euclidean_cluster.hpp

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#ifndef _EUCLIDEAN_CLUSTER_HPP_
#define _EUCLIDEAN_CLUSTER_HPP_


#include <pointcloud_segmentation/euclidean_cluster.h>

template<class T>
void euclidean_cluster_extraction<T>::callback_cloud (const sensor_msgs::PointCloud2Ptr& msg)
{
    typename PointCloud<T>::Ptr cloud (new PointCloud<T> ());
    fromROSMsg(*msg,*cloud);
    if ((int)cloud->points.size()>0)
    {
        // Euclidean segmentation
            EuclideanClusterExtraction<T> ec_inside;
            vector<PointIndices> inside_indices;
            ec_inside.setClusterTolerance (cluster_tolerance); // 20cm
            ec_inside.setMinClusterSize (min_cluster_size);
            ec_inside.setMaxClusterSize (max_cluster_size);
            ec_inside.setInputCloud (cloud);
            ec_inside.extract (inside_indices);
            
            // Declare markers class
            markers<T> mk;
            
            // Delete all previous markers
            static int marker_id;
            if (marker_id>0)
            {
                for (int i=0; i<=marker_id; ++i)
                {
                    visualization_msgs::Marker marker_eraser=mk.unmark(msg->header.frame_id, "Obstacle", i);
                    pub_marker_ptr->publish(marker_eraser);
                    pub_marker_text_ptr->publish(marker_eraser);
                }
            }
            
            marker_id=0;
            for (vector<PointIndices>::const_iterator it = inside_indices.begin (); it != inside_indices.end (); ++it)
            {
                typename PointCloud<T>::Ptr inside_cluster (new PointCloud<T>);
                inside_cluster->header.frame_id=msg->header.frame_id;
                for (vector<int>::const_iterator pit = it->indices.begin (); pit != it->indices.end (); pit++)
                    inside_cluster->points.push_back (cloud->points[*pit]);   
                
                visualization_msgs::Marker marker_info=mk.mark_text(inside_cluster, "Obstacle" ,marker_id, 1.0, 0.0, 0.0);
                visualization_msgs::Marker marker=mk.mark(inside_cluster, "Obstacle" ,marker_id, 0.0, 1.0, 0.0);
                marker_id++;
                pub_marker_ptr->publish(marker);
                pub_marker_text_ptr->publish(marker_info);
                inside_cluster.reset();
            }
            
    }
    else
        ROS_ERROR("EUCLIDEAN_CLUSTERING: NO DATA POINTS RECEIVED!");
   
    cloud.reset();
};

#endif