class_docstr: MVTec 3D dataset class.
  
  Args:
      task (TaskType): Task type, ``classification``, ``detection`` or ``segmentation``
      transform (A.Compose): Albumentations Compose object describing the transforms that are applied to the inputs.
      split (str | Split | None): Split of the dataset, usually Split.TRAIN or Split.TEST
      root (Path | str): Path to the root of the dataset
      category (str): Sub-category of the dataset, e.g. 'bagel'
class_docstr_tok: ["MVTec","3D","dataset","class",".","Args",":","task","(","TaskType",")",":","Task","type",",","``","classification","``",",","``","detection","``","or","``","segmentation","``","transform","(","A.Compose",")",":","Albumentations","Compose","object","describing","the","transforms","that","are","applied","to","the","inputs",".","split","(","str","|","Split","|","None",")",":","Split","of","the","dataset",",","usually","Split.TRAIN","or","Split.TEST","root","(","Path","|","str",")",":","Path","to","the","root","of","the","dataset","category","(","str",")",":","Sub-category","of","the","dataset",",","e.g",".","'bagel","'"]
code: def _setup(self) -> None:
      self.samples = make_mvtec_3d_dataset(
          self.root_category,
          split=self.split,
          extensions=IMG_EXTENSIONS,
      )
  
file_path: anomalib/src/anomalib/data/mvtec_3d.py
imports: from __future__ import annotations
  import logging
  from pathlib import Path
  from typing import Sequence
  import albumentations
  from pandas import DataFrame
  from anomalib.data.base import AnomalibDataModule, AnomalibDepthDataset
  from anomalib.data.task_type import TaskType
  from anomalib.data.utils import DownloadInfo, InputNormalizationMethod, LabelName, Split, TestSplitMode, ValSplitMode, download_and_extract, get_transforms
label_desc: Use image node_id 2 for calling the MVTec3DDataset obj's underlying member method code with example usage: obj._setup() without return types