PCL均匀采样

代码如下：

#include <pcl/PCLPointCloud2.h>
#include <pcl/io/pcd_io.h>
#include <pcl/filters/uniform_sampling.h>
#include <pcl/console/print.h>
#include <pcl/console/parse.h>
#include <pcl/console/time.h>

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

double default_radius = 0.01;

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 leaf size of X,X,X to uniformly select 1 point per leaf (default: "); 
  print_value ("%f", default_radius); print_info (")\n");
}

bool
loadCloud (const 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 ());

  return (true);
}

void
compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output,
         double radius)
{
  // Convert data to PointCloud<T>
  PointCloud<PointXYZ>::Ptr xyz (new PointCloud<PointXYZ>);
  fromPCLPointCloud2 (*input, *xyz);

  // Estimate
  TicToc tt;
  tt.tic ();
  
  print_highlight (stderr, "Computing ");

  UniformSampling<PointXYZ> us;
  us.setInputCloud (xyz);
  us.setRadiusSearch (radius);
  PointCloud<PointXYZ> output_;
  us.filter (output_);

  print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output_.size()); print_info (" points]\n");

  // Convert data back
  toPCLPointCloud2 (output_, output);
}

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

  print_highlight ("Saving "); print_value ("%s ", filename.c_str ());

  PCDWriter w;
  w.writeBinaryCompressed (filename, output, translation, orientation);
  
  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 ("Uniform subsampling using UniformSampling. For more information, use: %s -h\n", argv[0]);

  if (argc < 3)
  {
    printHelp (argc, argv);
    return (-1);
  }

  // Parse the command line arguments for .pcd files
  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);
  print_info ("Extracting uniform points with a leaf size of: "); 
  print_value ("%f\n", radius); 

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

  // Perform the keypoint estimation
  pcl::PCLPointCloud2 output;
  compute (cloud, output, radius);

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

来源：PCL官方示例

标签：采样,info,file,value,radius,PCL,均匀,print,output
来源： https://blog.csdn.net/com1098247427/article/details/120713140