mednet.engine.classify.saliency.interpretability¶
Engine and functions for human interpretability analysis.
Functions
|
Compute the proportional energy and average saliency focus for a given target label in a DataModule. |
- mednet.engine.classify.saliency.interpretability.run(input_folder, target_label, datamodule, only_dataset)[source]¶
Compute the proportional energy and average saliency focus for a given target label in a DataModule.
- Parameters:
input_folder (
Path
) – Directory in which the saliency maps are stored for a specific visualization type.target_label (
int
) – The label to target for evaluating interpretability metrics. Samples contining any other label are ignored.datamodule (
LightningDataModule
) – The lightning DataModule to iterate on.only_dataset (
str
|None
) – If set, will only run this code for the named dataset on the provided datamodule, skipping any other datasets.
- Return type:
- Returns:
A dictionary where keys are dataset names in the provided DataModule, and values are lists containing sample information alongside metrics calculated:
Sample name (str)
Sample target class (int)
Proportional energy (float)
Average saliency focus (float)