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Add https://youtu.be/5XYdm5CYODA to docs (#16392)

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54
docs/en/tasks/obb.md
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@ -19,28 +19,16 @@ The output of an oriented object detector is a set of rotated bounding boxes tha
YOLOv8 OBB models use the `-obb` suffix, i.e. `yolov8n-obb.pt` and are pretrained on [DOTAv1](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/DOTAv1.yaml).
<table>
<tr>
<td align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Z7Z9pHF8wJc"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Object Detection using Ultralytics YOLOv8 Oriented Bounding Boxes (YOLOv8-OBB)
</td>
<td align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/uZ7SymQfqKI"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Object Detection with YOLOv8-OBB using Ultralytics HUB
</td>
</tr>
</table>
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/Z7Z9pHF8wJc"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Object Detection using Ultralytics YOLOv8 Oriented Bounding Boxes (YOLOv8-OBB)
</p>
## Visual Samples
@ -98,6 +86,17 @@ Train YOLOv8n-obb on the `dota8.yaml` dataset for 100 epochs at image size 640.
yolo obb train data=dota8.yaml model=yolov8n-obb.yaml pretrained=yolov8n-obb.pt epochs=100 imgsz=640
```
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/uZ7SymQfqKI"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to Train Ultralytics YOLOv8-OBB (Oriented Bounding Boxes) Models on DOTA Dataset using Ultralytics HUB
</p>
### Dataset format
OBB dataset format can be found in detail in the [Dataset Guide](../datasets/obb/index.md).
@ -158,6 +157,17 @@ Use a trained YOLOv8n-obb model to run predictions on images.
yolo obb predict model=path/to/best.pt source='https://ultralytics.com/images/bus.jpg' # predict with custom model
```
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/5XYdm5CYODA"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to Detect and Track Storage Tanks using Ultralytics YOLOv8-OBB | Oriented Bounding Boxes | DOTA
</p>
See full `predict` mode details in the [Predict](../modes/predict.md) page.
## Export