mirror of
https://github.com/open-mmlab/mmsegmentation.git
synced 2025-06-03 22:03:48 +08:00
81 lines
2.4 KiB
Python
81 lines
2.4 KiB
Python
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# model settings
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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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pretrained=None,
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backbone=dict(
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type='BiSeNetV2',
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detail_channels=(64, 64, 128),
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semantic_channels=(16, 32, 64, 128),
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semantic_expansion_ratio=6,
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bga_channels=128,
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out_indices=(0, 1, 2, 3, 4),
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init_cfg=None,
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align_corners=False),
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decode_head=dict(
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type='FCNHead',
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in_channels=128,
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in_index=0,
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channels=1024,
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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=19,
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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=[
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dict(
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type='FCNHead',
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in_channels=16,
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channels=16,
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num_convs=2,
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num_classes=19,
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in_index=1,
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norm_cfg=norm_cfg,
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concat_input=False,
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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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dict(
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type='FCNHead',
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in_channels=32,
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channels=64,
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num_convs=2,
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num_classes=19,
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in_index=2,
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norm_cfg=norm_cfg,
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concat_input=False,
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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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dict(
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type='FCNHead',
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in_channels=64,
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channels=256,
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num_convs=2,
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num_classes=19,
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in_index=3,
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norm_cfg=norm_cfg,
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concat_input=False,
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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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dict(
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type='FCNHead',
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in_channels=128,
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channels=1024,
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num_convs=2,
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num_classes=19,
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in_index=4,
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norm_cfg=norm_cfg,
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concat_input=False,
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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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],
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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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