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pretrained densenet169 weights #40

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Kexiii opened this issue May 17, 2018 · 8 comments
Open

pretrained densenet169 weights #40

Kexiii opened this issue May 17, 2018 · 8 comments

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@Kexiii
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Kexiii commented May 17, 2018

Hi, thanks for your great work!
I'm working on densenet169 these days, do you know where I can find the ImageNet pretrained weights for this efficient implementation? Or do you have any example code to show how to convert the other implementation's pretrained model to this one?
I do have noticed this #13 , but it seems @ZhengRui didn't provide any example code, and I don't know where to start..

@gpleiss
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gpleiss commented May 23, 2018

I think you should be able to use any of the PyTorch pretrained DenseNets:

model_urls = {
    'densenet121': 'https://download.pytorch.org/models/densenet121-a639ec97.pth',
    'densenet169': 'https://download.pytorch.org/models/densenet169-b2777c0a.pth',
    'densenet201': 'https://download.pytorch.org/models/densenet201-c1103571.pth',
    'densenet161': 'https://download.pytorch.org/models/densenet161-8d451a50.pth',
}

Those urls should have the weights. Let me know if this works!

@Kexiii
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Kexiii commented May 24, 2018

Thanks for your reply!
I forgot to mention that I'm using the old pytorch0.3 implementation and it can't directly use the pretrained weights you provided.

@gpleiss
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gpleiss commented May 24, 2018

Did you try the ones here: https://github.com/mingminzhen/densenet-efficient-model

@Kexiii
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Kexiii commented May 24, 2018

Yes, but it is based on the pretrained memory efficient torch model(232,264):
https://github.com/liuzhuang13/DenseNet
In the tech report, they didn't provide efficient densenet169 pretrained torch model that I want

@gpleiss
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gpleiss commented May 24, 2018 via email

@Kexiii
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Kexiii commented May 24, 2018

Thanks for your advice,
want to let you know I've tried to convert the densenet169:https://github.com/Kexiii/Pretrained-Efficient-DenseNet

@ZZXin
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ZZXin commented Mar 15, 2020

I think you should be able to use any of the PyTorch pretrained DenseNets:

model_urls = {
    'densenet121': 'https://download.pytorch.org/models/densenet121-a639ec97.pth',
    'densenet169': 'https://download.pytorch.org/models/densenet169-b2777c0a.pth',
    'densenet201': 'https://download.pytorch.org/models/densenet201-c1103571.pth',
    'densenet161': 'https://download.pytorch.org/models/densenet161-8d451a50.pth',
}

Those urls should have the weights. Let me know if this works!

Hi,
I have a question On which dataset these weights are pretrained,ImageNet?

@gpleiss
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gpleiss commented Mar 23, 2020

Yup. Imagenet.

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