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| # model settings | |
| norm_cfg = dict(type='SyncBN', requires_grad=True) | |
| data_preprocessor = dict( | |
| type='SegDataPreProcessor', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| bgr_to_rgb=True, | |
| pad_val=0, | |
| seg_pad_val=255) | |
| model = dict( | |
| type='EncoderDecoder', | |
| data_preprocessor=data_preprocessor, | |
| pretrained='pretrain/jx_vit_base_p16_224-80ecf9dd.pth', | |
| backbone=dict( | |
| type='VisionTransformer', | |
| img_size=(512, 512), | |
| patch_size=16, | |
| in_channels=3, | |
| embed_dims=768, | |
| num_layers=12, | |
| num_heads=12, | |
| mlp_ratio=4, | |
| out_indices=(2, 5, 8, 11), | |
| qkv_bias=True, | |
| drop_rate=0.0, | |
| attn_drop_rate=0.0, | |
| drop_path_rate=0.0, | |
| with_cls_token=True, | |
| norm_cfg=dict(type='LN', eps=1e-6), | |
| act_cfg=dict(type='GELU'), | |
| norm_eval=False, | |
| interpolate_mode='bicubic'), | |
| neck=dict( | |
| type='MultiLevelNeck', | |
| in_channels=[768, 768, 768, 768], | |
| out_channels=768, | |
| scales=[4, 2, 1, 0.5]), | |
| decode_head=dict( | |
| type='UPerHead', | |
| in_channels=[768, 768, 768, 768], | |
| in_index=[0, 1, 2, 3], | |
| pool_scales=(1, 2, 3, 6), | |
| channels=512, | |
| dropout_ratio=0.1, | |
| num_classes=19, | |
| norm_cfg=norm_cfg, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), | |
| auxiliary_head=dict( | |
| type='FCNHead', | |
| in_channels=768, | |
| in_index=3, | |
| channels=256, | |
| num_convs=1, | |
| concat_input=False, | |
| dropout_ratio=0.1, | |
| num_classes=19, | |
| norm_cfg=norm_cfg, | |
| align_corners=False, | |
| loss_decode=dict( | |
| type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), | |
| # model training and testing settings | |
| train_cfg=dict(), | |
| test_cfg=dict(mode='whole')) # yapf: disable | |