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Update detector docs
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@ -344,6 +344,12 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl
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[D-FINE](https://github.com/Peterande/D-FINE) is a DETR based model. The ONNX exported models are supported, but not included by default. See [the models section](#downloading-d-fine-model) for more information on downloading the D-FINE model for use in Frigate.
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:::warning
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Currently D-FINE models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
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:::
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After placing the downloaded onnx model in your config/model_cache folder, you can use the following configuration:
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```yaml
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@ -653,7 +659,7 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl
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After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
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```
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```yaml
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detectors:
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onnx:
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type: onnx
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@ -671,7 +677,7 @@ model:
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[D-FINE](https://github.com/Peterande/D-FINE) is a DETR based model. The ONNX exported models are supported, but not included by default. See [the models section](#downloading-d-fine-model) for more information on downloading the D-FINE model for use in Frigate.
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After placing the downloaded onnx model in your config/model_cache folder, you can use the following configuration:
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After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
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```yaml
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detectors:
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@ -898,7 +904,7 @@ Make sure you change the batch size to 1 before exporting.
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To export as ONNX:
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1. `pip3 install rfdetr`
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2. `python`
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2. `python3`
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3. `from rfdetr import RFDETRBase`
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4. `x = RFDETRBase()`
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5. `x.export()`
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