vol-curvature-measures-icnc-3d.cpp

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#include <iostream>
#include <fstream>
#include <algorithm>
#include "DGtal/base/Common.h"
#include "DGtal/shapes/SurfaceMesh.h"
#include "DGtal/geometry/meshes/CorrectedNormalCurrentComputer.h"
#include "DGtal/helpers/Shortcuts.h"
#include "DGtal/helpers/ShortcutsGeometry.h"
#include "DGtal/io/writers/SurfaceMeshWriter.h"
#include "DGtal/io/colormaps/GradientColorMap.h"
#include "DGtal/io/colormaps/QuantifiedColorMap.h"
 
DGtal::GradientColorMap< double >
makeColorMap( double min_value, double max_value )
{
  DGtal::GradientColorMap< double > gradcmap( min_value, max_value );
  gradcmap.addColor( DGtal::Color( 0, 0, 255 ) );
  gradcmap.addColor( DGtal::Color( 0, 255, 255 ) );
  gradcmap.addColor( DGtal::Color( 255, 255, 255 ) );
  gradcmap.addColor( DGtal::Color( 255, 255, 0 ) );
  gradcmap.addColor( DGtal::Color( 255, 0, 0 ) );
  return gradcmap;
}
 
void usage( char* argv[] )
{
  std::cout << "Usage: " << std::endl
            << "\t" << argv[ 0 ] << " <filename.vol> <R> <m> <M> <Hmax> <Gmax>" << std::endl
            << std::endl
            << "Computation of mean and Gaussian curvatures on a vol file, " << std::endl
            << "using interpolated corrected curvature measures (based " << std::endl
            << "on the theory of corrected normal currents)."            << std::endl
            << "- builds the surface mesh from file <filename.vol>"      << std::endl
            << "- <R> is the radius of the measuring balls"              << std::endl
            << "- <m> is the min threshold value for the vol file"       << std::endl
            << "- <M> is the max threshold value for the vol file"       << std::endl
            << "- <Hmax> gives the colormap range [-Hmax,Hmax] for"      << std::endl
            << "  the output of mean curvature estimates"                << std::endl
            << "- <Gmax> gives the colormap range [-Gmax,Gmax] for"      << std::endl
            << "  the output of mean curvature estimates"                << std::endl
            << "It produces several OBJ files to display mean and"       << std::endl
            << "Gaussian curvature estimation results: `example-cnc-H.obj`" << std::endl
            << "and `example-cnc-G.obj` as well as the associated MTL file." << std::endl;
}
 
int main( int argc, char* argv[] )
{
  if ( argc <= 1 )
    {
      usage( argv );
      return 0;
    }
  using namespace DGtal;
  using namespace DGtal::Z3i;
  typedef SurfaceMesh< RealPoint, RealVector >                    SM;
  typedef CorrectedNormalCurrentComputer< RealPoint, RealVector > CNC;
  typedef Shortcuts< KSpace >          SH;
  typedef ShortcutsGeometry< KSpace > SHG;
  // VOL file
  std::string input = argv[ 1 ];
  const double    R = argc > 2 ? atof( argv[ 2 ] ) : 2.0; // radius of measuring ball
  const int       m = argc > 3 ? atoi( argv[ 3 ] ) : 0; // min threshold
  const int       M = argc > 4 ? atoi( argv[ 4 ] ) : 1; // max threshold
  const double Hmax = argc > 5 ? atof( argv[ 5 ] ) : 0.33; // range mean curvature colormap
  const double Gmax = argc > 6 ? atof( argv[ 6 ] ) : 0.1; // range Gaussian curvature colormap

  // Read VOL file and build digital surface
  auto params = SH::defaultParameters() | SHG::defaultParameters();
  params( "thresholdMin", m )( "thresholdMax", M )( "closed", 1);
  params( "t-ring", 3 )( "surfaceTraversal", "Default" );
  auto bimage = SH::makeBinaryImage( input.c_str(), params );
  if ( bimage == nullptr ) 
    {
      trace.error() <<  "Unable to read file <" << input.c_str() << ">" << std::endl;
      return 1;
    }
  auto K      = SH::getKSpace( bimage, params );
  auto sembedder   = SH::getSCellEmbedder( K );
  auto embedder    = SH::getCellEmbedder( K );
  auto surface     = SH::makeDigitalSurface( bimage, K, params );
  auto surfels     = SH::getSurfelRange( surface, params );
  trace.info() << "- surface has " << surfels.size()<< " surfels." << std::endl;

  SM smesh;
  std::vector< SM::Vertices > faces;
  SH::Cell2Index c2i;
  auto pointels = SH::getPointelRange( c2i, surface );
  auto vertices = SH::RealPoints( pointels.size() );
  std::transform( pointels.cbegin(), pointels.cend(), vertices.begin(),
                  [&] (const SH::Cell& c) { return embedder( c ); } ); 
  for ( auto&& surfel : *surface )
    {
      const auto primal_surfel_vtcs = SH::getPointelRange( K, surfel );
      SM::Vertices face;              
      for ( auto&& primal_vtx : primal_surfel_vtcs )
        face.push_back( c2i[ primal_vtx ] );
      faces.push_back( face );
    }
  smesh.init( vertices.cbegin(), vertices.cend(),
              faces.cbegin(),    faces.cend() );
  trace.info() << smesh << std::endl;

  // Builds a CorrectedNormalCurrentComputer object onto the SurfaceMesh object
  CNC cnc( smesh );
  // Estimates normal vectors using Convolved Trivial Normal estimator 
  auto face_normals = SHG::getCTrivialNormalVectors( surface, surfels, params );
  smesh.setFaceNormals( face_normals.cbegin(), face_normals.cend() );
  // if ( smesh.vertexNormals().empty() )
  //   smesh.computeVertexNormalsFromFaceNormals();
  // computes area, mean and Gaussian curvature measures
  std::cout << "Compute mu0" << std::endl;
  auto mu0 = cnc.computeMu0();
  std::cout << "Compute mu1" << std::endl;
  auto mu1 = cnc.computeMu1();
  std::cout << "Compute mu2" << std::endl;
  auto mu2 = cnc.computeMu2();

  // estimates mean (H) and Gaussian (G) curvatures by measure normalization.
  std::vector< double > H( smesh.nbFaces() );
  std::vector< double > G( smesh.nbFaces() );
  for ( auto f = 0; f < smesh.nbFaces(); ++f )
    {
      const auto b    = smesh.faceCentroid( f );
      const auto area = mu0.measure( b, R, f );
      H[ f ] = cnc.meanCurvature    ( area, mu1.measure( b, R, f ) );
      G[ f ] = cnc.GaussianCurvature( area, mu2.measure( b, R, f ) );
    }

  auto H_min_max = std::minmax_element( H.cbegin(), H.cend() );
  auto G_min_max = std::minmax_element( G.cbegin(), G.cend() );
  std::cout << "Computed mean curvatures:"
            << " min=" << *H_min_max.first << " max=" << *H_min_max.second
            << std::endl;
  std::cout << "Computed Gaussian curvatures:"
            << " min=" << *G_min_max.first << " max=" << *G_min_max.second
            << std::endl;

  // Remove normals for better blocky display.
  smesh.vertexNormals() = SH::RealVectors();
  smesh.faceNormals()   = SH::RealVectors();
  typedef SurfaceMeshWriter< RealPoint, RealVector > SMW;
  const auto colormapH = makeQuantifiedColorMap( makeColorMap( -Hmax, Hmax ) );
  const auto colormapG = makeQuantifiedColorMap( makeColorMap( -Gmax, Gmax ) );
  auto colorsH = SMW::Colors( smesh.nbFaces() );
  auto colorsG = SMW::Colors( smesh.nbFaces() );
  for ( auto i = 0; i < smesh.nbFaces(); i++ )
    {
      colorsH[ i ] = colormapH( H[ i ] );
      colorsG[ i ] = colormapG( G[ i ] );
    }
  SMW::writeOBJ( "example-cnc-H", smesh, colorsH );
  SMW::writeOBJ( "example-cnc-G", smesh, colorsG );
  return 0;
}