NVR with realtime local object detection for IP cameras
Go to file
Nicolas Mowen 93260f6cfd
Add region count to database and use for motion activity (#10480)
* Add region count to database and use for motion activity

* Fix test
2024-03-15 09:29:22 -06:00
.devcontainer Remove deprecated RTMP port 1935 (#9137) 2024-01-31 12:56:11 +00:00
.github Fix image cleanup (#10364) 2024-03-10 14:18:44 -04:00
.vscode
config
docker Improve preview loading (#10406) 2024-03-12 18:19:16 -05:00
docs Update live.md (#10366) 2024-03-11 07:13:07 -05:00
frigate Add region count to database and use for motion activity (#10480) 2024-03-15 09:29:22 -06:00
migrations Add region count to database and use for motion activity (#10480) 2024-03-15 09:29:22 -06:00
web Fix switching camera group bug (#10478) 2024-03-15 08:59:41 -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 Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
labelmap.txt Cleanup Detector labelmap (#4932) 2023-01-06 07:03:16 -06:00
LICENSE
Makefile Update Makefile for 0.13.2 (#9687) 2024-02-05 17:50:35 -06:00
netlify.toml Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
process_clip.py Remove rtmp (#8941) 2024-01-31 12:56:11 +00:00
pyproject.toml Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
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