NVR with realtime local object detection for IP cameras
Go to file
2021-09-04 16:56:01 -05:00
.devcontainer updated devcontainer 2021-06-12 07:23:14 -05:00
.github
docker tweak vod settings for varying iframe intervals 2021-08-28 21:26:23 -05:00
docs remove font_scale in timestamp_style and calculate dynamically again 2021-09-04 16:34:48 -05:00
frigate disallow extra keys in config 2021-09-04 16:56:01 -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
.pylintrc
benchmark.py
docker-compose.yml update birdseye layout calculations 2021-06-12 07:23:14 -05:00
labelmap.txt
LICENSE
Makefile aarch64 makefile fix 2021-09-03 07:13:05 -05:00
README.md clean house on clips 2021-08-15 08:30:27 -05:00

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 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