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