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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2012, Jeremie Papon
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of Willow Garage, Inc. nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* Author : jpapon@gmail.com
* Email : jpapon@gmail.com
*/
#pragma once
namespace pcl {
namespace octree {
/** \brief @b Octree adjacency leaf container class- stores a list of pointers to
* neighbors, number of points added, and a DataT value \note This class implements a
* leaf node that stores pointers to neighboring leaves \note This class also has a
* virtual computeData function, which is called by
* octreePointCloudAdjacency::addPointsFromInputCloud. \note You should make explicit
* instantiations of it for your pointtype/datatype combo (if needed) see
* supervoxel_clustering.hpp for an example of this
*/
template <typename PointInT, typename DataT = PointInT>
class OctreePointCloudAdjacencyContainer : public OctreeContainerBase {
template <typename T, typename U, typename V>
friend class OctreePointCloudAdjacency;
public:
using NeighborListT = std::list<OctreePointCloudAdjacencyContainer<PointInT, DataT>*>;
using const_iterator = typename NeighborListT::const_iterator;
// const iterators to neighbors
inline const_iterator
cbegin() const
{
return (neighbors_.begin());
}
inline const_iterator
cend() const
{
return (neighbors_.end());
}
// size of neighbors
inline std::size_t
size() const
{
return neighbors_.size();
}
/** \brief Class initialization. */
OctreePointCloudAdjacencyContainer() : OctreeContainerBase() { this->reset(); }
/** \brief Empty class deconstructor. */
~OctreePointCloudAdjacencyContainer() {}
/** \brief Returns the number of neighbors this leaf has
* \returns number of neighbors
*/
std::size_t
getNumNeighbors() const
{
return neighbors_.size();
}
/** \brief Gets the number of points contributing to this leaf */
int
getPointCounter() const
{
return num_points_;
}
/** \brief Returns a reference to the data member to access it without copying */
DataT&
getData()
{
return data_;
}
/** \brief Sets the data member
* \param[in] data_arg New value for data
*/
void
setData(const DataT& data_arg)
{
data_ = data_arg;
}
/** \brief virtual method to get size of container
* \return number of points added to leaf node container.
*/
std::size_t
getSize() const override
{
return num_points_;
}
protected:
// iterators to neighbors
using iterator = typename NeighborListT::iterator;
inline iterator
begin()
{
return (neighbors_.begin());
}
inline iterator
end()
{
return (neighbors_.end());
}
/** \brief deep copy function */
virtual OctreePointCloudAdjacencyContainer*
deepCopy() const
{
OctreePointCloudAdjacencyContainer* new_container =
new OctreePointCloudAdjacencyContainer;
new_container->setNeighbors(this->neighbors_);
new_container->setPointCounter(this->num_points_);
return new_container;
}
/** \brief Add new point to container- this just counts points
* \note To actually store data in the leaves, need to specialize this
* for your point and data type as in supervoxel_clustering.hpp
*/
// param[in] new_point the new point to add
void
addPoint(const PointInT& /*new_point*/)
{
using namespace pcl::common;
++num_points_;
}
/** \brief Function for working on data added. Base implementation does nothing
* */
void
computeData()
{}
/** \brief Sets the number of points contributing to this leaf */
void
setPointCounter(int points_arg)
{
num_points_ = points_arg;
}
/** \brief Clear the voxel centroid */
void
reset() override
{
neighbors_.clear();
num_points_ = 0;
data_ = DataT();
}
/** \brief Add new neighbor to voxel.
* \param[in] neighbor the new neighbor to add
*/
void
addNeighbor(OctreePointCloudAdjacencyContainer* neighbor)
{
neighbors_.push_back(neighbor);
}
/** \brief Remove neighbor from neighbor set.
* \param[in] neighbor the neighbor to remove
*/
void
removeNeighbor(OctreePointCloudAdjacencyContainer* neighbor)
{
for (iterator neighb_it = neighbors_.begin(); neighb_it != neighbors_.end();
++neighb_it) {
if (*neighb_it == neighbor) {
neighbors_.erase(neighb_it);
return;
}
}
}
/** \brief Sets the whole neighbor set
* \param[in] neighbor_arg the new set
*/
void
setNeighbors(const NeighborListT& neighbor_arg)
{
neighbors_ = neighbor_arg;
}
private:
int num_points_;
NeighborListT neighbors_;
DataT data_;
};
} // namespace octree
} // namespace pcl
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