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[Tools] Add vit/swin/mit convert weight scripts #783

Merged
merged 16 commits into from
Aug 18, 2021
Merged

[Tools] Add vit/swin/mit convert weight scripts #783

merged 16 commits into from
Aug 18, 2021

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xiexinch
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Motivation

Remove convert keys operation at init_weight function, use script instead.

@xiexinch xiexinch requested a review from MengzhangLI August 12, 2021 12:45
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codecov bot commented Aug 12, 2021 •
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Codecov Report

Merging #783 (37822c5) into master (6eff941) will not change coverage.
The diff coverage is n/a.

❗ Current head 37822c5 differs from pull request most recent head 9d73900. Consider uploading reports for the commit 9d73900 to get more accurate results
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@@           Coverage Diff           @@
##           master     #783   +/-   ##
=======================================
  Coverage   86.09%   86.09%           
=======================================
  Files         108      108           
  Lines        5860     5860           
  Branches      953      953           
=======================================
  Hits         5045     5045           
  Misses        630      630           
  Partials      185      185
Flag Coverage Δ
unittests 86.07% <ø> (ø)

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@Junjun2016
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The description or docstring is too short.

@Junjun2016
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Please refer to https://github.com/open-mmlab/mmdetection/blob/master/docs/useful_tools.md.

@xiexinch
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The description or docstring is too short.

What information should be included?

@Junjun2016
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The description or docstring is too short.

What information should be included?

Describe what the script does, such as

RegNet model to MMDetection

tools/model_converters/regnet2mmdet.py convert keys in pycls pretrained RegNet models to MMDetection style.
https://github.com/open-mmlab/mmdetection/blob/master/docs/useful_tools.md#regnet-model-to-mmdetection

Please update the Chinese document at the same time.

Junjun2016
Junjun2016 reviewed Aug 13, 2021
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Junjun2016
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Junjun2016
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Junjun2016
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MengzhangLI
MengzhangLI approved these changes Aug 13, 2021
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@xvjiarui
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We may delete convert function from ViT/Swin backbones in a new PR.
And we may add instruction on how to convert model in their README.md.

(It seems that Segformer's readme.md should be renamed as README.md, and model-index is also missing).

@xiexinch xiexinch mentioned this pull request Aug 14, 2021
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Junjun2016
Junjun2016 reviewed Aug 16, 2021
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docs/useful_tools.md Outdated
@@ -277,6 +277,14 @@ We provide scripts to convert pretrain models provided by other repos to MMSegme
python tools/model_converters/swin2mmseg.py ${SRC} ${DST}
```

- Segformer
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Suggested change
- Segformer
- SegFormer

@MengzhangLI MengzhangLI self-requested a review August 16, 2021 05:51
@xvjiarui xvjiarui mentioned this pull request Aug 18, 2021
Merged
@xvjiarui xvjiarui merged commit f72727c into open-mmlab:master Aug 18, 2021
459737087 pushed a commit to 459737087/mmsegmentation that referenced this pull request Aug 23, 2021
@459737087
[Tools] Add vit/swin/mit convert weight scripts (open-mmlab#783)
0828871 
* init scripts

* update markdown

* update markdown

* add docs

* delete mit converter and use torch load function

* rename segformer readme

* update doc

* modify doc

* 更新中文文档

* Update useful_tools.md

* Update useful_tools.md

* modify doc

* update segformer.yml
This was referenced Sep 2, 2021
Merged
Open
bowenroom pushed a commit to bowenroom/mmsegmentation that referenced this pull request Feb 25, 2022
[Tools] Add vit/swin/mit convert weight scripts (open-mmlab#783)
ebf3c08 
* init scripts

* update markdown

* update markdown

* add docs

* delete mit converter and use torch load function

* rename segformer readme

* update doc

* modify doc

* 更新中文文档

* Update useful_tools.md

* Update useful_tools.md

* modify doc

* update segformer.yml
wjkim81 pushed a commit to wjkim81/mmsegmentation that referenced this pull request Dec 3, 2023
@jin-s13
update resource limit (open-mmlab#783)
fe4fdad
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@Junjun2016 Junjun2016 Junjun2016 left review comments

@xvjiarui xvjiarui xvjiarui approved these changes

@MengzhangLI MengzhangLI Awaiting requested review from MengzhangLI

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4 participants
@xiexinch @Junjun2016 @xvjiarui @MengzhangLI