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* Base path via environment variable * Feedback refactored * Update docker/main/rootfs/usr/local/nginx/conf/nginx.conf Co-authored-by: Blake Blackshear <blake.blackshear@gmail.com> * Update docker/main/rootfs/usr/local/nginx/templates/base_path.gotmpl Co-authored-by: Blake Blackshear <blake.blackshear@gmail.com> * Revert api regex change * Lint fix * Fix https to http * Base path documentation * Base path contains leading slash * Frigate specific environment variable * Typo in comment Co-authored-by: Blake Blackshear <blake.blackshear@gmail.com> * Typo in comment Co-authored-by: Blake Blackshear <blake.blackshear@gmail.com> --------- Co-authored-by: Blake Blackshear <blake.blackshear@gmail.com>
Frigate - NVR With 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 Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
- 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.