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# YOLOv5 🚀 by Ultralytics, AGPL-3.0 license





  
  

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# COCO 2017 dataset http://cocodataset.org by Microsoft





  
  

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# Example usage: python train.py --data coco.yaml





  
  

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# parent





  
  

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# ├── yolov5





  
  

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# └── datasets





  
  

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#     └── coco  ← downloads here (20.1 GB)





  
  

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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/coco  # dataset root dir





  
  

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train: train2017.txt  # train images (relative to 'path') 118287 images





  
  

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val: val2017.txt  # val images (relative to 'path') 5000 images





  
  

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test: test-dev2017.txt  # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794





  
  

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# Classes





  
  

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names:





  
  

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  0: person





  
  

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  1: bicycle





  
  

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  2: car





  
  

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  3: motorcycle





  
  

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  4: airplane





  
  

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  5: bus





  
  

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  6: train





  
  

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  7: truck





  
  

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  8: boat





  
  

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  9: traffic light





  
  

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  10: fire hydrant





  
  

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  11: stop sign





  
  

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  12: parking meter





  
  

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  13: bench





  
  

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  14: bird





  
  

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  15: cat





  
  

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  16: dog





  
  

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  17: horse





  
  

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  18: sheep





  
  

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  19: cow





  
  

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  20: elephant





  
  

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  21: bear





  
  

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  22: zebra





  
  

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  23: giraffe





  
  

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  24: backpack





  
  

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  25: umbrella





  
  

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  26: handbag





  
  

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  27: tie





  
  

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  28: suitcase





  
  

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  29: frisbee





  
  

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  30: skis





  
  

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  31: snowboard





  
  

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  32: sports ball





  
  

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  33: kite





  
  

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  34: baseball bat





  
  

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  35: baseball glove





  
  

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  36: skateboard





  
  

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  37: surfboard





  
  

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  38: tennis racket





  
  

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  39: bottle





  
  

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  40: wine glass





  
  

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  41: cup





  
  

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  42: fork





  
  

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  43: knife





  
  

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  44: spoon





  
  

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  45: bowl





  
  

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  46: banana





  
  

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  47: apple





  
  

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  48: sandwich





  
  

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  49: orange





  
  

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  50: broccoli





  
  

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  51: carrot





  
  

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  52: hot dog





  
  

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  53: pizza





  
  

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  54: donut





  
  

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  55: cake





  
  

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  56: chair





  
  

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  57: couch





  
  

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  58: potted plant





  
  

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  59: bed





  
  

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  60: dining table





  
  

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  61: toilet





  
  

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  62: tv





  
  

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  63: laptop





  
  

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  64: mouse





  
  

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  65: remote





  
  

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  66: keyboard





  
  

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  67: cell phone





  
  

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  68: microwave





  
  

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  69: oven





  
  

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  70: toaster





  
  

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  71: sink





  
  

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  72: refrigerator





  
  

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  73: book





  
  

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  74: clock





  
  

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  75: vase





  
  

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  76: scissors





  
  

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  77: teddy bear





  
  

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  78: hair drier





  
  

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  79: toothbrush





  
  

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# Download script/URL (optional)





  
  

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download: |





  
  

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  from utils.general import download, Path





  
  

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  # Download labels





  
  

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  segments = False  # segment or box labels





  
  

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  dir = Path(yaml['path'])  # dataset root dir





  
  

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  url = 'https://github.com/ultralytics/yolov5/releases/download/v1.0/'





  
  

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  urls = [url + ('coco2017labels-segments.zip' if segments else 'coco2017labels.zip')]  # labels





  
  

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  download(urls, dir=dir.parent)





  
  

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  # Download data





  
  

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  urls = ['http://images.cocodataset.org/zips/train2017.zip',  # 19G, 118k images





  
  

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          'http://images.cocodataset.org/zips/val2017.zip',  # 1G, 5k images





  
  

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          'http://images.cocodataset.org/zips/test2017.zip']  # 7G, 41k images (optional)





  
  

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  download(urls, dir=dir / 'images', threads=3)