230 lines
8.7 KiB
C++
230 lines
8.7 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of 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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// Authors:
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// * Peter Andreas Entschev, peter@entschev.com
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//
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//M*/
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#include "precomp.hpp"
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#include "opencl_kernels.hpp"
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using namespace cv;
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using namespace cv::ocl;
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cv::ocl::FAST_OCL::FAST_OCL(int _threshold, bool _nonmaxSupression, double _keypointsRatio) :
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nonmaxSupression(_nonmaxSupression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0)
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{
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}
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void cv::ocl::FAST_OCL::operator ()(const oclMat& image, const oclMat& mask, std::vector<KeyPoint>& keypoints)
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{
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if (image.empty())
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return;
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(*this)(image, mask, d_keypoints_);
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downloadKeypoints(d_keypoints_, keypoints);
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}
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void cv::ocl::FAST_OCL::downloadKeypoints(const oclMat& d_keypoints, std::vector<KeyPoint>& keypoints)
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{
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if (d_keypoints.empty())
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return;
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Mat h_keypoints(d_keypoints);
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convertKeypoints(h_keypoints, keypoints);
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}
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void cv::ocl::FAST_OCL::convertKeypoints(const Mat& h_keypoints, std::vector<KeyPoint>& keypoints)
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{
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if (h_keypoints.empty())
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return;
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CV_Assert(h_keypoints.rows == ROWS_COUNT && h_keypoints.elemSize() == 4);
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int npoints = h_keypoints.cols;
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keypoints.resize(npoints);
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const float* loc_x = h_keypoints.ptr<float>(X_ROW);
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const float* loc_y = h_keypoints.ptr<float>(Y_ROW);
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const float* response_row = h_keypoints.ptr<float>(RESPONSE_ROW);
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for (int i = 0; i < npoints; ++i)
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{
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KeyPoint kp(loc_x[i], loc_y[i], static_cast<float>(FEATURE_SIZE), -1, response_row[i]);
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keypoints[i] = kp;
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}
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}
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void cv::ocl::FAST_OCL::operator ()(const oclMat& img, const oclMat& mask, oclMat& keypoints)
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{
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calcKeyPointsLocation(img, mask);
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keypoints.cols = getKeyPoints(keypoints);
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}
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int cv::ocl::FAST_OCL::calcKeyPointsLocation(const oclMat& img, const oclMat& mask)
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{
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CV_Assert(img.type() == CV_8UC1);
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CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == img.size()));
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int maxKeypoints = static_cast<int>(keypointsRatio * img.size().area());
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ensureSizeIsEnough(ROWS_COUNT, maxKeypoints, CV_32SC1, kpLoc_);
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kpLoc_.setTo(Scalar::all(0));
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if (nonmaxSupression)
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{
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ensureSizeIsEnough(img.size(), CV_32SC1, score_);
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score_.setTo(Scalar::all(0));
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}
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count_ = calcKeypointsOCL(img, mask, maxKeypoints);
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count_ = std::min(count_, maxKeypoints);
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return count_;
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}
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int cv::ocl::FAST_OCL::calcKeypointsOCL(const oclMat& img, const oclMat& mask, int maxKeypoints)
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{
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size_t localThreads[3] = {16, 16, 1};
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size_t globalThreads[3] = {divUp(img.cols - 6, localThreads[0]) * localThreads[0],
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divUp(img.rows - 6, localThreads[1]) * localThreads[1],
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1};
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Context *clCxt = Context::getContext();
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String kernelName = (mask.empty()) ? "calcKeypoints" : "calcKeypointsWithMask";
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std::vector< std::pair<size_t, const void *> > args;
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int counter = 0;
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int err = CL_SUCCESS;
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cl_mem counterCL = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(),
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CL_MEM_COPY_HOST_PTR, sizeof(int),
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&counter, &err);
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int kpLocStep = kpLoc_.step / kpLoc_.elemSize();
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int scoreStep = score_.step / score_.elemSize();
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int nms = (nonmaxSupression) ? 1 : 0;
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&img.data));
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if (!mask.empty()) args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mask.data));
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&kpLoc_.data));
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&score_.data));
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&counterCL));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&nms));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&maxKeypoints));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&threshold));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&img.step));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&img.rows));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&img.cols));
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if (!mask.empty()) args.push_back( std::make_pair( sizeof(cl_int), (void *)&mask.step));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&kpLocStep));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&scoreStep));
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openCLExecuteKernel(clCxt, &featdetect_fast, kernelName, globalThreads, localThreads, args, -1, -1);
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openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(),
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counterCL, CL_TRUE, 0, sizeof(int), &counter, 0, NULL, NULL));
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openCLSafeCall(clReleaseMemObject(counterCL));
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return counter;
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}
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int cv::ocl::FAST_OCL::nonmaxSupressionOCL(oclMat& keypoints)
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{
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size_t localThreads[3] = {256, 1, 1};
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size_t globalThreads[3] = {count_, 1, 1};
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Context *clCxt = Context::getContext();
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String kernelName = "nonmaxSupression";
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std::vector< std::pair<size_t, const void *> > args;
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int counter = 0;
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int err = CL_SUCCESS;
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cl_mem counterCL = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(),
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CL_MEM_COPY_HOST_PTR, sizeof(int),
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&counter, &err);
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int kpLocStep = kpLoc_.step / kpLoc_.elemSize();
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int sStep = score_.step / score_.elemSize();
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int kStep = keypoints.step / keypoints.elemSize();
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&kpLoc_.data));
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&score_.data));
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&keypoints.data));
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args.push_back( std::make_pair( sizeof(cl_mem), (void *)&counterCL));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&count_));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&kpLocStep));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&sStep));
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args.push_back( std::make_pair( sizeof(cl_int), (void *)&kStep));
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openCLExecuteKernel(clCxt, &featdetect_fast, kernelName, globalThreads, localThreads, args, -1, -1);
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openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(),
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counterCL, CL_TRUE, 0, sizeof(int), &counter, 0, NULL, NULL));
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openCLSafeCall(clReleaseMemObject(counterCL));
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return counter;
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}
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int cv::ocl::FAST_OCL::getKeyPoints(oclMat& keypoints)
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{
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if (count_ == 0)
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return 0;
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if (nonmaxSupression)
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{
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ensureSizeIsEnough(ROWS_COUNT, count_, CV_32FC1, keypoints);
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return nonmaxSupressionOCL(keypoints);
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}
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kpLoc_.convertTo(keypoints, CV_32FC1);
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Mat k = keypoints;
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return count_;
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}
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void cv::ocl::FAST_OCL::release()
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{
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kpLoc_.release();
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score_.release();
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d_keypoints_.release();
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}
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