|
|
|
norm_cfg = dict(type='SyncBN', requires_grad=True, momentum=0.01) |
|
model = dict( |
|
type='EncoderDecoder', |
|
backbone=dict( |
|
type='FastSCNN', |
|
downsample_dw_channels=(32, 48), |
|
global_in_channels=64, |
|
global_block_channels=(64, 96, 128), |
|
global_block_strides=(2, 2, 1), |
|
global_out_channels=128, |
|
higher_in_channels=64, |
|
lower_in_channels=128, |
|
fusion_out_channels=128, |
|
out_indices=(0, 1, 2), |
|
norm_cfg=norm_cfg, |
|
align_corners=False), |
|
decode_head=dict( |
|
type='DepthwiseSeparableFCNHead', |
|
in_channels=128, |
|
channels=128, |
|
concat_input=False, |
|
num_classes=19, |
|
in_index=-1, |
|
norm_cfg=norm_cfg, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=0.4)), |
|
auxiliary_head=[ |
|
dict( |
|
type='FCNHead', |
|
in_channels=128, |
|
channels=32, |
|
num_convs=1, |
|
num_classes=19, |
|
in_index=-2, |
|
norm_cfg=norm_cfg, |
|
concat_input=False, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=0.4)), |
|
dict( |
|
type='FCNHead', |
|
in_channels=64, |
|
channels=32, |
|
num_convs=1, |
|
num_classes=19, |
|
in_index=-3, |
|
norm_cfg=norm_cfg, |
|
concat_input=False, |
|
align_corners=False, |
|
loss_decode=dict( |
|
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=0.4)), |
|
], |
|
|
|
train_cfg=dict(), |
|
test_cfg=dict(mode='whole')) |
|
|
