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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
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* Wait for config to load before evaluating route access Fix race condition where custom role users are temporarily denied access after login while config is still loading. Defer route rendering in DefaultAppView until config is available so the complete role list is known before ProtectedRoute evaluates permissions * Use batching for state classification generation * Ignore incorrect scoring images if they make it through the deletion * Delete unclassified images * mitigate tensorflow atexit crash by pre-importing tflite/tensorflow on main thread Pre-import Interpreter in embeddings maintainer and add defensive lazy imports in classification processors to avoid worker-thread tensorflow imports causing "can't register atexit after shutdown" * don't require old password for users with admin role when changing passwords * don't render actions menu if no options are available * Remove hwaccel arg as it is not used for encoding * change password button text --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> |
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| frigate | ||
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| benchmark.py | ||
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| README_CN.md | ||
| README.md | ||
| TRADEMARK.md | ||
Frigate NVR™ - Realtime Object Detection for IP Cameras
English
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 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.
