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* Fix Birdseye rapid camera switching in single-camera view (#10845) Add a configurable min_camera_hold (default 5s) to prevent Birdseye from rapidly flipping between cameras when multiple have simultaneous activity. Also fix the max_cameras cooldown which was bypassed whenever more cameras were active than the configured limit. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Remove min_camera_hold config, use hardcoded CAMERA_HOLD_SECONDS constant Replace the configurable min_camera_hold field with a module-level CAMERA_HOLD_SECONDS = 5 constant to keep behavior simple and avoid adding config complexity. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Fix max_cameras hold blocking count changes, add count-increase test The >= guard could prevent cameras from appearing when the displayed count was below max_cameras. Now the hold only applies when the limited count matches the currently displayed count, so count changes are always immediate. Adds a dedicated test for this case. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Apply reviewer feedback: simplify max_cameras hold, remove single-camera hold - Use hawkeye217's suggested condition for max_cameras cooldown: only hold when currently showing exactly max_cameras and there are at least max_cameras active - Remove single-camera hold entirely — without max_cameras set, the hold only triggers when one camera expires as another activates, keeping the inactive camera visible unnecessarily - Remove last_layout_change_time (no longer used) - Remove single-camera hold tests (feature removed) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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.