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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2009-2011, Willow Garage, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of Willow Garage, Inc. nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id$
*
*
*/
#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/features/normal_3d.h>
#include <pcl/segmentation/extract_clusters.h>
int
main (int argc, char **argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ> ());
pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal> ());
pcl::PCDWriter writer;
if (argc < 2)
{
std::cout<<"No PCD file given!"<<std::endl;
return (-1);
}
if (pcl::io::loadPCDFile<pcl::PointXYZ> (argv[1], *cloud_ptr) == -1)
{
std::cout<<"Couldn't read the file "<<argv[1]<<std::endl;
return (-1);
}
std::cout << "Loaded pcd file " << argv[1] << " with " << cloud_ptr->size () << std::endl;
// Normal estimation
pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> ne;
ne.setInputCloud (cloud_ptr);
pcl::search::KdTree<pcl::PointXYZ>::Ptr tree_n (new pcl::search::KdTree<pcl::PointXYZ>());
ne.setSearchMethod (tree_n);
ne.setRadiusSearch (0.03);
ne.compute (*cloud_normals);
std::cout << "Estimated the normals" << std::endl;
// Creating the kdtree object for the search method of the extraction
pcl::KdTree<pcl::PointXYZ>::Ptr tree_ec (new pcl::KdTreeFLANN<pcl::PointXYZ> ());
tree_ec->setInputCloud (cloud_ptr);
// Extracting Euclidean clusters using cloud and its normals
std::vector<pcl::PointIndices> cluster_indices;
const float tolerance = 0.5f; // 50cm tolerance in (x, y, z) coordinate system
const double eps_angle = 5 * (M_PI / 180.0); // 5degree tolerance in normals
const unsigned int min_cluster_size = 50;
pcl::extractEuclideanClusters (*cloud_ptr, *cloud_normals, tolerance, tree_ec, cluster_indices, eps_angle, min_cluster_size);
std::cout << "No of clusters formed are " << cluster_indices.size () << std::endl;
// Saving the clusters in separate pcd files
int j = 0;
for (const auto& cluster : cluster_indices)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
for (const auto &index : cluster.indices) {
cloud_cluster->push_back((*cloud_ptr)[index]);
}
cloud_cluster->width = cloud_cluster->size ();
cloud_cluster->height = 1;
cloud_cluster->is_dense = true;
std::cout << "PointCloud representing the Cluster using xyzn: " << cloud_cluster->size () << " data " << std::endl;
std::stringstream ss;
ss << "./cloud_cluster_" << j << ".pcd";
writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false);
++j;
}
return (0);
}
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