalcLayerDetAndTrace_gpu(surf_.det, surf_.trace, octave, surf_.nOctaveLayers, layer_rows); |
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icvFindMaximaInLayer_gpu(surf_.det, surf_.trace, surf_.maxPosBuffer, counters, 1 + octave, |
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octave, use_mask, surf_.nOctaveLayers, layer_rows, layer_cols); |
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unsigned int maxCounter = Mat(counters).at<unsigned int>(1 + octave); |
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maxCounter = std::min(maxCounter, static_cast<unsigned int>(maxCandidates)); |
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if (maxCounter > 0) |
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{ |
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icvInterpolateKeypoint_gpu(surf_.det, surf_.maxPosBuffer, maxCounter, |
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keypoints, counters, octave, layer_rows, maxFeatures); |
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} |
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} |
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unsigned int featureCounter = Mat(counters).at<unsigned int>(0); |
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featureCounter = std::min(featureCounter, static_cast<unsigned int>(maxFeatures)); |
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keypoints.cols = featureCounter; |
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if (surf_.upright) |
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keypoints.row(SURF_OCL::ANGLE_ROW).setTo(Scalar::all(90.0)); |
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else |
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findOrientation(keypoints); |
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} |
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void findOrientation(oclMat& keypoints) |
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{ |
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const int nFeatures = keypoints.cols; |
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if (nFeatures > 0) |
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{ |
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icvCalcOrientation_gpu(keypoints, nFeatures); |
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} |
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} |
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void computeDescriptors(const oclMat& keypoints, oclMat& descriptors, int descriptorSize) |
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{ |
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const int nFeatures = keypoints.cols; |
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if (nFeatures > 0) |
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{ |
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descriptors.create(nFeatures, descriptorSize, CV_32F); |
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compute_descriptors_gpu(descriptors, keypoints, nFeatures); |
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} |
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} |
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~SURF_OCL_Invoker() |
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{ |
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if(imgTex) |
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openCLFree(imgTex); |
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if(sumTex) |
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openCLFree(sumTex); |
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if(maskSumTex) |
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openCLFree(maskSumTex); |
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additioalParamBuffer.release(); |
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} |
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private: |
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SURF_OCL& surf_; |
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int img_cols, img_rows; |
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bool use_mask; |
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int maxCandidates; |
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int maxFeatures; |
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oclMat counters; |
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// texture buffers |
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cl_mem imgTex; |
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cl_mem sumTex; |
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cl_mem maskSumTex; |
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oclMat additioalParamBuffer; |
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}; |
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} |
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cv::ocl::SURF_OCL::SURF_OCL() |
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{ |
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hessianThreshold = 100.0f; |
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extended = true; |
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nOctaves = 4; |
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nOctaveLayers = 2; |
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keypointsRatio = 0.01f; |
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upright = false; |
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} |
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cv::ocl::SURF_OCL::SURF_OCL(double _threshold, int _nOctaves, int _nOctaveLayers, bool _extended, float _keypointsRatio, bool _upright) |
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{ |
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hessianThreshold = _threshold; |
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extended = _extended; |
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nOctaves = _nOctaves; |
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nOctaveLayers = _nOctaveLayers; |
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keypointsRatio = _keypointsRatio; |
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upright = _upright; |
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} |
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int cv::ocl::SURF_OCL::descriptorSize() const |
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{ |
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return extended ? 128 : 64; |
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} |
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void cv::ocl::SURF_OCL::uploadKeypoints(const vector<KeyPoint>& keypoints, oclMat& keypointsGPU) |
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{ |
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if (keypoints.empty()) |
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keypointsGPU.release(); |
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else |
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{ |
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Mat keypointsCPU(SURF_OCL::ROWS_COUNT, static_cast<int>(keypoints.size()), CV_32FC1); |
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float* kp_x = keypointsCPU.ptr<float>(SURF_OCL::X_ROW); |
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float* kp_y = keypointsCPU.ptr<float>(SURF_OCL::Y_ROW); |
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int* kp_laplacian = keypointsCPU.ptr<int>(SURF_OCL::LAPLACIAN_ROW); |
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int* kp_octave = keypointsCPU.ptr<int>(SURF_OCL::OCTAVE_ROW); |
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float* kp_size = keypointsCPU.ptr<float>(SURF_OCL::SIZE_ROW); |
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float* kp_dir = keypointsCPU.ptr<float>(SURF_OCL::ANGLE_ROW); |
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float* kp_hessian = keypointsCPU.ptr<float>(SURF_OCL::HESSIAN_ROW); |
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for (size_t i = 0, size = keypoints.size(); i < size; ++i) |
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{ |
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const KeyPoint& kp = keypoints[i]; |
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kp_x[i] = kp.pt.x; |
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kp_y[i] = kp.pt.y; |
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kp_octave[i] = kp.octave; |
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kp_size[i] = kp.size; |
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kp_dir[i] = kp.angle; |
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kp_hessian[i] = kp.response; |
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kp_laplacian[i] = 1; |
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} |
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keypointsGPU.upload(keypointsCPU); |
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} |
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} |
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void cv::ocl::SURF_OCL::downloadKeypoints(const oclMat& keypointsGPU, vector<KeyPoint>& keypoints) |
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{ |
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const int nFeatures = keypointsGPU.cols; |
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if (nFeatures == 0) |
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keypoints.clear(); |
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else |
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{ |
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CV_Assert(keypointsGPU.type() == CV_32FC1 && keypointsGPU.rows == ROWS_COUNT); |
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Mat keypointsCPU(keypointsGPU); |
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keypoints.resize(nFeatures); |
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float* kp_x = keypointsCPU.ptr<float>(SURF_OCL::X_ROW); |
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float* kp_y = keypointsCPU.ptr<float>(SURF_OCL::Y_ROW); |
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int* kp_laplacian = keypointsCPU.ptr<int>(SURF_OCL::LAPLACIAN_ROW); |
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int* kp_octave = keypointsCPU.ptr<int>(SURF_OCL::OCTAVE_ROW); |
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float* kp_size = keypointsCPU.ptr<float>(SURF_OCL::SIZE_ROW); |
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float* kp_dir = keypointsCPU.ptr<float>(SURF_OCL::ANGLE_ROW); |
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float* kp_hessian = keypointsCPU.ptr<float>(SURF_OCL::HESSIAN_ROW); |
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for (int i = 0; i < nFeatures; ++i) |
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{ |
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KeyPoint& kp = keypoints[i]; |
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kp.pt.x = kp_x[i]; |
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kp.pt.y = kp_y[i]; |
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kp.class_id = kp_laplacian[i]; |
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kp.octave = kp_octave[i]; |
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kp.size = kp_size[i]; |
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kp.angle = kp_dir[i]; |
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kp.response = kp_hessian[i]; |
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} |
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} |
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} |
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void cv::ocl::SURF_OCL::downloadDescriptors(const oclMat& descriptorsGPU, vector<float>& descriptors) |
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{ |
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if (descriptorsGPU.empty()) |
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descriptors.clear(); |
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else |
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{ |
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CV_Assert(descriptorsGPU.type() == CV_32F); |
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descriptors.resize(descriptorsGPU.rows * descriptorsGPU.cols); |
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Mat descriptorsCPU(descriptorsGPU.size(), CV_32F, &descriptors[0]); |
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descriptorsGPU.download(descriptorsCPU); |
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} |
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} |
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void cv::ocl::SURF_OCL::operator()(const oclMat& img, const oclMat& mask, oclMat& keypoints) |
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{ |
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if (!img.empty()) |
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{ |
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SURF_OCL_Invoker surf(*this, img, mask); |
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surf.detectKeypoints(keypoints); |
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} |
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} |
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void cv::ocl::SURF_OCL::operator()(const oclMat& img, const oclMat& mask, oclMat& keypoints, oclMat& descriptors, |
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bool useProvidedKeypoints) |
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{ |
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if (!img.empty()) |
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{ |
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SURF_OCL_Invoker surf(*this, img, mask); |
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if (!useProvidedKeypoints) |
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surf.detectKeypoints(keypoints); |
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else if (!upright) |
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{ |
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surf.findOrientation(keypoints); |
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} |
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surf.computeDescriptors(keypoints, descriptors, descriptorSize()); |
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} |
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} |
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void cv::ocl::SURF_OCL::operator()(const oclMat& img, const oclMat& mask, vector<KeyPoint>& keypoints) |
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{ |
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oclMat keypointsGPU; |
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(*this)(img, mask, keypointsGPU); |
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downloadKeypoints(keypointsGPU, keypoints); |
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} |
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void cv::ocl::SURF_OCL::operator()(const oclMat& img, const oclMat& mask, vector<KeyPoint>& keypoints, |
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oclMat& descriptors, bool useProvidedKeypoints) |
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{ |
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oclMat keypointsGPU; |
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if (useProvidedKeypoints) |
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uploadKeypoints(keypoints, keypointsGPU); |
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(*this)(img, mask, keypointsGPU, descriptors, useProvidedKeypoints); |
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downloadKeypoints(keypointsGPU, keypoints); |
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} |
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void cv::ocl::SURF_OCL::operator()(const oclMat& img, const oclMat& mask, vector<KeyPoint>& keypoints, |
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vector<float>& descriptors, bool useProvidedKeypoints) |
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{ |
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oclMat descriptorsGPU; |
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(*this)(img, mask, keypoints, descriptorsGPU, useProvidedKeypoints); |
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downloadDescriptors(descriptorsGPU, descriptors); |
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} |
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void cv::ocl::SURF_OCL::releaseMemory() |
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{ |
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sum.release(); |
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mask1.release(); |
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maskSum.release(); |
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intBuffer.release(); |
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det.release(); |
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trace.release(); |
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maxPosBuffer.release(); |
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} |
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// Facilities |
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//// load SURF constants into device memory |
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//void SURF_OCL_Invoker::loadGlobalConstants(int maxCandidates, int maxFeatures, int img_rows, int img_cols, int nOctaveLayers, float hessianThreshold) |
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//{ |
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// Mat tmp(1, 9, CV_32FC1); |
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// float * tmp_data = tmp.ptr<float>(); |
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// *tmp_data = maxCandidates; |
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// *(++tmp_data) = maxFeatures; |
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// *(++tmp_data) = img_rows; |
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// *(++tmp_data) = img_cols; |
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// *(++tmp_data) = nOctaveLayers; |
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// *(++tmp_data) = hessianThreshold; |
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// additioalParamBuffer = tmp; |
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//} |
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//void SURF_OCL_Invoker::loadOctaveConstants(int octave, int layer_rows, int layer_cols) |
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//{ |
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// Mat tmp = additioalParamBuffer; |
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// float * tmp_data = tmp.ptr<float>(); |
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// tmp_data += 6; |
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// *tmp_data = octave; |
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// *(++tmp_data) = layer_rows; |
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// *(++tmp_data) = layer_cols; |
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// additioalParamBuffer = tmp; |
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//} |
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// create and bind source buffer to image oject. |
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void SURF_OCL_Invoker::bindImgTex(const oclMat& img) |
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{ |
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Mat cpu_img(img); // time consuming |
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cl_image_format format; |
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int err; |
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format.image_channel_data_type = CL_UNSIGNED_INT8; |
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format.image_channel_order = CL_R; |
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#if CL_VERSION_1_2 |
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cl_image_desc desc; |
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desc.image_type = CL_MEM_OBJECT_IMAGE2D; |
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desc.image_width = cpu_img.cols; |
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desc.image_height = cpu_img.rows; |
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desc.image_depth = NULL; |
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desc.image_array_size = 1; |
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desc.image_row_pitch = cpu_img.step; |
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desc.image_slice_pitch= 0; |
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desc.buffer = NULL; |
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desc.num_mip_levels = 0; |
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desc.num_samples = 0; |
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imgTex = clCreateImage(img.clCxt->impl->clContext, CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR, &format, &desc, cpu_img.data, &err); |
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#else |
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imgTex = clCreateImage2D( |
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img.clCxt->impl->clContext, |
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CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR, |
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&format, |
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cpu_img.cols, |
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cpu_img.rows, |
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cpu_img.step, |
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cpu_img.data, |
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&err); |
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#endif |
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openCLSafeCall(err); |
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} |
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void SURF_OCL_Invoker::bindSumTex(const oclMat& sum) |
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{ |
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Mat cpu_img(sum); // time consuming |
|
cl_image_format format; |
|
int err; |
|
format.image_channel_data_type = CL_UNSIGNED_INT32; |
|
format.image_channel_order = CL_R; |
|
#if CL_VERSION_1_2 |
|
cl_image_desc desc; |
|
desc.image_type = CL_MEM_OBJECT_IMAGE2D; |
|
desc.image_width = cpu_img.cols; |
|
desc.image_height = cpu_img.rows; |
|
desc.image_depth = NULL; |
|
desc.image_array_size = 1; |
|
desc.image_row_pitch = cpu_img.step; |
|
desc.image_slice_pitch= 0; |
|
desc.buffer = NULL; |
|
desc.num_mip_levels = 0; |
|
desc.num_samples = 0; |
|
sumTex = clCreateImage(sum.clCxt->impl->clContext, CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR, &format, &desc, cpu_img.data, &err); |
|
#else |
|
sumTex = clCreateImage2D( |
|
sum.clCxt->impl->clContext, |
|
CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR, |
|
&format, |
|
cpu_img.cols, |
|
cpu_img.rows, |
|
cpu_img.step, |
|
cpu_img.data, |
|
&err); |
|
#endif |
|
openCLSafeCall(err); |
|
} |
|
void SURF_OCL_Invoker::bindMaskSumTex(const oclMat& maskSum) |
|
{ |
|
Mat cpu_img(maskSum); // time consuming |
|
cl_image_format format; |
|
int err; |
|
format.image_channel_data_type = CL_UNSIGNED_INT32; |
|
format.image_channel_order = CL_R; |
|
#if CL_VERSION_1_2 |
|
cl_image_desc desc; |
|
desc.image_type = CL_MEM_OBJECT_IMAGE2D; |
|
desc.image_width = cpu_img.cols; |
|
desc.image_height = cpu_img.rows; |
|
desc.image_depth = NULL; |
|
desc.image_array_size = 1; |
|
desc.image_row_pitch = cpu_img.step; |
|
desc.image_slice_pitch= 0; |
|
desc.buffer = NULL; |
|
desc.num_mip_levels = 0; |
|
desc.num_samples = 0; |
|
maskSumTex = clCreateImage(maskSum.clCxt->impl->clContext, CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR, &format, &desc, cpu_img.data, &err); |
|
#else |
|
maskSumTex = clCreateImage2D( |
|
maskSum.clCxt->impl->clContext, |
|
CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR, |
|
&format, |
|
cpu_img.cols, |
|
cpu_img.rows, |
|
cpu_img.step, |
|
cpu_img.data, |
|
&err); |
|
#endif |
|
openCLSafeCall(err); |
|
} |
|
|
|
//////////////////////////// |
|
// kernel caller definitions |
|
void SURF_OCL_Invoker::icvCalcLayerDetAndTrace_gpu(oclMat& det, oclMat& trace, int octave, int nOctaveLayers, int c_layer_rows) |
|
{ |
|
const int min_size = calcSize(octave, 0); |
|
const int max_samples_i = 1 + ((img_rows - min_size) >> octave); |
|
const int max_samples_j = 1 + ((img_cols - min_size) >> octave); |
|
|
|
Context *clCxt = det.clCxt; |
|
string kernelName = "icvCalcLayerDetAndTrace"; |
|
vector< pair<size_t, const void *> > args; |
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&sumTex)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&det.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&trace.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&det.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&trace.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&nOctaveLayers)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&octave)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&c_layer_rows)); |
|
|
|
size_t localThreads[3] = {16, 16, 1}; |
|
size_t globalThreads[3] = { |
|
divUp(max_samples_j, localThreads[0]) * localThreads[0], |
|
divUp(max_samples_i, localThreads[1]) * localThreads[1] * (nOctaveLayers + 2), |
|
1}; |
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
} |
|
|
|
void SURF_OCL_Invoker::icvFindMaximaInLayer_gpu(const oclMat& det, const oclMat& trace, oclMat& maxPosBuffer, oclMat& maxCounter, int counterOffset, |
|
int octave, bool use_mask, int nLayers, int layer_rows, int layer_cols) |
|
{ |
|
const int min_margin = ((calcSize(octave, 2) >> 1) >> octave) + 1; |
|
|
|
Context *clCxt = det.clCxt; |
|
string kernelName = use_mask ? "icvFindMaximaInLayer_withmask" : "icvFindMaximaInLayer"; |
|
vector< pair<size_t, const void *> > args; |
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&det.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&trace.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&maxPosBuffer.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&maxCounter.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&counterOffset)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&det.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&trace.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&nLayers)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&octave)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&layer_rows)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&layer_cols)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&maxCandidates)); |
|
args.push_back( make_pair( sizeof(cl_float), (void *)&surf_.hessianThreshold)); |
|
|
|
if(use_mask) |
|
{ |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&maskSumTex)); |
|
} |
|
|
|
size_t localThreads[3] = {16, 16, 1}; |
|
size_t globalThreads[3] = {divUp(layer_cols - 2 * min_margin, localThreads[0] - 2) * localThreads[0], |
|
divUp(layer_rows - 2 * min_margin, localThreads[1] - 2) * nLayers * localThreads[1], |
|
1}; |
|
|
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
} |
|
|
|
void SURF_OCL_Invoker::icvInterpolateKeypoint_gpu(const oclMat& det, const oclMat& maxPosBuffer, unsigned int maxCounter, |
|
oclMat& keypoints, oclMat& counters, int octave, int layer_rows, int maxFeatures) |
|
{ |
|
Context *clCxt = det.clCxt; |
|
string kernelName = "icvInterpolateKeypoint"; |
|
vector< pair<size_t, const void *> > args; |
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&det.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&maxPosBuffer.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&counters.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&det.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&octave)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&layer_rows)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&maxFeatures)); |
|
|
|
size_t localThreads[3] = {3, 3, 3}; |
|
size_t globalThreads[3] = {maxCounter * localThreads[0], 1, 1}; |
|
|
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
} |
|
|
|
void SURF_OCL_Invoker::icvCalcOrientation_gpu(const oclMat& keypoints, int nFeatures) |
|
{ |
|
Context * clCxt = counters.clCxt; |
|
string kernelName = "icvCalcOrientation"; |
|
|
|
vector< pair<size_t, const void *> > args; |
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&sumTex)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_rows)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&img_cols)); |
|
|
|
size_t localThreads[3] = {32, 4, 1}; |
|
size_t globalThreads[3] = {nFeatures * localThreads[0], localThreads[1], 1}; |
|
|
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
} |
|
|
|
void SURF_OCL_Invoker::compute_descriptors_gpu(const oclMat& descriptors, const oclMat& keypoints, int nFeatures) |
|
{ |
|
// compute unnormalized descriptors, then normalize them - odd indexing since grid must be 2D |
|
Context *clCxt = descriptors.clCxt; |
|
string kernelName = ""; |
|
vector< pair<size_t, const void *> > args; |
|
size_t localThreads[3] = {1, 1, 1}; |
|
size_t globalThreads[3] = {1, 1, 1}; |
|
|
|
if(descriptors.cols == 64) |
|
{ |
|
kernelName = "compute_descriptors64"; |
|
|
|
localThreads[0] = 6; |
|
localThreads[1] = 6; |
|
|
|
globalThreads[0] = nFeatures * localThreads[0]; |
|
globalThreads[1] = 16 * localThreads[1]; |
|
|
|
args.clear(); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&imgTex)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step)); |
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
|
|
kernelName = "normalize_descriptors64"; |
|
|
|
localThreads[0] = 64; |
|
localThreads[1] = 1; |
|
|
|
globalThreads[0] = nFeatures * localThreads[0]; |
|
globalThreads[1] = localThreads[1]; |
|
|
|
args.clear(); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step)); |
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
} |
|
else |
|
{ |
|
kernelName = "compute_descriptors128"; |
|
|
|
localThreads[0] = 6; |
|
localThreads[1] = 6; |
|
|
|
globalThreads[0] = nFeatures * localThreads[0]; |
|
globalThreads[1] = 16 * localThreads[1]; |
|
|
|
args.clear(); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&imgTex)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data)); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&keypoints.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&keypoints.step)); |
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
|
|
kernelName = "normalize_descriptors128"; |
|
|
|
localThreads[0] = 128; |
|
localThreads[1] = 1; |
|
|
|
globalThreads[0] = nFeatures * localThreads[0]; |
|
globalThreads[1] = localThreads[1]; |
|
|
|
args.clear(); |
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data)); |
|
args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step)); |
|
openCLExecuteKernel(clCxt, &nonfree_surf, kernelName, globalThreads, localThreads, args, -1, -1); |
|
} |
|
} |
|
|
|
#endif // /* !defined (HAVE_OPENCL) */ |
|
|
|
|