Update `retina_masks` description (#17587)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
pull/17550/head^2
Mohammed Yasin 1 week ago committed by GitHub
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  1. 2
      docs/en/macros/predict-args.md

@ -13,7 +13,7 @@
| `augment` | `bool` | `False` | Enables test-time augmentation (TTA) for predictions, potentially improving detection robustness at the cost of inference speed. | | `augment` | `bool` | `False` | Enables test-time augmentation (TTA) for predictions, potentially improving detection robustness at the cost of inference speed. |
| `agnostic_nms` | `bool` | `False` | Enables class-agnostic Non-Maximum Suppression (NMS), which merges overlapping boxes of different classes. Useful in multi-class detection scenarios where class overlap is common. | | `agnostic_nms` | `bool` | `False` | Enables class-agnostic Non-Maximum Suppression (NMS), which merges overlapping boxes of different classes. Useful in multi-class detection scenarios where class overlap is common. |
| `classes` | `list[int]` | `None` | Filters predictions to a set of class IDs. Only detections belonging to the specified classes will be returned. Useful for focusing on relevant objects in multi-class detection tasks. | | `classes` | `list[int]` | `None` | Filters predictions to a set of class IDs. Only detections belonging to the specified classes will be returned. Useful for focusing on relevant objects in multi-class detection tasks. |
| `retina_masks` | `bool` | `False` | Uses high-resolution segmentation masks if available in the model. This can enhance mask quality for segmentation tasks, providing finer detail. | | `retina_masks` | `bool` | `False` | Returns high-resolution segmentation masks. The returned masks (`masks.data`) will match the original image size if enabled. If disabled, they have the image size used during inference. |
| `embed` | `list[int]` | `None` | Specifies the layers from which to extract feature vectors or [embeddings](https://www.ultralytics.com/glossary/embeddings). Useful for downstream tasks like clustering or similarity search. | | `embed` | `list[int]` | `None` | Specifies the layers from which to extract feature vectors or [embeddings](https://www.ultralytics.com/glossary/embeddings). Useful for downstream tasks like clustering or similarity search. |
| `project` | `str` | `None` | Name of the project directory where prediction outputs are saved if `save` is enabled. | | `project` | `str` | `None` | Name of the project directory where prediction outputs are saved if `save` is enabled. |
| `name` | `str` | `None` | Name of the prediction run. Used for creating a subdirectory within the project folder, where prediction outputs are stored if `save` is enabled. | | `name` | `str` | `None` | Name of the prediction run. Used for creating a subdirectory within the project folder, where prediction outputs are stored if `save` is enabled. |

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