class_docstr: Folder dataset.
  
  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): Fixed subset split that follows from folder structure on file system.
          Choose from [Split.FULL, Split.TRAIN, Split.TEST]
      normal_dir (str | Path): Path to the directory containing normal images.
      root (str | Path | None): Root folder of the dataset.
      abnormal_dir (str | Path | None, optional): Path to the directory containing abnormal images.
      normal_test_dir (str | Path | None, optional): Path to the directory containing
          normal images for the test dataset. Defaults to None.
      mask_dir (str | Path | None, optional): Path to the directory containing
          the mask annotations. Defaults to None.
      normal_depth_dir (str | Path | None, optional): Path to the directory containing
          normal depth images for the test dataset. Normal test depth images will be a split of `normal_dir`
      abnormal_depth_dir (str | Path | None, optional): Path to the directory containing
          abnormal depth images for the test dataset.
      normal_test_depth_dir (str | Path | None, optional): Path to the directory containing
          normal depth images for the test dataset. Normal test images will be a split of `normal_dir`
          if `None`. Defaults to None.
      extensions (tuple[str, ...] | None, optional): Type of the image extensions to read from the
          directory.
      val_split_mode (ValSplitMode): Setting that determines how the validation subset is obtained.
  
  Raises:
      ValueError: When task is set to classification and `mask_dir` is provided. When `mask_dir` is
          provided, `task` should be set to `segmentation`.
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docstr: Assign samples.
docstr_tok: ["Assign","samples","."]
code: def _setup(self) -> None:
      """Assign samples."""
      self.samples = make_folder3d_dataset(
          root=self.root,
          normal_dir=self.normal_dir,
          abnormal_dir=self.abnormal_dir,
          normal_test_dir=self.normal_test_dir,
          mask_dir=self.mask_dir,
          normal_depth_dir=self.normal_depth_dir,
          abnormal_depth_dir=self.abnormal_depth_dir,
          normal_test_depth_dir=self.normal_test_depth_dir,
          split=self.split,
          extensions=self.extensions,
      )
  
file_path: anomalib/src/anomalib/data/folder_3d.py
imports: from __future__ import annotations
  from pathlib import Path
  import albumentations
  from pandas import DataFrame, isna
  from anomalib.data.base import AnomalibDataModule, AnomalibDepthDataset
  from anomalib.data.task_type import TaskType
  from anomalib.data.utils import DirType, InputNormalizationMethod, LabelName, Split, TestSplitMode, ValSplitMode, get_transforms
  from anomalib.data.utils.path import _prepare_files_labels, _resolve_path
label_desc: Use image node_id 2 for calling the Folder3DDataset obj's underlying member method code with example usage: obj._setup() without return types