C++程序
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108.25 KB
/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// copy or use the software.
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//
// License Agreement
// For Open Source Computer Vision Library
//
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#include "precomp.hpp"
using namespace cv;
using namespace cv::cuda;
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
Ptr<cuda::HOG> cv::cuda::HOG::create(Size, Size, Size, Size, int) { throw_no_cuda(); return Ptr<cuda::HOG>(); }
#else
namespace cv { namespace cuda { namespace device
{
namespace hog
{
void set_up_constants(int nbins, int block_stride_x, int block_stride_y,
int nblocks_win_x, int nblocks_win_y);
void compute_hists(int nbins, int block_stride_x, int blovck_stride_y,
int height, int width, const cv::cuda::PtrStepSzf& grad,
const cv::cuda::PtrStepSzb& qangle, float sigma, float* block_hists);
void normalize_hists(int nbins, int block_stride_x, int block_stride_y,
int height, int width, float* block_hists, float threshold);
void 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, float* block_hists, float* coefs, float free_coef,
float threshold, unsigned char* labels);
void compute_confidence_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, float* block_hists,
float* coefs, float free_coef, float threshold, float *confidences);
void 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, float* block_hists,
cv::cuda::PtrStepSzf descriptors);
void 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, float* block_hists,
cv::cuda::PtrStepSzf descriptors);
void compute_gradients_8UC1(int nbins, int height, int width, const cv::cuda::PtrStepSzb& img,
float angle_scale, cv::cuda::PtrStepSzf grad, cv::cuda::PtrStepSzb qangle, bool correct_gamma);
void compute_gradients_8UC4(int nbins, int height, int width, const cv::cuda::PtrStepSzb& img,
float angle_scale, cv::cuda::PtrStepSzf grad, cv::cuda::PtrStepSzb qangle, bool correct_gamma);
void resize_8UC1(const cv::cuda::PtrStepSzb& src, cv::cuda::PtrStepSzb dst);
void resize_8UC4(const cv::cuda::PtrStepSzb& src, cv::cuda::PtrStepSzb dst);
}
}}}
using namespace cv::cuda::device;
namespace
{
class HOG_Impl : public cv::cuda::HOG
{
public:
HOG_Impl(Size win_size,
Size block_size,
Size block_stride,
Size cell_size,
int nbins);
virtual void setWinSigma(double win_sigma) { win_sigma_ = win_sigma; }
virtual double getWinSigma() const;
virtual void setL2HysThreshold(double threshold_L2hys) { threshold_L2hys_ = threshold_L2hys; }
virtual double getL2HysThreshold() const { return threshold_L2hys_; }
virtual void setGammaCorrection(bool gamma_correction) { gamma_correction_ = gamma_correction; }
virtual bool getGammaCorrection() const { return gamma_correction_; }
virtual void setNumLevels(int nlevels) { nlevels_ = nlevels; }
virtual int getNumLevels() const { return nlevels_; }
virtual void setHitThreshold(double hit_threshold) { hit_threshold_ = hit_threshold; }
virtual double getHitThreshold() const { return hit_threshold_; }
virtual void setWinStride(Size win_stride) { win_stride_ = win_stride; }
virtual Size getWinStride() const { return win_stride_; }
virtual void setScaleFactor(double scale0) { scale0_ = scale0; }
virtual double getScaleFactor() const { return scale0_; }
virtual void setGroupThreshold(int group_threshold) { group_threshold_ = group_threshold; }
virtual int getGroupThreshold() const { return group_threshold_; }
virtual void setDescriptorFormat(int descr_format) { descr_format_ = descr_format; }
virtual int getDescriptorFormat() const { return descr_format_; }
virtual size_t getDescriptorSize() const;
virtual size_t getBlockHistogramSize() const;
virtual void setSVMDetector(InputArray detector);
virtual Mat getDefaultPeopleDetector() const;
virtual void detect(InputArray img,
std::vector<Point>& found_locations,
std::vector<double>* confidences);
virtual void detectMultiScale(InputArray img,
std::vector<Rect>& found_locations,
std::vector<double>* confidences);
virtual void compute(InputArray img,
OutputArray descriptors,
Stream& stream);
private:
Size win_size_;
Size block_size_;
Size block_stride_;
Size cell_size_;
int nbins_;
double win_sigma_;
double threshold_L2hys_;
bool gamma_correction_;
int nlevels_;
double hit_threshold_;
Size win_stride_;
double scale0_;
int group_threshold_;
int descr_format_;
private:
int getTotalHistSize(Size img_size) const;
void computeBlockHistograms(const GpuMat& img, GpuMat& block_hists);
void computeGradient(const GpuMat& img, GpuMat& grad, GpuMat& qangle);
// Coefficients of the separating plane
float free_coef_;
GpuMat detector_;
};
HOG_Impl::HOG_Impl(Size win_size,
Size block_size,
Size block_stride,
Size cell_size,
int nbins) :
win_size_(win_size),
block_size_(block_size),
block_stride_(block_stride),
cell_size_(cell_size),
nbins_(nbins),
win_sigma_(-1.0),
threshold_L2hys_(0.2),
gamma_correction_(true),
nlevels_(64),
hit_threshold_(0.0),
win_stride_(block_stride),
scale0_(1.05),
group_threshold_(2),
descr_format_(DESCR_FORMAT_COL_BY_COL)
{
CV_Assert((win_size.width - block_size.width ) % block_stride.width == 0 &&
(win_size.height - block_size.height) % block_stride.height == 0);
CV_Assert(block_size.width % cell_size.width == 0 &&
block_size.height % cell_size.height == 0);
CV_Assert(block_stride == cell_size);
CV_Assert(cell_size == Size(8, 8));
Size cells_per_block(block_size.width / cell_size.width, block_size.height / cell_size.height);
CV_Assert(cells_per_block == Size(2, 2));
}
static int numPartsWithin(int size, int part_size, int stride)
{
return (size - part_size + stride) / stride;
}
static Size numPartsWithin(Size size, Size part_size, Size stride)
{
return Size(numPartsWithin(size.width, part_size.width, stride.width),
numPartsWithin(size.height, part_size.height, stride.height));
}
size_t HOG_Impl::getDescriptorSize() const
{
return numPartsWithin(win_size_, block_size_, block_stride_).area() * getBlockHistogramSize();
}
size_t HOG_Impl::getBlockHistogramSize() const
{
Size cells_per_block(block_size_.width / cell_size_.width, block_size_.height / cell_size_.height);
return nbins_ * cells_per_block.area();
}
double HOG_Impl::getWinSigma() const
{
return win_sigma_ >= 0 ? win_sigma_ : (block_size_.width + block_size_.height) / 8.0;
}
void HOG_Impl::setSVMDetector(InputArray _detector)
{
const int descriptor_size = static_cast<int>(getDescriptorSize());
const Mat detector = _detector.getMat();
CV_Assert( detector.type() == CV_32FC1 );
CV_Assert( detector.rows == 1 );
CV_Assert( detector.cols == descriptor_size || detector.cols == descriptor_size + 1 );
std::vector<float> detector_reordered(detector.ptr<float>(), detector.ptr<float>() + detector.cols);
size_t block_hist_size = getBlockHistogramSize();
Size blocks_per_win = numPartsWithin(win_size_, block_size_, block_stride_);
for (int i = 0; i < blocks_per_win.height; ++i)
{
for (int j = 0; j < blocks_per_win.width; ++j)
{
const float* src = detector.ptr<float>() + (j * blocks_per_win.height + i) * block_hist_size;
float* dst = &detector_reordered[0] + (i * blocks_per_win.width + j) * block_hist_size;
for (size_t k = 0; k < block_hist_size; ++k)
dst[k] = src[k];
}
}
detector_.upload(Mat(detector_reordered).reshape(1, 1));
free_coef_ = detector.cols > descriptor_size ? detector.at<float>(0, descriptor_size) : 0;
}
static Mat getPeopleDetector64x128();
static Mat getPeopleDetector48x96();
Mat HOG_Impl::getDefaultPeopleDetector() const
{
CV_Assert( win_size_ == Size(64, 128) || win_size_ == Size(48, 96) );
if (win_size_ == Size(64, 128))
return getPeopleDetector64x128();
else
return getPeopleDetector48x96();
}
void HOG_Impl::detect(InputArray _img, std::vector<Point>& hits, std::vector<double>* confidences)
{
const GpuMat img = _img.getGpuMat();
CV_Assert( img.type() == CV_8UC1 || img.type() == CV_8UC4 );
CV_Assert( win_stride_.width % block_stride_.width == 0 && win_stride_.height % block_stride_.height == 0 );
hits.clear();
if (detector_.empty())
return;
BufferPool pool(Stream::Null());
GpuMat block_hists = pool.getBuffer(1, getTotalHistSize(img.size()), CV_32FC1);
computeBlockHistograms(img, block_hists);
Size wins_per_img = numPartsWithin(img.size(), win_size_, win_stride_);
if (confidences == NULL)
{
GpuMat labels = pool.getBuffer(1, wins_per_img.area(), CV_8UC1);
hog::classify_hists(win_size_.height, win_size_.width,
block_stride_.height, block_stride_.width,
win_stride_.height, win_stride_.width,
img.rows, img.cols,
block_hists.ptr<float>(),
detector_.ptr<float>(),
(float)free_coef_,
(float)hit_threshold_,
labels.ptr());
Mat labels_host;
labels.download(labels_host);
unsigned char* vec = labels_host.ptr();
for (int i = 0; i < wins_per_img.area(); i++)
{
int y = i / wins_per_img.width;
int x = i - wins_per_img.width * y;
if (vec[i])
hits.push_back(Point(x * win_stride_.width, y * win_stride_.height));
}
}
else
{
GpuMat labels = pool.getBuffer(1, wins_per_img.area(), CV_32FC1);
hog::compute_confidence_hists(win_size_.height, win_size_.width,
block_stride_.height, block_stride_.width,
win_stride_.height, win_stride_.width,
img.rows, img.cols,
block_hists.ptr<float>(),
detector_.ptr<float>(),
(float)free_coef_,
(float)hit_threshold_,
labels.ptr<float>());
Mat labels_host;
labels.download(labels_host);
float* vec = labels_host.ptr<float>();
confidences->clear();
for (int i = 0; i < wins_per_img.area(); i++)
{
int y = i / wins_per_img.width;
int x = i - wins_per_img.width * y;
if (vec[i] >= hit_threshold_)
{
hits.push_back(Point(x * win_stride_.width, y * win_stride_.height));
confidences->push_back((double)vec[i]);
}
}
}
}
void HOG_Impl::detectMultiScale(InputArray _img,
std::vector<Rect>& found_locations,
std::vector<double>* confidences)
{
const GpuMat img = _img.getGpuMat();
CV_Assert( img.type() == CV_8UC1 || img.type() == CV_8UC4 );
CV_Assert( confidences == NULL || group_threshold_ == 0 );
std::vector<double> level_scale;
double scale = 1.0;
int levels = 0;
for (levels = 0; levels < nlevels_; levels++)
{
level_scale.push_back(scale);
if (cvRound(img.cols / scale) < win_size_.width ||
cvRound(img.rows / scale) < win_size_.height ||
scale0_ <= 1)
{
break;
}
scale *= scale0_;
}
levels = std::max(levels, 1);
level_scale.resize(levels);
std::vector<Point> level_hits;
std::vector<double> level_confidences;
BufferPool pool(Stream::Null());
found_locations.clear();
for (size_t i = 0; i < level_scale.size(); i++)
{
scale = level_scale[i];
Size sz(cvRound(img.cols / scale), cvRound(img.rows / scale));
GpuMat smaller_img;
if (sz == img.size())
{
smaller_img = img;
}
else
{
smaller_img = pool.getBuffer(sz, img.type());
switch (img.type())
{
case CV_8UC1: hog::resize_8UC1(img, smaller_img); break;
case CV_8UC4: hog::resize_8UC4(img, smaller_img); break;
}
}
detect(smaller_img, level_hits,
confidences ? &level_confidences : NULL);
Size scaled_win_size(cvRound(win_size_.width * scale),
cvRound(win_size_.height * scale));
for (size_t j = 0; j < level_hits.size(); j++)
{
found_locations.push_back(Rect(Point2d(level_hits[j]) * scale, scaled_win_size));
if (confidences)
confidences->push_back(level_confidences[j]);
}
}
if (group_threshold_ > 0)
{
groupRectangles(found_locations, group_threshold_, 0.2/*magic number copied from CPU version*/);
}
}
void HOG_Impl::compute(InputArray _img,
OutputArray _descriptors,
Stream& stream)
{
const GpuMat img = _img.getGpuMat();
CV_Assert( img.type() == CV_8UC1 || img.type() == CV_8UC4 );
CV_Assert( win_stride_.width % block_stride_.width == 0 && win_stride_.height % block_stride_.height == 0 );
CV_Assert( !stream );
BufferPool pool(stream);
GpuMat block_hists = pool.getBuffer(1, getTotalHistSize(img.size()), CV_32FC1);
computeBlockHistograms(img, block_hists);
const size_t block_hist_size = getBlockHistogramSize();
Size blocks_per_win = numPartsWithin(win_size_, block_size_, block_stride_);
Size wins_per_img = numPartsWithin(img.size(), win_size_, win_stride_);
_descriptors.create(wins_per_img.area(), static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32FC1);
GpuMat descriptors = _descriptors.getGpuMat();
switch (descr_format_)
{
case DESCR_FORMAT_ROW_BY_ROW:
hog::extract_descrs_by_rows(win_size_.height, win_size_.width,
block_stride_.height, block_stride_.width,
win_stride_.height, win_stride_.width,
img.rows, img.cols,
block_hists.ptr<float>(),
descriptors);
break;
case DESCR_FORMAT_COL_BY_COL:
hog::extract_descrs_by_cols(win_size_.height, win_size_.width,
block_stride_.height, block_stride_.width,
win_stride_.height, win_stride_.width,
img.rows, img.cols,
block_hists.ptr<float>(),
descriptors);
break;
default:
CV_Error(cv::Error::StsBadArg, "Unknown descriptor format");
}
}
int HOG_Impl::getTotalHistSize(Size img_size) const
{
size_t block_hist_size = getBlockHistogramSize();
Size blocks_per_img = numPartsWithin(img_size, block_size_, block_stride_);
return static_cast<int>(block_hist_size * blocks_per_img.area());
}
void HOG_Impl::computeBlockHistograms(const GpuMat& img, GpuMat& block_hists)
{
cv::Size blocks_per_win = numPartsWithin(win_size_, block_size_, block_stride_);
hog::set_up_constants(nbins_, block_stride_.width, block_stride_.height, blocks_per_win.width, blocks_per_win.height);
BufferPool pool(Stream::Null());
GpuMat grad = pool.getBuffer(img.size(), CV_32FC2);
GpuMat qangle = pool.getBuffer(img.size(), CV_8UC2);
computeGradient(img, grad, qangle);
block_hists.create(1, getTotalHistSize(img.size()), CV_32FC1);
hog::compute_hists(nbins_,
block_stride_.width, block_stride_.height,
img.rows, img.cols,
grad, qangle,
(float)getWinSigma(),
block_hists.ptr<float>());
hog::normalize_hists(nbins_,
block_stride_.width, block_stride_.height,
img.rows, img.cols,
block_hists.ptr<float>(),
(float)threshold_L2hys_);
}
void HOG_Impl::computeGradient(const GpuMat& img, GpuMat& grad, GpuMat& qangle)
{
grad.create(img.size(), CV_32FC2);
qangle.create(img.size(), CV_8UC2);
float angleScale = (float)(nbins_ / CV_PI);
switch (img.type())
{
case CV_8UC1:
hog::compute_gradients_8UC1(nbins_, img.rows, img.cols, img, angleScale, grad, qangle, gamma_correction_);
break;
case CV_8UC4:
hog::compute_gradients_8UC4(nbins_, img.rows, img.cols, img, angleScale, grad, qangle, gamma_correction_);
break;
}
}
}
Ptr<cuda::HOG> cv::cuda::HOG::create(Size win_size,
Size block_size,
Size block_stride,
Size cell_size,
int nbins)
{
return makePtr<HOG_Impl>(win_size, block_size, block_stride, cell_size, nbins);
}
namespace
{
static Mat getPeopleDetector48x96()
{
static float detector[] = {
0.294350f, -0.098796f, -0.129522f, 0.078753f, 0.387527f, 0.261529f,
0.145939f, 0.061520f, 0.328699f, 0.227148f, -0.066467f, -0.086723f,
0.047559f, 0.106714f, 0.037897f, 0.111461f, -0.024406f, 0.304769f,
0.254676f, -0.069235f, 0.082566f, 0.147260f, 0.326969f, 0.148888f,
0.055270f, -0.087985f, 0.261720f, 0.143442f, 0.026812f, 0.238212f,
0.194020f, 0.056341f, -0.025854f, -0.034444f, -0.156631f, 0.205174f,
0.089008f, -0.139811f, -0.100147f, -0.037830f, -0.029230f, -0.055641f,
0.033248f, -0.016512f, 0.155244f, 0.247315f, -0.124694f, -0.048414f,
-0.062219f, 0.193683f, 0.004574f, 0.055089f, 0.093565f, 0.167712f,
0.167581f, 0.018895f, 0.215258f, 0.122609f, 0.090520f, -0.067219f,
-0.049029f, -0.099615f, 0.241804f, -0.094893f, -0.176248f, 0.001727f,
-0.134473f, 0.104442f, 0.050942f, 0.081165f, 0.072156f, 0.121646f,
0.002656f, -0.297974f, -0.133587f, -0.060121f, -0.092515f, -0.048974f,
-0.084754f, -0.180111f, -0.038590f, 0.086283f, -0.134636f, -0.107249f,
0.132890f, 0.141556f, 0.249425f, 0.130273f, -0.030031f, 0.073212f,
-0.008155f, 0.019931f, 0.071688f, 0.000300f, -0.019525f, -0.021725f,
-0.040993f, -0.086841f, 0.070124f, 0.240033f, 0.265350f, 0.043208f,
0.166754f, 0.091453f, 0.060916f, -0.036972f, -0.091043f, 0.079873f,
0.219781f, 0.158102f, -0.140618f, -0.043016f, 0.124802f, 0.093668f,
0.103208f, 0.094872f, 0.080541f, 0.137711f, 0.160566f, -0.169231f,
0.013983f, 0.309508f, -0.004217f, -0.057200f, -0.064489f, 0.014066f,
0.361009f, 0.251328f, -0.080983f, -0.044183f, 0.061436f, -0.037381f,
-0.078786f, 0.030993f, 0.066314f, 0.037683f, 0.152325f, -0.091683f,
0.070203f, 0.217856f, 0.036435f, -0.076462f, 0.006254f, -0.094431f,
0.154829f, -0.023038f, -0.196961f, -0.024594f, 0.178465f, -0.050139f,
-0.045932f, -0.000965f, 0.109112f, 0.046165f, -0.159373f, -0.008713f,
0.041307f, 0.097129f, -0.057211f, -0.064599f, 0.077165f, 0.176167f,
0.138322f, 0.065753f, -0.104950f, 0.017933f, 0.136255f, -0.011598f,
0.047007f, 0.080550f, 0.068619f, 0.084661f, -0.035493f, -0.091314f,
-0.041411f, 0.060971f, -0.101912f, -0.079870f, -0.085977f, -0.022686f,
0.079788f, -0.098064f, -0.054603f, 0.040383f, 0.300794f, 0.128603f,
0.094844f, 0.047407f, 0.101825f, 0.061832f, -0.162160f, -0.204553f,
-0.035165f, 0.101450f, -0.016641f, -0.027140f, -0.134392f, -0.008743f,
0.102331f, 0.114853f, 0.009644f, 0.062823f, 0.237339f, 0.167843f,
0.053066f, -0.012592f, 0.043158f, 0.002305f, 0.065001f, -0.038929f,
-0.020356f, 0.152343f, 0.043469f, -0.029967f, -0.042948f, 0.032481f,
0.068488f, -0.110840f, -0.111083f, 0.111980f, -0.002072f, -0.005562f,
0.082926f, 0.006635f, -0.108153f, 0.024242f, -0.086464f, -0.189884f,
-0.017492f, 0.191456f, -0.007683f, -0.128769f, -0.038017f, -0.132380f,
0.091926f, 0.079696f, -0.106728f, -0.007656f, 0.172744f, 0.011576f,
0.009883f, 0.083258f, -0.026516f, 0.145534f, 0.153924f, -0.130290f,
-0.108945f, 0.124490f, -0.003186f, -0.100485f, 0.015024f, -0.060512f,
0.026288f, -0.086713f, -0.169012f, 0.076517f, 0.215778f, 0.043701f,
-0.131642f, -0.012585f, -0.045181f, -0.118183f, -0.241544f, -0.167293f,
-0.020107f, -0.019917f, -0.101827f, -0.107096f, -0.010503f, 0.044938f,
0.189680f, 0.217119f, -0.046086f, 0.044508f, 0.199716f, -0.036004f,
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0.083224f, 0.099533f, -0.039432f, -0.138880f, 0.005482f, -0.024120f,
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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 Mat(1, static_cast<int>(sizeof(detector)/sizeof(detector[0])), CV_32FC1, detector);
}
Mat getPeopleDetector64x128()
{
static 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,
-3.55954492e-003f, 0.07818956f, 0.07730991f, 0.07890715f, 0.06222893f,
0.09001380f, -0.03574381f, 0.03414327f, 0.05677258f, -0.04773581f,
0.03746637f, -0.03521175f, 0.06955440f, -0.03849038f, 0.01052293f,
0.01736112f, 0.10867710f, 0.08748853f, 3.29739624e-003f, 0.10907028f,
0.07913758f, 0.10393070f, 0.02091867f, 0.11594022f, 0.13182420f,
0.09879354f, 0.05362710f, -0.06745391f, -7.01260753e-003f,
5.24702156e-003f, 0.03236255f, 0.01407916f, 0.02207983f, 0.02537322f,
0.04547948f, 0.07200756f, 0.03129894f, -0.06274468f, 0.02107014f,
0.06035208f, 0.08636236f, 4.53164103e-003f, 0.02193363f, 0.02309801f,
0.05568166f, -0.02645093f, 0.04448695f, 0.02837519f, 0.08975694f,
0.04461516f, 0.08975355f, 0.07514391f, 0.02306982f, 0.10410084f,
0.06368385f, 0.05943464f, 4.58420580e-003f, 0.05220337f, 0.06675851f,
0.08358569f, 0.06712101f, 0.06559004f, -0.03930482f, -9.15936660e-003f,
-0.05897915f, 0.02816453f, 0.05032348f, 0.06780671f, 0.03377650f,
-6.09417039e-004f, -0.01795146f, -0.03083684f, -0.01302475f,
-0.02972313f, 7.88706727e-003f, -0.03525961f, -2.50397739e-003f,
0.05245084f, 0.11791293f, -0.02167498f, 0.05299332f, 0.06640524f,
0.05190265f, -8.27316567e-003f, 0.03033127f, 0.05842173f,
-4.01050318e-003f, -6.25105947e-003f, 0.05862958f, -0.02465461f,
0.05546781f, -0.08228195f, -0.07234028f, 0.04640540f, -0.01308254f,
-0.02506191f, 0.03100746f, -0.04665651f, -0.04591486f, 0.02949927f,
0.06035462f, 0.02244646f, -0.01698639f, 0.01040041f, 0.01131170f,
0.05419579f, -0.02130277f, -0.04321722f, -0.03665198f, 0.01126490f,
-0.02606488f, -0.02228328f, -0.02255680f, -0.03427236f,
-7.75165204e-003f, -0.06195229f, 8.21638294e-003f, 0.09535975f,
-0.03709979f, -0.06942501f, 0.14579427f, -0.05448192f, -0.02055904f,
0.05747357f, 0.02781788f, -0.07077577f, -0.05178314f, -0.10429011f,
-0.11235505f, 0.07529039f, -0.07559302f, -0.08786739f, 0.02983843f,
0.02667585f, 0.01382199f, -0.01797496f, -0.03141199f, -0.02098101f,
0.09029204f, 0.04955018f, 0.13718739f, 0.11379953f, 1.80019124e-003f,
-0.04577610f, -1.11108483e-003f, -0.09470536f, -0.11596080f,
0.04489342f, 0.01784211f, 3.06850672e-003f, 0.10781866f,
3.36498418e-003f, -0.10842580f, -0.07436839f, -0.10535070f,
-0.01866805f, 0.16057891f, -5.07316366e-003f, -0.04295658f,
-5.90488780e-003f, 8.82003549e-003f, -0.01492646f, -0.05029279f,
-0.12875880f, 8.78831954e-004f, -0.01297184f, -0.07592774f,
-0.02668831f, -6.93787413e-004f, 0.02406698f, -0.01773298f,
-0.03855745f, -0.05877856f, 0.03259695f, 0.12826584f, 0.06292590f,
-4.10733931e-003f, 0.10996531f, 0.01332991f, 0.02088735f, 0.04037504f,
-0.05210760f, 0.07760046f, 0.06399347f, -0.05751930f, -0.10053057f,
0.07505023f, -0.02139782f, 0.01796176f, 2.34400877e-003f, -0.04208319f,
0.07355055f, 0.05093350f, -0.02996780f, -0.02219072f, 0.03355330f,
0.04418742f, -0.05580705f, -0.05037573f, -0.04548179f, 0.01379514f,
0.02150671f, -0.02194211f, -0.13682702f, 0.05464972f, 0.01608082f,
0.05309116f, 0.04701022f, 1.33690401e-003f, 0.07575664f, 0.09625306f,
8.92647635e-003f, -0.02819123f, 0.10866830f, -0.03439325f,
-0.07092371f, -0.06004780f, -0.02712298f, -7.07467366e-003f,
-0.01637020f, 0.01336790f, -0.10313606f, 0.04906582f, -0.05732445f,
-0.02731079f, 0.01042235f, -0.08340668f, 0.03686501f, 0.06108340f,
0.01322748f, -0.07809529f, 0.03774724f, -0.03413248f, -0.06096525f,
-0.04212124f, -0.07982176f, -1.25973229e-003f, -0.03045501f,
-0.01236493f, -0.06312395f, 0.04789570f, -0.04602066f, 0.08576570f,
0.02521080f, 0.02988098f, 0.10314583f, 0.07060035f, 0.04520544f,
-0.04426654f, 0.13146530f, 0.08386490f, 0.02164590f, -2.12280243e-003f,
-0.03686353f, -0.02074944f, -0.03829959f, -0.01530596f, 0.02689708f,
0.11867401f, -0.06043470f, -0.02785023f, -0.04775074f, 0.04878745f,
0.06350956f, 0.03494788f, 0.01467400f, 1.17890188e-003f, 0.04379614f,
2.03681854e-003f, -0.03958609f, -0.01072688f, 6.43705716e-003f,
0.02996500f, -0.03418507f, -0.01960307f, -0.01219154f,
-4.37000440e-003f, -0.02549453f, 0.02646318f, -0.01632513f,
6.46516960e-003f, -0.01929734f, 4.78711911e-003f, 0.04962371f,
0.03809111f, 0.07265724f, 0.05758125f, -0.03741554f, 0.01648608f,
-8.45285598e-003f, 0.03996826f, -0.08185477f, 0.02638875f,
-0.04026615f, -0.02744674f, -0.04071517f, 1.05096330e-003f,
-0.04741232f, -0.06733172f, 8.70434940e-003f, -0.02192543f,
1.35350740e-003f, -0.03056974f, -0.02975521f, -0.02887780f,
-0.01210713f, -0.04828526f, -0.09066251f, -0.09969629f, -0.03665164f,
-8.88111943e-004f, -0.06826669f, -0.01866150f, -0.03627640f,
-0.01408288f, 0.01874239f, -0.02075835f, 0.09145175f, -0.03547291f,
0.05396780f, 0.04198981f, 0.01301925f, -0.03384354f, -0.12201976f,
0.06830920f, -0.03715654f, 9.55848210e-003f, 5.05685573e-003f,
0.05659294f, 3.90764466e-003f, 0.02808490f, -0.05518097f, -0.03711621f,
-0.02835565f, -0.04420464f, -0.01031947f, 0.01883466f,
-8.49525444e-003f, -0.09419250f, -0.01269387f, -0.02133371f,
-0.10190815f, -0.07844430f, 2.43644323e-003f, -4.09610150e-003f,
0.01202551f, -0.06452291f, -0.10593818f, -0.02464746f, -0.02199699f,
-0.07401930f, 0.07285886f, 8.87513801e-004f, 9.97662079e-003f,
8.46779719e-003f, 0.03730333f, -0.02905126f, 0.03573337f, -0.04393689f,
-0.12014472f, 0.03176554f, -2.76015815e-003f, 0.10824566f, 0.05090732f,
-3.30179278e-003f, -0.05123822f, 5.04784798e-003f, -0.05664124f,
-5.99415926e-003f, -0.05341901f, -0.01221393f, 0.01291318f,
9.91760660e-003f, -7.56987557e-003f, -0.06193124f, -2.24549137e-003f,
0.01987562f, -0.02018840f, -0.06975540f, -0.06601523f, -0.03349112f,
-0.08910118f, -0.03371435f, -0.07406893f, -0.02248047f, -0.06159951f,
2.77751544e-003f, -0.05723337f, -0.04792468f, 0.07518548f,
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0.03758875f, -0.04446875f, 0.04933187f, 0.01345535f, 0.06921103f,
0.07364785f, 0.05518956f, 0.02899585f, 0.09375840f, 0.10518434f,
-0.04420241f, 0.01915282f, -3.56386811e-003f, 0.14586878f, 0.10286101f,
-0.04360626f, -0.12723237f, 0.09076386f, 0.11119842f, -0.06035013f,
0.09674817f, 0.08938243f, 0.07065924f, 0.02603180f, 5.84815582e-003f,
-0.05922065f, 0.12360309f, 3.59695964e-003f, 2.99844006e-003f,
0.03697936f, 0.02043072f, 0.04168725f, 0.01025975f, -0.01359980f,
-0.01600920f, 0.02581056f, 0.02329250f, 2.98100687e-003f, 0.01629762f,
0.06652115f, 0.05855627f, 0.01237463f, -0.01297135f, 0.01761587f,
0.05090865f, 0.06549342f, -0.04425945f, 2.43203156e-003f,
3.07327788e-003f, 0.06678630f, -0.04303836f, 0.01082393f, -0.06476044f,
0.04077786f, 0.12441979f, 0.08237778f, 0.07424165f, 0.04065890f,
0.06905543f, 0.09556347f, 0.12724875f, -0.02132082f, 0.08514154f,
-0.04175328f, -0.02666954f, 0.01897836f, 0.03317382f, 9.45465732e-003f,
-0.01238974f, -0.04242500f, -0.01419479f, -0.03545213f, -0.02440874f,
0.08684119f, 0.04212951f, 0.02462858f, -0.01104825f, -5.01706870e-003f,
0.02968982f, 0.02597476f, -0.01568939f, 0.04514892f, 0.06974549f,
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 Mat(1, static_cast<int>(sizeof(detector)/sizeof(detector[0])), CV_32FC1, detector);
}
}
#endif