mednet.engine.detect.evaluator

Defines functionality for the evaluation of object detection predictions.

Functions

make_plots(results[, iou_threshold])

Create plots for all curves and score distributions in results.

make_table(data, fmt)

Tabulate summaries from multiple splits.

run(predictions, binning[, iou_threshold])

Run inference and calculates measures for multilabel object detection.

mednet.engine.detect.evaluator.run(predictions, binning, iou_threshold=None)[source]

Run inference and calculates measures for multilabel object detection.

Parameters:
Return type:

dict[str, Any]

Returns:

A dictionary containing the performance summary on the specified threshold, general performance curves (under the key curves), and score histograms (under the key score-histograms).

mednet.engine.detect.evaluator.make_table(data, fmt)[source]

Tabulate summaries from multiple splits.

This function can properly tabulate the various summaries produced for all the splits in a prediction database.

Parameters:
Returns:

A string containing the tabulated information.

Return type:

str

mednet.engine.detect.evaluator.make_plots(results, iou_threshold=None)[source]

Create plots for all curves and score distributions in results.

Parameters:
  • results (dict[str, dict[str, Any]]) – Evaluation data as returned by run().

  • iou_threshold (float | None) – IOU threshold by which we consider successful object detection. If set, it is shown on plots.

Return type:

list

Returns:

A list of figures to record to file