NVR with realtime local object detection for IP cameras
Go to file
2024-10-30 06:30:00 -06:00
.cspell Add service manager infrastructure (#14150) 2024-10-21 10:00:38 -05:00
.devcontainer Removed usage of PyYAML for config parsing. (#13883) 2024-09-22 10:56:57 -05:00
.github Add docs update to type of change (#14686) 2024-10-30 06:30:00 -06:00
.vscode Fix vscode launch configuration (#13795) 2024-09-17 10:42:10 -05:00
config
docker Update Hailo Driver to 4.19 (#14674) 2024-10-29 18:40:24 -05:00
docs Add specific section about GPU in semantic search (#14685) 2024-10-30 07:23:10 -05:00
frigate Fix config loading (#14684) 2024-10-30 07:16:56 -05:00
migrations
notebooks
web UI changes and bugfixes (#14669) 2024-10-30 05:54:06 -06:00
.dockerignore
.gitignore Removed usage of PyYAML for config parsing. (#13883) 2024-09-22 10:56:57 -05:00
.pylintrc
audio-labelmap.txt
benchmark_motion.py
benchmark.py Custom classes for Process and Metrics (#13950) 2024-09-27 07:53:23 -05:00
CODEOWNERS
cspell.json Work through most of the cspell warnings in python (#13794) 2024-09-17 10:41:46 -05:00
docker-compose.yml
labelmap.txt
LICENSE
Makefile Formatting improvements (#13765) 2024-09-17 07:39:44 -05:00
netlify.toml
package-lock.json
process_clip.py Removed usage of PyYAML for config parsing. (#13883) 2024-09-22 10:56:57 -05:00
pyproject.toml
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

Live dashboard

Live dashboard

Streamlined review workflow

Streamlined review workflow

Multi-camera scrubbing

Multi-camera scrubbing

Built-in mask and zone editor

Multi-camera scrubbing