53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
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# model settings
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backbone_norm_cfg = dict(type='LN')
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norm_cfg = dict(type='SyncBN', 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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type='PCPVT',
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init_cfg=dict(
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type='Pretrained', checkpoint='pretrained/pcpvt_small.pth'),
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in_channels=3,
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embed_dims=[64, 128, 320, 512],
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num_heads=[1, 2, 5, 8],
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patch_sizes=[4, 2, 2, 2],
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strides=[4, 2, 2, 2],
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mlp_ratios=[8, 8, 4, 4],
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out_indices=(0, 1, 2, 3),
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qkv_bias=True,
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norm_cfg=backbone_norm_cfg,
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depths=[3, 4, 6, 3],
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sr_ratios=[8, 4, 2, 1],
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norm_after_stage=False,
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drop_rate=0.0,
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attn_drop_rate=0.,
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drop_path_rate=0.2),
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decode_head=dict(
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type='UPerHead',
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in_channels=[64, 128, 320, 512],
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in_index=[0, 1, 2, 3],
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pool_scales=(1, 2, 3, 6),
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channels=512,
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dropout_ratio=0.1,
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num_classes=150,
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norm_cfg=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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auxiliary_head=dict(
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type='FCNHead',
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in_channels=320,
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in_index=2,
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channels=256,
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num_convs=1,
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concat_input=False,
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dropout_ratio=0.1,
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num_classes=150,
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norm_cfg=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=0.4)),
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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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