Image list fixes: Bounding boxes image missmatch, Unknown annotation category

[PaulHax]

• When selecting a set of images, some of which share the same image shape, the bouding boxes could be on the wrong image.
• The horse drawn trolly thing in the sample dataset has a category ID of 0, which caused a JS error. Not sure about root cause...

[vicentebolea]

Thanks for the PR, why do we need to change the return type of the object_detector to a [path:{model pred}] as opposed to the current array of model predictions. The model keeps the order of the array that we pass as input.

[PaulHax]

object_detector.eval still returns an array of predictions. The "image group by size/shape" code was reording the order we pass images to self.pipeline. Then the output predictions order did not match the input paths order which made problems here: https://github.com/Kitware/nrtk-explorer/blob/main/src/nrtk_explorer/app/transforms.py#L160-L162

[vicentebolea]

object_detector.eval still returns an array of predictions. The "image group by size/shape" code was reording the order we pass images to self.pipeline. Then the output predictions order did not match the input paths order which made problems here:

You are right, we did not test for over the batching default size... Good catch here :)

[vicentebolea]

Ill come back to this PR later, I think that we can further refactor.

[vicentebolea]

@PaulHax I pushed a commit to this PR that adds your changes to object_dectector but also changes the output. Let me know what do you think

[PaulHax]

+1 Works good!