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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
36c61a3607
The record watchdog treats a stale maintainer heartbeat as a dead recorder. But the heartbeat is published by the recording maintainer, so whenever the maintainer lags (e.g. "Unable to keep up with recording segments in cache", #9661) every camera looks stale at once and all record processes restart together - while recording was actually healthy. The restart churn then produces more, shorter segments, making the maintainer fall further behind. Before restarting on staleness, check the camera's newest cache segment on disk: if a segment is fresher than the staleness threshold, the recorder is demonstrably writing - log a warning, adopt the disk mtime as the heartbeat, and skip the restart. The invalid-segment path is untouched. Validated on a 26-camera production deployment (0.17.1 backport of this change): synchronized mass restarts went from 52/hour to zero, with heartbeat-stale events still occurring ~2/hour but now correctly identified as maintainer lag instead of recording failure. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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Frigate NVR™ - Realtime Object Detection for IP Cameras
EnglishA 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.