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#pragma once

#include <pcl/features/feature.h>

namespace pcl
{
  /** \brief IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud 
    * dataset containing points and intensity.  For more information about the intensity-domain spin image descriptor, 
    * see:
    *
    *   Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. 
    *   A sparse texture representation using local affine regions. 
    *   In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 27, pages 1265-1278, August 2005.
    * \author Michael Dixon
    * \ingroup features
    */
  template <typename PointInT, typename PointOutT>
  class IntensitySpinEstimation: public Feature<PointInT, PointOutT>
  {
    public:
      using Ptr = shared_ptr<IntensitySpinEstimation<PointInT, PointOutT> >;
      using ConstPtr = shared_ptr<const IntensitySpinEstimation<PointInT, PointOutT> >;
      using Feature<PointInT, PointOutT>::feature_name_;
      using Feature<PointInT, PointOutT>::getClassName;

      using Feature<PointInT, PointOutT>::input_;
      using Feature<PointInT, PointOutT>::indices_;
      using Feature<PointInT, PointOutT>::surface_;

      using Feature<PointInT, PointOutT>::tree_;
      using Feature<PointInT, PointOutT>::search_radius_;
      
      using PointCloudIn = pcl::PointCloud<PointInT>;
      using PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut;

      /** \brief Empty constructor. */
      IntensitySpinEstimation () : nr_distance_bins_ (4), nr_intensity_bins_ (5), sigma_ (1.0)
      {
        feature_name_ = "IntensitySpinEstimation";
      };

      /** \brief Estimate the intensity-domain spin image descriptor for a given point based on its spatial
        * neighborhood of 3D points and their intensities. 
        * \param[in] cloud the dataset containing the Cartesian coordinates and intensity values of the points
        * \param[in] radius the radius of the feature
        * \param[in] sigma the standard deviation of the Gaussian smoothing kernel to use during the soft histogram update
        * \param[in] k the number of neighbors to use from \a indices and \a squared_distances
        * \param[in] indices the indices of the points that comprise the query point's neighborhood
        * \param[in] squared_distances the squared distances from the query point to each point in the neighborhood
        * \param[out] intensity_spin_image the resultant intensity-domain spin image descriptor
        */
      void 
      computeIntensitySpinImage (const PointCloudIn &cloud, 
                                 float radius, float sigma, int k, 
                                 const std::vector<int> &indices, 
                                 const std::vector<float> &squared_distances, 
                                 Eigen::MatrixXf &intensity_spin_image);

      /** \brief Set the number of bins to use in the distance dimension of the spin image
        * \param[in] nr_distance_bins the number of bins to use in the distance dimension of the spin image
        */
      inline void 
      setNrDistanceBins (std::size_t nr_distance_bins) { nr_distance_bins_ = static_cast<int> (nr_distance_bins); };

      /** \brief Returns the number of bins in the distance dimension of the spin image. */
      inline int 
      getNrDistanceBins () { return (nr_distance_bins_); };

      /** \brief Set the number of bins to use in the intensity dimension of the spin image.
        * \param[in] nr_intensity_bins the number of bins to use in the intensity dimension of the spin image
        */
      inline void 
      setNrIntensityBins (std::size_t nr_intensity_bins) { nr_intensity_bins_ = static_cast<int> (nr_intensity_bins); };

      /** \brief Returns the number of bins in the intensity dimension of the spin image. */
      inline int 
      getNrIntensityBins () { return (nr_intensity_bins_); };

      /** \brief Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images.  
        * \param[in] sigma the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images
        */
      inline void 
      setSmoothingBandwith (float sigma) { sigma_ = sigma; };

      /** \brief Returns the standard deviation of the Gaussian smoothing kernel used to construct the spin images.  */
      inline float 
      getSmoothingBandwith () { return (sigma_); };


      /** \brief Estimate the intensity-domain descriptors at a set of points given by <setInputCloud (), setIndices ()>
        *  using the surface in setSearchSurface (), and the spatial locator in setSearchMethod ().
        * \param[out] output the resultant point cloud model dataset that contains the intensity-domain spin image features
        */
      void 
      computeFeature (PointCloudOut &output) override;
    
      /** \brief The number of distance bins in the descriptor. */
      int nr_distance_bins_;

      /** \brief The number of intensity bins in the descriptor. */
      int nr_intensity_bins_;

      /** \brief The standard deviation of the Gaussian smoothing kernel used to construct the spin images. */
      float sigma_;
  };
}

#ifdef PCL_NO_PRECOMPILE
#include <pcl/features/impl/intensity_spin.hpp>
#endif




