# 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
