| _base_ = './ocrnet_hr18_512x512_80k_ade20k.py' |
| norm_cfg = dict(type='SyncBN', requires_grad=True) |
| model = dict( |
| pretrained='open-mmlab://msra/hrnetv2_w48', |
| backbone=dict( |
| extra=dict( |
| stage2=dict(num_channels=(48, 96)), |
| stage3=dict(num_channels=(48, 96, 192)), |
| stage4=dict(num_channels=(48, 96, 192, 384)))), |
| decode_head=[ |
| dict( |
| type='FCNHead', |
| in_channels=[48, 96, 192, 384], |
| channels=sum([48, 96, 192, 384]), |
| input_transform='resize_concat', |
| in_index=(0, 1, 2, 3), |
| kernel_size=1, |
| num_convs=1, |
| norm_cfg=norm_cfg, |
| concat_input=False, |
| dropout_ratio=-1, |
| num_classes=150, |
| align_corners=False, |
| loss_decode=dict( |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), |
| dict( |
| type='OCRHead', |
| in_channels=[48, 96, 192, 384], |
| channels=512, |
| ocr_channels=256, |
| input_transform='resize_concat', |
| in_index=(0, 1, 2, 3), |
| norm_cfg=norm_cfg, |
| dropout_ratio=-1, |
| num_classes=150, |
| align_corners=False, |
| loss_decode=dict( |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)) |
| ]) |
|
|
