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* [Enhancement] Change readme style and prepare for metafiles update. * Update apcnet github repo url. * add code snippet. * split code snippet & official repo. * update md2yml hook. * Update metafiles. * Add converted from attribute. * process conflict. * Put defualt variable value. * update bisenet v2 metafile. * checkout to ubuntu environment. * pop empty attribute & make task attribute list. * update readme style * update readme style * update metafiles Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
98 lines
2.9 KiB
YAML
98 lines
2.9 KiB
YAML
Collections:
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- Name: setr
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Metadata:
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Training Data:
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- ADE20K
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Paper:
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URL: https://arxiv.org/abs/2012.15840
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Title: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective
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with Transformers
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README: configs/setr/README.md
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Code:
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URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/setr_up_head.py#L11
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Version: v0.17.0
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Converted From:
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Code: https://github.com/fudan-zvg/SETR
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Models:
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- Name: setr_naive_512x512_160k_b16_ade20k
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In Collection: setr
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Metadata:
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backbone: ViT-L
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 211.86
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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memory (GB): 18.4
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 48.28
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mIoU(ms+flip): 49.56
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Config: configs/setr/setr_naive_512x512_160k_b16_ade20k.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/setr/setr_naive_512x512_160k_b16_ade20k/setr_naive_512x512_160k_b16_ade20k_20210619_191258-061f24f5.pth
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- Name: setr_pup_512x512_160k_b16_ade20k
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In Collection: setr
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Metadata:
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backbone: ViT-L
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 222.22
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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memory (GB): 19.54
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 48.24
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mIoU(ms+flip): 49.99
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Config: configs/setr/setr_pup_512x512_160k_b16_ade20k.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/setr/setr_pup_512x512_160k_b16_ade20k/setr_pup_512x512_160k_b16_ade20k_20210619_191343-7e0ce826.pth
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- Name: setr_mla_512x512_160k_b8_ade20k
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In Collection: setr
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Metadata:
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backbone: ViT-L
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crop size: (512,512)
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lr schd: 160000
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memory (GB): 10.96
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 47.34
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mIoU(ms+flip): 49.05
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Config: configs/setr/setr_mla_512x512_160k_b8_ade20k.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/setr/setr_mla_512x512_160k_b8_ade20k/setr_mla_512x512_160k_b8_ade20k_20210619_191118-c6d21df0.pth
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- Name: setr_mla_512x512_160k_b16_ade20k
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In Collection: setr
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Metadata:
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backbone: ViT-L
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 190.48
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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memory (GB): 17.3
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 47.54
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mIoU(ms+flip): 49.37
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Config: configs/setr/setr_mla_512x512_160k_b16_ade20k.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/setr/setr_mla_512x512_160k_b16_ade20k/setr_mla_512x512_160k_b16_ade20k_20210619_191057-f9741de7.pth
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