RIOT/tests/pkg/emlearn

Emlearn package test application

This application shows how to use a machine learning model with emlearn on RIOT in order to predict a value from a hand written digit image. The model is a Scikit-Learn random forest estimator trained on the MNIST dataset.

Expected output

The default digit to predict is a hand-written '6', so the application output is the following:

Predicted digit: 6

Use the Python scripts

The application comes with 3 Python scripts:

• generate_digit.py is used to generate a new digit file. This file is embedded in the firmware image and is used as input for the inference engine. Use the -i option to select a different digit. For example, the following command:

  $ ./generate_digit.py -i 1
  

  will generate a digit containing a '9'. The digit is displayed at the end of the script so one knows which digit is stored. Note that each time a new digit is generated, the firmware image must be rebuilt to include this new digit.
• train_model.py is used to train a new Scikit-Learn Random Forest estimator. The trained model is stored in the model binary file.

  $ ./train_model.py
  

  will just train the model.
• generate_model.py is used to generate the sonar.h header file from the model binary file. The script is called automatically by the build system when the model binary file is updated.