forked from Github/frigate
7a1215d581195d24990d443f6c5915e3081e7cb7
* Adding configuration example for retain modes Reading the documentation on its own didn't help me but when I found https://github.com/blakeblackshear/frigate/discussions/2447 I was able to understand how to add this to my configuration. I've added the example given in that discussion to help future readers of the page. * Update record.md Added suggested changes and have also added wording beneath the example mentioning the configuration can be added on a per camera basis. Have also built on the example to add object specific retentions timings - Not sure if it would be preferred to have it all within one example to not complicate things? Let me know your thoughts * Update record.md Created Object Specific Retention header * Typo Co-authored-by: Blake Blackshear <blake@frigate.video>
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 RTMP to reduce the number of connections to your camera
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
Integration into Home Assistant
Also comes with a builtin UI:
Description
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