mirror of
https://github.com/blakeblackshear/frigate.git
synced 2025-12-08 06:15:43 +03:00
27 lines
1.3 KiB
Markdown
27 lines
1.3 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 for object detection.
|