mednet.engine.segment.dumper

Functions

run(datamodule, output_folder)

Dump annotations from input datamodule.
mednet.engine.segment.dumper.run(datamodule, output_folder)[source]

Dump annotations from input datamodule.

Parameters:

  • datamodule (LightningDataModule) – The lightning DataModule to extract annotations from.

  • output_folder (Path) – Folder where to store HDF5 representations of annotations.

Return type:

dict[str, list[tuple[str, str]]] | list[list[tuple[str, str]]] | list[tuple[str, str]] | None

Returns:

A JSON-able representation of sample data stored at output_folder. For every split (dataloader), a list of samples in the form [sample-name, hdf5-path] is returned. In the cases where the predict_dataloader() returns a single loader, we then return a list. A dictionary is returned in case predict_dataloader() also returns a dictionary.

Raises:

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