discopat.nn_training.evaluation.base

Functions

compute_ap(matching_dict, threshold)

Compute the Average Precision (AP) for a given localization threshold.

evaluate(model, data_loader, ...)

Evaluate a model on a data loader.
discopat.nn_training.evaluation.base.compute_ap(matching_dict, threshold)[source]

Compute the Average Precision (AP) for a given localization threshold.

Parameters:

  • matching_dict (dict[str, dict[str, array]]) –

    dictionary in the form: image_id: {

    ”matching_matrix”: array of shape (N_preds, N_gts), “scores”: array of shape (N_preds,)

    }

  • threshold (float) – localization threshold,

Returns:

The AP.

Return type:

float

Note

The predictions and scores should already be sorted by descending score.

discopat.nn_training.evaluation.base.evaluate(model, data_loader, localization_criterion, device)[source]

Evaluate a model on a data loader.

Parameters:

  • model (NeuralNet) – the neural network to be evaluated,

  • data_loader (DataLoader) – the evaluation dataloader,

  • localization_criterion (str) – metric used for GT-pred matching,

  • device (ComputingDevice) – computing device on which the model is stored.

Returns:

AP50, AP[50:95:05].

Return type:

A dict containing the name and values of the following metrics