object_detection.DataLoader

class maite.protocols.object_detection.DataLoader(*args, **kwargs)

A dataloader protocol for the object detection AI problem providing batch-level data access.

Implementers must provide an iterable object (returning an iterator via the __iter__ method) that yields tuples containing batches of data. These tuples contain types Sequence [ArrayLike] (elements of shape (C, H, W)), Sequence [ObjectDetectionTarget], and Sequence [DatumMetadata], which correspond to model input batch, model target batch, and a datum metadata batch.

Note: Unlike Dataset, this protocol does not require indexing support, only iterating.

Methods

__iter__ -> Iterator[tuple[Sequence[ArrayLike], Sequence[ObjectDetectionTarget], Sequence[DatumMetadata]]]

Return an iterator over batches of data, where each batch contains a tuple of of model input batch (as Sequence [ArrayLike]), model target batch (as Sequence [ObjectDetectionTarget]), and batched datum-level metadata (as Sequence[DatumMetadata]]), respectively.