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Replace the tmp-file duty-cycle handoff (and the FRIGATE_TMP env var nothing else reads) with a third multiprocessing.Value alongside avg_inference_speed and detection_start: ObjectDetectProcess creates it, AsyncDetectorRunner passes it to the detector, and the plugin publishes busy/wall of the blocking ModelInstance.run over a 2s window, mirroring how memryx receives its shared state. No filesystem path, no staleness window, no atomic rename, and stats/hardware.py no longer imports the plugin module to find the file. The producer also ticks the window while the queue is empty, so the duty cycle falls to 0 when the card idles instead of sticking at its last value. Name it what it is: host-side occupancy of the run call, including DMA and driver time, not an AIPU core counter (the runtime exposes no device-side one). The NPU entry now reads temperature from the board controller plus the detector-reported run duty cycle folded in where the detector processes are in reach.
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.
Description
NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
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