blakeblackshear.frigate/docs/docs/configuration/hardware_acceleration_enrichments.md
Josh Hawkins dba9206898
Fixes (#18500)
* fix i18n keys

* hide disable from context menu for viewers

* Fix auto live check for default dashboard and camera groups

Disabling the Automatic Live View switch in Settings should prevent streaming from occurring. Overriding any settings in a camera group will override the global setting. The check here incorrectly always returned false instead of undefined.

* clarify hardware accelerated enrichments

* clarify

* add note about detect stream to face rec docs

* add note about low end Dahuas for autotracking

* Catch invalid face box / image

* Video tab tweaks

With the changes in https://github.com/blakeblackshear/frigate/pull/18220, the video tab in the Tracked Object Details pane now correctly trims the in-browser HLS video. Because of keyframes and record/detect stream differences, we can manually subtract a couple of seconds from the event start_time to ensure the first few frames aren't cut off from the video

* Clarify

* Don't use Migraphx by default

* Provide better support for running embeddings on GPU

* correctly join cameras

* Adjust blur confidence reduction

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2025-06-03 06:33:32 -06:00

33 lines
1.6 KiB
Markdown

---
id: hardware_acceleration_enrichments
title: Enrichments
---
# Enrichments
Some of Frigate's enrichments can use a discrete GPU for accelerated processing.
## Requirements
Object detection and enrichments (like Semantic Search, Face Recognition, and License Plate Recognition) are independent features. To use a GPU for object detection, see the [Object Detectors](/configuration/object_detectors.md) documentation. If you want to use your GPU for any supported enrichments, you must choose the appropriate Frigate Docker image for your GPU and configure the enrichment according to its specific documentation.
- **AMD**
- ROCm will automatically be detected and used for enrichments in the `-rocm` Frigate image.
- **Intel**
- OpenVINO will automatically be detected and used for enrichments in the default Frigate image.
- **Nvidia**
- Nvidia GPUs will automatically be detected and used for enrichments in the `-tensorrt` Frigate image.
- Jetson devices will automatically be detected and used for enrichments in the `-tensorrt-jp6` Frigate image.
Utilizing a GPU for enrichments does not require you to use the same GPU for object detection. For example, you can run the `tensorrt` Docker image for enrichments and still use other dedicated hardware like a Coral or Hailo for object detection. However, one combination that is not supported is TensorRT for object detection and OpenVINO for enrichments.
:::note
A Google Coral is a TPU (Tensor Processing Unit), not a dedicated GPU (Graphics Processing Unit) and therefore does not provide any kind of acceleration for Frigate's enrichments.
:::