| .. | ||
| migraphx | ||
| Dockerfile | ||
| README.md | ||
| rocm-pin-600 | ||
| rocm.hcl | ||
| rocm.list | ||
| rocm.mk | ||
AMD/ROCm GPU based detector
Building
Running make local-rocm results in following images:
frigate:latest-rocm, 7.64 GB, all possible chipsetsfrigate:latest-rocm-gfx1030, 3.72 GB, gfx1030 and compatiblefrigate: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