ChangeFormer-mit-b0/small/config.py

_base_ = [
    '/home/liuziyuan/proj/RS-CD/rs-cd-cgwx/configs/_base_/models/changeformer_mit-b0.py', 
    '/home/liuziyuan/proj/RS-CD/rs-cd-cgwx/configs/common/train_small_512x512_100k_cgwx.py']

dataset_type = 'LEVIR_CD_Dataset'
data_root = '/nas/datasets/lzy/RS-ChangeDetection/CGWX'

crop_size = (512, 512)

checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/segformer/mit_b0_20220624-7e0fe6dd.pth'  # noqa

model = dict(pretrained=checkpoint, decode_head=dict(num_classes=2))

# optimizer
optimizer=dict(
    type='AdamW', lr=0.00006, betas=(0.9, 0.999), weight_decay=0.01)

optim_wrapper = dict(
    _delete_=True,
    type='OptimWrapper',
    optimizer=optimizer,
    paramwise_cfg=dict(
        custom_keys={
            'pos_block': dict(decay_mult=0.),
            'norm': dict(decay_mult=0.),
            'head': dict(lr_mult=10.)
        }))

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=100000,
        eta_min=0.0,
        by_epoch=False,
    )
]

# training schedule for 100k
train_cfg = dict(type='IterBasedTrainLoop', max_iters=100000, val_interval=1000)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
default_hooks = dict(
    timer=dict(type='IterTimerHook'),
    logger=dict(type='LoggerHook', interval=50, 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)))