45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
# dataset settings
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dataset_type = 'CityscapesDataset'
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data_root = 'data/cityscapes/'
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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crop_size = (512, 1024)
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train_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='LoadAnnotations'),
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dict(type='RandomResize', scale=(2048, 1024), ratio_range=(0.5, 2.0)),
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dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
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dict(type='RandomFlip', prob=0.5),
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dict(type='PhotoMetricDistortion'),
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dict(type='Pad', size=crop_size),
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dict(type='PackSegInputs')
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]
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='Resize', scale=(2048, 1024), keep_ratio=True),
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dict(type='PackSegInputs')
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]
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train_dataloader = dict(
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batch_size=2,
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num_workers=2,
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persistent_workers=True,
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sampler=dict(type='DefaultSampler', shuffle=True),
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dataset=dict(
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type=dataset_type,
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data_root=data_root,
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data_prefix=dict(
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img_path='leftImg8bit/train', seg_map_path='gtFine/train'),
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pipeline=train_pipeline))
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val_dataloader = dict(
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batch_size=4,
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num_workers=4,
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persistent_workers=True,
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sampler=dict(type='DefaultSampler', shuffle=False),
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dataset=dict(
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type=dataset_type,
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data_root=data_root,
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data_prefix=dict(
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img_path='leftImg8bit/val', seg_map_path='gtFine/val'),
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pipeline=test_pipeline))
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test_dataloader = val_dataloader
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