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https://github.com/open-mmlab/mmsegmentation.git
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86d473002f
* added cgnet * added testing for cgnet * git test * add cgnet * fix __init__ * rename FGlo with GlobalContextExtractor * add readme.md and rename bn with norm * delete cg_head * fix a language mistake * rename cgnet_m3n21.py to cgnet.py * modify README.md * modify list to tuple * add fcn_head test * add assert to fcn_head * blank * fix fcn_head assert bug * add * add cgnet to README.md and model_zoo.md * modify cgnet README.md Co-authored-by: KID <wps_@mail.nankai.edu.cn>
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
# model settings
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norm_cfg = dict(type='SyncBN', eps=1e-03, 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='CGNet',
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norm_cfg=norm_cfg,
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in_channels=3,
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num_channels=(32, 64, 128),
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num_blocks=(3, 21),
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dilations=(2, 4),
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reductions=(8, 16)),
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decode_head=dict(
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type='FCNHead',
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in_channels=256,
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in_index=2,
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channels=256,
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num_convs=0,
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concat_input=False,
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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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loss_decode=dict(
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type='CrossEntropyLoss',
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use_sigmoid=False,
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loss_weight=1.0,
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class_weight=[
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2.5959933, 6.7415504, 3.5354059, 9.8663225, 9.690899, 9.369352,
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10.289121, 9.953208, 4.3097677, 9.490387, 7.674431, 9.396905,
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10.347791, 6.3927646, 10.226669, 10.241062, 10.280587,
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10.396974, 10.055647
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])))
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# model training and testing settings
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train_cfg = dict(sampler=None)
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test_cfg = dict(mode='whole')
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