CGAL 5.1 - Classification
Classification/example_classification.cpp
#if defined (_MSC_VER) && !defined (_WIN64)
#pragma warning(disable:4244) // boost::number_distance::distance()
// converts 64 to 32 bits integers
#endif
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <string>
#include <CGAL/Simple_cartesian.h>
#include <CGAL/Classification.h>
#include <CGAL/bounding_box.h>
#include <CGAL/tags.h>
#include <CGAL/IO/read_ply_points.h>
#include <CGAL/Real_timer.h>
typedef CGAL::Parallel_if_available_tag Concurrency_tag;
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::Planimetric_grid<Kernel, Point_range, Pmap> Planimetric_grid;
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::Distance_to_plane<Point_range, Pmap> Distance_to_plane;
typedef Classification::Feature::Elevation<Kernel, Point_range, Pmap> Elevation;
typedef Classification::Feature::Vertical_dispersion<Kernel, Point_range, Pmap> Dispersion;
int main (int argc, char** argv)
{
std::string filename (argc > 1 ? argv[1] : "data/b9.ply");
std::ifstream in (filename.c_str());
std::vector<Point> pts;
std::cerr << "Reading input" << std::endl;
if (!in
|| !(CGAL::read_ply_points (in, std::back_inserter (pts))))
{
std::cerr << "Error: cannot read " << filename << std::endl;
return EXIT_FAILURE;
}
float grid_resolution = 0.34f;
unsigned int number_of_neighbors = 6;
std::cerr << "Computing useful structures" << std::endl;
Iso_cuboid_3 bbox = CGAL::bounding_box (pts.begin(), pts.end());
Planimetric_grid grid (pts, Pmap(), bbox, grid_resolution);
Neighborhood neighborhood (pts, Pmap());
Local_eigen_analysis eigen
= Local_eigen_analysis::create_from_point_set
(pts, Pmap(), neighborhood.k_neighbor_query(number_of_neighbors));
float radius_neighbors = 1.7f;
float radius_dtm = 15.0f;
std::cerr << "Computing features" << std::endl;
Feature_set features;
#ifdef CGAL_LINKED_WITH_TBB
features.begin_parallel_additions();
#endif
Feature_handle distance_to_plane = features.add<Distance_to_plane> (pts, Pmap(), eigen);
Feature_handle dispersion = features.add<Dispersion> (pts, Pmap(), grid,
radius_neighbors);
Feature_handle elevation = features.add<Elevation> (pts, Pmap(), grid,
radius_dtm);
#ifdef CGAL_LINKED_WITH_TBB
features.end_parallel_additions();
#endif
Label_set labels;
Label_handle ground = labels.add ("ground");
Label_handle vegetation = labels.add ("vegetation");
Label_handle roof = labels.add ("roof");
std::cerr << "Setting weights" << std::endl;
Classifier classifier (labels, features);
classifier.set_weight (distance_to_plane, 6.75e-2f);
classifier.set_weight (dispersion, 5.45e-1f);
classifier.set_weight (elevation, 1.47e1f);
std::cerr << "Setting effects" << std::endl;
classifier.set_effect (ground, distance_to_plane, Classifier::NEUTRAL);
classifier.set_effect (ground, dispersion, Classifier::NEUTRAL);
classifier.set_effect (ground, elevation, Classifier::PENALIZING);
classifier.set_effect (vegetation, distance_to_plane, Classifier::FAVORING);
classifier.set_effect (vegetation, dispersion, Classifier::FAVORING);
classifier.set_effect (vegetation, elevation, Classifier::NEUTRAL);
classifier.set_effect (roof, distance_to_plane, Classifier::NEUTRAL);
classifier.set_effect (roof, dispersion, Classifier::NEUTRAL);
classifier.set_effect (roof, elevation, Classifier::FAVORING);
// Run classification
std::cerr << "Classifying" << std::endl;
std::vector<int> label_indices (pts.size(), -1);
CGAL::Real_timer t;
t.start();
Classification::classify<Concurrency_tag> (pts, labels, classifier, label_indices);
t.stop();
std::cerr << "Raw classification performed in " << t.time() << " second(s)" << std::endl;
t.reset();
t.start();
Classification::classify_with_local_smoothing<Concurrency_tag>
(pts, Pmap(), labels, classifier,
neighborhood.sphere_neighbor_query(radius_neighbors),
label_indices);
t.stop();
std::cerr << "Classification with local smoothing performed in " << t.time() << " second(s)" << std::endl;
t.reset();
t.start();
Classification::classify_with_graphcut<Concurrency_tag>
(pts, Pmap(), labels, classifier,
neighborhood.k_neighbor_query(12),
0.2f, 4, label_indices);
t.stop();
std::cerr << "Classification with graphcut performed in " << t.time() << " second(s)" << std::endl;
// Save the output in a colored PLY format
std::ofstream f ("classification.ply");
f << "ply" << std::endl
<< "format ascii 1.0" << std::endl
<< "element vertex " << pts.size() << std::endl
<< "property float x" << std::endl
<< "property float y" << std::endl
<< "property float z" << std::endl
<< "property uchar red" << std::endl
<< "property uchar green" << std::endl
<< "property uchar blue" << std::endl
<< "end_header" << std::endl;
for (std::size_t i = 0; i < pts.size(); ++ i)
{
f << pts[i] << " ";
Label_handle label = labels[std::size_t(label_indices[i])];
if (label == ground)
f << "245 180 0" << std::endl;
else if (label == vegetation)
f << "0 255 27" << std::endl;
else if (label == roof)
f << "255 0 170" << std::endl;
else
{
f << "0 0 0" << std::endl;
std::cerr << "Error: unknown classification label" << std::endl;
}
}
std::cerr << "All done" << std::endl;
return EXIT_SUCCESS;
}