Running a Keras machine learning model under macOS with coreML

Update (10 July 2019):

Code updated for Python 3

Requirements

A python virtual environment can be created from the requirements file.
macOS

Data

Example images are included in the img folder. Note that these are lower resolution than the original images changes the classification results in some cases.

Model creation

Run create_and_save_ml_model.py to load a pretrained ResNet50 model, run it on example images and save it in the mlmodel format

Swift command line application

Add the ResNet50.mlmodel to the Xcode library
Build the project in Xcode
See example results in blog
Find the compiled binary and run on an example image e.g. ./CmdSand /path/to/example.img