spin_estimation.cpp

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#include <pcl/PCLPointCloud2.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/spin_image.h>
#include <pcl/console/print.h>
#include <pcl/console/parse.h>
#include <pcl/console/time.h>

using namespace pcl;
using namespace pcl::io;
using namespace pcl::console;

POINT_CLOUD_REGISTER_POINT_STRUCT (pcl::Histogram<153>,
  (float[153], histogram, spinimage)
)

int    default_image_width = 8;
double default_support_angle = 0.5;
int    default_min_neigh = 1;
double default_radius = 0.0;

Eigen::Vector4f    translation;
Eigen::Quaternionf orientation;

void
printHelp (int, char **argv)
{
  print_error ("Syntax is: %s input.pcd output.pcd <options>\n", argv[0]);
  print_info ("  where options are:\n");
  print_info ("                     -radius X     = use a radius of Xm around each point to determine the neighborhood (default: "); 
  print_value ("%f", default_radius); print_info (")\n");
  print_info ("                     -width X      = resolution (width) of a spin-image (default: "); 
  print_value ("%d", default_image_width); print_info (")\n");
  print_info ("                     -suppangle X  = min cosine of support angle for filtering points by normals (default: "); 
  print_value ("%f", default_support_angle); print_info (")\n");
  print_info ("                     -neigh X      = min number of neighbours to compute a spin-image (default: "); 
  print_value ("%d", default_min_neigh); print_info (")\n");

  print_info ("                     -radial        = toggles radial structure of a spin-image (default: false)\n");
  print_info ("                     -angular       = toggles angular domain of a spin-image (default: false)\n");
}

bool
loadCloud (const std::string &filename, pcl::PCLPointCloud2 &cloud)
{
  TicToc tt;
  print_highlight ("Loading "); print_value ("%s ", filename.c_str ());

  tt.tic ();
  if (loadPCDFile (filename, cloud, translation, orientation) < 0)
    return (false);
  print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", cloud.width * cloud.height); print_info (" points]\n");
  print_info ("Available dimensions: "); print_value ("%s\n", getFieldsList (cloud).c_str ());

  // Check if the dataset has normals
  if (getFieldIndex (cloud, "normal_x") == -1)
  {
    print_error ("The input dataset does not contain normal information!\n");
    return (false);
  }
  return (true);
}



void
saveCloud (const std::string &filename, const pcl::PCLPointCloud2 &output)
{
  TicToc tt;
  tt.tic ();

  print_highlight ("Saving "); print_value ("%s ", filename.c_str ());
  
  io::savePCDFile (filename, output, translation, orientation, false);
  
  print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output.width * output.height); print_info (" points]\n");
}

/* ---[ */
int
main (int argc, char** argv)
{
  print_info ("Estimate spin-image descriptors using pcl::SpinEstimation. For more information, use: %s -h\n", argv[0]);
  bool help = false;
  parse_argument (argc, argv, "-h", help);
  if (argc < 3 || help)
  {
    printHelp (argc, argv);
    return (-1);
  }

  // Parse the command line arguments for .pcd files
  std::vector<int> p_file_indices;
  p_file_indices = parse_file_extension_argument (argc, argv, ".pcd");
  if (p_file_indices.size () != 2)
  {
    print_error ("Need one input PCD file and one output PCD file to continue.\n");
    return (-1);
  }

  // Command line parsing
  double radius = default_radius;
  parse_argument (argc, argv, "-radius", radius);
  int    image_width = default_image_width;
  parse_argument (argc, argv, "-width", image_width);
  double support_angle = default_support_angle;
  parse_argument (argc, argv, "-suppangle", support_angle);
  int min_neigh = default_min_neigh;
  parse_argument (argc, argv, "-neigh", min_neigh);

  // Load the first file
  pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2);
  if (!loadCloud (argv[p_file_indices[0]], *cloud)) 
    return (-1);

  // Perform the feature estimation
  pcl::PCLPointCloud2 output;
  
  // Convert data to PointCloud<T>
  PointCloud<PointNormal>::Ptr xyznormals (new PointCloud<PointNormal>);
  fromPCLPointCloud2 (*cloud, *xyznormals);

  // Estimate
  TicToc tt;
  tt.tic ();

  print_highlight (stderr, "Computing ");

  using SpinImage = Histogram<153>;
  SpinImageEstimation<PointNormal, PointNormal, SpinImage> spin_est (image_width, support_angle, min_neigh); 
  //spin_est.setInputWithNormals (xyznormals, xyznormals);
  spin_est.setInputCloud (xyznormals);
  spin_est.setInputNormals (xyznormals);
  spin_est.setSearchMethod (search::KdTree<PointNormal>::Ptr (new search::KdTree<PointNormal>));
  spin_est.setRadiusSearch (radius);

  if (find_argument(argc, argv, "-radial") > 0)
    spin_est.setRadialStructure();

  if (find_argument(argc, argv, "-angular") > 0)
    spin_est.setAngularDomain();

  PointCloud<SpinImage> descriptors;
  spin_est.compute (descriptors);

  print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", descriptors.width * descriptors.height); print_info (" points]\n");

  // Convert data back
  pcl::PCLPointCloud2 output_descr;
  toPCLPointCloud2 (descriptors, output_descr);
  concatenateFields (*cloud, output_descr, output);


  // Save into the second file
  saveCloud (argv[p_file_indices[1]], output);
}