Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

ImageNet-22k classifier layout #27

Closed
rwightman opened this issue Feb 17, 2023 · 3 comments
Closed

ImageNet-22k classifier layout #27

rwightman opened this issue Feb 17, 2023 · 3 comments

Comments

@rwightman
Copy link

Can you share the classifier layout of your ImageNet-22k heads? It does not match any canonical layouts I'm aware of and it'd be useful to have as these models are useful as is for more than just pretrain (but not without the layout).

You have 21842 classes, that does not match either the fall11 (21841) or google's internal (21843). It does not match winter21 which is < 20k classes. I cannot add a background '0' class to offset 21481 -> 21842 (assuming lexicographical sorting of the sysnets which is standard practice for imagenet classifier layouts).

Thanks

@jwyang
Copy link
Member

jwyang commented Feb 17, 2023

Hi, @rwightman , thanks for pointing out this issue!

Please find our 22k layout here: https://github.com/microsoft/FocalNet/blob/main/labelmap_22k_reorder.txt

We did some reorderings of the labels so that we could directly evaluate our model on in1k using the first 1000 logits. Please note that one category, the 851th class (label=850) in 1k is missed in 22k. that's why we have labels in [0,21841] with 850 missed.

thanks,
Jianwei

@rwightman
Copy link
Author

@jwyang awesome, thank you! that's definitely handy for in1k eval.

@HostGuest
Copy link

can u help me about the env plz ? which versions do u use , pytorch cuda, .....
i have errors seting up the env ? i have cuda 11.8 , ubunto 20

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants