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  1. # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
  2. # COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
  3. # Example usage: python train.py --data coco128.yaml
  4. # parent
  5. # ├── yolov5
  6. # └── datasets
  7. # └── coco128 ← downloads here
  8. # 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, ..]
  9. path: ../datasets/coco128 # dataset root dir
  10. train: images/train2017 # train images (relative to 'path') 128 images
  11. val: images/train2017 # val images (relative to 'path') 128 images
  12. test: # test images (optional)
  13. # Classes
  14. nc: 80 # number of classes
  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'] # class names
  24. # Download script/URL (optional)
  25. download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip