Начало Каталог Помощ
Вход
rootless
/
frigate
1
0
Разклонения 0
Файлове Задачи 0 Заявки за сливане 0 Уики

Няма описание

ИН на ревизия: 8de15af7b4
Клонове Маркери
frigate
ZIP TAR.GZ
Jason Hunter 8de15af7b4 Fix duration for long events and playback rate for top of the hour преди 3 години
.devcontainer b91b0d39dd updated devcontainer преди 3 години
.github 6eecb6780e Run python unit tests in a github actions (#2589) преди 3 години
docker 0bef16bb17 upgrade npm in dev container преди 3 години
docs 3e90f3032c make stationary_threshold configurable преди 3 години
frigate 21178613de Only send significant update once when motionless count reaches the defined threshold. преди 3 години
migrations 7c74bf2566 fix migrations преди 3 години
web 8de15af7b4 Fix duration for long events and playback rate for top of the hour преди 3 години
.dockerignore c1132e6897 update ignore files преди 3 години
.gitignore 0695bb097d revamp process clip преди 3 години
.pylintrc 040ffda687 use fstr log style преди 4 години
LICENSE 53ccc903da switch to MIT license преди 4 години
Makefile 6eecb6780e Run python unit tests in a github actions (#2589) преди 3 години
README.md 74986982a0 update docs url преди 3 години
benchmark.py f946813ccb support multiple coral devices (fixes #100) преди 4 години
docker-compose.yml c70419bd0b update birdseye layout calculations преди 3 години
labelmap.txt acb75fa02d refactor and reduce false positives преди 4 години
process_clip.py 93f418ac0b fix process_clip преди 3 години

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