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37 lines
1.1 KiB
37 lines
1.1 KiB
# Ultralytics YOLO 🚀, AGPL-3.0 license |
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# DOTA 2.0 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/DOTAv2 # 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 2.0 |
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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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16: airport |
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17: helipad |
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# Download script/URL (optional) |
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download: https://github.com/ultralytics/yolov5/releases/download/v1.0/DOTAv2.zip
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