mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-09-25 22:38:58 +03:00
Josh HawkinsandGitHub
9664d9ceae
* Notice and status bar improvements Status bar problems added in the same pass got the same `Date.now()` id and overwrote each other, so usually only one showed. Messages now fall back to their text as the id. The desktop status bar shows the most severe message with a count of the rest that opens a popover listing all of them, and the mobile drawer stacks them vertically instead of placing them side by side. Dismissing a notice hid it for good, so a detector that restarted again after a dismissal was never shown. Dismiss is replaced by acknowledge, which hides a notice until it happens again, and mute, which hides it permanently. Kinds that never repeat (config and stream checks, the update notice) can only be muted. `reopen_at_count` is removed since acknowledge covers the failed login case. * move camera CPU warnings to notices High ffmpeg and detect CPU warnings sat in the status bar with no way to dismiss them. They're now `ffmpeg_high_cpu` and `detect_high_cpu` notices, raised per episode by the same tracker as skipped detections. Also stop failed login attempts held from before an acknowledgement from reopening the notice. * fix mypy and handle missing cpu stats in notices
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.