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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
98c2fe00c1
* Add score fusion helpers for find_similar_objects chat tool * Add candidate query builder for find_similar_objects chat tool * register find_similar_objects chat tool definition * implement _execute_find_similar_objects chat tool dispatcher * Dispatch find_similar_objects in chat tool executor * Teach chat system prompt when to use find_similar_objects * Add i18n strings for find_similar_objects chat tool * Add frontend extractor for find_similar_objects tool response * Render anchor badge and similarity scores in chat results * formatting * filter similarity results in python, not sqlite-vec * extract pure chat helpers to chat_util module * Teach chat system prompt about attached_event marker * Add parseAttachedEvent and prependAttachment helpers * Add i18n strings for chat event attachments * Add ChatAttachmentChip component * Make chat thumbnails attach to composer on click * Render attachment chip in user chat bubbles * Add ChatQuickReplies pill row component * Add ChatPaperclipButton with event picker popover * Wire event attachments into chat composer and messages * add ability to stop streaming * tweak cursor to appear at the end of the same line of the streaming response * use abort signal * add tooltip * display label and camera on attachment chip |
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| frigate | ||
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| CONTRIBUTING.md | ||
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| README_CN.md | ||
| README.md | ||
| TRADEMARK.md | ||
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.