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NVR with realtime local object detection for IP cameras
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make go2rtc always rebuild config at startup (#8664) 
* make go2rtc always rebuild config at startup

/dev/shm can be left mounted (in fact im pretty sure it's always left mounted) on the docker host after shutting down the frigate container.
If we only check that the file doesn't exist, stale data gets re-read every startup 
This will make troubleshooting a nightmare for the average user.

I had given up troubleshooting go2rtc several times because of this.

* generate config after supervisor data is loaded

* Fix fi

* fix fi

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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2023-11-19 07:08:42 -06:00
.devcontainer Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
.github Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
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docker make go2rtc always rebuild config at startup (#8664) 2023-11-19 07:08:42 -06:00
docs Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
frigate Set max value for pre_capture (#8656) 2023-11-18 15:37:06 -06:00
migrations Performance increase with lots of recordings (#8525) 2023-11-07 23:18:26 +00:00
web update web deps (#8663) 2023-11-19 05:24:52 -06:00
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docker-compose.yml Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
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netlify.toml Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
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pyproject.toml Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
README.md

README.md

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Frigate - NVR With Realtime Object Detection for IP Cameras

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.

Screenshots

Integration into Home Assistant

Also comes with a builtin UI:

Events