Define features of 0.1

[DrAnaximandre]

We should agree on some features to put in the frozen version.
I thought about the following :

• refactor all the code in the same manner Refactor prepare_data.py #6
• remake readme Update the readme #5 (@tfunk)
• separate the models from the sources Separate the models from the sources #8
• begin CI and unit tests (tbd, it might be really overkill)
• improve oob experience for those who want to play with the models without wanting to mess with too much data wrangling Make a CLI ? #11
• write a documentation Write a documentation #9 (readthedoc?) (@tfunk) (@DrAnaximandre)
• Make clobber specific to specific processing steps Make clobber specific #10 (@tfunk)
• find a new name

Feel free to add issues and ideas or tell if some feature is not essential.

[tfunck]

I agree with all of the above. I also started adding a 'verbose' option will 4 different levels:
0 -- run silently
1 -- basic: basic info about what the program is doing (e.g., load data, train model, save model, etc.)
2 -- detailed: detailed information about what's going (e.g., which subject is being loaded/saved to numpy, which image is being predicted and saved, etc.)
3 -- debug: print information that would be of no interest to anyone except developpers (e.g., size of numpy arrays, etc.)

[tfunck]

I can take care of the readme, documentation and clobber

[tfunck]

Also we may want to change the name of the project because the code can now do much more than just learn brain masks from PET images. The user can define the string that the code uses to find the inputs (by default PET) and labels (by default brain masks). So one could try to set the inputs to T1 images and the outputs to FDG PET, or T1 images to brain masks, or T1 images to any other labeled image.

This makes the code super useful to anyone in brain imaging who wants to do deep learning but doesn't want to deal with the hassles of data management.

So the point of giving the project a new name would be to convey the idea that this is a sort of all purpose code for doing deep learning with keras on brain images.