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* start audio transcription post processor when enabled on any camera * Fetch embed key whenever an error occurs in case the llama server was restarted * mypy * add tooltips for colored dots in settings menu * add ability to reorder cameras from management pane * add ability to reorder birdseye * add reordering save text to camera management view * Include NPU in latency performance hint * Implement turbo for NPU on object detection * hide order fields * drop auto-derived field paths from camera value when unset globally * use correct field type for export hwaccel args * add debug replay to detail actions menu * clarify debug replay in docs * guard get_current_frame_time against missing camera state * Implement debug reply from export * Refactor debug replay to use sources for dynamic playback * Mypy * fix debug export replay source timestamp handling * skip replay cameras in stats immediately * broadcast debug replay state over ws and buffer pre-OPEN sends - push debug replay session state over the job_state ws topic so the status bar reacts instantly to start/stop without polling - fix child-effect-before-parent-effect race in WsProvider that silently dropped initial snapshot requests on cold load * fix debug replay test hang --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.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.