| |
| 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')) |
|
|
