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_base_ = [
'/home/liuziyuan/proj/RS-CD/rs-cd-cgwx/configs/_base_/models/tinycd.py',
'/home/liuziyuan/proj/RS-CD/rs-cd-cgwx/configs/common/train_medium_512x512_100k_cgwx.py']
dataset_type = 'LEVIR_CD_Dataset'
data_root = '/nas/datasets/lzy/RS-ChangeDetection/CGWX'
crop_size = (512, 512)
model = dict(
decode_head=dict(num_classes=2, out_channels=1),
# test_cfg=dict(mode='slide', crop_size=crop_size, stride=(crop_size[0]//2, crop_size[1]//2))
)
# optimizer
optimizer = dict(
type='AdamW',
lr=0.00356799066427741,
betas=(0.9, 0.999),
weight_decay=0.009449677083344786)
optim_wrapper = dict(
_delete_=True,
type='OptimWrapper',
optimizer=optimizer)
param_scheduler = [
dict(
type='LinearLR', start_factor=1e-6, by_epoch=False, begin=0, end=1000),
dict(
type='PolyLR',
power=1.0,
begin=1000,
end=200000,
eta_min=0.0,
by_epoch=False,
)
]
# training schedule for 100k
train_cfg = dict(type='IterBasedTrainLoop', max_iters=200000, val_interval=1000)
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=100, log_metric_by_epoch=False),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=1000,
save_best='mIoU'),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(type='CDVisualizationHook', interval=1,
img_shape=(512, 512, 3))) |