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- Replace the full-frame float64 clip-and-rescale in motion contrast enhancement with a 256-entry uint8 LUT applied via cv2.LUT. This removes several full-frame float64 temporaries per frame while producing a bit-identical result (verified), and merges the two np.percentile calls into one partition. - Convert the frame to BGR once per match_and_update instead of once per detection for autotracking histogram embeddings, by splitting get_histogram_from_bgr out of get_histogram. Output is unchanged. - Read ffmpeg frames directly into shared memory with stdout.readinto instead of read() + slice assignment, removing a full-frame allocation and copy per frame in the capture thread. - Hoist the invariant /proc/uptime read and the SC_CLK_TCK / SC_PAGE_SIZE sysconf lookups out of the per-process loop in get_cpu_stats.
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.