layered_maps.cpp

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#include <tuw_geometry/layered_maps.h>
 
#include <opencv2/core/core.hpp>
#include <opencv2/core/core_c.h>
#include <opencv2/opencv.hpp>
 
using namespace tuw;
using namespace std;
using namespace cv;
 
LayeredMaps::LayeredMaps () {
 
}
 
void LayeredMaps::initLayers( int width_pixel, int height_pixel, 
                              double min_x, double max_x, 
                              double min_y, double max_y, double rotation  ) {    
    init(width_pixel, height_pixel, min_x, max_x, min_y, max_y, rotation);
    initLayers();
}
 
size_t LayeredMaps::sizeLayers() const {
    return mapLayers_.size();
}
 
 
void LayeredMaps::resizeLayers( const size_t& _n ) {
    mapLayers_.resize ( _n );
}
 
void LayeredMaps::initLayers() {
    for(size_t i = 0; i < mapLayers_.size(); i++){ mapLayers_[i].create ( width(), height(), CV_32FC1 ); clearLayer(i); }
}
 
void LayeredMaps::clearLayers() {
    for(size_t i = 0; i < mapLayers_.size(); i++){ clearLayer(i); }
}
void LayeredMaps::clearLayer( const size_t& _layer ) {
    mapLayers_[_layer].setTo( 1 );
}
 
cv::Mat& LayeredMaps::mapLayer( const size_t& _layer ) {
    return mapLayers_[_layer];
}
const cv::Mat& LayeredMaps::mapLayer( const size_t& _layer ) const {
    return mapLayers_[_layer];
}
 
double LayeredMaps::getVal( const size_t& _layer, const Point2D& _worldPos, Interpolation _interpolationType ) const
{
  double retVal = -100;
  Point2D mapPos = w2m(_worldPos);
  if (!mapPos.inside(0, 0, mapLayer(_layer).rows - 1, mapLayer(_layer).cols - 1))
  {
    return retVal;
  }
  const double mapPos_row_d = mapPos.y()       , mapPos_col_d = mapPos.x();
  const int    mapPos_row_i = int(mapPos_row_d), mapPos_col_i = int(mapPos_col_d);
    
  switch ( _interpolationType )
  {
          case SIMPLE :
            retVal = mapLayer(_layer).at<float_t>( mapPos_row_i, mapPos_col_i ); 
            break;
          case BILINEAR:
            //if((mapPos_y_i+1 >= mapLayer(layer).rows)||(mapPos_x_i+1 >= mapLayer(layer).cols)||(mapPos_y_i <0)||(mapPos_x_i <0)){throw 0;}
            
            const double f00 = mapLayer(_layer).at<float_t>(mapPos_row_i    , mapPos_col_i    );
            const double f10 = mapLayer(_layer).at<float_t>(mapPos_row_i + 1, mapPos_col_i    );
            const double f01 = mapLayer(_layer).at<float_t>(mapPos_row_i    , mapPos_col_i + 1);
            const double f11 = mapLayer(_layer).at<float_t>(mapPos_row_i + 1, mapPos_col_i + 1);
            
            const double mapPosRed_row = mapPos_row_d - mapPos_row_i, mapPosRed_col = mapPos_col_d - mapPos_col_i;
            
            retVal =  f00 * (1 - mapPosRed_row) * (1 - mapPosRed_col) + 
                      f10 *      mapPosRed_row  * (1 - mapPosRed_col) + 
                      f01 * (1 - mapPosRed_row) *      mapPosRed_col  + 
                      f11 *      mapPosRed_row  *      mapPosRed_col;
            break;
    }
    return retVal;
}
 
float distance2probabilitySigmoid ( float d, float threshold ) {
    float p = 0;
    if ( d < threshold ) {
        p = tanh ( ( 2*M_PI*-d ) /threshold+M_PI ) * 0.5 + 0.5;
    }
    return p;
}
float distance2probabilityTriangle ( float d, float threshold ) {
    float p = 0;
    if ( d < threshold ) {
        p = 1.-d/threshold;
    }
    return p;
}
 
void LayeredMaps::computeDistanceField ( Mat& _mDst, vector< Point2D >& _pSrc, const double& _radius, bool _flipDistance, bool connectPoints ) const {
    Mat srcMap;  srcMap.create ( width(), height(), CV_32FC1 ); srcMap.setTo ( 1 );
    Scalar colour ( 0 );
    if(connectPoints){ for ( size_t i = 1; i < _pSrc.size(); i++ ) { line   ( srcMap, _pSrc[i-1], _pSrc[i], colour, 8); } } 
    else             { for ( size_t i = 0; i < _pSrc.size(); i++ ) { circle ( srcMap, _pSrc[i], 1, colour, 1, 8); } }
    computeDistanceField ( _mDst, srcMap, _radius, _flipDistance );
}
 
 
void LayeredMaps::computeDistanceField ( Mat& _mDst, Mat& _mSrc, const double& _radius, bool _flipDistance ) const {
    Mat srcMap; 
    _mSrc.convertTo(srcMap, CV_8U);
    int maskSize0 = cv::DIST_MASK_PRECISE;
    int voronoiType = -1;
    int distType0 = cv::DIST_L2;//CV_DIST_L1;
    int maskSize = voronoiType >= 0 ? cv::DIST_MASK_5 : maskSize0;
    int distType = voronoiType >= 0 ? cv::DIST_L2     : distType0;
    Mat destMap_f,  labels;  
//     destMap_f.create ( width(), height(), CV_32F );
    if ( voronoiType < 0 ){ cv::distanceTransform ( srcMap, destMap_f, distType, maskSize ); }
    else                  { cv::distanceTransform ( srcMap, destMap_f, labels, distType, maskSize, voronoiType ); }
//     destMap_f.convertTo(destMap_ui, CV_8U );
 
    CV_Assert(destMap_f.depth() == CV_32F);
    int channels = destMap_f.channels();
    int nRows    = destMap_f.rows;
    int nCols    = destMap_f.cols * channels;
    if (destMap_f.isContinuous()) { nCols *= nRows; nRows = 1; }
 
    float threshold = _radius * scale_x ();
    float_t* p_d; float* p_s;
    for(int i = 0; i < nRows; ++i) {
        p_d = destMap_f.ptr<float_t>(i);
        for (int j = 0; j < nCols; ++j) { if (_flipDistance) { p_d[j] = (float_t)(       distance2probabilityTriangle ( p_d[j], threshold )   ); }
                                          else               { p_d[j] = (float_t)( (1. - distance2probabilityTriangle ( p_d[j], threshold ) ) ); } }
    }
    if ( ( _mDst.channels() != 1 ) && ( _mDst.channels() != 5 ) )  { cvtColor(destMap_f, _mDst, cv::COLOR_GRAY2BGR ); }
    else                                                           { _mDst = destMap_f;                        }
    
}