NVR with realtime local object detection for IP cameras
Go to file
Nicolas Mowen fe4fb645d3
Save exports to database (#11040)
* Save review thumbs in dedicated folder

* Create exports table

* Save exports to DB and save thumbnail for export

* Save full frame always

* Fix rounded corners

* Save exports that are in progress

* No need to remove spaces

* Reorganize apis to use IDs

* Use new apis for frontend

* Get video playback working

* Fix deleting and renaming

* Import existing exports to DB

* Implement downloading

* Formatting
2024-04-19 17:11:41 -05:00
.devcontainer Remove deprecated RTMP port 1935 (#9137) 2024-01-31 12:56:11 +00:00
.github Bump actions/setup-python from 5.0.0 to 5.1.0 (#10703) 2024-04-07 06:13:26 -06:00
.vscode
config
docker Implement config migration and restructure config for new review format (#10961) 2024-04-13 06:08:20 -06:00
docs Remove use_experimental config as part of config migration (#11003) 2024-04-17 07:02:59 -05:00
frigate Save exports to database (#11040) 2024-04-19 17:11:41 -05:00
migrations Save exports to database (#11040) 2024-04-19 17:11:41 -05:00
web Save exports to database (#11040) 2024-04-19 17:11:41 -05:00
.dockerignore
.gitignore Small autotracking changes (#9571) 2024-02-02 06:23:14 -06:00
.pylintrc
audio-labelmap.txt Audio events (#6848) 2023-07-01 08:18:33 -05:00
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
LICENSE
Makefile increment version 2024-01-31 06:23:54 -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

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