info on input shape and problem domain from models?

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Roberta Rocca

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Nov 5, 2020, 9:46:56 AM11/5/20
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I am using the latest version of tensorflow hub, and wondering how one gets information on a model's expected input shape, as well as on what type of collection the model belongs to. For example, is there a way to get info on the expected image shape after having loaded a model in Python this way?

model = hub.load("https://tfhub.dev/tensorflow/faster_rcnn/inception_resnet_v2_640x640/1")

or this way?

model = hub.KerasLayer("https://tfhub.dev/tensorflow/faster_rcnn/inception_resnet_v2_640x640/1")

It seems that in neither case the model object stores info on what the expected shape is - both in terms of image height/width, and batch size. On the other hand, this info can be found through load_module_spec for older TF models, as far as I understand. Any insights?

One more question: is there a way to get information programmatically on which "problem domain" the model belongs to? It can be looked up on https://tfhub.dev/, but what if one needed to access that info from model object itself or via tensorflow_hub functions?

Thanks!

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