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https://github.com/open-mmlab/mmsegmentation.git
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5245edb0a0
* add config * add cityscapes config * add default value to docstring * fix lint * add deit-s and deit-b * add readme * add eps at norm_cfg * add drop_path_rate experiment * add deit case at init_weight * add upernet result * update result and add upernet 160k config * update upernet result and fix settings * Update iters number * update result and delete some configs * fix import error * fix drop_path_rate * update result and restore config * update benchmark result * remove cityscapes exp * remove neck * neck exp * add more configs * fix init error * fix ffn setting * update result * update results * update result * update results and fill table * delete or rename configs * fix link delimiter * rename configs and fix link * rename neck to mln
9 lines
401 B
Python
9 lines
401 B
Python
_base_ = './upernet_vit-b16_mln_512x512_160k_ade20k.py'
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model = dict(
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pretrained='https://dl.fbaipublicfiles.com/deit/deit_small_patch16_224-cd65a155.pth', # noqa
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backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1),
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decode_head=dict(num_classes=150, in_channels=[384, 384, 384, 384]),
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neck=None,
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auxiliary_head=dict(num_classes=150, in_channels=384)) # yapf: disable
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