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Hi, zeryx: How does this work in production? I'm especially curious about the stuff that isn't part of the TensorFlow graph like anchor generation and post-pro
by Q6T46nT668w6i3m 9y ago
Hi, zeryx:
How does this work in production? I'm especially curious about the stuff that isn't part of the TensorFlow graph like anchor generation and post-processing. Is your service running the graph directly or does it run some Python script that executes the graph?
- zeryx 9y agoSo 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.