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Merge remote-tracking branch 'origin/master' into dev
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@@ -824,6 +824,38 @@ cpu:
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models:
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- devices:
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- cpu:3
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xdna2:
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title: AMD XDNA2
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models:
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- key: yolov9
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label: YOLOv9
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recommended: true
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download: |-
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Prepare the model using the frigate-xdna setup instructions linked above. For local YOLO models, Frigate must have access to the same ONNX file bytes as the sidecar. The example below uses YOLOv9-C at 320x320. Frigate+ models may instead use the same `plus://MODEL_ID` in Frigate and the sidecar.
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ui: |-
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Navigate to **Settings > System > Detection models** and add a model. The ZMQ endpoint is not reported by the hardware probe, so set `devices` to `zmq:tcp://xdna:5555` in YAML. Then, on the same model, open the **Custom Model** tab and configure:
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| Field | Value |
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| ---------------------------------------- | ------------------------------------------ |
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| **Custom object detector model path** | `/config/models/yolov9-c-320.onnx` |
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| **Label map for custom object detector** | `/labelmap/coco-80.txt` |
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| **Object detection model input width** | `320` |
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| **Object detection model input height** | `320` |
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| **Model Input Pixel Color Format** | `rgb` (Frigate's default value) |
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| **Model Input Tensor Shape** | `nchw` |
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| **Model Input D Type** | `float` |
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| **Object Detection Model Type** | `yolo-generic` |
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yaml: |-
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models:
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- devices:
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- zmq:tcp://xdna:5555
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model_type: yolo-generic
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width: 320
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height: 320
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input_tensor: nchw
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input_dtype: float
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path: /config/models/yolov9-c-320.onnx
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labelmap_path: /labelmap/coco-80.txt
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memryx:
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title: MemryX
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models:
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