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Josh Hawkins 696434b36d Initial framework for new UI with React/Typescript (#8885 )

* Write a low resolution low fps stream from decoded frames (#8673)

* Generate low res low fps previews for recordings viewer

* Make sure previews end on the hour

* Fix durations and decrase keyframe interval to ensure smooth scrubbing

* Ensure minimized resolution is compatible with yuv

* Add ability to configure preview quality

* Fix

* Clean up previews more efficiently

* Use iterator

* Ensure final frame in preview is not duplicated

* initial react/ts framework

* fix gitignore glob excluding ts files

* ignore folders in web-new

* SWRConfig changes for swr 2.x

* use frigateConfig type in websocket handlers

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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

2024-01-31 12:56:11 +00:00

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Docs improvements (#8641 )

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Initial framework for new UI with React/Typescript (#8885 )

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audio-labelmap.txt

Audio events (#6848 )

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use a different method for blur and contrast to reduce CPU (#6940 )

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CODEOWNERS

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process_clip.py

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pyproject.toml

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README.md

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README.md

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