Micropython integration for the emlearn Machine Learning library for microcontrollers.
The goal is to enable applications to run ML inference on the microcontroller, without having to touch any C code.
Proof of Concept
- Can run RandomForest/DecisionTree
- Module must be built manually (no pre-built releases)
- Has been tested with the
unixMicroPython port
Wishing the support was more production level? Vote in the issue tracker. Or contribute yourself!
Minimally you will need
- Python 3.10+ on host
- MicroPython running onto your device
If there is no ready-made build for your device/architecture, then you will need to build the .mpy module yourself. For that you need to install more dependencies, see MicroPython: Building native modules.
mpi install FIXME-make-release-on-github ESP32/RP2040
Build the .mpy native module
make -C eml_trees/ ARCH=x64 MPY_DIR=../../micropython
Install it on device
FIXME: document
Train a model with scikit-learn
pip install emlearn scikit-learn
python examples/xor_train.py
Copy model file to device
Copy the main script to device
examples/xor_device.py