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 * $Id: test_pfh_estimation.cpp 4747 2012-02-26 20:51:51Z svn $
 *
 */

#include <pcl/test/gtest.h>
#include <pcl/point_cloud.h>
#include <pcl/features/normal_3d.h>
#include <pcl/features/cvfh.h>
#include <pcl/io/pcd_io.h>
#include <pcl/filters/voxel_grid.h>

using namespace pcl;
using namespace pcl::io;
using namespace std;

using KdTreePtr = search::KdTree<PointXYZ>::Ptr;
using CloudPtr = PointCloud<PointXYZ>::Ptr;

PointCloud<PointXYZ> cloud;
std::vector<int> indices;
KdTreePtr tree;

CloudPtr cloud_milk;
KdTreePtr tree_milk;
float leaf_size_ = 0.005f;

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (PCL, CVFHEstimation)
{
  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  // set parameters
  n.setInputCloud (cloud.makeShared ());
  pcl::IndicesPtr indicesptr (new pcl::Indices (indices));
  n.setIndices (indicesptr);
  n.setSearchMethod (tree);
  n.setKSearch (10); // Use 10 nearest neighbors to estimate the normals
  // estimate
  n.compute (*normals);
  CVFHEstimation<PointXYZ, Normal, VFHSignature308> cvfh;
  cvfh.setInputNormals (normals);

  // Object
  PointCloud<VFHSignature308>::Ptr vfhs (new PointCloud<VFHSignature308> ());

  // set parameters
  cvfh.setInputCloud (cloud.makeShared ());
  cvfh.setIndices (indicesptr);
  cvfh.setSearchMethod (tree);

  // estimate
  cvfh.compute (*vfhs);
  EXPECT_EQ (static_cast<int>(vfhs->points.size ()), 1);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (PCL, CVFHEstimationMilk)
{

  // Estimate normals first
  NormalEstimation<PointXYZ, Normal> n;
  PointCloud<Normal>::Ptr normals (new PointCloud<Normal> ());
  n.setInputCloud (cloud_milk);
  n.setSearchMethod (tree);
  n.setRadiusSearch (leaf_size_ * 4); //2cm to estimate normals
  n.compute (*normals);

  CVFHEstimation<PointXYZ, Normal, VFHSignature308> cvfh;
  cvfh.setInputCloud (cloud_milk);
  cvfh.setInputNormals (normals);
  cvfh.setSearchMethod (tree_milk);
  cvfh.setClusterTolerance (leaf_size_ * 3);
  cvfh.setEPSAngleThreshold (0.13f);
  cvfh.setCurvatureThreshold (0.025f);
  cvfh.setNormalizeBins (false);
  cvfh.setRadiusNormals (leaf_size_ * 4);

  // Object
  PointCloud<VFHSignature308>::Ptr vfhs (new PointCloud<VFHSignature308> ());

  // estimate
  cvfh.compute (*vfhs);
  EXPECT_EQ (static_cast<int>(vfhs->points.size ()), 2);
}

/* ---[ */
int
main (int argc, char** argv)
{
  if (argc < 3)
  {
    std::cerr << "No test file given. Please download `bun0.pcd` and `milk.pcd` pass its path to the test." << std::endl;
    return (-1);
  }

  if (loadPCDFile<PointXYZ> (argv[1], cloud) < 0)
  {
    std::cerr << "Failed to read test file. Please download `bun0.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  CloudPtr milk_loaded(new PointCloud<PointXYZ>());
  if (loadPCDFile<PointXYZ> (argv[2], *milk_loaded) < 0)
  {
    std::cerr << "Failed to read test file. Please download `milk.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  indices.resize (cloud.points.size ());
  for (std::size_t i = 0; i < indices.size (); ++i)
  {
    indices[i] = static_cast<int>(i);
  }

  tree.reset (new search::KdTree<PointXYZ> (false));
  tree->setInputCloud (cloud.makeShared ());

  cloud_milk.reset(new PointCloud<PointXYZ>());
  CloudPtr grid;
  pcl::VoxelGrid < pcl::PointXYZ > grid_;
  grid_.setInputCloud (milk_loaded);
  grid_.setLeafSize (leaf_size_, leaf_size_, leaf_size_);
  grid_.filter (*cloud_milk);

  tree_milk.reset (new search::KdTree<PointXYZ> (false));
  tree_milk->setInputCloud (cloud_milk);

  testing::InitGoogleTest (&argc, argv);
  return (RUN_ALL_TESTS ());
}
/* ]--- */
