Spaces:
Runtime error
Runtime error
| # model settings | |
| norm_cfg = dict(type='SyncBN', requires_grad=True) | |
| backbone_norm_cfg = dict(type='LN', 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=None, | |
| backbone=dict( | |
| type='SwinTransformer', | |
| pretrain_img_size=224, | |
| embed_dims=96, | |
| patch_size=4, | |
| window_size=7, | |
| mlp_ratio=4, | |
| depths=[2, 2, 6, 2], | |
| num_heads=[3, 6, 12, 24], | |
| strides=(4, 2, 2, 2), | |
| out_indices=(0, 1, 2, 3), | |
| qkv_bias=True, | |
| qk_scale=None, | |
| patch_norm=True, | |
| drop_rate=0., | |
| attn_drop_rate=0., | |
| drop_path_rate=0.3, | |
| use_abs_pos_embed=False, | |
| act_cfg=dict(type='GELU'), | |
| norm_cfg=backbone_norm_cfg), | |
| decode_head=dict( | |
| type='UPerHead', | |
| in_channels=[96, 192, 384, 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=384, | |
| in_index=2, | |
| 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')) | |