mednet.engine.detect.predictor

Prediction engine for object detection tasks.

Functions

run(model, datamodule, device_manager)

Run inference on input data, output predictions.

mednet.engine.detect.predictor.run(model, datamodule, device_manager)[source]

Run inference on input data, output predictions.

Parameters:
  • model (LightningModule) – Neural network model (e.g. faster-rcnn).

  • datamodule (LightningDataModule) – The lightning DataModule to run predictions on.

  • device_manager (DeviceManager) – An internal device representation, to be used for training and validation. This representation can be converted into a pytorch device or a lightning accelerator setup.

Return type:

Union[list[tuple[str, Sequence[tuple[Sequence[int], int]], Sequence[tuple[Sequence[int | float], int, float]]]], list[list[tuple[str, Sequence[tuple[Sequence[int], int]], Sequence[tuple[Sequence[int | float], int, float]]]]], Mapping[str, Sequence[tuple[str, Sequence[tuple[Sequence[int], int]], Sequence[tuple[Sequence[int | float], int, float]]]]], None]

Returns:

Depending on the return type of the DataModule’s predict_dataloader() method:

Raises:

TypeError – If the DataModule’s predict_dataloader() method does not return any of the types described above.