Dataloader for COCO json and corresponding imagery

This should load annotations as arrays converted to tensors in a format that can be accepted by the oneformer transformers model. see https://github.com/developmentseed/slickformer/blob/main/notebooks/evaluation_mrcnn.ipynb for an initial example of this where the annotations are loaded as numpy arrays. For speed, I think we can test out the encode method of the image processor and encode these masks as semantic segmentation maps. Later we can properly treat these instance segments with a custom processor.

https://huggingface.co/docs/transformers/model_doc/oneformer#transformers.OneFormerImageProcessor.encode_inputs

cc @srmsoumya