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78be4f66f7
Conflicts: CMakeLists.txt modules/calib3d/src/calibration.cpp modules/ocl/src/cl_programcache.cpp modules/ocl/src/filtering.cpp modules/ocl/src/imgproc.cpp samples/ocl/adaptive_bilateral_filter.cpp samples/ocl/bgfg_segm.cpp samples/ocl/clahe.cpp samples/ocl/facedetect.cpp samples/ocl/pyrlk_optical_flow.cpp samples/ocl/squares.cpp samples/ocl/surf_matcher.cpp samples/ocl/tvl1_optical_flow.cpp
1947 lines
117 KiB
C++
1947 lines
117 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) 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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// Wenju He, wenju@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 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 bpied warranties, including, but not limited to, the bpied
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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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#include "opencl_kernels.hpp"
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using namespace cv;
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using namespace cv::ocl;
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#define CELL_WIDTH 8
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#define CELL_HEIGHT 8
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#define CELLS_PER_BLOCK_X 2
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#define CELLS_PER_BLOCK_Y 2
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#define NTHREADS 256
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static oclMat gauss_w_lut;
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static bool hog_device_cpu;
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namespace cv
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{
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namespace ocl
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{
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namespace device
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{
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namespace hog
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{
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int cnbins;
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int cblock_stride_x;
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int cblock_stride_y;
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int cnblocks_win_x;
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int cnblocks_win_y;
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int cblock_hist_size;
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int cdescr_size;
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int cdescr_width;
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int cdescr_height;
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void set_up_constants(int nbins, int block_stride_x, int block_stride_y,
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int nblocks_win_x, int nblocks_win_y);
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void compute_hists(int nbins, int block_stride_x, int blovck_stride_y,
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int height, int width, const cv::ocl::oclMat &grad,
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const cv::ocl::oclMat &qangle,
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const cv::ocl::oclMat &gauss_w_lut, cv::ocl::oclMat &block_hists);
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void normalize_hists(int nbins, int block_stride_x, int block_stride_y,
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int height, int width, cv::ocl::oclMat &block_hists,
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float threshold);
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void classify_hists(int win_height, int win_width, int block_stride_y,
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int block_stride_x, int win_stride_y, int win_stride_x,
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int height, int width, const cv::ocl::oclMat &block_hists,
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const cv::ocl::oclMat &coefs, float free_coef,
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float threshold, cv::ocl::oclMat &labels);
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void extract_descrs_by_rows(int win_height, int win_width, int block_stride_y,
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int block_stride_x, int win_stride_y, int win_stride_x,
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int height, int width, const cv::ocl::oclMat &block_hists,
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cv::ocl::oclMat &descriptors);
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void extract_descrs_by_cols(int win_height, int win_width, int block_stride_y,
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int block_stride_x, int win_stride_y, int win_stride_x,
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int height, int width, const cv::ocl::oclMat &block_hists,
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cv::ocl::oclMat &descriptors);
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void compute_gradients_8UC1(int height, int width, const cv::ocl::oclMat &img,
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float angle_scale, cv::ocl::oclMat &grad,
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cv::ocl::oclMat &qangle, bool correct_gamma);
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void compute_gradients_8UC4(int height, int width, const cv::ocl::oclMat &img,
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float angle_scale, cv::ocl::oclMat &grad,
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cv::ocl::oclMat &qangle, bool correct_gamma);
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}
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}
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}
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}
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using namespace ::cv::ocl::device;
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cv::ocl::HOGDescriptor::HOGDescriptor(Size win_size_, Size block_size_, Size block_stride_,
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Size cell_size_, int nbins_, double win_sigma_,
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double threshold_L2hys_, bool gamma_correction_, int nlevels_)
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: win_size(win_size_),
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block_size(block_size_),
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block_stride(block_stride_),
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cell_size(cell_size_),
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nbins(nbins_),
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win_sigma(win_sigma_),
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threshold_L2hys(threshold_L2hys_),
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gamma_correction(gamma_correction_),
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nlevels(nlevels_)
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{
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CV_Assert((win_size.width - block_size.width ) % block_stride.width == 0 &&
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(win_size.height - block_size.height) % block_stride.height == 0);
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CV_Assert(block_size.width % cell_size.width == 0 &&
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block_size.height % cell_size.height == 0);
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CV_Assert(block_stride == cell_size);
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CV_Assert(cell_size == Size(8, 8));
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Size cells_per_block(block_size.width / cell_size.width,
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block_size.height / cell_size.height);
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CV_Assert(cells_per_block == Size(2, 2));
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cv::Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride);
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hog::set_up_constants(nbins, block_stride.width, block_stride.height,
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blocks_per_win.width, blocks_per_win.height);
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effect_size = Size(0, 0);
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if (isCpuDevice())
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hog_device_cpu = true;
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else
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hog_device_cpu = false;
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}
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size_t cv::ocl::HOGDescriptor::getDescriptorSize() const
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{
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return numPartsWithin(win_size, block_size, block_stride).area() * getBlockHistogramSize();
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}
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size_t cv::ocl::HOGDescriptor::getBlockHistogramSize() const
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{
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Size cells_per_block = Size(block_size.width / cell_size.width,
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block_size.height / cell_size.height);
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return (size_t)(nbins * cells_per_block.area());
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}
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double cv::ocl::HOGDescriptor::getWinSigma() const
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{
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return win_sigma >= 0 ? win_sigma : (block_size.width + block_size.height) / 8.0;
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}
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bool cv::ocl::HOGDescriptor::checkDetectorSize() const
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{
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size_t detector_size = detector.rows * detector.cols;
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size_t descriptor_size = getDescriptorSize();
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return detector_size == 0 || detector_size == descriptor_size ||
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detector_size == descriptor_size + 1;
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}
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void cv::ocl::HOGDescriptor::setSVMDetector(const std::vector<float> &_detector)
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{
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std::vector<float> detector_reordered(_detector.size());
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size_t block_hist_size = getBlockHistogramSize();
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cv::Size blocks_per_img = numPartsWithin(win_size, block_size, block_stride);
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for (int i = 0; i < blocks_per_img.height; ++i)
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for (int j = 0; j < blocks_per_img.width; ++j)
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{
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const float *src = &_detector[0] + (j * blocks_per_img.height + i) * block_hist_size;
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float *dst = &detector_reordered[0] + (i * blocks_per_img.width + j) * block_hist_size;
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for (size_t k = 0; k < block_hist_size; ++k)
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dst[k] = src[k];
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}
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this->detector.upload(Mat(detector_reordered).reshape(1, 1));
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size_t descriptor_size = getDescriptorSize();
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free_coef = _detector.size() > descriptor_size ? _detector[descriptor_size] : 0;
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CV_Assert(checkDetectorSize());
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}
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void cv::ocl::HOGDescriptor::init_buffer(const oclMat &img, Size win_stride)
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{
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if (!image_scale.empty())
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return;
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if (effect_size == Size(0, 0))
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effect_size = img.size();
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grad.create(img.size(), CV_32FC2);
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qangle.create(img.size(), CV_8UC2);
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const size_t block_hist_size = getBlockHistogramSize();
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const Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride);
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block_hists.create(1,
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static_cast<int>(block_hist_size * blocks_per_img.area()) + 256, CV_32F);
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Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride);
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labels.create(1, wins_per_img.area(), CV_8U);
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float sigma = getWinSigma();
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float scale = 1.f / (2.f * sigma * sigma);
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Mat gaussian_lut(1, 512, CV_32FC1);
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int idx = 0;
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for(int i=-8; i<8; i++)
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for(int j=-8; j<8; j++)
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gaussian_lut.at<float>(idx++) = std::exp(-(j * j + i * i) * scale);
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for(int i=-8; i<8; i++)
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for(int j=-8; j<8; j++)
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gaussian_lut.at<float>(idx++) = (8.f - fabs(j + 0.5f)) * (8.f - fabs(i + 0.5f)) / 64.f;
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gauss_w_lut.upload(gaussian_lut);
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}
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void cv::ocl::HOGDescriptor::computeGradient(const oclMat &img, oclMat &grad, oclMat &qangle)
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{
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CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
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float angleScale = (float)(nbins / CV_PI);
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switch (img.type())
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{
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case CV_8UC1:
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hog::compute_gradients_8UC1(effect_size.height, effect_size.width, img,
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angleScale, grad, qangle, gamma_correction);
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break;
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case CV_8UC4:
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hog::compute_gradients_8UC4(effect_size.height, effect_size.width, img,
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angleScale, grad, qangle, gamma_correction);
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break;
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}
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}
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void cv::ocl::HOGDescriptor::computeBlockHistograms(const oclMat &img)
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{
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computeGradient(img, this->grad, this->qangle);
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hog::compute_hists(nbins, block_stride.width, block_stride.height, effect_size.height,
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effect_size.width, grad, qangle, gauss_w_lut, block_hists);
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hog::normalize_hists(nbins, block_stride.width, block_stride.height, effect_size.height,
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effect_size.width, block_hists, (float)threshold_L2hys);
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}
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void cv::ocl::HOGDescriptor::getDescriptors(const oclMat &img, Size win_stride,
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oclMat &descriptors, int descr_format)
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{
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CV_Assert(win_stride.width % block_stride.width == 0 &&
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win_stride.height % block_stride.height == 0);
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init_buffer(img, win_stride);
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computeBlockHistograms(img);
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const size_t block_hist_size = getBlockHistogramSize();
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Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride);
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Size wins_per_img = numPartsWithin(effect_size, win_size, win_stride);
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descriptors.create(wins_per_img.area(),
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static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F);
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switch (descr_format)
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{
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case DESCR_FORMAT_ROW_BY_ROW:
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hog::extract_descrs_by_rows(win_size.height, win_size.width,
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block_stride.height, block_stride.width, win_stride.height, win_stride.width,
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effect_size.height, effect_size.width, block_hists, descriptors);
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break;
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case DESCR_FORMAT_COL_BY_COL:
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hog::extract_descrs_by_cols(win_size.height, win_size.width,
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block_stride.height, block_stride.width, win_stride.height, win_stride.width,
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effect_size.height, effect_size.width, block_hists, descriptors);
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break;
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default:
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CV_Error(Error::StsBadArg, "Unknown descriptor format");
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}
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}
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void cv::ocl::HOGDescriptor::detect(const oclMat &img, std::vector<Point> &hits,
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double hit_threshold, Size win_stride, Size padding)
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{
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CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
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CV_Assert(padding == Size(0, 0));
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hits.clear();
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if (detector.empty())
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return;
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if (win_stride == Size())
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win_stride = block_stride;
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else
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CV_Assert(win_stride.width % block_stride.width == 0 &&
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win_stride.height % block_stride.height == 0);
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init_buffer(img, win_stride);
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computeBlockHistograms(img);
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hog::classify_hists(win_size.height, win_size.width, block_stride.height,
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block_stride.width, win_stride.height, win_stride.width,
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effect_size.height, effect_size.width, block_hists, detector,
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(float)free_coef, (float)hit_threshold, labels);
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labels.download(labels_host);
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unsigned char *vec = labels_host.ptr();
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Size wins_per_img = numPartsWithin(effect_size, win_size, win_stride);
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for (int i = 0; i < wins_per_img.area(); i++)
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{
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int y = i / wins_per_img.width;
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int x = i - wins_per_img.width * y;
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if (vec[i])
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hits.push_back(Point(x * win_stride.width, y * win_stride.height));
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}
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}
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void cv::ocl::HOGDescriptor::detectMultiScale(const oclMat &img, std::vector<Rect> &found_locations,
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double hit_threshold, Size win_stride, Size padding,
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double scale0, int group_threshold)
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{
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CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
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CV_Assert(scale0 > 1);
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std::vector<double> level_scale;
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double scale = 1.;
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int levels = 0;
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for (levels = 0; levels < nlevels; levels++)
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{
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level_scale.push_back(scale);
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if (cvRound(img.cols / scale) < win_size.width ||
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cvRound(img.rows / scale) < win_size.height || scale0 <= 1)
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break;
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scale *= scale0;
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}
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levels = std::max(levels, 1);
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level_scale.resize(levels);
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std::vector<Rect> all_candidates;
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std::vector<Point> locations;
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if (win_stride == Size())
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win_stride = block_stride;
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else
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CV_Assert(win_stride.width % block_stride.width == 0 &&
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win_stride.height % block_stride.height == 0);
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init_buffer(img, win_stride);
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image_scale.create(img.size(), img.type());
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for (size_t i = 0; i < level_scale.size(); i++)
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{
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scale = level_scale[i];
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effect_size = Size(cvRound(img.cols / scale), cvRound(img.rows / scale));
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if (effect_size == img.size())
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{
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detect(img, locations, hit_threshold, win_stride, padding);
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}
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else
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{
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resize(img, image_scale, effect_size);
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detect(image_scale, locations, hit_threshold, win_stride, padding);
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}
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Size scaled_win_size(cvRound(win_size.width * scale),
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cvRound(win_size.height * scale));
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for (size_t j = 0; j < locations.size(); j++)
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all_candidates.push_back(Rect(Point2d(locations[j]) * scale, scaled_win_size));
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}
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found_locations.assign(all_candidates.begin(), all_candidates.end());
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groupRectangles(found_locations, group_threshold, 0.2);
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}
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int cv::ocl::HOGDescriptor::numPartsWithin(int size, int part_size, int stride)
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{
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return (size - part_size + stride) / stride;
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}
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cv::Size cv::ocl::HOGDescriptor::numPartsWithin(cv::Size size, cv::Size part_size,
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cv::Size stride)
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{
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return Size(numPartsWithin(size.width, part_size.width, stride.width),
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numPartsWithin(size.height, part_size.height, stride.height));
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}
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std::vector<float> cv::ocl::HOGDescriptor::getDefaultPeopleDetector()
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{
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return getPeopleDetector64x128();
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}
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std::vector<float> cv::ocl::HOGDescriptor::getPeopleDetector48x96()
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{
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static const float detector[] =
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{
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0.294350f, -0.098796f, -0.129522f, 0.078753f, 0.387527f, 0.261529f,
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0.145939f, 0.061520f, 0.328699f, 0.227148f, -0.066467f, -0.086723f,
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0.047559f, 0.106714f, 0.037897f, 0.111461f, -0.024406f, 0.304769f,
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0.254676f, -0.069235f, 0.082566f, 0.147260f, 0.326969f, 0.148888f,
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0.055270f, -0.087985f, 0.261720f, 0.143442f, 0.026812f, 0.238212f,
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0.194020f, 0.056341f, -0.025854f, -0.034444f, -0.156631f, 0.205174f,
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0.089008f, -0.139811f, -0.100147f, -0.037830f, -0.029230f, -0.055641f,
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0.033248f, -0.016512f, 0.155244f, 0.247315f, -0.124694f, -0.048414f,
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-0.062219f, 0.193683f, 0.004574f, 0.055089f, 0.093565f, 0.167712f,
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0.167581f, 0.018895f, 0.215258f, 0.122609f, 0.090520f, -0.067219f,
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-0.049029f, -0.099615f, 0.241804f, -0.094893f, -0.176248f, 0.001727f,
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-0.054920f, 0.144955f, 0.036517f, -0.085412f, -0.229070f, -0.143710f,
|
|
-0.049486f, 0.156634f, -0.008673f, -0.064778f, 0.082344f, 0.145673f,
|
|
0.002912f, -0.210121f, -0.116564f, 0.078425f, 0.220908f, -0.067594f,
|
|
0.048610f, 0.084912f, -0.066202f, -0.112515f, -0.217767f, -0.082640f,
|
|
-0.017414f, 0.230265f, -0.070735f, 0.066073f, 0.215256f, 0.071157f,
|
|
-0.087220f, -0.202235f, -0.011918f, 0.099562f, 0.174716f, -0.063845f,
|
|
-0.121055f, 0.014367f, 0.132709f, -0.005060f, -0.244606f, -0.179693f,
|
|
-0.134690f, 0.023239f, -0.193116f, -0.076975f, -0.021164f, -0.001938f,
|
|
-0.163799f, -0.111437f, -0.210362f, -0.166376f, 0.034754f, 0.010036f,
|
|
-0.021917f, 0.068014f, -0.086893f, -0.251746f, -0.267171f, 0.037383f,
|
|
0.003966f, 0.033571f, -0.151506f, 0.025437f, -0.020626f, -0.308454f,
|
|
-0.343143f, -0.092263f, -0.026261f, -0.028345f, 0.036036f, 0.035169f,
|
|
0.129470f, 0.122205f, 0.015661f, -0.070612f, -0.094333f, -0.066055f,
|
|
-0.041083f, 0.159146f, 0.073184f, 0.110044f, 0.174471f, 0.078069f,
|
|
-0.014881f, 0.008116f, 0.013209f, 0.075857f, 0.195605f, 0.062714f,
|
|
0.067955f, 0.056544f, -0.153908f, -0.141749f, -0.072550f, 0.033523f,
|
|
-0.024665f, 0.134487f, 0.079076f, 0.133562f, 0.227130f, 0.018054f,
|
|
0.004928f, 0.169162f, 0.065152f, 0.072160f, 0.131631f, 0.096303f,
|
|
0.054288f, 0.106256f, 0.114632f, 0.119038f, 0.515200f, 0.247429f,
|
|
0.199134f, 0.211957f, 0.127558f, -0.294684f, -0.194890f, -0.049988f,
|
|
-0.112247f, -0.008122f, -0.006176f, 0.037035f, -0.110881f, -0.249989f,
|
|
0.152434f, 0.234621f, 0.153340f, 0.349283f, 0.683049f, 0.157174f,
|
|
0.124844f, 0.099136f, 0.064407f, -0.248400f, -0.155323f, -0.026498f,
|
|
-0.023450f, 0.049051f, -0.114187f, 0.007195f, -0.176825f, -0.376926f,
|
|
0.366159f, -0.179938f, -0.148508f, 0.006043f, 0.170048f, 0.097866f,
|
|
-0.102658f, -0.260430f, 0.248868f, 0.037019f, -0.118111f, 0.078176f,
|
|
0.194171f, 0.211328f, 0.368612f, 0.361213f, 0.130013f, 0.094650f,
|
|
0.227396f, -0.178058f, -0.114782f, -0.008093f, 0.231080f, -0.011843f,
|
|
-0.097917f, -0.325788f, 0.141879f, 0.119738f, -0.230427f, -0.117419f,
|
|
-0.114153f, 0.037903f, 0.116383f, 0.218773f, -0.101884f, 0.059466f,
|
|
0.119255f, 0.010874f, -0.031449f, 0.045996f, 0.119931f, 0.273760f,
|
|
0.311700f, 0.261794f, 0.194809f, 0.339829f, 0.239449f, 0.064140f,
|
|
0.077597f, 0.098996f, 0.143534f, 0.184602f, 0.037507f, 0.225494f,
|
|
0.096142f, -0.147370f, -0.207833f, -0.174742f, -0.086391f, -0.038942f,
|
|
0.159577f, -0.088492f, -0.000989f, 0.108154f, -0.025890f, -0.072713f,
|
|
0.025997f, -0.006803f, -0.086879f, -0.011290f, -0.269200f, -0.103450f,
|
|
-0.124910f, -0.116340f, 0.141459f, 0.208800f, 0.042268f, 0.265034f,
|
|
0.516474f, 0.217591f, -0.018843f, -0.313328f, -0.168363f, 0.047129f,
|
|
0.090480f, -0.109852f, -0.018761f, 0.210669f, 0.281269f, -0.043591f,
|
|
-0.034147f, -0.237772f, -0.134843f, -0.072481f, -0.103831f, 0.038355f,
|
|
0.308619f, 0.148023f, -0.045867f, -0.123950f, -0.210860f, -0.064973f,
|
|
-0.036308f, -0.046731f, -0.022099f, 0.095776f, 0.409423f, 0.060635f,
|
|
-0.065196f, 0.051828f, 0.027981f, -0.009609f, -0.137681f, -0.095011f,
|
|
-0.019045f, 0.177278f, 0.009759f, -0.092119f, -0.016958f, -0.133860f,
|
|
-0.118421f, -0.032039f, -0.006214f, -0.084541f, 0.063971f, -0.073642f,
|
|
0.165676f, 0.110443f, 0.044131f, 0.046568f, 0.053292f, -0.055466f,
|
|
0.015512f, 0.371947f, 0.232102f, -0.016923f, 0.103979f, -0.091758f,
|
|
0.005907f, 0.209100f, 0.157433f, 0.030518f, 0.250366f, 0.062322f,
|
|
0.036720f, 0.094676f, 0.017306f, -0.010328f, -0.079012f, 0.016781f,
|
|
-0.112435f, 0.061795f, 0.042543f, -0.126799f, -0.009975f, -0.056760f,
|
|
0.046424f, -0.194712f, -0.139399f, -0.037731f, 0.157989f, -0.016261f,
|
|
0.123345f, 0.230563f, 0.083300f, -0.016392f, 0.059567f, -0.016035f,
|
|
-0.064767f, 0.231945f, 0.156629f, 0.034602f, 0.145628f, 0.041315f,
|
|
0.034535f, 0.019967f, -0.089188f, -0.012091f, 0.307857f, 0.211405f,
|
|
-0.025091f, -0.148249f, -0.129384f, 0.063536f, -0.068603f, -0.067941f,
|
|
-0.035104f, 0.210832f, 0.063810f, 0.062764f, -0.089889f, -0.030554f,
|
|
0.014791f, -0.053362f, -0.037818f, -0.196640f, 0.008388f, -0.082654f,
|
|
0.143056f, 0.064221f, 0.069795f, 0.191040f, 0.097321f, -0.028679f,
|
|
0.075794f, 0.313154f, 0.086240f, 0.207643f, 0.017809f, 0.122867f,
|
|
0.224586f, 0.167403f, -0.023884f, 0.047434f, 0.344091f, 0.187745f,
|
|
0.136177f, 0.141738f, 0.063799f, 0.045233f, -0.077342f, -0.003525f,
|
|
-0.165041f, -0.025616f, -0.073745f, 0.164439f, 0.011200f, -0.145896f,
|
|
-0.027954f, -0.061987f, -0.039874f, -0.142775f, 0.151042f, -0.038238f,
|
|
0.053152f, 0.078615f, 0.086061f, 0.100593f, 0.128046f, -0.071006f,
|
|
-0.116558f, 0.208445f, 0.051086f, 0.076843f, 0.023191f, -0.084781f,
|
|
-0.011790f, 0.147807f, -0.048554f, -0.113932f, 0.283322f, 0.190934f,
|
|
0.092789f, 0.033018f, -0.142428f, -0.142480f, -0.099023f, -0.041020f,
|
|
-0.042760f, 0.203295f, -0.053475f, 0.042424f, 0.222839f, -0.019167f,
|
|
-0.133176f, -0.276216f, -0.031998f, 0.117290f, 0.177827f, -0.059973f,
|
|
-0.064744f, -0.117040f, -0.155482f, -0.099531f, 0.164121f, -0.026682f,
|
|
-0.093810f, 0.238993f, -0.006506f, 0.007830f, 0.065819f, -0.203643f,
|
|
-0.100925f, -0.053652f, -0.130770f, 0.026277f, 0.131796f, 0.032742f,
|
|
0.127186f, 0.116694f, -0.161122f, -0.279773f, -0.252515f, -0.002638f,
|
|
0.042812f, 0.096776f, -0.123280f, 0.064858f, -0.010455f, -0.219760f,
|
|
-0.239331f, -0.104363f, -0.058022f, -0.053584f, 0.025611f, 0.005129f,
|
|
-0.100418f, -0.045712f, -0.194418f, -0.126366f, -0.030530f, 0.051168f,
|
|
0.215959f, 0.172402f, -0.054700f, -0.185995f, -0.278360f, -0.193693f,
|
|
-0.040309f, 0.003735f, -0.007770f, 0.123556f, 0.190179f, -0.077315f,
|
|
0.117403f, 0.212942f, 0.012160f, 0.000113f, 0.027331f, 0.040202f,
|
|
0.033293f, 0.219438f, 0.184174f, 0.259349f, 0.311206f, 0.082547f,
|
|
-0.047875f, -0.078417f, 0.010746f, 0.082620f, 0.311931f, 0.307605f,
|
|
0.003863f, 0.021405f, -0.026388f, -0.019572f, 0.020582f, -0.059353f,
|
|
0.025199f, 0.261319f, 0.086316f, 0.143614f, 0.107780f, 0.003900f,
|
|
-0.188397f, -0.038563f, -0.106045f, -0.125154f, -0.010509f, 0.054021f,
|
|
0.242130f, 0.279152f, 0.215546f, 0.346995f, 0.440856f, 0.237452f,
|
|
0.234154f, 0.301646f, 0.168929f, -0.208358f, -0.126848f, 0.010260f,
|
|
0.121018f, -0.062975f, -0.052848f, 0.050341f, -0.061103f, -0.266482f,
|
|
0.107186f, 0.140221f, 0.280065f, 0.287889f, 0.373198f, 0.151596f,
|
|
0.013593f, 0.115616f, 0.014616f, -0.281710f, -0.237597f, -0.117305f,
|
|
-0.000034f, -0.136739f, -0.196275f, -0.095225f, -0.125310f, -0.250514f,
|
|
0.236804f, -0.071805f, -0.037421f, 0.048230f, 0.321596f, 0.063632f,
|
|
0.024039f, -0.029133f, 0.230983f, 0.160593f, -0.154355f, -0.013086f,
|
|
-0.079929f, 0.094692f, 0.160391f, 0.180239f, 0.053895f, 0.100759f,
|
|
0.288631f, 0.038191f, 0.181692f, 0.229682f, 0.440166f, 0.063401f,
|
|
0.006273f, 0.020865f, 0.338695f, 0.256244f, -0.043927f, 0.115617f,
|
|
0.003296f, 0.173965f, 0.021318f, -0.040936f, -0.118932f, 0.182380f,
|
|
0.235922f, -0.053233f, -0.015053f, -0.101057f, 0.095341f, 0.051111f,
|
|
0.161831f, 0.032614f, 0.159496f, 0.072375f, 0.025089f, 0.023748f,
|
|
0.029151f, 0.161284f, -0.117717f, -0.036191f, -0.176822f, -0.162006f,
|
|
0.226542f, -0.078329f, 0.043079f, -0.119172f, 0.054614f, -0.101365f,
|
|
-0.064541f, -0.115304f, 0.135170f, 0.298872f, 0.098060f, 0.089428f,
|
|
-0.007497f, 0.110391f, -0.028824f, 0.020835f, -0.036804f, 0.125411f,
|
|
0.192105f, -0.048931f, 0.003086f, -0.010681f, 0.074698f, -0.016263f,
|
|
0.096063f, 0.060267f, -0.007277f, 0.139139f, -0.080635f, 0.036628f,
|
|
0.086058f, 0.131979f, 0.085707f, 0.025301f, 0.226094f, 0.194759f,
|
|
0.042193f, -0.157846f, -0.068402f, -0.141450f, -0.112659f, -0.076305f,
|
|
-0.069085f, -0.114332f, -0.102005f, 0.132193f, -0.067042f, 0.106643f,
|
|
0.198964f, 0.171616f, 0.167237f, -0.033730f, -0.026755f, 0.083621f,
|
|
0.149459f, -0.002799f, -0.000318f, 0.011753f, 0.065889f, -0.089375f,
|
|
-0.049610f, 0.224579f, 0.216548f, -0.034908f, -0.017851f, -0.088144f,
|
|
0.007530f, 0.240268f, 0.073270f, 0.013263f, 0.175323f, 0.012082f,
|
|
0.093993f, 0.015282f, 0.105854f, 0.107990f, 0.077798f, -0.096166f,
|
|
-0.079607f, 0.177820f, 0.142392f, 0.033337f, -0.078100f, -0.081616f,
|
|
-0.046993f, 0.139459f, 0.020272f, -0.123161f, 0.175269f, 0.105217f,
|
|
0.057328f, 0.080909f, -0.012612f, -0.097081f, 0.082060f, -0.096716f,
|
|
-0.063921f, 0.201884f, 0.128166f, -0.035051f, -0.032227f, -0.068139f,
|
|
-0.115915f, 0.095080f, -0.086007f, -0.067543f, 0.030776f, 0.032712f,
|
|
0.088937f, 0.054336f, -0.039329f, -0.114022f, 0.171672f, -0.112321f,
|
|
-0.217646f, 0.065186f, 0.060223f, 0.192174f, 0.055580f, -0.131107f,
|
|
-0.144338f, 0.056730f, -0.034707f, -0.081616f, -0.135298f, -0.000614f,
|
|
0.087189f, 0.014614f, 0.067709f, 0.107689f, 0.225780f, 0.084361f,
|
|
-0.008544f, 0.051649f, -0.048369f, -0.037739f, -0.060710f, 0.002654f,
|
|
0.016935f, 0.085563f, -0.015961f, -0.019265f, 0.111788f, 0.062376f,
|
|
0.202019f, 0.047713f, 0.042261f, 0.069716f, 0.242913f, 0.021052f,
|
|
-0.072812f, -0.155920f, -0.026436f, 0.035621f, -0.079300f, -0.028787f,
|
|
-0.048329f, 0.084718f, -0.060565f, -0.083750f, -0.164075f, -0.040742f,
|
|
-0.086219f, 0.015271f, -0.005204f, -0.016038f, 0.045816f, -0.050433f,
|
|
-0.077652f, 0.117109f, 0.009611f, -0.009045f, -0.008634f, -0.055373f,
|
|
-0.085968f, 0.028527f, -0.054736f, -0.168089f, 0.175839f, 0.071205f,
|
|
-0.023603f, 0.037907f, -0.004561f, -0.022634f, 0.123831f, 0.094469f,
|
|
-0.072920f, -0.133642f, -0.014032f, -0.142754f, -0.026999f, -0.199409f,
|
|
0.013268f, 0.226989f, 0.048650f, -0.170988f, -0.050141f, 0.007880f,
|
|
0.061880f, 0.019078f, -0.043578f, -0.038139f, 0.134814f, 0.054097f,
|
|
-0.081670f, 0.176838f, 0.047920f, -0.038176f, 0.050406f, -0.107181f,
|
|
-0.036279f, 0.027060f, 0.081594f, -0.002820f, 0.090507f, -0.033338f,
|
|
-0.059571f, 0.013404f, -0.099860f, 0.073371f, 0.342805f, 0.098305f,
|
|
-0.150910f, -0.020822f, -0.056960f, 0.046262f, -0.043413f, -0.149405f,
|
|
-0.129105f, -0.010899f, -0.014229f, -0.179949f, -0.113044f, -0.049468f,
|
|
-0.065513f, 0.090269f, -0.011919f, 0.087846f, 0.095796f, 0.146127f,
|
|
0.101599f, 0.078066f, -0.084348f, -0.100002f, -0.020134f, -0.050169f,
|
|
0.062122f, 0.014640f, 0.019143f, 0.036543f, 0.180924f, -0.013976f,
|
|
-0.066768f, -0.001090f, -0.070419f, -0.004839f, -0.001504f, 0.034483f,
|
|
-0.044954f, -0.050336f, -0.088638f, -0.174782f, -0.116082f, -0.205507f,
|
|
0.015587f, -0.042839f, -0.096879f, -0.144097f, -0.050268f, -0.196796f,
|
|
0.109639f, 0.271411f, 0.173732f, 0.108070f, 0.156437f, 0.124255f,
|
|
0.097242f, 0.238693f, 0.083941f, 0.109105f, 0.223940f, 0.267188f,
|
|
0.027385f, 0.025819f, 0.125070f, 0.093738f, 0.040353f, 0.038645f,
|
|
-0.012730f, 0.144063f, 0.052931f, -0.009138f, 0.084193f, 0.160272f,
|
|
-0.041366f, 0.011951f, -0.121446f, -0.106713f, -0.047566f, 0.047984f,
|
|
-0.255224f, -0.076116f, 0.098685f, -0.150845f, -0.171513f, -0.156590f,
|
|
0.058331f, 0.187493f, 0.413018f, 0.554265f, 0.372242f, 0.237943f,
|
|
0.124571f, 0.110829f, 0.010322f, -0.174477f, -0.067627f, -0.001979f,
|
|
0.142913f, 0.040597f, 0.019907f, 0.025963f, -0.043585f, -0.120732f,
|
|
0.099937f, 0.091059f, 0.247307f, 0.204226f, -0.042753f, -0.068580f,
|
|
-0.119002f, 0.026722f, 0.034853f, -0.060934f, -0.025054f, -0.093026f,
|
|
-0.035372f, -0.233209f, -0.049869f, -0.039151f, -0.022279f, -0.065380f,
|
|
-9.063785f
|
|
};
|
|
return std::vector<float>(detector, detector + sizeof(detector) / sizeof(detector[0]));
|
|
}
|
|
|
|
|
|
|
|
|
|
std::vector<float> cv::ocl::HOGDescriptor::getPeopleDetector64x128()
|
|
{
|
|
static const float detector[] =
|
|
{
|
|
0.05359386f, -0.14721455f, -0.05532170f, 0.05077307f,
|
|
0.11547081f, -0.04268804f, 0.04635834f, -0.05468199f, 0.08232084f,
|
|
0.10424068f, -0.02294518f, 0.01108519f, 0.01378693f, 0.11193510f,
|
|
0.01268418f, 0.08528346f, -0.06309239f, 0.13054633f, 0.08100729f,
|
|
-0.05209739f, -0.04315529f, 0.09341384f, 0.11035026f, -0.07596218f,
|
|
-0.05517511f, -0.04465296f, 0.02947334f, 0.04555536f,
|
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|
|
0.08670278f, 0.06828108f, 0.10238872f, 0.05405957f, 0.06548470f,
|
|
-0.03763957f, 0.01366090f, 0.07069602f, 0.05363748f, 0.04798120f,
|
|
0.11706422f, 0.05466456f, -0.01869259f, 0.06344382f, 0.03106543f,
|
|
0.08432506f, -0.02061096f, 0.03821088f, -6.92190882e-003f,
|
|
6.40467042e-003f, -0.01271779f, 6.89014705e-005f, 0.04541415f,
|
|
-0.01899539f, -0.05020239f, 0.03000903f, 0.01090422f, 4.52452758e-003f,
|
|
0.02573632f, -0.02388454f, -0.04200457f, 1.72783900e-003f,
|
|
-0.05978370f, -0.02720562f, 0.06573715f, 0.01154317f, 0.01265615f,
|
|
0.07375994f, -9.19828378e-003f, -0.04914120f, 0.02124831f, 0.06455322f,
|
|
0.04372910f, -0.03310043f, 0.03605788f, -6.78055827e-003f,
|
|
9.36202332e-003f, 0.01747596f, -0.06406314f, -0.06812935f, 0.08080816f,
|
|
-0.02778088f, 0.02735260f, 0.06393493f, 0.06652229f, 0.05676993f,
|
|
0.08640018f, -7.59188086e-003f, -0.02012847f, -0.04741159f,
|
|
-0.01657069f, -0.01624399f, 0.05547778f, -2.33309763e-003f,
|
|
0.01120033f, 0.06141156f, -0.06285004f, -0.08732341f, -0.09313398f,
|
|
-0.04267832f, 5.57443965e-003f, 0.04809862f, 0.01773641f,
|
|
5.37361018e-003f, 0.14842421f, -0.06298012f, -0.02935147f, 0.11443478f,
|
|
-0.05034208f, 5.65494271e-003f, 0.02076526f, -0.04577984f,
|
|
-0.04735741f, 0.02961071f, -0.09307127f, -0.04417921f, -0.04990027f,
|
|
-0.03940028f, 0.01306016f, 0.06267900f, 0.03758737f, 0.08460117f,
|
|
0.13858789f, 0.04862388f, -0.06319809f, -0.05655516f, 0.01885816f,
|
|
-0.03285607f, 0.03371567f, -0.07040928f, -0.04514049f, 0.01392166f,
|
|
0.08184422f, -0.07230316f, 0.02386871f, 0.02184591f, 0.02605764f,
|
|
-0.01033954f, 9.29878280e-003f, 7.67351175e-003f, 0.15189242f,
|
|
0.02069071f, -0.09738296f, -0.08894105f, -0.07768748f, 0.02332268f,
|
|
-0.01778995f, -0.03258888f, -0.08180822f, -0.08492987f, 0.02290156f,
|
|
-0.11368170f, -0.03554465f, -0.04533844f, -0.02861580f, 0.06782424f,
|
|
0.01113123f, 0.02453644f, 0.12721945f, 0.08084814f, -0.03607795f,
|
|
0.01109122f, 0.04803548f, -0.03489929f, 0.03399536f, -0.05682014f,
|
|
8.59533902e-003f, -4.27904585e-003f, 0.03230887f, -0.01300198f,
|
|
-0.01038137f, -0.07930113f, 8.33097473e-003f, 0.02296994f,
|
|
-0.01306500f, -0.01881626f, 0.04413369f, 0.05729880f, -0.03761553f,
|
|
0.01942326f, 1.64540811e-003f, -0.03811319f, 0.04190650f, -0.14978096f,
|
|
-0.04514487f, 0.01209545f, -5.46460645e-003f, -0.01647195f,
|
|
7.63064111e-003f, -0.07494587f, 0.08415288f, 0.10020141f, -0.01228561f,
|
|
0.06553826f, 0.04554005f, 0.07890417f, 0.03041138f, 0.01752007f,
|
|
0.09208256f, -3.74419295e-004f, 0.10549527f, 0.04686913f, 0.01894833f,
|
|
-0.02651412f, -4.34682379e-003f, 5.44942822e-003f, 0.01444484f,
|
|
0.05882156f, -0.03336544f, 0.04603891f, -0.10432546f, 0.01923928f,
|
|
0.01842845f, -0.01712168f, -0.02222766f, 0.04693324f, -0.06202956f,
|
|
-0.01422159f, 0.08732220f, -0.07706107f, 0.02661049f, -0.04300238f,
|
|
-0.03092422f, -0.03552184f, -0.01886088f, -0.04979934f, 0.03906401f,
|
|
0.04608644f, 0.04966111f, 0.04275464f, -0.04621769f, -0.02653212f,
|
|
8.57011229e-003f, 0.03839684f, 0.05818764f, 0.03880796f,
|
|
-2.76100676e-004f, 0.03076511f, -0.03266929f, -0.05374557f,
|
|
0.04986527f, -9.45429131e-003f, 0.03582499f, -2.64564669e-003f,
|
|
-1.07461517e-003f, 0.02962313f, -0.01483363f, 0.03060869f, 0.02448327f,
|
|
0.01845641f, 0.03282966f, -0.03534438f, -0.01084059f, -0.01119136f,
|
|
-1.85360224e-003f, -5.94652840e-004f, -0.04451817f, 2.98327743e-003f,
|
|
0.06272484f, -0.02152076f, -3.05971340e-003f, -0.05070828f,
|
|
0.01531762f, 0.01282815f, 0.05167150f, 9.46266949e-003f,
|
|
-3.34558333e-003f, 0.11442288f, -0.03906701f, -2.67325155e-003f,
|
|
0.03069184f, -0.01134165f, 0.02949462f, 0.02879886f, 0.03855566f,
|
|
-0.03450781f, 0.09142872f, -0.02156654f, 0.06075062f, -0.06220816f,
|
|
0.01944680f, 6.68372354e-003f, -0.06656796f, 8.70784000e-003f,
|
|
0.03456013f, 0.02434320f, -0.13236357f, -0.04177035f, -0.02069627f,
|
|
0.01068112f, 0.01505432f, -0.07517391f, -3.83571628e-003f,
|
|
-0.06298508f, -0.02881260f, -0.13101046f, -0.07221562f,
|
|
-5.79945277e-003f, -8.57300125e-003f, 0.03782469f, 0.02762164f,
|
|
0.04942456f, -0.02936396f, 0.09597211f, 0.01921411f, 0.06101191f,
|
|
-0.04787507f, -0.01379578f, -7.40224449e-003f, -0.02220136f,
|
|
-0.01313756f, 7.77558051e-003f, 0.12296968f, 0.02939998f, 0.03594062f,
|
|
-0.07788624f, -0.01133144f, 3.99316690e-004f, -0.06090347f,
|
|
-0.01122066f, -4.68682544e-003f, 0.07633100f, -0.06748922f,
|
|
-0.05640298f, -0.05265681f, -0.01139122f, -0.01624347f, -0.04715714f,
|
|
-0.01099092f, 0.01048561f, 3.28499987e-003f, -0.05810167f,
|
|
-0.07699911f, -0.03330683f, 0.04185145f, 0.03478536f, 0.02275165f,
|
|
0.02304766f, 6.66040834e-003f, 0.10968148f, -5.93013782e-003f,
|
|
-0.04858336f, -0.04203213f, -0.09316786f, -6.13074889e-003f,
|
|
-0.02544625f, 0.01366201f, 9.18555818e-003f, -0.01846578f,
|
|
-0.05622401f, -0.03989377f, -0.07810296f, 6.91275718e-003f,
|
|
0.05957597f, -0.03901334f, 0.01572002f, -0.01193903f,
|
|
-6.89400872e-003f, -0.03093356f, -0.04136098f, -0.01562869f,
|
|
-0.04604580f, 0.02865234f, -0.08678447f, -0.03232484f, -0.05364593f,
|
|
-0.01445016f, -0.07003860f, -0.08669746f, -0.04520775f, 0.04274122f,
|
|
0.03117515f, 0.08175703f, 0.01081109f, 0.06379741f, 0.06199206f,
|
|
0.02865988f, 0.02360346f, 0.06725410f, -0.03248780f, -9.37702879e-003f,
|
|
0.08265898f, -0.02245839f, 0.05125763f, -0.01862395f, 0.01973453f,
|
|
-0.01994494f, -0.10770868f, 0.03180375f, 3.23935156e-003f,
|
|
-0.02142080f, -0.04256190f, 0.04760900f, 0.04282863f, 0.05635953f,
|
|
-0.01870849f, 0.05540622f, -0.03042666f, 0.01455277f, -0.06630179f,
|
|
-0.05843807f, -0.03739681f, -0.09739155f, -0.03220233f, -0.05620182f,
|
|
-0.10381401f, 0.07400211f, 4.20676917e-003f, 0.03258535f,
|
|
2.14308966e-003f, 0.05121966f, -0.01274337f, 0.02384761f, 0.06335578f,
|
|
-0.07905591f, 0.08375625f, -0.07898903f, -0.06508528f, -0.02498444f,
|
|
0.06535810f, 0.03970535f, 0.04895468f, -0.01169566f, -0.03980601f,
|
|
0.05682293f, 0.05925463f, -0.01165808f, -0.07936699f, -0.04208954f,
|
|
0.01333987f, 0.09051196f, 0.10098671f, -0.03974256f, 0.01238771f,
|
|
-0.07501741f, -0.03655440f, -0.04301528f, 0.09216860f,
|
|
4.63579083e-004f, 0.02851115f, 0.02142735f, 1.28244064e-004f,
|
|
0.02879687f, -0.08554889f, -0.04838862f, 0.08135369f, -0.05756533f,
|
|
0.01413900f, 0.03451880f, -0.06619488f, -0.03053130f, 0.02961676f,
|
|
-0.07384635f, 0.01135692f, 0.05283910f, -0.07778034f, -0.02107482f,
|
|
-0.05511716f, -0.13473752f, 0.03030157f, 0.06722020f, -0.06218817f,
|
|
-0.05826827f, 0.06254654f, 0.02895772f, -0.01664000f, -0.03620280f,
|
|
-0.01612278f, -1.46097376e-003f, 0.14013411f, -8.96181818e-003f,
|
|
-0.03250246f, 3.38630192e-003f, 2.64779478e-003f, 0.03359732f,
|
|
-0.02411991f, -0.04229729f, 0.10666174f, -6.66579151f
|
|
};
|
|
return std::vector<float>(detector, detector + sizeof(detector) / sizeof(detector[0]));
|
|
}
|
|
|
|
/* Returns the nearest upper power of two, works only for
|
|
the typical GPU thread count (pert block) values */
|
|
static int power_2up(unsigned int n)
|
|
{
|
|
if (n < 1) return 1;
|
|
else if (n < 2) return 2;
|
|
else if (n < 4) return 4;
|
|
else if (n < 8) return 8;
|
|
else if (n < 16) return 16;
|
|
else if (n < 32) return 32;
|
|
else if (n < 64) return 64;
|
|
else if (n < 128) return 128;
|
|
else if (n < 256) return 256;
|
|
else if (n < 512) return 512;
|
|
else if (n < 1024) return 1024;
|
|
return -1; // Input is too big
|
|
}
|
|
|
|
void cv::ocl::device::hog::set_up_constants(int nbins,
|
|
int block_stride_x, int block_stride_y,
|
|
int nblocks_win_x, int nblocks_win_y)
|
|
{
|
|
cnbins = nbins;
|
|
cblock_stride_x = block_stride_x;
|
|
cblock_stride_y = block_stride_y;
|
|
cnblocks_win_x = nblocks_win_x;
|
|
cnblocks_win_y = nblocks_win_y;
|
|
|
|
int block_hist_size = nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y;
|
|
cblock_hist_size = block_hist_size;
|
|
|
|
int descr_width = nblocks_win_x * block_hist_size;
|
|
cdescr_width = descr_width;
|
|
cdescr_height = nblocks_win_y;
|
|
|
|
int descr_size = descr_width * nblocks_win_y;
|
|
cdescr_size = descr_size;
|
|
}
|
|
|
|
void cv::ocl::device::hog::compute_hists(int nbins,
|
|
int block_stride_x, int block_stride_y,
|
|
int height, int width,
|
|
const cv::ocl::oclMat &grad,
|
|
const cv::ocl::oclMat &qangle,
|
|
const cv::ocl::oclMat &gauss_w_lut,
|
|
cv::ocl::oclMat &block_hists)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
String kernelName = "compute_hists_lut_kernel";
|
|
|
|
int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x)
|
|
/ block_stride_x;
|
|
int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y)
|
|
/ block_stride_y;
|
|
int blocks_total = img_block_width * img_block_height;
|
|
|
|
int grad_quadstep = grad.step >> 2;
|
|
int qangle_step = qangle.step;
|
|
|
|
int blocks_in_group = 4;
|
|
size_t localThreads[3] = { blocks_in_group * 24, 2, 1 };
|
|
size_t globalThreads[3] = {
|
|
divUp(img_block_width * img_block_height, blocks_in_group) * localThreads[0], 2, 1 };
|
|
|
|
int hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y * 12) * sizeof(float);
|
|
int final_hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y) * sizeof(float);
|
|
|
|
int smem = (hists_size + final_hists_size) * blocks_in_group;
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cblock_stride_x));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cblock_stride_y));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cnbins));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cblock_hist_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_block_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&blocks_in_group));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&blocks_total));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&grad_quadstep));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&qangle_step));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&grad.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&qangle.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&gauss_w_lut.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&block_hists.data));
|
|
args.push_back( std::make_pair( smem, (void *)NULL));
|
|
|
|
if(hog_device_cpu)
|
|
{
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1, "-D CPU");
|
|
}
|
|
else
|
|
{
|
|
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
|
|
size_t wave_size = queryWaveFrontSize(kernel);
|
|
char opt[32] = {0};
|
|
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1, opt);
|
|
}
|
|
}
|
|
|
|
void cv::ocl::device::hog::normalize_hists(int nbins,
|
|
int block_stride_x, int block_stride_y,
|
|
int height, int width,
|
|
cv::ocl::oclMat &block_hists,
|
|
float threshold)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
String kernelName;
|
|
|
|
int block_hist_size = nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y;
|
|
int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x)
|
|
/ block_stride_x;
|
|
int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y)
|
|
/ block_stride_y;
|
|
int nthreads;
|
|
size_t globalThreads[3] = { 1, 1, 1 };
|
|
size_t localThreads[3] = { 1, 1, 1 };
|
|
|
|
if ( nbins == 9 )
|
|
{
|
|
/* optimized for the case of 9 bins */
|
|
kernelName = "normalize_hists_36_kernel";
|
|
int blocks_in_group = NTHREADS / block_hist_size;
|
|
nthreads = blocks_in_group * block_hist_size;
|
|
int num_groups = divUp( img_block_width * img_block_height, blocks_in_group);
|
|
globalThreads[0] = nthreads * num_groups;
|
|
localThreads[0] = nthreads;
|
|
}
|
|
else
|
|
{
|
|
kernelName = "normalize_hists_kernel";
|
|
nthreads = power_2up(block_hist_size);
|
|
globalThreads[0] = img_block_width * nthreads;
|
|
globalThreads[1] = img_block_height;
|
|
localThreads[0] = nthreads;
|
|
|
|
if ((nthreads < 32) || (nthreads > 512) )
|
|
cv::error(Error::StsBadArg, "normalize_hists: histogram's size is too small or too big",
|
|
"normalize_hists", __FILE__, __LINE__);
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&nthreads));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&block_hist_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_block_width));
|
|
}
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&block_hists.data));
|
|
args.push_back( std::make_pair( sizeof(cl_float), (void *)&threshold));
|
|
args.push_back( std::make_pair( nthreads * sizeof(float), (void *)NULL));
|
|
|
|
if(hog_device_cpu)
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1, "-D CPU");
|
|
else
|
|
{
|
|
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
|
|
size_t wave_size = queryWaveFrontSize(kernel);
|
|
char opt[32] = {0};
|
|
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1, opt);
|
|
}
|
|
}
|
|
|
|
void cv::ocl::device::hog::classify_hists(int win_height, int win_width,
|
|
int block_stride_y, int block_stride_x,
|
|
int win_stride_y, int win_stride_x,
|
|
int height, int width,
|
|
const cv::ocl::oclMat &block_hists,
|
|
const cv::ocl::oclMat &coefs,
|
|
float free_coef, float threshold,
|
|
cv::ocl::oclMat &labels)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
|
|
int nthreads;
|
|
String kernelName;
|
|
switch (cdescr_width)
|
|
{
|
|
case 180:
|
|
nthreads = 180;
|
|
kernelName = "classify_hists_180_kernel";
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_height));
|
|
break;
|
|
case 252:
|
|
nthreads = 256;
|
|
kernelName = "classify_hists_252_kernel";
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_height));
|
|
break;
|
|
default:
|
|
nthreads = 256;
|
|
kernelName = "classify_hists_kernel";
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_width));
|
|
}
|
|
|
|
int win_block_stride_x = win_stride_x / block_stride_x;
|
|
int win_block_stride_y = win_stride_y / block_stride_y;
|
|
int img_win_width = (width - win_width + win_stride_x) / win_stride_x;
|
|
int img_win_height = (height - win_height + win_stride_y) / win_stride_y;
|
|
int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) /
|
|
block_stride_x;
|
|
|
|
size_t globalThreads[3] = { img_win_width * nthreads, img_win_height, 1 };
|
|
size_t localThreads[3] = { nthreads, 1, 1 };
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cblock_hist_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_win_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_block_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&win_block_stride_x));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&win_block_stride_y));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&block_hists.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&coefs.data));
|
|
args.push_back( std::make_pair( sizeof(cl_float), (void *)&free_coef));
|
|
args.push_back( std::make_pair( sizeof(cl_float), (void *)&threshold));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&labels.data));
|
|
|
|
if(hog_device_cpu)
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1, "-D CPU");
|
|
else
|
|
{
|
|
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
|
|
size_t wave_size = queryWaveFrontSize(kernel);
|
|
char opt[32] = {0};
|
|
sprintf(opt, "-D WAVE_SIZE=%d", (int)wave_size);
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1, opt);
|
|
}
|
|
}
|
|
|
|
void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width,
|
|
int block_stride_y, int block_stride_x,
|
|
int win_stride_y, int win_stride_x,
|
|
int height, int width,
|
|
const cv::ocl::oclMat &block_hists,
|
|
cv::ocl::oclMat &descriptors)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
String kernelName = "extract_descrs_by_rows_kernel";
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
|
|
int win_block_stride_x = win_stride_x / block_stride_x;
|
|
int win_block_stride_y = win_stride_y / block_stride_y;
|
|
int img_win_width = (width - win_width + win_stride_x) / win_stride_x;
|
|
int img_win_height = (height - win_height + win_stride_y) / win_stride_y;
|
|
int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) /
|
|
block_stride_x;
|
|
int descriptors_quadstep = descriptors.step >> 2;
|
|
|
|
size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 };
|
|
size_t localThreads[3] = { NTHREADS, 1, 1 };
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cblock_hist_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&descriptors_quadstep));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_block_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&win_block_stride_x));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&win_block_stride_y));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&block_hists.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&descriptors.data));
|
|
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1);
|
|
}
|
|
|
|
void cv::ocl::device::hog::extract_descrs_by_cols(int win_height, int win_width,
|
|
int block_stride_y, int block_stride_x,
|
|
int win_stride_y, int win_stride_x,
|
|
int height, int width,
|
|
const cv::ocl::oclMat &block_hists,
|
|
cv::ocl::oclMat &descriptors)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
String kernelName = "extract_descrs_by_cols_kernel";
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
|
|
int win_block_stride_x = win_stride_x / block_stride_x;
|
|
int win_block_stride_y = win_stride_y / block_stride_y;
|
|
int img_win_width = (width - win_width + win_stride_x) / win_stride_x;
|
|
int img_win_height = (height - win_height + win_stride_y) / win_stride_y;
|
|
int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) /
|
|
block_stride_x;
|
|
int descriptors_quadstep = descriptors.step >> 2;
|
|
|
|
size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 };
|
|
size_t localThreads[3] = { NTHREADS, 1, 1 };
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cblock_hist_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&descriptors_quadstep));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cdescr_size));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cnblocks_win_x));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cnblocks_win_y));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_block_width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&win_block_stride_x));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&win_block_stride_y));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&block_hists.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&descriptors.data));
|
|
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1);
|
|
}
|
|
|
|
void cv::ocl::device::hog::compute_gradients_8UC1(int height, int width,
|
|
const cv::ocl::oclMat &img,
|
|
float angle_scale,
|
|
cv::ocl::oclMat &grad,
|
|
cv::ocl::oclMat &qangle,
|
|
bool correct_gamma)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
String kernelName = "compute_gradients_8UC1_kernel";
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
|
|
size_t localThreads[3] = { NTHREADS, 1, 1 };
|
|
size_t globalThreads[3] = { width, height, 1 };
|
|
char correctGamma = (correct_gamma) ? 1 : 0;
|
|
int img_step = img.step;
|
|
int grad_quadstep = grad.step >> 3;
|
|
int qangle_step = qangle.step >> 1;
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&height));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_step));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&grad_quadstep));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&qangle_step));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&img.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&grad.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&qangle.data));
|
|
args.push_back( std::make_pair( sizeof(cl_float), (void *)&angle_scale));
|
|
args.push_back( std::make_pair( sizeof(cl_char), (void *)&correctGamma));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cnbins));
|
|
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1);
|
|
}
|
|
|
|
void cv::ocl::device::hog::compute_gradients_8UC4(int height, int width,
|
|
const cv::ocl::oclMat &img,
|
|
float angle_scale,
|
|
cv::ocl::oclMat &grad,
|
|
cv::ocl::oclMat &qangle,
|
|
bool correct_gamma)
|
|
{
|
|
Context *clCxt = Context::getContext();
|
|
String kernelName = "compute_gradients_8UC4_kernel";
|
|
std::vector< std::pair<size_t, const void *> > args;
|
|
|
|
size_t localThreads[3] = { NTHREADS, 1, 1 };
|
|
size_t globalThreads[3] = { width, height, 1 };
|
|
|
|
char correctGamma = (correct_gamma) ? 1 : 0;
|
|
int img_step = img.step >> 2;
|
|
int grad_quadstep = grad.step >> 3;
|
|
int qangle_step = qangle.step >> 1;
|
|
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&height));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&width));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&img_step));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&grad_quadstep));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&qangle_step));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&img.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&grad.data));
|
|
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&qangle.data));
|
|
args.push_back( std::make_pair( sizeof(cl_float), (void *)&angle_scale));
|
|
args.push_back( std::make_pair( sizeof(cl_char), (void *)&correctGamma));
|
|
args.push_back( std::make_pair( sizeof(cl_int), (void *)&cnbins));
|
|
|
|
openCLExecuteKernel2(clCxt, &objdetect_hog, kernelName, globalThreads,
|
|
localThreads, args, -1, -1);
|
|
}
|