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Preprocess reused three fresh arrays per frame (resize output, quantised copy, strided channel flip at write time) and refilled the whole padded input buffer. Now resize writes into a scratch with cv2 dst=, the BGR->RGB swap is a cvtColor into scratch (no strided copy), the int8 quantise runs with out=, and only the border strips the content rect does not cover get memset. Measured 39% faster on the 704x576 -> 640x640 path. Dequantise allocated two fp32 temporaries per head (astype then the dequant expression) before the transpose copy. copyto now casts int8->fp32 while transposing straight into a reused fp32 feed buffer, and the zp/scale math runs in place. Measured 78% faster for the YOLOX-S head set, outputs bit-identical (int8->fp32 cast is lossless). Argmax+gather replaces max+argmax (one class-axis reduction instead of two), and the postprocess session pins intra_op_num_threads=1: one frame is in flight through the decoder, extra ORT threads only add context switches.
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.