feature_evaluator.cpp

/*
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*/

#include "precomp.hpp"

namespace cv {
namespace xobjdetect {

float calcNormFactor( const Mat& sum, const Mat& sqSum )
{
    CV_DbgAssert( sum.cols > 3 && sqSum.rows > 3 );
    Rect normrect( 1, 1, sum.cols - 3, sum.rows - 3 );
    size_t p0, p1, p2, p3;
    CV_SUM_OFFSETS( p0, p1, p2, p3, normrect, sum.step1() )
    double area = normrect.width * normrect.height;
    const int *sp = sum.ptr<int>();
    int valSum = sp[p0] - sp[p1] - sp[p2] + sp[p3];
    const double *sqp = sqSum.ptr<double>();
    double valSqSum = sqp[p0] - sqp[p1] - sqp[p2] + sqp[p3];
    return (float) sqrt( (double) (area * valSqSum - (double)valSum * valSum) );
}

CvParams::CvParams() : name( "params" ) {}
void CvParams::printDefaults() const
{ std::cout << "--" << name << "--" << std::endl; }
void CvParams::printAttrs() const {}
bool CvParams::scanAttr( const std::string, const std::string ) { return false; }


//---------------------------- FeatureParams --------------------------------------

CvFeatureParams::CvFeatureParams() : maxCatCount( 0 ), featSize( 1 )
{
    name = CC_FEATURE_PARAMS;
}

void CvFeatureParams::init( const CvFeatureParams& fp )
{
    maxCatCount = fp.maxCatCount;
    featSize = fp.featSize;
}

void CvFeatureParams::write( FileStorage &fs ) const
{
    fs << CC_MAX_CAT_COUNT << maxCatCount;
    fs << CC_FEATURE_SIZE << featSize;
}

bool CvFeatureParams::read( const FileNode &node )
{
    if ( node.empty() )
        return false;
    maxCatCount = node[CC_MAX_CAT_COUNT];
    featSize = node[CC_FEATURE_SIZE];
    return ( maxCatCount >= 0 && featSize >= 1 );
}

Ptr<CvFeatureParams> CvFeatureParams::create()
{
    return Ptr<CvFeatureParams>(new CvLBPFeatureParams);
}

//------------------------------------- FeatureEvaluator ---------------------------------------

void CvFeatureEvaluator::init(const CvFeatureParams *_featureParams,
                              int _maxSampleCount, Size _winSize )
{
    CV_Assert(_maxSampleCount > 0);
    featureParams = (CvFeatureParams *)_featureParams;
    winSize = _winSize;
    numFeatures = 0;
    cls.create( (int)_maxSampleCount, 1, CV_32FC1 );
    generateFeatures();
}

void CvFeatureEvaluator::setImage(const Mat &, uchar clsLabel, int idx, const std::vector<int>&)
{
    //CV_Assert(img.cols == winSize.width);
    //CV_Assert(img.rows == winSize.height);
    CV_Assert(idx < cls.rows);
    cls.ptr<float>(idx)[0] = clsLabel;
}

Ptr<CvFeatureEvaluator> CvFeatureEvaluator::create()
{
    return Ptr<CvFeatureEvaluator>(new CvLBPEvaluator);
}

}
}