mirror of
https://github.com/open-mmlab/mmsegmentation.git
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d966f98f83
* add icnet backbone * add icnet head * add icnet configs * nclass -> num_classes * Support ICNet * ICNet * ICNet * Add ICNeck * Add ICNeck * Add ICNeck * Add ICNeck * Adding unittest * Uploading models & logs * Uploading models & logs * add comment * smaller test_swin.py * try to delete test_swin.py * delete test_unet.py * delete test_unet.py * temp * smaller test_unet.py Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
75 lines
2.1 KiB
Python
75 lines
2.1 KiB
Python
# 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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backbone=dict(
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type='ICNet',
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backbone_cfg=dict(
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type='ResNetV1c',
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in_channels=3,
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depth=50,
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num_stages=4,
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out_indices=(0, 1, 2, 3),
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dilations=(1, 1, 2, 4),
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strides=(1, 2, 1, 1),
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norm_cfg=norm_cfg,
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norm_eval=False,
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style='pytorch',
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contract_dilation=True),
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in_channels=3,
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layer_channels=(512, 2048),
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light_branch_middle_channels=32,
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psp_out_channels=512,
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out_channels=(64, 256, 256),
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norm_cfg=norm_cfg,
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align_corners=False,
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),
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neck=dict(
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type='ICNeck',
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in_channels=(64, 256, 256),
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out_channels=128,
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norm_cfg=norm_cfg,
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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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channels=128,
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num_convs=1,
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in_index=2,
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dropout_ratio=0,
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num_classes=19,
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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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auxiliary_head=[
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dict(
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type='FCNHead',
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in_channels=128,
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channels=128,
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num_convs=1,
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num_classes=19,
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in_index=0,
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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=0.4)),
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dict(
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type='FCNHead',
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in_channels=128,
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channels=128,
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num_convs=1,
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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=0.4)),
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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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