| .cspell | ||
| .devcontainer | ||
| .github | ||
| .vscode | ||
| config | ||
| docker | ||
| docs | ||
| frigate | ||
| migrations | ||
| notebooks | ||
| web | ||
| .dockerignore | ||
| .gitignore | ||
| .pylintrc | ||
| audio-labelmap.txt | ||
| benchmark_motion.py | ||
| benchmark.py | ||
| CODEOWNERS | ||
| COMPLETE_CONFIG_SCHEMA.json | ||
| CONFIG_SCHEMA_SUMMARY.md | ||
| cspell.json | ||
| docker-compose.yml | ||
| labelmap.txt | ||
| LICENSE | ||
| Makefile | ||
| netlify.toml | ||
| package-lock.json | ||
| process_clip.py | ||
| pyproject.toml | ||
| README_CN.md | ||
| README.md | ||
| verify_gui_completeness.py | ||
🎨 Frigate with GUI Configuration Editor
Fork of blakeblackshear/frigate featuring a comprehensive GUI configuration editor - No more YAML nightmares!
✨ What's Different in This Fork?
This fork adds a complete GUI-based configuration editor that makes Frigate accessible to everyone:
🚀 New Feature: GUI Configuration Editor
No YAML knowledge required! Configure everything through beautiful forms:
- ✅ 100% Coverage: All 500+ configuration fields accessible
- ✅ 17+ Organized Sections: Cameras, Detectors, Objects, Recording, Motion, MQTT, Audio, Face Recognition, LPR, and more
- ✅ Smart Validation: Real-time error checking with helpful messages
- ✅ Tooltips Everywhere: Every field has descriptions and examples
- ✅ YAML Toggle: Switch between GUI and YAML modes anytime
- ✅ Schema-Driven: Automatically adapts when new Frigate features are added
📖 Read the GUI Configuration Guide
About Frigate
English
A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
Use of a GPU or AI accelerator such as a Google Coral or Hailo is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead.
- Tight integration with Home Assistant via a custom component
- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
- Uses a very low overhead motion detection to determine where to run object detection
- Object detection with TensorFlow runs in separate processes for maximum FPS
- Communicates over MQTT for easy integration into other systems
- Records video with retention settings based on detected objects
- 24/7 recording
- Re-streaming via RTSP to reduce the number of connections to your camera
- WebRTC & MSE support for low-latency live view
Documentation
View the documentation at https://docs.frigate.video
Donations
If you would like to make a donation to support development, please use Github Sponsors.
Screenshots
Live dashboard
Streamlined review workflow
Multi-camera scrubbing
Built-in mask and zone editor
Translations
We use Weblate to support language translations. Contributions are always welcome.
