2020-07-07 20:52:19 +08:00
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_base_ = './cityscapes.py'
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crop_size = (769, 769)
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train_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='LoadAnnotations'),
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2022-05-31 22:28:42 +08:00
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dict(type='RandomResize', scale=(2049, 1025), ratio_range=(0.5, 2.0)),
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2022-05-27 21:52:49 +08:00
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dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
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2020-11-08 01:53:12 +08:00
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dict(type='RandomFlip', prob=0.5),
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2020-07-07 20:52:19 +08:00
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dict(type='PhotoMetricDistortion'),
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2022-05-31 22:28:42 +08:00
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dict(type='PackSegInputs')
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2020-07-07 20:52:19 +08:00
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]
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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2022-05-31 22:28:42 +08:00
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dict(type='Resize', scale=(2049, 1025), keep_ratio=True),
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2022-06-13 13:33:34 +08:00
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# add loading annotation after ``Resize`` because ground truth
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# does not need to do resize data transform
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dict(type='LoadAnnotations'),
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2022-05-31 22:28:42 +08:00
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dict(type='PackSegInputs')
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2020-07-07 20:52:19 +08:00
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]
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2022-05-31 22:28:42 +08:00
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train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
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val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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test_dataloader = val_dataloader
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2022-06-08 16:22:42 +08:00
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val_evaluator = dict(type='IoUMetric', metrics=['mIoU'])
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test_evaluator = val_evaluator
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