Connecting Matlab to Tensorflow

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I am using an open-source Matlab toolbox for brain-computer interface (BCI). I want to send the brain imaging data over to Tensorflow for classification and get the results back to Matlab. Is there any way to pass data structures from Matlab to Tensorflow and get the results back into Matlab?

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In case someone lands here with a similar question, I'd like to suggest a Matlab package I am currently writing. It's called tensorflow.m and it's available on GitHub. There's no stable release yet, but simple functionality like importing a frozen graph and running an inference is already possible (see the examples) - this is all you'd need to classify the images in Matlab (only).

The advantage is that you don't need any expensive toolbox nor a Python/Tensorflow installation on your machine. The Python interface of Matlab also seems to be rather adventurous, while tensorflow.m is pure Matlab/C. I'd be glad if the package can be of use for someone looking for similar solutions; even more so, in case you extend/implement something and open a PR.

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So far the best way I found is to run your python module in matlab through matlab's now built-in mechanism for connecting to python:

I wrote my python script in a .py file and in there I imported tensorflow and used it in different functions. You can then return the results to matlab by calling

results = py.myModule.myFunction(arg1,arg2,...,argN)

More detailed instructions for calling user-defined python modules in matlab could be found in the following link:

http://www.mathworks.com/help/matlab/matlab_external/call-user-defined-custom-module.html