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import os |
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from .base_dataset import BaseDataset |
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from config import DATA_ROOT |
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'''dataset source: https://hci.iwr.uni-heidelberg.de/content/weakly-supervised-learning-industrial-optical-inspection''' |
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DAGM_CLS_NAMES = [ |
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'Class1', 'Class2', 'Class3', 'Class4', 'Class5','Class6','Class7','Class8','Class9','Class10', |
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] |
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DAGM_ROOT = os.path.join(DATA_ROOT, 'DAGM_anomaly_detection') |
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class DAGMDataset(BaseDataset): |
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def __init__(self, transform, target_transform, clsnames=DAGM_CLS_NAMES, aug_rate=0.0, root=DAGM_ROOT, training=True): |
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super(DAGMDataset, self).__init__( |
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clsnames=clsnames, transform=transform, target_transform=target_transform, |
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root=root, aug_rate=aug_rate, training=training |
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) |
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