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[wenwu2021]

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class Folder(AnomalibDataModule):
"""Folder DataModule.

Args:
    name (str): Name of the dataset. Used for logging/saving.
    normal_dir (str | Path | Sequence): Directory containing normal images.
    root (str | Path | None): Root folder containing normal and abnormal
        directories. Defaults to ``None``.
    abnormal_dir (str | Path | None | Sequence): Directory containing
        abnormal images. Defaults to ``None``.
    normal_test_dir (str | Path | Sequence | None): Directory containing
        normal test images. Defaults to ``None``.
    mask_dir (str | Path | Sequence | None): Directory containing mask
        annotations. Defaults to ``None``.
    normal_split_ratio (float): Ratio to split normal training images for
        test set when no normal test images exist.
        Defaults to ``0.2``.
    extensions (tuple[str, ...] | None): Image extensions to include.
        Defaults to ``None``.
    train_batch_size (int): Training batch size.
        Defaults to ``32``.
    eval_batch_size (int): Validation/test batch size.
        Defaults to ``32``.
    num_workers (int): Number of workers for data loading.
        Defaults to ``8``.
    train_augmentations (Transform | None): Augmentations to apply dto the training images
        Defaults to ``None``.
    val_augmentations (Transform | None): Augmentations to apply to the validation images.
        Defaults to ``None``.
    test_augmentations (Transform | None): Augmentations to apply to the test images.
        Defaults to ``None``.
    augmentations (Transform | None): General augmentations to apply if stage-specific
        augmentations are not provided.
    test_split_mode (TestSplitMode): Method to obtain test subset.
        Defaults to ``TestSplitMode.FROM_DIR``.
    test_split_ratio (float): Fraction of train images for testing.
        Defaults to ``0.2``.
    val_split_mode (ValSplitMode): Method to obtain validation subset.
        Defaults to ``ValSplitMode.FROM_TEST``.
    val_split_ratio (float): Fraction of images for validation.
        Defaults to ``0.5``.
    seed (int | None): Random seed for splitting.
        Defaults to ``None``.

Example:
    Create and setup a folder datamodule::

        >>> from anomalib.data import Folder
        >>> datamodule = Folder(
        ...     name="custom",
        ...     root="./datasets/custom",
        ...     normal_dir="good",
        ...     abnormal_dir="defect",
        ...     mask_dir="mask"
        ... )
        >>> datamodule.setup()

    Get a batch from train dataloader::

        >>> batch = next(iter(datamodule.train_dataloader()))
        >>> batch.keys()
        dict_keys(['image', 'label', 'mask', 'image_path', 'mask_path'])

    Get a batch from test dataloader::

        >>> batch = next(iter(datamodule.test_dataloader()))
        >>> batch.keys()
        dict_keys(['image', 'label', 'mask', 'image_path', 'mask_path'])
"""

def __init__(
    self,
    name: str,
    normal_dir: str | Path | Sequence[str | Path],
    root: str | Path | None = None,
    abnormal_dir: str | Path | Sequence[str | Path] | None = None,
    normal_test_dir: str | Path | Sequence[str | Path] | None = None,
    mask_dir: str | Path | Sequence[str | Path] | None = None,
    normal_split_ratio: float = 0.2,
    extensions: tuple[str] | None = None,
    train_batch_size: int = 32,
    eval_batch_size: int = 32,
    num_workers: int = 8,
    train_augmentations: Transform | None = None,
    val_augmentations: Transform | None = None,
    test_augmentations: Transform | None = None,
    augmentations: Transform | None = None,
    test_split_mode: TestSplitMode | str = TestSplitMode.FROM_DIR,
    test_split_ratio: float = 0.2,
    val_split_mode: ValSplitMode | str = ValSplitMode.FROM_TEST,
    val_split_ratio: float = 0.5,
    seed: int | None = None,
) -> None:
    self._name = name
    self.root = root
    self.normal_dir = normal_dir
    self.abnormal_dir = abnormal_dir
    self.normal_test_dir = normal_test_dir
    self.mask_dir = mask_dir
    self.extensions = extensions
    test_split_mode = TestSplitMode(test_split_mode)
    val_split_mode = ValSplitMode(val_split_mode)
    super().__init__(
        train_batch_size=train_batch_size,
        eval_batch_size=eval_batch_size,
        num_workers=num_workers,
        train_augmentations=train_augmentations,
        val_augmentations=val_augmentations,
        test_augmentations=test_augmentations,
        augmentations=augmentations,
        test_split_mode=test_split_mode,
        test_split_ratio=test_split_ratio,
        val_split_mode=val_split_mode,
        val_split_ratio=val_split_ratio,
        seed=seed,
    )

      What is the relationship between   test_split_mode and  val_split_mode？

What is the relationship between test_split_ratio and val_split_ratio? Is the data get from this normal_test-dir
How to set ？

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[alfieroddan]

duplicate of #2825