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Add Docs glossary links (#16448)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-09-23 23:48:46 +02:00 • committed by GitHub
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docs/en/tasks/obb.md
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@ -5,7 +5,7 @@ keywords: Oriented Bounding Boxes, OBB, Object Detection, YOLOv8, Ultralytics, D
model_name: yolov8n-obb
---
# Oriented Bounding Boxes Object Detection
# Oriented Bounding Boxes [Object Detection](https://www.ultralytics.com/glossary/object-detection)
<!-- obb task poster -->
@ -55,7 +55,7 @@ YOLOv8 pretrained OBB models are shown here, which are pretrained on the [DOTAv1
## Train
Train YOLOv8n-obb on the `dota8.yaml` dataset for 100 epochs at image size 640. For a full list of available arguments see the [Configuration](../usage/cfg.md) page.
Train YOLOv8n-obb on the `dota8.yaml` dataset for 100 [epochs](https://www.ultralytics.com/glossary/epoch) at image size 640. For a full list of available arguments see the [Configuration](../usage/cfg.md) page.
!!! example
@ -103,7 +103,7 @@ OBB dataset format can be found in detail in the [Dataset Guide](../datasets/obb
## Val
Validate trained YOLOv8n-obb model accuracy on the DOTA8 dataset. No arguments are needed as the `model` retains its training `data` and arguments as model attributes.
Validate trained YOLOv8n-obb model [accuracy](https://www.ultralytics.com/glossary/accuracy) on the DOTA8 dataset. No arguments are needed as the `model` retains its training `data` and arguments as model attributes.
!!! example