Nicolas Mowen 4d05bc25f4 Safely load config file for go2rtc (#11491)
* Safely load config file for go2rtc

* Add log for default config

* Cleanup
2024-05-22 18:10:55 -05:00
2024-05-20 07:37:56 -06:00
2024-05-18 10:36:13 -06:00
2024-05-22 08:51:59 -06:00
2024-05-18 10:36:13 -06:00
2024-05-22 10:06:40 -06:00
2024-02-02 06:23:14 -06:00
2021-02-25 07:01:59 -06:00
2023-07-01 08:18:33 -05:00
2023-05-29 05:31:17 -05:00
2024-05-20 07:37:56 -06:00
2023-11-18 08:04:43 -06:00
2023-01-06 07:03:16 -06:00
2020-07-26 12:07:47 -05:00
2024-01-31 06:23:54 -06:00
2023-11-18 08:04:43 -06:00
2023-11-18 08:04:43 -06:00
2023-01-13 07:20:25 -06:00

logo

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

Languages
TypeScript 49%
Python 48.7%
CSS 0.7%
Shell 0.6%
Dockerfile 0.4%
Other 0.4%