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Update detector docs

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Nicolas Mowen 2025-03-22 07:37:12 -06:00
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commit a6de759b01
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docs/docs/configuration/object_detectors.md
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@ -344,6 +344,12 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl
[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. [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.
:::warning
Currently D-FINE models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
:::
After placing the downloaded onnx model in your config/model_cache folder, you can use the following configuration: After placing the downloaded onnx model in your config/model_cache folder, you can use the following configuration:
```yaml ```yaml
@ -653,7 +659,7 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl
After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration: After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
``` ```yaml
detectors: detectors:
onnx: onnx:
type: onnx type: onnx
@ -671,7 +677,7 @@ model:
[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. [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.
After placing the downloaded onnx model in your config/model_cache folder, you can use the following configuration: After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
```yaml ```yaml
detectors: detectors:
@ -898,7 +904,7 @@ Make sure you change the batch size to 1 before exporting.
To export as ONNX: To export as ONNX:
1. `pip3 install rfdetr` 1. `pip3 install rfdetr`
2. `python` 2. `python3`
3. `from rfdetr import RFDETRBase` 3. `from rfdetr import RFDETRBase`
4. `x = RFDETRBase()` 4. `x = RFDETRBase()`
5. `x.export()` 5. `x.export()`