Point Cloud Library (PCL)  1.11.1-dev
conversions.h
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39 
40 #pragma once
41 
42 #ifdef __GNUC__
43 #pragma GCC system_header
44 #endif
45 
46 #include <pcl/PCLPointField.h>
47 #include <pcl/PCLPointCloud2.h>
48 #include <pcl/PCLImage.h>
49 #include <pcl/point_cloud.h>
50 #include <pcl/type_traits.h>
51 #include <pcl/for_each_type.h>
52 #include <pcl/console/print.h>
53 #ifndef Q_MOC_RUN
54 #include <boost/foreach.hpp>
55 #endif
56 
57 namespace pcl
58 {
59  namespace detail
60  {
61  // For converting template point cloud to message.
62  template<typename PointT>
63  struct FieldAdder
64  {
65  FieldAdder (std::vector<pcl::PCLPointField>& fields) : fields_ (fields) {};
66 
67  template<typename U> void operator() ()
68  {
70  f.name = traits::name<PointT, U>::value;
71  f.offset = traits::offset<PointT, U>::value;
72  f.datatype = traits::datatype<PointT, U>::value;
73  f.count = traits::datatype<PointT, U>::size;
74  fields_.push_back (f);
75  }
76 
77  std::vector<pcl::PCLPointField>& fields_;
78  };
79 
80  // For converting message to template point cloud.
81  template<typename PointT>
82  struct FieldMapper
83  {
84  FieldMapper (const std::vector<pcl::PCLPointField>& fields,
85  std::vector<FieldMapping>& map)
86  : fields_ (fields), map_ (map)
87  {
88  }
89 
90  template<typename Tag> void
92  {
93  for (const auto& field : fields_)
94  {
95  if (FieldMatches<PointT, Tag>()(field))
96  {
97  FieldMapping mapping;
98  mapping.serialized_offset = field.offset;
99  mapping.struct_offset = traits::offset<PointT, Tag>::value;
100  mapping.size = sizeof (typename traits::datatype<PointT, Tag>::type);
101  map_.push_back (mapping);
102  return;
103  }
104  }
105  // Disable thrown exception per #595: http://dev.pointclouds.org/issues/595
106  PCL_WARN ("Failed to find match for field '%s'.\n", traits::name<PointT, Tag>::value);
107  //throw pcl::InvalidConversionException (ss.str ());
108  }
109 
110  const std::vector<pcl::PCLPointField>& fields_;
111  std::vector<FieldMapping>& map_;
112  };
113 
114  inline bool
116  {
117  return (a.serialized_offset < b.serialized_offset);
118  }
119 
120  } //namespace detail
121 
122  template<typename PointT> void
123  createMapping (const std::vector<pcl::PCLPointField>& msg_fields, MsgFieldMap& field_map)
124  {
125  // Create initial 1-1 mapping between serialized data segments and struct fields
126  detail::FieldMapper<PointT> mapper (msg_fields, field_map);
127  for_each_type< typename traits::fieldList<PointT>::type > (mapper);
128 
129  // Coalesce adjacent fields into single memcpy's where possible
130  if (field_map.size() > 1)
131  {
132  std::sort(field_map.begin(), field_map.end(), detail::fieldOrdering);
133  MsgFieldMap::iterator i = field_map.begin(), j = i + 1;
134  while (j != field_map.end())
135  {
136  // This check is designed to permit padding between adjacent fields.
137  /// @todo One could construct a pathological case where the struct has a
138  /// field where the serialized data has padding
139  if (j->serialized_offset - i->serialized_offset == j->struct_offset - i->struct_offset)
140  {
141  i->size += (j->struct_offset + j->size) - (i->struct_offset + i->size);
142  j = field_map.erase(j);
143  }
144  else
145  {
146  ++i;
147  ++j;
148  }
149  }
150  }
151  }
152 
153  /** \brief Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
154  * \param[in] msg the PCLPointCloud2 binary blob
155  * \param[out] cloud the resultant pcl::PointCloud<T>
156  * \param[in] field_map a MsgFieldMap object
157  *
158  * \note Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) directly or create you
159  * own MsgFieldMap using:
160  *
161  * \code
162  * MsgFieldMap field_map;
163  * createMapping<PointT> (msg.fields, field_map);
164  * \endcode
165  */
166  template <typename PointT> void
168  const MsgFieldMap& field_map)
169  {
170  // Copy info fields
171  cloud.header = msg.header;
172  cloud.width = msg.width;
173  cloud.height = msg.height;
174  cloud.is_dense = msg.is_dense == 1;
175 
176  // Copy point data
177  std::uint32_t num_points = msg.width * msg.height;
178  cloud.resize (num_points);
179  std::uint8_t* cloud_data = reinterpret_cast<std::uint8_t*>(&cloud[0]);
180 
181  // Check if we can copy adjacent points in a single memcpy. We can do so if there
182  // is exactly one field to copy and it is the same size as the source and destination
183  // point types.
184  if (field_map.size() == 1 &&
185  field_map[0].serialized_offset == 0 &&
186  field_map[0].struct_offset == 0 &&
187  field_map[0].size == msg.point_step &&
188  field_map[0].size == sizeof(PointT))
189  {
190  std::uint32_t cloud_row_step = static_cast<std::uint32_t> (sizeof (PointT) * cloud.width);
191  const std::uint8_t* msg_data = &msg.data[0];
192  // Should usually be able to copy all rows at once
193  if (msg.row_step == cloud_row_step)
194  {
195  memcpy (cloud_data, msg_data, msg.data.size ());
196  }
197  else
198  {
199  for (std::uint32_t i = 0; i < msg.height; ++i, cloud_data += cloud_row_step, msg_data += msg.row_step)
200  memcpy (cloud_data, msg_data, cloud_row_step);
201  }
202 
203  }
204  else
205  {
206  // If not, memcpy each group of contiguous fields separately
207  for (index_t row = 0; row < msg.height; ++row)
208  {
209  const std::uint8_t* row_data = &msg.data[row * msg.row_step];
210  for (index_t col = 0; col < msg.width; ++col)
211  {
212  const std::uint8_t* msg_data = row_data + col * msg.point_step;
213  for (const detail::FieldMapping& mapping : field_map)
214  {
215  memcpy (cloud_data + mapping.struct_offset, msg_data + mapping.serialized_offset, mapping.size);
216  }
217  cloud_data += sizeof (PointT);
218  }
219  }
220  }
221  }
222 
223  /** \brief Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object.
224  * \param[in] msg the PCLPointCloud2 binary blob
225  * \param[out] cloud the resultant pcl::PointCloud<T>
226  */
227  template<typename PointT> void
229  {
230  MsgFieldMap field_map;
231  createMapping<PointT> (msg.fields, field_map);
232  fromPCLPointCloud2 (msg, cloud, field_map);
233  }
234 
235  /** \brief Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
236  * \param[in] cloud the input pcl::PointCloud<T>
237  * \param[out] msg the resultant PCLPointCloud2 binary blob
238  */
239  template<typename PointT> void
241  {
242  // Ease the user's burden on specifying width/height for unorganized datasets
243  if (cloud.width == 0 && cloud.height == 0)
244  {
245  msg.width = cloud.size ();
246  msg.height = 1;
247  }
248  else
249  {
250  assert (cloud.size () == cloud.width * cloud.height);
251  msg.height = cloud.height;
252  msg.width = cloud.width;
253  }
254 
255  // Fill point cloud binary data (padding and all)
256  std::size_t data_size = sizeof (PointT) * cloud.size ();
257  msg.data.resize (data_size);
258  if (data_size)
259  {
260  memcpy(&msg.data[0], &cloud[0], data_size);
261  }
262 
263  // Fill fields metadata
264  msg.fields.clear ();
265  for_each_type<typename traits::fieldList<PointT>::type> (detail::FieldAdder<PointT>(msg.fields));
266 
267  msg.header = cloud.header;
268  msg.point_step = sizeof (PointT);
269  msg.row_step = static_cast<std::uint32_t> (sizeof (PointT) * msg.width);
270  msg.is_dense = cloud.is_dense;
271  /// @todo msg.is_bigendian = ?;
272  }
273 
274  /** \brief Copy the RGB fields of a PointCloud into pcl::PCLImage format
275  * \param[in] cloud the point cloud message
276  * \param[out] msg the resultant pcl::PCLImage
277  * CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGBA>
278  * \note will throw std::runtime_error if there is a problem
279  */
280  template<typename CloudT> void
281  toPCLPointCloud2 (const CloudT& cloud, pcl::PCLImage& msg)
282  {
283  // Ease the user's burden on specifying width/height for unorganized datasets
284  if (cloud.width == 0 && cloud.height == 0)
285  throw std::runtime_error("Needs to be a dense like cloud!!");
286  else
287  {
288  if (cloud.size () != cloud.width * cloud.height)
289  throw std::runtime_error("The width and height do not match the cloud size!");
290  msg.height = cloud.height;
291  msg.width = cloud.width;
292  }
293 
294  // ensor_msgs::image_encodings::BGR8;
295  msg.encoding = "bgr8";
296  msg.step = msg.width * sizeof (std::uint8_t) * 3;
297  msg.data.resize (msg.step * msg.height);
298  for (std::size_t y = 0; y < cloud.height; y++)
299  {
300  for (std::size_t x = 0; x < cloud.width; x++)
301  {
302  std::uint8_t * pixel = &(msg.data[y * msg.step + x * 3]);
303  memcpy (pixel, &cloud (x, y).rgb, 3 * sizeof(std::uint8_t));
304  }
305  }
306  }
307 
308  /** \brief Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format
309  * \param cloud the point cloud message
310  * \param msg the resultant pcl::PCLImage
311  * will throw std::runtime_error if there is a problem
312  */
313  inline void
315  {
316  const auto predicate = [](const auto& field) { return field.name == "rgb"; };
317  const auto result = std::find_if(cloud.fields.cbegin (), cloud.fields.cend (), predicate);
318  if (result == cloud.fields.end ())
319  throw std::runtime_error ("No rgb field!!");
320 
321  const auto rgb_index = std::distance(cloud.fields.begin (), result);
322  if (cloud.width == 0 && cloud.height == 0)
323  throw std::runtime_error ("Needs to be a dense like cloud!!");
324  else
325  {
326  msg.height = cloud.height;
327  msg.width = cloud.width;
328  }
329  int rgb_offset = cloud.fields[rgb_index].offset;
330  int point_step = cloud.point_step;
331 
332  // pcl::image_encodings::BGR8;
333  msg.encoding = "bgr8";
334  msg.step = static_cast<std::uint32_t>(msg.width * sizeof (std::uint8_t) * 3);
335  msg.data.resize (msg.step * msg.height);
336 
337  for (std::size_t y = 0; y < cloud.height; y++)
338  {
339  for (std::size_t x = 0; x < cloud.width; x++, rgb_offset += point_step)
340  {
341  std::uint8_t * pixel = &(msg.data[y * msg.step + x * 3]);
342  memcpy (pixel, &(cloud.data[rgb_offset]), 3 * sizeof (std::uint8_t));
343  }
344  }
345  }
346 }
pcl::PCLImage::height
index_t height
Definition: PCLImage.h:16
pcl
Definition: convolution.h:46
pcl::PCLImage::data
std::vector< std::uint8_t > data
Definition: PCLImage.h:23
pcl::PCLImage::encoding
std::string encoding
Definition: PCLImage.h:18
pcl::uint32_t
std::uint32_t uint32_t
Definition: types.h:58
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:415
pcl::geometry::distance
float distance(const PointT &p1, const PointT &p2)
Definition: geometry.h:60
pcl::PCLPointCloud2::point_step
index_t point_step
Definition: PCLPointCloud2.h:27
pcl::PCLImage::step
index_t step
Definition: PCLImage.h:21
pcl::PCLPointCloud2::height
index_t height
Definition: PCLPointCloud2.h:20
pcl::PCLPointField::count
uindex_t count
Definition: PCLPointField.h:18
pcl::detail::fieldOrdering
bool fieldOrdering(const FieldMapping &a, const FieldMapping &b)
Definition: conversions.h:115
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: distances.h:55
pcl::PCLPointCloud2::row_step
index_t row_step
Definition: PCLPointCloud2.h:28
pcl::index_t
detail::int_type_t< detail::index_type_size, detail::index_type_signed > index_t
Type used for an index in PCL.
Definition: types.h:120
pcl::PointXYZRGB
A point structure representing Euclidean xyz coordinates, and the RGB color.
Definition: point_types.hpp:628
pcl::PCLPointCloud2::is_dense
std::uint8_t is_dense
Definition: PCLPointCloud2.h:32
pcl::PCLPointCloud2::header
::pcl::PCLHeader header
Definition: PCLPointCloud2.h:18
pcl::detail::FieldMapping
Definition: point_cloud.h:61
pcl::PCLPointField::offset
uindex_t offset
Definition: PCLPointField.h:16
pcl::PCLPointField::datatype
std::uint8_t datatype
Definition: PCLPointField.h:17
pcl::PCLPointCloud2::width
index_t width
Definition: PCLPointCloud2.h:21
pcl::detail::FieldMapper
Definition: conversions.h:82
pcl::detail::FieldMapping::size
std::size_t size
Definition: point_cloud.h:65
pcl::detail::FieldMapper::FieldMapper
FieldMapper(const std::vector< pcl::PCLPointField > &fields, std::vector< FieldMapping > &map)
Definition: conversions.h:84
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:413
pcl::PCLPointCloud2::fields
std::vector<::pcl::PCLPointField > fields
Definition: PCLPointCloud2.h:23
pcl::detail::FieldMapper::operator()
void operator()()
Definition: conversions.h:91
pcl::detail::FieldAdder::fields_
std::vector< pcl::PCLPointField > & fields_
Definition: conversions.h:77
pcl::PointCloud::is_dense
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
Definition: point_cloud.h:418
pcl::PointCloud::resize
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition: point_cloud.h:477
pcl::PointCloud::header
pcl::PCLHeader header
The point cloud header.
Definition: point_cloud.h:407
pcl::PCLPointCloud2::data
std::vector< std::uint8_t > data
Definition: PCLPointCloud2.h:30
pcl::PCLPointCloud2
Definition: PCLPointCloud2.h:16
pcl::PointCloud::size
std::size_t size() const
Definition: point_cloud.h:458
pcl::detail::FieldAdder::FieldAdder
FieldAdder(std::vector< pcl::PCLPointField > &fields)
Definition: conversions.h:65
pcl::detail::FieldAdder::operator()
void operator()()
Definition: conversions.h:67
pcl::PCLImage
Definition: PCLImage.h:12
pcl::uint8_t
std::uint8_t uint8_t
Definition: types.h:54
pcl::PCLPointField::name
std::string name
Definition: PCLPointField.h:14
pcl::detail::FieldMapper::fields_
const std::vector< pcl::PCLPointField > & fields_
Definition: conversions.h:110
pcl::detail::FieldMapping::serialized_offset
std::size_t serialized_offset
Definition: point_cloud.h:63
pcl::PCLPointField
Definition: PCLPointField.h:12
pcl::toPCLPointCloud2
void toPCLPointCloud2(const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
Definition: conversions.h:240
pcl::FieldMatches
Definition: PCLPointField.h:53
pcl::MsgFieldMap
std::vector< detail::FieldMapping > MsgFieldMap
Definition: point_cloud.h:71
pcl::createMapping
void createMapping(const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map)
Definition: conversions.h:123
pcl::detail::FieldAdder
Definition: conversions.h:63
pcl::detail::FieldMapping::struct_offset
std::size_t struct_offset
Definition: point_cloud.h:64
pcl::detail::FieldMapper::map_
std::vector< FieldMapping > & map_
Definition: conversions.h:111
pcl::fromPCLPointCloud2
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
Definition: conversions.h:167
pcl::PCLImage::width
index_t width
Definition: PCLImage.h:17