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Co-authored-by: Hosted Weblate <hosted@weblate.org>
Co-authored-by: Julius Hyvönen <julius.hyvonen@gmail.com>
Co-authored-by: Risto Toivanen <risto.toivanen@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/audio/fi/
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Translate-URL: https://hosted.weblate.org/projects/frigate-nvr/views-search/fi/
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Translation: Frigate NVR/components-filter
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Translation: Frigate NVR/views-facelibrary
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Frigate - NVR With Realtime Object Detection for IP Cameras

Translation status

[English] | 简体中文

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 GPU or AI accelerator such as a Google Coral or Hailo is highly recommended. AI accelerators will outperform even the best CPUs 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

Translations

We use Weblate to support language translations. Contributions are always welcome.

Translation status
Languages
TypeScript 49%
Python 48.7%
CSS 0.7%
Shell 0.6%
Dockerfile 0.4%
Other 0.4%