Inference using large amount of GPU memory about fcn.tensorflow

[shekkizh]

@NeuroRoboticTech Thanks for the feedback. I'm glad that you find the code useful.
As far as I know tensorflow allocates all gpu memory when it starts irrespective of how much it uses. This was the case in older version 0.11 and such - not sure if this was changed. This would explain why you see all memory being used in case of titan X.
The model by itself is really big with many variables and at inference each "convolution layer" requires memory in the order of the size of image. One way you can try to fit in a smaller GPU is by setting batch size to 1 or working with smaller images/dividing a larger image into multiple smaller regions and performing inference.
Hope this is helpful.