DetectionEngine.evaluate_classes

DetectionEngine.evaluate_classes(model_name=None, split='validation')

One row per class instead of one row per model.

The row that matters on an unbalanced dataset, which is most of them: BCCD has 4155 red cells against 372 white and 361 platelets, so a single number is a number about red cells.

Parameters

Name	Type	Description	Default
model_name	str | None	Which detector. Defaults to the first.	None
split	str	Which data to score on.	'validation'

Returns

Name	Type	Description
	list[dict[str, Any]]	One row per class: average precision at IoU 0.5, the mean overlap of the boxes
	list[dict[str, Any]]	that matched, how many truth boxes there were, and precision and recall at the
	list[dict[str, Any]]	model’s operating_point. The row that matters on unbalanced data, which is
	list[dict[str, Any]]	most detection data.