A Class for nearest neighbor search.
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#include <NearestNeighborSearch.h>
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| | NearestNeighborSearch (const Tensor &dataset_points, const Dtype &index_dtype=core::Int32) |
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| | ~NearestNeighborSearch () |
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| | NearestNeighborSearch (const NearestNeighborSearch &)=delete |
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| NearestNeighborSearch & | operator= (const NearestNeighborSearch &)=delete |
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| bool | KnnIndex () |
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| bool | MultiRadiusIndex () |
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| bool | FixedRadiusIndex (utility::optional< double > radius={}) |
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| bool | HybridIndex (utility::optional< double > radius={}) |
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| std::pair< Tensor, Tensor > | KnnSearch (const Tensor &query_points, int knn) |
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| std::tuple< Tensor, Tensor, Tensor > | FixedRadiusSearch (const Tensor &query_points, double radius, bool sort=true) |
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| std::tuple< Tensor, Tensor, Tensor > | MultiRadiusSearch (const Tensor &query_points, const Tensor &radii) |
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| std::tuple< Tensor, Tensor, Tensor > | HybridSearch (const Tensor &query_points, const double radius, const int max_knn) const |
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A Class for nearest neighbor search.
◆ NearestNeighborSearch() [1/2]
| open3d::core::nns::NearestNeighborSearch::NearestNeighborSearch |
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const Tensor & |
dataset_points, |
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const Dtype & |
index_dtype = core::Int32 |
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) |
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Constructor.
- Parameters
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| dataset_points | Dataset points for constructing search index. Must be 2D, with shape {n, d}. |
◆ ~NearestNeighborSearch()
| open3d::core::nns::NearestNeighborSearch::~NearestNeighborSearch |
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◆ NearestNeighborSearch() [2/2]
◆ FixedRadiusIndex()
| bool open3d::core::nns::NearestNeighborSearch::FixedRadiusIndex |
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utility::optional< double > |
radius = {} | ) |
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Set index for fixed-radius search.
- Parameters
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| radius | optional radius parameter. required for gpu fixed radius index. |
- Returns
- Returns true if building index success, otherwise false.
◆ FixedRadiusSearch()
| std::tuple< Tensor, Tensor, Tensor > open3d::core::nns::NearestNeighborSearch::FixedRadiusSearch |
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const Tensor & |
query_points, |
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double |
radius, |
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bool |
sort = true |
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) |
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Perform fixed radius search. All query points share the same radius.
- Parameters
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| query_points | Data points for querying. Must be 2D, with shape {n, d}. |
| radius | Radius. |
| sort | Sort the results by distance. Default is True. |
- Returns
- Tuple of Tensors, (indices, distances, num_neighbors):
- indicecs: Tensor of shape {total_number_of_neighbors,}, with dtype same as index_dtype_.
- distances: Tensor of shape {total_number_of_neighbors,}, same dtype with query_points. The distances are squared L2 distances.
- num_neighbors: Tensor of shape {n+1,}, with dtype Int64. The Tensor is a prefix sum of the number of neighbors for each query point.
◆ HybridIndex()
| bool open3d::core::nns::NearestNeighborSearch::HybridIndex |
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utility::optional< double > |
radius = {} | ) |
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Set index for hybrid search.
- Returns
- Returns true if building index success, otherwise false.
◆ HybridSearch()
| std::tuple< Tensor, Tensor, Tensor > open3d::core::nns::NearestNeighborSearch::HybridSearch |
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const Tensor & |
query_points, |
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const double |
radius, |
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const int |
max_knn |
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Perform hybrid search.
- Parameters
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| query_points | Data points for querying. Must be 2D, with shape {n, d}. |
| radius | Radius. |
| max_knn | Maximum number of neighbor to search per query. |
- Returns
- Tuple of Tensors, (indices, distances, counts):
- indices: Tensor of shape {n, knn}, with dtype same as index_dtype_.
- distainces: Tensor of shape {n, knn}, with same dtype with query_points. The distances are squared L2 distances.
- counts: Counts of neighbour for each query points. [Tensor of shape {n}, with dtype same as index_dtype_].
◆ KnnIndex()
| bool open3d::core::nns::NearestNeighborSearch::KnnIndex |
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Set index for knn search.
- Returns
- Returns true if building index success, otherwise false.
◆ KnnSearch()
| std::pair< Tensor, Tensor > open3d::core::nns::NearestNeighborSearch::KnnSearch |
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const Tensor & |
query_points, |
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int |
knn |
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Perform knn search.
- Parameters
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| query_points | Query points. Must be 2D, with shape {n, d}. |
| knn | Number of neighbors to search per query point. |
- Returns
- Pair of Tensors, (indices, distances):
- indices: Tensor of shape {n, knn}, with dtype same as index_dtype_.
- distances: Tensor of shape {n, knn}, same dtype with query_points. The distances are squared L2 distances.
◆ MultiRadiusIndex()
| bool open3d::core::nns::NearestNeighborSearch::MultiRadiusIndex |
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Set index for multi-radius search.
- Returns
- Returns true if building index success, otherwise false.
◆ MultiRadiusSearch()
| std::tuple< Tensor, Tensor, Tensor > open3d::core::nns::NearestNeighborSearch::MultiRadiusSearch |
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const Tensor & |
query_points, |
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const Tensor & |
radii |
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) |
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Perform multi-radius search. Each query point has an independent radius.
- Parameters
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| query_points | Query points. Must be 2D, with shape {n, d}. |
| radii | Radii of query points. Each query point has one radius. Must be 1D, with shape {n,}. |
- Returns
- Tuple of Tensors, (indices,distances, num_neighbors):
- indicecs: Tensor of shape {total_number_of_neighbors,}, with dtype same as index_dtype_.
- distances: Tensor of shape {total_number_of_neighbors,}, same dtype with query_points. The distances are squared L2 distances.
- num_neighbors: Tensor of shape {n+1,}, with dtype Int64. The Tensor is a prefix sum of the number of neighbors for each query point.
◆ operator=()
◆ dataset_points_
| const Tensor open3d::core::nns::NearestNeighborSearch::dataset_points_ |
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protected |
◆ fixed_radius_index_
◆ index_dtype_
| const Dtype open3d::core::nns::NearestNeighborSearch::index_dtype_ |
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◆ knn_index_
| std::unique_ptr<nns::KnnIndex> open3d::core::nns::NearestNeighborSearch::knn_index_ |
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◆ nanoflann_index_
| std::unique_ptr<NanoFlannIndex> open3d::core::nns::NearestNeighborSearch::nanoflann_index_ |
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protected |
The documentation for this class was generated from the following files:
1.9.4