DetectionEngine.box_shapes

DetectionEngine.box_shapes(model_name=None, split='train')

The cloud of box shapes in a split, with the anchors in use beside it.

Everything a picture of the anchor fit needs, in one call and in one set of coordinates: both are fractions of the model’s input, computed by the same function that fitted the anchors. The alternative - widths and heights from one place and anchors from another - is how a plot comes to show boxes in different places from where the anchors were fitted, which looks like a bad fit and is a bug.

Worth drawing for a split the anchors were not fitted on, for the same reason as anchor_coverage: it is the only way to see a class the anchors have nothing near.

Parameters

Name	Type	Description	Default
model_name	str | None	Which detector. Defaults to the first.	None
split	str	Which split’s boxes to return.	'train'

Returns

Name	Type	Description
	dict[str, Any]	Every box’s width and height, normalised by the letterboxed input rather
	dict[str, Any]	than by the source image - which is the convention the anchors use, and getting
	dict[str, Any]	it wrong is how a coverage figure of 0.67 was quoted for two years against a
	dict[str, Any]	true 0.65.