Are bounding box/bbox definitions consistent across datasets?

Do all Datasets checked into the Tensorflow Datasets definitions follow a common specification for Bounding Boxes (bbox)?

The Stanford Dogs dataset uses a range of (0.0, 0.0)->(1.0, 1.0). Do all of them follow this pattern? If so, where is this documented?

Thank you,

Lance Norskog

I don’t know if they are all in this range:

TFDS CoCo it seems the same:

But it seems preferred not mandatory:

I don’t think that’s the case for all datasets.

I couldn’t at least find this anywhere

Yeah, I will assume it is a free-for-all. Thanks!

I hope that many will respect this recommendation:

Prefer more specific type instead of tfds.features.Tensor

When possible, prefer the more specific types tfds.features.ClassLabel, tfds.features.BBoxFeatures,… instead of the generic tfds.features.Tensor.
Rationale: In addition of being more semantically correct, specific features provides additional metadata to users and are detected by tools.