Fix typos in NearestNeighborSearch.h, NanoFlannIndex and NNSIndex (#6705

)

cpp/open3d/core/nns/NNSIndex.h

@@ -51,7 +51,7 @@ class NNSIndex {
     /// \param knn Number of nearest neighbor to search.
     /// \return Pair of Tensors: (indices, distances):
     /// - indices: Tensor of shape {n, knn}, with dtype Int32.
-    /// - distainces: Tensor of shape {n, knn}, same dtype with dataset_points.
+    /// - distances: Tensor of shape {n, knn}, same dtype with dataset_points.
     virtual std::pair<Tensor, Tensor> SearchKnn(const Tensor &query_points,
                                                 int knn) const = 0;
 
@@ -61,7 +61,7 @@ class NNSIndex {
     /// dtype with dataset_points.
     /// \param radii list of radius. Must be 1D, with shape {n, }.
     /// \return Tuple of Tensors: (indices, distances, num_neighbors):
-    /// - indicecs: Tensor of shape {total_num_neighbors,}, dtype Int32.
+    /// - indices: Tensor of shape {total_num_neighbors,}, dtype Int32.
     /// - distances: Tensor of shape {total_num_neighbors,}, same dtype with
     /// dataset_points.
     /// - num_neighbors: Tensor of shape {n,}, dtype Int32.
@@ -76,7 +76,7 @@ class NNSIndex {
     /// dtype with dataset_points.
     /// \param radius Radius.
     /// \return Tuple of Tensors, (indices, distances, num_neighbors):
-    /// - indicecs: Tensor of shape {total_num_neighbors,}, dtype Int32.
+    /// - indices: Tensor of shape {total_num_neighbors,}, dtype Int32.
     /// - distances: Tensor of shape {total_num_neighbors,}, same dtype with
     /// dataset_points.
     /// - num_neighbors: Tensor of shape {n}, dtype Int32.

cpp/open3d/core/nns/NanoFlannIndex.h

@@ -54,7 +54,7 @@ class NanoFlannIndex : public NNSIndex {
     /// \param knn Number of nearest neighbor to search.
     /// \return Pair of Tensors: (indices, distances):
     /// - indices: Tensor of shape {n, knn}, with dtype Int32.
-    /// - distainces: Tensor of shape {n, knn}, same dtype with dataset_points.
+    /// - distances: Tensor of shape {n, knn}, same dtype with dataset_points.
     std::pair<Tensor, Tensor> SearchKnn(const Tensor &query_points,
                                         int knn) const override;
 
@@ -64,7 +64,7 @@ class NanoFlannIndex : public NNSIndex {
     /// dtype with dataset_points.
     /// \param radii list of radius. Must be 1D, with shape {n, }.
     /// \return Tuple of Tensors: (indices, distances, counts):
-    /// - indicecs: Tensor of shape {total_num_neighbors,}, dtype Int32.
+    /// - indices: Tensor of shape {total_num_neighbors,}, dtype Int32.
     /// - distances: Tensor of shape {total_num_neighbors,}, same dtype with
     /// dataset_points.
     /// - counts: Tensor of shape {n,}, dtype Int64.
@@ -79,7 +79,7 @@ class NanoFlannIndex : public NNSIndex {
     /// dtype with dataset_points.
     /// \param radius Radius.
     /// \return Tuple of Tensors, (indices, distances, counts):
-    /// - indicecs: Tensor of shape {total_num_neighbors,}, dtype Int32.
+    /// - indices: Tensor of shape {total_num_neighbors,}, dtype Int32.
     /// - distances: Tensor of shape {total_num_neighbors,}, same dtype with
     /// dataset_points.
     /// - counts: Tensor of shape {n}, dtype Int64.

cpp/open3d/core/nns/NearestNeighborSearch.h

@@ -76,7 +76,7 @@ class NearestNeighborSearch {
     /// \param radius Radius.
     /// \param sort Sort the results by distance. Default is True.
     /// \return Tuple of Tensors, (indices, distances, num_neighbors):
-    /// - indicecs: Tensor of shape {total_number_of_neighbors,}, with dtype
+    /// - indices: 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.
@@ -91,7 +91,7 @@ class NearestNeighborSearch {
     /// \param radii Radii of query points. Each query point has one radius.
     /// Must be 1D, with shape {n,}.
     /// \return Tuple of Tensors, (indices,distances, num_neighbors):
-    /// - indicecs: Tensor of shape {total_number_of_neighbors,}, with dtype
+    /// - indices: 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.
@@ -108,7 +108,7 @@ class NearestNeighborSearch {
     /// \param max_knn Maximum number of neighbor to search per query.
     /// \return 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
+    /// - distances: 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_].