_base_ = [ '/home/liuziyuan/proj/rmcd-kd/configs/_base_/models/KD-lightcdnet.py', '/home/liuziyuan/proj/rmcd-kd/configs/common/standard_512x512_200k_cgwx.py'] dataset_type = 'LEVIR_CD_Dataset' data_root = '/nas/datasets/lzy/RS-ChangeDetection/CGWX' crop_size = (512, 512) checkpoint_student = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/initial/best_mIoU_iter_195000.pth' checkpoint_teacher_l = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/large/best_mIoU_iter_185000.pth' checkpoint_teacher_m = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/medium/best_mIoU_iter_199000.pth' checkpoint_teacher_s = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/small/best_mIoU_iter_193000.pth' model = dict( # student init_cfg=dict(type='Pretrained', checkpoint=checkpoint_student), # teacher large init_cfg_t_l = dict(type='Pretrained', checkpoint=checkpoint_teacher_l), # teacher medium init_cfg_t_m = dict(type='Pretrained', checkpoint=checkpoint_teacher_m), # teacher small init_cfg_t_s = dict(type='Pretrained', checkpoint=checkpoint_teacher_s), decode_head=dict( sampler=dict(type='mmseg.OHEMPixelSampler', thresh=0.7, min_kept=100000))) # optimizer optimizer = dict( type='AdamW', lr=0.003, betas=(0.9, 0.999), weight_decay=0.05) 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=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=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)))