So the object detection extension is mostly focused on breaking down complex operations like anchor generation into functional steps that are compatible with th

So the object detection extension is mostly focused on breaking down complex operations like anchor generation into functional steps that are compatible with the base tensorflow metagraph definition. You can see these builders here: https://github.com/tensorflow/models/tree/master/research/object_detection/anchor_generators https://github.com/tensorflow/models/tree/master/research/ob... What that means is that when it comes to inference in a production environment, we only need our Tensorflow python package, as the metagraph is defined in terms that the base Tensorflow package can decypher. Although as I'm not an author of the object detection API, there is probably a more nuanced answer here.