Tensorflow: restoring a graph and model then running evaluation on a single image

Question

I think it would be immensely helpful to the Tensorflow community if there was a well-documented solution to the crucial task of testing a single new image against the model

Answer 1

I don't have working code for you I'm afraid, but here's how we often tackle this problem in production:

• Save out the GraphDef to disk, using something like write_graph.

• Use freeze_graph to load the GraphDef and checkpoints, and save out a GraphDef with the Variables converted into Constants.

• Load the GraphDef in something like label_image or classify_image.

For your example this is overkill, but I would at least suggest serializing the graph in the original example as a GraphDef, and then loading it in your script (so you don't have to duplicate the code generating the graph). With the same graph created, you should be able to populate it from a SaverDef, and the freeze_graph script may help as an example.