conversions.h
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#ifndef PCL_CONVERSIONS_H_
#define PCL_CONVERSIONS_H_
#ifdef __GNUC__
#pragma GCC system_header
#endif
#include <pcl/PCLPointField.h>
#include <pcl/PCLPointCloud2.h>
#include <pcl/PCLImage.h>
#include <pcl/point_cloud.h>
#include <pcl/point_traits.h>
#include <pcl/for_each_type.h>
#include <pcl/exceptions.h>
#include <pcl/console/print.h>
#ifndef Q_MOC_RUN
#include <boost/foreach.hpp>
#endif
namespace pcl
{
namespace detail
{
// For converting template point cloud to message.
template<typename PointT>
struct FieldAdder
{
FieldAdder (std::vector<pcl::PCLPointField>& fields) : fields_ (fields) {};
template<typename U> void operator() ()
{
pcl::PCLPointField f;
f.name = traits::name<PointT, U>::value;
f.offset = traits::offset<PointT, U>::value;
f.datatype = traits::datatype<PointT, U>::value;
f.count = traits::datatype<PointT, U>::size;
fields_.push_back (f);
}
std::vector<pcl::PCLPointField>& fields_;
};
// For converting message to template point cloud.
template<typename PointT>
struct FieldMapper
{
FieldMapper (const std::vector<pcl::PCLPointField>& fields,
std::vector<FieldMapping>& map)
: fields_ (fields), map_ (map)
{
}
template<typename Tag> void
operator () ()
{
BOOST_FOREACH (const pcl::PCLPointField& field, fields_)
{
if (FieldMatches<PointT, Tag>()(field))
{
FieldMapping mapping;
mapping.serialized_offset = field.offset;
mapping.struct_offset = traits::offset<PointT, Tag>::value;
mapping.size = sizeof (typename traits::datatype<PointT, Tag>::type);
map_.push_back (mapping);
return;
}
}
// Disable thrown exception per #595: http://dev.pointclouds.org/issues/595
PCL_WARN ("Failed to find match for field '%s'.\n", traits::name<PointT, Tag>::value);
//throw pcl::InvalidConversionException (ss.str ());
}
const std::vector<pcl::PCLPointField>& fields_;
std::vector<FieldMapping>& map_;
};
inline bool
fieldOrdering (const FieldMapping& a, const FieldMapping& b)
{
return (a.serialized_offset < b.serialized_offset);
}
} //namespace detail
template<typename PointT> void
createMapping (const std::vector<pcl::PCLPointField>& msg_fields, MsgFieldMap& field_map)
{
// Create initial 1-1 mapping between serialized data segments and struct fields
detail::FieldMapper<PointT> mapper (msg_fields, field_map);
for_each_type< typename traits::fieldList<PointT>::type > (mapper);
// Coalesce adjacent fields into single memcpy's where possible
if (field_map.size() > 1)
{
std::sort(field_map.begin(), field_map.end(), detail::fieldOrdering);
MsgFieldMap::iterator i = field_map.begin(), j = i + 1;
while (j != field_map.end())
{
// This check is designed to permit padding between adjacent fields.
/// @todo One could construct a pathological case where the struct has a
/// field where the serialized data has padding
if (j->serialized_offset - i->serialized_offset == j->struct_offset - i->struct_offset)
{
i->size += (j->struct_offset + j->size) - (i->struct_offset + i->size);
j = field_map.erase(j);
}
else
{
++i;
++j;
}
}
}
}
/** \brief Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
* \param[in] msg the PCLPointCloud2 binary blob
* \param[out] cloud the resultant pcl::PointCloud<T>
* \param[in] field_map a MsgFieldMap object
*
* \note Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) directly or create you
* own MsgFieldMap using:
*
* \code
* MsgFieldMap field_map;
* createMapping<PointT> (msg.fields, field_map);
* \endcode
*/
template <typename PointT> void
fromPCLPointCloud2 (const pcl::PCLPointCloud2& msg, pcl::PointCloud<PointT>& cloud,
const MsgFieldMap& field_map)
{
// Copy info fields
cloud.header = msg.header;
cloud.width = msg.width;
cloud.height = msg.height;
cloud.is_dense = msg.is_dense == 1;
// Copy point data
uint32_t num_points = msg.width * msg.height;
cloud.points.resize (num_points);
uint8_t* cloud_data = reinterpret_cast<uint8_t*>(&cloud.points[0]);
// Check if we can copy adjacent points in a single memcpy. We can do so if there
// is exactly one field to copy and it is the same size as the source and destination
// point types.
if (field_map.size() == 1 &&
field_map[0].serialized_offset == 0 &&
field_map[0].struct_offset == 0 &&
field_map[0].size == msg.point_step &&
field_map[0].size == sizeof(PointT))
{
uint32_t cloud_row_step = static_cast<uint32_t> (sizeof (PointT) * cloud.width);
const uint8_t* msg_data = &msg.data[0];
// Should usually be able to copy all rows at once
if (msg.row_step == cloud_row_step)
{
memcpy (cloud_data, msg_data, msg.data.size ());
}
else
{
for (uint32_t i = 0; i < msg.height; ++i, cloud_data += cloud_row_step, msg_data += msg.row_step)
memcpy (cloud_data, msg_data, cloud_row_step);
}
}
else
{
// If not, memcpy each group of contiguous fields separately
for (uint32_t row = 0; row < msg.height; ++row)
{
const uint8_t* row_data = &msg.data[row * msg.row_step];
for (uint32_t col = 0; col < msg.width; ++col)
{
const uint8_t* msg_data = row_data + col * msg.point_step;
BOOST_FOREACH (const detail::FieldMapping& mapping, field_map)
{
memcpy (cloud_data + mapping.struct_offset, msg_data + mapping.serialized_offset, mapping.size);
}
cloud_data += sizeof (PointT);
}
}
}
}
/** \brief Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object.
* \param[in] msg the PCLPointCloud2 binary blob
* \param[out] cloud the resultant pcl::PointCloud<T>
*/
template<typename PointT> void
fromPCLPointCloud2 (const pcl::PCLPointCloud2& msg, pcl::PointCloud<PointT>& cloud)
{
MsgFieldMap field_map;
createMapping<PointT> (msg.fields, field_map);
fromPCLPointCloud2 (msg, cloud, field_map);
}
/** \brief Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob.
* \param[in] cloud the input pcl::PointCloud<T>
* \param[out] msg the resultant PCLPointCloud2 binary blob
*/
template<typename PointT> void
toPCLPointCloud2 (const pcl::PointCloud<PointT>& cloud, pcl::PCLPointCloud2& msg)
{
// Ease the user's burden on specifying width/height for unorganized datasets
if (cloud.width == 0 && cloud.height == 0)
{
msg.width = static_cast<uint32_t>(cloud.points.size ());
msg.height = 1;
}
else
{
assert (cloud.points.size () == cloud.width * cloud.height);
msg.height = cloud.height;
msg.width = cloud.width;
}
// Fill point cloud binary data (padding and all)
size_t data_size = sizeof (PointT) * cloud.points.size ();
msg.data.resize (data_size);
if (data_size)
{
memcpy(&msg.data[0], &cloud.points[0], data_size);
}
// Fill fields metadata
msg.fields.clear ();
for_each_type<typename traits::fieldList<PointT>::type> (detail::FieldAdder<PointT>(msg.fields));
msg.header = cloud.header;
msg.point_step = sizeof (PointT);
msg.row_step = static_cast<uint32_t> (sizeof (PointT) * msg.width);
msg.is_dense = cloud.is_dense;
/// @todo msg.is_bigendian = ?;
}
/** \brief Copy the RGB fields of a PointCloud into pcl::PCLImage format
* \param[in] cloud the point cloud message
* \param[out] msg the resultant pcl::PCLImage
* CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGBA>
* \note will throw std::runtime_error if there is a problem
*/
template<typename CloudT> void
toPCLPointCloud2 (const CloudT& cloud, pcl::PCLImage& msg)
{
// Ease the user's burden on specifying width/height for unorganized datasets
if (cloud.width == 0 && cloud.height == 0)
throw std::runtime_error("Needs to be a dense like cloud!!");
else
{
if (cloud.points.size () != cloud.width * cloud.height)
throw std::runtime_error("The width and height do not match the cloud size!");
msg.height = cloud.height;
msg.width = cloud.width;
}
// ensor_msgs::image_encodings::BGR8;
msg.encoding = "bgr8";
msg.step = msg.width * sizeof (uint8_t) * 3;
msg.data.resize (msg.step * msg.height);
for (size_t y = 0; y < cloud.height; y++)
{
for (size_t x = 0; x < cloud.width; x++)
{
uint8_t * pixel = &(msg.data[y * msg.step + x * 3]);
memcpy (pixel, &cloud (x, y).rgb, 3 * sizeof(uint8_t));
}
}
}
/** \brief Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format
* \param cloud the point cloud message
* \param msg the resultant pcl::PCLImage
* will throw std::runtime_error if there is a problem
*/
inline void
toPCLPointCloud2 (const pcl::PCLPointCloud2& cloud, pcl::PCLImage& msg)
{
int rgb_index = -1;
// Get the index we need
for (size_t d = 0; d < cloud.fields.size (); ++d)
if (cloud.fields[d].name == "rgb")
{
rgb_index = static_cast<int>(d);
break;
}
if(rgb_index == -1)
throw std::runtime_error ("No rgb field!!");
if (cloud.width == 0 && cloud.height == 0)
throw std::runtime_error ("Needs to be a dense like cloud!!");
else
{
msg.height = cloud.height;
msg.width = cloud.width;
}
int rgb_offset = cloud.fields[rgb_index].offset;
int point_step = cloud.point_step;
// pcl::image_encodings::BGR8;
msg.encoding = "bgr8";
msg.step = static_cast<uint32_t>(msg.width * sizeof (uint8_t) * 3);
msg.data.resize (msg.step * msg.height);
for (size_t y = 0; y < cloud.height; y++)
{
for (size_t x = 0; x < cloud.width; x++, rgb_offset += point_step)
{
uint8_t * pixel = &(msg.data[y * msg.step + x * 3]);
memcpy (pixel, &(cloud.data[rgb_offset]), 3 * sizeof (uint8_t));
}
}
}
}
#endif //#ifndef PCL_CONVERSIONS_H_
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:169
pcl::PCLImage::height
pcl::uint32_t height
Definition: PCLImage.h:24
pcl::PointCloud::points
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
Definition: point_cloud.h:410
pcl::detail::FieldAdder::fields_
std::vector< pcl::PCLPointField > & fields_
Definition: conversions.h:79
pcl::PCLPointCloud2::point_step
pcl::uint32_t point_step
Definition: PCLPointCloud2.h:43
pcl
Definition: convolution.h:45
pcl::PCLPointField::offset
pcl::uint32_t offset
Definition: PCLPointField.h:23
pcl::detail::fieldOrdering
bool fieldOrdering(const FieldMapping &a, const FieldMapping &b)
Definition: conversions.h:117
pcl::PCLPointCloud2::header
::pcl::PCLHeader header
Definition: PCLPointCloud2.h:35
pcl::PCLPointCloud2::is_dense
pcl::uint8_t is_dense
Definition: PCLPointCloud2.h:48
pcl::PointCloud::height
uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:415
pcl::PCLImage::width
pcl::uint32_t width
Definition: PCLImage.h:25
pcl::PointCloud::width
uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:413
pcl::FieldMatches
Definition: point_traits.h:201
pcl::PCLPointField::count
pcl::uint32_t count
Definition: PCLPointField.h:25
pcl::detail::FieldMapping::struct_offset
size_t struct_offset
Definition: point_cloud.h:59
pcl::PCLImage::step
pcl::uint32_t step
Definition: PCLImage.h:29
pcl::PCLPointCloud2::row_step
pcl::uint32_t row_step
Definition: PCLPointCloud2.h:44
pcl::detail::FieldMapping::serialized_offset
size_t serialized_offset
Definition: point_cloud.h:58
pcl::PCLPointCloud2::width
pcl::uint32_t width
Definition: PCLPointCloud2.h:38
pcl::detail::FieldAdder::operator()
void operator()()
Definition: conversions.h:69
pcl::detail::FieldMapper
Definition: conversions.h:84
pcl::traits::name
Definition: point_traits.h:138
pcl::detail::FieldMapping::size
size_t size
Definition: point_cloud.h:60
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points. ...
Definition: projection_matrix.h:53
pcl::PCLPointCloud2::fields
std::vector< ::pcl::PCLPointField > fields
Definition: PCLPointCloud2.h:40
pcl::PointCloud::header
pcl::PCLHeader header
The point cloud header.
Definition: point_cloud.h:407
pcl::PCLPointCloud2::height
pcl::uint32_t height
Definition: PCLPointCloud2.h:37
pcl::detail::FieldAdder
Definition: conversions.h:65
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:242
pcl::PCLImage::data
std::vector< pcl::uint8_t > data
Definition: PCLImage.h:31
pcl::traits::datatype
Definition: point_traits.h:162
pcl::traits::offset
Definition: point_traits.h:150
pcl::PCLPointField
Definition: PCLPointField.h:16
pcl::PointCloud::is_dense
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values).
Definition: point_cloud.h:418
pcl::PCLImage::encoding
std::string encoding
Definition: PCLImage.h:26
pcl::PCLPointField::datatype
pcl::uint8_t datatype
Definition: PCLPointField.h:24
pcl::PCLPointCloud2
Definition: PCLPointCloud2.h:20
pcl::PCLPointField::name
std::string name
Definition: PCLPointField.h:21
pcl::PointXYZRGB
A point structure representing Euclidean xyz coordinates, and the RGB color.
Definition: point_types.hpp:606
pcl::detail::FieldAdder::FieldAdder
FieldAdder(std::vector< pcl::PCLPointField > &fields)
Definition: conversions.h:67
pcl::detail::FieldMapper::map_
std::vector< FieldMapping > & map_
Definition: conversions.h:113
pcl::MsgFieldMap
std::vector< detail::FieldMapping > MsgFieldMap
Definition: point_cloud.h:65
pcl::PCLImage
Definition: PCLImage.h:16
pcl::PCLPointCloud2::data
std::vector< pcl::uint8_t > data
Definition: PCLPointCloud2.h:46
pcl::createMapping
void createMapping(const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map)
Definition: conversions.h:125
pcl::detail::FieldMapper::fields_
const std::vector< pcl::PCLPointField > & fields_
Definition: conversions.h:112
pcl::detail::FieldMapper::FieldMapper
FieldMapper(const std::vector< pcl::PCLPointField > &fields, std::vector< FieldMapping > &map)
Definition: conversions.h:86
pcl::detail::FieldMapping
Definition: point_cloud.h:56