Josh Hawkins 8094dd4075
Fixes (#18117)
* face library i18n fixes

* face library i18n fixes

* add ability to use ctrl/cmd S to save in the config editor

* Use datetime as ID

* Update metrics inference speed to start with 0 ms

* fix android formatted thumbnail

* ensure role is comma separated and stripped correctly

* improve face library deletion

- add a confirmation dialog
- add ability to select all / delete faces in collections

* Implement lazy loading for video previews

* Force GPU for large embedding model

* GPU is required

* settings i18n fixes

* Don't delete train tab

* webpush debugging logs

* Fix incorrectly copying zones

* copy path data

* Ensure that cache dir exists for Frigate+

* face docs update

* Add description to upload image step to clarify the image

* Clean up

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2025-05-09 07:36:44 -06:00
2025-03-24 12:25:36 -05:00
2025-05-03 06:24:30 -06:00
2025-05-09 07:36:44 -06:00
2025-05-09 07:36:44 -06:00
2025-03-15 07:11:45 -06:00
2025-04-16 09:01:15 -06:00
2025-05-09 07:36:44 -06:00
2021-02-25 07:01:59 -06:00
2023-07-01 08:18:33 -05:00
2023-01-06 07:03:16 -06:00
2020-07-26 12:07:47 -05:00
2025-02-08 12:47:01 -06:00
2023-11-18 08:04:43 -06:00
2023-11-18 08:04:43 -06:00
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Frigate - NVR With Realtime Object Detection for IP Cameras

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[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.

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Languages
TypeScript 53.4%
Python 44.8%
CSS 0.5%
Shell 0.5%
Dockerfile 0.3%
Other 0.2%