Core ML – Preparing the environment
Hello again! In preparation to training a model to be converted by Core ML to be used in an application, I would like to make sure we have a suitable environment to work on.
One of the first things that came to my attention looking at the Python 3 is now finally supported! In the meantime you can see the countdown to Python 2’s retirement here, and thanks Python 2 for the many years of service…
coreml module is the fact that it only supports Python 2! Yes, you read correctly, you will have to make sure you use Python 2.7 if you want to make this work. As you probably know, Python 2 will be retired in 2020, so I hope that Apple is considering in their development cycles.
Anyway, if you are a Python
2 3 user, then you are good to go. If on the other hand you have moved with the times you may need to make appropriate installations. I am using Anaconda (you may use your favourite distro) and I will be creating a conda environment (I’m calling it
coreml) with Python 2.7 and some of the libraries I will be using:
> conda create --name coreml python=3 ipython jupyter scikit-learn > conda activate coreml (coreml) > pip install coremltools
I am sure there may be other modules that will be needed, and I will make appropriate installations (and additions to this post) as that becomes clearer.
You can get a look at Apple’s coremltools github repo here.
ADDITIONS: As I mentioned, there may have been other modules that needed installing in the new environment here is a list: