NVR with realtime local object detection for IP cameras
Go to file
Nicolas Mowen 97f5ba0145
Update go2rtc and implement stream probe to only show 2 way talk when supported (#11407)
* Support two way talk validation

* Fix handling

* Use go2rtc stream info to infer audio output

* Update go2rtc

* Update bundle policy

* Formatting
2024-05-17 07:30:22 -06:00
.devcontainer Remove deprecated RTMP port 1935 (#9137) 2024-01-31 12:56:11 +00:00
.github
.vscode
config
docker Update go2rtc and implement stream probe to only show 2 way talk when supported (#11407) 2024-05-17 07:30:22 -06:00
docs Update go2rtc and implement stream probe to only show 2 way talk when supported (#11407) 2024-05-17 07:30:22 -06:00
frigate Update go2rtc and implement stream probe to only show 2 way talk when supported (#11407) 2024-05-17 07:30:22 -06:00
migrations Save exports to database (#11040) 2024-04-19 17:11:41 -05:00
web Update go2rtc and implement stream probe to only show 2 way talk when supported (#11407) 2024-05-17 07:30:22 -06:00
.dockerignore
.gitignore Small autotracking changes (#9571) 2024-02-02 06:23:14 -06:00
.pylintrc use fstr log style 2021-02-25 07:01:59 -06:00
audio-labelmap.txt
benchmark_motion.py
benchmark.py
CODEOWNERS AMD GPU support with the rocm detector and YOLOv8 pretrained model download (#9762) 2024-02-10 06:41:46 -06:00
docker-compose.yml
labelmap.txt
LICENSE
Makefile increment version 2024-01-31 06:23:54 -06:00
netlify.toml
process_clip.py
pyproject.toml
README.md

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