_base_ = './upernet_beit-base_8x2_640x640_160k_ade20k.py'

img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)

test_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(
        type='MultiScaleFlipAug',
        img_scale=(2560, 640),
        img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
        flip=True,
        transforms=[
            dict(type='Resize', keep_ratio=True, min_size=640),
            dict(type='RandomFlip'),
            dict(type='Normalize', **img_norm_cfg),
            dict(type='ImageToTensor', keys=['img']),
            dict(type='Collect', keys=['img']),
        ])
]
data = dict(
    val=dict(pipeline=test_pipeline),
    test=dict(pipeline=test_pipeline),
    samples_per_gpu=2)