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_base_ = [ |
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'../_base_/models/setr_naive.py', '../_base_/datasets/ade20k.py', |
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' |
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] |
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crop_size = (512, 512) |
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data_preprocessor = dict(size=crop_size) |
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norm_cfg = dict(type='SyncBN', requires_grad=True) |
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model = dict( |
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data_preprocessor=data_preprocessor, |
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pretrained=None, |
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backbone=dict( |
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img_size=(512, 512), |
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drop_rate=0., |
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init_cfg=dict( |
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type='Pretrained', checkpoint='pretrain/vit_large_p16.pth')), |
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decode_head=dict(num_classes=150), |
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auxiliary_head=[ |
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dict( |
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type='SETRUPHead', |
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in_channels=1024, |
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channels=256, |
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in_index=0, |
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num_classes=150, |
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dropout_ratio=0, |
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norm_cfg=norm_cfg, |
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act_cfg=dict(type='ReLU'), |
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num_convs=2, |
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kernel_size=1, |
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align_corners=False, |
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loss_decode=dict( |
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
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dict( |
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type='SETRUPHead', |
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in_channels=1024, |
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channels=256, |
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in_index=1, |
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num_classes=150, |
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dropout_ratio=0, |
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norm_cfg=norm_cfg, |
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act_cfg=dict(type='ReLU'), |
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num_convs=2, |
|
kernel_size=1, |
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align_corners=False, |
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loss_decode=dict( |
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
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dict( |
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type='SETRUPHead', |
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in_channels=1024, |
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channels=256, |
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in_index=2, |
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num_classes=150, |
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dropout_ratio=0, |
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norm_cfg=norm_cfg, |
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act_cfg=dict(type='ReLU'), |
|
num_convs=2, |
|
kernel_size=1, |
|
align_corners=False, |
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loss_decode=dict( |
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)) |
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], |
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test_cfg=dict(mode='slide', crop_size=(512, 512), stride=(341, 341)), |
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) |
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|
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optimizer = dict(lr=0.01, weight_decay=0.0) |
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optim_wrapper = dict( |
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type='OptimWrapper', |
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optimizer=optimizer, |
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paramwise_cfg=dict(custom_keys={'head': dict(lr_mult=10.)})) |
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|
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train_dataloader = dict(batch_size=2) |
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val_dataloader = dict(batch_size=1) |
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test_dataloader = val_dataloader |
|
|
