blakeblackshear.frigate/docker/rocm/README.md

AMD/ROCm GPU based detector

Building

Running make local-rocm results in following images:

• frigate:latest-rocm, 7.64 GB, all possible chipsets
• frigate:latest-rocm-gfx1030, 3.72 GB, gfx1030 and compatible
• frigate:latest-rocm-gfx900, 3.64 GB, gfx900 and compatible

Docker settings

AMD/ROCm needs access to /dev/kfd and /dev/dri. When running as user also needs the video group. Sometimes also needs the render and ssh/_ssh groups. For reference/comparison see running ROCm PyTorch Docker image.

$ docker run --device=/dev/kfd --device=/dev/dri --group-add video \
    ...

When running on iGPU you likely need to specify the proper HSA_OVERRIDE_GFX_VERSION environment variable. For chip specific docker images this is done automatically, for others you need to figure out what it is. AMD/ROCm does not officially support the iGPUs. See the ROCm issue for context and examples.

If you have gfx90c (can be queried with /opt/rocm/bin/rocminfo) then you need to run with the gfx900 driver, so you would modify the docker launch by something like this:

$ docker run ... -e HSA_OVERRIDE_GFX_VERSION=9.0.0 ...

Frigate configuration

An example of a working configuration:

model:
  path: /yolov8n_320x320.onnx
  labelmap_path: /yolov8s_labels.txt
  model_type: yolov8
detectors:
  rocm:
    type: rocm