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RIOT/tests/pkg/emlearn/README.md

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## 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](https://scikit-learn.org) 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.