iterator support

BufferGetAndValidate */

This method has no effects in this class, but raises an exception if the expected size does not match */

Write ".ply" files Parameters ---------- filename : string the name of the file to which the data is saved. A '.ply' e

CIntToPy */

CIntFromPy */

Returns the dim'th component of the idx'th point in the class:

Returns the dim'th component of the idx'th point in the class:

Returns the dim'th component of the idx'th point in the class:

Read ".ply" files Parameters ---------- filename : string the name of the file to read. Returns -------

direct access to data (read-only)

Fast confusion matrix (100x faster than Scikit learn). But only works if labels are la :param true: :param false: :param num_clas

ExtTypeTest */

Helper accessor to the dataset points:

Helper accessor to the dataset points:

Helper accessor to the dataset points:

RaiseArgTupleInvalid */

BufferFallbackError */

* Builds the index */

Computes IoU from confusion matrices. :param confusions: ([..., n_c, n_c] np.int32). Can be any dimension, the confusion matrices should be

Initialize parameters for KPConvDeformable. :param kernel_size: Number of kernel points. :param p_dim: dimension of the po

assign one value to all elements

Method performing batch and neighbors calibration. Batch calibration: Set "batch_limit" (the maximum number of points allowed in

Must return the number of data points

Must return the number of data points

Must return the number of data points

GetBuiltinName */

CIntToPy */

Computes neighbors for a batch of queries and supports :param queries: (N1, 3) the query points :param supports: (N2, 3) the support p

Filter neighborhoods with max number of neighbors. Limit is set to keep XX% of the neighborhoods untouched. Limit is computed at in

Query for the \a 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->

Train the model on a particular dataset.

Implementation of an augmentation transform for point clouds.

* Builds the index */

CPP wrapper for a grid subsampling (method = barycenter for points and features) :param points: (N, 3) matrix of input points :param f

:param support_pts: points you have, B*N1*3 , search on these points :param query_pts: points you want to know the neighbour index, B

Read ".ply" files Parameters ---------- filename : string the name of the file to read. Returns -------

GetItemInt */

ParseKeywords */

Create rotation matrices from a list of axes and angles. Code from wikipedia on quaternions :param axis: float32[N, 3] :param angle: f

Frees the previously-built index. Automatically called within * buildIndex(). */

Frees the previously-built index. Automatically called within buildIndex(). */

Frees the previously-built index. Automatically called within * buildIndex(). */