29 lines
1.0 KiB
Python
29 lines
1.0 KiB
Python
_base_ = './segnext_mscan-t_1xb16-adamw-160k_ade20k-512x512.py'
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# model settings
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checkpoint_file = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/segnext/mscan_b_20230227-3ab7d230.pth' # noqa
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ham_norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
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model = dict(
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type='EncoderDecoder',
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backbone=dict(
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embed_dims=[64, 128, 320, 512],
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depths=[3, 3, 12, 3],
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init_cfg=dict(type='Pretrained', checkpoint=checkpoint_file),
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drop_path_rate=0.1,
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norm_cfg=dict(type='BN', requires_grad=True)),
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decode_head=dict(
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type='LightHamHead',
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in_channels=[128, 320, 512],
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in_index=[1, 2, 3],
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channels=512,
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ham_channels=512,
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dropout_ratio=0.1,
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num_classes=150,
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norm_cfg=ham_norm_cfg,
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align_corners=False,
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loss_decode=dict(
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
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# model training and testing settings
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train_cfg=dict(),
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test_cfg=dict(mode='whole'))
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