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## Motivation The original version of Visual Attention Network (VAN) can be found from https://github.com/Visual-Attention-Network/VAN-Segmentation 添加Visual Attention Network (VAN)的支持。 ## Modification added a floder mmsegmentation/projects/van/ added 13 configs totally and aligned performance basically. 只增加了一个文件夹，共增加13个配置文件，基本对齐性能（没有全部跑）。 ## Use cases (Optional) Before running, you may need to download the pretrain model from https://cloud.tsinghua.edu.cn/d/0100f0cea37d41ba8d08/ and then move them to the folder mmsegmentation/pretrained/, i.e. "mmsegmentation/pretrained/van_b2.pth". After that, run the following command: cd mmsegmentation bash tools/dist_train.sh projects/van/configs/van/van-b2_pre1k_upernet_4xb2-160k_ade20k-512x512.py 4 --------- Co-authored-by: xiexinch <xiexinch@outlook.com>
15 lines
546 B
Python
15 lines
546 B
Python
# dataset settings
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_base_ = '../../../../../configs/_base_/datasets/ade20k.py'
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='Resize', scale=(2048, 512), keep_ratio=True),
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dict(type='ResizeToMultiple', size_divisor=32),
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# add loading annotation after ``Resize`` because ground truth
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# does not need to do resize data transform
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dict(type='LoadAnnotations', reduce_zero_label=True),
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dict(type='PackSegInputs')
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]
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val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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test_dataloader = val_dataloader
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