1 /*
2 * Software License Agreement (BSD License)
3 *
4 * Point Cloud Library (PCL) - www.pointclouds.org
5 * Copyright (c) 2010-2011, Willow Garage, Inc.
6 * Copyright (c) 2012-, Open Perception, Inc.
7 *
8 * All rights reserved.
9 *
10 * Redistribution and use in source and binary forms, with or without
11 * modification, are permitted provided that the following conditions
12 * are met:
13 *
14 * * Redistributions of source code must retain the above copyright
15 * notice, this list of conditions and the following disclaimer.
16 * * Redistributions in binary form must reproduce the above
17 * copyright notice, this list of conditions and the following
18 * disclaimer in the documentation and/or other materials provided
19 * with the distribution.
20 * * Neither the name of the copyright holder(s) nor the names of its
21 * contributors may be used to endorse or promote products derived
22 * from this software without specific prior written permission.
23 *
24 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
25 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
26 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
27 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
28 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
29 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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31 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
32 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
33 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
34 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
35 * POSSIBILITY OF SUCH DAMAGE.
36 *
37 * $Id$
38 *
39 */
40
41 #include <pcl/PCLPointCloud2.h>
42 #include <pcl/io/pcd_io.h>
43 #include <pcl/features/normal_3d.h>
44 #include <pcl/features/integral_image_normal.h>
45 #include <pcl/console/print.h>
46 #include <pcl/console/parse.h>
47 #include <pcl/console/time.h>
48 #include <boost/filesystem.hpp> // for path, exists, ...
49 #include <boost/algorithm/string/case_conv.hpp> // for to_upper_copy
50
51 using namespace pcl;
52 using namespace pcl::io;
53 using namespace pcl::console;
54
55 int default_k = 0;
56 double default_radius = 0.0;
57
58 void
printHelp(int,char ** argv)59 printHelp (int, char **argv)
60 {
61 print_error ("Syntax is: %s input.pcd output.pcd <options> [optional_arguments]\n", argv[0]);
62 print_info (" where options are:\n");
63 print_info (" -radius X = use a radius of Xm around each point to determine the neighborhood (default: ");
64 print_value ("%f", default_radius); print_info (")\n");
65 print_info (" -k X = use a fixed number of X-nearest neighbors around each point (default: ");
66 print_value ("%f", default_k); print_info (")\n");
67 print_info (" For organized datasets, an IntegralImageNormalEstimation approach will be used, with the RADIUS given value as SMOOTHING SIZE.\n");
68 print_info ("\nOptional arguments are:\n");
69 print_info (" -input_dir X = batch process all PCD files found in input_dir\n");
70 print_info (" -output_dir X = save the processed files from input_dir in this directory\n");
71 }
72
73 bool
loadCloud(const std::string & filename,pcl::PCLPointCloud2 & cloud,Eigen::Vector4f & translation,Eigen::Quaternionf & orientation)74 loadCloud (const std::string &filename, pcl::PCLPointCloud2 &cloud,
75 Eigen::Vector4f &translation, Eigen::Quaternionf &orientation)
76 {
77 if (loadPCDFile (filename, cloud, translation, orientation) < 0)
78 return (false);
79
80 return (true);
81 }
82
83 void
compute(const pcl::PCLPointCloud2::ConstPtr & input,pcl::PCLPointCloud2 & output,int k,double radius)84 compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output,
85 int k, double radius)
86 {
87 // Convert data to PointCloud<T>
88 PointCloud<PointXYZ>::Ptr xyz (new PointCloud<PointXYZ>);
89 fromPCLPointCloud2 (*input, *xyz);
90
91 TicToc tt;
92 tt.tic ();
93
94 PointCloud<Normal> normals;
95
96 // Try our luck with organized integral image based normal estimation
97 if (xyz->isOrganized ())
98 {
99 IntegralImageNormalEstimation<PointXYZ, Normal> ne;
100 ne.setInputCloud (xyz);
101 ne.setNormalEstimationMethod (IntegralImageNormalEstimation<PointXYZ, Normal>::COVARIANCE_MATRIX);
102 ne.setNormalSmoothingSize (float (radius));
103 ne.setDepthDependentSmoothing (true);
104 ne.compute (normals);
105 }
106 else
107 {
108 NormalEstimation<PointXYZ, Normal> ne;
109 ne.setInputCloud (xyz);
110 ne.setSearchMethod (search::KdTree<PointXYZ>::Ptr (new search::KdTree<PointXYZ>));
111 ne.setKSearch (k);
112 ne.setRadiusSearch (radius);
113 ne.compute (normals);
114 }
115
116 print_highlight ("Computed normals in "); print_value ("%g", tt.toc ()); print_info (" ms for "); print_value ("%d", normals.width * normals.height); print_info (" points.\n");
117
118 // Convert data back
119 pcl::PCLPointCloud2 output_normals;
120 toPCLPointCloud2 (normals, output_normals);
121 concatenateFields (*input, output_normals, output);
122 }
123
124 void
saveCloud(const std::string & filename,const pcl::PCLPointCloud2 & output,const Eigen::Vector4f & translation,const Eigen::Quaternionf & orientation)125 saveCloud (const std::string &filename, const pcl::PCLPointCloud2 &output,
126 const Eigen::Vector4f &translation, const Eigen::Quaternionf &orientation)
127 {
128 PCDWriter w;
129 w.writeBinaryCompressed (filename, output, translation, orientation);
130 }
131
132 int
batchProcess(const std::vector<std::string> & pcd_files,std::string & output_dir,int k,double radius)133 batchProcess (const std::vector<std::string> &pcd_files, std::string &output_dir, int k, double radius)
134 {
135 #pragma omp parallel for \
136 default(none) \
137 shared(k, output_dir, pcd_files, radius)
138 for (int i = 0; i < int (pcd_files.size ()); ++i)
139 {
140 // Load the first file
141 Eigen::Vector4f translation;
142 Eigen::Quaternionf rotation;
143 pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2);
144 if (!loadCloud (pcd_files[i], *cloud, translation, rotation))
145 continue;
146
147 // Perform the feature estimation
148 pcl::PCLPointCloud2 output;
149 compute (cloud, output, k, radius);
150
151 // Prepare output file name
152 std::string filename = boost::filesystem::path(pcd_files[i]).filename().string();
153
154 // Save into the second file
155 const std::string filepath = output_dir + '/' + filename;
156 saveCloud (filepath, output, translation, rotation);
157 }
158 return (0);
159 }
160
161 /* ---[ */
162 int
main(int argc,char ** argv)163 main (int argc, char** argv)
164 {
165 print_info ("Estimate surface normals using NormalEstimation. For more information, use: %s -h\n", argv[0]);
166
167 if (argc < 3)
168 {
169 printHelp (argc, argv);
170 return (-1);
171 }
172
173 bool batch_mode = false;
174
175 // Command line parsing
176 int k = default_k;
177 double radius = default_radius;
178 parse_argument (argc, argv, "-k", k);
179 parse_argument (argc, argv, "-radius", radius);
180 std::string input_dir, output_dir;
181 if (parse_argument (argc, argv, "-input_dir", input_dir) != -1)
182 {
183 PCL_INFO ("Input directory given as %s. Batch process mode on.\n", input_dir.c_str ());
184 if (parse_argument (argc, argv, "-output_dir", output_dir) == -1)
185 {
186 PCL_ERROR ("Need an output directory! Please use -output_dir to continue.\n");
187 return (-1);
188 }
189
190 // Both input dir and output dir given, switch into batch processing mode
191 batch_mode = true;
192 }
193
194 if (!batch_mode)
195 {
196 // Parse the command line arguments for .pcd files
197 std::vector<int> p_file_indices;
198 p_file_indices = parse_file_extension_argument (argc, argv, ".pcd");
199 if (p_file_indices.size () != 2)
200 {
201 print_error ("Need one input PCD file and one output PCD file to continue.\n");
202 return (-1);
203 }
204
205 print_info ("Estimating normals with a k/radius/smoothing size of: ");
206 print_value ("%d / %f / %f\n", k, radius, radius);
207
208 // Load the first file
209 Eigen::Vector4f translation;
210 Eigen::Quaternionf rotation;
211 pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2);
212 if (!loadCloud (argv[p_file_indices[0]], *cloud, translation, rotation))
213 return (-1);
214
215 // Perform the feature estimation
216 pcl::PCLPointCloud2 output;
217 compute (cloud, output, k, radius);
218
219 // Save into the second file
220 saveCloud (argv[p_file_indices[1]], output, translation, rotation);
221 }
222 else
223 {
224 if (!input_dir.empty() && boost::filesystem::exists (input_dir))
225 {
226 std::vector<std::string> pcd_files;
227 boost::filesystem::directory_iterator end_itr;
228 for (boost::filesystem::directory_iterator itr (input_dir); itr != end_itr; ++itr)
229 {
230 // Only add PCD files
231 if (!is_directory (itr->status ()) && boost::algorithm::to_upper_copy (boost::filesystem::extension (itr->path ())) == ".PCD" )
232 {
233 pcd_files.push_back (itr->path ().string ());
234 PCL_INFO ("[Batch processing mode] Added %s for processing.\n", itr->path ().string ().c_str ());
235 }
236 }
237 batchProcess (pcd_files, output_dir, k, radius);
238 }
239 else
240 {
241 PCL_ERROR ("Batch processing mode enabled, but invalid input directory (%s) given!\n", input_dir.c_str ());
242 return (-1);
243 }
244 }
245 }
246
247