`anomalib.models.draem.utils`¶

Helpers for the DRAEM model implementation.

Submodules¶

Class that generates noisy augmentations of input images.

class anomalib.models.draem.utils.Augmenter(anomaly_source_path: Optional[str] = None)[source]¶

Class that generates noisy augmentations of input images.

Parameters

anomaly_source_path (Optional[str]) – Path to a folder of images that will be used as source of the anomalous
specified (noise. If not) –
instead. (random noise will be used) –

rand_augmenter() → imgaug.augmenters.Sequential¶

Selects 3 random transforms that will be applied to the anomaly source images.

generate_perturbation(height: int, width: int, anomaly_source_path: Optional[str]) → Tuple[numpy.ndarray, numpy.ndarray]¶

Generate an image containing a random anomalous perturbation using a source image.

Parameters

height (int) – height of the generated image.
width – (int): width of the generated image.
anomaly_source_path (Optional[str]) – Path to an image file. If not provided, random noise will be used
instead. –

Returns

Image containing a random anomalous perturbation, and the corresponding ground truth anomaly mask.

augment_batch(batch: torch.Tensor) → Tuple[torch.Tensor, torch.Tensor]¶

Generate anomalous augmentations for a batch of input images.

Parameters

batch (Tensor) – Batch of input images

Returns