| |
| norm_cfg = dict(type='SyncBN', requires_grad=True) |
| model = dict( |
| type='EncoderDecoder', |
| backbone=dict( |
| type='VisionTransformer', |
| model_name='vit_base_patch16_224', |
| img_size=768, |
| patch_size=16, |
| in_chans=3, |
| embed_dim=1024, |
| depth=24, |
| num_heads=16, |
| num_classes=19, |
| drop_rate=0.1, |
| norm_cfg=norm_cfg, |
| pos_embed_interp=True, |
| align_corners=False, |
| ), |
| decode_head=dict( |
| type='VisionTransformerUpHead', |
| in_channels=1024, |
| channels=512, |
| in_index=23, |
| img_size=768, |
| embed_dim=1024, |
| num_classes=19, |
| norm_cfg=norm_cfg, |
| num_conv=2, |
| upsampling_method='bilinear', |
| align_corners=False, |
| loss_decode=dict( |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))) |
| |
| train_cfg = dict() |
| test_cfg = dict(mode='whole') |
|
|
