CGAL 5.5.2 - Point Set Processing
Point_set_processing_3/clustering_example.cpp
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h>
#include <CGAL/Point_set_3.h>
#include <CGAL/Point_set_3/IO.h>
#include <CGAL/cluster_point_set.h>
#include <CGAL/compute_average_spacing.h>
#include <CGAL/Random.h>
#include <CGAL/Real_timer.h>
#include <fstream>
#include <iostream>
using Point_3 = Kernel::Point_3;
using Point_set = CGAL::Point_set_3<Point_3>;
int main (int argc, char** argv)
{
// Read input file
std::ifstream ifile((argc > 1) ? argv[1] : CGAL::data_file_path("points_3/hippo1.ply"), std::ios_base::binary);
Point_set points;
ifile >> points;
// Add a cluster map
Point_set::Property_map<int> cluster_map = points.add_property_map<int>("cluster", -1).first;
// Compute average spacing
double spacing = CGAL::compute_average_spacing<CGAL::Parallel_if_available_tag> (points, 12);
std::cerr << "Spacing = " << spacing << std::endl;
// Adjacencies stored in vector
std::vector<std::pair<std::size_t, std::size_t> > adjacencies;
// Compute clusters
CGAL::Real_timer t;
t.start();
std::size_t nb_clusters
= CGAL::cluster_point_set(points, cluster_map,
points.parameters().neighbor_radius(spacing)
.adjacencies(std::back_inserter(adjacencies)));
t.stop();
std::cerr << "Found " << nb_clusters << " clusters with " << adjacencies.size()
<< " adjacencies in " << t.time() << " seconds" << std::endl;
// Output a colored PLY file
Point_set::Property_map<unsigned char> red = points.add_property_map<unsigned char>("red", 0).first;
Point_set::Property_map<unsigned char> green = points.add_property_map<unsigned char>("green", 0).first;
Point_set::Property_map<unsigned char> blue = points.add_property_map<unsigned char>("blue", 0).first;
for(Point_set::Index idx : points)
{
// One color per cluster
CGAL::Random rand (cluster_map[idx]);
red[idx] = rand.get_int(64, 192);
green[idx] = rand.get_int(64, 192);
blue[idx] = rand.get_int(64, 192);
}
std::ofstream ofile("out.ply", std::ios_base::binary);
ofile << points;
return EXIT_SUCCESS;
}