NVR with realtime local object detection for IP cameras
Go to file
2023-11-10 18:12:20 -06:00
.devcontainer Check ffmpeg version instead of checking for presence of BTBN_PATH (#7023) 2023-07-06 07:35:26 -05:00
.github fix image tag (#8560) 2023-11-09 19:02:16 -06:00
.vscode Set User Agent for FFmpeg calls (#4555) 2022-11-30 16:53:45 -06:00
config Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
docker Fix nginx cache (#8558) 2023-11-09 16:09:25 -06:00
docs Update go2rtc to 1.8.2 (#8459) 2023-11-09 06:43:06 -06:00
frigate Don't run forever in autotracking (#8579) 2023-11-10 18:12:20 -06:00
migrations Performance increase with lots of recordings (#8525) 2023-11-07 23:18:26 +00:00
web Show error when clicking on image before mask (#8547) 2023-11-09 06:42:19 -06:00
.dockerignore Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
.gitignore Migrate default database path from /media/frigate to /config (#5219) 2023-04-23 11:35:40 -05:00
.pylintrc use fstr log style 2021-02-25 07:01:59 -06:00
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 Add isort and ruff linter (#6575) 2023-05-29 05:31:17 -05:00
CODEOWNERS Initial support for rockchip boards (#8382) 2023-11-02 12:55:24 +00:00
docker-compose.yml Nvidia Jetson ffmpeg + TensorRT support (#6458) 2023-07-26 05:50:41 -05:00
labelmap.txt Cleanup Detector labelmap (#4932) 2023-01-06 07:03:16 -06:00
LICENSE switch to MIT license 2020-07-26 12:07:47 -05:00
Makefile Community Supported Boards Framework (#7114) 2023-07-23 16:45:29 -05:00
process_clip.py Improve tracking (#6516) 2023-05-31 08:12:43 -06:00
pyproject.toml Fix bug introduced in new linter (#6754) 2023-06-11 07:18:47 -05:00
README.md Clarify docs about rtmp (#5052) 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