CamWatch

Face and Car detector from video streams using Computer Vision with Face Recognition and Car Number Plate detection for integration with MQTT and Home Assistant

Features

• Records video on motion detection
• Detect faces and cars
• Train recognising faces from image files
• Detect and OCR Car Number plates
• Publish events and snapshots to MQTT
• integration with Home Assistant
• extensive user configurable parameters for tuning video sources to correct false positives

This project is still under-development.

Further updates and documentation improvement are coming soon.

Quick Start

Installation

• git clone https://github.com/joelee/camwatch.git
• cd camwatch
• Install uv: https://docs.astral.sh/uv/getting-started/installation/
• Install native build/runtime dependencies required by OpenCV, dlib, and Tesseract on your system
• uv venv --python 3.14.3
• uv sync
• requirements.txt is deprecated and only kept temporarily for compatibility
• Face recognition is optional on Python 3.14 for now; try uv sync --extra face only after installing native build tooling and validating dlib

Configuration

• cp config/camwatch-quick_start.yaml config/camwatch.yaml
• Edit and customise config/camwatch.yaml
• see camwatch-defaults.yaml for more settings

Start monitoring a video channel

• uv run python src/capture.py {channel_name}

Start face recognition training

• Set the path of your training data in the configuration: services.face_recognition.location
• Install the optional face stack first: uv sync --extra face
• Add the face photos under named sub-folders, e.g.:
  • john/
    • john_photo1.jpg
    • john_photo2.jpg
  • jill/
    • jill_photo1.jpg
    • jill_photo2.jpg
• Start trainer: uv run python src/face_trainer.py