mmsegmentation/configs/beit/upernet_beit-base_640x640_1...

25 lines
763 B
Python

_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)