gpu_seeded_hue_segmentation.h

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#pragma once
 
#include <pcl/point_types.h>
#include <pcl/point_cloud.h>
#include <pcl/PointIndices.h>
#include <pcl/pcl_macros.h>
 
namespace pcl
{
  namespace gpu
  {
    void
    seededHueSegmentation (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr  &host_cloud_,
                           const pcl::gpu::Octree::Ptr                   &tree,
                           float                                         tolerance,
                           PointIndices                                  &clusters_in,
                           PointIndices                                  &clusters_out,
                           float                                         delta_hue = 0.0);
 
    class SeededHueSegmentation
    {
      public:
        using PointType = pcl::PointXYZ;
        using PointCloudHost = pcl::PointCloud<pcl::PointXYZ>;
        using PointCloudHostPtr = PointCloudHost::Ptr;
        using PointCloudHostConstPtr = PointCloudHost::ConstPtr;
 
        using PointIndicesPtr = PointIndices::Ptr;
        using PointIndicesConstPtr = PointIndices::ConstPtr;
 
        using GPUTree = pcl::gpu::Octree;
        using GPUTreePtr = pcl::gpu::Octree::Ptr;
 
        using CloudDevice = pcl::gpu::Octree::PointCloud;
 
        //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
        /** \brief Empty constructor. */
        SeededHueSegmentation () : delta_hue_ (0.0) 
        {};
 
        /** \brief Provide a pointer to the search object.
          * \param tree a pointer to the spatial search object.
          */
        inline void setSearchMethod (const GPUTreePtr &tree) { tree_ = tree; }
 
        /** \brief Get a pointer to the search method used. 
          *  @todo fix this for a generic search tree
          */
        inline GPUTreePtr getSearchMethod () { return (tree_); }
 
        /** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
          * \param tolerance the spatial cluster tolerance as a measure in the L2 Euclidean space
          */
        inline void setClusterTolerance (double tolerance) { cluster_tolerance_ = tolerance; }
 
        /** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space. */
        inline double getClusterTolerance () { return (cluster_tolerance_); }
 
        inline void setInput (CloudDevice input) {input_ = input;}
 
        inline void setHostCloud (PointCloudHostPtr host_cloud) {host_cloud_ = host_cloud;}
 
        /** \brief Set the tollerance on the hue
          * \param[in] delta_hue the new delta hue
          */
        inline void 
        setDeltaHue (float delta_hue) { delta_hue_ = delta_hue; }
 
        /** \brief Get the tolerance on the hue */
        inline float 
        getDeltaHue () { return (delta_hue_); }
 
        /** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
          * \param indices_in
          * \param indices_out
          */
        void segment (PointIndices &indices_in, PointIndices &indices_out);
 
      protected:
        /** \brief the input cloud on the GPU */
        CloudDevice input_;
 
        /** \brief the original cloud the Host */
        PointCloudHostPtr host_cloud_;
 
        /** \brief A pointer to the spatial search object. */
        GPUTreePtr tree_;
 
        /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
        double cluster_tolerance_;
 
        /** \brief The allowed difference on the hue*/
        float delta_hue_;
 
        /** \brief Class getName method. */
        virtual std::string getClassName () const { return ("gpu::SeededHueSegmentation"); }
    };
    /** \brief Sort clusters method (for std::sort). 
      * \ingroup segmentation
      */
    inline bool 
      comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
    {
      return (a.indices.size () < b.indices.size ());
    }
  }
}