uvgVPCCenc 1.0.0
uvgVPCCenc is an open-source real-time V-PCC encoder library written in C++ from scratch.
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#include <nanoflann.hpp>
Public Types | |
using | self_t = KDTreeVectorOfVectorsAdaptor< VectorOfVectorsType, num_t, DIM, Distance, IndexType > |
using | metric_t = typename Distance::template traits< num_t, self_t >::distance_t |
using | index_t = nanoflann::KDTreeSingleIndexAdaptor< metric_t, self_t, DIM, IndexType > |
Public Member Functions | |
KDTreeVectorOfVectorsAdaptor (const size_t, const VectorOfVectorsType &mat, const int leaf_max_size=10, const unsigned int n_thread_build=1) | |
~KDTreeVectorOfVectorsAdaptor () | |
void | query (const num_t *query_point, const size_t num_closest, IndexType *out_indices, num_t *out_distances_sq) const |
Interface expected by KDTreeSingleIndexAdaptor | |
const self_t & | derived () const |
self_t & | derived () |
size_t | kdtree_get_point_count () const |
num_t | kdtree_get_pt (const size_t idx, const size_t dim) const |
template<class BBOX > | |
bool | kdtree_get_bbox (BBOX &) const |
Public Attributes | |
index_t * | index = nullptr |
const VectorOfVectorsType & | m_data |
A simple vector-of-vectors adaptor for nanoflann, without duplicating the storage. The i'th vector represents a point in the state space.
DIM | If set to >0, it specifies a compile-time fixed dimensionality for the points in the data set, allowing more compiler optimizations. |
num_t | The type of the point coordinates (typ. double or float). |
Distance | The distance metric to use: nanoflann::metric_L1, nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc. |
IndexType | The type for indices in the KD-tree index (typically, size_t of int) |
using KDTreeVectorOfVectorsAdaptor< VectorOfVectorsType, num_t, DIM, Distance, IndexType >::index_t = nanoflann::KDTreeSingleIndexAdaptor<metric_t, self_t, DIM, IndexType> |
using KDTreeVectorOfVectorsAdaptor< VectorOfVectorsType, num_t, DIM, Distance, IndexType >::metric_t = typename Distance::template traits<num_t, self_t>::distance_t |
using KDTreeVectorOfVectorsAdaptor< VectorOfVectorsType, num_t, DIM, Distance, IndexType >::self_t = KDTreeVectorOfVectorsAdaptor<VectorOfVectorsType, num_t, DIM, Distance, IndexType> |
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Constructor: takes a const ref to the vector of vectors object with the data points
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Query for the num_closest closest points to a given point (entered as query_point[0:dim-1]). Note that this is a short-cut method for index->findNeighbors(). The user can also call index->... methods as desired.
index_t* KDTreeVectorOfVectorsAdaptor< VectorOfVectorsType, num_t, DIM, Distance, IndexType >::index = nullptr |
The kd-tree index for the user to call its methods as usual with any other FLANN index
const VectorOfVectorsType& KDTreeVectorOfVectorsAdaptor< VectorOfVectorsType, num_t, DIM, Distance, IndexType >::m_data |