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- # Ultralytics YOLO 🚀, AGPL-3.0 license
- # DOTA 2.0 dataset https://captain-whu.github.io/DOTA/index.html for object detection in aerial images by Wuhan University
- # Example usage: yolo train model=yolov8n-obb.pt data=DOTAv2.yaml
- # parent
- # ├── ultralytics
- # └── datasets
- # └── dota2 ← downloads here (2GB)
- # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
- path: ../datasets/DOTAv2 # dataset root dir
- train: images/train # train images (relative to 'path') 1411 images
- val: images/val # val images (relative to 'path') 458 images
- test: images/test # test images (optional) 937 images
- # Classes for DOTA 2.0
- names:
- 0: plane
- 1: ship
- 2: storage tank
- 3: baseball diamond
- 4: tennis court
- 5: basketball court
- 6: ground track field
- 7: harbor
- 8: bridge
- 9: large vehicle
- 10: small vehicle
- 11: helicopter
- 12: roundabout
- 13: soccer ball field
- 14: swimming pool
- 15: container crane
- 16: airport
- 17: helipad
- # Download script/URL (optional)
- download: https://github.com/ultralytics/yolov5/releases/download/v1.0/DOTAv2.zip
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