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#pragma once

#include <pcl/registration/correspondence_rejection.h>
#include <pcl/conversions.h> // for fromPCLPointCloud2
#include <pcl/memory.h>      // for static_pointer_cast
#include <pcl/point_cloud.h>

namespace pcl {
namespace registration {
/** \brief CorrespondenceRejectorMedianDistance implements a simple correspondence
 * rejection method based on thresholding based on the median distance between the
 * correspondences.
 *
 * \note If \ref setInputCloud and \ref setInputTarget are given, then the
 * distances between correspondences will be estimated using the given XYZ
 * data, and not read from the set of input correspondences.
 *
 * \author Aravindhan K Krishnan. This code is ported from libpointmatcher
 * (https://github.com/ethz-asl/libpointmatcher) \ingroup registration
 */
class PCL_EXPORTS CorrespondenceRejectorMedianDistance : public CorrespondenceRejector {
  using CorrespondenceRejector::getClassName;
  using CorrespondenceRejector::input_correspondences_;
  using CorrespondenceRejector::rejection_name_;

public:
  using Ptr = shared_ptr<CorrespondenceRejectorMedianDistance>;
  using ConstPtr = shared_ptr<const CorrespondenceRejectorMedianDistance>;

  /** \brief Empty constructor. */
  CorrespondenceRejectorMedianDistance() : median_distance_(0), factor_(1.0)
  {
    rejection_name_ = "CorrespondenceRejectorMedianDistance";
  }

  /** \brief Get a list of valid correspondences after rejection from the original set
   * of correspondences. \param[in] original_correspondences the set of initial
   * correspondences given \param[out] remaining_correspondences the resultant filtered
   * set of remaining correspondences
   */
  void
  getRemainingCorrespondences(const pcl::Correspondences& original_correspondences,
                              pcl::Correspondences& remaining_correspondences) override;

  /** \brief Get the median distance used for thresholding in correspondence rejection.
   */
  inline double
  getMedianDistance() const
  {
    return (median_distance_);
  };

  /** \brief Provide a source point cloud dataset (must contain XYZ
   * data!), used to compute the correspondence distance.
   * \param[in] cloud a cloud containing XYZ data
   */
  template <typename PointT>
  inline void
  setInputSource(const typename pcl::PointCloud<PointT>::ConstPtr& cloud)
  {
    if (!data_container_)
      data_container_.reset(new DataContainer<PointT>);
    static_pointer_cast<DataContainer<PointT>>(data_container_)->setInputSource(cloud);
  }

  /** \brief Provide a target point cloud dataset (must contain XYZ
   * data!), used to compute the correspondence distance.
   * \param[in] target a cloud containing XYZ data
   */
  template <typename PointT>
  inline void
  setInputTarget(const typename pcl::PointCloud<PointT>::ConstPtr& target)
  {
    if (!data_container_)
      data_container_.reset(new DataContainer<PointT>);
    static_pointer_cast<DataContainer<PointT>>(data_container_)->setInputTarget(target);
  }

  /** \brief See if this rejector requires source points */
  bool
  requiresSourcePoints() const override
  {
    return (true);
  }

  /** \brief Blob method for setting the source cloud */
  void
  setSourcePoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
  {
    PointCloud<PointXYZ>::Ptr cloud(new PointCloud<PointXYZ>);
    fromPCLPointCloud2(*cloud2, *cloud);
    setInputSource<PointXYZ>(cloud);
  }

  /** \brief See if this rejector requires a target cloud */
  bool
  requiresTargetPoints() const override
  {
    return (true);
  }

  /** \brief Method for setting the target cloud */
  void
  setTargetPoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
  {
    PointCloud<PointXYZ>::Ptr cloud(new PointCloud<PointXYZ>);
    fromPCLPointCloud2(*cloud2, *cloud);
    setInputTarget<PointXYZ>(cloud);
  }

  /** \brief Provide a pointer to the search object used to find correspondences in
   * the target cloud.
   * \param[in] tree a pointer to the spatial search object.
   * \param[in] force_no_recompute If set to true, this tree will NEVER be
   * recomputed, regardless of calls to setInputTarget. Only use if you are
   * confident that the tree will be set correctly.
   */
  template <typename PointT>
  inline void
  setSearchMethodTarget(const typename pcl::search::KdTree<PointT>::Ptr& tree,
                        bool force_no_recompute = false)
  {
    static_pointer_cast<DataContainer<PointT>>(data_container_)
        ->setSearchMethodTarget(tree, force_no_recompute);
  }

  /** \brief Set the factor for correspondence rejection. Points with distance greater
   * than median times factor will be rejected \param[in] factor value
   */
  inline void
  setMedianFactor(double factor)
  {
    factor_ = factor;
  };

  /** \brief Get the factor used for thresholding in correspondence rejection. */
  inline double
  getMedianFactor() const
  {
    return factor_;
  };

protected:
  /** \brief Apply the rejection algorithm.
   * \param[out] correspondences the set of resultant correspondences.
   */
  inline void
  applyRejection(pcl::Correspondences& correspondences) override
  {
    getRemainingCorrespondences(*input_correspondences_, correspondences);
  }

  /** \brief The median distance threshold between two correspondent points in source
   * <-> target.
   */
  double median_distance_;

  /** \brief The factor for correspondence rejection. Points with distance greater than
   * median times factor will be rejected
   */
  double factor_;

  using DataContainerPtr = DataContainerInterface::Ptr;

  /** \brief A pointer to the DataContainer object containing the input and target point
   * clouds */
  DataContainerPtr data_container_;
};
} // namespace registration
} // namespace pcl
