https://github.com/blakeblackshear/frigate

NVR with realtime local object detection for IP cameras
https://github.com/blakeblackshear/frigate

ai camera google-coral home-assistant home-automation homeautomation mqtt nvr object-detection realtime rtsp tensorflow

Last synced: about 18 hours ago
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NVR with realtime local object detection for IP cameras

Host: GitHub
URL: https://github.com/blakeblackshear/frigate
Owner: blakeblackshear
License: mit
Created: 2019-01-26T13:52:38.000Z (about 6 years ago)
Default Branch: dev
Last Pushed: 2025-04-15T01:30:05.000Z (8 days ago)
Last Synced: 2025-04-15T05:09:30.371Z (8 days ago)
Topics: ai, camera, google-coral, home-assistant, home-automation, homeautomation, mqtt, nvr, object-detection, realtime, rtsp, tensorflow
Language: TypeScript
Homepage: https://frigate.video
Size: 88 MB
Stars: 22,003
Watchers: 195
Forks: 2,042
Open Issues: 151
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Codeowners: CODEOWNERS

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README

logo

# Frigate - NVR With Realtime Object Detection for IP Cameras

\[English\] | [简体中文](https://github.com/blakeblackshear/frigate/blob/dev/README_CN.md)

A complete and local NVR designed for [Home Assistant](https://www.home-assistant.io) with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.

Use of a GPU or AI accelerator such as a [Google Coral](https://coral.ai/products/) or [Hailo](https://hailo.ai/) is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead.

- Tight integration with Home Assistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration)
- 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](https://github.com/sponsors/blakeblackshear).

## Screenshots

### Live dashboard