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| # Ultralytics YOLO 🚀, AGPL-3.0 license | |
| # COCO 2017 dataset https://cocodataset.org by Microsoft | |
| # Documentation: https://docs.ultralytics.com/datasets/detect/coco/ | |
| # Example usage: yolo train data=coco.yaml | |
| # parent | |
| # ├── ultralytics | |
| # └── datasets | |
| # └── coco ← downloads here (20.1 GB) | |
| # 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, ..] | |
| path: ../datasets/coco # dataset root dir | |
| train: train2017.txt # train images (relative to 'path') 118287 images | |
| val: val2017.txt # val images (relative to 'path') 5000 images | |
| test: test-dev2017.txt # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794 | |
| # Classes | |
| names: | |
| 0: person | |
| 1: bicycle | |
| 2: car | |
| 3: motorcycle | |
| 4: airplane | |
| 5: bus | |
| 6: train | |
| 7: truck | |
| 8: boat | |
| 9: traffic light | |
| 10: fire hydrant | |
| 11: stop sign | |
| 12: parking meter | |
| 13: bench | |
| 14: bird | |
| 15: cat | |
| 16: dog | |
| 17: horse | |
| 18: sheep | |
| 19: cow | |
| 20: elephant | |
| 21: bear | |
| 22: zebra | |
| 23: giraffe | |
| 24: backpack | |
| 25: umbrella | |
| 26: handbag | |
| 27: tie | |
| 28: suitcase | |
| 29: frisbee | |
| 30: skis | |
| 31: snowboard | |
| 32: sports ball | |
| 33: kite | |
| 34: baseball bat | |
| 35: baseball glove | |
| 36: skateboard | |
| 37: surfboard | |
| 38: tennis racket | |
| 39: bottle | |
| 40: wine glass | |
| 41: cup | |
| 42: fork | |
| 43: knife | |
| 44: spoon | |
| 45: bowl | |
| 46: banana | |
| 47: apple | |
| 48: sandwich | |
| 49: orange | |
| 50: broccoli | |
| 51: carrot | |
| 52: hot dog | |
| 53: pizza | |
| 54: donut | |
| 55: cake | |
| 56: chair | |
| 57: couch | |
| 58: potted plant | |
| 59: bed | |
| 60: dining table | |
| 61: toilet | |
| 62: tv | |
| 63: laptop | |
| 64: mouse | |
| 65: remote | |
| 66: keyboard | |
| 67: cell phone | |
| 68: microwave | |
| 69: oven | |
| 70: toaster | |
| 71: sink | |
| 72: refrigerator | |
| 73: book | |
| 74: clock | |
| 75: vase | |
| 76: scissors | |
| 77: teddy bear | |
| 78: hair drier | |
| 79: toothbrush | |
| # Download script/URL (optional) | |
| download: | | |
| from ultralytics.utils.downloads import download | |
| from pathlib import Path | |
| # Download labels | |
| segments = True # segment or box labels | |
| dir = Path(yaml['path']) # dataset root dir | |
| url = 'https://github.com/ultralytics/yolov5/releases/download/v1.0/' | |
| urls = [url + ('coco2017labels-segments.zip' if segments else 'coco2017labels.zip')] # labels | |
| download(urls, dir=dir.parent) | |
| # Download data | |
| urls = ['http://images.cocodataset.org/zips/train2017.zip', # 19G, 118k images | |
| 'http://images.cocodataset.org/zips/val2017.zip', # 1G, 5k images | |
| 'http://images.cocodataset.org/zips/test2017.zip'] # 7G, 41k images (optional) | |
| download(urls, dir=dir / 'images', threads=3) | |