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* Add sub label to model and set / delete funs * Add migrations for sub label * Tweaks to API and model * Show sublabel if available * Cleanups * Update docs * Show person in UI title * Fix typo and don't fail on no json * Transfer sub labels for in progress events * Remove sublabel reset * Remove person only check * Make default null * Update docs and formatting * Make default null * Make nullable in migration * Undo null * Update model to accept null * Update migration to accept null * Don't set to default values * Remove redundant defaults and update http logic * Only need a single route * Enforce 20 character limit in http * Update docs to mention 20 character limit * Cleanup * Separate insert and update to make sure updated values are retained when event ends * Use insert instead of replace * Remove redundant if and have should_update_db include clip or snapshot requirement.
Frigate - NVR With Realtime Object Detection for IP Cameras
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 Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS 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 RTMP to reduce the number of connections to your camera
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
Integration into Home Assistant
Also comes with a builtin UI:
