PointSampler.cpp

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// -*- c-basic-offset: 4 -*-
#include "PointSampler.h"
 
#include <algorithms/basic/CalculateOptimalScale.h>
#include <algorithms/nona/FitPanorama.h>
#include <algorithms/nona/CenterHorizontally.h>
#include <vigra/convolution.hxx>
 
namespace HuginBase
{
 
LimitIntensity::LimitIntensity()
{
    m_minI = -FLT_MAX;
    m_maxI = FLT_MAX;
};
 
LimitIntensity::LimitIntensity(LimitIntensity::LimitType limit)
{
    switch (limit)
    {
        case LIMIT_UINT8:
            m_minI = 1 / 255.0f;
            m_maxI = 250 / 255.0f;
            break;
        case LIMIT_UINT16:
            m_minI = 1 / 65535.0f;
            m_maxI = 65000 / 65535.0f;
            break;
        case LIMIT_FLOAT:
            m_minI = -FLT_MAX;
            m_maxI = FLT_MAX;
            break;
    };
};
 
bool PointSampler::runAlgorithm()
{
    // is this correct? how much progress requierd?
    sampleAndExtractPoints(getProgressDisplay());
    
    if (getProgressDisplay()->wasCancelled())
    {
        cancelAlgorithm();
    };
 
    return wasCancelled();
}
 
void PointSampler::sampleAndExtractPoints(AppBase::ProgressDisplay* progress)
{
    PanoramaData& pano = *(o_panorama.getNewCopy()); // don't forget to delete!
    std::vector<vigra::FRGBImage*>& images = o_images;
    int& nPoints = o_numPoints;
    std::vector<vigra_ext::PointPairRGB>& points = o_resultPoints;
    
    std::vector<vigra::FImage *> lapImgs;
    std::vector<vigra::Size2D> origsize;
    
    // convert to interpolating images
    typedef vigra_ext::ImageInterpolator<vigra::FRGBImage::const_traverser, vigra::FRGBImage::ConstAccessor, vigra_ext::interp_cubic> InterpolImg;
    std::vector<InterpolImg> interpolImages;
    
    vigra_ext::interp_cubic interp;
    // adjust sizes in panorama
    HuginBase::VariableMapVector vars(pano.getNrOfImages());
    for (unsigned i=0; i < pano.getNrOfImages(); i++)
    {
        SrcPanoImage simg = pano.getSrcImage(i);
        origsize.push_back(simg.getSize());
        simg.resize(images[i]->size(), &vars[i]);
        pano.setSrcImage(i, simg);
        interpolImages.push_back(InterpolImg(srcImageRange(*(images[i])), interp, false));
        
        vigra::FImage * lap = new vigra::FImage(images[i]->size());
        lapImgs.push_back(lap);
    }
    // now update all possible linked variables
    // this has to be done separately, otherwise the linked variables
    // would be updated several times
    for (unsigned i = 0; i < pano.getNrOfImages(); ++i)
    {
        if (!vars[i].empty())
        {
            pano.updateVariables(i, vars[i]);
        };
    };
#pragma omp parallel for
    for (int i = 0; i < pano.getNrOfImages(); i++)
    {
        vigra::laplacianOfGaussian(srcImageRange(*(images[i]), vigra::GreenAccessor<vigra::RGBValue<float> >()), destImage(*(lapImgs[i])), 1);
    }
    
    // extract the overlapping points.
//    PanoramaOptions opts = pano.getOptions();
//    double scale = CalculateOptimalScale::calcOptimalPanoScale(pano.getSrcImage(0),opts);
//    opts.setWidth(utils::roundi(opts.getWidth()*scale), true);    
//    pano.setOptions(opts);
    // center panorama and do fit to get minimum of black/unused space around panorama
    CenterHorizontally(pano).run();
    PanoramaOptions opts = pano.getOptions();
    CalculateFitPanorama fitPano(pano);
    fitPano.run();
    opts.setHFOV(fitPano.getResultHorizontalFOV());
    opts.setHeight(hugin_utils::roundi(fitPano.getResultHeight()));
    // set roi to maximal size, so that the whole panorama is used for sampling
    // a more reasonable solution would be to use the maximal
    // used area, but this is currently not support to
    // calculate optimal roi
    opts.setROI(vigra::Rect2D(opts.getSize()));
    pano.setOptions(opts);
    SetWidthOptimal(pano).run();
    
    // if random points.
    // extract random points.
    // need to get the maximum gray value here..
    
    std::vector<std::multimap<double, vigra_ext::PointPairRGB> > radiusHist(10);
    
    unsigned nGoodPoints = 0;
    unsigned nBadPoints = 0;
    
    
    // call the samplePoints method of this class
    progress->setMessage("sampling points");
    samplePoints(interpolImages,
                 lapImgs,
                 pano,
                 m_limits,
                 radiusHist,
                 nGoodPoints,
                 nBadPoints,
                 progress);
        
    // select points with low laplacian of gaussian values.
    progress->setMessage("extracting good points");
    sampleRadiusUniform(radiusHist, nPoints, points, progress);
    
    // scale point coordinates to fit into original panorama.
    for (size_t i=0; i < points.size(); i++) {
        double scaleF1 = origsize[points[i].imgNr1].x / (float) images[points[i].imgNr1]->size().x;
        double scaleF2 = origsize[points[i].imgNr2].x / (float) images[points[i].imgNr2]->size().x;
        points[i].p1.x = points[i].p1.x * scaleF1;
        points[i].p1.y = points[i].p1.y * scaleF1;
        points[i].p2.x = points[i].p2.x * scaleF2;
        points[i].p2.y = points[i].p2.y * scaleF2;
    }
 
    for (size_t i=0; i < images.size(); i++) {
        delete images[i];
        delete lapImgs[i];
    }
    
    delete &pano; // deleting the NewCopy
}
 
}; // namespace