1 /*M///////////////////////////////////////////////////////////////////////////////////////
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3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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5 // By downloading, copying, installing or using the software you agree to this license.
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6 // If you do not agree to this license, do not download, install,
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7 // copy or use the software.
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10 // License Agreement
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11 // For Open Source Computer Vision Library
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13 // Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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14 // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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15 // Third party copyrights are property of their respective owners.
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17 // Redistribution and use in source and binary forms, with or without modification,
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18 // are permitted provided that the following conditions are met:
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20 // * Redistribution's of source code must retain the above copyright notice,
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21 // this list of conditions and the following disclaimer.
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23 // * Redistribution's in binary form must reproduce the above copyright notice,
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24 // this list of conditions and the following disclaimer in the documentation
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25 // and/or other GpuMaterials provided with the distribution.
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27 // * The name of the copyright holders may not be used to endorse or promote products
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28 // derived from this software without specific prior written permission.
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30 // This software is provided by the copyright holders and contributors "as is" and
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31 // any express or bpied warranties, including, but not limited to, the bpied
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32 // warranties of merchantability and fitness for a particular purpose are disclaimed.
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33 // In no event shall the Intel Corporation or contributors be liable for any direct,
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34 // indirect, incidental, special, exemplary, or consequential damages
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35 // (including, but not limited to, procurement of substitute goods or services;
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36 // loss of use, data, or profits; or business interruption) however caused
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37 // and on any theory of liability, whether in contract, strict liability,
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38 // or tort (including negligence or otherwise) arising in any way out of
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39 // the use of this software, even if advised of the possibility of such damage.
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43 #include "precomp.hpp"
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45 #if !defined (HAVE_CUDA)
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47 cv::gpu::HOGDescriptor::HOGDescriptor(Size, Size, Size, Size, int, double, double, bool, int) { throw_nogpu(); }
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48 size_t cv::gpu::HOGDescriptor::getDescriptorSize() const { throw_nogpu(); return 0; }
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49 size_t cv::gpu::HOGDescriptor::getBlockHistogramSize() const { throw_nogpu(); return 0; }
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50 double cv::gpu::HOGDescriptor::getWinSigma() const { throw_nogpu(); return 0; }
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51 bool cv::gpu::HOGDescriptor::checkDetectorSize() const { throw_nogpu(); return false; }
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52 void cv::gpu::HOGDescriptor::setSVMDetector(const vector<float>&) { throw_nogpu(); }
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53 void cv::gpu::HOGDescriptor::detect(const GpuMat&, vector<Point>&, double, Size, Size) { throw_nogpu(); }
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54 void cv::gpu::HOGDescriptor::detectMultiScale(const GpuMat&, vector<Rect>&, double, Size, Size, double, int) { throw_nogpu(); }
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55 void cv::gpu::HOGDescriptor::computeBlockHistograms(const GpuMat&) { throw_nogpu(); }
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56 void cv::gpu::HOGDescriptor::getDescriptors(const GpuMat&, Size, GpuMat&, int) { throw_nogpu(); }
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57 std::vector<float> cv::gpu::HOGDescriptor::getDefaultPeopleDetector() { throw_nogpu(); return std::vector<float>(); }
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58 std::vector<float> cv::gpu::HOGDescriptor::getPeopleDetector48x96() { throw_nogpu(); return std::vector<float>(); }
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59 std::vector<float> cv::gpu::HOGDescriptor::getPeopleDetector64x128() { throw_nogpu(); return std::vector<float>(); }
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63 namespace cv { namespace gpu { namespace device
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67 void set_up_constants(int nbins, int block_stride_x, int block_stride_y,
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68 int nblocks_win_x, int nblocks_win_y);
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70 void compute_hists(int nbins, int block_stride_x, int blovck_stride_y,
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71 int height, int width, const cv::gpu::DevMem2Df& grad,
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72 const cv::gpu::DevMem2Db& qangle, float sigma, float* block_hists);
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74 void normalize_hists(int nbins, int block_stride_x, int block_stride_y,
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75 int height, int width, float* block_hists, float threshold);
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77 void classify_hists(int win_height, int win_width, int block_stride_y,
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78 int block_stride_x, int win_stride_y, int win_stride_x, int height,
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79 int width, float* block_hists, float* coefs, float free_coef,
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80 float threshold, unsigned char* labels);
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82 void extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, int block_stride_x,
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83 int win_stride_y, int win_stride_x, int height, int width, float* block_hists,
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84 cv::gpu::DevMem2Df descriptors);
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85 void extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, int block_stride_x,
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86 int win_stride_y, int win_stride_x, int height, int width, float* block_hists,
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87 cv::gpu::DevMem2Df descriptors);
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89 void compute_gradients_8UC1(int nbins, int height, int width, const cv::gpu::DevMem2Db& img,
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90 float angle_scale, cv::gpu::DevMem2Df grad, cv::gpu::DevMem2Db qangle, bool correct_gamma);
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91 void compute_gradients_8UC4(int nbins, int height, int width, const cv::gpu::DevMem2Db& img,
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92 float angle_scale, cv::gpu::DevMem2Df grad, cv::gpu::DevMem2Db qangle, bool correct_gamma);
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94 void resize_8UC1(const cv::gpu::DevMem2Db& src, cv::gpu::DevMem2Db dst);
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95 void resize_8UC4(const cv::gpu::DevMem2Db& src, cv::gpu::DevMem2Db dst);
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99 using namespace ::cv::gpu::device;
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101 cv::gpu::HOGDescriptor::HOGDescriptor(Size win_size_, Size block_size_, Size block_stride_, Size cell_size_,
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102 int nbins_, double win_sigma_, double threshold_L2hys_, bool gamma_correction_, int nlevels_)
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103 : win_size(win_size_),
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104 block_size(block_size_),
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105 block_stride(block_stride_),
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106 cell_size(cell_size_),
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108 win_sigma(win_sigma_),
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109 threshold_L2hys(threshold_L2hys_),
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110 gamma_correction(gamma_correction_),
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113 CV_Assert((win_size.width - block_size.width ) % block_stride.width == 0 &&
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114 (win_size.height - block_size.height) % block_stride.height == 0);
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116 CV_Assert(block_size.width % cell_size.width == 0 && block_size.height % cell_size.height == 0);
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118 CV_Assert(block_stride == cell_size);
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120 CV_Assert(cell_size == Size(8, 8));
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122 Size cells_per_block = Size(block_size.width / cell_size.width, block_size.height / cell_size.height);
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123 CV_Assert(cells_per_block == Size(2, 2));
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125 cv::Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride);
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126 hog::set_up_constants(nbins, block_stride.width, block_stride.height, blocks_per_win.width, blocks_per_win.height);
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129 size_t cv::gpu::HOGDescriptor::getDescriptorSize() const
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131 return numPartsWithin(win_size, block_size, block_stride).area() * getBlockHistogramSize();
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134 size_t cv::gpu::HOGDescriptor::getBlockHistogramSize() const
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136 Size cells_per_block = Size(block_size.width / cell_size.width, block_size.height / cell_size.height);
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137 return (size_t)(nbins * cells_per_block.area());
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140 double cv::gpu::HOGDescriptor::getWinSigma() const
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142 return win_sigma >= 0 ? win_sigma : (block_size.width + block_size.height) / 8.0;
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145 bool cv::gpu::HOGDescriptor::checkDetectorSize() const
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147 size_t detector_size = detector.rows * detector.cols;
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148 size_t descriptor_size = getDescriptorSize();
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149 return detector_size == 0 || detector_size == descriptor_size || detector_size == descriptor_size + 1;
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152 void cv::gpu::HOGDescriptor::setSVMDetector(const vector<float>& _detector)
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154 std::vector<float> detector_reordered(_detector.size());
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156 size_t block_hist_size = getBlockHistogramSize();
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157 cv::Size blocks_per_img = numPartsWithin(win_size, block_size, block_stride);
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159 for (int i = 0; i < blocks_per_img.height; ++i)
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160 for (int j = 0; j < blocks_per_img.width; ++j)
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162 const float* src = &_detector[0] + (j * blocks_per_img.height + i) * block_hist_size;
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163 float* dst = &detector_reordered[0] + (i * blocks_per_img.width + j) * block_hist_size;
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164 for (size_t k = 0; k < block_hist_size; ++k)
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168 this->detector.upload(Mat(detector_reordered).reshape(1, 1));
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170 size_t descriptor_size = getDescriptorSize();
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171 free_coef = _detector.size() > descriptor_size ? _detector[descriptor_size] : 0;
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173 CV_Assert(checkDetectorSize());
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176 cv::gpu::GpuMat cv::gpu::HOGDescriptor::getBuffer(const Size& sz, int type, GpuMat& buf)
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178 if (buf.empty() || buf.type() != type)
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179 buf.create(sz, type);
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181 if (buf.cols < sz.width || buf.rows < sz.height)
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182 buf.create(std::max(buf.rows, sz.height), std::max(buf.cols, sz.width), type);
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184 return buf(Rect(Point(0,0), sz));
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187 cv::gpu::GpuMat cv::gpu::HOGDescriptor::getBuffer(int rows, int cols, int type, GpuMat& buf)
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189 return getBuffer(Size(cols, rows), type, buf);
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193 void cv::gpu::HOGDescriptor::computeGradient(const GpuMat& img, GpuMat& _grad, GpuMat& _qangle)
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195 CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
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197 // grad.create(img.size(), CV_32FC2);
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198 _grad = getBuffer(img.size(), CV_32FC2, grad_buf);
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200 // qangle.create(img.size(), CV_8UC2);
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201 _qangle = getBuffer(img.size(), CV_8UC2, qangle_buf);
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203 float angleScale = (float)(nbins / CV_PI);
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204 switch (img.type())
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207 hog::compute_gradients_8UC1(nbins, img.rows, img.cols, img, angleScale, _grad, _qangle, gamma_correction);
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210 hog::compute_gradients_8UC4(nbins, img.rows, img.cols, img, angleScale, _grad, _qangle, gamma_correction);
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216 void cv::gpu::HOGDescriptor::computeBlockHistograms(const GpuMat& img)
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218 computeGradient(img, grad, qangle);
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220 size_t block_hist_size = getBlockHistogramSize();
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221 Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride);
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223 // block_hists.create(1, block_hist_size * blocks_per_img.area(), CV_32F);
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224 block_hists = getBuffer(1, static_cast<int>(block_hist_size * blocks_per_img.area()), CV_32F, block_hists_buf);
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226 hog::compute_hists(nbins, block_stride.width, block_stride.height, img.rows, img.cols,
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227 grad, qangle, (float)getWinSigma(), block_hists.ptr<float>());
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229 hog::normalize_hists(nbins, block_stride.width, block_stride.height, img.rows, img.cols,
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230 block_hists.ptr<float>(), (float)threshold_L2hys);
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234 void cv::gpu::HOGDescriptor::getDescriptors(const GpuMat& img, Size win_stride, GpuMat& descriptors, int descr_format)
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236 CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0);
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238 computeBlockHistograms(img);
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240 const size_t block_hist_size = getBlockHistogramSize();
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241 Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride);
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242 Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride);
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244 descriptors.create(wins_per_img.area(), static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F);
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246 switch (descr_format)
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248 case DESCR_FORMAT_ROW_BY_ROW:
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249 hog::extract_descrs_by_rows(win_size.height, win_size.width, block_stride.height, block_stride.width,
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250 win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(), descriptors);
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252 case DESCR_FORMAT_COL_BY_COL:
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253 hog::extract_descrs_by_cols(win_size.height, win_size.width, block_stride.height, block_stride.width,
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254 win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(), descriptors);
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257 CV_Error(CV_StsBadArg, "Unknown descriptor format");
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262 void cv::gpu::HOGDescriptor::detect(const GpuMat& img, vector<Point>& hits, double hit_threshold, Size win_stride, Size padding)
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264 CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
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265 CV_Assert(padding == Size(0, 0));
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268 if (detector.empty())
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271 computeBlockHistograms(img);
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273 if (win_stride == Size())
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274 win_stride = block_stride;
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276 CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0);
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278 Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride);
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279 // labels.create(1, wins_per_img.area(), CV_8U);
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280 labels = getBuffer(1, wins_per_img.area(), CV_8U, labels_buf);
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282 hog::classify_hists(win_size.height, win_size.width, block_stride.height, block_stride.width,
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283 win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(),
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284 detector.ptr<float>(), (float)free_coef, (float)hit_threshold, labels.ptr());
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286 labels.download(labels_host);
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287 unsigned char* vec = labels_host.ptr();
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288 for (int i = 0; i < wins_per_img.area(); i++)
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290 int y = i / wins_per_img.width;
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291 int x = i - wins_per_img.width * y;
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293 hits.push_back(Point(x * win_stride.width, y * win_stride.height));
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299 void cv::gpu::HOGDescriptor::detectMultiScale(const GpuMat& img, vector<Rect>& found_locations, double hit_threshold,
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300 Size win_stride, Size padding, double scale0, int group_threshold)
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303 CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4);
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305 vector<double> level_scale;
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309 for (levels = 0; levels < nlevels; levels++)
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311 level_scale.push_back(scale);
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312 if (cvRound(img.cols/scale) < win_size.width ||
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313 cvRound(img.rows/scale) < win_size.height || scale0 <= 1)
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317 levels = std::max(levels, 1);
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318 level_scale.resize(levels);
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319 image_scales.resize(levels);
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321 std::vector<Rect> all_candidates;
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322 vector<Point> locations;
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324 for (size_t i = 0; i < level_scale.size(); i++)
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326 scale = level_scale[i];
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327 Size sz(cvRound(img.cols / scale), cvRound(img.rows / scale));
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328 GpuMat smaller_img;
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330 if (sz == img.size())
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334 image_scales[i].create(sz, img.type());
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335 switch (img.type())
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337 case CV_8UC1: hog::resize_8UC1(img, image_scales[i]); break;
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338 case CV_8UC4: hog::resize_8UC4(img, image_scales[i]); break;
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340 smaller_img = image_scales[i];
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343 detect(smaller_img, locations, hit_threshold, win_stride, padding);
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344 Size scaled_win_size(cvRound(win_size.width * scale), cvRound(win_size.height * scale));
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345 for (size_t j = 0; j < locations.size(); j++)
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346 all_candidates.push_back(Rect(Point2d((CvPoint)locations[j]) * scale, scaled_win_size));
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349 found_locations.assign(all_candidates.begin(), all_candidates.end());
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350 groupRectangles(found_locations, group_threshold, 0.2/*magic number copied from CPU version*/);
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353 int cv::gpu::HOGDescriptor::numPartsWithin(int size, int part_size, int stride)
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355 return (size - part_size + stride) / stride;
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358 cv::Size cv::gpu::HOGDescriptor::numPartsWithin(cv::Size size, cv::Size part_size, cv::Size stride)
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360 return Size(numPartsWithin(size.width, part_size.width, stride.width), numPartsWithin(size.height, part_size.height, stride.height));
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363 std::vector<float> cv::gpu::HOGDescriptor::getDefaultPeopleDetector()
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365 return getPeopleDetector64x128();
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368 std::vector<float> cv::gpu::HOGDescriptor::getPeopleDetector48x96()
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370 static const float detector[] = {
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371 0.294350f, -0.098796f, -0.129522f, 0.078753f, 0.387527f, 0.261529f,
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372 0.145939f, 0.061520f, 0.328699f, 0.227148f, -0.066467f, -0.086723f,
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373 0.047559f, 0.106714f, 0.037897f, 0.111461f, -0.024406f, 0.304769f,
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374 0.254676f, -0.069235f, 0.082566f, 0.147260f, 0.326969f, 0.148888f,
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375 0.055270f, -0.087985f, 0.261720f, 0.143442f, 0.026812f, 0.238212f,
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376 0.194020f, 0.056341f, -0.025854f, -0.034444f, -0.156631f, 0.205174f,
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377 0.089008f, -0.139811f, -0.100147f, -0.037830f, -0.029230f, -0.055641f,
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378 0.033248f, -0.016512f, 0.155244f, 0.247315f, -0.124694f, -0.048414f,
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379 -0.062219f, 0.193683f, 0.004574f, 0.055089f, 0.093565f, 0.167712f,
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380 0.167581f, 0.018895f, 0.215258f, 0.122609f, 0.090520f, -0.067219f,
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381 -0.049029f, -0.099615f, 0.241804f, -0.094893f, -0.176248f, 0.001727f,
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382 -0.134473f, 0.104442f, 0.050942f, 0.081165f, 0.072156f, 0.121646f,
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383 0.002656f, -0.297974f, -0.133587f, -0.060121f, -0.092515f, -0.048974f,
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384 -0.084754f, -0.180111f, -0.038590f, 0.086283f, -0.134636f, -0.107249f,
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385 0.132890f, 0.141556f, 0.249425f, 0.130273f, -0.030031f, 0.073212f,
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386 -0.008155f, 0.019931f, 0.071688f, 0.000300f, -0.019525f, -0.021725f,
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387 -0.040993f, -0.086841f, 0.070124f, 0.240033f, 0.265350f, 0.043208f,
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388 0.166754f, 0.091453f, 0.060916f, -0.036972f, -0.091043f, 0.079873f,
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389 0.219781f, 0.158102f, -0.140618f, -0.043016f, 0.124802f, 0.093668f,
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390 0.103208f, 0.094872f, 0.080541f, 0.137711f, 0.160566f, -0.169231f,
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391 0.013983f, 0.309508f, -0.004217f, -0.057200f, -0.064489f, 0.014066f,
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392 0.361009f, 0.251328f, -0.080983f, -0.044183f, 0.061436f, -0.037381f,
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393 -0.078786f, 0.030993f, 0.066314f, 0.037683f, 0.152325f, -0.091683f,
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394 0.070203f, 0.217856f, 0.036435f, -0.076462f, 0.006254f, -0.094431f,
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395 0.154829f, -0.023038f, -0.196961f, -0.024594f, 0.178465f, -0.050139f,
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396 -0.045932f, -0.000965f, 0.109112f, 0.046165f, -0.159373f, -0.008713f,
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397 0.041307f, 0.097129f, -0.057211f, -0.064599f, 0.077165f, 0.176167f,
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398 0.138322f, 0.065753f, -0.104950f, 0.017933f, 0.136255f, -0.011598f,
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399 0.047007f, 0.080550f, 0.068619f, 0.084661f, -0.035493f, -0.091314f,
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400 -0.041411f, 0.060971f, -0.101912f, -0.079870f, -0.085977f, -0.022686f,
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401 0.079788f, -0.098064f, -0.054603f, 0.040383f, 0.300794f, 0.128603f,
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402 0.094844f, 0.047407f, 0.101825f, 0.061832f, -0.162160f, -0.204553f,
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403 -0.035165f, 0.101450f, -0.016641f, -0.027140f, -0.134392f, -0.008743f,
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404 0.102331f, 0.114853f, 0.009644f, 0.062823f, 0.237339f, 0.167843f,
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405 0.053066f, -0.012592f, 0.043158f, 0.002305f, 0.065001f, -0.038929f,
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406 -0.020356f, 0.152343f, 0.043469f, -0.029967f, -0.042948f, 0.032481f,
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407 0.068488f, -0.110840f, -0.111083f, 0.111980f, -0.002072f, -0.005562f,
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408 0.082926f, 0.006635f, -0.108153f, 0.024242f, -0.086464f, -0.189884f,
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409 -0.017492f, 0.191456f, -0.007683f, -0.128769f, -0.038017f, -0.132380f,
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410 0.091926f, 0.079696f, -0.106728f, -0.007656f, 0.172744f, 0.011576f,
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411 0.009883f, 0.083258f, -0.026516f, 0.145534f, 0.153924f, -0.130290f,
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412 -0.108945f, 0.124490f, -0.003186f, -0.100485f, 0.015024f, -0.060512f,
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413 0.026288f, -0.086713f, -0.169012f, 0.076517f, 0.215778f, 0.043701f,
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414 -0.131642f, -0.012585f, -0.045181f, -0.118183f, -0.241544f, -0.167293f,
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415 -0.020107f, -0.019917f, -0.101827f, -0.107096f, -0.010503f, 0.044938f,
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416 0.189680f, 0.217119f, -0.046086f, 0.044508f, 0.199716f, -0.036004f,
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417 -0.148927f, 0.013355f, -0.078279f, 0.030451f, 0.056301f, -0.024609f,
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418 0.083224f, 0.099533f, -0.039432f, -0.138880f, 0.005482f, -0.024120f,
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419 -0.140468f, -0.066381f, -0.017057f, 0.009260f, -0.058004f, -0.028486f,
\r
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586 -0.036308f, -0.046731f, -0.022099f, 0.095776f, 0.409423f, 0.060635f,
\r
587 -0.065196f, 0.051828f, 0.027981f, -0.009609f, -0.137681f, -0.095011f,
\r
588 -0.019045f, 0.177278f, 0.009759f, -0.092119f, -0.016958f, -0.133860f,
\r
589 -0.118421f, -0.032039f, -0.006214f, -0.084541f, 0.063971f, -0.073642f,
\r
590 0.165676f, 0.110443f, 0.044131f, 0.046568f, 0.053292f, -0.055466f,
\r
591 0.015512f, 0.371947f, 0.232102f, -0.016923f, 0.103979f, -0.091758f,
\r
592 0.005907f, 0.209100f, 0.157433f, 0.030518f, 0.250366f, 0.062322f,
\r
593 0.036720f, 0.094676f, 0.017306f, -0.010328f, -0.079012f, 0.016781f,
\r
594 -0.112435f, 0.061795f, 0.042543f, -0.126799f, -0.009975f, -0.056760f,
\r
595 0.046424f, -0.194712f, -0.139399f, -0.037731f, 0.157989f, -0.016261f,
\r
596 0.123345f, 0.230563f, 0.083300f, -0.016392f, 0.059567f, -0.016035f,
\r
597 -0.064767f, 0.231945f, 0.156629f, 0.034602f, 0.145628f, 0.041315f,
\r
598 0.034535f, 0.019967f, -0.089188f, -0.012091f, 0.307857f, 0.211405f,
\r
599 -0.025091f, -0.148249f, -0.129384f, 0.063536f, -0.068603f, -0.067941f,
\r
600 -0.035104f, 0.210832f, 0.063810f, 0.062764f, -0.089889f, -0.030554f,
\r
601 0.014791f, -0.053362f, -0.037818f, -0.196640f, 0.008388f, -0.082654f,
\r
602 0.143056f, 0.064221f, 0.069795f, 0.191040f, 0.097321f, -0.028679f,
\r
603 0.075794f, 0.313154f, 0.086240f, 0.207643f, 0.017809f, 0.122867f,
\r
604 0.224586f, 0.167403f, -0.023884f, 0.047434f, 0.344091f, 0.187745f,
\r
605 0.136177f, 0.141738f, 0.063799f, 0.045233f, -0.077342f, -0.003525f,
\r
606 -0.165041f, -0.025616f, -0.073745f, 0.164439f, 0.011200f, -0.145896f,
\r
607 -0.027954f, -0.061987f, -0.039874f, -0.142775f, 0.151042f, -0.038238f,
\r
608 0.053152f, 0.078615f, 0.086061f, 0.100593f, 0.128046f, -0.071006f,
\r
609 -0.116558f, 0.208445f, 0.051086f, 0.076843f, 0.023191f, -0.084781f,
\r
610 -0.011790f, 0.147807f, -0.048554f, -0.113932f, 0.283322f, 0.190934f,
\r
611 0.092789f, 0.033018f, -0.142428f, -0.142480f, -0.099023f, -0.041020f,
\r
612 -0.042760f, 0.203295f, -0.053475f, 0.042424f, 0.222839f, -0.019167f,
\r
613 -0.133176f, -0.276216f, -0.031998f, 0.117290f, 0.177827f, -0.059973f,
\r
614 -0.064744f, -0.117040f, -0.155482f, -0.099531f, 0.164121f, -0.026682f,
\r
615 -0.093810f, 0.238993f, -0.006506f, 0.007830f, 0.065819f, -0.203643f,
\r
616 -0.100925f, -0.053652f, -0.130770f, 0.026277f, 0.131796f, 0.032742f,
\r
617 0.127186f, 0.116694f, -0.161122f, -0.279773f, -0.252515f, -0.002638f,
\r
618 0.042812f, 0.096776f, -0.123280f, 0.064858f, -0.010455f, -0.219760f,
\r
619 -0.239331f, -0.104363f, -0.058022f, -0.053584f, 0.025611f, 0.005129f,
\r
620 -0.100418f, -0.045712f, -0.194418f, -0.126366f, -0.030530f, 0.051168f,
\r
621 0.215959f, 0.172402f, -0.054700f, -0.185995f, -0.278360f, -0.193693f,
\r
622 -0.040309f, 0.003735f, -0.007770f, 0.123556f, 0.190179f, -0.077315f,
\r
623 0.117403f, 0.212942f, 0.012160f, 0.000113f, 0.027331f, 0.040202f,
\r
624 0.033293f, 0.219438f, 0.184174f, 0.259349f, 0.311206f, 0.082547f,
\r
625 -0.047875f, -0.078417f, 0.010746f, 0.082620f, 0.311931f, 0.307605f,
\r
626 0.003863f, 0.021405f, -0.026388f, -0.019572f, 0.020582f, -0.059353f,
\r
627 0.025199f, 0.261319f, 0.086316f, 0.143614f, 0.107780f, 0.003900f,
\r
628 -0.188397f, -0.038563f, -0.106045f, -0.125154f, -0.010509f, 0.054021f,
\r
629 0.242130f, 0.279152f, 0.215546f, 0.346995f, 0.440856f, 0.237452f,
\r
630 0.234154f, 0.301646f, 0.168929f, -0.208358f, -0.126848f, 0.010260f,
\r
631 0.121018f, -0.062975f, -0.052848f, 0.050341f, -0.061103f, -0.266482f,
\r
632 0.107186f, 0.140221f, 0.280065f, 0.287889f, 0.373198f, 0.151596f,
\r
633 0.013593f, 0.115616f, 0.014616f, -0.281710f, -0.237597f, -0.117305f,
\r
634 -0.000034f, -0.136739f, -0.196275f, -0.095225f, -0.125310f, -0.250514f,
\r
635 0.236804f, -0.071805f, -0.037421f, 0.048230f, 0.321596f, 0.063632f,
\r
636 0.024039f, -0.029133f, 0.230983f, 0.160593f, -0.154355f, -0.013086f,
\r
637 -0.079929f, 0.094692f, 0.160391f, 0.180239f, 0.053895f, 0.100759f,
\r
638 0.288631f, 0.038191f, 0.181692f, 0.229682f, 0.440166f, 0.063401f,
\r
639 0.006273f, 0.020865f, 0.338695f, 0.256244f, -0.043927f, 0.115617f,
\r
640 0.003296f, 0.173965f, 0.021318f, -0.040936f, -0.118932f, 0.182380f,
\r
641 0.235922f, -0.053233f, -0.015053f, -0.101057f, 0.095341f, 0.051111f,
\r
642 0.161831f, 0.032614f, 0.159496f, 0.072375f, 0.025089f, 0.023748f,
\r
643 0.029151f, 0.161284f, -0.117717f, -0.036191f, -0.176822f, -0.162006f,
\r
644 0.226542f, -0.078329f, 0.043079f, -0.119172f, 0.054614f, -0.101365f,
\r
645 -0.064541f, -0.115304f, 0.135170f, 0.298872f, 0.098060f, 0.089428f,
\r
646 -0.007497f, 0.110391f, -0.028824f, 0.020835f, -0.036804f, 0.125411f,
\r
647 0.192105f, -0.048931f, 0.003086f, -0.010681f, 0.074698f, -0.016263f,
\r
648 0.096063f, 0.060267f, -0.007277f, 0.139139f, -0.080635f, 0.036628f,
\r
649 0.086058f, 0.131979f, 0.085707f, 0.025301f, 0.226094f, 0.194759f,
\r
650 0.042193f, -0.157846f, -0.068402f, -0.141450f, -0.112659f, -0.076305f,
\r
651 -0.069085f, -0.114332f, -0.102005f, 0.132193f, -0.067042f, 0.106643f,
\r
652 0.198964f, 0.171616f, 0.167237f, -0.033730f, -0.026755f, 0.083621f,
\r
653 0.149459f, -0.002799f, -0.000318f, 0.011753f, 0.065889f, -0.089375f,
\r
654 -0.049610f, 0.224579f, 0.216548f, -0.034908f, -0.017851f, -0.088144f,
\r
655 0.007530f, 0.240268f, 0.073270f, 0.013263f, 0.175323f, 0.012082f,
\r
656 0.093993f, 0.015282f, 0.105854f, 0.107990f, 0.077798f, -0.096166f,
\r
657 -0.079607f, 0.177820f, 0.142392f, 0.033337f, -0.078100f, -0.081616f,
\r
658 -0.046993f, 0.139459f, 0.020272f, -0.123161f, 0.175269f, 0.105217f,
\r
659 0.057328f, 0.080909f, -0.012612f, -0.097081f, 0.082060f, -0.096716f,
\r
660 -0.063921f, 0.201884f, 0.128166f, -0.035051f, -0.032227f, -0.068139f,
\r
661 -0.115915f, 0.095080f, -0.086007f, -0.067543f, 0.030776f, 0.032712f,
\r
662 0.088937f, 0.054336f, -0.039329f, -0.114022f, 0.171672f, -0.112321f,
\r
663 -0.217646f, 0.065186f, 0.060223f, 0.192174f, 0.055580f, -0.131107f,
\r
664 -0.144338f, 0.056730f, -0.034707f, -0.081616f, -0.135298f, -0.000614f,
\r
665 0.087189f, 0.014614f, 0.067709f, 0.107689f, 0.225780f, 0.084361f,
\r
666 -0.008544f, 0.051649f, -0.048369f, -0.037739f, -0.060710f, 0.002654f,
\r
667 0.016935f, 0.085563f, -0.015961f, -0.019265f, 0.111788f, 0.062376f,
\r
668 0.202019f, 0.047713f, 0.042261f, 0.069716f, 0.242913f, 0.021052f,
\r
669 -0.072812f, -0.155920f, -0.026436f, 0.035621f, -0.079300f, -0.028787f,
\r
670 -0.048329f, 0.084718f, -0.060565f, -0.083750f, -0.164075f, -0.040742f,
\r
671 -0.086219f, 0.015271f, -0.005204f, -0.016038f, 0.045816f, -0.050433f,
\r
672 -0.077652f, 0.117109f, 0.009611f, -0.009045f, -0.008634f, -0.055373f,
\r
673 -0.085968f, 0.028527f, -0.054736f, -0.168089f, 0.175839f, 0.071205f,
\r
674 -0.023603f, 0.037907f, -0.004561f, -0.022634f, 0.123831f, 0.094469f,
\r
675 -0.072920f, -0.133642f, -0.014032f, -0.142754f, -0.026999f, -0.199409f,
\r
676 0.013268f, 0.226989f, 0.048650f, -0.170988f, -0.050141f, 0.007880f,
\r
677 0.061880f, 0.019078f, -0.043578f, -0.038139f, 0.134814f, 0.054097f,
\r
678 -0.081670f, 0.176838f, 0.047920f, -0.038176f, 0.050406f, -0.107181f,
\r
679 -0.036279f, 0.027060f, 0.081594f, -0.002820f, 0.090507f, -0.033338f,
\r
680 -0.059571f, 0.013404f, -0.099860f, 0.073371f, 0.342805f, 0.098305f,
\r
681 -0.150910f, -0.020822f, -0.056960f, 0.046262f, -0.043413f, -0.149405f,
\r
682 -0.129105f, -0.010899f, -0.014229f, -0.179949f, -0.113044f, -0.049468f,
\r
683 -0.065513f, 0.090269f, -0.011919f, 0.087846f, 0.095796f, 0.146127f,
\r
684 0.101599f, 0.078066f, -0.084348f, -0.100002f, -0.020134f, -0.050169f,
\r
685 0.062122f, 0.014640f, 0.019143f, 0.036543f, 0.180924f, -0.013976f,
\r
686 -0.066768f, -0.001090f, -0.070419f, -0.004839f, -0.001504f, 0.034483f,
\r
687 -0.044954f, -0.050336f, -0.088638f, -0.174782f, -0.116082f, -0.205507f,
\r
688 0.015587f, -0.042839f, -0.096879f, -0.144097f, -0.050268f, -0.196796f,
\r
689 0.109639f, 0.271411f, 0.173732f, 0.108070f, 0.156437f, 0.124255f,
\r
690 0.097242f, 0.238693f, 0.083941f, 0.109105f, 0.223940f, 0.267188f,
\r
691 0.027385f, 0.025819f, 0.125070f, 0.093738f, 0.040353f, 0.038645f,
\r
692 -0.012730f, 0.144063f, 0.052931f, -0.009138f, 0.084193f, 0.160272f,
\r
693 -0.041366f, 0.011951f, -0.121446f, -0.106713f, -0.047566f, 0.047984f,
\r
694 -0.255224f, -0.076116f, 0.098685f, -0.150845f, -0.171513f, -0.156590f,
\r
695 0.058331f, 0.187493f, 0.413018f, 0.554265f, 0.372242f, 0.237943f,
\r
696 0.124571f, 0.110829f, 0.010322f, -0.174477f, -0.067627f, -0.001979f,
\r
697 0.142913f, 0.040597f, 0.019907f, 0.025963f, -0.043585f, -0.120732f,
\r
698 0.099937f, 0.091059f, 0.247307f, 0.204226f, -0.042753f, -0.068580f,
\r
699 -0.119002f, 0.026722f, 0.034853f, -0.060934f, -0.025054f, -0.093026f,
\r
700 -0.035372f, -0.233209f, -0.049869f, -0.039151f, -0.022279f, -0.065380f,
\r
702 return vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
\r
708 std::vector<float> cv::gpu::HOGDescriptor::getPeopleDetector64x128()
\r
710 static const float detector[] = {
\r
711 0.05359386f, -0.14721455f, -0.05532170f, 0.05077307f,
\r
712 0.11547081f, -0.04268804f, 0.04635834f, -0.05468199f, 0.08232084f,
\r
713 0.10424068f, -0.02294518f, 0.01108519f, 0.01378693f, 0.11193510f,
\r
714 0.01268418f, 0.08528346f, -0.06309239f, 0.13054633f, 0.08100729f,
\r
715 -0.05209739f, -0.04315529f, 0.09341384f, 0.11035026f, -0.07596218f,
\r
716 -0.05517511f, -0.04465296f, 0.02947334f, 0.04555536f,
\r
717 -3.55954492e-003f, 0.07818956f, 0.07730991f, 0.07890715f, 0.06222893f,
\r
718 0.09001380f, -0.03574381f, 0.03414327f, 0.05677258f, -0.04773581f,
\r
719 0.03746637f, -0.03521175f, 0.06955440f, -0.03849038f, 0.01052293f,
\r
720 0.01736112f, 0.10867710f, 0.08748853f, 3.29739624e-003f, 0.10907028f,
\r
721 0.07913758f, 0.10393070f, 0.02091867f, 0.11594022f, 0.13182420f,
\r
722 0.09879354f, 0.05362710f, -0.06745391f, -7.01260753e-003f,
\r
723 5.24702156e-003f, 0.03236255f, 0.01407916f, 0.02207983f, 0.02537322f,
\r
724 0.04547948f, 0.07200756f, 0.03129894f, -0.06274468f, 0.02107014f,
\r
725 0.06035208f, 0.08636236f, 4.53164103e-003f, 0.02193363f, 0.02309801f,
\r
726 0.05568166f, -0.02645093f, 0.04448695f, 0.02837519f, 0.08975694f,
\r
727 0.04461516f, 0.08975355f, 0.07514391f, 0.02306982f, 0.10410084f,
\r
728 0.06368385f, 0.05943464f, 4.58420580e-003f, 0.05220337f, 0.06675851f,
\r
729 0.08358569f, 0.06712101f, 0.06559004f, -0.03930482f, -9.15936660e-003f,
\r
730 -0.05897915f, 0.02816453f, 0.05032348f, 0.06780671f, 0.03377650f,
\r
731 -6.09417039e-004f, -0.01795146f, -0.03083684f, -0.01302475f,
\r
732 -0.02972313f, 7.88706727e-003f, -0.03525961f, -2.50397739e-003f,
\r
733 0.05245084f, 0.11791293f, -0.02167498f, 0.05299332f, 0.06640524f,
\r
734 0.05190265f, -8.27316567e-003f, 0.03033127f, 0.05842173f,
\r
735 -4.01050318e-003f, -6.25105947e-003f, 0.05862958f, -0.02465461f,
\r
736 0.05546781f, -0.08228195f, -0.07234028f, 0.04640540f, -0.01308254f,
\r
737 -0.02506191f, 0.03100746f, -0.04665651f, -0.04591486f, 0.02949927f,
\r
738 0.06035462f, 0.02244646f, -0.01698639f, 0.01040041f, 0.01131170f,
\r
739 0.05419579f, -0.02130277f, -0.04321722f, -0.03665198f, 0.01126490f,
\r
740 -0.02606488f, -0.02228328f, -0.02255680f, -0.03427236f,
\r
741 -7.75165204e-003f, -0.06195229f, 8.21638294e-003f, 0.09535975f,
\r
742 -0.03709979f, -0.06942501f, 0.14579427f, -0.05448192f, -0.02055904f,
\r
743 0.05747357f, 0.02781788f, -0.07077577f, -0.05178314f, -0.10429011f,
\r
744 -0.11235505f, 0.07529039f, -0.07559302f, -0.08786739f, 0.02983843f,
\r
745 0.02667585f, 0.01382199f, -0.01797496f, -0.03141199f, -0.02098101f,
\r
746 0.09029204f, 0.04955018f, 0.13718739f, 0.11379953f, 1.80019124e-003f,
\r
747 -0.04577610f, -1.11108483e-003f, -0.09470536f, -0.11596080f,
\r
748 0.04489342f, 0.01784211f, 3.06850672e-003f, 0.10781866f,
\r
749 3.36498418e-003f, -0.10842580f, -0.07436839f, -0.10535070f,
\r
750 -0.01866805f, 0.16057891f, -5.07316366e-003f, -0.04295658f,
\r
751 -5.90488780e-003f, 8.82003549e-003f, -0.01492646f, -0.05029279f,
\r
752 -0.12875880f, 8.78831954e-004f, -0.01297184f, -0.07592774f,
\r
753 -0.02668831f, -6.93787413e-004f, 0.02406698f, -0.01773298f,
\r
754 -0.03855745f, -0.05877856f, 0.03259695f, 0.12826584f, 0.06292590f,
\r
755 -4.10733931e-003f, 0.10996531f, 0.01332991f, 0.02088735f, 0.04037504f,
\r
756 -0.05210760f, 0.07760046f, 0.06399347f, -0.05751930f, -0.10053057f,
\r
757 0.07505023f, -0.02139782f, 0.01796176f, 2.34400877e-003f, -0.04208319f,
\r
758 0.07355055f, 0.05093350f, -0.02996780f, -0.02219072f, 0.03355330f,
\r
759 0.04418742f, -0.05580705f, -0.05037573f, -0.04548179f, 0.01379514f,
\r
760 0.02150671f, -0.02194211f, -0.13682702f, 0.05464972f, 0.01608082f,
\r
761 0.05309116f, 0.04701022f, 1.33690401e-003f, 0.07575664f, 0.09625306f,
\r
762 8.92647635e-003f, -0.02819123f, 0.10866830f, -0.03439325f,
\r
763 -0.07092371f, -0.06004780f, -0.02712298f, -7.07467366e-003f,
\r
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1466 -1.85360224e-003f, -5.94652840e-004f, -0.04451817f, 2.98327743e-003f,
\r
1467 0.06272484f, -0.02152076f, -3.05971340e-003f, -0.05070828f,
\r
1468 0.01531762f, 0.01282815f, 0.05167150f, 9.46266949e-003f,
\r
1469 -3.34558333e-003f, 0.11442288f, -0.03906701f, -2.67325155e-003f,
\r
1470 0.03069184f, -0.01134165f, 0.02949462f, 0.02879886f, 0.03855566f,
\r
1471 -0.03450781f, 0.09142872f, -0.02156654f, 0.06075062f, -0.06220816f,
\r
1472 0.01944680f, 6.68372354e-003f, -0.06656796f, 8.70784000e-003f,
\r
1473 0.03456013f, 0.02434320f, -0.13236357f, -0.04177035f, -0.02069627f,
\r
1474 0.01068112f, 0.01505432f, -0.07517391f, -3.83571628e-003f,
\r
1475 -0.06298508f, -0.02881260f, -0.13101046f, -0.07221562f,
\r
1476 -5.79945277e-003f, -8.57300125e-003f, 0.03782469f, 0.02762164f,
\r
1477 0.04942456f, -0.02936396f, 0.09597211f, 0.01921411f, 0.06101191f,
\r
1478 -0.04787507f, -0.01379578f, -7.40224449e-003f, -0.02220136f,
\r
1479 -0.01313756f, 7.77558051e-003f, 0.12296968f, 0.02939998f, 0.03594062f,
\r
1480 -0.07788624f, -0.01133144f, 3.99316690e-004f, -0.06090347f,
\r
1481 -0.01122066f, -4.68682544e-003f, 0.07633100f, -0.06748922f,
\r
1482 -0.05640298f, -0.05265681f, -0.01139122f, -0.01624347f, -0.04715714f,
\r
1483 -0.01099092f, 0.01048561f, 3.28499987e-003f, -0.05810167f,
\r
1484 -0.07699911f, -0.03330683f, 0.04185145f, 0.03478536f, 0.02275165f,
\r
1485 0.02304766f, 6.66040834e-003f, 0.10968148f, -5.93013782e-003f,
\r
1486 -0.04858336f, -0.04203213f, -0.09316786f, -6.13074889e-003f,
\r
1487 -0.02544625f, 0.01366201f, 9.18555818e-003f, -0.01846578f,
\r
1488 -0.05622401f, -0.03989377f, -0.07810296f, 6.91275718e-003f,
\r
1489 0.05957597f, -0.03901334f, 0.01572002f, -0.01193903f,
\r
1490 -6.89400872e-003f, -0.03093356f, -0.04136098f, -0.01562869f,
\r
1491 -0.04604580f, 0.02865234f, -0.08678447f, -0.03232484f, -0.05364593f,
\r
1492 -0.01445016f, -0.07003860f, -0.08669746f, -0.04520775f, 0.04274122f,
\r
1493 0.03117515f, 0.08175703f, 0.01081109f, 0.06379741f, 0.06199206f,
\r
1494 0.02865988f, 0.02360346f, 0.06725410f, -0.03248780f, -9.37702879e-003f,
\r
1495 0.08265898f, -0.02245839f, 0.05125763f, -0.01862395f, 0.01973453f,
\r
1496 -0.01994494f, -0.10770868f, 0.03180375f, 3.23935156e-003f,
\r
1497 -0.02142080f, -0.04256190f, 0.04760900f, 0.04282863f, 0.05635953f,
\r
1498 -0.01870849f, 0.05540622f, -0.03042666f, 0.01455277f, -0.06630179f,
\r
1499 -0.05843807f, -0.03739681f, -0.09739155f, -0.03220233f, -0.05620182f,
\r
1500 -0.10381401f, 0.07400211f, 4.20676917e-003f, 0.03258535f,
\r
1501 2.14308966e-003f, 0.05121966f, -0.01274337f, 0.02384761f, 0.06335578f,
\r
1502 -0.07905591f, 0.08375625f, -0.07898903f, -0.06508528f, -0.02498444f,
\r
1503 0.06535810f, 0.03970535f, 0.04895468f, -0.01169566f, -0.03980601f,
\r
1504 0.05682293f, 0.05925463f, -0.01165808f, -0.07936699f, -0.04208954f,
\r
1505 0.01333987f, 0.09051196f, 0.10098671f, -0.03974256f, 0.01238771f,
\r
1506 -0.07501741f, -0.03655440f, -0.04301528f, 0.09216860f,
\r
1507 4.63579083e-004f, 0.02851115f, 0.02142735f, 1.28244064e-004f,
\r
1508 0.02879687f, -0.08554889f, -0.04838862f, 0.08135369f, -0.05756533f,
\r
1509 0.01413900f, 0.03451880f, -0.06619488f, -0.03053130f, 0.02961676f,
\r
1510 -0.07384635f, 0.01135692f, 0.05283910f, -0.07778034f, -0.02107482f,
\r
1511 -0.05511716f, -0.13473752f, 0.03030157f, 0.06722020f, -0.06218817f,
\r
1512 -0.05826827f, 0.06254654f, 0.02895772f, -0.01664000f, -0.03620280f,
\r
1513 -0.01612278f, -1.46097376e-003f, 0.14013411f, -8.96181818e-003f,
\r
1514 -0.03250246f, 3.38630192e-003f, 2.64779478e-003f, 0.03359732f,
\r
1515 -0.02411991f, -0.04229729f, 0.10666174f, -6.66579151f };
\r
1516 return vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
\r