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#if defined (_MSC_VER) && !defined (_WIN64)
#pragma warning(disable:4244) // boost::number_distance::distance()
// converts 64 to 32 bits integers
#endif
#include <CGAL/Simple_cartesian.h>
#include <CGAL/Classification.h>
#include <CGAL/IO/read_points.h>
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <string>
typedef CGAL::Simple_cartesian<double> Kernel;
typedef Kernel::Point_3 Point;
typedef Kernel::Iso_cuboid_3 Iso_cuboid_3;
typedef std::vector<Point> Point_range;
typedef CGAL::Identity_property_map<Point> Pmap;
namespace Classification = CGAL::Classification;
typedef Classification::Sum_of_weighted_features_classifier Classifier;
typedef Classification::Point_set_neighborhood<Kernel, Point_range, Pmap> Neighborhood;
typedef Classification::Local_eigen_analysis Local_eigen_analysis;
typedef Classification::Label_handle Label_handle;
typedef Classification::Feature_handle Feature_handle;
typedef Classification::Label_set Label_set;
typedef Classification::Feature_set Feature_set;
typedef Classification::Feature::Verticality<Kernel> Verticality;
///////////////////////////////////////////////////////////////////
//! [Feature]
// User-defined feature that identifies a specific area of the 3D
// space. This feature takes value 1 for points that lie inside the
// area and 0 for the others.
class My_feature : public CGAL::Classification::Feature_base
{
const Point_range& range;
double xmin, xmax, ymin, ymax;
public:
My_feature (const Point_range& range,
double xmin, double xmax, double ymin, double ymax)
: range (range), xmin(xmin), xmax(xmax), ymin(ymin), ymax(ymax)
{
this->set_name ("my_feature");
}
float value (std::size_t pt_index)
{
if (xmin < range[pt_index].x() && range[pt_index].x() < xmax &&
ymin < range[pt_index].y() && range[pt_index].y() < ymax)
return 1.f;
else
return 0.f;
}
};
//! [Feature]
///////////////////////////////////////////////////////////////////
int main (int argc, char** argv)
{
std::string filename (argc > 1 ? argv[1] : CGAL::data_file_path("points_3/b9.ply"));
std::vector<Point> pts;
std::cerr << "Reading input" << std::endl;
if (!(CGAL::IO::read_points(filename, std::back_inserter(pts),
// the PLY reader expects a binary file by default
CGAL::parameters::use_binary_mode(false))))
{
std::cerr << "Error: cannot read " << filename << std::endl;
return EXIT_FAILURE;
}
Neighborhood neighborhood (pts, Pmap());
Local_eigen_analysis eigen
= Local_eigen_analysis::create_from_point_set (pts, Pmap(), neighborhood.k_neighbor_query(6));
Label_set labels;
Label_handle a = labels.add ("label_A");
Label_handle b = labels.add ("label_B");
///////////////////////////////////////////////////////////////////
//! [Addition]
std::cerr << "Computing features" << std::endl;
Feature_set features;
// Feature that identifies points whose x coordinate is between -20
// and 20 and whose y coordinate is between -15 and 15
Feature_handle my_feature = features.add<My_feature> (pts, -20., 20., -15., 15.);
//! [Addition]
///////////////////////////////////////////////////////////////////
Feature_handle verticality = features.add<Verticality> (pts, eigen);
Classifier classifier (labels, features);
std::cerr << "Setting weights" << std::endl;
classifier.set_weight(verticality, 0.5);
classifier.set_weight(my_feature, 0.25);
std::cerr << "Setting up labels" << std::endl;
classifier.set_effect (a, verticality, Classifier::FAVORING);
classifier.set_effect (a, my_feature, Classifier::FAVORING);
classifier.set_effect (b, verticality, Classifier::PENALIZING);
classifier.set_effect (b, my_feature, Classifier::PENALIZING);
std::cerr << "Classifying" << std::endl;
std::vector<int> label_indices(pts.size(), -1);
Classification::classify_with_graphcut<CGAL::Parallel_if_available_tag>
(pts, Pmap(), labels, classifier,
neighborhood.k_neighbor_query(12),
0.5, 1, label_indices);
std::cerr << "All done" << std::endl;
return EXIT_SUCCESS;
}
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