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  1. # COCO 2017 dataset http://cocodataset.org
  2. # Download command: bash yolov5/data/get_coco2017.sh
  3. # Train command: python train.py --data coco.yaml
  4. # Default dataset location is next to /yolov5:
  5. # /parent_folder
  6. # /coco
  7. # /yolov5
  8. # train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
  9. train: ../coco/train2017.txt # 118287 images
  10. val: ../coco/val2017.txt # 5000 images
  11. test: ../coco/test-dev2017.txt # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794
  12. # number of classes
  13. nc: 80
  14. # class names
  15. names: ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
  16. 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
  17. 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
  18. 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
  19. 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
  20. 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
  21. 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
  22. 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
  23. 'hair drier', 'toothbrush']
  24. # Print classes
  25. # with open('data/coco.yaml') as f:
  26. # d = yaml.load(f, Loader=yaml.FullLoader) # dict
  27. # for i, x in enumerate(d['names']):
  28. # print(i, x)