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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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