unary_classifier.h

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 * Author : Christian Potthast
 * Email  : potthast@usc.edu
 *
 */
 
#pragma once
 
#include <pcl/memory.h>
#include <pcl/pcl_macros.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
 
#include <pcl/features/fpfh.h>
 
#include <pcl/ml/kmeans.h>
 
namespace pcl
{
  /** \brief
    * 
    */
  template <typename PointT>
  class PCL_EXPORTS UnaryClassifier
  {
    public:
 
      /** \brief Constructor that sets default values for member variables. */
      UnaryClassifier ();
 
      /** \brief This destructor destroys the cloud...
        * 
        */
      ~UnaryClassifier ();
 
      /** \brief This method sets the input cloud.
        * \param[in] input_cloud input point cloud
        */
      void
      setInputCloud (typename pcl::PointCloud<PointT>::Ptr input_cloud);
 
      void 
      train (pcl::PointCloud<pcl::FPFHSignature33>::Ptr &output);
      
      void
      trainWithLabel (std::vector<pcl::PointCloud<pcl::FPFHSignature33>, Eigen::aligned_allocator<pcl::PointCloud<pcl::FPFHSignature33> > > &output);
 
      void
      segment (pcl::PointCloud<pcl::PointXYZRGBL>::Ptr &out);
 
      void
      queryFeatureDistances (std::vector<pcl::PointCloud<pcl::FPFHSignature33>::Ptr> &trained_features,
                             pcl::PointCloud<pcl::FPFHSignature33>::Ptr query_features,
                             pcl::Indices &indi,
                             std::vector<float> &dist);
 
      void
      assignLabels (pcl::Indices &indi,
                    std::vector<float> &dist,
                    int n_feature_means,
                    float feature_threshold,
                    pcl::PointCloud<pcl::PointXYZRGBL>::Ptr out);
 
      void
      setClusterSize (unsigned int k){cluster_size_ = k;};
      
      void
      setNormalRadiusSearch (float param){normal_radius_search_ = param;};
      
      void
      setFPFHRadiusSearch (float param){fpfh_radius_search_ = param;};
      
      void
      setLabelField (bool l){label_field_ = l;};
 
      void
      setTrainedFeatures (std::vector<pcl::PointCloud<pcl::FPFHSignature33>::Ptr> &features){trained_features_ = features;};
 
      void
      setFeatureThreshold (float threshold){feature_threshold_ = threshold;};
 
    protected:
 
      void
      convertCloud (typename pcl::PointCloud<PointT>::Ptr in,
                    pcl::PointCloud<pcl::PointXYZ>::Ptr out);
 
      void
      convertCloud (typename pcl::PointCloud<PointT>::Ptr in,
                    pcl::PointCloud<pcl::PointXYZRGBL>::Ptr out);
 
      void
      findClusters (typename pcl::PointCloud<PointT>::Ptr in,
                    std::vector<int> &cluster_numbers);
 
      void
      getCloudWithLabel (typename pcl::PointCloud<PointT>::Ptr in,
                         pcl::PointCloud<pcl::PointXYZ>::Ptr out,
                         int label_num);
 
      void
      computeFPFH (pcl::PointCloud<pcl::PointXYZ>::Ptr in,
                   pcl::PointCloud<pcl::FPFHSignature33>::Ptr out,
                   float normal_radius_search,
                   float fpfh_radius_search);
      
      void
      kmeansClustering (pcl::PointCloud<pcl::FPFHSignature33>::Ptr in,
                        pcl::PointCloud<pcl::FPFHSignature33>::Ptr out,
                        int k);
 
 
 
      /** \brief Contains the input cloud */
      typename pcl::PointCloud<PointT>::Ptr input_cloud_;
      
      bool label_field_;
      
      unsigned int cluster_size_;
 
      float normal_radius_search_;
      float fpfh_radius_search_;
      float feature_threshold_;
      
      
      std::vector<pcl::PointCloud<pcl::FPFHSignature33>::Ptr> trained_features_;
 
      /** \brief Contains normals of the points that will be segmented. */
      //typename pcl::PointCloud<pcl::Normal>::Ptr normals_;
 
      /** \brief Stores the cloud that will be segmented. */
      //typename pcl::PointCloud<PointT>::Ptr cloud_for_segmentation_;
 
    public:
      PCL_MAKE_ALIGNED_OPERATOR_NEW
 };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/segmentation/impl/unary_classifier.hpp>
#endif