Add Swin-Transformer to keras.applications about keras-cv HOT 14 CLOSED

Thanks for this FR, could you provide the link to the original paper so that we can take a look?

In general, I think we are open accept new application models if they are widely recognized. Currently we might host it in keras.application, but will very likely to move them to keras-cv repository, which is targeted for CV specific components.

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So far we are scoping it and draft the roadmap for it. Will have more details later this year.

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@Rishit-dagli are you interested to contribute here?

Context:
tensorflow/models#10269

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Thanks for the reference. If you would like to contribute, you are welcome to send it to keras CV, which will be new home for cv related application model.

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@Rishit-dagli are you interested to contribute here?

Context: tensorflow/models#10269

Thanks @bhack , I would definitely love to take this up!

So far we are scoping it and draft the roadmap for it. Will have more details later this year.

@qlzh727 Please do let me know if this should be contributed to keras.applications or keras-cv .

Until then I will start reading the contributing guidelines for both and take a look at a couple of past PRs as well.

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Sorry for the late reply. We probably have to host this in the keras/application for now. Eventually we will move this to keras-cv, but we are not ready yet. Feel free to send PR if you have any.

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Can we close this for #671?

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Just FYI, you can take a look for the new guidance for adding application to keras in keras-team/keras#15447.

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@qlzh727
The paper link is provided.

I'm really excited about the keras-cv repo. Any good news?

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@qlzh727 any update on this. luke informed us that the new model will be placed to keras-application for now. FYI, there is already a version 2 of swin-transformer.

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@qlzh727 Thanks for clarifying.
cc. @Rishit-dagli

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@qlzh727
Could you please move this issue to keras-cv? I think it's more fit there now.

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Thanks for the notice.

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It seems I created a duplicate issue. Yes we'd like to accept the contribution as a keras-application style model.
Is there any way to split the work, for example, porting on SWIN-T Base first?

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