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Optimize Docs images (#15900)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-08-30 05:52:10 +05:00 • committed by GitHub
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docs/en/datasets/obb/dota-v2.md
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@ -8,7 +8,7 @@ keywords: DOTA dataset, object detection, aerial images, oriented bounding boxes
[DOTA](https://captain-whu.github.io/DOTA/index.html) stands as a specialized dataset, emphasizing object detection in aerial images. Originating from the DOTA series of datasets, it offers annotated images capturing a diverse array of aerial scenes with Oriented Bounding Boxes (OBB).
![DOTA classes visual](https://user-images.githubusercontent.com/26833433/259461765-72fdd0d8-266b-44a9-8199-199329bf5ca9.jpg)
![DOTA classes visual](https://github.com/ultralytics/docs/releases/download/0/dota-classes-visual.avif)
## Key Features
@ -126,7 +126,7 @@ To train a model on the DOTA v1 dataset, you can utilize the following code snip
Having a glance at the dataset illustrates its depth:
![Dataset sample image](https://captain-whu.github.io/DOTA/images/instances-DOTA.jpg)
![Dataset sample image](https://github.com/ultralytics/docs/releases/download/0/instances-DOTA.avif)
- **DOTA examples**: This snapshot underlines the complexity of aerial scenes and the significance of Oriented Bounding Box annotations, capturing objects in their natural orientation.