108 lines
3.6 KiB
C++
108 lines
3.6 KiB
C++
#include <cstdlib>
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#include <fstream>
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#include <iostream>
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#include <string>
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#include <CGAL/Simple_cartesian.h>
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#include <CGAL/Classification.h>
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#include <CGAL/IO/read_ply_points.h>
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typedef CGAL::Simple_cartesian<double> Kernel;
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typedef Kernel::Point_3 Point;
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typedef Kernel::Iso_cuboid_3 Iso_cuboid_3;
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typedef std::vector<Point> Point_range;
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typedef CGAL::Identity_property_map<Point> Pmap;
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namespace Classif = CGAL::Classification;
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typedef Classif::Sum_of_weighted_features_predicate Classification_predicate;
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typedef Classif::Point_set_neighborhood<Kernel, Point_range, Pmap> Neighborhood;
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typedef Classif::Local_eigen_analysis<Kernel, Point_range, Pmap> Local_eigen_analysis;
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typedef Classif::Label_handle Label_handle;
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typedef Classif::Feature_handle Feature_handle;
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typedef Classif::Label_set Label_set;
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typedef Classif::Feature_set Feature_set;
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typedef Classif::Feature::Sphericity<Kernel, Point_range, Pmap> Sphericity;
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// User-defined feature that identifies a specific area of the 3D
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// space. This feature takes value 1 for points that lie inside the
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// area and 0 for the others.
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class My_feature : public CGAL::Classification::Feature_base
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{
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const Point_range& range;
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double xmin, xmax, ymin, ymax;
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public:
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My_feature (const Point_range& range,
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double xmin, double xmax, double ymin, double ymax)
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: range (range), xmin(xmin), xmax(xmax), ymin(ymin), ymax(ymax)
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{
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this->set_name ("my_feature");
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}
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double value (std::size_t pt_index)
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{
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if (xmin < range[pt_index].x() && range[pt_index].x() < xmax &&
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ymin < range[pt_index].y() && range[pt_index].y() < ymax)
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return 1.;
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else
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return 0.;
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}
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};
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int main (int argc, char** argv)
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{
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std::string filename (argc > 1 ? argv[1] : "data/b9.ply");
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std::ifstream in (filename.c_str());
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std::vector<Point> pts;
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std::cerr << "Reading input" << std::endl;
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if (!in
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|| !(CGAL::read_ply_points (in, std::back_inserter (pts))))
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{
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std::cerr << "Error: cannot read " << filename << std::endl;
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return EXIT_FAILURE;
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}
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Neighborhood neighborhood (pts, Pmap());
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Local_eigen_analysis eigen (pts, Pmap(), neighborhood.k_neighbor_query(6));
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Label_set labels;
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Label_handle a = labels.add ("label_A");
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Label_handle b = labels.add ("label_B");
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std::cerr << "Computing features" << std::endl;
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Feature_set features;
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Feature_handle sphericity = features.add<Sphericity> (pts, eigen);
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// Feature that identifies points whose x coordinate is between -20
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// and 20 and whose y coordinate is between -15 and 15
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Feature_handle my_feature = features.add<My_feature> (pts, -20., 20., -15., 15.);
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Classification_predicate predicate (labels, features);
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std::cerr << "Setting weights" << std::endl;
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predicate.set_weight(sphericity, 0.5);
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predicate.set_weight(my_feature, 0.25);
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std::cerr << "Setting up labels" << std::endl;
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predicate.set_effect (a, sphericity, Classification_predicate::FAVORING);
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predicate.set_effect (a, my_feature, Classification_predicate::FAVORING);
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predicate.set_effect (b, sphericity, Classification_predicate::PENALIZING);
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predicate.set_effect (b, my_feature, Classification_predicate::PENALIZING);
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std::vector<std::size_t> label_indices;
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Classif::classify_with_graphcut<CGAL::Sequential_tag>
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(pts, Pmap(), Pmap(), labels, predicate,
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neighborhood.k_neighbor_query(12),
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0.5, 1, label_indices);
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std::cerr << "All done" << std::endl;
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return EXIT_SUCCESS;
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}
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