Point Cloud Library (PCL) 1.14.0
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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
54#include <algorithm>
55#include <iterator>
56
57namespace pcl
58{
59 namespace detail
60 {
61 // For converting template point cloud to message.
62 template<typename PointT>
64 {
65 FieldAdder (std::vector<pcl::PCLPointField>& fields) : fields_ (fields) {};
66
67 template<typename U> void operator() ()
68 {
70 f.name = pcl::traits::name<PointT, U>::value;
71 f.offset = pcl::traits::offset<PointT, U>::value;
72 f.datatype = pcl::traits::datatype<PointT, U>::value;
73 f.count = pcl::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>
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 = pcl::traits::offset<PointT, Tag>::value;
100 mapping.size = sizeof (typename pcl::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", pcl::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 {
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 (note that the binary point data in msg.data will not be used!)
155 * \param[out] cloud the resultant pcl::PointCloud<T>
156 * \param[in] field_map a MsgFieldMap object
157 * \param[in] msg_data pointer to binary blob data, used instead of msg.data
158 *
159 * \note Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) instead, except if you have a binary blob of
160 * point data that you do not want to copy into a pcl::PCLPointCloud2 in order to use fromPCLPointCloud2.
161 */
162 template <typename PointT> void
164 const MsgFieldMap& field_map, const std::uint8_t* msg_data)
165 {
166 // Copy info fields
167 cloud.header = msg.header;
168 cloud.width = msg.width;
169 cloud.height = msg.height;
170 cloud.is_dense = msg.is_dense == 1;
171
172 // Resize cloud
173 cloud.resize (msg.width * msg.height);
174
175 // check if there is data to copy
176 if (msg.width * msg.height == 0)
177 {
178 PCL_WARN("[pcl::fromPCLPointCloud2] No data to copy.\n");
179 return;
180 }
181
182 // Copy point data
183 std::uint8_t* cloud_data = reinterpret_cast<std::uint8_t*>(cloud.data());
184
185 // Check if we can copy adjacent points in a single memcpy. We can do so if there
186 // is exactly one field to copy and it is the same size as the source and destination
187 // point types.
188 if (field_map.size() == 1 &&
189 field_map[0].serialized_offset == 0 &&
190 field_map[0].struct_offset == 0 &&
191 field_map[0].size == msg.point_step &&
192 field_map[0].size == sizeof(PointT))
193 {
194 const auto cloud_row_step = (sizeof (PointT) * cloud.width);
195 // Should usually be able to copy all rows at once
196 if (msg.row_step == cloud_row_step)
197 {
198 memcpy (cloud_data, msg_data, msg.width * msg.height * sizeof(PointT));
199 }
200 else
201 {
202 for (uindex_t i = 0; i < msg.height; ++i, cloud_data += cloud_row_step, msg_data += msg.row_step)
203 memcpy (cloud_data, msg_data, cloud_row_step);
204 }
205
206 }
207 else
208 {
209 // If not, memcpy each group of contiguous fields separately
210 for (std::size_t row = 0; row < msg.height; ++row)
211 {
212 const std::uint8_t* row_data = msg_data + row * msg.row_step;
213 for (std::size_t col = 0; col < msg.width; ++col)
214 {
215 const std::uint8_t* msg_data = row_data + col * msg.point_step;
216 for (const detail::FieldMapping& mapping : field_map)
217 {
218 std::copy(msg_data + mapping.serialized_offset, msg_data + mapping.serialized_offset + mapping.size,
219 cloud_data + mapping.struct_offset);
220 }
221 cloud_data += sizeof (PointT);
222 }
223 }
224 }
225 }
226
227 /** \brief Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
228 * \param[in] msg the PCLPointCloud2 binary blob
229 * \param[out] cloud the resultant pcl::PointCloud<T>
230 * \param[in] field_map a MsgFieldMap object
231 *
232 * \note Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) directly or create you
233 * own MsgFieldMap using:
234 *
235 * \code
236 * MsgFieldMap field_map;
237 * createMapping<PointT> (msg.fields, field_map);
238 * \endcode
239 */
240 template <typename PointT> void
242 const MsgFieldMap& field_map)
243 {
244 fromPCLPointCloud2 (msg, cloud, field_map, msg.data.data());
245 }
246
247 /** \brief Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object.
248 * \param[in] msg the PCLPointCloud2 binary blob
249 * \param[out] cloud the resultant pcl::PointCloud<T>
250 */
251 template<typename PointT> void
253 {
254 MsgFieldMap field_map;
255 createMapping<PointT> (msg.fields, field_map);
256 fromPCLPointCloud2 (msg, cloud, field_map);
257 }
258
259 /** \brief Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
260 * \param[in] cloud the input pcl::PointCloud<T>
261 * \param[out] msg the resultant PCLPointCloud2 binary blob
262 */
263 template<typename PointT> void
265 {
266 // Ease the user's burden on specifying width/height for unorganized datasets
267 if (cloud.width == 0 && cloud.height == 0)
268 {
269 msg.width = cloud.size ();
270 msg.height = 1;
271 }
272 else
273 {
274 assert (cloud.size () == cloud.width * cloud.height);
275 msg.height = cloud.height;
276 msg.width = cloud.width;
277 }
278
279 // Fill point cloud binary data (padding and all)
280 std::size_t data_size = sizeof (PointT) * cloud.size ();
281 msg.data.resize (data_size);
282 if (data_size)
283 {
284 memcpy(msg.data.data(), cloud.data(), data_size);
285 }
286
287 // Fill fields metadata
288 msg.fields.clear ();
289 for_each_type<typename traits::fieldList<PointT>::type> (detail::FieldAdder<PointT>(msg.fields));
290
291 msg.header = cloud.header;
292 msg.point_step = sizeof (PointT);
293 msg.row_step = (sizeof (PointT) * msg.width);
294 msg.is_dense = cloud.is_dense;
295 /// @todo msg.is_bigendian = ?;
296 }
297
298 /** \brief Copy the RGB fields of a PointCloud into pcl::PCLImage format
299 * \param[in] cloud the point cloud message
300 * \param[out] msg the resultant pcl::PCLImage
301 * CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGBA>
302 * \note will throw std::runtime_error if there is a problem
303 */
304 template<typename CloudT> void
305 toPCLPointCloud2 (const CloudT& cloud, pcl::PCLImage& msg)
306 {
307 // Ease the user's burden on specifying width/height for unorganized datasets
308 if (cloud.width == 0 && cloud.height == 0)
309 throw std::runtime_error("Needs to be a dense like cloud!!");
310 else
311 {
312 if (cloud.size () != cloud.width * cloud.height)
313 throw std::runtime_error("The width and height do not match the cloud size!");
314 msg.height = cloud.height;
315 msg.width = cloud.width;
316 }
317
318 // ensor_msgs::image_encodings::BGR8;
319 msg.header = cloud.header;
320 msg.encoding = "bgr8";
321 msg.step = msg.width * sizeof (std::uint8_t) * 3;
322 msg.data.resize (msg.step * msg.height);
323 for (std::size_t y = 0; y < cloud.height; y++)
324 {
325 for (std::size_t x = 0; x < cloud.width; x++)
326 {
327 std::uint8_t * pixel = &(msg.data[y * msg.step + x * 3]);
328 memcpy (pixel, &cloud (x, y).rgb, 3 * sizeof(std::uint8_t));
329 }
330 }
331 }
332
333 /** \brief Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format
334 * \param cloud the point cloud message
335 * \param msg the resultant pcl::PCLImage
336 * will throw std::runtime_error if there is a problem
337 */
338 inline void
340 {
341 const auto predicate = [](const auto& field) { return field.name == "rgb"; };
342 const auto result = std::find_if(cloud.fields.cbegin (), cloud.fields.cend (), predicate);
343 if (result == cloud.fields.end ())
344 throw std::runtime_error ("No rgb field!!");
345
346 const auto rgb_index = std::distance(cloud.fields.begin (), result);
347 if (cloud.width == 0 && cloud.height == 0)
348 throw std::runtime_error ("Needs to be a dense like cloud!!");
349 else
350 {
351 msg.height = cloud.height;
352 msg.width = cloud.width;
353 }
354 auto rgb_offset = cloud.fields[rgb_index].offset;
355 const auto point_step = cloud.point_step;
356
357 // pcl::image_encodings::BGR8;
358 msg.header = cloud.header;
359 msg.encoding = "bgr8";
360 msg.step = (msg.width * sizeof (std::uint8_t) * 3);
361 msg.data.resize (msg.step * msg.height);
362
363 for (std::size_t y = 0; y < cloud.height; y++)
364 {
365 for (std::size_t x = 0; x < cloud.width; x++, rgb_offset += point_step)
366 {
367 std::uint8_t * pixel = &(msg.data[y * msg.step + x * 3]);
368 std::copy(&cloud.data[rgb_offset], &cloud.data[rgb_offset] + 3, pixel);
369 }
370 }
371 }
372}
PointCloud represents the base class in PCL for storing collections of 3D points.
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
void resize(std::size_t count)
Resizes the container to contain count elements.
PointT * data() noexcept
std::uint32_t width
The point cloud width (if organized as an image-structure).
pcl::PCLHeader header
The point cloud header.
std::uint32_t height
The point cloud height (if organized as an image-structure).
std::size_t size() const
bool fieldOrdering(const FieldMapping &a, const FieldMapping &b)
detail::int_type_t< detail::index_type_size, false > uindex_t
Type used for an unsigned index in PCL.
Definition types.h:120
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map, const std::uint8_t *msg_data)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
void toPCLPointCloud2(const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
void createMapping(const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map)
std::vector< detail::FieldMapping > MsgFieldMap
Definition point_cloud.h:72
uindex_t step
Definition PCLImage.h:21
uindex_t height
Definition PCLImage.h:16
std::string encoding
Definition PCLImage.h:18
std::vector< std::uint8_t > data
Definition PCLImage.h:23
uindex_t width
Definition PCLImage.h:17
::pcl::PCLHeader header
Definition PCLImage.h:14
std::uint8_t is_dense
std::vector<::pcl::PCLPointField > fields
::pcl::PCLHeader header
std::vector< std::uint8_t > data
std::uint8_t datatype
A point structure representing Euclidean xyz coordinates, and the RGB color.
FieldAdder(std::vector< pcl::PCLPointField > &fields)
Definition conversions.h:65
std::vector< pcl::PCLPointField > & fields_
Definition conversions.h:77
FieldMapper(const std::vector< pcl::PCLPointField > &fields, std::vector< FieldMapping > &map)
Definition conversions.h:84
const std::vector< pcl::PCLPointField > & fields_
std::vector< FieldMapping > & map_
std::size_t serialized_offset
Definition point_cloud.h:64