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2b79cff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | _base_ = [
'/home/liuziyuan/proj/RS-CD/rs-cd-cgwx/configs/_base_/models/changer_s50.py',
'/home/liuziyuan/proj/RS-CD/rs-cd-cgwx/configs/common/standard_512x512_200k_cgwx.py']
crop_size = (512, 512)
model = dict(
backbone=dict(
interaction_cfg=(
None,
dict(type='SpatialExchange', p=1/2),
dict(type='ChannelExchange', p=1/2),
dict(type='ChannelExchange', p=1/2))
),
decode_head=dict(
num_classes=2,
sampler=dict(type='mmseg.OHEMPixelSampler', thresh=0.7, min_kept=100000)),
# test_cfg=dict(mode='slide', crop_size=crop_size, stride=(crop_size[0]//2, crop_size[1]//2)),
)
train_pipeline = [
dict(type='MultiImgLoadImageFromFile'),
dict(type='MultiImgLoadAnnotations'),
dict(type='MultiImgRandomRotFlip', rotate_prob=0.5, flip_prob=0.5, degree=(-20, 20)),
dict(type='MultiImgRandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
dict(type='MultiImgExchangeTime', prob=0.5),
dict(
type='MultiImgPhotoMetricDistortion',
brightness_delta=10,
contrast_range=(0.8, 1.2),
saturation_range=(0.8, 1.2),
hue_delta=10),
dict(type='MultiImgPackSegInputs')
]
train_dataloader = dict(
dataset=dict(pipeline=train_pipeline))
# optimizer
optimizer=dict(
type='AdamW', lr=0.005, betas=(0.9, 0.999), weight_decay=0.05)
optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer)
# compile = True # use PyTorch 2.x |