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
2,425 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%
086eb37ece
Go to file
Nicolas Mowen 086eb37ece
Cleanup to use new preview video player in dynamic player (#10335) 
* Cleanup to use new preview video player

* Make it so motion persists the selected time

* Don't jump when player first starts

* Get autoplay working right
2024-03-08 17:24:12 -06:00
.devcontainer Remove deprecated RTMP port 1935 (#9137) 2024-01-31 12:56:11 +00:00
.github Set Compute Level for CI build (#10276) 2024-03-07 05:59:33 -06:00
.vscode
config
docker Pass computes value to libyolo_layer build (#10210) 2024-03-05 06:04:13 -06:00
docs Organize api docs and add new review and preview apis (#10268) 2024-03-05 15:33:39 -06:00
frigate Tweaks fixes (#10311) 2024-03-07 08:34:11 -06:00
migrations Migrate pydantic to V2 (#10142) 2024-02-29 16:10:13 -07:00
web Cleanup to use new preview video player in dynamic player (#10335) 2024-03-08 17:24:12 -06:00
.dockerignore
.gitignore Small autotracking changes (#9571) 2024-02-02 06:23:14 -06:00
.pylintrc
audio-labelmap.txt
benchmark_motion.py
benchmark.py
CODEOWNERS AMD GPU support with the rocm detector and YOLOv8 pretrained model download (#9762) 2024-02-10 06:41:46 -06:00
docker-compose.yml
labelmap.txt
LICENSE
Makefile
netlify.toml
process_clip.py Remove rtmp (#8941) 2024-01-31 12:56:11 +00:00
pyproject.toml
README.md Clarify docs about rtmp (#5052) 2023-01-13 07:20:25 -06:00

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 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