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train: |
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- ../datasets/GlobalWheat2020/images/arvalis_1 |
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- ../datasets/GlobalWheat2020/images/arvalis_2 |
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- ../datasets/GlobalWheat2020/images/arvalis_3 |
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- ../datasets/GlobalWheat2020/images/ethz_1 |
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- ../datasets/GlobalWheat2020/images/rres_1 |
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- ../datasets/GlobalWheat2020/images/inrae_1 |
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- ../datasets/GlobalWheat2020/images/usask_1 |
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val: |
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- ../datasets/GlobalWheat2020/images/ethz_1 |
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test: |
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- ../datasets/GlobalWheat2020/images/utokyo_1 |
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- ../datasets/GlobalWheat2020/images/utokyo_2 |
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- ../datasets/GlobalWheat2020/images/nau_1 |
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- ../datasets/GlobalWheat2020/images/uq_1 |
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nc: 1 |
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names: [ 'wheat_head' ] |
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download: | |
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from utils.general import download, Path |
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dir = Path('../datasets/GlobalWheat2020') |
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urls = ['https://zenodo.org/record/4298502/files/global-wheat-codalab-official.zip', |
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'https://github.com/ultralytics/yolov5/releases/download/v1.0/GlobalWheat2020_labels.zip'] |
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download(urls, dir=dir) |
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for p in 'annotations', 'images', 'labels': |
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(dir / p).mkdir(parents=True, exist_ok=True) |
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for p in 'arvalis_1', 'arvalis_2', 'arvalis_3', 'ethz_1', 'rres_1', 'inrae_1', 'usask_1', \ |
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'utokyo_1', 'utokyo_2', 'nau_1', 'uq_1': |
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(dir / p).rename(dir / 'images' / p) |
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f = (dir / p).with_suffix('.json') |
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if f.exists(): |
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f.rename((dir / 'annotations' / p).with_suffix('.json')) |
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