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Replace the content-based pixel-token pairing with the reviewer's scheme: the feeder registers every yielded frame on a pending deque (None for primer/keep-alive synthetics, the connection id for real frames) and collect() pops exactly one entry per result, so synthetics are dropped and real results always reach the connection that owns them - without reading the returned image at all. Validated on hardware first: the SDK InferenceStream returns results strictly in input order, one per yielded frame (200/200 frames in order, no drops or duplicates, synthetics interleaved included), and the per-frame image read (img.asarray + band decode) measured 0.58 ms against a 14.36 ms back-to-back round-trip, i.e. not the driver of the System Metrics latency. A desync guard raises (detector restarts) if the SDK ever emits a result with no registered frame, instead of silently misattributing everything after it (the P1 failure mode). The pixel-token path and its 200/200 FIFO probe stay in git history for rollback.
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.