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[NiftyNet] Save models in TensorFlow SavedModel format for broader API utilization

The user wants to use NiftyNet's trained models in non-Python environments (e.g., C++). Currently, models are saved as TensorFlow checkpoints, which are hard to load via C++ API. Request is to save them as TensorFlow SavedModel format for easier cross-platform utilization.

Original Source

@@tobon | 0 pts | 3/1/2019

First of all, thank you for all your great work on NiftyNet! I would love to use some of the trained models in the model zoo in a non-python environment (cross-platform C++ application in my case). In trying to reverse engineer the model structure, I noticed that the models seem to be stored as tensorflow checkpoints. My understanding is that I cannot load these back directly through C++ API, and I am wondering if these could instead be saved as a tensorflow "[SavedModel](https://www.tensorflow.org/guide/saved_model)" instead. I think this could really open up the utilization of these trained models in other architectures, but please let me know if there is another way that I am missing here. Thanks!

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