/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include <stdio.h>
#include "precomp.hpp" //包含了 objdetect.hpp
#include <iterator>
#ifdef HAVE_IPP
#include "ipp.h"
#endif
/****************************************************************************************\
The code below is implementation of HOG (Histogram-of-Oriented Gradients)
descriptor and object detection, introduced by Navneet Dalal and Bill Triggs.
The computed feature vectors are compatible with the
INRIA Object Detection and Localization Toolkit
(http://pascal.inrialpes.fr/soft/olt/)
\****************************************************************************************/
namespace cv
{
size_t HOGDescriptor::getDescriptorSize() const
{
CV_Assert(blockSize.width % cellSize.width == 0 &&
blockSize.height % cellSize.height == 0);
CV_Assert((winSize.width - blockSize.width) % blockStride.width == 0 &&
(winSize.height - blockSize.height) % blockStride.height == 0 );
return (size_t)nbins*
(blockSize.width/cellSize.width)*
(blockSize.height/cellSize.height)*
((winSize.width - blockSize.width)/blockStride.width + 1)*
((winSize.height - blockSize.height)/blockStride.height + 1);//描述向量總長度
}
double HOGDescriptor::getWinSigma() const
{
return winSigma >= 0 ? winSigma : (blockSize.width + blockSize.height)/8.; //默認-1
}
bool HOGDescriptor::checkDetectorSize() const
{
size_t detectorSize = svmDetector.size(), descriptorSize = getDescriptorSize();
return detectorSize == 0 ||
detectorSize == descriptorSize ||
detectorSize == descriptorSize + 1;
}
void HOGDescriptor::setSVMDetector(InputArray _svmDetector)
{
_svmDetector.getMat().convertTo(svmDetector, CV_32F);
CV_Assert( checkDetectorSize() );
}
#define CV_TYPE_NAME_HOG_DESCRIPTOR "opencv-object-detector-hog"
bool HOGDescriptor::read(FileNode& obj)
{
if( !obj.isMap() )
return false;
FileNodeIterator it = obj["winSize"].begin();
it >> winSize.width >> winSize.height;
it = obj["blockSize"].begin();
it >> blockSize.width >> blockSize.height;
it = obj["blockStride"].begin();
it >> blockStride.width >> blockStride.height;
it = obj["cellSize"].begin();
it >> cellSize.width >> cellSize.height;
obj["nbins"] >> nbins;
obj["derivAperture"] >> derivAperture;
obj["winSigma"] >> winSigma;
obj["histogramNormType"] >> histogramNormType;
obj["L2HysThreshold"] >> L2HysThreshold;
obj["gammaCorrection"] >> gammaCorrection;
obj["nlevels"] >> nlevels;
FileNode vecNode = obj["SVMDetector"];
if( vecNode.isSeq() )
{
vecNode >> svmDetector;
CV_Assert(checkDetectorSize());
}
return true;
}
void HOGDescriptor::write(FileStorage& fs, const String& objName) const
{
if( !objName.empty() )
fs << objName;
fs << "{" CV_TYPE_NAME_HOG_DESCRIPTOR
<< "winSize" << winSize
<< "blockSize" << blockSize
<< "blockStride" << blockStride
<< "cellSize" << cellSize
<< "nbins" << nbins
<< "derivAperture" << derivAperture
<< "winSigma" << getWinSigma()
<< "histogramNormType" << histogramNormType
<< "L2HysThreshold" << L2HysThreshold
<< "gammaCorrection" << gammaCorrection
<< "nlevels" << nlevels;
if( !svmDetector.empty() )
fs << "SVMDetector" << svmDetector;
fs << "}";
}
bool HOGDescriptor::load(const String& filename, const String& objname)
{
FileStorage fs(filename, FileStorage::READ);
FileNode obj = !objname.empty() ? fs[objname] : fs.getFirstTopLevelNode();
return read(obj);
}
void HOGDescriptor::save(const String& filename, const String& objName) const
{
FileStorage fs(filename, FileStorage::WRITE);
write(fs, !objName.empty() ? objName : FileStorage::getDefaultObjectName(filename));
}
void HOGDescriptor::copyTo(HOGDescriptor& c) const
{
c.winSize = winSize;
c.blockSize = blockSize;
c.blockStride = blockStride;
c.cellSize = cellSize;
c.nbins = nbins;
c.derivAperture = derivAperture;
c.winSigma = winSigma;
c.histogramNormType = histogramNormType;
c.L2HysThreshold = L2HysThreshold;
c.gammaCorrection = gammaCorrection;
c.svmDetector = svmDetector;
c.nlevels = nlevels;
}
//返回 grad：梯度的模在與梯度方向相鄰的兩個bin的插值值，qangle：與梯度方向相鄰的兩個bin的編號
void HOGDescriptor::computeGradient(const Mat& img, Mat& grad, Mat& qangle,
Size paddingTL, Size paddingBR) const
{
CV_Assert( img.type() == CV_8U || img.type() == CV_8UC3 );
Size gradsize(img.cols + paddingTL.width + paddingBR.width,
img.rows + paddingTL.height + paddingBR.height);
grad.create(gradsize, CV_32FC2); // <magnitude*(1-alpha), magnitude*alpha>，與該點梯度方向相鄰兩個bin的梯度模值，由該點線性插值得到
qangle.create(gradsize, CV_8UC2); // [0..nbins-1] - quantized gradient orientation，與該點梯度方向相鄰兩個bin的編號
Size wholeSize;
Point roiofs;
img.locateROI(wholeSize, roiofs); //img如果是一個大圖像IMG的Region of interesting,那麼IMG和img共享內存
//比如IMG(120x120),img取自IMG的一部分TL座標（10,10），BR座標（109,109）那麼尺寸爲（100x100）
//這個函數就返回父矩陣IMG的size（120x120），以及img在IMG中的座標偏移（roiofs.x=10,roiofs.y=10）
/*
Locates the matrix header within a parent matrix.
wholeSize – Output parameter that contains the size of the whole matrix containing *this as a part
ofs – Output parameter that contains an offset of *this inside the whole matrix.
*/
int i, x, y;
int cn = img.channels();
Mat_<float> _lut(1, 256); //gamma 校正Look up table,Mat_ 簡化版的 Mat,元素訪問直接 用（x,y），無需 .at,但是速度是一樣的
const float* lut = &_lut(0,0); //只能讀
if( gammaCorrection )
for( i = 0; i < 256; i++ )
_lut(0,i) = std::sqrt((float)i); //gammma 校正 r=0.5,暗區對比度提高，亮區對比度下降
else
for( i = 0; i < 256; i++ )
_lut(0,i) = (float)i;
AutoBuffer<int> mapbuf(gradsize.width + gradsize.height + 4); //自動buffer，就不需要我們malloc，free
int* xmap = (int*)mapbuf + 1;
int* ymap = xmap + gradsize.width + 2;
const int borderType = (int)BORDER_REFLECT_101;
//一種很奇怪的插值方式，擴展出來的邊緣用原圖像中的像素值，並沒有真正擴展存儲空間
//比如說原圖爲 100x100，現在要訪問（-10，-10）的值，但是內存裏面不不存在這個值，這種插值方法就是在原圖像中找個像素點（比如（5,6））的值作爲（-10,-10）的值
//也就是將擴展後的座標範圍比如（120x120）映射到（100x100）。x,y座標分別映射，映射表存在xmap,ymap。上面的例子中xmap[-10]=5,ymap[-10]=6
for( x = -1; x < gradsize.width + 1; x++ )
xmap[x] = borderInterpolate(x - paddingTL.width + roiofs.x,wholeSize.width, borderType) - roiofs.x;
for( y = -1; y < gradsize.height + 1; y++ )
ymap[y] = borderInterpolate(y - paddingTL.height + roiofs.y,wholeSize.height, borderType) - roiofs.y;
// x- & y- derivatives for the whole row
int width = gradsize.width;
AutoBuffer<float> _dbuf(width*4);
float* dbuf = _dbuf;
Mat Dx(1, width, CV_32F, dbuf);
Mat Dy(1, width, CV_32F, dbuf + width);
Mat Mag(1, width, CV_32F, dbuf + width*2);
Mat Angle(1, width, CV_32F, dbuf + width*3);
int _nbins = nbins;
float angleScale = (float)(_nbins/CV_PI); //算某一弧度，對應落在哪一個bin的scale
#ifdef HAVE_IPP //intel的ipp庫，優化
Mat lutimg(img.rows,img.cols,CV_MAKETYPE(CV_32F,cn)); //cn ,爲1/3，對於類型 CV_32FC1、CV_32FC3
Mat hidxs(1, width, CV_32F);
Ipp32f* pHidxs = (Ipp32f*)hidxs.data;
Ipp32f* pAngles = (Ipp32f*)Angle.data;
IppiSize roiSize;
roiSize.width = img.cols;
roiSize.height = img.rows;
//對原始圖像，進行gamma校正，結果保存在 imglutPtr
for( y = 0; y < roiSize.height; y++ )
{
const uchar* imgPtr = img.data + y*img.step;
float* imglutPtr = (float*)(lutimg.data + y*lutimg.step);
for( x = 0; x < roiSize.width*cn; x++ )
{
imglutPtr[x] = lut[imgPtr[x]]; //查表 gamma校正
}
}
#endif
//好長的循環體，計算了四個梯度的四個量 Dx，Dy, Angle,Mag,最終是保存了Angle,Mag兩個量給後續的工作用
for( y = 0; y < gradsize.height; y++ )
{
//行指針(加上了補丁)
#ifdef HAVE_IPP
const float* imgPtr = (float*)(lutimg.data + lutimg.step*ymap[y]);
const float* prevPtr = (float*)(lutimg.data + lutimg.step*ymap[y-1]);
const float* nextPtr = (float*)(lutimg.data + lutimg.step*ymap[y+1]);
#else
const uchar* imgPtr = img.data + img.step*ymap[y];
const uchar* prevPtr = img.data + img.step*ymap[y-1];
const uchar* nextPtr = img.data + img.step*ymap[y+1];
#endif
float* gradPtr = (float*)grad.ptr(y); //Returns a pointer to the specified matrix row.
uchar* qanglePtr = (uchar*)qangle.ptr(y);
//計算 水平和垂直梯度 保存在 dbuf 的前兩段
if( cn == 1 )
{
for( x = 0; x < width; x++ )
{
int x1 = xmap[x];
#ifdef HAVE_IPP
dbuf[x] = (float)(imgPtr[xmap[x+1]] - imgPtr[xmap[x-1]]); //水平微分模板 [-1 0 1]
dbuf[width + x] = (float)(nextPtr[x1] - prevPtr[x1]); //垂直微分模板 [-1 0 1]'
#else
dbuf[x] = (float)(lut[imgPtr[xmap[x+1]]] - lut[imgPtr[xmap[x-1]]]); //dbuf length: width*4
dbuf[width + x] = (float)(lut[nextPtr[x1]] - lut[prevPtr[x1]]); //使用了IPP優化，就已經gamm校正了，這裏是先gamm校正然後在計算梯度
#endif
}
}
else ////取B,G,R通道中梯度模最大的梯度作爲該點的梯度，
{
for( x = 0; x < width; x++ )
{
int x1 = xmap[x]*3; //height*width*element,element:8UC3/32FC3
float dx0, dy0, dx, dy, mag0, mag;
#ifdef HAVE_IPP
const float* p2 = imgPtr + xmap[x+1]*3;
const float* p0 = imgPtr + xmap[x-1]*3;
//R通道的梯度
dx0 = p2[2] - p0[2];
dy0 = nextPtr[x1+2] - prevPtr[x1+2];
mag0 = dx0*dx0 + dy0*dy0;
//G通道的梯度
dx = p2[1] - p0[1];
dy = nextPtr[x1+1] - prevPtr[x1+1];
mag = dx*dx + dy*dy;
if( mag0 < mag ) //取G,R通道中梯度模最大的
{
dx0 = dx;
dy0 = dy;
mag0 = mag;
}
//B通道的梯度
dx = p2[0] - p0[0];
dy = nextPtr[x1] - prevPtr[x1];
mag = dx*dx + dy*dy;
#else
const uchar* p2 = imgPtr + xmap[x+1]*3;
const uchar* p0 = imgPtr + xmap[x-1]*3;
dx0 = lut[p2[2]] - lut[p0[2]];
dy0 = lut[nextPtr[x1+2]] - lut[prevPtr[x1+2]];
mag0 = dx0*dx0 + dy0*dy0;
dx = lut[p2[1]] - lut[p0[1]];
dy = lut[nextPtr[x1+1]] - lut[prevPtr[x1+1]];
mag = dx*dx + dy*dy;
if( mag0 < mag )
{
dx0 = dx;
dy0 = dy;
mag0 = mag;
}
dx = lut[p2[0]] - lut[p0[0]];
dy = lut[nextPtr[x1]] - lut[prevPtr[x1]];
mag = dx*dx + dy*dy;
#endif
if( mag0 < mag ) //取B,G,R通道中梯度模最大的
{
dx0 = dx;
dy0 = dy;
mag0 = mag;
}
dbuf[x] = dx0;
dbuf[x+width] = dy0;
}
}
#ifdef HAVE_IPP
ippsCartToPolar_32f((const Ipp32f*)Dx.data, (const Ipp32f*)Dy.data, (Ipp32f*)Mag.data, pAngles, width);
for( x = 0; x < width; x++ )
{
if(pAngles[x] < 0.f)
pAngles[x] += (Ipp32f)(CV_PI*2.);
}
ippsNormalize_32f(pAngles, pAngles, width, 0.5f/angleScale, 1.f/angleScale);
ippsFloor_32f(pAngles,(Ipp32f*)hidxs.data,width);
ippsSub_32f_I((Ipp32f*)hidxs.data,pAngles,width);
ippsMul_32f_I((Ipp32f*)Mag.data,pAngles,width);
ippsSub_32f_I(pAngles,(Ipp32f*)Mag.data,width);
ippsRealToCplx_32f((Ipp32f*)Mag.data,pAngles,(Ipp32fc*)gradPtr,width);
#else
//計算梯度的模和角度，默認結果爲弧度
cartToPolar( Dx, Dy, Mag, Angle, false ); //Calculates the magnitude and angle of 2D vectors. angle(I) = atan2(y(I); x(I))
#endif
for( x = 0; x < width; x++ )
{
#ifdef HAVE_IPP
int hidx = (int)pHidxs[x];
#else
//保存該梯度方向在左右相鄰的bin的模，本來只有一個模何來的兩個？插值！
//線性插值，比如某點算出來應該屬於 bin 7.6,但是我們的bin都是整數的，四捨五入，把他劃分到bin 8又太粗糙了
//那就按該點到bin7,bin8的距離分配，這樣部分屬於8，部分屬於7。
float mag = dbuf[x+width*2], angle = dbuf[x+width*3]*angleScale - 0.5f; // 每一格 pi/9, 那現在算 t落在哪一格自然是 t/(pi/9)
int hidx = cvFloor(angle); //向下取整
angle -= hidx;
gradPtr[x*2] = mag*(1.f - angle); //binx的大小是梯度方向和模的共同體現
gradPtr[x*2+1] = mag*angle;
#endif
if( hidx < 0 )
hidx += _nbins;
else if( hidx >= _nbins )
hidx -= _nbins;
assert( (unsigned)hidx < (unsigned)_nbins );
//保存與該梯度方向相鄰的左右兩個bin編號
qanglePtr[x*2] = (uchar)hidx; //也是向下取整
hidx++;
hidx &= hidx < _nbins ? -1 : 0; // hidx &= ( (hidx < _nbins ) ? -1 : 0;)，如果hidx < nbins good;如果超過了，就算子bin 0 ；-1的補碼是全1
qanglePtr[x*2+1] = (uchar)hidx;
}
}
}
struct HOGCache
{
struct BlockData
{
BlockData() : histOfs(0), imgOffset() {}
int histOfs;
Point imgOffset;
};
struct PixData
{
size_t gradOfs, qangleOfs;
int histOfs[4];
float histWeights[4];
float gradWeight;
};
HOGCache();
HOGCache(const HOGDescriptor* descriptor,
const Mat& img, Size paddingTL, Size paddingBR,
bool useCache, Size cacheStride);
virtual ~HOGCache() {};
virtual void init(const HOGDescriptor* descriptor,
const Mat& img, Size paddingTL, Size paddingBR,
bool useCache, Size cacheStride);
Size windowsInImage(Size imageSize, Size winStride) const;
Rect getWindow(Size imageSize, Size winStride, int idx) const;
const float* getBlock(Point pt, float* buf);
virtual void normalizeBlockHistogram(float* histogram) const;
vector<PixData> pixData;
vector<BlockData> blockData;
bool useCache;
vector<int> ymaxCached;
Size winSize, cacheStride;
Size nblocks, ncells;
int blockHistogramSize;
int count1, count2, count4;
Point imgoffset;
Mat_<float> blockCache;
Mat_<uchar> blockCacheFlags;
Mat grad, qangle;
const HOGDescriptor* descriptor;
};
HOGCache::HOGCache()
{
useCache = false;
blockHistogramSize = count1 = count2 = count4 = 0;
descriptor = 0;
}
HOGCache::HOGCache(const HOGDescriptor* _descriptor,
const Mat& _img, Size _paddingTL, Size _paddingBR,
bool _useCache, Size _cacheStride)
{
init(_descriptor, _img, _paddingTL, _paddingBR, _useCache, _cacheStride);
}
void HOGCache::init(const HOGDescriptor* _descriptor,
const Mat& _img, Size _paddingTL, Size _paddingBR,
bool _useCache, Size _cacheStride)
{
descriptor = _descriptor;
cacheStride = _cacheStride;
useCache = _useCache;
/*--------------------------------------計算梯度----------------------------------------------*/
//返回值
//size：img.cols + paddingTL.width + paddingBR.width,img.rows + paddingTL.height + paddingBR.height,類型 CV_32FC2
//grad：梯度的模在與梯度方向相鄰的兩個bin的插值值
//qangle：與梯度方向相鄰的兩個bin的編號
descriptor->computeGradient(_img, grad, qangle, _paddingTL, _paddingBR);
imgoffset = _paddingTL;
winSize = descriptor->winSize; //默認值：winSize(64,128)
Size blockSize = descriptor->blockSize;//blockSize(16,16)
Size blockStride = descriptor->blockStride;//lockStride(8,8)
Size cellSize = descriptor->cellSize;//cellSize(8,8)
int i, j, nbins = descriptor->nbins;//nbins(9)
int rawBlockSize = blockSize.width*blockSize.height;
nblocks = Size((winSize.width - blockSize.width)/blockStride.width + 1,
(winSize.height - blockSize.height)/blockStride.height + 1);
//這種算法非常直觀，也許你會覺得可以和下面一樣直接除，但是當(winSize.height - blockSize.height) % blockStride.height 不爲0時，就不一定
//比如 blockSize=4,blockStride=3,winSize.width =9,那麼直接除9/3=3，但是只能有兩個block, 4|3|2,只能移動一次
ncells = Size(blockSize.width/cellSize.width, blockSize.height/cellSize.height);
blockHistogramSize = ncells.width*ncells.height*nbins;//默認2*2*9
if( useCache ) //
{
Size cacheSize((grad.cols - blockSize.width)/cacheStride.width+1,
(winSize.height/cacheStride.height)+1);
blockCache.create(cacheSize.height, cacheSize.width*blockHistogramSize);
blockCacheFlags.create(cacheSize);
size_t cacheRows = blockCache.rows;
ymaxCached.resize(cacheRows);
for(size_t ii = 0; ii < cacheRows; ii++ )
ymaxCached[ii] = -1;
}
Mat_<float> weights(blockSize);//16*16 高斯模板
float sigma = (float)descriptor->getWinSigma();//-1
float scale = 1.f/(sigma*sigma*2);
for(i = 0; i < blockSize.height; i++)
for(j = 0; j < blockSize.width; j++)
{
float di = i - blockSize.height*0.5f;
float dj = j - blockSize.width*0.5f;//中心
weights(i,j) = std::exp(-(di*di + dj*dj)*scale);//weights(i,j)=exp(-(distance/sigma)^2)
}
blockData.resize(nblocks.width*nblocks.height);
pixData.resize(rawBlockSize*3);// vector::resize(newsize,value),不是Mat::resize,16*16*3個結構體
/*
vector<PixData> pixData;
struct PixData{
size_t gradOfs, qangleOfs;
int histOfs[4];
float histWeights[4];
float gradWeight;
};
*/
// Initialize 2 lookup tables, pixData & blockData.
// Here is why:
//
// The detection algorithm runs in 4 nested loops (at each pyramid layer):
// loop over the windows within the input image
// loop over the blocks within each window
// loop over the cells within each block
// loop over the pixels in each cell
//
// As each of the loops runs over a 2-dimensional array,
// we could get 8(!) nested loops in total, which is very-very slow.
//
// To speed the things up, we do the following:
// 1. loop over windows is unrolled in the HOGDescriptor::{compute|detect} methods;
// inside we compute the current search window using getWindow() method.
// Yes, it involves some overhead (function call + couple of divisions),
// but it's tiny in fact.
// 2. loop over the blocks is also unrolled. Inside we use pre-computed blockData[j]
// to set up gradient and histogram pointers.
// 3. loops over cells and pixels in each cell are merged
// (since there is no overlap between cells, each pixel in the block is processed once)
// and also unrolled. Inside we use PixData[k] to access the gradient values and
// update the histogram
//
count1 = count2 = count4 = 0;
for( j = 0; j < blockSize.width; j++ )//16,先水平，再垂直
for( i = 0; i < blockSize.height; i++ )//16
{
PixData* data = 0;
float cellX = (j+0.5f)/cellSize.width - 0.5f; //這是幹什麼 ？？？
float cellY = (i+0.5f)/cellSize.height - 0.5f;
int icellX0 = cvFloor(cellX); //-1（j=0..3）,0(j=4..11),1(j=12..15)
int icellY0 = cvFloor(cellY);
int icellX1 = icellX0 + 1, icellY1 = icellY0 + 1;//0 1 2
cellX -= icellX0;
cellY -= icellY0;
if( (unsigned)icellX0 < (unsigned)ncells.width && // icellX0 == 0
(unsigned)icellX1 < (unsigned)ncells.width ) //判斷條件時特別小心，int 轉成了 unsigned,(unsigned)(-1)=2^32-1，真對這作者無語
{
// icellX0 == 0，icellY0 == 0 對相鄰的四個cell都有貢獻，即F,J,G,K區域
if( (unsigned)icellY0 < (unsigned)ncells.height && // cellX，cellY 範圍（0,1）
(unsigned)icellY1 < (unsigned)ncells.height )
{
data = &pixData[rawBlockSize*2 + (count4++)];
data->histOfs[0] = (icellX0*ncells.height + icellY0)*nbins;//cell 0 在整個block的bin中的偏移
data->histWeights[0] = (1.f - cellX)*(1.f - cellY); //到對稱中心的“距離”即cell 3
data->histOfs[1] = (icellX1*ncells.height + icellY0)*nbins;//cell 1的偏移 2*9
data->histWeights[1] = cellX*(1.f - cellY); //到對稱中心的“距離”即 cell 2
data->histOfs[2] = (icellX0*ncells.height + icellY1)*nbins;//cell 2的偏移 1*9
data->histWeights[2] = (1.f - cellX)*cellY; //到對稱中心的“距離”即 cell 1
data->histOfs[3] = (icellX1*ncells.height + icellY1)*nbins;//cell 3的偏移3*9
data->histWeights[3] = cellX*cellY; //到對稱中心的“距離”即 cell 0
}
else // icellX0 == 0，icellY0 == -1/1，對左右相鄰的兩個cell有貢獻，即B,C,N,O
{
// cellX 範圍（0,1），cellY 範圍 （0.5,1）/（0,0.5）
data = &pixData[rawBlockSize + (count2++)];
//下部分的cellY範圍也落在（0.5,1），icellY1==icellY0 == 1
if( (unsigned)icellY0 < (unsigned)ncells.height )//icellY0 == 1
{
icellY1 = icellY0;
cellY = 1.f - cellY;
}
data->histOfs[0] = (icellX0*ncells.height + icellY1)*nbins;// 上部分0；下部分1
data->histWeights[0] = (1.f - cellX)*cellY;
data->histOfs[1] = (icellX1*ncells.height + icellY1)*nbins;// 上部分2；下部分3
data->histWeights[1] = cellX*cellY;
data->histOfs[2] = data->histOfs[3] = 0;// 均爲0
data->histWeights[2] = data->histWeights[3] = 0;
}
}
else //icellX0 == -1/1,cellX範圍（0.5,1）/（0,0.5）
{
//右部分的cellX範圍也落在（0.5,1），icellX1==icellX0 == 1
if( (unsigned)icellX0 < (unsigned)ncells.width )
{
icellX1 = icellX0;
cellX = 1.f - cellX;
}
//E,H,I,L
if( (unsigned)icellY0 < (unsigned)ncells.height &&
(unsigned)icellY1 < (unsigned)ncells.height )
{
data = &pixData[rawBlockSize + (count2++)];
data->histOfs[0] = (icellX1*ncells.height + icellY0)*nbins;//左：0，右：2*9
data->histWeights[0] = cellX*(1.f - cellY);
data->histOfs[1] = (icellX1*ncells.height + icellY1)*nbins;//左：1*9 右：3*9
data->histWeights[1] = cellX*cellY;
data->histOfs[2] = data->histOfs[3] = 0;
data->histWeights[2] = data->histWeights[3] = 0;
}
// A,D,M,P
else
{
data = &pixData[count1++];
if( (unsigned)icellY0 < (unsigned)ncells.height )
{
icellY1 = icellY0;
cellY = 1.f - cellY;
}
data->histOfs[0] = (icellX1*ncells.height + icellY1)*nbins;
data->histWeights[0] = cellX*cellY;
data->histOfs[1] = data->histOfs[2] = data->histOfs[3] = 0;
data->histWeights[1] = data->histWeights[2] = data->histWeights[3] = 0;
}
}
data->gradOfs = (grad.cols*i + j)*2; //block窗口的（0,0）位置有相對於整個圖像的偏移，此偏移爲相對於block(0,0)的偏移
data->qangleOfs = (qangle.cols*i + j)*2;//計算方式很古怪，但是你畫張圖就明白了（grad.cols*i多算的==+j少算的），實際上 block窗口的（0,0）的offset加上此offset就可以直接在grad中找到對應的梯度
data->gradWeight = weights(i,j); //該點的高斯權值，大小與到block中心的距離成反比
}
assert( count1 + count2 + count4 == rawBlockSize );//16*16
// defragment pixData,整理碎片.
//數據合併 xxx.........yyy.........zzz.........->xxxyyyzzz..................
//（.表示未賦值空間，x爲count1存儲的數據，y爲count2存儲的數據...）
for( j = 0; j < count2; j++ )
pixData[j + count1] = pixData[j + rawBlockSize];
for( j = 0; j < count4; j++ )
pixData[j + count1 + count2] = pixData[j + rawBlockSize*2];
count2 += count1;
count4 += count2;
// initialize blockData
/*
struct BlockData{
BlockData() : histOfs(0), imgOffset() {}
int histOfs;
Point imgOffset;
};
*/
for( j = 0; j < nblocks.width; j++ )
for( i = 0; i < nblocks.height; i++ )
{
BlockData& data = blockData[j*nblocks.height + i];
data.histOfs = (j*nblocks.height + i)*blockHistogramSize;
data.imgOffset = Point(j*blockStride.width,i*blockStride.height);
}
}
const float* HOGCache::getBlock(Point pt, float* buf)
{
float* blockHist = buf;
assert(descriptor != 0);
Size blockSize = descriptor->blockSize;
pt += imgoffset; //imgoffset:padingTL,先前減去pading，現在又加過來，爲嘛？？？？
CV_Assert( (unsigned)pt.x <= (unsigned)(grad.cols - blockSize.width) &&
(unsigned)pt.y <= (unsigned)(grad.rows - blockSize.height) );
if( useCache ) //默認未使用
{
CV_Assert( pt.x % cacheStride.width == 0 &&
pt.y % cacheStride.height == 0 );
Point cacheIdx(pt.x/cacheStride.width,
(pt.y/cacheStride.height) % blockCache.rows);
if( pt.y != ymaxCached[cacheIdx.y] )
{
Mat_<uchar> cacheRow = blockCacheFlags.row(cacheIdx.y);
cacheRow = (uchar)0;
ymaxCached[cacheIdx.y] = pt.y;
}
blockHist = &blockCache[cacheIdx.y][cacheIdx.x*blockHistogramSize];
uchar& computedFlag = blockCacheFlags(cacheIdx.y, cacheIdx.x);
if( computedFlag != 0 )
return blockHist;
computedFlag = (uchar)1; // set it at once, before actual computing
}
int k, C1 = count1, C2 = count2, C4 = count4;//64,128,256
const float* gradPtr = (const float*)(grad.data + grad.step*pt.y) + pt.x*2;//block(0,0)在與其梯度方向相鄰的兩個bin上的插值分量
const uchar* qanglePtr = qangle.data + qangle.step*pt.y + pt.x*2;//與block(0,0)梯度方向相鄰的兩個bin的bin編號
CV_Assert( blockHist != 0 );
#ifdef HAVE_IPP
ippsZero_32f(blockHist,blockHistogramSize);
#else
for( k = 0; k < blockHistogramSize; k++ )
blockHist[k] = 0.f;
#endif
const PixData* _pixData = &pixData[0];//pixData在init中已經計算好了，相對於block（0,0）的偏移
//ADMP
for( k = 0; k < C1; k++ )
{
const PixData& pk = _pixData[k];
const float* a = gradPtr + pk.gradOfs;//該點的梯度指針
float w = pk.gradWeight*pk.histWeights[0];
const uchar* h = qanglePtr + pk.qangleOfs;//該點的梯度編號指針
int h0 = h[0], h1 = h[1];//梯度編號
float* hist = blockHist + pk.histOfs[0];//該點的hist指針
float t0 = hist[h0] + a[0]*w;
float t1 = hist[h1] + a[1]*w;
hist[h0] = t0; hist[h1] = t1;
}
//BCEINPHL
for( ; k < C2; k++ )
{
const PixData& pk = _pixData[k];
const float* a = gradPtr + pk.gradOfs;
float w, t0, t1, a0 = a[0], a1 = a[1];
const uchar* h = qanglePtr + pk.qangleOfs;
int h0 = h[0], h1 = h[1];
float* hist = blockHist + pk.histOfs[0];
w = pk.gradWeight*pk.histWeights[0];
t0 = hist[h0] + a0*w;
t1 = hist[h1] + a1*w;
hist[h0] = t0; hist[h1] = t1;
hist = blockHist + pk.histOfs[1];
w = pk.gradWeight*pk.histWeights[1];
t0 = hist[h0] + a0*w;
t1 = hist[h1] + a1*w;
hist[h0] = t0; hist[h1] = t1;
}
//FGJK
for( ; k < C4; k++ )
{
const PixData& pk = _pixData[k];
const float* a = gradPtr + pk.gradOfs;
float w, t0, t1, a0 = a[0], a1 = a[1];
const uchar* h = qanglePtr + pk.qangleOfs;
int h0 = h[0], h1 = h[1];
float* hist = blockHist + pk.histOfs[0];
w = pk.gradWeight*pk.histWeights[0];
t0 = hist[h0] + a0*w;
t1 = hist[h1] + a1*w;
hist[h0] = t0; hist[h1] = t1;
hist = blockHist + pk.histOfs[1];
w = pk.gradWeight*pk.histWeights[1];
t0 = hist[h0] + a0*w;
t1 = hist[h1] + a1*w;
hist[h0] = t0; hist[h1] = t1;
hist = blockHist + pk.histOfs[2];
w = pk.gradWeight*pk.histWeights[2];
t0 = hist[h0] + a0*w;
t1 = hist[h1] + a1*w;
hist[h0] = t0; hist[h1] = t1;
hist = blockHist + pk.histOfs[3];
w = pk.gradWeight*pk.histWeights[3];
t0 = hist[h0] + a0*w;
t1 = hist[h1] + a1*w;
hist[h0] = t0; hist[h1] = t1;
}
normalizeBlockHistogram(blockHist);
return blockHist;
}
//L2HysThreshold：先L2歸一化，再限制所有的值的範圍（0,0.2），再重新L2歸一化
void HOGCache::normalizeBlockHistogram(float* _hist) const
{
float* hist = &_hist[0];
#ifdef HAVE_IPP
size_t sz = blockHistogramSize;
#else
size_t i, sz = blockHistogramSize;
#endif
float sum = 0;
#ifdef HAVE_IPP
ippsDotProd_32f(hist,hist,sz,&sum);
#else
for( i = 0; i < sz; i++ )
sum += hist[i]*hist[i];
#endif
float scale = 1.f/(std::sqrt(sum)+sz*0.1f), thresh = (float)descriptor->L2HysThreshold;
#ifdef HAVE_IPP
ippsMulC_32f_I(scale,hist,sz);
ippsThreshold_32f_I( hist, sz, thresh, ippCmpGreater );
ippsDotProd_32f(hist,hist,sz,&sum);
#else
for( i = 0, sum = 0; i < sz; i++ )
{
hist[i] = std::min(hist[i]*scale, thresh);
sum += hist[i]*hist[i];
}
#endif
scale = 1.f/(std::sqrt(sum)+1e-3f);
#ifdef HAVE_IPP
ippsMulC_32f_I(scale,hist,sz);
#else
for( i = 0; i < sz; i++ )
hist[i] *= scale;
#endif
}
Size HOGCache::windowsInImage(Size imageSize, Size winStride) const
{
return Size((imageSize.width - winSize.width)/winStride.width + 1,
(imageSize.height - winSize.height)/winStride.height + 1);
}
Rect HOGCache::getWindow(Size imageSize, Size winStride, int idx) const
{
int nwindowsX = (imageSize.width - winSize.width)/winStride.width + 1;
int y = idx / nwindowsX;
int x = idx - nwindowsX*y;
return Rect( x*winStride.width, y*winStride.height, winSize.width, winSize.height );
}
void HOGDescriptor::compute(const Mat& img, vector<float>& descriptors,
Size winStride, Size padding,
const vector<Point>& locations) const
{
if( winStride == Size() )
winStride = cellSize;
Size cacheStride(gcd(winStride.width, blockStride.width),
gcd(winStride.height, blockStride.height));
size_t nwindows = locations.size();
padding.width = (int)alignSize(std::max(padding.width, 0), cacheStride.width);
padding.height = (int)alignSize(std::max(padding.height, 0), cacheStride.height);
Size paddedImgSize(img.cols + padding.width*2, img.rows + padding.height*2);
HOGCache cache(this, img, padding, padding, nwindows == 0, cacheStride);
if( !nwindows )
nwindows = cache.windowsInImage(paddedImgSize, winStride).area();
const HOGCache::BlockData* blockData = &cache.blockData[0];
int nblocks = cache.nblocks.area();
int blockHistogramSize = cache.blockHistogramSize;
size_t dsize = getDescriptorSize(); //檢測窗口內描述子的總長度，即總bin數
descriptors.resize(dsize*nwindows); //整張圖片的描述子長度
for( size_t i = 0; i < nwindows; i++ )
{
float* descriptor = &descriptors[i*dsize];
Point pt0;
if( !locations.empty() )
{
pt0 = locations[i];
if( pt0.x < -padding.width || pt0.x > img.cols + padding.width - winSize.width ||
pt0.y < -padding.height || pt0.y > img.rows + padding.height - winSize.height )
continue;
}
else//默認是這種情況
{
pt0 = cache.getWindow(paddedImgSize, winStride, (int)i).tl() - Point(padding);
CV_Assert(pt0.x % cacheStride.width == 0 && pt0.y % cacheStride.height == 0);
}
for( int j = 0; j < nblocks; j++ )
{
const HOGCache::BlockData& bj = blockData[j];
Point pt = pt0 + bj.imgOffset;
float* dst = descriptor + bj.histOfs;
const float* src = cache.getBlock(pt, dst);
if( src != dst )
#ifdef HAVE_IPP
ippsCopy_32f(src,dst,blockHistogramSize);
#else
for( int k = 0; k < blockHistogramSize; k++ )
dst[k] = src[k];
#endif
}
}
}
void HOGDescriptor::detect(const Mat& img,
vector<Point>& hits, vector<double>& weights, double hitThreshold,
Size winStride, Size padding, const vector<Point>& locations) const
/*
img – Source image. CV_8UC1 and CV_8UC4 types are supported for now.
found_locations – Left-top corner points of detected objects boundaries.
hit_threshold – Threshold for the distance between features and SVM classifying plane.
win_stride – Window stride. It must be a multiple of block stride.
padding – Mock parameter to keep the CPU interface compatibility. It must be (0,0).
*/
//hog->detect(smallerImg, locations, hitsWeights, hitThreshold, winStride, padding);
//smallerImg size:(cvRound(img.cols/scale), cvRound(img.rows/scale));
{
hits.clear();
if( svmDetector.empty() )
return;
if( winStride == Size() )//未指定winStride的情況下，winStride==（8,8）
winStride = cellSize;
Size cacheStride(gcd(winStride.width, blockStride.width),
gcd(winStride.height, blockStride.height));// gcd,求最大公約數，默認結果（8,8）
size_t nwindows = locations.size(); // 默認：0
//對於我們自己設定的LTpading=BRpading=pading,進行調整使得pading的寬高與casheStride的寬高對齊，類似於4字節補充對齊
padding.width = (int)alignSize(std::max(padding.width, 0), cacheStride.width);//alignSize(m, n)，返回n的倍數中大於等於m的最小值
padding.height = (int)alignSize(std::max(padding.height, 0), cacheStride.height);
Size paddedImgSize(img.cols + padding.width*2, img.rows + padding.height*2);
/*--------------------------------------------------------------------*/
// 1.計算梯度的模，方向
// 2.預先計算好了一個block的bin基偏移、高斯權重、插值距離
HOGCache cache(this, img, padding, padding, nwindows == 0, cacheStride); //調用了，computeGradient，計算了pading後的梯度
//Note:尺度變化時，重新計算了梯度
//histOfs = (j*nblocks.height + i)*blockHistogramSize;
//imgOffset = Point(j*blockStride.width,i*blockStride.height);
if( !nwindows )
nwindows = cache.windowsInImage(paddedImgSize, winStride).area();//整個img 的檢測窗口數
const HOGCache::BlockData* blockData = &cache.blockData[0];
int nblocks = cache.nblocks.area(); //檢測窗口內的block數
int blockHistogramSize = cache.blockHistogramSize; //一個block的histogram的bin總數，2*2*9
size_t dsize = getDescriptorSize();//一個窗口的描述子總數
double rho = svmDetector.size() > dsize ? svmDetector[dsize] : 0;// > 成立的情況，即svm的 懲罰項係數 C 不爲0
vector<float> blockHist(blockHistogramSize);
for( size_t i = 0; i < nwindows; i++ )
{
Point pt0;
if( !locations.empty() )
{
pt0 = locations[i];
if( pt0.x < -padding.width || pt0.x > img.cols + padding.width - winSize.width ||
pt0.y < -padding.height || pt0.y > img.rows + padding.height - winSize.height )
continue;
}
else
{
//得到第i個檢測窗口在pading之後的圖像中的區域，這裏減去pading,後面geitblock又pt += imgoffset;
pt0 = cache.getWindow(paddedImgSize, winStride, (int)i).tl()- Point(padding);
CV_Assert(pt0.x % cacheStride.width == 0 && pt0.y % cacheStride.height == 0);
}
double s = rho;
const float* svmVec = &svmDetector[0];
#ifdef HAVE_IPP
int j;
#else
int j, k;
#endif
for( j = 0; j < nblocks; j++, svmVec += blockHistogramSize )
{
const HOGCache::BlockData& bj = blockData[j];//檢測窗口中第j個block
// .histOfs = (j*nblocks.height + i)*blockHistogramSize;
// .imgOffset = Point(j*blockStride.width,i*blockStride.height);
Point pt = pt0 + bj.imgOffset; //得到第i個檢測窗口中第j個block在pading之後的圖像中的TL座標
//得到以pt爲TL座標的block的hist（2*2*9）數據
const float* vec = cache.getBlock(pt, &blockHist[0]);
#ifdef HAVE_IPP
Ipp32f partSum;
ippsDotProd_32f(vec,svmVec,blockHistogramSize,&partSum);
s += (double)partSum;
#else
//計算到分類超平面的距離
for( k = 0; k <= blockHistogramSize - 4; k += 4 )
s += vec[k]*svmVec[k] + vec[k+1]*svmVec[k+1] +
vec[k+2]*svmVec[k+2] + vec[k+3]*svmVec[k+3];
for( ; k < blockHistogramSize; k++ )
s += vec[k]*svmVec[k];
#endif
}
if( s >= hitThreshold )
{
hits.push_back(pt0);
weights.push_back(s);
}
}
}
void HOGDescriptor::detect(const Mat& img, vector<Point>& hits, double hitThreshold,
Size winStride, Size padding, const vector<Point>& locations) const
{
vector<double> weightsV;
detect(img, hits, weightsV, hitThreshold, winStride, padding, locations);
}
class HOGInvoker : public ParallelLoopBody
{
public:
HOGInvoker( const HOGDescriptor* _hog, const Mat& _img,
double _hitThreshold, Size _winStride, Size _padding,
const double* _levelScale, std::vector<Rect> * _vec, Mutex* _mtx,
std::vector<double>* _weights=0, std::vector<double>* _scales=0 )
{
hog = _hog;
img = _img;
hitThreshold = _hitThreshold;
winStride = _winStride;
padding = _padding;
levelScale = _levelScale;
vec = _vec;
weights = _weights;
scales = _scales;
mtx = _mtx;
}
void operator()( const Range& range ) const
{
int i, i1 = range.start, i2 = range.end;
double minScale = i1 > 0 ? levelScale[i1] : i2 > 1 ? levelScale[i1+1] : std::max(img.cols, img.rows);
Size maxSz(cvCeil(img.cols/minScale), cvCeil(img.rows/minScale));
Mat smallerImgBuf(maxSz, img.type());
vector<Point> locations;
vector<double> hitsWeights;
for( i = i1; i < i2; i++ )
{
double scale = levelScale[i];
Size sz(cvRound(img.cols/scale), cvRound(img.rows/scale));//cvRound：四捨五入
Mat smallerImg(sz, img.type(), smallerImgBuf.data);
if( sz == img.size() ) //scale==1，不需要用 smallerImgBuf的空間，所以最大的內存應該是 scale==levelScale[i1+1]的情況
smallerImg = Mat(sz, img.type(), img.data, img.step);//共享數據
else
resize(img, smallerImg, sz);//dst的內存空間超過src時，dst的空間是不是並沒有縮小呢，
//也就是說是不是先釋放內存，再按照新的size重新申請,從程序上看一直霸佔原始內存空間才能起到減少內存申請釋放所耗費的時間
hog->detect(smallerImg, locations, hitsWeights, hitThreshold, winStride, padding);
Size scaledWinSize = Size(cvRound(hog->winSize.width*scale), cvRound(hog->winSize.height*scale));
mtx->lock();
for( size_t j = 0; j < locations.size(); j++ )
{
vec->push_back(Rect(cvRound(locations[j].x*scale),
cvRound(locations[j].y*scale),
scaledWinSize.width, scaledWinSize.height));//恢復爲原圖像中的位置
if (scales)
{
scales->push_back(scale);
}
}
mtx->unlock();
if (weights && (!hitsWeights.empty()))
{
mtx->lock();
for (size_t j = 0; j < locations.size(); j++)
{
weights->push_back(hitsWeights[j]);
}
mtx->unlock();
}
}
}
const HOGDescriptor* hog;
Mat img;
double hitThreshold;
Size winStride;
Size padding;
const double* levelScale;
std::vector<Rect>* vec;
std::vector<double>* weights;
std::vector<double>* scales;
Mutex* mtx;
};
void HOGDescriptor::detectMultiScale(
const Mat& img, vector<Rect>& foundLocations, vector<double>& foundWeights,
double hitThreshold, Size winStride, Size padding,
double scale0, double finalThreshold, bool useMeanshiftGrouping) const
/*
img – Source image.
foundLocations – Detected objects boundaries.
foundWeights -
hit_threshold – Threshold for the distance between features and SVM classifying plane，到分類超平面的距離，越大則要求越嚴格，一般設爲0.
win_stride – Window stride. It must be a multiple of block stride.
padding – Mock parameter to keep the CPU interface compatibility. It must be (0,0).
scale0 – Coefficient of the detection window increase.
group_threshold – Coefficient to regulate the similarity threshold（相似性閾值）. When detected, some
objects can be covered by many rectangles. 0 means not to perform groupin
*/
{
double scale = 1.;
int levels = 0;
vector<double> levelScale;
//要使檢測窗口的尺度變大有兩種方案，法一：圖像尺寸不變，增大檢測窗口的大小；法二：反過來，檢測窗口不變，縮小圖片
//這裏使用的正是第二種方法
for( levels = 0; levels < nlevels; levels++ ) //默認值：64
{
levelScale.push_back(scale);
if( cvRound(img.cols/scale) < winSize.width || // 小於64層尺度的尺度數由是由圖形的尺寸 和 scale0 決定的，
cvRound(img.rows/scale) < winSize.height || //當圖像縮放到已經小於檢測窗口時就已經不能在增加尺度了
scale0 <= 1 )
break;
scale *= scale0;
}
levels = std::max(levels, 1);
levelScale.resize(levels);
std::vector<Rect> allCandidates;
std::vector<double> tempScales;
std::vector<double> tempWeights;
std::vector<double> foundScales;
Mutex mtx;
//[begin，end)
//TBB，參考 http://blog.csdn.net/zoufeiyy/article/details/1887579
parallel_for_(Range(0, (int)levelScale.size()),
HOGInvoker(this, img, hitThreshold, winStride, padding, &levelScale[0], &allCandidates, &mtx, &tempWeights, &tempScales));
std::copy(tempScales.begin(), tempScales.end(), back_inserter(foundScales));//把tempScales的內容添加到 foundScales 後面
foundLocations.clear();
std::copy(allCandidates.begin(), allCandidates.end(), back_inserter(foundLocations));
foundWeights.clear();
std::copy(tempWeights.begin(), tempWeights.end(), back_inserter(foundWeights));
if ( useMeanshiftGrouping )
{
groupRectangles_meanshift(foundLocations, foundWeights, foundScales, finalThreshold, winSize);
}
else
{
groupRectangles(foundLocations, (int)finalThreshold, 0.2);
}
}
void HOGDescriptor::detectMultiScale(const Mat& img, vector<Rect>& foundLocations,
double hitThreshold, Size winStride, Size padding,
double scale0, double finalThreshold, bool useMeanshiftGrouping) const
{
vector<double> foundWeights;
detectMultiScale(img, foundLocations, foundWeights, hitThreshold, winStride,
padding, scale0, finalThreshold, useMeanshiftGrouping);
}
typedef RTTIImpl<HOGDescriptor> HOGRTTI;
CvType hog_type( CV_TYPE_NAME_HOG_DESCRIPTOR, HOGRTTI::isInstance,
HOGRTTI::release, HOGRTTI::read, HOGRTTI::write, HOGRTTI::clone);
vector<float> HOGDescriptor::getDefaultPeopleDetector()
{
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,
-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,
2.77279224e-003f, 0.04211938f, 0.03100502f, 0.05278448f, 0.03954679f,
-0.03006846f, -0.03851741f, -0.02792403f, -0.02875333f, 0.01531280f,
0.02186953f, -0.01989829f, 2.50679464e-003f, -0.10258728f,
-0.04785743f, -0.02887216f, 3.85063468e-003f, 0.01112236f,
8.29218887e-003f, -0.04822981f, -0.04503597f, -0.03713100f,
-0.06988008f, -0.11002295f, -2.69209221e-003f, 1.85383670e-003f,
-0.05921049f, -0.06105053f, -0.08458050f, -0.04527602f,
8.90329306e-004f, -0.05875023f, -2.68602883e-003f, -0.01591195f,
0.03631859f, 0.05493166f, 0.07300330f, 5.53333294e-003f, 0.06400407f,
0.01847740f, -5.76280477e-003f, -0.03210877f, 4.25160583e-003f,
0.01166520f, -1.44864211e-003f, 0.02253744f, -0.03367080f, 0.06983195f,
-4.22323542e-003f, -8.89401045e-003f, -0.07943393f, 0.05199728f,
0.06065201f, 0.04133492f, 1.44032843e-003f, -0.09585235f, -0.03964731f,
0.04232114f, 0.01750465f, -0.04487902f, -7.59733608e-003f, 0.02011171f,
0.04673622f, 0.09011173f, -0.07869188f, -0.04682482f, -0.05080139f,
-3.99383716e-003f, -0.05346331f, 0.01085723f, -0.03599333f,
-0.07097908f, 0.03551549f, 0.02680387f, 0.03471529f, 0.01790393f,
0.05471273f, 9.62048303e-003f, -0.03180215f, 0.05864431f, 0.02330614f,
0.01633144f, -0.05616681f, -0.10245429f, -0.08302189f, 0.07291322f,
-0.01972590f, -0.02619633f, -0.02485327f, -0.04627592f,
1.48853404e-003f, 0.05514185f, -0.01270860f, -0.01948900f, 0.06373586f,
0.05002292f, -0.03009798f, 8.76216311e-003f, -0.02474238f,
-0.05504891f, 1.74034527e-003f, -0.03333667f, 0.01524987f, 0.11663762f,
-1.32344989e-003f, -0.06608453f, 0.05687166f, -6.89525274e-004f,
-0.04402352f, 0.09450210f, -0.04222684f, -0.05360983f, 0.01779531f,
0.02561388f, -0.11075410f, -8.77790991e-003f, -0.01099504f,
-0.10380266f, 0.03103457f, -0.02105741f, -0.07371717f, 0.05146710f,
0.10581432f, -0.08617968f, -0.02892107f, 0.01092199f, 0.14551543f,
-2.24320893e-003f, -0.05818033f, -0.07390742f, 0.05701261f,
0.12937020f, -0.04986651f, 0.10182415f, 0.05028650f, 0.12515625f,
0.09175041f, 0.06404983f, 0.01523394f, 0.09460562f, 0.06106631f,
-0.14266998f, -0.02926703f, 0.02762171f, 0.02164151f,
-9.58488265e-004f, -0.04231362f, -0.09866509f, 0.04322244f,
0.05872034f, -0.04838847f, 0.06319253f, 0.02443798f, -0.03606876f,
9.38737206e-003f, 0.04289991f, -0.01027411f, 0.08156885f, 0.08751175f,
-0.13191354f, 8.16054735e-003f, -0.01452161f, 0.02952677f, 0.03615945f,
-2.09128903e-003f, 0.02246693f, 0.09623287f, 0.09412123f, -0.02924758f,
-0.07815186f, -0.02203079f, -2.02566991e-003f, 0.01094733f,
-0.01442332f, 0.02838561f, 0.11882371f, 7.28798332e-003f, -0.10345965f,
0.07561217f, -0.02049661f, 4.44177445e-003f, 0.01609347f, -0.04893158f,
-0.08758243f, -7.67420698e-003f, 0.08862378f, 0.06098121f, 0.06565887f,
7.32981879e-003f, 0.03558407f, -0.03874352f, -0.02490055f,
-0.06771075f, 0.09939223f, -0.01066077f, 0.01382995f, -0.07289080f,
7.47184316e-003f, 0.10621431f, -0.02878659f, 0.02383525f, -0.03274646f,
0.02137008f, 0.03837290f, 0.02450992f, -0.04296818f, -0.02895143f,
0.05327370f, 0.01499020f, 0.04998732f, 0.12938657f, 0.09391870f,
0.04292390f, -0.03359194f, -0.06809492f, 0.01125796f, 0.17290455f,
-0.03430733f, -0.06255233f, -0.01813114f, 0.11726857f, -0.06127599f,
-0.08677909f, -0.03429872f, 0.04684938f, 0.08161420f, 0.03538774f,
0.01833884f, 0.11321855f, 0.03261845f, -0.04826299f, 0.01752407f,
-0.01796414f, -0.10464549f, -3.30041884e-003f, 2.29343961e-004f,
0.01457292f, -0.02132982f, -0.02602923f, -9.87351313e-003f,
0.04273872f, -0.02103316f, -0.07994065f, 0.02614958f, -0.02111666f,
-0.06964913f, -0.13453490f, -0.06861878f, -6.09341264e-003f,
0.08251446f, 0.15612499f, 2.46531400e-003f, 8.88424646e-003f,
-0.04152999f, 0.02054853f, 0.05277953f, -0.03087788f, 0.02817579f,
0.13939077f, 0.07641046f, -0.03627627f, -0.03015098f, -0.04041540f,
-0.01360690f, -0.06227205f, -0.02738223f, 0.13577610f, 0.15235767f,
-0.05392922f, -0.11175954f, 0.02157129f, 0.01146481f, -0.05264937f,
-0.06595174f, -0.02749175f, 0.11812254f, 0.17404149f, -0.06137035f,
-0.11003478f, -0.01351621f, -0.01745916f, -0.08577441f, -0.04469909f,
-0.06106115f, 0.10559758f, 0.20806813f, -0.09174948f, 7.09621934e-004f,
0.03579374f, 0.07215115f, 0.02221742f, 0.01827742f, -7.90785067e-003f,
0.01489554f, 0.14519960f, -0.06425831f, 0.02990399f, -1.80181325e-003f,
-0.01401528f, -0.04171134f, -3.70530109e-003f, -0.09090481f,
0.09520713f, 0.08845516f, -0.02651753f, -0.03016730f, 0.02562448f,
0.03563816f, -0.03817881f, 0.01433385f, 0.02256983f, 0.02872120f,
0.01001934f, -0.06332260f, 0.04338406f, 0.07001807f, -0.04705722f,
-0.07318907f, 0.02630457f, 0.03106382f, 0.06648342f, 0.10913180f,
-0.01630815f, 0.02910308f, 0.02895109f, 0.08040254f, 0.06969310f,
0.06797734f, 6.08639978e-003f, 4.16588830e-003f, 0.08926726f,
-0.03123648f, 0.02700146f, 0.01168734f, -0.01631594f, 4.61015804e-003f,
8.51359498e-003f, -0.03544224f, 0.03571994f, 4.29766066e-003f,
-0.01970077f, -8.79793242e-003f, 0.09607988f, 0.01544222f,
-0.03923707f, 0.07308586f, 0.06061262f, 1.31683104e-004f,
-7.98222050e-003f, 0.02399261f, -0.06084389f, -0.02743429f,
-0.05475523f, -0.04131311f, 0.03559756f, 0.03055342f, 0.02981433f,
0.14860515f, 0.01766787f, 0.02945257f, 0.04898238f, 0.01026922f,
0.02811658f, 0.08267091f, 0.02732154f, -0.01237693f, 0.11760156f,
0.03802063f, -0.03309754f, 5.24957618e-003f, -0.02460510f, 0.02691451f,
0.05399988f, -0.10133506f, 0.06385437f, -0.01818005f, 0.02259503f,
0.03573135f, 0.01042848f, -0.04153402f, -0.04043029f, 0.01643575f,
0.08326677f, 4.61383024e-004f, -0.05308095f, -0.08536223f,
-1.61011645e-003f, -0.02163720f, -0.01783352f, 0.03859637f,
0.08498885f, -0.01725216f, 0.08625131f, 0.10995087f, 0.09177644f,
0.08498347f, 0.07646490f, 0.05580502f, 0.02693516f, 0.09996913f,
0.09070327f, 0.06667200f, 0.05873008f, -0.02247842f, 0.07772321f,
0.12408436f, 0.12629253f, -8.41997913e-004f, 0.01477783f, 0.09165990f,
-2.98401713e-003f, -0.06466447f, -0.07057302f, 2.09516948e-004f,
0.02210209f, -0.02158809f, -0.08602506f, -0.02284836f,
4.01876355e-003f, 9.56660323e-003f, -0.02073978f, -0.04635138f,
-7.59423291e-003f, -0.01377393f, -0.04559359f, -0.13284740f,
-0.08671406f, -0.03654395f, 0.01142869f, 0.03287891f, -0.04392983f,
0.06142959f, 0.17710890f, 0.10385257f, 0.01329137f, 0.10067633f,
0.12450829f, -0.04476709f, 0.09049144f, 0.04589312f, 0.11167907f,
0.08587538f, 0.04767583f, 1.67188141e-003f, 0.02359802f, -0.03808852f,
0.03126272f, -0.01919029f, -0.05698918f, -0.02365112f, -0.06519032f,
-0.05599358f, -0.07097308f, -0.03301812f, -0.04719102f, -0.02566297f,
0.01324074f, -0.09230672f, -0.05518232f, -0.04712864f, -0.03380903f,
-0.06719479f, 0.01183908f, -0.09326738f, 0.01642865f, 0.03789867f,
-6.61567831e-003f, 0.07796386f, 0.07246574f, 0.04706347f, -0.02523437f,
-0.01696830f, -0.08068866f, 0.06030888f, 0.10527060f, -0.06611756f,
0.02977346f, 0.02621830f, 0.01913855f, -0.08479366f, -0.06322418f,
-0.13570616f, -0.07644490f, 9.31900274e-003f, -0.08095149f,
-0.10197903f, -0.05204025f, 0.01413151f, -0.07800411f, -0.01885122f,
-0.07509381f, -0.10136326f, -0.05212355f, -0.09944065f,
-1.33606605e-003f, -0.06342617f, -0.04178550f, -0.12373723f,
-0.02832736f, -0.06057501f, 0.05830070f, 0.07604282f, -0.06462587f,
8.02447461e-003f, 0.11580125f, 0.12332212f, 0.01978462f,
-2.72378162e-003f, 0.05850752f, -0.04674481f, 0.05148062f,
-2.62542837e-003f, 0.11253355f, 0.09893716f, 0.09785093f, -0.04659257f,
-0.01102429f, -0.07002308f, 0.03088913f, -0.02565549f, -0.07671449f,
3.17443861e-003f, -0.10783514f, -0.02314270f, -0.11089555f,
-0.01024768f, 0.03116021f, -0.04964825f, 0.02281825f, 5.50005678e-003f,
-0.08427856f, -0.14685495f, -0.07719755f, -0.13342668f, -0.04525511f,
-0.09914210f, 0.02588859f, 0.03469279f, 0.04664020f, 0.11688190f,
0.09647275f, 0.10857815f, -0.01448726f, 0.04299758f, -0.06763151f,
1.33257592e-003f, 0.14331576f, 0.07574340f, 0.09166205f, 0.05674926f,
0.11325553f, -0.01106494f, 0.02062161f, -0.11484840f, -0.07492137f,
-0.02864293f, -0.01275638f, -0.06946032f, -0.10101652f, -0.04113498f,
-0.02214783f, -0.01273942f, -0.07480393f, -0.10556041f, -0.07622112f,
-0.09988393f, -0.11453961f, -0.12073903f, -0.09412795f, -0.07146588f,
-0.04054537f, -0.06127083f, 0.04221122f, 0.07688113f, 0.04099256f,
0.12663734f, 0.14683802f, 0.21761774f, 0.12525328f, 0.18431792f,
-1.66402373e-003f, 2.37777247e-003f, 0.01445475f, 0.03509416f,
0.02654697f, 0.01716739f, 0.05374011f, 0.02944174f, 0.11323927f,
-0.01485456f, -0.01611330f, -1.85554172e-003f, -0.01708549f,
-0.05435753f, -0.05302101f, 0.05260378f, -0.03582945f,
-3.42867890e-004f, 1.36076682e-003f, -0.04436073f, -0.04228432f,
0.03281291f, -0.05480836f, -0.10197772f, -0.07206279f, -0.10741059f,
-0.02366946f, 0.10278475f, -2.74783419e-003f, -0.03242477f,
0.02308955f, 0.02835869f, 0.10348799f, 0.19580358f, 0.10252027f,
0.08039929f, 0.05525554f, -0.13250865f, -0.14395352f, 3.13586881e-003f,
-0.03387071f, 8.94669443e-003f, 0.05406157f, -4.97324532e-003f,
-0.01189114f, 2.82919413e-004f, -0.03901557f, -0.04898705f,
0.02164520f, -0.01382906f, -0.01850416f, 0.01869347f, -0.02450060f,
0.02291678f, 0.08196463f, 0.03309153f, -0.10629974f, 0.02473924f,
0.05344394f, -0.02404823f, -0.03243643f, -5.55244600e-003f,
-0.08009996f, 0.02811539f, 0.04235742f, 0.01859004f, 0.04902123f,
-0.01438252f, -0.01526853f, 0.02044195f, -0.05008660f, 0.04244113f,
0.07611816f, 0.04950470f, -0.06020549f, -4.26026015e-003f, 0.13133512f,
-0.01438738f, -0.01958807f, -0.04044152f, -0.12425045f,
2.84353318e-003f, -0.05042776f, -0.09121484f, 7.34345755e-003f,
0.09388847f, 0.11800314f, 4.72295098e-003f, 4.44378285e-003f,
-0.07984917f, -0.03613737f, 0.04490915f, -0.02246483f, 0.04681071f,
0.05240871f, 0.02157206f, -0.04603431f, -0.01197929f, -0.02748779f,
0.13621049f, 0.08812155f, -0.07802048f, 4.86458559e-003f, -0.01598836f,
0.01024450f, -0.03463517f, -0.02304239f, -0.08692665f, 0.06655128f,
0.05785803f, -0.12640759f, 0.02307472f, 0.07337402f, 0.07525434f,
0.04943763f, -0.02241034f, -0.09978238f, 0.14487994f, -0.06570521f,
-0.07855482f, 0.02830222f, -5.29603509e-004f, -0.04669895f,
-0.11822784f, -0.12246452f, -0.15365660f, -0.02969127f, 0.08078201f,
0.13512598f, 0.11505685f, 0.04740673f, 0.01376022f, -0.05852978f,
-0.01537809f, -0.05541119f, 0.02491065f, -0.02870786f, 0.02760978f,
0.23836176f, 0.22347429f, 0.10306466f, -0.06919070f, -0.10132039f,
-0.20198342f, -0.05040560f, 0.27163076f, 0.36987007f, 0.34540465f,
0.29095781f, 0.05649706f, 0.04125737f, 0.07505883f, -0.02737836f,
-8.43431335e-003f, 0.07368195f, 0.01653876f, -0.09402955f,
-0.09574359f, 0.01474337f, -0.07128561f, -0.03460737f, 0.11438941f,
0.13752601f, -0.06385452f, -0.06310338f, 8.19548313e-003f, 0.11622470f,
5.05133113e-003f, -0.07602754f, 0.06695660f, 0.25723928f, 0.09037900f,
0.28826267f, 0.13165380f, -0.05312614f, -0.02137198f, -0.03442232f,
-0.06255679f, 0.03899667f, 0.18391028f, 0.26016650f, 0.03374462f,
0.01860465f, 0.19077586f, 0.18160543f, 3.43634398e-003f, -0.03036782f,
0.19683038f, 0.35378191f, 0.24968483f, -0.03222649f, 0.28972381f,
0.43091634f, 0.30778357f, 0.02335266f, -0.09877399f, -6.85245218e-003f,
0.08945240f, -0.08150686f, 0.02792493f, 0.24806842f, 0.17338486f,
0.06231801f, -0.10432383f, -0.16653322f, -0.13197899f, -0.08531576f,
-0.19271527f, -0.13536365f, 0.22240199f, 0.39219588f, 0.26597717f,
-0.01231649f, 0.01016179f, 0.13379875f, 0.12018334f, -0.04852953f,
-0.07915270f, 0.07036012f, 3.87723115e-003f, -0.06126805f,
-0.15015170f, -0.11406515f, -0.08556531f, -0.07429333f, -0.16115491f,
0.13214062f, 0.25691369f, 0.05697750f, 0.06861912f, -6.02903729e-003f,
-7.94562511e-003f, 0.04799571f, 0.06695165f, -0.01926842f, 0.06206308f,
0.13450983f, -0.06381495f, -2.98370165e-003f, -0.03482971f,
7.53991678e-003f, 0.03895611f, 0.11464261f, 0.01669971f,
8.27818643e-003f, -7.49160210e-003f, -0.11712562f, -0.10650621f,
-0.10353880f, -0.04994106f, -7.65618810e-004f, 0.03023767f,
-0.04759270f, -0.07302686f, -0.05825012f, -0.13156348f, -0.10639747f,
-0.19393684f, -0.09973683f, -0.07918908f, 4.63177625e-004f,
-6.61382044e-004f, 0.15853868f, 0.08561199f, -0.07660093f,
-0.08015265f, -0.06164073f, 0.01882577f, -7.29908410e-004f,
0.06840892f, 0.03843764f, 0.20274927f, 0.22028814f, -5.26101235e-003f,
0.01452435f, -0.06331623f, 0.02865064f, 0.05673740f, 0.12171564f,
0.03837196f, 0.03555467f, -0.02662914f, -0.10280123f, -0.06526285f,
-0.11066351f, -0.08988424f, -0.10103678f, 8.10526591e-003f,
5.95238712e-003f, 0.02617721f, -0.01705742f, -0.10897956f,
-0.08004991f, -0.11271993f, -0.06185647f, -0.06103712f, 0.01597041f,
-0.05923606f, 0.09410726f, 0.22858568f, 0.03263380f, 0.06772990f,
-0.09003516f, 0.01017870f, 0.01931688f, 0.08628357f, -0.01430009f,
0.10954945f, 0.16612452f, -0.02434544f, -0.03310068f, -0.04236627f,
0.01212392f, -6.15046406e-003f, 0.06954194f, 0.03015283f, 0.01787957f,
0.02781667f, -0.05561153f, -8.96244217e-003f, -0.04971489f,
0.07510284f, 0.01775282f, 0.05889897f, -0.07981427f, 0.03647643f,
-3.73833324e-003f, -0.08894575f, -0.06429435f, -0.08068276f,
0.03567704f, -0.07131936f, -7.21910037e-003f, -0.09566668f,
0.17886090f, 0.14911725f, 0.02070032f, -0.05017120f, -0.04992622f,
0.01570143f, -0.09906903f, 0.06456193f, 0.15329507f, 0.18820767f,
0.11689861f, -0.01178513f, -0.02225163f, -0.01905318f, 0.10271224f,
-7.27029052e-003f, 0.11664233f, 0.14796902f, 0.07771893f, 0.02400013f,
-0.05361797f, -0.01972888f, 0.01376177f, 0.06740040f, -0.06525395f,
0.05726178f, -0.02404981f, -0.14018567f, -0.02074987f, -0.04621970f,
-0.04688627f, -0.01842059f, 0.07722727f, -0.04852883f, 0.01529004f,
-0.19639495f, 0.10817073f, 0.03795860f, -0.09435206f, -0.07984378f,
-0.03383440f, 0.11081333f, 0.02237366f, 0.12703256f, 0.21613893f,
0.02918790f, 4.66472283e-003f, -0.10274266f, -0.04854131f,
-3.46305710e-003f, 0.08652268f, 0.02251546f, 0.09636052f, 0.17180754f,
-0.09272388f, 4.59174305e-004f, -0.11723048f, -0.12210111f,
-0.15547538f, 0.07218186f, -0.05297846f, 0.03779940f, 0.05150875f,
-0.03802310f, 0.03870645f, -0.15250699f, -0.08696499f, -0.02021560f,
0.04118926f, -0.15177974f, 0.01577647f, 0.10249301f, 7.50041893e-003f,
0.01721806f, -0.06828983f, -0.02397596f, -0.06598977f, -0.04317593f,
-0.08064980f, 6.66632550e-003f, 0.03333484f, 0.07093620f, 0.08231064f,
-0.06577903f, -0.06698844f, -0.06984019f, -0.06508023f, -0.14145090f,
-0.02393239f, 0.06485303f, 8.83263443e-003f, 0.09251080f, -0.07557579f,
-0.05067699f, -0.09798748f, -0.06703258f, -0.14056294f, 0.03245994f,
0.12554143f, 0.01761621f, 0.12980327f, -0.04081950f, -0.11906909f,
-0.14813015f, -0.08376863f, -0.12200681f, 0.04988137f, 0.05424247f,
-3.90952639e-003f, 0.03255733f, -0.12717837f, -0.07461493f,
-0.05703964f, -0.01736189f, -0.08026433f, -0.05433894f, -0.01719359f,
0.02886275f, 0.01772653f, -0.09163518f, 3.57789593e-003f, -0.10129993f,
-0.02653764f, -0.08131415f, -0.03847986f, -7.62157550e-004f,
0.06486648f, 0.19675669f, -0.04919156f, -0.07059129f, -0.04857785f,
-0.01042383f, -0.08328653f, 0.03660302f, -0.03696846f, 0.04969259f,
0.08241162f, -0.12514858f, -0.06122676f, -0.03750202f,
6.52989605e-003f, -0.10247213f, 0.02568346f, 4.51781414e-003f,
-0.03734229f, -0.01131264f, -0.05412074f, 8.89345480e-004f,
-0.12388977f, -0.05959237f, -0.12418608f, -0.06151643f, -0.07310260f,
0.02441575f, 0.07023528f, -0.07548289f, -7.57147965e-004f,
-0.09061348f, -0.08112976f, -0.06920306f, 9.54394229e-003f,
-0.01219902f, 1.21273217e-003f, -8.88989680e-003f, -0.08309301f,
-0.04552661f, -0.10739882f, -0.05691034f, -0.13928030f, 0.09027749f,
0.15123098f, 0.03175976f, 0.17763577f, 3.29913251e-004f, 0.05151888f,
-0.09844074f, -0.09475287f, -0.08571247f, 0.16241577f, 0.19336018f,
8.57454538e-003f, 0.11474732f, -0.01493934f, 0.03352379f, -0.08966240f,
-0.02322310f, 0.02663568f, 0.05448750f, -0.03536883f, -0.07210463f,
-0.06807277f, -0.03121621f, -0.05932408f, -0.17282860f, -0.15873498f,
-0.04956378f, 0.01603377f, -0.12385946f, 0.13878587f, 0.21468069f,
0.13510075f, 0.20992437f, 0.08845878f, 0.08104013f, 0.03754176f,
0.12173114f, 0.11103114f, 0.10643122f, 0.13941477f, 0.11640384f,
0.14786847f, 0.01218238f, 0.01160753f, 0.03547940f, 0.08794311f,
-0.01695384f, -0.07692261f, -0.08236158f, 6.79194089e-003f,
-0.02458403f, 0.13022894f, 0.10953187f, 0.09857773f, 0.04735930f,
-0.04353498f, -0.15173385f, -0.17904443f, -0.10450364f, -0.13418166f,
-0.06633098f, -0.03170381f, -0.06839000f, -0.11350126f, -0.06983913f,
0.19083543f, 0.17604128f, 0.07730632f, 0.10022651f, 0.36428109f,
0.28291923f, 0.12688625f, 0.15942036f, 0.14064661f, -0.11201853f,
-0.13969108f, -0.09088077f, -0.14107047f, 0.05117374f,
-2.63348082e-003f, -0.10794610f, -0.09715455f, -0.05284977f,
0.01565668f, 0.05031200f, 0.07021113f, -0.02963028f, 0.01766960f,
0.08333644f, -0.03211382f, 4.90096770e-003f, 0.05186674f, -0.05045737f,
-0.09624767f, -0.02525997f, 0.06916669f, 0.01213916f, 0.05333899f,
-0.03443280f, -0.10055527f, -0.06291115f, 5.42851724e-003f,
-6.30360236e-003f, 0.02270257f, -0.01769792f, 0.03273688f, 0.07746078f,
7.77099328e-003f, 0.05041346f, 0.01648103f, -0.02321534f, -0.09930186f,
-0.02293853f, 0.02034990f, -0.08324204f, 0.08510064f, -0.03732836f,
-0.06465405f, -0.06086946f, 0.13680504f, -0.11469388f, -0.03896406f,
-0.07142810f, 2.67581246e-003f, -0.03639632f, -0.09849060f,
-0.11014334f, 0.17489147f, 0.17610909f, -0.16091567f, -0.07248894f,
0.01567141f, 0.23742996f, 0.07552249f, -0.06270349f, -0.07303379f,
0.25442186f, 0.16903116f, -0.08168741f, -0.05913896f, -0.03954096f,
6.81776879e-003f, -0.05615319f, -0.07303037f, -0.12176382f,
0.12385108f, 0.22084464f, -0.05543206f, -0.03310431f, 0.05731593f,
0.19481890f, 0.04016430f, -0.06480758f, -0.12353460f, 0.18733442f,
-0.09631214f, -0.11192076f, 0.12404587f, 0.15671748f, 0.19256128f,
0.10895617f, 0.03391477f, -0.13032004f, -0.05626907f, -0.09025607f,
0.23485197f, 0.27812332f, 0.26725492f, 0.07255980f, 0.16565137f,
0.22388470f, 0.07441066f, -0.21003133f, -0.08075339f, -0.15031935f,
0.07023834f, 0.10872041f, 0.18156518f, 0.20037253f, 0.13571967f,
-0.11915682f, -0.11131983f, -0.18878011f, 0.06074620f, 0.20578890f,
0.12413109f, 0.03930207f, 0.29176015f, 0.29502738f, 0.27856228f,
-0.01803601f, 0.16646385f, 0.19268319f, 0.01900682f, 0.06026287f,
2.35868432e-003f, 0.01558199f, 0.02707230f, 0.11383014f, 0.12103992f,
0.03907350f, 0.04637353f, 0.09020995f, 0.11919726f, -3.63007211e-003f,
0.02220155f, 0.10336831f, 0.17351882f, 0.12259731f, 0.18983354f,
0.15736865f, 0.01160725f, -0.01690723f, -9.69582412e-004f, 0.07213813f,
0.01161613f, 0.17864859f, 0.24486147f, 0.18208991f, 0.20177495f,
0.05972528f, -8.93934630e-003f, -0.02316955f, 0.14436610f, 0.14114498f,
0.05520950f, 0.06353590f, -0.19124921f, 0.10174713f, 0.29414919f,
0.26448128f, 0.09344960f, 0.15284036f, 0.19797507f, 0.11369792f,
-0.12722753f, -0.21396367f, -0.02008235f, -0.06566695f, -0.01662150f,
-0.03937003f, 0.04778343f, 0.05017274f, -0.02299062f, -0.20208496f,
-0.06395898f, 0.13721776f, 0.22544557f, 0.14888357f, 0.08687132f,
0.27088094f, 0.32206613f, 0.09782200f, -0.18523243f, -0.17232181f,
-0.01041531f, 0.04008654f, 0.04199702f, -0.08081299f, -0.03755421f,
-0.04809646f, -0.05222081f, -0.21709201f, -0.06622940f, 0.02945281f,
-0.04600435f, -0.05256077f, -0.08432942f, 0.02848100f, 0.03490564f,
8.28621630e-003f, -0.11051246f, -0.11210597f, -0.01998289f,
-0.05369405f, -0.08869293f, -0.18799506f, -0.05436598f, -0.05011634f,
-0.05419716f, -0.06151857f, -0.10827805f, 0.04346735f, 0.04016083f,
0.01520820f, -0.12173316f, -0.04880285f, -0.01101406f, 0.03250847f,
-0.06009551f, -0.03082932f, -0.02295134f, -0.06856834f, -0.08775249f,
-0.23793389f, -0.09174541f, -0.05538322f, -0.04321031f, -0.11874759f,
-0.04221844f, -0.06070468f, 0.01194489f, 0.02608565f, -0.03892140f,
-0.01643151f, -0.02602034f, -0.01305472f, 0.03920100f, -0.06514261f,
0.01126918f, -6.27710763e-003f, -0.02720047f, -0.11133634f,
0.03300330f, 0.02398472f, 0.04079665f, -0.10564448f, 0.05966159f,
0.01195221f, -0.03179441f, -0.01692590f, -0.06177841f, 0.01841576f,
-5.51078189e-003f, -0.06821765f, -0.03191888f, -0.09545476f,
0.03030550f, -0.04896152f, -0.02914624f, -0.13283344f, -0.04783419f,
6.07836898e-003f, -0.01449538f, -0.13358212f, -0.09687774f,
-0.02813793f, 0.01213498f, 0.06650011f, -0.02039067f, 0.13356198f,
0.05986415f, -9.12760664e-003f, -0.18780160f, -0.11992817f,
-0.06342237f, 0.01229534f, 0.07143231f, 0.10713009f, 0.11085765f,
0.06569190f, -0.02956399f, -0.16288325f, -0.13993549f, -0.01292515f,
0.03833013f, 0.09130384f, -0.05086257f, 0.05617329f, -0.03896667f,
-0.06282311f, -0.11490010f, -0.14264110f, -0.04530499f, 0.01598189f,
0.09167797f, 0.08663294f, 0.04885277f, -0.05741219f, -0.07565769f,
-0.17136464f, -0.02619422f, -0.02477579f, 0.02679587f, 0.11621952f,
0.08788391f, 0.15520640f, 0.04709549f, 0.04504483f, -0.10214074f,
-0.12293372f, -0.04820546f, -0.05484834f, 0.05473754f, 0.07346445f,
0.05577277f, -0.08209965f, 0.03462975f, -0.20962234f, -0.09324598f,
3.79481679e-003f, 0.03617633f, 0.16742408f, 0.07058107f, 0.10204960f,
-0.06795346f, 3.22807301e-003f, -0.12589309f, -0.17496960f,
0.02078314f, -0.07694324f, 0.12184640f, 0.08997164f, 0.04793497f,
-0.11383379f, -0.08046359f, -0.25716835f, -0.08080962f,
6.80711539e-003f, -0.02930280f, -3.04938294e-003f, -0.11106286f,
-0.04628860f, -0.07821649f, 7.70127494e-003f, -0.10247706f,
1.21042714e-003f, 0.20573859f, -0.03241005f, 8.42972286e-003f,
0.01946464f, -0.01197973f, -0.14579976f, 0.04233614f,
-4.14096704e-003f, -0.06866436f, -0.02431862f, -0.13529138f,
1.25891645e-003f, -0.11425111f, -0.04303651f, -0.01694815f,
0.05720210f, -0.16040207f, 0.02772896f, 0.05498345f, -0.15010567f,
0.01450866f, 0.02350303f, -0.04301004f, -0.04951802f, 0.21702233f,
-0.03159155f, -0.01963303f, 0.18232647f, -0.03263875f,
-2.88476888e-003f, 0.01587562f, -1.94303901e-003f, -0.07789494f,
0.04674156f, -6.25576358e-003f, 0.08925962f, 0.21353747f, 0.01254677f,
-0.06999976f, -0.05931328f, -0.01884327f, -0.04306272f, 0.11794136f,
0.03842728f, -0.03907030f, 0.05636114f, -0.09766009f, -0.02104000f,
8.72711372e-003f, -0.02736877f, -0.05112274f, 0.16996814f, 0.02955785f,
0.02094014f, 0.08414304f, -0.03335762f, -0.03617457f, -0.05808248f,
-0.08872101f, 0.02927705f, 0.27077839f, 0.06075108f, 0.07478261f,
0.15282831f, -0.03908454f, -0.05101782f, -9.51998029e-003f,
-0.03272416f, -0.08735625f, 0.07633440f, -0.07185312f, 0.13841286f,
0.07812646f, -0.12901451f, -0.05488589f, -0.05644578f, -0.03290703f,
-0.11184757f, 0.03751570f, -0.05978153f, -0.09155276f, 0.05657315f,
-0.04328186f, -0.03047933f, -0.01413135f, -0.10181040f, -0.01384013f,
0.20132534f, -0.01536873f, -0.07641169f, 0.05906778f, -0.07833145f,
-0.01523801f, -0.07502609f, -0.09461885f, -0.15013233f, 0.16050665f,
0.09021381f, 0.08473236f, 0.03386267f, -0.09147339f, -0.09170618f,
-0.08498498f, -0.05119187f, -0.10431040f, 0.01041618f, -0.03064913f,
0.09340212f, 0.06448522f, -0.03881054f, -0.04985436f, -0.14794017f,
-0.05200112f, -0.02144495f, 0.04000821f, 0.12420804f, -0.01851651f,
-0.04116732f, -0.11951703f, -0.04879033f, -0.08722515f, -0.08454733f,
-0.10549165f, 0.11251976f, 0.10766345f, 0.19201984f, 0.06128913f,
-0.02734615f, -0.08834923f, -0.16999826f, -0.03548348f,
-5.36092324e-003f, 0.08297954f, 0.07226378f, 0.04194529f, 0.04668673f,
8.73902347e-003f, 0.06980139f, 0.05652480f, 0.05879445f, 0.02477076f,
0.02451423f, 0.12433673f, 0.05600227f, 0.06886370f, 0.03863076f,
0.07459056f, 0.02264139f, 0.01495469f, 0.06344220f, 0.06945208f,
0.02931899f, 0.11719371f, 0.04527427f, 0.03248192f, 2.08271481e-003f,
0.02044626f, 0.11403449f, 0.04303892f, 0.06444661f, 0.04959024f,
0.08174094f, 0.09240247f, 0.04894639f, 0.02252937f, -0.01652530f,
0.07587013f, 0.06064249f, 0.13954395f, 0.02772832f, 0.07093039f,
0.08501238f, 0.01701301f, 0.09055722f, 0.33421436f, 0.20163782f,
0.09821030f, 0.07951369f, 0.08695120f, -0.12757730f, -0.13865978f,
-0.06610068f, -0.10985506f, 0.03406816f, -0.01116336f, -0.07281768f,
-0.13525715f, -0.12844718f, 0.08956250f, 0.09171610f, 0.10092317f,
0.23385370f, 0.34489515f, 0.09901748f, 0.02002922f, 0.12335990f,
0.07606190f, -0.14899330f, -0.15634622f, -0.06494618f, -0.01760547f,
0.03404277f, -0.13208845f, -0.12101169f, -0.18294574f, -0.16560709f,
0.02183887f, -0.02752613f, 0.01813638f, 0.02000757f, 0.01319924f,
0.08030242f, 0.01220535f, 2.98233377e-003f, -0.01307070f, 0.05970297f,
-0.05345284f, -0.03381982f, -9.87543724e-003f, -0.06869387f,
0.03956730f, -0.03108176f, -0.05732809f, 0.02172386f, 0.04159765f,
2.62783933e-003f, 0.04813229f, 0.09358983f, -8.18389002e-003f,
0.01724574f, -0.02547474f, -0.04967288f, -0.02390376f, 0.06640504f,
-0.06306566f, 0.01137518f, 0.05589378f, -0.08237787f, 0.02455001f,
-0.03059422f, -0.08953978f, 0.06851497f, 0.07190268f, -0.07610799f,
7.87237938e-003f, -7.85830803e-003f, 0.06006952f, -0.01126728f,
-2.85743061e-003f, -0.04772895f, 0.01884944f, 0.15005857f,
-0.06268821f, -0.01989072f, 0.01138399f, 0.08760451f, 0.03879007f,
-9.66926850e-003f, -0.08012961f, 0.06414555f, -0.01362950f,
-0.09135523f, 0.01755159f, 0.04459474f, 0.09650917f, 0.05219948f,
-2.19440833e-003f, -0.07037939f, -0.01599054f, 0.13103317f,
-0.02492603f, -0.01032540f, -0.02903307f, 0.04489160f, 0.05148086f,
0.01858173f, -0.02919228f, 0.08299296f, -0.04590359f, -0.15745632f,
-0.09068198f, -0.02972453f, 0.12985018f, 0.22320485f, 0.24261914f,
0.03642650f, -0.05506422f, 2.67413049e-003f, -0.03834032f, 0.06449424f,
0.03834866f, 0.03816991f, 0.25039271f, 0.34212017f, 0.32433882f,
0.18824573f, -0.08599839f, -0.17599408f, -0.15317015f, -0.09913155f,
-0.02856072f, -0.05304699f, -1.06437842e-003f, -0.06641813f,
-0.07509298f, 0.01463361f, -0.07551918f, -0.04510373f,
-8.44620075e-003f, 0.01772176f, 0.04068235f, 0.20295307f, 0.15719447f,
0.05712103f, 0.26296997f, 0.14657754f, 0.01547317f, -0.05052776f,
-0.03881342f, -0.01437883f, -0.04930177f, 0.11719568f, 0.24098417f,
0.26468599f, 0.31698579f, 0.10103608f, -0.01096375f, -0.01367013f,
0.17104232f, 0.20065314f, 2.67622480e-003f, -0.01190034f, 0.18301608f,
0.09459770f, -0.06357619f, -0.06473801f, 0.01377906f, -0.10032775f,
-0.06388740f, 3.80393048e-003f, 0.06206078f, 0.10349120f, 0.26804337f,
8.17918684e-003f, -0.02314351f, 9.34422202e-003f, 0.09198381f,
0.03681326f, -8.77339672e-003f, -0.09662418f, -0.02715708f,
0.13503517f, 0.08962728f, -6.57071499e-003f, -0.03201199f, 0.28510824f,
0.32095715f, 0.18512695f, -0.14230858f, -0.14048551f, -0.07181299f,
-0.08575408f, -0.08661680f, -0.17416079f, 7.54326640e-004f,
0.05601677f, 0.13585392f, -0.04960437f, -0.07708392f, 0.10676333f,
-0.04407546f, -0.07209078f, 0.03663663f, 0.28949317f, 0.41127121f,
0.27431169f, -0.06900328f, -0.21474190f, -0.15578632f, -0.19555484f,
-0.15209621f, -0.11269179f, 0.07416003f, 0.18991330f, 0.26858172f,
0.01952259f, 0.01017922f, 0.02159843f, -4.95165400e-003f, -0.04368168f,
-0.12721671f, -0.06673957f, -0.11275250f, 0.04413409f, 0.05578312f,
0.03896771f, 0.03566417f, -0.05871816f, -0.07388090f, -0.17965563f,
-0.08570268f, -0.15273231f, -0.06022318f, -0.06999847f,
-6.81510568e-003f, 0.06294262f, -6.54901436e-004f, -0.01128654f,
-0.02289657f, 0.04849290f, 0.04140804f, 0.23681939f, 0.14545733f,
0.01989965f, 0.12032662f, 3.87463090e-003f, -6.02597650e-003f,
-0.05919775f, -0.03067224f, -0.07787777f, 0.10834727f, 0.02153730f,
0.02765649f, 0.03975543f, -0.12182906f, -0.04900113f, -0.09940100f,
-0.06453611f, -0.13757215f, -0.03721382f, 0.02827376f, -0.04351249f,
0.01907038f, -0.10284120f, -0.05671160f, -0.10760647f, -0.09624009f,
-0.09565596f, -0.01303654f, 0.03080539f, 0.01416511f, 0.05846142f,
-5.42971538e-003f, 0.06221476f, -0.03320325f, -0.06791797f,
-0.05791342f, 0.12851369f, 0.14990346f, 0.03634374f, 0.14262885f,
0.04330391f, 0.05032569f, -0.05631914f, 0.01606137f, 0.04387223f,
0.22344995f, 0.15722635f, -0.04693628f, 0.03006579f, -2.52882647e-003f,
0.05717621f, -0.07529724f, -0.02848588f, -0.06868757f,
-4.51729307e-003f, 0.06466042f, -0.05935378f, -0.04704857f,
-0.07363959f, 0.04843248f, -0.13421375f, -0.09789340f, -0.10255270f,
0.03509852f, 0.04751543f, -0.03822323f, 0.09740467f, 0.04762916f,
0.03940146f, -0.08283259f, 0.09552965f, 0.05038739f, 0.21258622f,
0.09646992f, 0.03241193f, 0.05167701f, 0.04614570f, 0.04330090f,
-0.02671840f, -0.06259909f, -0.02301898f, 0.18829170f, 0.10522786f,
0.04313190f, 0.01670948f, -0.08421925f, 0.05911417f, -0.10582602f,
-0.04855484f, -0.08373898f, 0.07775915f, 0.03723533f, -0.12047344f,
4.86345543e-003f, -0.10520902f, 0.06571782f, -0.07528137f,
-0.03245651f, -0.09869066f, -0.02917477f, -0.18293270f, 0.14810945f,
9.24033765e-003f, -0.04354914f, 0.02266885f, -0.11872729f,
-0.04016589f, 0.02830229f, 0.22539048f, 0.20565644f, 0.16701797f,
0.09019924f, 0.01300652f, 0.09760600f, -0.03675831f, -0.01935448f,
-0.06894835f, 0.08077277f, 0.19047537f, 0.11312226f, 0.04106043f,
-0.11187182f, 0.04312806f, -0.18548580f, -0.11287174f, -0.08794551f,
0.02078281f, -0.15295486f, 0.11806386f, -0.01103218f, -0.15971117f,
0.02153538f, -0.05232147f, -0.10835317f, -0.13910367f, 0.05920752f,
-0.10122602f, 0.20174250f, 0.09105796f, -0.01881348f, 0.09559010f,
-0.03725745f, -0.09442931f, -0.09763174f, 0.05854454f, 0.08287182f,
0.12919849f, 0.08594352f, -2.49806582e-003f, 0.02398440f,
5.67950122e-003f, -0.06296340f, -0.12993270f, 0.03855852f, 0.05186560f,
0.10839908f, -0.03380463f, -0.12654832f, -0.05399339f, -0.07456800f,
-0.04736232f, -0.10164231f, 0.07496139f, 0.08125214f, 0.07656177f,
-0.04999603f, -0.12823077f, -0.07692395f, -0.11317524f, -0.09118655f,
-0.05695669f, 0.10477209f, 0.07468581f, 0.01630048f, -8.00961629e-003f,
-0.06582128f, -0.04019095f, -0.04682907f, -0.01907842f, -0.10997720f,
0.04911406f, 0.02931030f, 0.04197735f, -0.05773980f, -0.09670641f,
-0.03594951f, -0.03402121f, -0.07149299f, -0.10566200f, 0.10601286f,
0.06340689f, -0.01518632f, -5.96402306e-003f, -0.07628012f,
-3.52779147e-003f, -0.02683854f, -0.10265494f, -0.02680815f,
0.16338381f, 0.03103515f, 0.02296976f, 0.01624348f, -0.10831620f,
-0.02314233f, -0.04789969f, -0.05530700f, -0.06461314f, 0.10494506f,
0.04642856f, -0.07592955f, -0.06197905f, -0.09042154f, -0.01445521f,
-0.04297818f, -0.11262015f, -0.11430512f, 0.03174541f, -0.03677487f,
-0.02963996f, -0.06610169f, -0.13292049f, -0.07059067f, -0.08444111f,
-0.02640536f, -0.07136250f, 0.04559967f, 0.01459980f, 0.17989251f,
0.04435328f, -0.12464730f, -0.02871115f, -0.10752209f, -0.03393742f,
-0.03791408f, 0.02548251f, 0.01956050f, 0.19245651f, 0.13963254f,
-0.05904696f, -0.07424626f, -0.10411884f, 1.54176133e-003f,
0.01797429f, 0.13025844f, 0.04547642f, -0.05710349f, -0.10697161f,
-0.13489437f, -0.06515755f, -0.06406886f, -4.08572936e-003f,
-0.01336483f, 0.04368737f, -0.11259720f, -0.05701635f, -0.06469971f,
-0.08346602f, -0.04166770f, -0.05795543f, -0.08247511f, -0.05742628f,
0.08452254f, -0.03350224f, 0.13980860f, 0.13252275f, 0.07589617f,
0.07539988f, 0.12155797f, 0.19087289f, 0.15050751f, 0.21250245f,
0.14206800f, 0.01298489f, 0.07450245f, 0.06559097f, 0.01700557f,
0.04512971f, 0.16950700f, 0.10261577f, 0.16389982f, 0.05505059f,
-0.03453077f, 0.08622462f, 0.07935954f, 0.03976260f, 0.02036091f,
3.95744899e-003f, 0.03267065f, 0.15235919f, 0.01297494f, -0.08109194f,
0.01407558f, 4.40693414e-003f, -0.15157418f, -0.11390478f,
-0.07487597f, -7.81322457e-003f, -0.02749545f, -0.10181408f,
0.13755716f, 0.14007211f, 0.13482562f, 0.27517235f, 0.34251109f,
0.07639657f, 0.07268607f, 0.19823882f, 0.16135791f, -0.04186463f,
-0.12784107f, -0.09846287f, 0.03169041f, 0.10974082f, -0.15051922f,
-0.08916726f, -0.07138767f, -0.04153349f, 6.25418453e-003f,
0.01266654f, 0.10533249f, 0.12749144f, 0.15148053f, 0.01498513f,
0.06305949f, -0.01247123f, -0.08778401f, -0.08551880f, -0.11955146f,
-0.08493572f, -0.02901620f, -0.02394859f, -0.13427313f, -0.11053200f,
-0.14413260f, -0.15203285f, 0.03972760f, -3.72127310e-004f,
-0.04200919f, 0.06105104f, 0.01904975f, -0.01106191f,
-7.27445772e-003f, -0.01520341f, 1.10228511e-003f, -0.04949187f,
-0.08013099f, 5.72071038e-003f, 0.08415454f, -0.06523152f, 0.03664081f,
-0.02673042f, -0.12066154f, -0.03702074f, 0.06006580f, 0.01628682f,
-6.17772620e-003f, 0.08192339f, -3.41629819e-003f, 0.02870512f,
0.05807141f, 0.04959986f, 0.04618251f, -0.04901629f, -0.10579574f,
0.02274442f, 0.12070961f, 2.23597488e-003f, 0.09831765f, -0.03019848f,
-0.11181970f, -0.04961075f, 0.02498928f, -0.03714991f, -0.01619653f,
0.02643486f, -7.62964319e-003f, -0.02882290f, -0.06242594f,
-0.08439861f, 0.07220893f, 0.07263952f, 0.01561574f, 0.03091968f,
0.01708712f, -0.03797151f, -3.18561122e-003f, 0.01624021f,
-0.02828573f, 0.11284444f, -1.32280716e-003f, -0.07784860f,
-0.07209100f, 0.03372242f, 0.12154529f, 0.02278104f, -0.05275500f,
-0.01918484f, 0.12989293f, 0.05424401f, 0.02333086f, 0.04029022f,
0.12392918f, 0.09495489f, 0.09190340f, 0.07935889f, 8.76816828e-003f,
0.17148446f, -8.51302687e-003f, -0.08011249f, -0.06796283f,
0.04884845f, 0.01112272f, -0.07835306f, -1.14811445e-003f,
-0.03440760f, 0.02845243f, 0.07695542f, -0.07069533f, -0.01151784f,
-8.53884313e-003f, -0.01662786f, -0.04163864f, 0.05400505f,
0.02859163f, 0.02921852f, 0.05003135f, -6.85718050e-003f, -0.01632611f,
0.07780217f, 0.04042810f, -0.01216440f, 3.60914599e-003f, -0.06322435f,
0.09516726f, 0.12877031f, -9.69162490e-003f, 0.01031179f, 0.05180895f,
-9.34659224e-003f, -0.01644533f, -0.04849347f, -0.04343236f,
0.10514783f, 0.08046635f, -0.04615205f, -0.03975486f, -0.01485525f,
0.13096830f, -0.01517950f, -0.06571898f, -0.04016372f, 0.01849786f,
0.02439670f, 0.08067258f, 1.74824719e-003f, 0.07053747f, 0.08819518f,
-5.08352555e-003f, -0.06550863f, -0.08266170f, -0.07780605f,
0.01453450f, -0.08756890f, 0.01096501f, -8.71319138e-003f, 0.10110464f,
0.02420769f, -0.06708383f, 0.02007811f, 5.93133038e-003f, 0.05398923f,
0.07538138f, 0.02049227f, 0.02242589f, 0.04011070f, -1.44875818e-003f,
-4.19115182e-003f, 0.06367654f, 0.02506934f, 0.02434536f, 0.05879405f,
-8.22952855e-003f, -0.01242441f, 0.04224926f, -0.01754923f,
0.05958161f, 0.03818886f, -0.01830363f, -0.04308917f, -0.04422197f,
-0.02432721f, 0.02264866f, 2.03751423e-003f, 0.01197031f, 0.04439203f,
0.12169247f, 0.03602713f, -0.02599251f, -1.98226492e-003f, 0.02046336f,
-0.02639058f, -1.91242550e-003f, -0.09334669f, -0.03595153f,
-9.88179818e-003f, -0.06848445f, -0.04666303f, -0.09955736f,
-0.04206430f, 0.02609075f, 9.09005292e-003f, -0.07138551f,
-4.22313227e-004f, 0.01766645f, 0.02756404f, 0.01308276f, 0.04052891f,
0.02387515f, 0.05337298f, 0.02500631f, -0.04970853f, -0.12467445f,
0.17604403f, 0.12256411f, -0.07512254f, 8.70451052e-003f, -0.05697548f,
-0.03626474f, -8.76623299e-003f, -0.01210897f, -0.09451522f,
0.07490732f, -0.02008001f, -0.02681278f, -0.06463405f, -0.01517507f,
7.33757764e-003f, 6.07147906e-003f, -0.09316964f, -0.04575328f,
0.13261597f, 0.15424870f, -0.01655918f, -0.02772390f, -0.05243644f,
-0.02356456f, -0.02351753f, -0.10211615f, -0.12873036f, 0.14549787f,
0.12519856f, 4.38762689e-003f, 0.02795992f, 0.05170322f, 0.09223596f,
0.05890015f, 0.02376701f, -0.02777346f, 0.09506908f, 0.02328936f,
-0.02319928f, -0.03218696f, -0.01527841f, -0.01016694f, -0.02674719f,
0.05137179f, 0.01980666f, 0.06544447f, -0.01746171f, 0.01026380f,
0.01561806f, 7.97004555e-004f, 0.07601810f, 0.01907250f, -0.03083035f,
-0.05987392f, 0.09242783f, 0.14555025f, 0.01035827f, 0.03092401f,
-0.09562709f, -0.03802354f, 0.02531144f, 0.03079449f, -0.07100715f,
0.03330721f, -2.69116857e-003f, 0.03167490f, 0.05744999f, 0.03259895f,
1.91266940e-003f, 0.03194578f, 0.07389776f, 0.02198060f, 0.07633314f,
0.03293105f, -0.09103648f, 0.04718142f, 0.06102672f, -0.01003063f,
5.85481385e-003f, -0.01522574f, 0.02323526f, 0.10584345f,
4.35879454e-003f, 0.06107873f, 0.05868603f, -0.03115531f, 0.01214679f,
0.08567052f, 3.93926632e-003f, -0.02521488f, -1.88425183e-003f,
0.02038053f, -6.26854831e-004f, 0.04897438f, -0.04280585f,
-0.04819689f, -0.04812867f, -0.01451186f, 0.05101469f,
-9.01125465e-003f, -0.03333859f, 0.03917955f, 0.04196448f, 0.04292135f,
0.02809529f, 0.02999715f, 0.04081348f, 9.10039060e-003f, 0.09703232f,
0.10379741f, 0.02348725f, -4.72756615e-003f, 0.01027325f, 0.10402658f,
0.12071823f, 0.09817299f, -0.02612033f, 0.03638414f, 0.05896405f,
0.04865025f, 0.04793910f, -0.03882321f, -0.02962117f, -0.01222268f,
0.04071597f, 0.01922777f, -0.02287866f, 0.03328381f, 0.01859092f,
0.09024994f, 0.03804455f, -0.01424510f, 0.01953739f, 0.02509617f,
-0.03390914f, -0.05663941f, -0.01641979f, 0.05848591f, 0.04639670f,
0.02092116f, 0.12911791f, 0.19918139f, 0.07739855f, -7.25806039e-003f,
0.04074838f, 0.03183993f, 1.39251316e-003f, -0.01428625f, 0.01865480f,
0.08529541f, 0.13547510f, 0.11189661f, 0.03998901f, 0.09575938f,
-0.02631102f, -0.03458253f, -0.04749985f, -0.06070716f,
4.71884012e-003f, 0.06445789f, -0.02450038f, -0.05483776f,
-0.04657237f, -0.02030717f, -0.03480766f, -0.09397731f, -0.06399718f,
-0.01804585f, 5.62348310e-003f, -6.64811488e-003f, -0.06517869f,
6.96210237e-003f, -0.01860148f, -0.04245830f, -0.05850367f,
-3.24417115e-003f, 0.07700698f, 0.11290991f, 0.09923030f, -0.02970599f,
0.05592411f, 0.04813979f, -0.09811195f, -0.09357996f, -0.03276114f,
0.05218338f, 0.04141375f, 3.92977800e-003f, -0.05047480f, 0.15960084f,
0.04612800f, -0.03114098f, -0.04650044f, -0.03249795f, -0.02425641f,
-0.04311355f, 0.04307659f, -0.09401883f, -0.04742785f, -0.01254499f,
-0.06598741f, 3.41369561e-003f, -0.05620445f, -7.28127593e-003f,
-0.05998361f, -0.03274450f, -0.07376868f, 3.19015374e-003f,
-0.07733069f, 0.05815864f, -0.02471071f, 0.03850617f, 0.13838784f,
0.15399861f, 0.01731321f, -0.01477586f, 0.10393341f, 0.05159833f,
-0.01945555f, -0.03427503f, -0.04867341f, 0.09237480f, 0.10732719f,
0.06071450f, -0.01355071f, 0.01844356f, -0.03480803f, -0.03796671f,
2.15628621e-004f, -0.05440186f, 0.01889855f, -0.01443413f,
-0.02607902f, -0.02938001f, 0.02720689f, -0.06228397f, -0.02970936f,
-0.03426210f, -0.10280876f, -0.06739304f, -0.05227850f, 0.03360292f,
-0.11278441f, -0.06966180f, -0.13937433f, 9.10932291e-003f,
2.52020749e-004f, -4.07359656e-003f, 0.12310639f, 0.09343060f,
0.07302511f, 0.03222093f, 0.07532879f, 0.03792387f, -0.04985180f,
0.01804602f, 0.02694195f, 0.13481498f, 0.04601225f, 0.04106982f,
0.08511057f, 0.12314661f, 0.01320830f, 0.05044121f, -5.52943908e-003f,
-0.08992624f, -0.02249301f, -0.08181777f, 0.06165213f, -0.03256603f,
-0.01068920f, -0.01323473f, -0.11970232f, -0.04616347f, -0.12088681f,
-0.06762606f, -0.08676834f, -0.06434575f, 0.01772529f, 0.03469615f,
-0.10926618f, 0.03013873f, 0.14030397f, 0.16130108f, 0.17985588f,
0.11281928f, 0.10530639f, 0.08905948f, 0.07733764f, 0.06695238f,
0.02142088f, 0.06438877f, 0.09794453f, 0.05745072f, 0.02788557f,
0.02632830f, 0.07985807f, 4.24902979e-003f, 8.47890321e-003f,
-0.02679466f, -5.28812688e-003f, -0.02162580f, -0.07490715f,
-0.08251337f, -0.02056576f, -0.01026194f, -1.15492963e-003f,
-5.75720915e-004f, -0.07210591f, -0.07320981f, -0.04883312f,
-0.10897151f, -0.07477258f, -0.08867134f, -0.09222437f, -0.10924666f,
-0.10430276f, 0.07953499f, 0.02767959f, 0.11393359f, 0.18779543f,
0.03313421f, 0.02143700f, 0.05852016f, -2.12067598e-003f,
-3.76984011e-003f, 0.02774167f, -0.03124610f, 0.01465141f, 0.01616004f,
-0.01391913f, -0.04404102f, -0.05444227f, -0.14684731f, -0.15016587f,
0.04509468f, 1.29563001e-003f, 0.01398350f, 0.05610404f, -0.04868806f,
-0.04776716f, -8.16873740e-003f, -2.30126386e-003f, -0.02286313f,
0.11983398f, -0.04703261f, -0.08814441f, -0.07585249f, -0.10799607f,
-0.03232087f, 0.01509786f, -0.04843464f, -0.03967846f, 0.09589416f,
0.01352560f, -0.01458119f, 0.01050829f, -0.03038946f, 0.01608388f,
1.11975556e-003f, -0.01250656f, 2.86211423e-003f, 0.04333691f,
-0.14603497f, -0.01946543f, -0.02327525f, -0.01973944f, 0.07944400f,
-0.02224544f, -0.06701808f, 0.03476532f, 0.11505594f, -0.02712801f,
-0.01665113f, 0.06315716f, -0.08205860f, 0.07431999f, 0.04915778f,
-0.04468752f, -0.01490402f, 0.07400476f, -0.11650901f, 0.05102430f,
0.04559118f, -0.05916039f, 0.08840760f, -0.01587902f, -0.14890194f,
0.07857784f, 0.04710254f, -0.05381983f, -0.07331945f, -0.03604643f,
0.15611970f, 0.07649943f, -0.05959348f, -0.02776607f, 0.11098688f,
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 vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
}
//This function renurn 1981 SVM coeffs obtained from daimler's base.
//To use these coeffs the detection window size should be (48,96)
vector<float> HOGDescriptor::getDaimlerPeopleDetector()
{
static const 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,
-0.148927f, 0.013355f, -0.078279f, 0.030451f,
0.056301f, -0.024609f, 0.083224f, 0.099533f,
-0.039432f, -0.138880f, 0.005482f, -0.024120f,
-0.140468f, -0.066381f, -0.017057f, 0.009260f,
-0.058004f, -0.028486f, -0.061610f, 0.007483f,
-0.158309f, -0.150687f, -0.044595f, -0.105121f,
-0.045763f, -0.006618f, -0.024419f, -0.117713f,
-0.119366f, -0.175941f, -0.071542f, 0.119027f,
0.111362f, 0.043080f, 0.034889f, 0.093003f,
0.007842f, 0.057368f, -0.108834f, -0.079968f,
0.230959f, 0.020205f, 0.011470f, 0.098877f,
0.101310f, -0.030215f, -0.018018f, -0.059552f,
-0.106157f, 0.021866f, -0.036471f, 0.080051f,
0.041165f, -0.082101f, 0.117726f, 0.030961f,
-0.054763f, -0.084102f, -0.185778f, -0.061305f,
-0.038089f, -0.110728f, -0.264010f, 0.076675f,
-0.077111f, -0.137644f, 0.036232f, 0.277995f,
0.019116f, 0.107738f, 0.144003f, 0.080304f,
0.215036f, 0.228897f, 0.072713f, 0.077773f,
0.120168f, 0.075324f, 0.062730f, 0.122478f,
-0.049008f, 0.164912f, 0.162450f, 0.041246f,
0.009891f, -0.097827f, -0.038700f, -0.023027f,
-0.120020f, 0.203364f, 0.248474f, 0.149810f,
-0.036276f, -0.082814f, -0.090343f, -0.027143f,
-0.075689f, -0.320310f, -0.000500f, -0.143334f,
-0.065077f, -0.186936f, 0.129372f, 0.116431f,
0.181699f, 0.170436f, 0.418854f, 0.460045f,
0.333719f, 0.230515f, 0.047822f, -0.044954f,
-0.068086f, 0.140179f, -0.044821f, 0.085550f,
0.092483f, -0.107296f, -0.130670f, -0.206629f,
0.114601f, -0.317869f, -0.076663f, 0.038680f,
0.212753f, -0.016059f, -0.126526f, -0.163602f,
0.210154f, 0.099887f, -0.126366f, 0.118453f,
0.019309f, -0.021611f, -0.096499f, -0.111809f,
-0.200489f, 0.142854f, 0.228840f, -0.353346f,
-0.179151f, 0.116834f, 0.252389f, -0.031728f,
-0.188135f, -0.158998f, 0.386523f, 0.122315f,
0.209944f, 0.394023f, 0.359030f, 0.260717f,
0.170335f, 0.013683f, -0.142596f, -0.026138f,
-0.011878f, -0.150519f, 0.047159f, -0.107062f,
-0.147347f, -0.187689f, -0.186027f, -0.208048f,
0.058468f, -0.073026f, -0.236556f, -0.079788f,
-0.146216f, -0.058563f, -0.101361f, -0.071294f,
-0.071093f, 0.116919f, 0.234304f, 0.306781f,
0.321866f, 0.240000f, 0.073261f, -0.012173f,
0.026479f, 0.050173f, 0.166127f, 0.228955f,
0.061905f, 0.156460f, 0.205990f, 0.120672f,
0.037350f, 0.167884f, 0.290099f, 0.420900f,
-0.012601f, 0.189839f, 0.306378f, 0.118383f,
-0.095598f, -0.072360f, -0.132496f, -0.224259f,
-0.126021f, 0.022714f, 0.284039f, 0.051369f,
-0.000927f, -0.058735f, -0.083354f, -0.141254f,
-0.187578f, -0.202669f, 0.048902f, 0.246597f,
0.441863f, 0.342519f, 0.066979f, 0.215286f,
0.188191f, -0.072240f, -0.208142f, -0.030196f,
0.178141f, 0.136985f, -0.043374f, -0.181098f,
0.091815f, 0.116177f, -0.126690f, -0.386625f,
0.368165f, 0.269149f, -0.088042f, -0.028823f,
0.092961f, 0.024099f, 0.046112f, 0.176756f,
0.135849f, 0.124955f, 0.195467f, -0.037218f,
0.167217f, 0.188938f, 0.053528f, -0.066561f,
0.133721f, -0.070565f, 0.115898f, 0.152435f,
-0.116993f, -0.110592f, -0.179005f, 0.026668f,
0.080530f, 0.075084f, -0.070401f, 0.012497f,
0.021849f, -0.139764f, -0.022020f, -0.096301f,
-0.064954f, -0.127446f, -0.013806f, -0.108315f,
0.156285f, 0.149867f, -0.011382f, 0.064532f,
0.029168f, 0.027393f, 0.069716f, 0.153735f,
0.038459f, 0.230714f, 0.253840f, 0.059522f,
-0.045053f, 0.014083f, 0.071103f, 0.068747f,
0.095887f, 0.005832f, 0.144887f, 0.026357f,
-0.067359f, -0.044151f, -0.123283f, -0.019911f,
0.005318f, 0.109208f, -0.003201f, -0.021734f,
0.142025f, -0.066907f, -0.120070f, -0.188639f,
0.012472f, -0.048704f, -0.012366f, -0.184828f,
0.168591f, 0.267166f, 0.058208f, -0.044101f,
0.033500f, 0.178558f, 0.104550f, 0.122418f,
0.080177f, 0.173246f, 0.298537f, 0.064173f,
0.053397f, 0.174341f, 0.230984f, 0.117025f,
0.166242f, 0.227781f, 0.120623f, 0.176952f,
-0.011393f, -0.086483f, -0.008270f, 0.051700f,
-0.153369f, -0.058837f, -0.057639f, -0.060115f,
0.026349f, -0.160745f, -0.037894f, -0.048575f,
0.041052f, -0.022112f, 0.060365f, 0.051906f,
0.162657f, 0.138519f, -0.050185f, -0.005938f,
0.071301f, 0.127686f, 0.062342f, 0.144400f,
0.072600f, 0.198436f, 0.246219f, -0.078185f,
-0.036169f, 0.075934f, 0.047328f, -0.013601f,
0.087205f, 0.019900f, 0.022606f, -0.015365f,
-0.092506f, 0.075275f, -0.116375f, 0.050500f,
0.045118f, 0.166567f, 0.072073f, 0.060371f,
0.131747f, -0.169863f, -0.039352f, -0.047486f,
-0.039797f, -0.204312f, 0.021710f, 0.129443f,
-0.021173f, 0.173416f, -0.070794f, -0.063986f,
0.069689f, -0.064099f, -0.123201f, -0.017372f,
-0.206870f, 0.065863f, 0.113226f, 0.024707f,
-0.071341f, -0.066964f, -0.098278f, -0.062927f,
0.075840f, 0.014716f, 0.019378f, 0.132699f,
-0.074191f, -0.089557f, -0.078446f, -0.197488f,
-0.173665f, 0.052583f, 0.044361f, 0.113549f,
0.098492f, 0.077379f, -0.011146f, -0.192593f,
-0.164435f, 0.045568f, 0.205699f, 0.049187f,
-0.082281f, 0.134874f, 0.185499f, 0.034968f,
-0.119561f, -0.112372f, -0.115091f, -0.054042f,
-0.183816f, -0.078100f, 0.190695f, 0.091617f,
0.004257f, -0.041135f, -0.061453f, -0.141592f,
-0.194809f, -0.120638f, 0.020168f, 0.109672f,
0.067398f, -0.015238f, -0.239145f, -0.264671f,
-0.185176f, 0.050472f, 0.020793f, 0.035678f,
0.022839f, -0.052055f, -0.127968f, -0.113049f,
-0.228416f, -0.258281f, -0.053437f, 0.076424f,
0.061450f, 0.237478f, 0.003618f, -0.055865f,
-0.108087f, -0.028937f, 0.045585f, 0.052829f,
-0.001471f, 0.022826f, 0.059565f, -0.104430f,
-0.077266f, -0.211882f, -0.212078f, 0.028074f,
0.075846f, 0.016265f, 0.161879f, 0.134477f,
0.008935f, -0.048041f, 0.074692f, 0.004928f,
-0.025156f, 0.192874f, 0.074410f, 0.308732f,
0.267400f, 0.094208f, -0.005251f, 0.042041f,
-0.032148f, 0.015588f, 0.252869f, 0.175302f,
0.022892f, 0.081673f, 0.063208f, 0.162626f,
0.194426f, 0.233890f, 0.262292f, 0.186930f,
0.084079f, -0.286388f, -0.213034f, -0.048867f,
-0.207669f, -0.170050f, 0.011673f, -0.092958f,
-0.192786f, -0.273536f, 0.230904f, 0.266732f,
0.320519f, 0.297155f, 0.548169f, 0.304922f,
0.132687f, 0.247333f, 0.212488f, -0.271472f,
-0.142105f, -0.002627f, -0.119215f, 0.128383f,
0.100079f, -0.057490f, -0.121902f, -0.228892f,
0.202292f, -0.399795f, -0.371326f, -0.095836f,
-0.063626f, -0.161375f, -0.311180f, -0.294797f,
0.242122f, 0.011788f, 0.095573f, 0.322523f,
0.511840f, 0.322880f, 0.313259f, 0.173331f,
0.002542f, -0.029802f, 0.324766f, -0.326170f,
-0.340547f, -0.138288f, -0.002963f, -0.114060f,
-0.377312f, -0.442570f, 0.212446f, -0.007759f,
-0.011576f, 0.169711f, 0.308689f, 0.317348f,
0.539390f, 0.332845f, 0.057331f, -0.068180f,
0.101994f, 0.266995f, 0.209570f, 0.355730f,
0.091635f, 0.170238f, 0.125215f, 0.274154f,
0.070223f, 0.025515f, 0.049946f, -0.000550f,
0.043715f, -0.141843f, 0.020844f, 0.129871f,
0.256588f, 0.105015f, 0.148339f, 0.170682f,
0.028792f, 0.074037f, 0.160042f, 0.405137f,
0.246187f, 0.352160f, 0.168951f, 0.222263f,
0.264439f, 0.065945f, 0.021963f, -0.075084f,
0.093105f, 0.027318f, 0.098864f, 0.057566f,
-0.080282f, 0.185032f, 0.314419f, 0.333727f,
0.125798f, 0.294919f, 0.386002f, 0.217619f,
-0.183517f, -0.278622f, -0.002342f, -0.027821f,
-0.134266f, -0.331843f, -0.008296f, 0.124564f,
0.053712f, -0.369016f, -0.095036f, 0.209381f,
0.423760f, 0.371760f, 0.106397f, 0.369408f,
0.485608f, 0.231201f, -0.138685f, -0.349208f,
-0.070083f, 0.028991f, -0.081630f, -0.395992f,
-0.146791f, -0.027354f, 0.063396f, -0.272484f,
0.058299f, 0.338207f, 0.110767f, -0.052642f,
-0.233848f, -0.027448f, 0.030328f, 0.155572f,
-0.093826f, 0.019331f, 0.120638f, 0.006292f,
-0.106083f, -0.236290f, -0.140933f, -0.088067f,
-0.025138f, -0.208395f, -0.025502f, 0.144192f,
-0.048353f, -0.106144f, -0.305121f, -0.114147f,
0.090963f, 0.327727f, 0.035606f, -0.093779f,
0.002651f, -0.171081f, -0.188131f, -0.216571f,
-0.209101f, -0.054402f, 0.157147f, -0.057127f,
0.066584f, 0.008988f, 0.041191f, 0.034456f,
-0.078255f, 0.052099f, -0.022239f, 0.066981f,
-0.117520f, -0.072637f, 0.062512f, 0.037570f,
-0.057544f, -0.312359f, 0.034357f, -0.031549f,
0.002566f, -0.207375f, -0.070654f, -0.018786f,
-0.044815f, -0.012814f, -0.076320f, 0.078183f,
0.023877f, 0.117078f, 0.022292f, -0.205424f,
-0.060430f, -0.017296f, -0.004827f, -0.321036f,
-0.092155f, 0.038837f, 0.073190f, -0.067513f,
0.026521f, 0.171945f, 0.087318f, 0.034495f,
-0.034089f, 0.154410f, -0.061431f, 0.007435f,
-0.111094f, -0.095976f, 0.014741f, -0.132324f,
-0.029517f, -0.192160f, 0.098667f, 0.020762f,
0.177050f, -0.064510f, -0.054437f, -0.058678f,
-0.001858f, 0.167602f, 0.015735f, 0.054338f,
0.016477f, 0.186381f, -0.010667f, 0.054692f,
0.126742f, 0.013140f, 0.090353f, -0.133608f,
-0.018017f, -0.152619f, 0.027600f, -0.138700f,
-0.050274f, 0.045141f, -0.118731f, 0.094797f,
-0.167605f, 0.097461f, -0.009131f, 0.199920f,
-0.052976f, 0.158194f, 0.178568f, -0.107600f,
0.009671f, -0.084072f, -0.040258f, -0.205673f,
0.102891f, 0.223511f, 0.042699f, 0.118548f,
-0.021274f, 0.110997f, -0.155121f, 0.027696f,
-0.149968f, 0.051552f, -0.129219f, 0.173524f,
0.073972f, -0.189045f, -0.034523f, -0.106655f,
-0.011843f, -0.197381f, 0.219413f, 0.183197f,
-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 vector<float>(detector, detector + sizeof(detector)/sizeof(detector[0]));
}
class HOGConfInvoker : public ParallelLoopBody
{
public:
HOGConfInvoker( const HOGDescriptor* _hog, const Mat& _img,
double _hitThreshold, Size _padding,
std::vector<DetectionROI>* locs,
std::vector<Rect>* _vec, Mutex* _mtx )
{
hog = _hog;
img = _img;
hitThreshold = _hitThreshold;
padding = _padding;
locations = locs;
vec = _vec;
mtx = _mtx;
}
void operator()( const Range& range ) const
{
int i, i1 = range.start, i2 = range.end;
Size maxSz(cvCeil(img.cols/(*locations)[0].scale), cvCeil(img.rows/(*locations)[0].scale));
Mat smallerImgBuf(maxSz, img.type());
vector<Point> dets;
for( i = i1; i < i2; i++ )
{
double scale = (*locations)[i].scale;
Size sz(cvRound(img.cols / scale), cvRound(img.rows / scale));
Mat smallerImg(sz, img.type(), smallerImgBuf.data);
if( sz == img.size() )
smallerImg = Mat(sz, img.type(), img.data, img.step);
else
resize(img, smallerImg, sz);
hog->detectROI(smallerImg, (*locations)[i].locations, dets, (*locations)[i].confidences, hitThreshold, Size(), padding);
Size scaledWinSize = Size(cvRound(hog->winSize.width*scale), cvRound(hog->winSize.height*scale));
mtx->lock();
for( size_t j = 0; j < dets.size(); j++ )
{
vec->push_back(Rect(cvRound(dets[j].x*scale),
cvRound(dets[j].y*scale),
scaledWinSize.width, scaledWinSize.height));
}
mtx->unlock();
}
}
const HOGDescriptor* hog;
Mat img;
double hitThreshold;
std::vector<DetectionROI>* locations;
Size padding;
std::vector<Rect>* vec;
Mutex* mtx;
};
void HOGDescriptor::detectROI(const cv::Mat& img, const vector<cv::Point> &locations,
CV_OUT std::vector<cv::Point>& foundLocations, CV_OUT std::vector<double>& confidences,
double hitThreshold, cv::Size winStride,
cv::Size padding) const
{
foundLocations.clear();
confidences.clear();
if( svmDetector.empty() )
return;
if( locations.empty() )
return;
if( winStride == Size() )
winStride = cellSize;
Size cacheStride(gcd(winStride.width, blockStride.width),
gcd(winStride.height, blockStride.height));
size_t nwindows = locations.size();
padding.width = (int)alignSize(std::max(padding.width, 0), cacheStride.width);
padding.height = (int)alignSize(std::max(padding.height, 0), cacheStride.height);
Size paddedImgSize(img.cols + padding.width*2, img.rows + padding.height*2);
// HOGCache cache(this, img, padding, padding, nwindows == 0, cacheStride);
HOGCache cache(this, img, padding, padding, true, cacheStride);
if( !nwindows )
nwindows = cache.windowsInImage(paddedImgSize, winStride).area();
const HOGCache::BlockData* blockData = &cache.blockData[0];
int nblocks = cache.nblocks.area();
int blockHistogramSize = cache.blockHistogramSize;
size_t dsize = getDescriptorSize();
double rho = svmDetector.size() > dsize ? svmDetector[dsize] : 0;
vector<float> blockHist(blockHistogramSize);
for( size_t i = 0; i < nwindows; i++ )
{
Point pt0;
pt0 = locations[i];
if( pt0.x < -padding.width || pt0.x > img.cols + padding.width - winSize.width ||
pt0.y < -padding.height || pt0.y > img.rows + padding.height - winSize.height )
{
// out of image
confidences.push_back(-10.0);
continue;
}
double s = rho;
const float* svmVec = &svmDetector[0];
int j, k;
for( j = 0; j < nblocks; j++, svmVec += blockHistogramSize )
{
const HOGCache::BlockData& bj = blockData[j];
Point pt = pt0 + bj.imgOffset;
// need to devide this into 4 parts!
const float* vec = cache.getBlock(pt, &blockHist[0]);
for( k = 0; k <= blockHistogramSize - 4; k += 4 )
s += vec[k]*svmVec[k] + vec[k+1]*svmVec[k+1] +
vec[k+2]*svmVec[k+2] + vec[k+3]*svmVec[k+3];
for( ; k < blockHistogramSize; k++ )
s += vec[k]*svmVec[k];
}
// cv::waitKey();
confidences.push_back(s);
if( s >= hitThreshold )
foundLocations.push_back(pt0);
}
}
void HOGDescriptor::detectMultiScaleROI(const cv::Mat& img,
CV_OUT std::vector<cv::Rect>& foundLocations,
std::vector<DetectionROI>& locations,
double hitThreshold,
int groupThreshold) const
{
std::vector<Rect> allCandidates;
Mutex mtx;
parallel_for_(Range(0, (int)locations.size()),
HOGConfInvoker(this, img, hitThreshold, Size(8, 8), &locations, &allCandidates, &mtx));
foundLocations.resize(allCandidates.size());
std::copy(allCandidates.begin(), allCandidates.end(), foundLocations.begin());
cv::groupRectangles(foundLocations, groupThreshold, 0.2);
}
void HOGDescriptor::readALTModel(std::string modelfile)
{
// read model from SVMlight format..
FILE *modelfl;
if ((modelfl = fopen(modelfile.c_str(), "rb")) == NULL)
{
std::string eerr("file not exist");
std::string efile(__FILE__);
std::string efunc(__FUNCTION__);
throw Exception(CV_StsError, eerr, efile, efunc, __LINE__);
}
char version_buffer[10];
if (!fread (&version_buffer,sizeof(char),10,modelfl))
{
std::string eerr("version?");
std::string efile(__FILE__);
std::string efunc(__FUNCTION__);
throw Exception(CV_StsError, eerr, efile, efunc, __LINE__);
}
if(strcmp(version_buffer,"V6.01")) {
std::string eerr("version doesnot match");
std::string efile(__FILE__);
std::string efunc(__FUNCTION__);
throw Exception(CV_StsError, eerr, efile, efunc, __LINE__);
}
/* read version number */
int version = 0;
if (!fread (&version,sizeof(int),1,modelfl))
{ throw Exception(); }
if (version < 200)
{
std::string eerr("version doesnot match");
std::string efile(__FILE__);
std::string efunc(__FUNCTION__);
throw Exception();
}
int kernel_type;
size_t nread;
nread=fread(&(kernel_type),sizeof(int),1,modelfl);
{// ignore these
int poly_degree;
nread=fread(&(poly_degree),sizeof(int),1,modelfl);
double rbf_gamma;
nread=fread(&(rbf_gamma),sizeof(double), 1, modelfl);
double coef_lin;
nread=fread(&(coef_lin),sizeof(double),1,modelfl);
double coef_const;
nread=fread(&(coef_const),sizeof(double),1,modelfl);
int l;
nread=fread(&l,sizeof(int),1,modelfl);
char* custom = new char[l];
nread=fread(custom,sizeof(char),l,modelfl);
delete[] custom;
}
int totwords;
nread=fread(&(totwords),sizeof(int),1,modelfl);
{// ignore these
int totdoc;
nread=fread(&(totdoc),sizeof(int),1,modelfl);
int sv_num;
nread=fread(&(sv_num), sizeof(int),1,modelfl);
}
double linearbias;
nread=fread(&linearbias, sizeof(double), 1, modelfl);
std::vector<float> detector;
detector.clear();
if(kernel_type == 0) { /* linear kernel */
/* save linear wts also */
double *linearwt = new double[totwords+1];
int length = totwords;
nread = fread(linearwt, sizeof(double), totwords + 1, modelfl);
if(nread != static_cast<size_t>(length) + 1)
throw Exception();
for(int i = 0; i < length; i++)
detector.push_back((float)linearwt[i]);
detector.push_back((float)-linearbias);
setSVMDetector(detector);
delete [] linearwt;
} else {
throw Exception();
}
fclose(modelfl);
}
}
Opencv HOG行人檢測 源碼分析(二)
前一篇博客大體講了下思路，對比較難理解的關係有些圖示
http://blog.csdn.net/soidnhp/article/details/11874285
發表評論
所有評論
還沒有人評論，想成為第一個評論的人麼? 請在上方評論欄輸入並且點擊發布.
相關文章