Mirrors/blakeblackshear.frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2025-02-18 00:16:41 +01:00
Code Issues Projects Releases Wiki Activity
NVR with realtime local object detection for IP cameras
1,986 Commits 48 Branches 134 Tags 252 MiB
TypeScript 49.3%
Python 46.6%
CSS 1.1%
C++ 0.8%
Shell 0.7%
Other 1.3%
9f3ac19e05
Go to file
Nicolas Mowen 9f3ac19e05
Limit max player height (#7974)
2023-09-28 18:01:23 -05:00
.devcontainer Check ffmpeg version instead of checking for presence of BTBN_PATH (#7023) 2023-07-06 07:35:26 -05:00
.github
.vscode
config Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
docker
docs Update api.md (#7971) 2023-09-28 18:00:32 -05:00
frigate thread lock for move queues (#7973) 2023-09-28 18:01:05 -05:00
migrations Save average dBFS and retain segment with dBFS in motion mode (#7158) 2023-07-14 19:05:14 -05:00
web Limit max player height (#7974) 2023-09-28 18:01:23 -05:00
.dockerignore
.gitignore
.pylintrc
audio-labelmap.txt Audio events (#6848) 2023-07-01 08:18:33 -05:00
benchmark_motion.py use a different method for blur and contrast to reduce CPU (#6940) 2023-06-30 07:27:31 -05:00
benchmark.py
CODEOWNERS
docker-compose.yml
labelmap.txt Cleanup Detector labelmap (#4932) 2023-01-06 07:03:16 -06:00
LICENSE
Makefile
process_clip.py
pyproject.toml
README.md

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