microsoft / DiscoFaceGAN

Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning (CVPR 2020 Oral)
MIT License
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generate wrong pictures #25

Open sunkymepro opened 3 years ago

sunkymepro commented 3 years ago

Dear author,thanks for your great work,it‘s very helpful for me But when I run the generate_images.py,I get very strange result 019_01 I download the pretrain .pkl file,and set --model=’network-snapshot-020126.pkl’ and =network-snapshot-020126.pkl The former result is added,the latter result is a blank picture. I think the reason of this phenomenon is not loading the pkl files fail or loading wrong file. Is there something needs to notice I miss?I really want to know the answer.

YuDeng commented 3 years ago

Hi, can you try not use --model argument and run the generate_images.py using the default setting? The code should download the pretrained model automatically.

grinawiem commented 2 years ago

Dear author, I'm studying your code about remaking the face with a new method. It's an amazing work ( DisentangledFaceGAN) in the field of information technology. Thank you for this wonderful and innovative effort. And here I am trying to study and understand your new strategy so that I can mention your work in my research that I am preparing, but when I tried to test it, it became clear to me that I had failed in creating the data correctly. Could you please help me and explain to me more about how to prepare it. Because when I try to teach the model, this result appears on the computer screen. Please help me; Screenshot from 2021-08-13 13-13-35 Screenshot from 2021-08-13 13-13-20

YuDeng commented 2 years ago

Dear author, I'm studying your code about remaking the face with a new method. It's an amazing work ( DisentangledFaceGAN) in the field of information technology. Thank you for this wonderful and innovative effort. And here I am trying to study and understand your new strategy so that I can mention your work in my research that I am preparing, but when I tried to test it, it became clear to me that I had failed in creating the data correctly. Could you please help me and explain to me more about how to prepare it. Because when I try to teach the model, this result appears on the computer screen. Please help me; Screenshot from 2021-08-13 13-13-35 Screenshot from 2021-08-13 13-13-20

Hi, it is strange to get NAN loss when training the VAE. What is your training data and what is the scale of your dataset? If there is too few data, it might fail to train a proper VAE.

Yitian-Li commented 2 years ago

Dear author, I'm studying your code about remaking the face with a new method. It's an amazing work ( DisentangledFaceGAN) in the field of information technology. Thank you for this wonderful and innovative effort. And here I am trying to study and understand your new strategy so that I can mention your work in my research that I am preparing, but when I tried to test it, it became clear to me that I had failed in creating the data correctly. Could you please help me and explain to me more about how to prepare it. Because when I try to teach the model, this result appears on the computer screen. Please help me; Screenshot from 2021-08-13 13-13-35 Screenshot from 2021-08-13 13-13-20

you should check your data path because you are using a dataset of size "0"

chinmayjog13 commented 8 months ago

@YuDeng I am facing the same issue when I provide the model argument. If I don't, I face the issue referenced in #33 . I am using python 3.6 and the correct versions of packages given in the readme. Please suggest a solution

Yitian-Li commented 8 months ago

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fak111 commented 1 month ago

image i get wrong picture too

Yitian-Li commented 1 month ago

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fak111 commented 1 month ago

i hava got the answer ,because of the environment. if u choose the another machine , do the again, maybe solove

fak111 commented 1 month ago

i hava got the answer ,because of the environment. if u choose the another machine , do the again, maybe solove

or because the computer has enough size of gpu ,,,model can't do well in weak computer

aurelianocyp commented 1 month ago

我在3090跑的结果和你一样,不太对。换成了 2080 Ti就成功了

jadechip commented 3 weeks ago

Has anyone a solution to this? I working in an environment based off of the tensorflow/tensorflow:1.13.2-gpu-py3-jupyter docker image, similar to the recommended specs and this is how my images look: 000_00

I have tried using multiple different GPUs.

Thank you.

Yitian-Li commented 3 weeks ago

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