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Base Datamodules

Base Datamodules#

Anomalib datamodule base class.

class anomalib.data.base.datamodule.AnomalibDataModule(train_batch_size, eval_batch_size, num_workers, val_split_mode, val_split_ratio, test_split_mode=None, test_split_ratio=None, seed=None)#

Bases: LightningDataModule, ABC

Base Anomalib data module.

Parameters:

  • train_batch_size (int) – Batch size used by the train dataloader.

  • eval_batch_size (int) – Batch size used by the val and test dataloaders.

  • num_workers (int) – Number of workers used by the train, val and test dataloaders.

  • val_split_mode (ValSplitMode) – Determines how the validation split is obtained. Options: [none, same_as_test, from_test, synthetic]

  • val_split_ratio (float) – Fraction of the train or test images held our for validation.

  • test_split_mode (Optional[TestSplitMode], optional) – Determines how the test split is obtained. Options: [none, from_dir, synthetic]. Defaults to None.

  • test_split_ratio (float) – Fraction of the train images held out for testing. Defaults to None.

  • seed (int | None, optional) – Seed used during random subset splitting. Defaults to None.

property is_setup: bool#

Checks if setup() has been called.

At least one of [train_data, val_data, test_data] should be setup.

predict_dataloader()#

Use the test dataloader for inference unless overridden.

Return type:

Any

setup(stage=None)#

Set up train, validation and test data.

Parameters:

stage (Optional[str]) – str | None: Train/Val/Test stages. Defaults to None.

Return type:

None

test_dataloader()#

Get test dataloader.

Return type:

Any

train_dataloader()#

Get train dataloader.

Return type:

Any

val_dataloader()#

Get validation dataloader.

Return type:

Any

anomalib.data.base.datamodule.collate_fn(batch)#

Collate bounding boxes as lists.

Bounding boxes are collated as a list of tensors, while the default collate function is used for all other entries.

Parameters:

batch (List) – list of items in the batch where len(batch) is equal to the batch size.

Returns:

Dictionary containing the collated batch information.

Return type:

dict[str, Any]

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