/*
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 *
 * Point Cloud Library (PCL) - www.pointclouds.org
 * Copyright (c) 2009-2011, Willow Garage, Inc.
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// STL
#include <iostream>

// PCL
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/common/io.h>
#include <pcl/features/normal_3d.h>
#include <pcl/kdtree/kdtree_flann.h>
#include <pcl/features/rift.h>
#include <pcl/features/intensity_gradient.h>

int
main (int, char** argv)
{
  std::string filename = argv[1];
  std::cout << "Reading " << filename << std::endl;

  pcl::PointCloud<pcl::PointXYZI>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZI>);

  if (pcl::io::loadPCDFile<pcl::PointXYZI> (filename, *cloud) == -1) // load the file
  {
    PCL_ERROR ("Couldn't read file");
    return -1;
  }

  std::cout << "points: " << cloud->points.size () << std::endl;

  // Estimate the surface normals
  pcl::PointCloud<pcl::Normal>::Ptr cloud_n (new pcl::PointCloud<pcl::Normal>);
  pcl::NormalEstimation<pcl::PointXYZI, pcl::Normal> norm_est;
  norm_est.setInputCloud(cloud);
  pcl::search::KdTree<pcl::PointXYZI>::Ptr treept1 (new pcl::search::KdTree<pcl::PointXYZI> (false));
  norm_est.setSearchMethod(treept1);
  norm_est.setRadiusSearch(0.25);
  norm_est.compute(*cloud_n);

  std::cout<<" Surface normals estimated";
  std::cout<<" with size "<< cloud_n->points.size() <<std::endl;
 
  // Estimate the Intensity Gradient
  pcl::PointCloud<pcl::IntensityGradient>::Ptr cloud_ig (new pcl::PointCloud<pcl::IntensityGradient>);
  pcl::IntensityGradientEstimation<pcl::PointXYZI, pcl::Normal, pcl::IntensityGradient> gradient_est;
  gradient_est.setInputCloud(cloud);
  gradient_est.setInputNormals(cloud_n);
  pcl::search::KdTree<pcl::PointXYZI>::Ptr treept2 (new pcl::search::KdTree<pcl::PointXYZI> (false));
  gradient_est.setSearchMethod(treept2);
  gradient_est.setRadiusSearch(0.25);
  gradient_est.compute(*cloud_ig);
  std::cout<<" Intesity Gradient estimated";
  std::cout<<" with size "<< cloud_ig->points.size() <<std::endl;


  // Estimate the RIFT feature
  pcl::RIFTEstimation<pcl::PointXYZI, pcl::IntensityGradient, pcl::Histogram<32> > rift_est;
  pcl::search::KdTree<pcl::PointXYZI>::Ptr treept3 (new pcl::search::KdTree<pcl::PointXYZI> (false));
  rift_est.setSearchMethod(treept3);
  rift_est.setRadiusSearch(10.0);
  rift_est.setNrDistanceBins (4);
  rift_est.setNrGradientBins (8);
  rift_est.setInputCloud(cloud);
  rift_est.setInputGradient(cloud_ig);
  pcl::PointCloud<pcl::Histogram<32> > rift_output;
  rift_est.compute(rift_output);

  std::cout<<" RIFT feature estimated";
  std::cout<<" with size "<<rift_output.points.size()<<std::endl;
  
  // Display and retrieve the rift descriptor vector for the first point
  pcl::Histogram<32> first_descriptor = rift_output.points[0];
  std::cout << first_descriptor << std::endl;
  return 0;
}
