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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=None, | |
| backbone=dict( | |
| type='MixVisionTransformer', | |
| in_channels=3, | |
| embed_dims=32, | |
| num_stages=4, | |
| num_layers=[2, 2, 2, 2], | |
| num_heads=[1, 2, 5, 8], | |
| patch_sizes=[7, 3, 3, 3], | |
| sr_ratios=[8, 4, 2, 1], | |
| out_indices=(0, 1, 2, 3), | |
| mlp_ratio=4, | |
| qkv_bias=True, | |
| drop_rate=0.0, | |
| attn_drop_rate=0.0, | |
| drop_path_rate=0.1), | |
| decode_head=dict( | |
| type='SegformerHead', | |
| in_channels=[32, 64, 160, 256], | |
| in_index=[0, 1, 2, 3], | |
| channels=256, | |
| 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)), | |
| # model training and testing settings | |
| train_cfg=dict(), | |
| test_cfg=dict(mode='whole')) | |