Running a Keras machine learning model under macOS with coreML

see blog post

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