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  1. # COCO 2017 dataset http://cocodataset.org
  2. # Train command: python train.py --data coco.yaml
  3. # Default dataset location is next to YOLOv5:
  4. # /parent_folder
  5. # /coco
  6. # /yolov5
  7. # download command/URL (optional)
  8. download: bash data/scripts/get_coco.sh
  9. # train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
  10. train: ../coco/train2017.txt # 118287 images
  11. val: ../coco/val2017.txt # 5000 images
  12. test: ../coco/test-dev2017.txt # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794
  13. # number of classes
  14. nc: 80
  15. # class names
  16. names: [ 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
  17. 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
  18. 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
  19. 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
  20. 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
  21. 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
  22. 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
  23. 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
  24. 'hair drier', 'toothbrush' ]
  25. # Print classes
  26. # with open('data/coco.yaml') as f:
  27. # d = yaml.safe_load(f) # dict
  28. # for i, x in enumerate(d['names']):
  29. # print(i, x)