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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>
#include <pcl/gpu/octree/octree.hpp>

namespace pcl
{
  namespace gpu
  {
    template <typename PointT> void
    extractLabeledEuclideanClusters (const typename pcl::PointCloud<PointT>::Ptr &host_cloud_,
                                     const pcl::gpu::Octree::Ptr                 &tree,
                                     float                                       tolerance,
                                     std::vector<PointIndices>                   &clusters,
                                     unsigned int                                min_pts_per_cluster, 
                                     unsigned int                                max_pts_per_cluster);

   /** \brief @b EuclideanLabeledClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree
    * \author Koen Buys, Radu Bogdan Rusu
    * \ingroup segmentation
    */
    template <typename PointT>
    class EuclideanLabeledClusterExtraction
    {
      public:
        using PointType = pcl::PointXYZ;
        using PointCloudHost = pcl::PointCloud<PointT>;
        using PointCloudHostPtr = typename PointCloudHost::Ptr;
        using PointCloudHostConstPtr = typename 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. */
        EuclideanLabeledClusterExtraction () : min_pts_per_cluster_ (1), max_pts_per_cluster_ (std::numeric_limits<int>::max ())
        {};

        /** \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_); }

        /** \brief Set the minimum number of points that a cluster needs to contain in order to be considered valid.
          * \param min_cluster_size the minimum cluster size
          */
        inline void setMinClusterSize (int min_cluster_size) { min_pts_per_cluster_ = min_cluster_size; }

        /** \brief Get the minimum number of points that a cluster needs to contain in order to be considered valid. */
        inline int getMinClusterSize () { return (min_pts_per_cluster_); }

        /** \brief Set the maximum number of points that a cluster needs to contain in order to be considered valid.
          * \param max_cluster_size the maximum cluster size
          */
        inline void setMaxClusterSize (int max_cluster_size) { max_pts_per_cluster_ = max_cluster_size; }

        /** \brief Get the maximum number of points that a cluster needs to contain in order to be considered valid. */
        inline int getMaxClusterSize () { return (max_pts_per_cluster_); }

        inline void setInput (CloudDevice input) {input_ = input;}

        inline void setHostCloud (PointCloudHostPtr host_cloud) {host_cloud_ = host_cloud;}

        /** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
          * \param clusters the resultant point clusters
          */
        void extract (std::vector<PointIndices> &clusters);

      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 minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). */
        int min_pts_per_cluster_;

        /** \brief The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). */
        int max_pts_per_cluster_;

        /** \brief Class getName method. */
        virtual std::string getClassName () const { return ("gpu::EuclideanLabeledClusterExtraction"); }
    };
    /** \brief Sort clusters method (for std::sort). 
      * \ingroup segmentation
      */
    inline bool 
      compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
    {
      return (a.indices.size () < b.indices.size ());
    }
  }
}
