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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
c136e5e8bd
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* Remove source_type from API * Don't require state classification models to select all classes * Specifically validate provided end_time for manual events * Remove yolov9 specification for warning * Remove warning for coral * clarify zone name tip * clarify replace rules in lpr docs * remove periods * Add explanation for review report * adjust HLS gap controller params defaults to false, should help to recover from hangs and stalling in tracking details videos on chrome * only redirect to login page once on 401 attempt to fix ios pwa safari redirect storm * Use contextual information from other cameras to inform report summary * Formatting and prompt improvements for review summary report * More improvements to prompt * Remove examples * Don't show admin action buttons on export card * fix redirect race condition Coordinate 401 redirect logic between ApiProvider and ProtectedRoute using a shared flag to prevent multiple simultaneous redirects that caused UI flashing. Ensure both auth error paths check and set the redirect flag before navigating to login, eliminating race conditions where both mechanisms could trigger at once --------- Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.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 LLC 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 © 2025 Frigate LLC.