Hi @Bhack, thanks a lot for your reply!
I have been using the tensorflow Object Detection API lately.
There are a few things that I don’t particularly like (absence of Callbacks, for example), and some bugs that arise when trying more custom usages (see for example the bug issue I opened last week: Object detection API - error when finetuning centernet and faster_rcnn models: RuntimeError: Groundtruth tensor weights has not been provided · Issue #10295 · tensorflow/models (github.com) 2). I also find the code for the models, meta architectures, training, etc. quite obscure (I am not a TF expert), so I was looking for an alternative approach.
I also noticed that the detection folder on the official repo is being deprecated as you are migrating it, and that’s why I was curious to know if there is an alternative approach to transfer learning in object detection that could be used in a similar way to the TF HUB transfer learning for image classification (that I linked in the OP).
If that’s not the case, I guess I’ll have to wait for the official release of object detection