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* fix autotracking tracker selection and crop before histogram conversion - Rebuild the norfair trackers when an onvif save changes autotracking enabled_in_config or the PTZ-tracked labels. The trackers were only built at startup, so disabling autotracking or removing person from its track list in the UI made get_tracker pick a tracker that didn't exist, and the KeyError killed the camera process until restart. Saves that leave the selection alone, and runtime MQTT toggles, don't touch tracking. - get_tracker now returns the default tracker that match_and_update actually feeds. On autotracking cameras it returned the static default for labels without their own tracker, so register missed the norfair object and lost the pre-initialization score history, and deregister pruned the wrong tracker. - get_histogram crops the box out of each I420 plane before converting to BGR instead of converting the whole frame. It runs per detection per frame on autotracking cameras and now costs about 0.2 ms at any resolution, down from 1 ms at 1080p and 5 ms at 4K. * don't rebuild trackers for track list edits while autotracking is disabled
Frigate NVR™ - Realtime Object Detection for IP Cameras
[English] | 简体中文
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 is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported object detectors.
- 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.
License
This project is licensed under the MIT License.
- Code: The source code, configuration files, and documentation in this repository are available under the MIT License. You are free to use, modify, and distribute the code as long as you include the original copyright notice.
- Trademarks: The "Frigate" name, the "Frigate NVR" brand, and the Frigate logo are trademarks of Frigate, Inc. and are not covered by the MIT License.
Please see our Trademark Policy for details on acceptable use of our brand assets.
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.
Copyright © 2026 Frigate, Inc.