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Getting started

There are three ways into this project, and they do not depend on each other. Pick the one that matches what you have in front of you.

  • Only a laptop

    Install the toolkit and run the live dashboard against your webcam. The detection pipeline, the risk logic and the tuning UI are all real; only the board is missing.

    Install the toolkit

  • A board on the desk

    Build, flash and monitor the firmware with ./plxy.sh dev, then join the board's access point to see what it sees.

    Quickstart

  • A box of parts

    Start at the hardware tutorial: four components, seven wires, and a test after every stage.

    Hardware setup tutorial

What you need

For You need
Desktop toolkit, live dashboard Python 3.10+ and a webcam
Training and export the above, plus a dataset (see Datasets)
.espdl quantization the above, plus esp-ppq
Firmware ESP-IDF 5.x on Windows, macOS or Linux, and the board
Documentation Python 3.10+ only — see the documentation pipeline

The 60-second version

git clone https://github.com/SengPhirum/PLXY_DrowsyGuard.git
cd PLXY_DrowsyGuard

python -m venv .venv
source .venv/bin/activate          # Windows: .venv\Scripts\Activate.ps1
pip install -e ".[live]"

drowsyguard doctor                 # what is installed, what is missing
drowsyguard fetch-models           # YuNet detector + eye-state model
python -m drowsyguard.cli live     # then open http://127.0.0.1:8000

No checkpoint is needed: eye mode is the default and uses the downloaded eye-state model.