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Co-authored-by: Yash Khurana <ykhurana6@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Swamita Gupta <swamita2001@gmail.com> Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com> Co-authored-by: Laughing-q <1185102784@qq.com> Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com> Co-authored-by: Laughing-q <1182102784@qq.com>
36 lines
1.1 KiB
YAML
36 lines
1.1 KiB
YAML
# Ultralytics YOLO 🚀, AGPL-3.0 license
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# DOTA 1.5 dataset https://captain-whu.github.io/DOTA/index.html for object detection in aerial images by Wuhan University
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# Example usage: yolo train model=yolov8n-obb.pt data=DOTAv2.yaml
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# parent
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# ├── ultralytics
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# └── datasets
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# └── dota2 ← downloads here (2GB)
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# 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, ..]
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path: ../datasets/DOTAv1.5 # dataset root dir
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train: images/train # train images (relative to 'path') 1411 images
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val: images/val # val images (relative to 'path') 458 images
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test: images/test # test images (optional) 937 images
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# Classes for DOTA 1.5
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names:
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0: plane
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1: ship
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2: storage tank
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3: baseball diamond
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4: tennis court
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5: basketball court
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6: ground track field
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7: harbor
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8: bridge
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9: large vehicle
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10: small vehicle
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11: helicopter
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12: roundabout
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13: soccer ball field
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14: swimming pool
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15: container crane
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# Download script/URL (optional)
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download: https://github.com/ultralytics/yolov5/releases/download/v1.0/DOTAv1.5.zip
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