src.model.deeplearn.dlrun.furthest_point_subsampling_post_processor

Classes

FurthestPointSubsamplingPostProcessor(...)

class src.model.deeplearn.dlrun.furthest_point_subsampling_post_processor.FurthestPointSubsamplingPostProcessor(fps_preproc, **kwargs)
Author:

Alberto M. Esmoris Pena

Postprocess an input in the furthest point subsampling space back to the original space before the subsampling.

See FurthestPointSubsamplingPreProcessor.

Variables:

fps_preproc (FurthestPointSubsamplingPreProcessor) – The preprocessor that generated the furthest point subsampling that must be reverted by the post-processor.

__init__(fps_preproc, **kwargs)

Initialization/instantiation of a Furthest Point Subsampling post-processor.

Parameters:

kwargs – The key-word arguments for the FurthestPointSubsamplingPostProcessor.

__call__(inputs, reducer=None)

Executes the post-processing logic.

Parameters:
  • inputs (dict) – A key-word input where the key “X” gives the coordinates of the points in the original point cloud. Also, the key “z” gives the predictions computed on a receptive field of \(R\) points that must be propagated back to the \(m\) points of the original point cloud.

  • reducer (PredictionReducer) – The prediction reducer for the post-processor, if any.

Returns:

The \(m\) point-wise predictions derived from the \(R\) input predictions on the receptive field.

post_process(inputs, reducer)

Assists the FurthestPointSubsamplingPreProcessor.__call__() providing the post-process logic itself.