Separate GPU CI job in actions (#4584)
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@ -133,13 +133,15 @@ To auto-annotate your dataset using the Ultralytics framework, you can use the `
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auto_annotate(data="path/to/images", det_model="yolov8x.pt", sam_model='sam_b.pt')
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```
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| Argument | Type | Description | Default |
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|------------|---------------------|---------------------------------------------------------------------------------------------------------|--------------|
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| data | str | Path to a folder containing images to be annotated. | |
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| det_model | str, optional | Pre-trained YOLO detection model. Defaults to 'yolov8x.pt'. | 'yolov8x.pt' |
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| sam_model | str, optional | Pre-trained SAM segmentation model. Defaults to 'sam_b.pt'. | 'sam_b.pt' |
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| device | str, optional | Device to run the models on. Defaults to an empty string (CPU or GPU, if available). | |
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| output_dir | str, None, optional | Directory to save the annotated results. Defaults to a 'labels' folder in the same directory as 'data'. | None |
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Certainly, here is the table updated with code snippets:
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| Argument | Type | Description | Default |
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|--------------|-------------------------|-------------------------------------------------------------------------------------------------------------|----------------|
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| `data` | `str` | Path to a folder containing images to be annotated. | `None` |
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| `det_model` | `str, optional` | Pre-trained YOLO detection model. Defaults to `'yolov8x.pt'`. | `'yolov8x.pt'` |
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| `sam_model` | `str, optional` | Pre-trained SAM segmentation model. Defaults to `'sam_b.pt'`. | `'sam_b.pt'` |
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| `device` | `str, optional` | Device to run the models on. Defaults to an empty string (CPU or GPU, if available). | `''` |
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| `output_dir` | `str or None, optional` | Directory to save the annotated results. Defaults to a `'labels'` folder in the same directory as `'data'`. | `None` |
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The `auto_annotate` function takes the path to your images, along with optional arguments for specifying the pre-trained detection and [SAM segmentation models](https://docs.ultralytics.com/models/sam), the device to run the models on, and the output directory for saving the annotated results.
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