administrator/frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2026-05-05 04:57:42 +03:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity
NVR with realtime local object detection for IP cameras
4,009 Commits 54 Branches 156 Tags 760 MiB
TypeScript 54.3%
Python 44.2%
CSS 0.4%
Shell 0.4%
Dockerfile 0.3%
Other 0.2%
f16f6f95b8
Go to file
ZhaiSoul f16f6f95b8 feat: add openai base_url setting
2025-04-15 15:38:11 +00:00
.cspell
.devcontainer
.github
.vscode
config
docker Include arch in name (#17667) 2025-04-12 07:50:17 -06:00
docs Small Tweaks (#17652) 2025-04-11 08:21:01 -06:00
frigate feat: add openai base_url setting 2025-04-15 15:38:11 +00:00
migrations
notebooks update YOLO_NAS notebook (#17414) 2025-03-27 10:33:03 -06:00
web revert: revert wrong label fix 2025-04-15 15:36:35 +00:00
.dockerignore
.gitignore
.pylintrc
audio-labelmap.txt
benchmark_motion.py
benchmark.py
CODEOWNERS
cspell.json
docker-compose.yml Devcontainer: update Mosquitto from 1.6 to 2.0 (#17415) 2025-03-27 10:33:49 -06:00
labelmap.txt
LICENSE
Makefile
netlify.toml
package-lock.json
process_clip.py
pyproject.toml
README_CN.md Update README_CN (#17581) 2025-04-07 08:32:43 -06:00
README.md Small Tweaks (#17652) 2025-04-11 08:21:01 -06:00

README.md

logo

Frigate - NVR With Realtime Object Detection for IP Cameras

Translation status 
English

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 GPU or AI accelerator such as a Google Coral or Hailo is highly recommended. AI accelerators will outperform even the best CPUs 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

Live dashboard

Live dashboard

Streamlined review workflow

Streamlined review workflow

Multi-camera scrubbing

Multi-camera scrubbing

Built-in mask and zone editor

Multi-camera scrubbing

Translations

We use Weblate to support language translations. Contributions are always welcome.

Translation status