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#include "opencv2/core.hpp"
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#include "opencv2/imgproc.hpp"
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#include "lbpfeatures.h"
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#include "cascadeclassifier.h"
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using namespace cv;
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CvLBPFeatureParams::CvLBPFeatureParams()
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{
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maxCatCount = 256;
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name = LBPF_NAME;
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}
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void CvLBPEvaluator::init(const CvFeatureParams *_featureParams, int _maxSampleCount, Size _winSize)
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{
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CV_Assert( _maxSampleCount > 0);
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sum.create((int)_maxSampleCount, (_winSize.width + 1) * (_winSize.height + 1), CV_32SC1);
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CvFeatureEvaluator::init( _featureParams, _maxSampleCount, _winSize );
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}
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void CvLBPEvaluator::setImage(const Mat &img, uchar clsLabel, int idx)
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{
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CV_DbgAssert( !sum.empty() );
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CvFeatureEvaluator::setImage( img, clsLabel, idx );
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Mat innSum(winSize.height + 1, winSize.width + 1, sum.type(), sum.ptr<int>((int)idx));
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integral( img, innSum );
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}
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void CvLBPEvaluator::writeFeatures( FileStorage &fs, const Mat& featureMap ) const
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{
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_writeFeatures( features, fs, featureMap );
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}
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void CvLBPEvaluator::generateFeatures()
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{
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int offset = winSize.width + 1;
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for( int x = 0; x < winSize.width; x++ )
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for( int y = 0; y < winSize.height; y++ )
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for( int w = 1; w <= winSize.width / 3; w++ )
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for( int h = 1; h <= winSize.height / 3; h++ )
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if ( (x+3*w <= winSize.width) && (y+3*h <= winSize.height) )
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features.push_back( Feature(offset, x, y, w, h ) );
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numFeatures = (int)features.size();
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}
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CvLBPEvaluator::Feature::Feature()
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{
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rect = cvRect(0, 0, 0, 0);
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}
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CvLBPEvaluator::Feature::Feature( int offset, int x, int y, int _blockWidth, int _blockHeight )
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{
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Rect tr = rect = cvRect(x, y, _blockWidth, _blockHeight);
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CV_SUM_OFFSETS( p[0], p[1], p[4], p[5], tr, offset )
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tr.x += 2*rect.width;
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CV_SUM_OFFSETS( p[2], p[3], p[6], p[7], tr, offset )
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tr.y +=2*rect.height;
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CV_SUM_OFFSETS( p[10], p[11], p[14], p[15], tr, offset )
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tr.x -= 2*rect.width;
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CV_SUM_OFFSETS( p[8], p[9], p[12], p[13], tr, offset )
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}
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void CvLBPEvaluator::Feature::write(FileStorage &fs) const
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{
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fs << CC_RECT << "[:" << rect.x << rect.y << rect.width << rect.height << "]";
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}
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