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#include <fstream>
#include <iostream>
#include <CGAL/property_map.h>
#include <CGAL/IO/read_points.h>
#include <CGAL/Point_with_normal_3.h>
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h>
#include <CGAL/Shape_detection/Efficient_RANSAC.h>
// Type declarations.
typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;
typedef Kernel::FT FT;
typedef std::pair<Kernel::Point_3, Kernel::Vector_3> Point_with_normal;
typedef std::vector<Point_with_normal> Pwn_vector;
typedef CGAL::First_of_pair_property_map<Point_with_normal> Point_map;
typedef CGAL::Second_of_pair_property_map<Point_with_normal> Normal_map;
typedef CGAL::Shape_detection::Efficient_RANSAC_traits
<Kernel, Pwn_vector, Point_map, Normal_map> Traits;
typedef CGAL::Shape_detection::Efficient_RANSAC<Traits> Efficient_ransac;
typedef CGAL::Shape_detection::Cone<Traits> Cone;
typedef CGAL::Shape_detection::Cylinder<Traits> Cylinder;
typedef CGAL::Shape_detection::Plane<Traits> Plane;
typedef CGAL::Shape_detection::Sphere<Traits> Sphere;
typedef CGAL::Shape_detection::Torus<Traits> Torus;
int main(int argc, char** argv) {
// Points with normals.
Pwn_vector points;
// Load point set from a file.
if (!CGAL::IO::read_points(
((argc > 1) ? argv[1] : CGAL::data_file_path("points_3/cube.pwn")),
std::back_inserter(points),
CGAL::parameters::point_map(Point_map()).
normal_map(Normal_map()))) {
std::cerr << "Error: cannot read file cube.pwn!" << std::endl;
return EXIT_FAILURE;
}
std::cout << points.size() << " points" << std::endl;
// Instantiate shape detection engine.
Efficient_ransac ransac;
// Provide input data.
ransac.set_input(points);
// Register shapes for detection.
ransac.add_shape_factory<Plane>();
ransac.add_shape_factory<Sphere>();
ransac.add_shape_factory<Cylinder>();
ransac.add_shape_factory<Cone>();
ransac.add_shape_factory<Torus>();
// Set parameters for shape detection.
Efficient_ransac::Parameters parameters;
// Set probability to miss the largest primitive at each iteration.
parameters.probability = 0.05;
// Detect shapes with at least 200 points.
parameters.min_points = 200;
// Set maximum Euclidean distance between a point and a shape.
parameters.epsilon = 0.002;
// Set maximum Euclidean distance between points to be clustered.
parameters.cluster_epsilon = 0.01;
// Set maximum normal deviation.
// 0.9 < dot(surface_normal, point_normal);
parameters.normal_threshold = 0.9;
// Detect shapes.
ransac.detect(parameters);
// Print number of detected shapes and unassigned points.
std::cout << ransac.shapes().end() - ransac.shapes().begin()
<< " detected shapes, "
<< ransac.number_of_unassigned_points()
<< " unassigned points." << std::endl;
// Efficient_ransac::shapes() provides
// an iterator range to the detected shapes.
Efficient_ransac::Shape_range shapes = ransac.shapes();
Efficient_ransac::Shape_range::iterator it = shapes.begin();
while (it != shapes.end()) {
// Get specific parameters depending on the detected shape.
if (Plane* plane = dynamic_cast<Plane*>(it->get())) {
Kernel::Vector_3 normal = plane->plane_normal();
std::cout << "Plane with normal " << normal << std::endl;
// Plane shape can also be converted to the Kernel::Plane_3.
std::cout << "Kernel::Plane_3: " <<
static_cast<Kernel::Plane_3>(*plane) << std::endl;
} else if (Cylinder* cyl = dynamic_cast<Cylinder*>(it->get())) {
Kernel::Line_3 axis = cyl->axis();
FT radius = cyl->radius();
std::cout << "Cylinder with axis "
<< axis << " and radius " << radius << std::endl;
} else {
// Print the parameters of the detected shape.
// This function is available for any type of shape.
std::cout << (*it)->info() << std::endl;
}
// Proceed with the next detected shape.
it++;
}
return EXIT_SUCCESS;
}
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