| _base_ = './ocrnet_hr18_512x1024_40k_cityscapes.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=19, | |
| 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=19, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)) | |
| ]) | |