#nn.functional.point_pillars_preprocess

#horizon_plugin_pytorch.nn.functional.point_pillars_preprocess(points_list: List[Tensor], pc_range: Tensor, voxel_size: Tensor, max_voxels: int, max_points_per_voxel: int, use_max: bool, norm_range: Tensor, norm_dims: Tensor)

Preprocess PointPillars.

• Parameters:
  • points_list – [(M1, ndim), (M2, ndim),…], List of PointCloud data.
  • pc_range – (6,), indicate voxel range, format: [x_min, y_min, z_min, x_max, y_max, z_max]
  • voxel_size – (3,), xyz, indicate voxel size.
  • max_voxels – Indicate maximum voxels.
  • max_points_per_voxel – Indicate maximum points contained in a voxel.
  • use_max – Whether to use max_voxels, for deploy should be True.
  • norm_range – Feature range, like [x_min, y_min, z_min, …, x_max, y_max, z_max, …].
  • norm_dims – Dims to do normalize.
• Returns: (features, coords), encoded feature and coordinates in (idx, z, y, x) format.
• Return type: (Tensor, Tensor)