passthrough_filter.cpp
Go to the documentation of this file.
00001 /*
00002  * Software License Agreement (BSD License)
00003  *
00004  *  Point Cloud Library (PCL) - www.pointclouds.org
00005  *  Copyright (c) 2010-2011, Willow Garage, Inc.
00006  *
00007  *  All rights reserved.
00008  *
00009  *  Redistribution and use in source and binary forms, with or without
00010  *  modification, are permitted provided that the following conditions
00011  *  are met:
00012  *
00013  *   * Redistributions of source code must retain the above copyright
00014  *     notice, this list of conditions and the following disclaimer.
00015  *   * Redistributions in binary form must reproduce the above
00016  *     copyright notice, this list of conditions and the following
00017  *     disclaimer in the documentation and/or other materials provided
00018  *     with the distribution.
00019  *   * Neither the name of the copyright holder(s) nor the names of its
00020  *     contributors may be used to endorse or promote products derived
00021  *     from this software without specific prior written permission.
00022  *
00023  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
00024  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
00025  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
00026  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
00027  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
00028  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
00029  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
00030  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
00031  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
00032  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
00033  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
00034  *  POSSIBILITY OF SUCH DAMAGE.
00035  *
00036  * $Id$
00037  */
00038 
00039 #include <pcl/PCLPointCloud2.h>
00040 #include <pcl/point_types.h>
00041 #include <pcl/io/pcd_io.h>
00042 #include <pcl/console/print.h>
00043 #include <pcl/console/parse.h>
00044 #include <pcl/console/time.h>
00045 #include <pcl/filters/passthrough.h>
00046 
00047 
00048 using namespace std;
00049 using namespace pcl;
00050 using namespace pcl::io;
00051 using namespace pcl::console;
00052 
00053 float default_min = 0.0f,
00054       default_max = 1.0f;
00055 bool default_inside = true;
00056 bool default_keep_organized = true;
00057 std::string default_field_name = "z";
00058 
00059 void
00060 printHelp (int, char **argv)
00061 {
00062   print_error ("Syntax is: %s input.pcd output.pcd <options>\n", argv[0]);
00063   print_info ("  where options are:\n");
00064   print_info ("                     -field X = the field of the point cloud we want to apply the filter to (default: ");
00065   print_value ("%s", default_field_name.c_str ()); print_info (")\n");
00066   print_info ("                     -min X = lower limit of the filter (default: ");
00067   print_value ("%f", default_min); print_info (")\n");
00068   print_info ("                     -max X = upper limit of the filter (default: ");
00069   print_value ("%f", default_max); print_info (")\n");
00070   print_info ("                     -inside X = keep the points inside the [min, max] interval or not (default: ");
00071   print_value ("%d", default_inside); print_info (")\n");
00072   print_info ("                     -keep 0/1 = keep the points organized (1) or not (default: ");
00073   print_value ("%d", default_keep_organized); print_info (")\n");
00074 }
00075 
00076 bool
00077 loadCloud (const std::string &filename, pcl::PCLPointCloud2 &cloud)
00078 {
00079   TicToc tt;
00080   print_highlight ("Loading "); print_value ("%s ", filename.c_str ());
00081 
00082   tt.tic ();
00083   if (loadPCDFile (filename, cloud) < 0)
00084     return (false);
00085   print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", cloud.width * cloud.height); print_info (" points]\n");
00086   print_info ("Available dimensions: "); print_value ("%s\n", pcl::getFieldsList (cloud).c_str ());
00087 
00088   return (true);
00089 }
00090 
00091 void
00092 compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output,
00093          std::string field_name, float min, float max, bool inside, bool keep_organized)
00094 {
00095   // Estimate
00096   TicToc tt;
00097   tt.tic ();
00098 
00099   print_highlight (stderr, "Computing ");
00100 
00101   PassThrough<pcl::PCLPointCloud2> passthrough_filter;
00102   passthrough_filter.setInputCloud (input);
00103   passthrough_filter.setFilterFieldName (field_name);
00104   passthrough_filter.setFilterLimits (min, max);
00105   passthrough_filter.setFilterLimitsNegative (!inside);
00106   passthrough_filter.setKeepOrganized (keep_organized);
00107   passthrough_filter.filter (output);
00108 
00109   print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output.width * output.height); print_info (" points]\n");
00110 }
00111 
00112 void
00113 saveCloud (const std::string &filename, const pcl::PCLPointCloud2 &output)
00114 {
00115   TicToc tt;
00116   tt.tic ();
00117 
00118   print_highlight ("Saving "); print_value ("%s ", filename.c_str ());
00119 
00120   PCDWriter w;
00121   w.writeBinaryCompressed (filename, output);
00122 
00123   print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output.width * output.height); print_info (" points]\n");
00124 }
00125 
00126 int
00127 batchProcess (const vector<string> &pcd_files, string &output_dir,
00128               std::string field_name, float min, float max, bool inside, bool keep_organized)
00129 {
00130   vector<string> st;
00131   for (size_t i = 0; i < pcd_files.size (); ++i)
00132   {
00133     // Load the first file
00134     pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2);
00135     if (!loadCloud (pcd_files[i], *cloud)) 
00136       return (-1);
00137 
00138     // Perform the feature estimation
00139     pcl::PCLPointCloud2 output;
00140     compute (cloud, output, field_name, min, max, inside, keep_organized);
00141 
00142     // Prepare output file name
00143     string filename = pcd_files[i];
00144     boost::trim (filename);
00145     boost::split (st, filename, boost::is_any_of ("/\\"), boost::token_compress_on);
00146     
00147     // Save into the second file
00148     stringstream ss;
00149     ss << output_dir << "/" << st.at (st.size () - 1);
00150     saveCloud (ss.str (), output);
00151   }
00152   return (0);
00153 }
00154 
00155 
00156 /* ---[ */
00157 int
00158 main (int argc, char** argv)
00159 {
00160   print_info ("Filter a point cloud using the pcl::PassThroughFilterEstimate. For more information, use: %s -h\n", argv[0]);
00161 
00162   if (argc < 3)
00163   {
00164     printHelp (argc, argv);
00165     return (-1);
00166   }
00167 
00168   bool batch_mode = false;
00169 
00170   // Command line parsing
00171   float min = default_min, max = default_max;
00172   bool inside = default_inside;
00173   bool keep_organized = default_keep_organized;
00174   std::string field_name = default_field_name;
00175   parse_argument (argc, argv, "-min", min);
00176   parse_argument (argc, argv, "-max", max);
00177   parse_argument (argc, argv, "-inside", inside);
00178   parse_argument (argc, argv, "-field", field_name);
00179   parse_argument (argc, argv, "-keep", keep_organized);
00180   string input_dir, output_dir;
00181   if (parse_argument (argc, argv, "-input_dir", input_dir) != -1)
00182   {
00183     PCL_INFO ("Input directory given as %s. Batch process mode on.\n", input_dir.c_str ());
00184     if (parse_argument (argc, argv, "-output_dir", output_dir) == -1)
00185     {
00186       PCL_ERROR ("Need an output directory! Please use -output_dir to continue.\n");
00187       return (-1);
00188     }
00189 
00190     // Both input dir and output dir given, switch into batch processing mode
00191     batch_mode = true;
00192   }
00193 
00194   if (!batch_mode)
00195   {
00196     // Parse the command line arguments for .pcd files
00197     std::vector<int> p_file_indices;
00198     p_file_indices = parse_file_extension_argument (argc, argv, ".pcd");
00199     if (p_file_indices.size () != 2)
00200     {
00201       print_error ("Need one input PCD file and one output PCD file to continue.\n");
00202       return (-1);
00203     }
00204 
00205     // Load the first file
00206     pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2);
00207     if (!loadCloud (argv[p_file_indices[0]], *cloud))
00208       return (-1);
00209 
00210     // Perform the feature estimation
00211     pcl::PCLPointCloud2 output;
00212     compute (cloud, output, field_name, min, max, inside, keep_organized);
00213 
00214     // Save into the second file
00215     saveCloud (argv[p_file_indices[1]], output);
00216   }
00217   else
00218   {
00219     if (input_dir != "" && boost::filesystem::exists (input_dir))
00220     {
00221       vector<string> pcd_files;
00222       boost::filesystem::directory_iterator end_itr;
00223       for (boost::filesystem::directory_iterator itr (input_dir); itr != end_itr; ++itr)
00224       {
00225         // Only add PCD files
00226         if (!is_directory (itr->status ()) && boost::algorithm::to_upper_copy (boost::filesystem::extension (itr->path ())) == ".PCD" )
00227         {
00228           pcd_files.push_back (itr->path ().string ());
00229           PCL_INFO ("[Batch processing mode] Added %s for processing.\n", itr->path ().string ().c_str ());
00230         }
00231       }
00232       batchProcess (pcd_files, output_dir, field_name, min, max, inside, keep_organized);
00233     }
00234     else
00235     {
00236       PCL_ERROR ("Batch processing mode enabled, but invalid input directory (%s) given!\n", input_dir.c_str ());
00237       return (-1);
00238     }
00239   }
00240 }


pcl
Author(s): Open Perception
autogenerated on Wed Aug 26 2015 15:27:52