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title: Reachy Mini Face Detection
emoji: π€
colorFrom: blue
colorTo: indigo
sdk: static
pinned: false
tags:
- reachy_mini
- reachy_mini_python_app
---
# Reachy Mini β Face & Expression Detection
A small [Reachy Mini](https://huggingface.co/docs/reachy_mini) app that watches
the camera, detects a face and a simple facial expression, and replies with a
random expressive movement (head + antennas + body).
- **Happy** (a smile is detected) β quick nods, antenna wiggles, cheerful bobs.
- **Neutral** (a face, no smile) β curious tilts, gentle look-arounds.
- **No face** β a slow idle "breathing" motion.
The design keeps the detection and behaviour logic completely separate from the
robot SDK, so you can develop and test the whole thing on your laptop.
## Project layout
```
face_detection/
βββ detector.py # Face + expression detection (OpenCV Haar cascades)
βββ behavior.py # Expression -> random Movement (pure logic, no SDK)
βββ main.py # ReachyMiniApp glue + daemon entry point
βββ local_preview.py # Run on a laptop webcam, no robot required
index.html # Boilerplate for Hugging Face Space
style.css # Boilerplate for Hugging Face Space
tests/ # Unit tests for detector + behaviour
```
## Requirements
- Python 3.12+
- [`uv`](https://docs.astral.sh/uv/) for environments and packaging
## Quick start (local, no robot)
```bash
uv venv --python 3.12
uv pip install -e ".[dev]"
# Run the test suite (TDD)
uv run pytest
# Try it live on your webcam β prints the detected expression and the
# movement the robot *would* perform. Press 'q' to quit.
uv run face-detection-preview
```
## Running on the robot
See [PUBLISHING.md](PUBLISHING.md) for packaging, installing and publishing the
app to a Reachy Mini via Hugging Face Spaces.
## How it works
1. The daemon launches the app and hands it a connected `ReachyMini` instance.
2. Each loop iteration grabs a camera frame (`mini.media.get_frame()`).
3. `FaceDetector` finds the largest face and classifies its expression.
4. `MovementPlanner` picks a random movement for that expression.
5. The app sends it to the robot with `goto_target(...)`.
6. On stop, the daemon returns the robot to its default pose.
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