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#pragma once
#ifndef PCL18_BACKPORTS_VOXEL_GRID_H
#define PCL18_BACKPORTS_VOXEL_GRID_H
#ifndef BACKPORT_PCL_VOXEL_GRID
#include <pcl/filters/voxel_grid.h>
namespace pcl
{
template <typename PointT>
using VoxelGrid18 = VoxelGrid<PointT>;
}
#else
// System has old PCL; backport VoxelGrid from pcl-1.8
#include <algorithm>
#include <cmath>
#include <functional>
#include <limits>
#include <string>
#include <utility>
#include <vector>
#include <pcl/common/centroid.h>
#include <pcl/filters/boost.h>
#include <pcl/filters/boost.h>
#include <pcl/filters/filter.h>
#include <pcl/filters/filter.h>
#include <map>
namespace pcl
namespace pcl
{
{
/** \brief Obtain the maximum and minimum points in 3D from a given point cloud.
/** \brief VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.
* \param[in] cloud the pointer to a pcl::PCLPointCloud2 dataset
*
* \param[in] x_idx the index of the X channel
* The VoxelGrid class creates a *3D voxel grid* (think about a voxel
* \param[in] y_idx the index of the Y channel
* grid as a set of tiny 3D boxes in space) over the input point cloud data.
* \param[in] z_idx the index of the Z channel
* Then, in each *voxel* (i.e., 3D box), all the points present will be
* \param[out] min_pt the minimum data point
* approximated (i.e., *downsampled*) with their centroid. This approach is
* \param[out] max_pt the maximum data point
* a bit slower than approximating them with the center of the voxel, but it
*/
* represents the underlying surface more accurately.
PCL_EXPORTS void
*
getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx,
* \author Radu B. Rusu, Bastian Steder
Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt);
* \ingroup filters
*/
template <typename PointT>
class VoxelGrid18 : public Filter<PointT>
{
protected:
using Filter<PointT>::filter_name_;
using Filter<PointT>::getClassName;
using Filter<PointT>::input_;
using Filter<PointT>::indices_;
/** \brief Obtain the maximum and minimum points in 3D from a given point cloud.
typedef typename Filter<PointT>::PointCloud PointCloud;
* \note Performs internal data filtering as well.
typedef typename PointCloud::Ptr PointCloudPtr;
* \param[in] cloud the pointer to a pcl::PCLPointCloud2 dataset
typedef typename PointCloud::ConstPtr PointCloudConstPtr;
* \param[in] x_idx the index of the X channel
* \param[in] y_idx the index of the Y channel
* \param[in] z_idx the index of the Z channel
* \param[in] distance_field_name the name of the dimension to filter data along to
* \param[in] min_distance the minimum acceptable value in \a distance_field_name data
* \param[in] max_distance the maximum acceptable value in \a distance_field_name data
* \param[out] min_pt the minimum data point
* \param[out] max_pt the maximum data point
* \param[in] limit_negative \b false if data \b inside of the [min_distance; max_distance] interval should be
* considered, \b true otherwise.
*/
PCL_EXPORTS void
getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx,
const std::string &distance_field_name, float min_distance, float max_distance,
Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative = false);
/** \brief Get the relative cell indices of the "upper half" 13 neighbors.
public:
* \note Useful in combination with getNeighborCentroidIndices() from \ref VoxelGrid
typedef boost::shared_ptr<VoxelGrid18<PointT>> Ptr;
* \ingroup filters
typedef boost::shared_ptr<const VoxelGrid18<PointT>> ConstPtr;
*/
inline Eigen::MatrixXi
/** \brief Empty constructor. */
getHalfNeighborCellIndices ()
VoxelGrid18()
: leaf_size_(Eigen::Vector4f::Zero())
, inverse_leaf_size_(Eigen::Array4f::Zero())
, leaf_layout_()
, min_b_(Eigen::Vector4i::Zero())
, max_b_(Eigen::Vector4i::Zero())
, div_b_(Eigen::Vector4i::Zero())
, divb_mul_(Eigen::Vector4i::Zero())
, filter_limit_min_(-std::numeric_limits<float>::max())
, filter_limit_max_(std::numeric_limits<float>::max())
, filter_limit_negative_(false)
, min_points_per_voxel_(0)
{
{
Eigen::MatrixXi relative_coordinates (3, 13);
filter_name_ = "VoxelGrid";
int idx = 0;
}
// 0 - 8
/** \brief Destructor. */
for (int i = -1; i < 2; i++)
virtual ~VoxelGrid18()
{
{
for (int j = -1; j < 2; j++)
}
{
relative_coordinates (0, idx) = i;
relative_coordinates (1, idx) = j;
relative_coordinates (2, idx) = -1;
idx++;
}
}
// 9 - 11
for (int i = -1; i < 2; i++)
{
relative_coordinates (0, idx) = i;
relative_coordinates (1, idx) = -1;
relative_coordinates (2, idx) = 0;
idx++;
}
// 12
relative_coordinates (0, idx) = -1;
relative_coordinates (1, idx) = 0;
relative_coordinates (2, idx) = 0;
return (relative_coordinates);
/** \brief Set the voxel grid leaf size.
* \param[in] leaf_size the voxel grid leaf size
*/
inline void
setLeafSize(const Eigen::Vector4f& leaf_size)
{
leaf_size_ = leaf_size;
// Avoid division errors
if (leaf_size_[3] == 0)
leaf_size_[3] = 1;
// Use multiplications instead of divisions
inverse_leaf_size_ = Eigen::Array4f::Ones() / leaf_size_.array();
}
}
/** \brief Get the relative cell indices of all the 26 neighbors.
/** \brief Set the voxel grid leaf size.
* \note Useful in combination with getNeighborCentroidIndices() from \ref VoxelGrid
* \param[in] lx the leaf size for X
* \ingroup filters
* \param[in] ly the leaf size for Y
*/
* \param[in] lz the leaf size for Z
inline Eigen::MatrixXi
*/
getAllNeighborCellIndices ()
inline void
setLeafSize(float lx, float ly, float lz)
{
{
Eigen::MatrixXi relative_coordinates = getHalfNeighborCellIndices ();
leaf_size_[0] = lx;
Eigen::MatrixXi relative_coordinates_all( 3, 26);
leaf_size_[1] = ly;
relative_coordinates_all.block<3, 13> (0, 0) = relative_coordinates;
leaf_size_[2] = lz;
relative_coordinates_all.block<3, 13> (0, 13) = -relative_coordinates;
// Avoid division errors
return (relative_coordinates_all);
if (leaf_size_[3] == 0)
leaf_size_[3] = 1;
// Use multiplications instead of divisions
inverse_leaf_size_ = Eigen::Array4f::Ones() / leaf_size_.array();
}
}
/** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions
/** \brief Get the voxel grid leaf size. */
* in a given pointcloud, without considering points outside of a distance threshold from the laser origin
inline Eigen::Vector3f
* \param[in] cloud the point cloud data message
getLeafSize() const
* \param[in] distance_field_name the field name that contains the distance values
{
* \param[in] min_distance the minimum distance a point will be considered from
return (leaf_size_.head<3>());
* \param[in] max_distance the maximum distance a point will be considered to
}
* \param[out] min_pt the resultant minimum bounds
* \param[out] max_pt the resultant maximum bounds
* \param[in] limit_negative if set to true, then all points outside of the interval (min_distance;max_distace) are considered
* \ingroup filters
*/
template <typename PointT> void
getMinMax3D (const typename pcl::PointCloud<PointT>::ConstPtr &cloud,
const std::string &distance_field_name, float min_distance, float max_distance,
Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative = false);
/** \brief Get the minimum and maximum values on each of the 3 (x-y-z) dimensions
/** \brief Set the minimum number of points required for a voxel to be used.
* in a given pointcloud, without considering points outside of a distance threshold from the laser origin
* \param[in] min_points_per_voxel the minimum number of points for required for a voxel to be used
* \param[in] cloud the point cloud data message
*/
* \param[in] indices the vector of indices to use
inline void
* \param[in] distance_field_name the field name that contains the distance values
setMinimumPointsNumberPerVoxel(unsigned int min_points_per_voxel)
* \param[in] min_distance the minimum distance a point will be considered from
{
* \param[in] max_distance the maximum distance a point will be considered to
min_points_per_voxel_ = min_points_per_voxel;
* \param[out] min_pt the resultant minimum bounds
}
* \param[out] max_pt the resultant maximum bounds
* \param[in] limit_negative if set to true, then all points outside of the interval (min_distance;max_distace) are considered
* \ingroup filters
*/
template <typename PointT> void
getMinMax3D (const typename pcl::PointCloud<PointT>::ConstPtr &cloud,
const std::vector<int> &indices,
const std::string &distance_field_name, float min_distance, float max_distance,
Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative = false);
/** \brief VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.
/** \brief Return the minimum number of points required for a voxel to be used.
*
* The VoxelGrid class creates a *3D voxel grid* (think about a voxel
* grid as a set of tiny 3D boxes in space) over the input point cloud data.
* Then, in each *voxel* (i.e., 3D box), all the points present will be
* approximated (i.e., *downsampled*) with their centroid. This approach is
* a bit slower than approximating them with the center of the voxel, but it
* represents the underlying surface more accurately.
*
* \author Radu B. Rusu, Bastian Steder
* \ingroup filters
*/
*/
template <typename PointT>
inline unsigned int
class VoxelGrid: public Filter<PointT>
getMinimumPointsNumberPerVoxel() const
{
{
protected:
return min_points_per_voxel_;
using Filter<PointT>::filter_name_;
}
using Filter<PointT>::getClassName;
using Filter<PointT>::input_;
using Filter<PointT>::indices_;
using PointCloud = typename Filter<PointT>::PointCloud;
using PointCloudPtr = typename PointCloud::Ptr;
using PointCloudConstPtr = typename PointCloud::ConstPtr;
public:
using Ptr = shared_ptr<VoxelGrid<PointT> >;
using ConstPtr = shared_ptr<const VoxelGrid<PointT> >;
/** \brief Empty constructor. */
VoxelGrid () :
leaf_size_ (Eigen::Vector4f::Zero ()),
inverse_leaf_size_ (Eigen::Array4f::Zero ()),
downsample_all_data_ (true),
save_leaf_layout_ (false),
min_b_ (Eigen::Vector4i::Zero ()),
max_b_ (Eigen::Vector4i::Zero ()),
div_b_ (Eigen::Vector4i::Zero ()),
divb_mul_ (Eigen::Vector4i::Zero ()),
filter_field_name_ (""),
filter_limit_min_ (-FLT_MAX),
filter_limit_max_ (FLT_MAX),
filter_limit_negative_ (false),
min_points_per_voxel_ (0)
{
filter_name_ = "VoxelGrid";
}
/** \brief Destructor. */
~VoxelGrid ()
{
}
/** \brief Set the voxel grid leaf size.
/** \brief Get the minimum coordinates of the bounding box (after
* \param[in] leaf_size the voxel grid leaf size
* filtering is performed).
*/
*/
inline void
inline Eigen::Vector3i
setLeafSize (const Eigen::Vector4f &leaf_size)
getMinBoxCoordinates() const
{
{
leaf_size_ = leaf_size;
return (min_b_.head<3>());
// Avoid division errors
}
if (leaf_size_[3] == 0)
leaf_size_[3] = 1;
// Use multiplications instead of divisions
inverse_leaf_size_ = Eigen::Array4f::Ones () / leaf_size_.array ();
}
/** \brief Set the voxel grid leaf size.
/** \brief Get the minimum coordinates of the bounding box (after
* \param[in] lx the leaf size for X
* filtering is performed).
* \param[in] ly the leaf size for Y
*/
* \param[in] lz the leaf size for Z
inline Eigen::Vector3i
*/
getMaxBoxCoordinates() const
inline void
{
setLeafSize (float lx, float ly, float lz)
return (max_b_.head<3>());
{
}
leaf_size_[0] = lx; leaf_size_[1] = ly; leaf_size_[2] = lz;
// Avoid division errors
if (leaf_size_[3] == 0)
leaf_size_[3] = 1;
// Use multiplications instead of divisions
inverse_leaf_size_ = Eigen::Array4f::Ones () / leaf_size_.array ();
}
/** \brief Get the voxel grid leaf size. */
/** \brief Get the number of divisions along all 3 axes (after filtering
inline Eigen::Vector3f
* is performed).
getLeafSize () const { return (leaf_size_.head<3> ()); }
*/
inline Eigen::Vector3i
getNrDivisions() const
{
return (div_b_.head<3>());
}
/** \brief Set to true if all fields need to be downsampled, or false if just XYZ.
/** \brief Get the multipliers to be applied to the grid coordinates in
* \param[in] downsample the new value (true/false)
* order to find the centroid index (after filtering is performed).
*/
*/
inline void
inline Eigen::Vector3i
setDownsampleAllData (bool downsample) { downsample_all_data_ = downsample; }
getDivisionMultiplier() const
{
return (divb_mul_.head<3>());
}
/** \brief Get the state of the internal downsampling parameter (true if
/** \brief Returns the index in the resulting downsampled cloud of the specified point.
* all fields need to be downsampled, false if just XYZ).
*
*/
* \note for efficiency, user must make sure that the saving of the leaf layout is enabled and filtering
inline bool
* performed, and that the point is inside the grid, to avoid invalid access (or use
getDownsampleAllData () const { return (downsample_all_data_); }
* getGridCoordinates+getCentroidIndexAt)
*
* \param[in] p the point to get the index at
*/
inline int
getCentroidIndex(const PointT& p) const
{
return (leaf_layout_.at((Eigen::Vector4i(static_cast<int>(std::floor(p.x * inverse_leaf_size_[0])),
static_cast<int>(std::floor(p.y * inverse_leaf_size_[1])),
static_cast<int>(std::floor(p.z * inverse_leaf_size_[2])), 0) -
min_b_)
.dot(divb_mul_)));
}
/** \brief Set the minimum number of points required for a voxel to be used.
/** \brief Returns the indices in the resulting downsampled cloud of the points at the specified grid coordinates,
* \param[in] min_points_per_voxel the minimum number of points for required for a voxel to be used
* relative to the grid coordinates of the specified point (or -1 if the cell was empty/out of bounds).
*/
* \param[in] reference_point the coordinates of the reference point (corresponding cell is allowed to be empty/out of bounds)
inline void
* \param[in] relative_coordinates matrix with the columns being the coordinates of the requested cells, relative to the reference point's cell
setMinimumPointsNumberPerVoxel (unsigned int min_points_per_voxel) { min_points_per_voxel_ = min_points_per_voxel; }
* \note for efficiency, user must make sure that the saving of the leaf layout is enabled and filtering performed
*/
inline std::vector<int>
getNeighborCentroidIndices(const PointT& reference_point, const Eigen::MatrixXi& relative_coordinates) const
{
Eigen::Vector4i ijk(static_cast<int>(std::floor(reference_point.x * inverse_leaf_size_[0])),
static_cast<int>(std::floor(reference_point.y * inverse_leaf_size_[1])),
static_cast<int>(std::floor(reference_point.z * inverse_leaf_size_[2])), 0);
Eigen::Array4i diff2min = min_b_ - ijk;
Eigen::Array4i diff2max = max_b_ - ijk;
std::vector<int> neighbors(relative_coordinates.cols());
for (int ni = 0; ni < relative_coordinates.cols(); ni++)
{
Eigen::Vector4i displacement = (Eigen::Vector4i() << relative_coordinates.col(ni), 0).finished();
// checking if the specified cell is in the grid
if ((diff2min <= displacement.array()).all() && (diff2max >= displacement.array()).all())
neighbors[ni] = leaf_layout_[((ijk + displacement - min_b_).dot(divb_mul_))]; // .at() can be omitted
else
neighbors[ni] = -1; // cell is out of bounds, consider it empty
}
return (neighbors);
}
/** \brief Return the minimum number of points required for a voxel to be used.
/** \brief Returns the layout of the leafs for fast access to cells relative to current position.
*/
* \note position at (i-min_x) + (j-min_y)*div_x + (k-min_z)*div_x*div_y holds the index of the element at coordinates (i,j,k) in the grid (-1 if empty)
inline unsigned int
*/
getMinimumPointsNumberPerVoxel () const { return min_points_per_voxel_; }
inline std::vector<int>
getLeafLayout() const
{
return (leaf_layout_);
}
/** \brief Set to true if leaf layout information needs to be saved for later access.
/** \brief Returns the corresponding (i,j,k) coordinates in the grid of point (x,y,z).
* \param[in] save_leaf_layout the new value (true/false)
* \param[in] x the X point coordinate to get the (i, j, k) index at
*/
* \param[in] y the Y point coordinate to get the (i, j, k) index at
inline void
* \param[in] z the Z point coordinate to get the (i, j, k) index at
setSaveLeafLayout (bool save_leaf_layout) { save_leaf_layout_ = save_leaf_layout; }
*/
inline Eigen::Vector3i
getGridCoordinates(float x, float y, float z) const
{
return (Eigen::Vector3i(static_cast<int>(std::floor(x * inverse_leaf_size_[0])),
static_cast<int>(std::floor(y * inverse_leaf_size_[1])),
static_cast<int>(std::floor(z * inverse_leaf_size_[2]))));
}
/** \brief Returns true if leaf layout information will to be saved for later access. */
/** \brief Returns the index in the downsampled cloud corresponding to a given set of coordinates.
inline bool
* \param[in] ijk the coordinates (i,j,k) in the grid (-1 if empty)
getSaveLeafLayout () const { return (save_leaf_layout_); }
*/
inline int
getCentroidIndexAt(const Eigen::Vector3i& ijk) const
{
int idx = ((Eigen::Vector4i() << ijk, 0).finished() - min_b_).dot(divb_mul_);
if (idx < 0 || idx >= static_cast<int>(leaf_layout_.size()))
// this checks also if leaf_layout_.size () == 0 i.e. everything was computed as needed
{
return (-1);
}
return (leaf_layout_[idx]);
}
/** \brief Get the minimum coordinates of the bounding box (after
/** \brief Set the field filter limits. All points having field values outside this interval will be discarded.
* filtering is performed).
* \param[in] limit_min the minimum allowed field value
*/
* \param[in] limit_max the maximum allowed field value
inline Eigen::Vector3i
*/
getMinBoxCoordinates () const { return (min_b_.head<3> ()); }
inline void
setFilterLimits(const double& limit_min, const double& limit_max)
{
filter_limit_min_ = limit_min;
filter_limit_max_ = limit_max;
}
/** \brief Get the minimum coordinates of the bounding box (after
/** \brief Get the field filter limits (min/max) set by the user. The default values are -std::numeric_limits<float>::max(), std::numeric_limits<float>::max().
* filtering is performed).
* \param[out] limit_min the minimum allowed field value
*/
* \param[out] limit_max the maximum allowed field value
inline Eigen::Vector3i
*/
getMaxBoxCoordinates () const { return (max_b_.head<3> ()); }
inline void
getFilterLimits(double& limit_min, double& limit_max) const
{
limit_min = filter_limit_min_;
limit_max = filter_limit_max_;
}
/** \brief Get the number of divisions along all 3 axes (after filtering
/** \brief Set to true if we want to return the data outside the interval specified by setFilterLimits (min, max).
* is performed).
* Default: false.
*/
* \param[in] limit_negative return data inside the interval (false) or outside (true)
inline Eigen::Vector3i
*/
getNrDivisions () const { return (div_b_.head<3> ()); }
inline void
setFilterLimitsNegative(const bool limit_negative)
{
filter_limit_negative_ = limit_negative;
}
/** \brief Get the multipliers to be applied to the grid coordinates in
/** \brief Get whether the data outside the interval (min/max) is to be returned (true) or inside (false).
* order to find the centroid index (after filtering is performed).
* \param[out] limit_negative true if data \b outside the interval [min; max] is to be returned, false otherwise
*/
*/
inline Eigen::Vector3i
inline void
getDivisionMultiplier () const { return (divb_mul_.head<3> ()); }
getFilterLimitsNegative(bool& limit_negative) const
{
limit_negative = filter_limit_negative_;
}
/** \brief Returns the index in the resulting downsampled cloud of the specified point.
/** \brief Get whether the data outside the interval (min/max) is to be returned (true) or inside (false).
*
* \return true if data \b outside the interval [min; max] is to be returned, false otherwise
* \note for efficiency, user must make sure that the saving of the leaf layout is enabled and filtering
*/
* performed, and that the point is inside the grid, to avoid invalid access (or use
inline bool
* getGridCoordinates+getCentroidIndexAt)
getFilterLimitsNegative() const
*
{
* \param[in] p the point to get the index at
return (filter_limit_negative_);
*/
}
inline int
getCentroidIndex (const PointT &p) const
{
return (leaf_layout_.at ((Eigen::Vector4i (static_cast<int> (std::floor (p.x * inverse_leaf_size_[0])),
static_cast<int> (std::floor (p.y * inverse_leaf_size_[1])),
static_cast<int> (std::floor (p.z * inverse_leaf_size_[2])), 0) - min_b_).dot (divb_mul_)));
}
/** \brief Returns the indices in the resulting downsampled cloud of the points at the specified grid coordinates,
protected:
* relative to the grid coordinates of the specified point (or -1 if the cell was empty/out of bounds).
/** \brief The size of a leaf. */
* \param[in] reference_point the coordinates of the reference point (corresponding cell is allowed to be empty/out of bounds)
Eigen::Vector4f leaf_size_;
* \param[in] relative_coordinates matrix with the columns being the coordinates of the requested cells, relative to the reference point's cell
* \note for efficiency, user must make sure that the saving of the leaf layout is enabled and filtering performed
*/
inline std::vector<int>
getNeighborCentroidIndices (const PointT &reference_point, const Eigen::MatrixXi &relative_coordinates) const
{
Eigen::Vector4i ijk (static_cast<int> (std::floor (reference_point.x * inverse_leaf_size_[0])),
static_cast<int> (std::floor (reference_point.y * inverse_leaf_size_[1])),
static_cast<int> (std::floor (reference_point.z * inverse_leaf_size_[2])), 0);
Eigen::Array4i diff2min = min_b_ - ijk;
Eigen::Array4i diff2max = max_b_ - ijk;
std::vector<int> neighbors (relative_coordinates.cols());
for (Eigen::Index ni = 0; ni < relative_coordinates.cols (); ni++)
{
Eigen::Vector4i displacement = (Eigen::Vector4i() << relative_coordinates.col(ni), 0).finished();
// checking if the specified cell is in the grid
if ((diff2min <= displacement.array()).all() && (diff2max >= displacement.array()).all())
neighbors[ni] = leaf_layout_[((ijk + displacement - min_b_).dot (divb_mul_))]; // .at() can be omitted
else
neighbors[ni] = -1; // cell is out of bounds, consider it empty
}
return (neighbors);
}
/** \brief Returns the layout of the leafs for fast access to cells relative to current position.
/** \brief Internal leaf sizes stored as 1/leaf_size_ for efficiency reasons. */
* \note position at (i-min_x) + (j-min_y)*div_x + (k-min_z)*div_x*div_y holds the index of the element at coordinates (i,j,k) in the grid (-1 if empty)
Eigen::Array4f inverse_leaf_size_;
*/
inline std::vector<int>
getLeafLayout () const { return (leaf_layout_); }
/** \brief Returns the corresponding (i,j,k) coordinates in the grid of point (x,y,z).
/** \brief The leaf layout information for fast access to cells relative to current position **/
* \param[in] x the X point coordinate to get the (i, j, k) index at
std::vector<int> leaf_layout_;
* \param[in] y the Y point coordinate to get the (i, j, k) index at
* \param[in] z the Z point coordinate to get the (i, j, k) index at
*/
inline Eigen::Vector3i
getGridCoordinates (float x, float y, float z) const
{
return (Eigen::Vector3i (static_cast<int> (std::floor (x * inverse_leaf_size_[0])),
static_cast<int> (std::floor (y * inverse_leaf_size_[1])),
static_cast<int> (std::floor (z * inverse_leaf_size_[2]))));
}
/** \brief Returns the index in the downsampled cloud corresponding to a given set of coordinates.
/** \brief The minimum and maximum bin coordinates, the number of divisions, and the division multiplier. */
* \param[in] ijk the coordinates (i,j,k) in the grid (-1 if empty)
Eigen::Vector4i min_b_, max_b_, div_b_, divb_mul_;
*/
inline int
getCentroidIndexAt (const Eigen::Vector3i &ijk) const
{
int idx = ((Eigen::Vector4i() << ijk, 0).finished() - min_b_).dot (divb_mul_);
if (idx < 0 || idx >= static_cast<int> (leaf_layout_.size ())) // this checks also if leaf_layout_.size () == 0 i.e. everything was computed as needed
{
//if (verbose)
// PCL_ERROR ("[pcl::%s::getCentroidIndexAt] Specified coordinate is outside grid bounds, or leaf layout is not saved, make sure to call setSaveLeafLayout(true) and filter(output) first!\n", getClassName ().c_str ());
return (-1);
}
return (leaf_layout_[idx]);
}
/** \brief Provide the name of the field to be used for filtering data. In conjunction with \a setFilterLimits,
/** \brief The minimum allowed filter value a point will be considered from. */
* points having values outside this interval will be discarded.
double filter_limit_min_;
* \param[in] field_name the name of the field that contains values used for filtering
*/
inline void
setFilterFieldName (const std::string &field_name)
{
filter_field_name_ = field_name;
}
/** \brief Get the name of the field used for filtering. */
/** \brief The maximum allowed filter value a point will be considered from. */
inline std::string const
double filter_limit_max_;
getFilterFieldName () const
{
return (filter_field_name_);
}
/** \brief Set the field filter limits. All points having field values outside this interval will be discarded.
/** \brief Set to true if we want to return the data outside
* \param[in] limit_min the minimum allowed field value
(\a filter_limit_min_;\a filter_limit_max_). Default: false. */
* \param[in] limit_max the maximum allowed field value
bool filter_limit_negative_;
*/
inline void
setFilterLimits (const double &limit_min, const double &limit_max)
{
filter_limit_min_ = limit_min;
filter_limit_max_ = limit_max;
}
/** \brief Get the field filter limits (min/max) set by the user. The default values are -FLT_MAX, FLT_MAX.
/** \brief Minimum number of points per voxel for the centroid to be computed */
* \param[out] limit_min the minimum allowed field value
unsigned int min_points_per_voxel_;
* \param[out] limit_max the maximum allowed field value
*/
inline void
getFilterLimits (double &limit_min, double &limit_max) const
{
limit_min = filter_limit_min_;
limit_max = filter_limit_max_;
}
/** \brief Set to true if we want to return the data outside the interval specified by setFilterLimits (min, max).
typedef typename pcl::traits::fieldList<PointT>::type FieldList;
* Default: false.
* \param[in] limit_negative return data inside the interval (false) or outside (true)
*/
inline void
setFilterLimitsNegative (const bool limit_negative)
{
filter_limit_negative_ = limit_negative;
}
/** \brief Get whether the data outside the interval (min/max) is to be returned (true) or inside (false).
/** \brief Downsample a Point Cloud using a voxelized grid approach
* \param[out] limit_negative true if data \b outside the interval [min; max] is to be returned, false otherwise
* \param[out] output the resultant point cloud message
*/
*/
inline void
void
getFilterLimitsNegative (bool &limit_negative) const
applyFilter(PointCloud& output)
{
{
limit_negative = filter_limit_negative_;
// Has the input dataset been set already?
}
if (!input_)
{
PCL_WARN("[pcl::%s::applyFilter] No input dataset given!\n", getClassName().c_str());
output.width = output.height = 0;
output.points.clear();
return;
}
/** \brief Get whether the data outside the interval (min/max) is to be returned (true) or inside (false).
// Copy the header (and thus the frame_id) + allocate enough space for points
* \return true if data \b outside the interval [min; max] is to be returned, false otherwise
output.height = 1; // downsampling breaks the organized structure
*/
output.is_dense = true; // we filter out invalid points
inline bool
getFilterLimitsNegative () const
{
return (filter_limit_negative_);
}
protected:
Eigen::Vector4f min_p, max_p;
/** \brief The size of a leaf. */
getMinMax3D<PointT>(*input_, *indices_, min_p, max_p);
Eigen::Vector4f leaf_size_;
/** \brief Internal leaf sizes stored as 1/leaf_size_ for efficiency reasons. */
// Check that the leaf size is not too small, given the size of the data
Eigen::Array4f inverse_leaf_size_;
int64_t dx = static_cast<int64_t>((max_p[0] - min_p[0]) * inverse_leaf_size_[0]) + 1;
int64_t dy = static_cast<int64_t>((max_p[1] - min_p[1]) * inverse_leaf_size_[1]) + 1;
int64_t dz = static_cast<int64_t>((max_p[2] - min_p[2]) * inverse_leaf_size_[2]) + 1;
/** \brief Set to true if all fields need to be downsampled, or false if just XYZ. */
if ((dx * dy * dz) > static_cast<int64_t>(std::numeric_limits<int32_t>::max()))
bool downsample_all_data_;
{
PCL_WARN("[pcl::%s::applyFilter] Leaf size is too small for the input dataset. Integer indices would overflow.",
getClassName().c_str());
output = *input_;
return;
}
/** \brief Set to true if leaf layout information needs to be saved in \a leaf_layout_. */
// Compute the minimum and maximum bounding box values
bool save_leaf_layout_;
min_b_[0] = static_cast<int>(std::floor(min_p[0] * inverse_leaf_size_[0]));
max_b_[0] = static_cast<int>(std::floor(max_p[0] * inverse_leaf_size_[0]));
min_b_[1] = static_cast<int>(std::floor(min_p[1] * inverse_leaf_size_[1]));
max_b_[1] = static_cast<int>(std::floor(max_p[1] * inverse_leaf_size_[1]));
min_b_[2] = static_cast<int>(std::floor(min_p[2] * inverse_leaf_size_[2]));
max_b_[2] = static_cast<int>(std::floor(max_p[2] * inverse_leaf_size_[2]));
/** \brief The leaf layout information for fast access to cells relative to current position **/
// Compute the number of divisions needed along all axis
std::vector<int> leaf_layout_;
div_b_ = max_b_ - min_b_ + Eigen::Vector4i::Ones();
div_b_[3] = 0;
/** \brief The minimum and maximum bin coordinates, the number of divisions, and the division multiplier. */
// Set up the division multiplier
Eigen::Vector4i min_b_, max_b_, div_b_, divb_mul_;
divb_mul_ = Eigen::Vector4i(1, div_b_[0], div_b_[0] * div_b_[1], 0);
/** \brief The desired user filter field name. */
// Storage for mapping leaf and pointcloud indexes
std::string filter_field_name_;
std::vector<cloud_point_index_idx> index_vector;
index_vector.reserve(indices_->size());
/** \brief The minimum allowed filter value a point will be considered from. */
// No distance filtering, process all data
double filter_limit_min_;
// First pass: go over all points and insert them into the index_vector vector
// with calculated idx. Points with the same idx value will contribute to the
// same point of resulting CloudPoint
for (std::vector<int>::const_iterator it = indices_->begin(); it != indices_->end(); ++it)
{
if (!input_->is_dense)
// Check if the point is invalid
if (!pcl_isfinite(input_->points[*it].x) ||
!pcl_isfinite(input_->points[*it].y) ||
!pcl_isfinite(input_->points[*it].z))
continue;
/** \brief The maximum allowed filter value a point will be considered from. */
int ijk0 = static_cast<int>(
double filter_limit_max_;
std::floor(input_->points[*it].x * inverse_leaf_size_[0]) - static_cast<float>(min_b_[0]));
int ijk1 = static_cast<int>(
std::floor(input_->points[*it].y * inverse_leaf_size_[1]) - static_cast<float>(min_b_[1]));
int ijk2 = static_cast<int>(
std::floor(input_->points[*it].z * inverse_leaf_size_[2]) - static_cast<float>(min_b_[2]));
/** \brief Set to true if we want to return the data outside (\a filter_limit_min_;\a filter_limit_max_). Default: false. */
// Compute the centroid leaf index
bool filter_limit_negative_;
int idx = ijk0 * divb_mul_[0] + ijk1 * divb_mul_[1] + ijk2 * divb_mul_[2];
index_vector.push_back(cloud_point_index_idx(static_cast<unsigned int>(idx), *it));
}
/** \brief Minimum number of points per voxel for the centroid to be computed */
// Second pass: sort the index_vector vector using value representing target cell as index
unsigned int min_points_per_voxel_;
// in effect all points belonging to the same output cell will be next to each other
std::sort(index_vector.begin(), index_vector.end(), std::less<cloud_point_index_idx>());
using FieldList = typename pcl::traits::fieldList<PointT>::type;
// Third pass: count output cells
// we need to skip all the same, adjacent idx values
unsigned int total = 0;
unsigned int index = 0;
// first_and_last_indices_vector[i] represents the index in index_vector of the first point in
// index_vector belonging to the voxel which corresponds to the i-th output point,
// and of the first point not belonging to.
std::vector<std::pair<unsigned int, unsigned int>> first_and_last_indices_vector;
// Worst case size
first_and_last_indices_vector.reserve(index_vector.size());
while (index < index_vector.size())
{
unsigned int i = index + 1;
while (i < index_vector.size() && index_vector[i].idx == index_vector[index].idx)
++i;
if (i - index >= min_points_per_voxel_)
{
++total;
first_and_last_indices_vector.push_back(std::pair<unsigned int, unsigned int>(index, i));
}
index = i;
}
/** \brief Downsample a Point Cloud using a voxelized grid approach
// Fourth pass: compute centroids, insert them into their final position
* \param[out] output the resultant point cloud message
output.points.resize(total);
*/
void
applyFilter (PointCloud &output) override;
};
/** \brief VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.
index = 0;
*
for (unsigned int cp = 0; cp < first_and_last_indices_vector.size(); ++cp)
* The VoxelGrid class creates a *3D voxel grid* (think about a voxel
{
* grid as a set of tiny 3D boxes in space) over the input point cloud data.
// calculate centroid - sum values from all input points, that have the same idx value in index_vector array
* Then, in each *voxel* (i.e., 3D box), all the points present will be
unsigned int first_index = first_and_last_indices_vector[cp].first;
* approximated (i.e., *downsampled*) with their centroid. This approach is
unsigned int last_index = first_and_last_indices_vector[cp].second;
* a bit slower than approximating them with the center of the voxel, but it
* represents the underlying surface more accurately.
*
* \author Radu B. Rusu, Bastian Steder, Radoslaw Cybulski
* \ingroup filters
*/
template <>
class PCL_EXPORTS VoxelGrid<pcl::PCLPointCloud2> : public Filter<pcl::PCLPointCloud2>
{
using Filter<pcl::PCLPointCloud2>::filter_name_;
using Filter<pcl::PCLPointCloud2>::getClassName;
using PCLPointCloud2 = pcl::PCLPointCloud2;
CentroidPoint<PointT> centroid;
using PCLPointCloud2Ptr = PCLPointCloud2::Ptr;
using PCLPointCloud2ConstPtr = PCLPointCloud2::ConstPtr;
public:
// fill in the accumulator with leaf points
/** \brief Empty constructor. */
for (unsigned int li = first_index; li < last_index; ++li)
VoxelGrid () :
centroid.add(input_->points[index_vector[li].cloud_point_index]);
leaf_size_ (Eigen::Vector4f::Zero ()),
inverse_leaf_size_ (Eigen::Array4f::Zero ()),
downsample_all_data_ (true),
save_leaf_layout_ (false),
min_b_ (Eigen::Vector4i::Zero ()),
max_b_ (Eigen::Vector4i::Zero ()),
div_b_ (Eigen::Vector4i::Zero ()),
divb_mul_ (Eigen::Vector4i::Zero ()),
filter_field_name_ (""),
filter_limit_min_ (-FLT_MAX),
filter_limit_max_ (FLT_MAX),
filter_limit_negative_ (false),
min_points_per_voxel_ (0)
{
filter_name_ = "VoxelGrid";
}
/** \brief Destructor. */
centroid.get(output.points[index]);
~VoxelGrid ()
{
}
/** \brief Set the voxel grid leaf size.
++index;
* \param[in] leaf_size the voxel grid leaf size
}
*/
output.width = static_cast<uint32_t>(output.points.size());
inline void
}
setLeafSize (const Eigen::Vector4f &leaf_size)
};
{
} // namespace pcl
leaf_size_ = leaf_size;
// Avoid division errors
if (leaf_size_[3] == 0)
leaf_size_[3] = 1;
// Use multiplications instead of divisions
inverse_leaf_size_ = Eigen::Array4f::Ones () / leaf_size_.array ();
}
/** \brief Set the voxel grid leaf size.
#endif // BACKPORT_PCL_VOXEL_GRID
* \param[in] lx the leaf size for X
* \param[in] ly the leaf size for Y
* \param[in] lz the leaf size for Z
*/
inline void
setLeafSize (float lx, float ly, float lz)
{
leaf_size_[0] = lx; leaf_size_[1] = ly; leaf_size_[2] = lz;
// Avoid division errors
if (leaf_size_[3] == 0)
leaf_size_[3] = 1;
// Use multiplications instead of divisions
inverse_leaf_size_ = Eigen::Array4f::Ones () / leaf_size_.array ();
}
/** \brief Get the voxel grid leaf size. */
#endif // PCL18_BACKPORTS_VOXEL_GRID_H
inline Eigen::Vector3f
getLeafSize () const { return (leaf_size_.head<3> ()); }
/** \brief Set to true if all fields need to be downsampled, or false if just XYZ.
* \param[in] downsample the new value (true/false)
*/
inline void
setDownsampleAllData (bool downsample) { downsample