Using TensorFlow object detection API models at prediction

Question

I have used the TensorFlow object detection API to train the SSD Inception model from scratch. The evaluation script shows that the model has learned something and now I want to use the model.

I have looked at the object detection ipynb that can feed single images to a trained model. However, this is for SSD with MobileNet. I have used the following line (after loading the meta graph) to print the tensor names of the TensorFlow model I trained.

print([str(op.name) for op in tf.get_default_graph().get_operations()] )

But it does not contain the same input or output tensor names as in the ipynb. I have also searched through the code, but many functions point toward each other and it is difficult to find what I am looking for.

How can I find the tensor names I need? Or is there another method I do not know about?

gdelab · Accepted Answer · 2017-10-18 12:18:13Z

2

To use the graph, you need to freeze/export it, using this provided script. The resulting .pb file will contain the nodes you need. I don't know why it's organized like that, but it is.

answered Oct 18, 2017 at 12:18

gdelab

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