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# YOLOv5 🚀 by Ultralytics, AGPL-3.0 license |
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# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics |
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# Example usage: python train.py --data coco128.yaml |
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# parent |
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# ├── yolov5 |
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# └── datasets |
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# └── coco128 ← downloads here (7 MB) |
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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/coco128 # dataset root dir |
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train: images/train2017 # train images (relative to 'path') 128 images |
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val: images/train2017 # val images (relative to 'path') 128 images |
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test: # test images (optional) |
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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: https://ultralytics.com/assets/coco128.zip |