c11da07e18
* delete convert function and add instruction to README.md * unified model convert and README * remove url * fix import error * fix unittest * rename pretrain * rename vit and deit pretrain * Update upernet_deit-b16_512x512_160k_ade20k.py * Update upernet_deit-b16_512x512_80k_ade20k.py * Update upernet_deit-b16_ln_mln_512x512_160k_ade20k.py * Update upernet_deit-b16_mln_512x512_160k_ade20k.py * Update upernet_deit-s16_512x512_160k_ade20k.py * Update upernet_deit-s16_512x512_80k_ade20k.py * Update upernet_deit-s16_ln_mln_512x512_160k_ade20k.py * Update upernet_deit-s16_mln_512x512_160k_ade20k.py Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com> Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn> |
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| .. | ||
| README.md | ||
| upernet_deit-b16_512x512_80k_ade20k.py | ||
| upernet_deit-b16_512x512_160k_ade20k.py | ||
| upernet_deit-b16_ln_mln_512x512_160k_ade20k.py | ||
| upernet_deit-b16_mln_512x512_160k_ade20k.py | ||
| upernet_deit-s16_512x512_80k_ade20k.py | ||
| upernet_deit-s16_512x512_160k_ade20k.py | ||
| upernet_deit-s16_ln_mln_512x512_160k_ade20k.py | ||
| upernet_deit-s16_mln_512x512_160k_ade20k.py | ||
| upernet_vit-b16_ln_mln_512x512_160k_ade20k.py | ||
| upernet_vit-b16_mln_512x512_80k_ade20k.py | ||
| upernet_vit-b16_mln_512x512_160k_ade20k.py | ||
| vit.yml | ||
README.md
Vision Transformer
Introduction
@article{dosoViTskiy2020,
title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
author={DosoViTskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and Uszkoreit, Jakob and Houlsby, Neil},
journal={arXiv preprint arXiv:2010.11929},
year={2020}
}
Usage
To use other repositories' pre-trained models, it is necessary to convert keys.
We provide a script vit2mmseg.py in the tools directory to convert the key of models from timm to MMSegmentation style.
python tools/model_converters/vit2mmseg.py ${PRETRAIN_PATH} ${STORE_PATH}
E.g.
python tools/model_converters/vit2mmseg.py https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_p16_224-80ecf9dd.pth pretrain/jx_vit_base_p16_224-80ecf9dd.pth
This script convert model from PRETRAIN_PATH and store the converted model in STORE_PATH.
Results and models
ADE20K
| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download |
|---|---|---|---|---|---|---|---|---|---|
| UPerNet | ViT-B + MLN | 512x512 | 80000 | 9.20 | 6.94 | 47.71 | 49.51 | config | model | log |
| UPerNet | ViT-B + MLN | 512x512 | 160000 | 9.20 | 7.58 | 46.75 | 48.46 | config | model | log |
| UPerNet | ViT-B + LN + MLN | 512x512 | 160000 | 9.21 | 6.82 | 47.73 | 49.95 | config | model | log |
| UPerNet | DeiT-S | 512x512 | 80000 | 4.68 | 29.85 | 42.96 | 43.79 | config | model | log |
| UPerNet | DeiT-S | 512x512 | 160000 | 4.68 | 29.19 | 42.87 | 43.79 | config | model | log |
| UPerNet | DeiT-S + MLN | 512x512 | 160000 | 5.69 | 11.18 | 43.82 | 45.07 | config | model | log |
| UPerNet | DeiT-S + LN + MLN | 512x512 | 160000 | 5.69 | 12.39 | 43.52 | 45.01 | config | model | log |
| UPerNet | DeiT-B | 512x512 | 80000 | 7.75 | 9.69 | 45.24 | 46.73 | config | model | log |
| UPerNet | DeiT-B | 512x512 | 160000 | 7.75 | 10.39 | 45.36 | 47.16 | config | model | log |
| UPerNet | DeiT-B + MLN | 512x512 | 160000 | 9.21 | 7.78 | 45.46 | 47.16 | config | model | log |
| UPerNet | DeiT-B + LN + MLN | 512x512 | 160000 | 9.21 | 7.75 | 45.37 | 47.23 | config | model | log |