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_base_ = './beit-base_upernet_8xb2-160k_ade20k-640x640.py'
test_pipeline = [
dict(type='LoadImageFromFile'),
# TODO: Refactor 'MultiScaleFlipAug' which supports
# `min_size` feature in `Resize` class
# img_ratios is [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
# original image scale is (2560, 640)
dict(type='Resize', scale=(2560, 640), keep_ratio=True),
# add loading annotation after ``Resize`` because ground truth
# does not need to do resize data transform
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='PackSegInputs'),
]
val_dataloader = dict(batch_size=1, dataset=dict(pipeline=test_pipeline))
test_dataloader = val_dataloader
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