I’m not sure which data augmentation libraries you are referring to, so would recommend to take a look at this Detection Tutorial using torchvision and these docs for albumentations, which are both using bounding boxes in their transformation.
Each torchvision.transforms provides the get_params method, which will return the parameters used for the current setup in the transformation.
In case you are still seeing missing functionalities, I’m sure the code owners would appreciate a pull request.