\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 5.0.4 - Shape Detection
Shape_detection/efficient_RANSAC_with_parameters.cpp
#include <fstream>
#include <iostream>
#include <CGAL/property_map.h>
#include <CGAL/IO/read_xyz_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 Kernel::FT FT;
typedef std::pair<Kernel::Point_3, Kernel::Vector_3> Point_with_normal;
typedef std::vector<Point_with_normal> Pwn_vector;
<Kernel, Pwn_vector, Point_map, Normal_map> Traits;
int main(int argc, char** argv) {
// Points with normals.
Pwn_vector points;
// Load point set from a file.
std::ifstream stream((argc > 1) ? argv[1] : "data/cube.pwn");
if (!stream ||
stream,
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;
}