|
_base_ = [ |
|
'../_base_/models/setr_mla.py', '../_base_/datasets/ade20k.py', |
|
'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' |
|
] |
|
crop_size = (512, 512) |
|
data_preprocessor = dict(size=crop_size) |
|
norm_cfg = dict(type='SyncBN', requires_grad=True) |
|
model = dict( |
|
data_preprocessor=data_preprocessor, |
|
pretrained=None, |
|
backbone=dict( |
|
img_size=(512, 512), |
|
drop_rate=0., |
|
init_cfg=dict( |
|
type='Pretrained', checkpoint='pretrain/vit_large_p16.pth')), |
|
decode_head=dict(num_classes=150), |
|
auxiliary_head=[ |
|
dict( |
|
type='FCNHead', |
|
in_channels=256, |
|
channels=256, |
|
in_index=0, |
|
dropout_ratio=0, |
|
norm_cfg=norm_cfg, |
|
act_cfg=dict(type='ReLU'), |
|
num_convs=0, |
|
kernel_size=1, |
|
concat_input=False, |
|
num_classes=150, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
|
dict( |
|
type='FCNHead', |
|
in_channels=256, |
|
channels=256, |
|
in_index=1, |
|
dropout_ratio=0, |
|
norm_cfg=norm_cfg, |
|
act_cfg=dict(type='ReLU'), |
|
num_convs=0, |
|
kernel_size=1, |
|
concat_input=False, |
|
num_classes=150, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
|
dict( |
|
type='FCNHead', |
|
in_channels=256, |
|
channels=256, |
|
in_index=2, |
|
dropout_ratio=0, |
|
norm_cfg=norm_cfg, |
|
act_cfg=dict(type='ReLU'), |
|
num_convs=0, |
|
kernel_size=1, |
|
concat_input=False, |
|
num_classes=150, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
|
dict( |
|
type='FCNHead', |
|
in_channels=256, |
|
channels=256, |
|
in_index=3, |
|
dropout_ratio=0, |
|
norm_cfg=norm_cfg, |
|
act_cfg=dict(type='ReLU'), |
|
num_convs=0, |
|
kernel_size=1, |
|
concat_input=False, |
|
num_classes=150, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
|
], |
|
test_cfg=dict(mode='slide', crop_size=(512, 512), stride=(341, 341)), |
|
) |
|
|
|
optimizer = dict(lr=0.001, weight_decay=0.0) |
|
optim_wrapper = dict( |
|
type='OptimWrapper', |
|
optimizer=optimizer, |
|
paramwise_cfg=dict(custom_keys={'head': dict(lr_mult=10.)})) |
|
|
|
train_dataloader = dict(batch_size=1) |
|
val_dataloader = dict(batch_size=1) |
|
test_dataloader = val_dataloader |
|
|