Merge remote-tracking branch 'origin/master' into dev

This commit is contained in:
Blake Blackshear
2026-10-02 06:39:23 -05:00
57 changed files with 1242 additions and 333 deletions
@@ -30,6 +30,7 @@ Frigate supports multiple different detectors that work on different types of ha
- [ROCm](#amdrocm-gpu-detector): ROCm can run on AMD Discrete GPUs to provide efficient object detection.
- [ONNX](#onnx): ROCm will automatically be detected and used as a detector in the `-rocm` Frigate image when a supported ONNX model is configured.
- <CommunityBadge /> [XDNA2](#amd-xdna2): AMD Ryzen AI / XDNA2 NPUs can run object detection through the community-maintained `frigate-xdna` ZMQ sidecar.
**Apple Silicon**
@@ -567,6 +568,28 @@ When using CPU detectors, you can add one CPU detector per camera. Adding more d
# Community Supported Detectors
## AMD XDNA2
AMD Ryzen AI / XDNA2 NPUs can be used through the community-maintained
[frigate-xdna](https://github.com/mitchins/frigate-xdna) detector sidecar.
The sidecar runs separately from Frigate and connects using Frigate's ZMQ
detector interface.
Currently qualified on **Ryzen AI Max 300 / Strix Halo**. Other XDNA2 devices
are not yet qualified; XDNA1 is unsupported.
Follow the frigate-xdna setup instructions to prepare and start the sidecar
before starting Frigate.
### Configuration {#configuration-xdna2}
Using the detector config below will connect Frigate to the sidecar:
<ModelConfigDropdown detectorTitle="AMD XDNA2" models={objectDetectorsModels.xdna2.models} />
The example assumes Frigate and the sidecar share a Docker network where the
sidecar is named `xdna`.
## MemryX MX3
This detector is available for use with the MemryX MX3 accelerator M.2 module. Frigate supports the MX3 on compatible hardware platforms, providing efficient and high-performance object detection.