Mirrors/blakeblackshear.frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2024-12-23 19:11:14 +01:00
Code Issues Projects Releases Wiki Activity
NVR with realtime local object detection for IP cameras
1,191 Commits 41 Branches 128 Tags 240 MiB
Python 47.8%
TypeScript 47.5%
CSS 1.4%
C++ 1.1%
Dockerfile 0.7%
Other 1.5%
5627b66a6e
Go to file
Nicolas Mowen 5627b66a6e Always show recording link even if recordings are currently disabled (#2787) 
* Always show recording link even if recordings are currently disabled

* Fix test to consider all cameras to have recording link
2022-02-18 21:18:26 -06:00
.devcontainer updated devcontainer 2021-06-12 07:23:14 -05:00
.github Run python unit tests in a github actions (#2589) 2022-02-18 21:18:26 -06:00
docker upgrade npm in dev container 2022-02-18 21:18:26 -06:00
docs update birdseye to handle stationary objects 2022-02-18 21:18:26 -06:00
frigate update birdseye to handle stationary objects 2022-02-18 21:18:26 -06:00
migrations fix migrations 2022-02-18 21:18:26 -06:00
web Always show recording link even if recordings are currently disabled (#2787) 2022-02-18 21:18:26 -06:00
.dockerignore update ignore files 2021-10-23 08:21:15 -05:00
.gitignore revamp process clip 2022-02-18 21:18:26 -06:00
.pylintrc
benchmark.py
docker-compose.yml update birdseye layout calculations 2021-06-12 07:23:14 -05:00
labelmap.txt
LICENSE
Makefile Run python unit tests in a github actions (#2589) 2022-02-18 21:18:26 -06:00
process_clip.py fix process_clip 2022-02-18 21:18:26 -06:00
README.md update docs url 2021-09-26 16:43:26 -05:00

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 RTMP to reduce the number of connections to your camera

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