Mirrors/blakeblackshear.frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2024-10-15 20:07:23 +02:00
Code Issues Projects Releases Wiki Activity
NVR with realtime local object detection for IP cameras
990 Commits 48 Branches 124 Tags 144 MiB
Python 47.8%
TypeScript 47.5%
CSS 1.4%
C++ 1.1%
Dockerfile 0.7%
Other 1.4%
00ff76a0b9
Go to file
Bernt Christian Egeland 00ff76a0b9
Events performance (#1645) 
* rearrange event route and splitted into several components

* useIntersectionObserver

* re-arrange

* searchstring improvement

* added xs tailwind breakpoint

* useOuterClick hook

* cleaned up

* removed some video controls for mobile devices

* lint

* moved hooks to global folder

* moved buttons for small devices

* added button groups

Co-authored-by: Bernt Christian Egeland <cbegelan@gmail.com>
2021-09-03 07:11:23 -05:00
.devcontainer updated devcontainer 2021-06-12 07:23:14 -05:00
.github Add paularmstrong to funding.yml 2021-02-24 20:58:44 -06:00
docker tweak vod settings for varying iframe intervals 2021-08-28 21:26:23 -05:00
docs Add RTMP and timestamp style to global config (#1674) 2021-09-03 07:03:36 -05:00
frigate Add RTMP and timestamp style to global config (#1674) 2021-09-03 07:03:36 -05:00
migrations remove backfill - only store rows moving forward 2021-06-10 07:04:28 -05:00
web Events performance (#1645) 2021-09-03 07:11:23 -05:00
.dockerignore expand dockerignore 2021-06-23 08:15:15 -05:00
.gitignore Use dataclasses for config handling 2021-05-23 20:38:57 -05:00
.pylintrc use fstr log style 2021-02-25 07:01:59 -06:00
benchmark.py
docker-compose.yml update birdseye layout calculations 2021-06-12 07:23:14 -05:00
labelmap.txt
LICENSE
Makefile add secure token module to NGINX in order to pass authSig down to segment files 2021-08-07 15:51:16 -05:00
README.md clean house on clips 2021-08-15 08:30:27 -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://blakeblackshear.github.io/frigate

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