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/*M/////////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// 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 "precomp.hpp"
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#ifdef HAVE_OPENCV_OCL
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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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namespace cv
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{
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namespace ocl
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{
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///////////////////////////OpenCL kernel strings///////////////////////////
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extern const char *surf;
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const char* noImage2dOption = "-D DISABLE_IMAGE2D";
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static void openCLExecuteKernelSURF(Context *clCxt , const char **source, string kernelName, size_t globalThreads[3],
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size_t localThreads[3], vector< pair<size_t, const void *> > &args, int channels, int depth)
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{
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if(support_image2d())
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{
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openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, channels, depth);
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}
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else
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{
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openCLExecuteKernel(clCxt, source, kernelName, globalThreads, localThreads, args, channels, depth, noImage2dOption);
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}
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}
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}
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}
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static inline size_t divUp(size_t total, size_t 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 neighbors 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, cl_mem &texture);
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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 declarations
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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, 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 icvSetUpright_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 declarations
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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()), counters(oclMat()),
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imgTex(NULL), sumTex(NULL), maskSumTex(NULL), _img(img)
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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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integral(img, surf_.sum);
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if(support_image2d())
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{
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bindImgTex(img, imgTex);
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bindImgTex(surf_.sum, sumTex);
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}
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maskSumTex = 0;
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if (use_mask)
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{
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CV_Error(CV_StsBadFunc, "Masked SURF detector is not implemented yet");
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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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//bindImgTex(surf_.maskSum, maskSumTex);
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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 Gaussian kernel.
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ensureSizeIsEnough(img_rows * (surf_.nOctaveLayers + 2), img_cols, CV_32FC1, surf_.det);
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ensureSizeIsEnough(img_rows * (surf_.nOctaveLayers + 2), img_cols, CV_32FC1, surf_.trace);
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ensureSizeIsEnough(1, maxCandidates, CV_32SC4, surf_.maxPosBuffer);
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ensureSizeIsEnough(SURF_OCL::ROWS_COUNT, maxFeatures, CV_32FC1, keypoints);
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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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int maxCounter = ((Mat)counters).at<int>(1 + octave);
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maxCounter = std::min(maxCounter, static_cast<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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int featureCounter = Mat(counters).at<int>(0);
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featureCounter = std::min(featureCounter, static_cast<int>(maxFeatures));
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keypoints.cols = featureCounter;
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if (surf_.upright)
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{
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//keypoints.row(SURF_OCL::ANGLE_ROW).setTo(Scalar::all(90.0));
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setUpright(keypoints);
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}
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else
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{
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findOrientation(keypoints);
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}
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}
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void setUpright(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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icvSetUpright_gpu(keypoints, keypoints.cols);
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}
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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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ensureSizeIsEnough(nFeatures, descriptorSize, CV_32F, descriptors);
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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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}
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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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const oclMat _img; // make a copy for non-image2d_t supported platform
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SURF_OCL_Invoker &operator= (const SURF_OCL_Invoker &right)
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{
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(*this) = right;
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return *this;
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} // remove warning C4512
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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 = saturate_cast<float>(_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);
|
|
|
|
float *kp_y = keypointsCPU.ptr<float>(SURF_OCL::Y_ROW);
|
|
|
|
int *kp_laplacian = keypointsCPU.ptr<int>(SURF_OCL::LAPLACIAN_ROW);
|
|
|
|
int *kp_octave = keypointsCPU.ptr<int>(SURF_OCL::OCTAVE_ROW);
|
|
|
|
float *kp_size = keypointsCPU.ptr<float>(SURF_OCL::SIZE_ROW);
|
|
|
|
float *kp_dir = keypointsCPU.ptr<float>(SURF_OCL::ANGLE_ROW);
|
|
|
|
float *kp_hessian = keypointsCPU.ptr<float>(SURF_OCL::HESSIAN_ROW);
|
|
|
|
|
|
|
|
for (int i = 0; i < nFeatures; ++i)
|
|
|
|
{
|
|
|
|
KeyPoint &kp = keypoints[i];
|
|
|
|
kp.pt.x = kp_x[i];
|
|
|
|
kp.pt.y = kp_y[i];
|
|
|
|
kp.class_id = kp_laplacian[i];
|
|
|
|
kp.octave = kp_octave[i];
|
|
|
|
kp.size = kp_size[i];
|
|
|
|
kp.angle = kp_dir[i];
|
|
|
|
kp.response = kp_hessian[i];
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::downloadDescriptors(const oclMat &descriptorsGPU, vector<float> &descriptors)
|
|
|
|
{
|
|
|
|
if (descriptorsGPU.empty())
|
|
|
|
descriptors.clear();
|
|
|
|
else
|
|
|
|
{
|
|
|
|
CV_Assert(descriptorsGPU.type() == CV_32F);
|
|
|
|
|
|
|
|
descriptors.resize(descriptorsGPU.rows * descriptorsGPU.cols);
|
|
|
|
Mat descriptorsCPU(descriptorsGPU.size(), CV_32F, &descriptors[0]);
|
|
|
|
descriptorsGPU.download(descriptorsCPU);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints)
|
|
|
|
{
|
|
|
|
if (!img.empty())
|
|
|
|
{
|
|
|
|
SURF_OCL_Invoker surf(*this, img, mask);
|
|
|
|
|
|
|
|
surf.detectKeypoints(keypoints);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints, oclMat &descriptors,
|
|
|
|
bool useProvidedKeypoints)
|
|
|
|
{
|
|
|
|
if (!img.empty())
|
|
|
|
{
|
|
|
|
SURF_OCL_Invoker surf(*this, img, mask);
|
|
|
|
|
|
|
|
if (!useProvidedKeypoints)
|
|
|
|
surf.detectKeypoints(keypoints);
|
|
|
|
else if (!upright)
|
|
|
|
{
|
|
|
|
surf.findOrientation(keypoints);
|
|
|
|
}
|
|
|
|
|
|
|
|
surf.computeDescriptors(keypoints, descriptors, descriptorSize());
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, vector<KeyPoint> &keypoints)
|
|
|
|
{
|
|
|
|
oclMat keypointsGPU;
|
|
|
|
|
|
|
|
(*this)(img, mask, keypointsGPU);
|
|
|
|
|
|
|
|
downloadKeypoints(keypointsGPU, keypoints);
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, vector<KeyPoint> &keypoints,
|
|
|
|
oclMat &descriptors, bool useProvidedKeypoints)
|
|
|
|
{
|
|
|
|
oclMat keypointsGPU;
|
|
|
|
|
|
|
|
if (useProvidedKeypoints)
|
|
|
|
uploadKeypoints(keypoints, keypointsGPU);
|
|
|
|
|
|
|
|
(*this)(img, mask, keypointsGPU, descriptors, useProvidedKeypoints);
|
|
|
|
|
|
|
|
downloadKeypoints(keypointsGPU, keypoints);
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::operator()(const oclMat &img, const oclMat &mask, vector<KeyPoint> &keypoints,
|
|
|
|
vector<float> &descriptors, bool useProvidedKeypoints)
|
|
|
|
{
|
|
|
|
oclMat descriptorsGPU;
|
|
|
|
|
|
|
|
(*this)(img, mask, keypoints, descriptorsGPU, useProvidedKeypoints);
|
|
|
|
|
|
|
|
downloadDescriptors(descriptorsGPU, descriptors);
|
|
|
|
}
|
|
|
|
|
|
|
|
void cv::ocl::SURF_OCL::releaseMemory()
|
|
|
|
{
|
|
|
|
sum.release();
|
|
|
|
mask1.release();
|
|
|
|
maskSum.release();
|
|
|
|
intBuffer.release();
|
|
|
|
det.release();
|
|
|
|
trace.release();
|
|
|
|
maxPosBuffer.release();
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// bind source buffer to image oject.
|
|
|
|
void SURF_OCL_Invoker::bindImgTex(const oclMat &img, cl_mem &texture)
|
|
|
|
{
|
|
|
|
if(texture)
|
|
|
|
{
|
|
|
|
openCLFree(texture);
|
|
|
|
}
|
|
|
|
texture = bindTexture(img);
|
|
|
|
}
|
|
|
|
|
|
|
|
////////////////////////////
|
|
|
|
// 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;
|
|
|
|
|
|
|
|
if(sumTex)
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&sumTex));
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.sum.data)); // if image2d is not supported
|
|
|
|
}
|
|
|
|
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));
|
|
|
|
args.push_back( make_pair( sizeof(cl_int), (void *)&surf_.sum.step));
|
|
|
|
|
|
|
|
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
|
|
|
|
};
|
|
|
|
openCLExecuteKernelSURF(clCxt, &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 useMask, int nLayers, int layer_rows, int layer_cols)
|
|
|
|
{
|
|
|
|
const int min_margin = ((calcSize(octave, 2) >> 1) >> octave) + 1;
|
|
|
|
|
|
|
|
Context *clCxt = det.clCxt;
|
|
|
|
string kernelName = useMask ? "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(useMask)
|
|
|
|
{
|
|
|
|
if(maskSumTex)
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&maskSumTex));
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.maskSum.data));
|
|
|
|
}
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.maskSum.step));
|
|
|
|
}
|
|
|
|
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
|
|
|
|
};
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
|
|
|
|
}
|
|
|
|
|
|
|
|
void SURF_OCL_Invoker::icvInterpolateKeypoint_gpu(const oclMat &det, const oclMat &maxPosBuffer, int maxCounter,
|
|
|
|
oclMat &keypoints, oclMat &counters_, int octave, int layer_rows, int max_features)
|
|
|
|
{
|
|
|
|
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 *)&max_features));
|
|
|
|
|
|
|
|
size_t localThreads[3] = {3, 3, 3};
|
|
|
|
size_t globalThreads[3] = {maxCounter *localThreads[0], localThreads[1], 1};
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &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;
|
|
|
|
|
|
|
|
if(sumTex)
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&sumTex));
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&surf_.sum.data)); // if image2d is not supported
|
|
|
|
}
|
|
|
|
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));
|
|
|
|
args.push_back( make_pair( sizeof(cl_int), (void *)&surf_.sum.step));
|
|
|
|
|
|
|
|
size_t localThreads[3] = {32, 4, 1};
|
|
|
|
size_t globalThreads[3] = {nFeatures *localThreads[0], localThreads[1], 1};
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
|
|
|
|
}
|
|
|
|
|
|
|
|
void SURF_OCL_Invoker::icvSetUpright_gpu(const oclMat &keypoints, int nFeatures)
|
|
|
|
{
|
|
|
|
Context *clCxt = counters.clCxt;
|
|
|
|
string kernelName = "icvSetUpright";
|
|
|
|
|
|
|
|
vector< pair<size_t, const void *> > args;
|
|
|
|
|
|
|
|
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 *)&nFeatures));
|
|
|
|
|
|
|
|
size_t localThreads[3] = {256, 1, 1};
|
|
|
|
size_t globalThreads[3] = {saturate_cast<size_t>(nFeatures), 1, 1};
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &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();
|
|
|
|
if(imgTex)
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&imgTex));
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&_img.data));
|
|
|
|
}
|
|
|
|
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));
|
|
|
|
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 *)&_img.step));
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
|
|
|
|
|
|
|
|
kernelName = "normalize_descriptors64";
|
|
|
|
|
|
|
|
localThreads[0] = 64;
|
|
|
|
localThreads[1] = 1;
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globalThreads[0] = nFeatures * localThreads[0];
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globalThreads[1] = localThreads[1];
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args.clear();
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args.push_back( make_pair( sizeof(cl_mem), (void *)&descriptors.data));
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args.push_back( make_pair( sizeof(cl_int), (void *)&descriptors.step));
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openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
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|
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}
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else
|
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{
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kernelName = "compute_descriptors128";
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|
|
|
|
|
|
|
localThreads[0] = 6;
|
|
|
|
localThreads[1] = 6;
|
|
|
|
|
|
|
|
globalThreads[0] = nFeatures * localThreads[0];
|
|
|
|
globalThreads[1] = 16 * localThreads[1];
|
|
|
|
|
|
|
|
args.clear();
|
|
|
|
if(imgTex)
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&imgTex));
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
args.push_back( make_pair( sizeof(cl_mem), (void *)&_img.data));
|
|
|
|
}
|
|
|
|
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));
|
|
|
|
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 *)&_img.step));
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &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));
|
|
|
|
|
|
|
|
openCLExecuteKernelSURF(clCxt, &surf, kernelName, globalThreads, localThreads, args, -1, -1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
#endif //HAVE_OPENCV_OCL
|