/*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 "precomp.hpp" #include "opencv2/core/core_c.h" #include "opencl_kernels.hpp" #include #include /****************************************************************************************\ 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 { #define NTHREADS 256 enum {DESCR_FORMAT_COL_BY_COL, DESCR_FORMAT_ROW_BY_ROW}; static int numPartsWithin(int size, int part_size, int stride) { return (size - part_size + stride) / stride; } static Size numPartsWithin(cv::Size size, cv::Size part_size, cv::Size stride) { return Size(numPartsWithin(size.width, part_size.width, stride.width), numPartsWithin(size.height, part_size.height, stride.height)); } static size_t getBlockHistogramSize(Size block_size, Size cell_size, int nbins) { Size cells_per_block = Size(block_size.width / cell_size.width, block_size.height / cell_size.height); return (size_t)(nbins * cells_per_block.area()); } 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); } double HOGDescriptor::getWinSigma() const { return winSigma >= 0 ? winSigma : (blockSize.width + blockSize.height)/8.; } 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()); Mat detector_reordered(1, (int)svmDetector.size(), CV_32FC1); size_t block_hist_size = getBlockHistogramSize(blockSize, cellSize, nbins); cv::Size blocks_per_img = numPartsWithin(winSize, blockSize, blockStride); for (int i = 0; i < blocks_per_img.height; ++i) for (int j = 0; j < blocks_per_img.width; ++j) { const float *src = &svmDetector[0] + (j * blocks_per_img.height + i) * block_hist_size; float *dst = (float*)detector_reordered.data + (i * blocks_per_img.width + j) * block_hist_size; for (size_t k = 0; k < block_hist_size; ++k) dst[k] = src[k]; } size_t descriptor_size = getDescriptorSize(); free_coef = svmDetector.size() > descriptor_size ? svmDetector[descriptor_size] : 0; detector_reordered.copyTo(oclSvmDetector); } #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; } 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); // qangle.create(gradsize, CV_8UC2); // [0..nbins-1] - quantized gradient orientation Size wholeSize; Point roiofs; img.locateROI(wholeSize, roiofs); int i, x, y; int cn = img.channels(); Mat_ _lut(1, 256); const float* const lut = &_lut(0,0); #if CV_SSE2 const int indeces[] = { 0, 1, 2, 3 }; __m128i idx = _mm_loadu_si128((const __m128i*)indeces); __m128i ifour = _mm_set1_epi32(4); float* const _data = &_lut(0, 0); if( gammaCorrection ) for( i = 0; i < 256; i += 4 ) { _mm_storeu_ps(_data + i, _mm_sqrt_ps(_mm_cvtepi32_ps(idx))); idx = _mm_add_epi32(idx, ifour); } else for( i = 0; i < 256; i += 4 ) { _mm_storeu_ps(_data + i, _mm_cvtepi32_ps(idx)); idx = _mm_add_epi32(idx, ifour); } #else if( gammaCorrection ) for( i = 0; i < 256; i++ ) _lut(0,i) = std::sqrt((float)i); else for( i = 0; i < 256; i++ ) _lut(0,i) = (float)i; #endif AutoBuffer mapbuf(gradsize.width + gradsize.height + 4); int* xmap = (int*)mapbuf + 1; int* ymap = xmap + gradsize.width + 2; const int borderType = (int)BORDER_REFLECT_101; 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 _dbuf(width*4); float* const 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); if (cn == 3) { int end = gradsize.width + 2; xmap -= 1, x = 0; #if CV_SSE2 __m128i ithree = _mm_set1_epi32(3); for ( ; x <= end - 4; x += 4) _mm_storeu_si128((__m128i*)(xmap + x), _mm_mullo_epi16(ithree, _mm_loadu_si128((const __m128i*)(xmap + x)))); #endif for ( ; x < end; ++x) xmap[x] *= 3; xmap += 1; } float angleScale = (float)(nbins/CV_PI); for( y = 0; y < gradsize.height; y++ ) { 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]; float* gradPtr = (float*)grad.ptr(y); uchar* qanglePtr = (uchar*)qangle.ptr(y); if( cn == 1 ) { for( x = 0; x < width; x++ ) { int x1 = xmap[x]; dbuf[x] = (float)(lut[imgPtr[xmap[x+1]]] - lut[imgPtr[xmap[x-1]]]); dbuf[width + x] = (float)(lut[nextPtr[x1]] - lut[prevPtr[x1]]); } } else { x = 0; #if CV_SSE2 for( ; x <= width - 4; x += 4 ) { int x0 = xmap[x], x1 = xmap[x+1], x2 = xmap[x+2], x3 = xmap[x+3]; typedef const uchar* const T; T p02 = imgPtr + xmap[x+1], p00 = imgPtr + xmap[x-1]; T p12 = imgPtr + xmap[x+2], p10 = imgPtr + xmap[x]; T p22 = imgPtr + xmap[x+3], p20 = p02; T p32 = imgPtr + xmap[x+4], p30 = p12; __m128 _dx0 = _mm_sub_ps(_mm_set_ps(lut[p32[0]], lut[p22[0]], lut[p12[0]], lut[p02[0]]), _mm_set_ps(lut[p30[0]], lut[p20[0]], lut[p10[0]], lut[p00[0]])); __m128 _dx1 = _mm_sub_ps(_mm_set_ps(lut[p32[1]], lut[p22[1]], lut[p12[1]], lut[p02[1]]), _mm_set_ps(lut[p30[1]], lut[p20[1]], lut[p10[1]], lut[p00[1]])); __m128 _dx2 = _mm_sub_ps(_mm_set_ps(lut[p32[2]], lut[p22[2]], lut[p12[2]], lut[p02[2]]), _mm_set_ps(lut[p30[2]], lut[p20[2]], lut[p10[2]], lut[p00[2]])); __m128 _dy0 = _mm_sub_ps(_mm_set_ps(lut[nextPtr[x3]], lut[nextPtr[x2]], lut[nextPtr[x1]], lut[nextPtr[x0]]), _mm_set_ps(lut[prevPtr[x3]], lut[prevPtr[x2]], lut[prevPtr[x1]], lut[prevPtr[x0]])); __m128 _dy1 = _mm_sub_ps(_mm_set_ps(lut[nextPtr[x3+1]], lut[nextPtr[x2+1]], lut[nextPtr[x1+1]], lut[nextPtr[x0+1]]), _mm_set_ps(lut[prevPtr[x3+1]], lut[prevPtr[x2+1]], lut[prevPtr[x1+1]], lut[prevPtr[x0+1]])); __m128 _dy2 = _mm_sub_ps(_mm_set_ps(lut[nextPtr[x3+2]], lut[nextPtr[x2+2]], lut[nextPtr[x1+2]], lut[nextPtr[x0+2]]), _mm_set_ps(lut[prevPtr[x3+2]], lut[prevPtr[x2+2]], lut[prevPtr[x1+2]], lut[prevPtr[x0+2]])); __m128 _mag0 = _mm_add_ps(_mm_mul_ps(_dx0, _dx0), _mm_mul_ps(_dy0, _dy0)); __m128 _mag1 = _mm_add_ps(_mm_mul_ps(_dx1, _dx1), _mm_mul_ps(_dy1, _dy1)); __m128 _mag2 = _mm_add_ps(_mm_mul_ps(_dx2, _dx2), _mm_mul_ps(_dy2, _dy2)); __m128 mask = _mm_cmpgt_ps(_mag2, _mag1); _dx2 = _mm_or_ps(_mm_and_ps(_dx2, mask), _mm_andnot_ps(mask, _dx1)); _dy2 = _mm_or_ps(_mm_and_ps(_dy2, mask), _mm_andnot_ps(mask, _dy1)); mask = _mm_cmpgt_ps(_mm_max_ps(_mag2, _mag1), _mag0); _dx2 = _mm_or_ps(_mm_and_ps(_dx2, mask), _mm_andnot_ps(mask, _dx0)); _dy2 = _mm_or_ps(_mm_and_ps(_dy2, mask), _mm_andnot_ps(mask, _dy0)); _mm_storeu_ps(dbuf + x, _dx2); _mm_storeu_ps(dbuf + x + width, _dy2); } #endif for( ; x < width; x++ ) { int x1 = xmap[x]; float dx0, dy0, dx, dy, mag0, mag; const uchar* p2 = imgPtr + xmap[x+1]; const uchar* p0 = imgPtr + xmap[x-1]; 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; if( mag0 < mag ) { dx0 = dx; dy0 = dy; mag0 = mag; } dbuf[x] = dx0; dbuf[x+width] = dy0; } } // computing angles and magnidutes cartToPolar( Dx, Dy, Mag, Angle, false ); // filling the result matrix x = 0; #if CV_SSE2 __m128 fhalf = _mm_set1_ps(0.5f), fzero = _mm_setzero_ps(); __m128 _angleScale = _mm_set1_ps(angleScale), fone = _mm_set1_ps(1.0f); __m128i ione = _mm_set1_epi32(1), _nbins = _mm_set1_epi32(nbins), izero = _mm_setzero_si128(); for ( ; x <= width - 4; x += 4) { int x2 = x << 1; __m128 _mag = _mm_loadu_ps(dbuf + x + (width << 1)); __m128 _angle = _mm_loadu_ps(dbuf + x + width * 3); _angle = _mm_sub_ps(_mm_mul_ps(_angleScale, _angle), fhalf); __m128 sign = _mm_and_ps(fone, _mm_cmplt_ps(_angle, fzero)); __m128i _hidx = _mm_cvttps_epi32(_angle); _hidx = _mm_sub_epi32(_hidx, _mm_cvtps_epi32(sign)); _angle = _mm_sub_ps(_angle, _mm_cvtepi32_ps(_hidx)); __m128 ft0 = _mm_mul_ps(_mag, _mm_sub_ps(fone, _angle)); __m128 ft1 = _mm_mul_ps(_mag, _angle); __m128 ft2 = _mm_unpacklo_ps(ft0, ft1); __m128 ft3 = _mm_unpackhi_ps(ft0, ft1); _mm_storeu_ps(gradPtr + x2, ft2); _mm_storeu_ps(gradPtr + x2 + 4, ft3); __m128i mask0 = _mm_sub_epi32(izero, _mm_srli_epi32(_hidx, 31)); __m128i it0 = _mm_and_si128(mask0, _nbins); mask0 = _mm_cmplt_epi32(_hidx, _nbins); __m128i it1 = _mm_andnot_si128(mask0, _nbins); _hidx = _mm_add_epi32(_hidx, _mm_sub_epi32(it0, it1)); it0 = _mm_packus_epi16(_mm_packs_epi32(_hidx, izero), izero); _hidx = _mm_add_epi32(ione, _hidx); _hidx = _mm_and_si128(_hidx, _mm_cmplt_epi32(_hidx, _nbins)); it1 = _mm_packus_epi16(_mm_packs_epi32(_hidx, izero), izero); it0 = _mm_unpacklo_epi8(it0, it1); _mm_storel_epi64((__m128i*)(qanglePtr + x2), it0); } #endif for( ; x < width; x++ ) { float mag = dbuf[x+width*2], angle = dbuf[x+width*3]*angleScale - 0.5f; int hidx = cvFloor(angle); angle -= hidx; gradPtr[x*2] = mag*(1.f - angle); gradPtr[x*2+1] = mag*angle; if( hidx < 0 ) hidx += nbins; else if( hidx >= nbins ) hidx -= nbins; CV_Assert( (unsigned)hidx < (unsigned)nbins ); qanglePtr[x*2] = (uchar)hidx; hidx++; hidx &= hidx < nbins ? -1 : 0; 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, const Size& paddingTL, const Size& paddingBR, bool useCache, const Size& cacheStride); virtual ~HOGCache() { } virtual void init(const HOGDescriptor* descriptor, const Mat& img, const Size& paddingTL, const Size& paddingBR, bool useCache, const Size& cacheStride); Size windowsInImage(const Size& imageSize, const Size& winStride) const; Rect getWindow(const Size& imageSize, const Size& winStride, int idx) const; const float* getBlock(Point pt, float* buf); virtual void normalizeBlockHistogram(float* histogram) const; std::vector pixData; std::vector blockData; bool useCache; std::vector ymaxCached; Size winSize; Size cacheStride; Size nblocks, ncells; int blockHistogramSize; int count1, count2, count4; Point imgoffset; Mat_ blockCache; Mat_ blockCacheFlags; Mat grad, qangle; const HOGDescriptor* descriptor; }; HOGCache::HOGCache() : blockHistogramSize(), count1(), count2(), count4() { useCache = false; descriptor = 0; } HOGCache::HOGCache(const HOGDescriptor* _descriptor, const Mat& _img, const Size& _paddingTL, const Size& _paddingBR, bool _useCache, const Size& _cacheStride) { init(_descriptor, _img, _paddingTL, _paddingBR, _useCache, _cacheStride); } void HOGCache::init(const HOGDescriptor* _descriptor, const Mat& _img, const Size& _paddingTL, const Size& _paddingBR, bool _useCache, const Size& _cacheStride) { descriptor = _descriptor; cacheStride = _cacheStride; useCache = _useCache; descriptor->computeGradient(_img, grad, qangle, _paddingTL, _paddingBR); imgoffset = _paddingTL; winSize = descriptor->winSize; Size blockSize = descriptor->blockSize; Size blockStride = descriptor->blockStride; Size cellSize = descriptor->cellSize; int i, j, nbins = descriptor->nbins; int rawBlockSize = blockSize.width*blockSize.height; nblocks = Size((winSize.width - blockSize.width)/blockStride.width + 1, (winSize.height - blockSize.height)/blockStride.height + 1); ncells = Size(blockSize.width/cellSize.width, blockSize.height/cellSize.height); blockHistogramSize = ncells.width*ncells.height*nbins; 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_ weights(blockSize); float sigma = (float)descriptor->getWinSigma(); float scale = 1.f/(sigma*sigma*2); { AutoBuffer di(blockSize.height), dj(blockSize.width); float* _di = (float*)di, *_dj = (float*)dj; float bh = blockSize.height * 0.5f, bw = blockSize.width * 0.5f; i = 0; #if CV_SSE2 const int a[] = { 0, 1, 2, 3 }; __m128i idx = _mm_loadu_si128((__m128i*)a); __m128 _bw = _mm_set1_ps(bw), _bh = _mm_set1_ps(bh); __m128i ifour = _mm_set1_epi32(4); for (; i <= blockSize.height - 4; i += 4) { __m128 t = _mm_sub_ps(_mm_cvtepi32_ps(idx), _bh); t = _mm_mul_ps(t, t); idx = _mm_add_epi32(idx, ifour); _mm_storeu_ps(_di + i, t); } #endif for ( ; i < blockSize.height; ++i) { _di[i] = i - bh; _di[i] *= _di[i]; } j = 0; #if CV_SSE2 idx = _mm_loadu_si128((__m128i*)a); for (; j <= blockSize.width - 4; j += 4) { __m128 t = _mm_sub_ps(_mm_cvtepi32_ps(idx), _bw); t = _mm_mul_ps(t, t); idx = _mm_add_epi32(idx, ifour); _mm_storeu_ps(_dj + j, t); } #endif for ( ; j < blockSize.width; ++j) { _dj[j] = j - bw; _dj[j] *= _dj[j]; } for(i = 0; i < blockSize.height; i++) for(j = 0; j < blockSize.width; j++) weights(i,j) = std::exp(-(_di[i] + _dj[j])*scale); } blockData.resize(nblocks.width*nblocks.height); pixData.resize(rawBlockSize*3); // 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++ ) for( i = 0; i < blockSize.height; i++ ) { PixData* data = 0; float cellX = (j+0.5f)/cellSize.width - 0.5f; float cellY = (i+0.5f)/cellSize.height - 0.5f; int icellX0 = cvFloor(cellX); int icellY0 = cvFloor(cellY); int icellX1 = icellX0 + 1, icellY1 = icellY0 + 1; cellX -= icellX0; cellY -= icellY0; if( (unsigned)icellX0 < (unsigned)ncells.width && (unsigned)icellX1 < (unsigned)ncells.width ) { if( (unsigned)icellY0 < (unsigned)ncells.height && (unsigned)icellY1 < (unsigned)ncells.height ) { data = &pixData[rawBlockSize*2 + (count4++)]; data->histOfs[0] = (icellX0*ncells.height + icellY0)*nbins; data->histWeights[0] = (1.f - cellX)*(1.f - cellY); data->histOfs[1] = (icellX1*ncells.height + icellY0)*nbins; data->histWeights[1] = cellX*(1.f - cellY); data->histOfs[2] = (icellX0*ncells.height + icellY1)*nbins; data->histWeights[2] = (1.f - cellX)*cellY; data->histOfs[3] = (icellX1*ncells.height + icellY1)*nbins; data->histWeights[3] = cellX*cellY; } else { data = &pixData[rawBlockSize + (count2++)]; if( (unsigned)icellY0 < (unsigned)ncells.height ) { icellY1 = icellY0; cellY = 1.f - cellY; } data->histOfs[0] = (icellX0*ncells.height + icellY1)*nbins; data->histWeights[0] = (1.f - cellX)*cellY; data->histOfs[1] = (icellX1*ncells.height + icellY1)*nbins; data->histWeights[1] = cellX*cellY; data->histOfs[2] = data->histOfs[3] = 0; data->histWeights[2] = data->histWeights[3] = 0; } } else { if( (unsigned)icellX0 < (unsigned)ncells.width ) { icellX1 = icellX0; cellX = 1.f - cellX; } if( (unsigned)icellY0 < (unsigned)ncells.height && (unsigned)icellY1 < (unsigned)ncells.height ) { data = &pixData[rawBlockSize + (count2++)]; data->histOfs[0] = (icellX1*ncells.height + icellY0)*nbins; data->histWeights[0] = cellX*(1.f - cellY); data->histOfs[1] = (icellX1*ncells.height + icellY1)*nbins; data->histWeights[1] = cellX*cellY; data->histOfs[2] = data->histOfs[3] = 0; data->histWeights[2] = data->histWeights[3] = 0; } 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; data->qangleOfs = (qangle.cols*i + j)*2; data->gradWeight = weights(i,j); } assert( count1 + count2 + count4 == rawBlockSize ); // defragment pixData 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 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; // CV_Assert( (unsigned)pt.x <= (unsigned)(grad.cols - blockSize.width) && // (unsigned)pt.y <= (unsigned)(grad.rows - blockSize.height) ); if( useCache ) { 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_ 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; const float* gradPtr = (const float*)(grad.data + grad.step*pt.y) + pt.x*2; const uchar* qanglePtr = qangle.data + qangle.step*pt.y + pt.x*2; // CV_Assert( blockHist != 0 ); memset(blockHist, 0, sizeof(float) * blockHistogramSize); const PixData* _pixData = &pixData[0]; for( k = 0; k < C1; k++ ) { const PixData& pk = _pixData[k]; const float* const a = gradPtr + pk.gradOfs; float w = pk.gradWeight*pk.histWeights[0]; const uchar* h = qanglePtr + pk.qangleOfs; int h0 = h[0], h1 = h[1]; float* hist = blockHist + pk.histOfs[0]; float t0 = hist[h0] + a[0]*w; float t1 = hist[h1] + a[1]*w; hist[h0] = t0; hist[h1] = t1; } #if CV_SSE2 float hist0[4], hist1[4]; for( ; k < C2; k++ ) { const PixData& pk = _pixData[k]; const float* const a = gradPtr + pk.gradOfs; const uchar* const h = qanglePtr + pk.qangleOfs; int h0 = h[0], h1 = h[1]; __m128 _a0 = _mm_set1_ps(a[0]), _a1 = _mm_set1_ps(a[1]); __m128 _w = _mm_mul_ps(_mm_set1_ps(pk.gradWeight), _mm_loadu_ps(pk.histWeights)); __m128 _t0 = _mm_mul_ps(_a0, _w), _t1 = _mm_mul_ps(_a1, _w); _mm_storeu_ps(hist0, _t0); _mm_storeu_ps(hist1, _t1); float* hist = blockHist + pk.histOfs[0]; float t0 = hist[h0] + hist0[0]; float t1 = hist[h1] + hist1[0]; hist[h0] = t0; hist[h1] = t1; hist = blockHist + pk.histOfs[1]; t0 = hist[h0] + hist0[1]; t1 = hist[h1] + hist1[1]; hist[h0] = t0; hist[h1] = t1; } #else for( ; k < C2; k++ ) { const PixData& pk = _pixData[k]; const float* const a = gradPtr + pk.gradOfs; float w, t0, t1, a0 = a[0], a1 = a[1]; const uchar* const 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; } #endif #if CV_SSE2 for( ; k < C4; k++ ) { const PixData& pk = _pixData[k]; const float* const a = gradPtr + pk.gradOfs; const uchar* const h = qanglePtr + pk.qangleOfs; int h0 = h[0], h1 = h[1]; __m128 _a0 = _mm_set1_ps(a[0]), _a1 = _mm_set1_ps(a[1]); __m128 _w = _mm_mul_ps(_mm_set1_ps(pk.gradWeight), _mm_loadu_ps(pk.histWeights)); __m128 _t0 = _mm_mul_ps(_a0, _w), _t1 = _mm_mul_ps(_a1, _w); _mm_storeu_ps(hist0, _t0); _mm_storeu_ps(hist1, _t1); float* hist = blockHist + pk.histOfs[0]; float t0 = hist[h0] + hist0[0]; float t1 = hist[h1] + hist1[0]; hist[h0] = t0; hist[h1] = t1; hist = blockHist + pk.histOfs[1]; t0 = hist[h0] + hist0[1]; t1 = hist[h1] + hist1[1]; hist[h0] = t0; hist[h1] = t1; hist = blockHist + pk.histOfs[2]; t0 = hist[h0] + hist0[2]; t1 = hist[h1] + hist1[2]; hist[h0] = t0; hist[h1] = t1; hist = blockHist + pk.histOfs[3]; t0 = hist[h0] + hist0[3]; t1 = hist[h1] + hist1[3]; hist[h0] = t0; hist[h1] = t1; // __m128 _hist0 = _mm_set_ps((blockHist + pk.histOfs[3])[h0], (blockHist + pk.histOfs[2])[h0], // (blockHist + pk.histOfs[1])[h0], (blockHist + pk.histOfs[0])[h0]); // __m128 _hist1 = _mm_set_ps((blockHist + pk.histOfs[3])[h1], (blockHist + pk.histOfs[2])[h1], // (blockHist + pk.histOfs[1])[h1], (blockHist + pk.histOfs[0])[h1]); // // _hist0 = _mm_add_ps(_t0, _hist0); // _hist1 = _mm_add_ps(_t1, _hist1); // // _mm_storeu_ps(hist0, _hist0); // _mm_storeu_ps(hist1, _hist1); // // (pk.histOfs[0] + blockHist)[h0] = hist0[0]; // (pk.histOfs[1] + blockHist)[h0] = hist0[1]; // (pk.histOfs[2] + blockHist)[h0] = hist0[2]; // (pk.histOfs[3] + blockHist)[h0] = hist0[3]; // // (pk.histOfs[0] + blockHist)[h1] = hist1[0]; // (pk.histOfs[1] + blockHist)[h1] = hist1[1]; // (pk.histOfs[2] + blockHist)[h1] = hist1[2]; // (pk.histOfs[3] + blockHist)[h1] = hist1[3]; } #else 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; } #endif normalizeBlockHistogram(blockHist); return blockHist; } void HOGCache::normalizeBlockHistogram(float* _hist) const { float* hist = &_hist[0], sum = 0.0f, partSum[4]; size_t i = 0, sz = blockHistogramSize; #if CV_SSE2 __m128 p0 = _mm_loadu_ps(hist); __m128 s = _mm_mul_ps(p0, p0); for (i = 4; i <= sz - 4; i += 4) { p0 = _mm_loadu_ps(hist + i); s = _mm_add_ps(s, _mm_mul_ps(p0, p0)); } _mm_storeu_ps(partSum, s); #else partSum[0] = 0.0f; partSum[1] = 0.0f; partSum[2] = 0.0f; partSum[3] = 0.0f; for ( ; i <= sz - 4; i += 4) { partSum[0] += hist[i] * hist[i]; partSum[1] += hist[i+1] * hist[i+1]; partSum[2] += hist[i+2] * hist[i+2]; partSum[3] += hist[i+3] * hist[i+3]; } #endif float t0 = partSum[0] + partSum[1]; float t1 = partSum[2] + partSum[3]; sum = t0 + t1; for ( ; i < sz; ++i) sum += hist[i]*hist[i]; float scale = 1.f/(std::sqrt(sum)+sz*0.1f), thresh = (float)descriptor->L2HysThreshold; i = 0, sum = 0.0f; #if CV_SSE2 __m128 _scale = _mm_set1_ps(scale); static __m128 _threshold = _mm_set1_ps(thresh); __m128 p = _mm_mul_ps(_scale, _mm_loadu_ps(hist)); p = _mm_min_ps(p, _threshold); s = _mm_mul_ps(p, p); _mm_storeu_ps(hist, p); for(i = 4 ; i <= sz - 4; i += 4) { p = _mm_loadu_ps(hist + i); p = _mm_mul_ps(p, _scale); p = _mm_min_ps(p, _threshold); s = _mm_add_ps(s, _mm_mul_ps(p, p)); _mm_storeu_ps(hist + i, p); } _mm_storeu_ps(partSum, s); #else partSum[0] = 0.0f; partSum[1] = 0.0f; partSum[2] = 0.0f; partSum[3] = 0.0f; for( ; i <= sz - 4; i += 4) { hist[i] = std::min(hist[i]*scale, thresh); hist[i+1] = std::min(hist[i+1]*scale, thresh); hist[i+2] = std::min(hist[i+2]*scale, thresh); hist[i+3] = std::min(hist[i+3]*scale, thresh); partSum[0] += hist[i]*hist[i]; partSum[1] += hist[i+1]*hist[i+1]; partSum[2] += hist[i+2]*hist[i+2]; partSum[3] += hist[i+3]*hist[i+3]; } #endif t0 = partSum[0] + partSum[1]; t1 = partSum[2] + partSum[3]; sum = t0 + t1; for( ; i < sz; ++i) { hist[i] = std::min(hist[i]*scale, thresh); sum += hist[i]*hist[i]; } scale = 1.f/(std::sqrt(sum)+1e-3f), i = 0; #if CV_SSE2 __m128 _scale2 = _mm_set1_ps(scale); for ( ; i <= sz - 4; i += 4) { __m128 t = _mm_mul_ps(_scale2, _mm_loadu_ps(hist + i)); _mm_storeu_ps(hist + i, t); } #endif for ( ; i < sz; ++i) hist[i] *= scale; } Size HOGCache::windowsInImage(const Size& imageSize, const Size& winStride) const { return Size((imageSize.width - winSize.width)/winStride.width + 1, (imageSize.height - winSize.height)/winStride.height + 1); } Rect HOGCache::getWindow(const Size& imageSize, const 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 ); } static inline int gcd(int a, int b) { if( a < b ) std::swap(a, b); while( b > 0 ) { int r = a % b; a = b; b = r; } return a; } #ifdef HAVE_OPENCL static bool ocl_compute_gradients_8UC1(int height, int width, InputArray _img, float angle_scale, UMat grad, UMat qangle, bool correct_gamma, int nbins) { ocl::Kernel k("compute_gradients_8UC1_kernel", ocl::objdetect::objdetect_hog_oclsrc); if(k.empty()) return false; UMat img = _img.getUMat(); size_t localThreads[3] = { NTHREADS, 1, 1 }; size_t globalThreads[3] = { width, height, 1 }; char correctGamma = (correct_gamma) ? 1 : 0; int grad_quadstep = (int)grad.step >> 3; int qangle_elem_size = CV_ELEM_SIZE1(qangle.type()); int qangle_step = (int)qangle.step / (2 * qangle_elem_size); int idx = 0; idx = k.set(idx, height); idx = k.set(idx, width); idx = k.set(idx, (int)img.step1()); idx = k.set(idx, grad_quadstep); idx = k.set(idx, qangle_step); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(img)); idx = k.set(idx, ocl::KernelArg::PtrWriteOnly(grad)); idx = k.set(idx, ocl::KernelArg::PtrWriteOnly(qangle)); idx = k.set(idx, angle_scale); idx = k.set(idx, correctGamma); idx = k.set(idx, nbins); return k.run(2, globalThreads, localThreads, false); } static bool ocl_computeGradient(InputArray img, UMat grad, UMat qangle, int nbins, Size effect_size, bool gamma_correction) { float angleScale = (float)(nbins / CV_PI); return ocl_compute_gradients_8UC1(effect_size.height, effect_size.width, img, angleScale, grad, qangle, gamma_correction, nbins); } #define CELL_WIDTH 8 #define CELL_HEIGHT 8 #define CELLS_PER_BLOCK_X 2 #define CELLS_PER_BLOCK_Y 2 static bool ocl_compute_hists(int nbins, int block_stride_x, int block_stride_y, int height, int width, UMat grad, UMat qangle, UMat gauss_w_lut, UMat block_hists, size_t block_hist_size) { ocl::Kernel k("compute_hists_lut_kernel", ocl::objdetect::objdetect_hog_oclsrc); if(k.empty()) return false; bool is_cpu = cv::ocl::Device::getDefault().type() == cv::ocl::Device::TYPE_CPU; cv::String opts; if(is_cpu) opts = "-D CPU "; else opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); k.create("compute_hists_lut_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); if(k.empty()) return false; int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x)/block_stride_x; int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y)/block_stride_y; int blocks_total = img_block_width * img_block_height; int qangle_elem_size = CV_ELEM_SIZE1(qangle.type()); int grad_quadstep = (int)grad.step >> 2; int qangle_step = (int)qangle.step / qangle_elem_size; int blocks_in_group = 4; size_t localThreads[3] = { blocks_in_group * 24, 2, 1 }; size_t globalThreads[3] = {((img_block_width * img_block_height + blocks_in_group - 1)/blocks_in_group) * localThreads[0], 2, 1 }; int hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y * 12) * sizeof(float); int final_hists_size = (nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y) * sizeof(float); int smem = (hists_size + final_hists_size) * blocks_in_group; int idx = 0; idx = k.set(idx, block_stride_x); idx = k.set(idx, block_stride_y); idx = k.set(idx, nbins); idx = k.set(idx, (int)block_hist_size); idx = k.set(idx, img_block_width); idx = k.set(idx, blocks_in_group); idx = k.set(idx, blocks_total); idx = k.set(idx, grad_quadstep); idx = k.set(idx, qangle_step); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(grad)); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(qangle)); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(gauss_w_lut)); idx = k.set(idx, ocl::KernelArg::PtrWriteOnly(block_hists)); idx = k.set(idx, (void*)NULL, (size_t)smem); return k.run(2, globalThreads, localThreads, false); } static int power_2up(unsigned int n) { for(unsigned int i = 1; i<=1024; i<<=1) if(n < i) return i; return -1; // Input is too big } static bool ocl_normalize_hists(int nbins, int block_stride_x, int block_stride_y, int height, int width, UMat block_hists, float threshold) { int block_hist_size = nbins * CELLS_PER_BLOCK_X * CELLS_PER_BLOCK_Y; int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x; int img_block_height = (height - CELLS_PER_BLOCK_Y * CELL_HEIGHT + block_stride_y) / block_stride_y; int nthreads; size_t globalThreads[3] = { 1, 1, 1 }; size_t localThreads[3] = { 1, 1, 1 }; int idx = 0; bool is_cpu = cv::ocl::Device::getDefault().type() == cv::ocl::Device::TYPE_CPU; cv::String opts; ocl::Kernel k; if ( nbins == 9 ) { k.create("normalize_hists_36_kernel", ocl::objdetect::objdetect_hog_oclsrc, ""); if(k.empty()) return false; if(is_cpu) opts = "-D CPU "; else opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); k.create("normalize_hists_36_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); if(k.empty()) return false; int blocks_in_group = NTHREADS / block_hist_size; nthreads = blocks_in_group * block_hist_size; int num_groups = (img_block_width * img_block_height + blocks_in_group - 1)/blocks_in_group; globalThreads[0] = nthreads * num_groups; localThreads[0] = nthreads; } else { k.create("normalize_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, ""); if(k.empty()) return false; if(is_cpu) opts = "-D CPU "; else opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); k.create("normalize_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); if(k.empty()) return false; nthreads = power_2up(block_hist_size); globalThreads[0] = img_block_width * nthreads; globalThreads[1] = img_block_height; localThreads[0] = nthreads; if ((nthreads < 32) || (nthreads > 512) ) return false; idx = k.set(idx, nthreads); idx = k.set(idx, block_hist_size); idx = k.set(idx, img_block_width); } idx = k.set(idx, ocl::KernelArg::PtrReadWrite(block_hists)); idx = k.set(idx, threshold); idx = k.set(idx, (void*)NULL, nthreads * sizeof(float)); return k.run(2, globalThreads, localThreads, false); } static bool ocl_extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, int block_stride_x, int win_stride_y, int win_stride_x, int height, int width, UMat block_hists, UMat descriptors, int block_hist_size, int descr_size, int descr_width) { ocl::Kernel k("extract_descrs_by_rows_kernel", ocl::objdetect::objdetect_hog_oclsrc); if(k.empty()) return false; int win_block_stride_x = win_stride_x / block_stride_x; int win_block_stride_y = win_stride_y / block_stride_y; int img_win_width = (width - win_width + win_stride_x) / win_stride_x; int img_win_height = (height - win_height + win_stride_y) / win_stride_y; int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x; int descriptors_quadstep = (int)descriptors.step >> 2; size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 }; size_t localThreads[3] = { NTHREADS, 1, 1 }; int idx = 0; idx = k.set(idx, block_hist_size); idx = k.set(idx, descriptors_quadstep); idx = k.set(idx, descr_size); idx = k.set(idx, descr_width); idx = k.set(idx, img_block_width); idx = k.set(idx, win_block_stride_x); idx = k.set(idx, win_block_stride_y); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(block_hists)); idx = k.set(idx, ocl::KernelArg::PtrWriteOnly(descriptors)); return k.run(2, globalThreads, localThreads, false); } static bool ocl_extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, int block_stride_x, int win_stride_y, int win_stride_x, int height, int width, UMat block_hists, UMat descriptors, int block_hist_size, int descr_size, int nblocks_win_x, int nblocks_win_y) { ocl::Kernel k("extract_descrs_by_cols_kernel", ocl::objdetect::objdetect_hog_oclsrc); if(k.empty()) return false; int win_block_stride_x = win_stride_x / block_stride_x; int win_block_stride_y = win_stride_y / block_stride_y; int img_win_width = (width - win_width + win_stride_x) / win_stride_x; int img_win_height = (height - win_height + win_stride_y) / win_stride_y; int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x; int descriptors_quadstep = (int)descriptors.step >> 2; size_t globalThreads[3] = { img_win_width * NTHREADS, img_win_height, 1 }; size_t localThreads[3] = { NTHREADS, 1, 1 }; int idx = 0; idx = k.set(idx, block_hist_size); idx = k.set(idx, descriptors_quadstep); idx = k.set(idx, descr_size); idx = k.set(idx, nblocks_win_x); idx = k.set(idx, nblocks_win_y); idx = k.set(idx, img_block_width); idx = k.set(idx, win_block_stride_x); idx = k.set(idx, win_block_stride_y); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(block_hists)); idx = k.set(idx, ocl::KernelArg::PtrWriteOnly(descriptors)); return k.run(2, globalThreads, localThreads, false); } static bool ocl_compute(InputArray _img, Size win_stride, std::vector& _descriptors, int descr_format, Size blockSize, Size cellSize, int nbins, Size blockStride, Size winSize, float sigma, bool gammaCorrection, double L2HysThreshold) { Size imgSize = _img.size(); Size effect_size = imgSize; UMat grad(imgSize, CV_32FC2); int qangle_type = ocl::Device::getDefault().isIntel() ? CV_32SC2 : CV_8UC2; UMat qangle(imgSize, qangle_type); const size_t block_hist_size = getBlockHistogramSize(blockSize, cellSize, nbins); const Size blocks_per_img = numPartsWithin(imgSize, blockSize, blockStride); UMat block_hists(1, static_cast(block_hist_size * blocks_per_img.area()) + 256, CV_32F); Size wins_per_img = numPartsWithin(imgSize, winSize, win_stride); UMat labels(1, wins_per_img.area(), CV_8U); float scale = 1.f / (2.f * sigma * sigma); Mat gaussian_lut(1, 512, CV_32FC1); int idx = 0; for(int i=-8; i<8; i++) for(int j=-8; j<8; j++) gaussian_lut.at(idx++) = std::exp(-(j * j + i * i) * scale); for(int i=-8; i<8; i++) for(int j=-8; j<8; j++) gaussian_lut.at(idx++) = (8.f - fabs(j + 0.5f)) * (8.f - fabs(i + 0.5f)) / 64.f; if(!ocl_computeGradient(_img, grad, qangle, nbins, effect_size, gammaCorrection)) return false; UMat gauss_w_lut; gaussian_lut.copyTo(gauss_w_lut); if(!ocl_compute_hists(nbins, blockStride.width, blockStride.height, effect_size.height, effect_size.width, grad, qangle, gauss_w_lut, block_hists, block_hist_size)) return false; if(!ocl_normalize_hists(nbins, blockStride.width, blockStride.height, effect_size.height, effect_size.width, block_hists, (float)L2HysThreshold)) return false; Size blocks_per_win = numPartsWithin(winSize, blockSize, blockStride); wins_per_img = numPartsWithin(effect_size, winSize, win_stride); int descr_size = blocks_per_win.area()*(int)block_hist_size; int descr_width = (int)block_hist_size*blocks_per_win.width; UMat descriptors(wins_per_img.area(), static_cast(blocks_per_win.area() * block_hist_size), CV_32F); switch (descr_format) { case DESCR_FORMAT_ROW_BY_ROW: if(!ocl_extract_descrs_by_rows(winSize.height, winSize.width, blockStride.height, blockStride.width, win_stride.height, win_stride.width, effect_size.height, effect_size.width, block_hists, descriptors, (int)block_hist_size, descr_size, descr_width)) return false; break; case DESCR_FORMAT_COL_BY_COL: if(!ocl_extract_descrs_by_cols(winSize.height, winSize.width, blockStride.height, blockStride.width, win_stride.height, win_stride.width, effect_size.height, effect_size.width, block_hists, descriptors, (int)block_hist_size, descr_size, blocks_per_win.width, blocks_per_win.height)) return false; break; default: return false; } descriptors.reshape(1, (int)descriptors.total()).getMat(ACCESS_READ).copyTo(_descriptors); return true; } #endif //HAVE_OPENCL void HOGDescriptor::compute(InputArray _img, std::vector& descriptors, Size winStride, Size padding, const std::vector& locations) const { if( winStride == Size() ) winStride = cellSize; Size cacheStride(gcd(winStride.width, blockStride.width), gcd(winStride.height, blockStride.height)); Size imgSize = _img.size(); 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(imgSize.width + padding.width*2, imgSize.height + padding.height*2); CV_OCL_RUN(_img.dims() <= 2 && _img.type() == CV_8UC1 && _img.isUMat(), ocl_compute(_img, winStride, descriptors, DESCR_FORMAT_COL_BY_COL, blockSize, cellSize, nbins, blockStride, winSize, (float)getWinSigma(), gammaCorrection, L2HysThreshold)) Mat img = _img.getMat(); 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(); descriptors.resize(dsize*nwindows); // for each window 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 { 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 ) memcpy(dst, src, blockHistogramSize * sizeof(float)); } } } void HOGDescriptor::detect(const Mat& img, std::vector& hits, std::vector& weights, double hitThreshold, Size winStride, Size padding, const std::vector& locations) const { hits.clear(); if( svmDetector.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); 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; std::vector blockHist(blockHistogramSize); #if CV_SSE2 float partSum[4]; #endif 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 { 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]; int j, k; for( j = 0; j < nblocks; j++, svmVec += blockHistogramSize ) { const HOGCache::BlockData& bj = blockData[j]; Point pt = pt0 + bj.imgOffset; const float* vec = cache.getBlock(pt, &blockHist[0]); #if CV_SSE2 __m128 _vec = _mm_loadu_ps(vec); __m128 _svmVec = _mm_loadu_ps(svmVec); __m128 sum = _mm_mul_ps(_svmVec, _vec); for( k = 4; k <= blockHistogramSize - 4; k += 4 ) { _vec = _mm_loadu_ps(vec + k); _svmVec = _mm_loadu_ps(svmVec + k); sum = _mm_add_ps(sum, _mm_mul_ps(_vec, _svmVec)); } _mm_storeu_ps(partSum, sum); double t0 = partSum[0] + partSum[1]; double t1 = partSum[2] + partSum[3]; s += t0 + t1; #else 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]; #endif for( ; k < blockHistogramSize; k++ ) s += vec[k]*svmVec[k]; } if( s >= hitThreshold ) { hits.push_back(pt0); weights.push_back(s); } } } void HOGDescriptor::detect(const Mat& img, std::vector& hits, double hitThreshold, Size winStride, Size padding, const std::vector& locations) const { std::vector weightsV; detect(img, hits, weightsV, hitThreshold, winStride, padding, locations); } class HOGInvoker : public ParallelLoopBody { public: HOGInvoker( const HOGDescriptor* _hog, const Mat& _img, double _hitThreshold, const Size& _winStride, const Size& _padding, const double* _levelScale, std::vector * _vec, Mutex* _mtx, std::vector* _weights=0, std::vector* _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()); std::vector locations; std::vector hitsWeights; for( i = i1; i < i2; i++ ) { double scale = levelScale[i]; 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->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)); 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(); } } } private: const HOGDescriptor* hog; Mat img; double hitThreshold; Size winStride; Size padding; const double* levelScale; std::vector* vec; std::vector* weights; std::vector* scales; Mutex* mtx; }; #ifdef HAVE_OPENCL static bool ocl_classify_hists(int win_height, int win_width, int block_stride_y, int block_stride_x, int win_stride_y, int win_stride_x, int height, int width, const UMat& block_hists, UMat detector, float free_coef, float threshold, UMat& labels, Size descr_size, int block_hist_size) { int nthreads; bool is_cpu = cv::ocl::Device::getDefault().type() == cv::ocl::Device::TYPE_CPU; cv::String opts; ocl::Kernel k; int idx = 0; switch (descr_size.width) { case 180: nthreads = 180; k.create("classify_hists_180_kernel", ocl::objdetect::objdetect_hog_oclsrc, ""); if(k.empty()) return false; if(is_cpu) opts = "-D CPU "; else opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); k.create("classify_hists_180_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); if(k.empty()) return false; idx = k.set(idx, descr_size.width); idx = k.set(idx, descr_size.height); break; case 252: nthreads = 256; k.create("classify_hists_252_kernel", ocl::objdetect::objdetect_hog_oclsrc, ""); if(k.empty()) return false; if(is_cpu) opts = "-D CPU "; else opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); k.create("classify_hists_252_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); if(k.empty()) return false; idx = k.set(idx, descr_size.width); idx = k.set(idx, descr_size.height); break; default: nthreads = 256; k.create("classify_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, ""); if(k.empty()) return false; if(is_cpu) opts = "-D CPU "; else opts = cv::format("-D WAVE_SIZE=%d", k.preferedWorkGroupSizeMultiple()); k.create("classify_hists_kernel", ocl::objdetect::objdetect_hog_oclsrc, opts); if(k.empty()) return false; idx = k.set(idx, descr_size.area()); idx = k.set(idx, descr_size.height); } int win_block_stride_x = win_stride_x / block_stride_x; int win_block_stride_y = win_stride_y / block_stride_y; int img_win_width = (width - win_width + win_stride_x) / win_stride_x; int img_win_height = (height - win_height + win_stride_y) / win_stride_y; int img_block_width = (width - CELLS_PER_BLOCK_X * CELL_WIDTH + block_stride_x) / block_stride_x; size_t globalThreads[3] = { img_win_width * nthreads, img_win_height, 1 }; size_t localThreads[3] = { nthreads, 1, 1 }; idx = k.set(idx, block_hist_size); idx = k.set(idx, img_win_width); idx = k.set(idx, img_block_width); idx = k.set(idx, win_block_stride_x); idx = k.set(idx, win_block_stride_y); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(block_hists)); idx = k.set(idx, ocl::KernelArg::PtrReadOnly(detector)); idx = k.set(idx, free_coef); idx = k.set(idx, threshold); idx = k.set(idx, ocl::KernelArg::PtrWriteOnly(labels)); return k.run(2, globalThreads, localThreads, false); } static bool ocl_detect(InputArray img, std::vector &hits, double hit_threshold, Size win_stride, const UMat& oclSvmDetector, Size blockSize, Size cellSize, int nbins, Size blockStride, Size winSize, bool gammaCorrection, double L2HysThreshold, float sigma, float free_coef) { hits.clear(); if (oclSvmDetector.empty()) return false; Size imgSize = img.size(); Size effect_size = imgSize; UMat grad(imgSize, CV_32FC2); int qangle_type = ocl::Device::getDefault().isIntel() ? CV_32SC2 : CV_8UC2; UMat qangle(imgSize, qangle_type); const size_t block_hist_size = getBlockHistogramSize(blockSize, cellSize, nbins); const Size blocks_per_img = numPartsWithin(imgSize, blockSize, blockStride); UMat block_hists(1, static_cast(block_hist_size * blocks_per_img.area()) + 256, CV_32F); Size wins_per_img = numPartsWithin(imgSize, winSize, win_stride); UMat labels(1, wins_per_img.area(), CV_8U); float scale = 1.f / (2.f * sigma * sigma); Mat gaussian_lut(1, 512, CV_32FC1); int idx = 0; for(int i=-8; i<8; i++) for(int j=-8; j<8; j++) gaussian_lut.at(idx++) = std::exp(-(j * j + i * i) * scale); for(int i=-8; i<8; i++) for(int j=-8; j<8; j++) gaussian_lut.at(idx++) = (8.f - fabs(j + 0.5f)) * (8.f - fabs(i + 0.5f)) / 64.f; if(!ocl_computeGradient(img, grad, qangle, nbins, effect_size, gammaCorrection)) return false; UMat gauss_w_lut; gaussian_lut.copyTo(gauss_w_lut); if(!ocl_compute_hists(nbins, blockStride.width, blockStride.height, effect_size.height, effect_size.width, grad, qangle, gauss_w_lut, block_hists, block_hist_size)) return false; if(!ocl_normalize_hists(nbins, blockStride.width, blockStride.height, effect_size.height, effect_size.width, block_hists, (float)L2HysThreshold)) return false; Size blocks_per_win = numPartsWithin(winSize, blockSize, blockStride); Size descr_size((int)block_hist_size*blocks_per_win.width, blocks_per_win.height); if(!ocl_classify_hists(winSize.height, winSize.width, blockStride.height, blockStride.width, win_stride.height, win_stride.width, effect_size.height, effect_size.width, block_hists, oclSvmDetector, free_coef, (float)hit_threshold, labels, descr_size, (int)block_hist_size)) return false; Mat labels_host = labels.getMat(ACCESS_READ); unsigned char *vec = labels_host.ptr(); for (int i = 0; i < wins_per_img.area(); i++) { int y = i / wins_per_img.width; int x = i - wins_per_img.width * y; if (vec[i]) { hits.push_back(Point(x * win_stride.width, y * win_stride.height)); } } return true; } static bool ocl_detectMultiScale(InputArray _img, std::vector &found_locations, std::vector& level_scale, double hit_threshold, Size win_stride, double group_threshold, const UMat& oclSvmDetector, Size blockSize, Size cellSize, int nbins, Size blockStride, Size winSize, bool gammaCorrection, double L2HysThreshold, float sigma, float free_coef) { std::vector all_candidates; std::vector locations; UMat image_scale; Size imgSize = _img.size(); image_scale.create(imgSize, _img.type()); for (size_t i = 0; i& foundLocations, std::vector& foundWeights, double hitThreshold, Size winStride, Size padding, double scale0, double finalThreshold, bool useMeanshiftGrouping) const { double scale = 1.; int levels = 0; Size imgSize = _img.size(); std::vector levelScale; for( levels = 0; levels < nlevels; levels++ ) { levelScale.push_back(scale); if( cvRound(imgSize.width/scale) < winSize.width || cvRound(imgSize.height/scale) < winSize.height || scale0 <= 1 ) break; scale *= scale0; } levels = std::max(levels, 1); levelScale.resize(levels); if(winStride == Size()) winStride = blockStride; CV_OCL_RUN(_img.dims() <= 2 && _img.type() == CV_8UC1 && scale0 > 1 && winStride.width % blockStride.width == 0 && winStride.height % blockStride.height == 0 && padding == Size(0,0) && _img.isUMat(), ocl_detectMultiScale(_img, foundLocations, levelScale, hitThreshold, winStride, finalThreshold, oclSvmDetector, blockSize, cellSize, nbins, blockStride, winSize, gammaCorrection, L2HysThreshold, (float)getWinSigma(), free_coef)); std::vector allCandidates; std::vector tempScales; std::vector tempWeights; std::vector foundScales; Mutex mtx; Mat img = _img.getMat(); Range range(0, (int)levelScale.size()); HOGInvoker invoker(this, img, hitThreshold, winStride, padding, &levelScale[0], &allCandidates, &mtx, &tempWeights, &tempScales); parallel_for_(range, invoker); std::copy(tempScales.begin(), tempScales.end(), back_inserter(foundScales)); 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, foundWeights, (int)finalThreshold, 0.2); } void HOGDescriptor::detectMultiScale(InputArray img, std::vector& foundLocations, double hitThreshold, Size winStride, Size padding, double scale0, double finalThreshold, bool useMeanshiftGrouping) const { std::vector foundWeights; detectMultiScale(img, foundLocations, foundWeights, hitThreshold, winStride, padding, scale0, finalThreshold, useMeanshiftGrouping); } template struct RTTIImpl { public: static int isInstance(const void* ptr) { static _ClsName dummy; static void* dummyp = &dummy; union { const void* p; const void** pp; } a, b; a.p = dummyp; b.p = ptr; return *a.pp == *b.pp; } static void release(void** dbptr) { if(dbptr && *dbptr) { delete (_ClsName*)*dbptr; *dbptr = 0; } } static void* read(CvFileStorage* fs, CvFileNode* n) { FileNode fn(fs, n); _ClsName* obj = new _ClsName; if(obj->read(fn)) return obj; delete obj; return 0; } static void write(CvFileStorage* _fs, const char* name, const void* ptr, CvAttrList) { if(ptr && _fs) { FileStorage fs(_fs, false); ((const _ClsName*)ptr)->write(fs, String(name)); } } static void* clone(const void* ptr) { if(!ptr) return 0; return new _ClsName(*(const _ClsName*)ptr); } }; typedef RTTIImpl HOGRTTI; CvType hog_type( CV_TYPE_NAME_HOG_DESCRIPTOR, HOGRTTI::isInstance, HOGRTTI::release, HOGRTTI::read, HOGRTTI::write, HOGRTTI::clone); std::vector 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 std::vector(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) std::vector 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 std::vector(detector, detector + sizeof(detector)/sizeof(detector[0])); } class HOGConfInvoker : public ParallelLoopBody { public: HOGConfInvoker( const HOGDescriptor* _hog, const Mat& _img, double _hitThreshold, const Size& _padding, std::vector* locs, std::vector* _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()); std::vector 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* locations; Size padding; std::vector* vec; Mutex* mtx; }; void HOGDescriptor::detectROI(const cv::Mat& img, const std::vector &locations, CV_OUT std::vector& foundLocations, CV_OUT std::vector& confidences, double hitThreshold, cv::Size winStride, cv::Size padding) const { foundLocations.clear(); confidences.clear(); if( svmDetector.empty() || 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; std::vector blockHist(blockHistogramSize); #if CV_SSE2 float partSum[4]; #endif 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]); #if CV_SSE2 __m128 _vec = _mm_loadu_ps(vec); __m128 _svmVec = _mm_loadu_ps(svmVec); __m128 sum = _mm_mul_ps(_svmVec, _vec); for( k = 4; k <= blockHistogramSize - 4; k += 4 ) { _vec = _mm_loadu_ps(vec + k); _svmVec = _mm_loadu_ps(svmVec + k); sum = _mm_add_ps(sum, _mm_mul_ps(_vec, _svmVec)); } _mm_storeu_ps(partSum, sum); double t0 = partSum[0] + partSum[1]; double t1 = partSum[2] + partSum[3]; s += t0 + t1; #else 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]; #endif for( ; k < blockHistogramSize; k++ ) s += vec[k]*svmVec[k]; } confidences.push_back(s); if( s >= hitThreshold ) foundLocations.push_back(pt0); } } void HOGDescriptor::detectMultiScaleROI(const cv::Mat& img, CV_OUT std::vector& foundLocations, std::vector& locations, double hitThreshold, int groupThreshold) const { std::vector 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(String modelfile) { // read model from SVMlight format.. FILE *modelfl; if ((modelfl = fopen(modelfile.c_str(), "rb")) == NULL) { String eerr("file not exist"); String efile(__FILE__); String efunc(__FUNCTION__); throw Exception(Error::StsError, eerr, efile, efunc, __LINE__); } char version_buffer[10]; if (!fread (&version_buffer,sizeof(char),10,modelfl)) { String eerr("version?"); String efile(__FILE__); String efunc(__FUNCTION__); throw Exception(Error::StsError, eerr, efile, efunc, __LINE__); } if(strcmp(version_buffer,"V6.01")) { String eerr("version doesnot match"); String efile(__FILE__); String efunc(__FUNCTION__); throw Exception(Error::StsError, eerr, efile, efunc, __LINE__); } /* read version number */ int version = 0; if (!fread (&version,sizeof(int),1,modelfl)) { throw Exception(); } if (version < 200) { String eerr("version doesnot match"); String efile(__FILE__); 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 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(length) + 1) { delete [] linearwt; 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); } void HOGDescriptor::groupRectangles(std::vector& rectList, std::vector& weights, int groupThreshold, double eps) const { if( groupThreshold <= 0 || rectList.empty() ) { return; } CV_Assert(rectList.size() == weights.size()); std::vector labels; int nclasses = partition(rectList, labels, SimilarRects(eps)); std::vector > rrects(nclasses); std::vector numInClass(nclasses, 0); std::vector foundWeights(nclasses, DBL_MIN); int i, j, nlabels = (int)labels.size(); for( i = 0; i < nlabels; i++ ) { int cls = labels[i]; rrects[cls].x += rectList[i].x; rrects[cls].y += rectList[i].y; rrects[cls].width += rectList[i].width; rrects[cls].height += rectList[i].height; foundWeights[cls] = max(foundWeights[cls], weights[i]); numInClass[cls]++; } for( i = 0; i < nclasses; i++ ) { // find the average of all ROI in the cluster cv::Rect_ r = rrects[i]; double s = 1.0/numInClass[i]; rrects[i] = cv::Rect_(cv::saturate_cast(r.x*s), cv::saturate_cast(r.y*s), cv::saturate_cast(r.width*s), cv::saturate_cast(r.height*s)); } rectList.clear(); weights.clear(); for( i = 0; i < nclasses; i++ ) { cv::Rect r1 = rrects[i]; int n1 = numInClass[i]; double w1 = foundWeights[i]; if( n1 <= groupThreshold ) continue; // filter out small rectangles inside large rectangles for( j = 0; j < nclasses; j++ ) { int n2 = numInClass[j]; if( j == i || n2 <= groupThreshold ) continue; cv::Rect r2 = rrects[j]; int dx = cv::saturate_cast( r2.width * eps ); int dy = cv::saturate_cast( r2.height * eps ); if( r1.x >= r2.x - dx && r1.y >= r2.y - dy && r1.x + r1.width <= r2.x + r2.width + dx && r1.y + r1.height <= r2.y + r2.height + dy && (n2 > std::max(3, n1) || n1 < 3) ) break; } if( j == nclasses ) { rectList.push_back(r1); weights.push_back(w1); } } } }