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

[Help] My generated images failed #33

Closed
SaranchaiAng opened this issue May 2, 2022 · 9 comments
Closed

[Help] My generated images failed #33

SaranchaiAng opened this issue May 2, 2022 · 9 comments

Comments

@SaranchaiAng
Copy link

SaranchaiAng commented May 2, 2022

sample
I just follow the generation guide with some modify(CUDA) as shown in the following code (I am quite new in deep learning)

set CUDA_VISIBLE_DEVICES=0 & python generate.py --ckpt_source ./checkpoints/ffhq_sketches.pt --ckpt_target ./checkpoints/ffhq_sketches.pt --load_noise noise.pt

And the attached image is the generated image I got.
I just wondering if I did something wrong? Any recommendation?

Thanks

@gouayao
Copy link

gouayao commented May 5, 2022

Your pre-training source domain model should be source_ffhq.pt.

@SaranchaiAng
Copy link
Author

SaranchaiAng commented May 5, 2022

Your pre-training source domain model should be source_ffhq.pt.

Thank you for your answer @gouayao. I do fix that but I still got preliminary face outline not an actual face as the image below, it looks like an unfinished generation. I attached the generate.py arguments default settings below. Please help thanks
image sample
sample

@gouayao
Copy link

gouayao commented May 5, 2022

Can I have a look at your code command?

@SaranchaiAng
Copy link
Author

Can I have a look at your code command?
Thank you @gouayao

First, I try out this code
set CUDA_VISIBLE_DEVICES=0 & python generate.py --ckpt_target checkpoints/source_ffhq.pt
and this is the generated image I got
sample

I tried another code
set CUDA_VISIBLE_DEVICES=0 & python generate.py --ckpt_target checkpoints/ffhq_sketches.pt --load_noise noise.pt
and this is the result I got
sample

Thanks for any advice.

@gouayao
Copy link

gouayao commented May 5, 2022

I recommend that you print the pixel value of the output image to see if it is at (-1, 1). I replicated it on my computer and it was correct. Maybe you can experiment again with the source code.

@SaranchaiAng
Copy link
Author

I recommend that you print the pixel value of the output image to see if it is at (-1, 1). I replicated it on my computer and it was correct. Maybe you can experiment again with the source code.

Hello brother thank you for all of your help.

I finally make it works.

However do you know if there is any way to snap the training model and continue the training later because my PC has insufficient GPU memory so I need to execute it on google colab and it keeps disconnecting after training.

Thanks

@gouayao
Copy link

gouayao commented May 11, 2022

You need about 24 GB GPU memory(3090, RTX). Or you can apply for a paid computer service. I'm sorry. I don't have a better way.

@SaranchaiAng
Copy link
Author

You need about 24 GB GPU memory(3090, RTX). Or you can apply for a paid computer service. I'm sorry. I don't have a better way.

Yeah. I paid for the colab pro now. Everything works fine and it trains much faster than the free colab.
Lastly, thanks a lot again brother.

@gouayao
Copy link

gouayao commented May 11, 2022 via email

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

2 participants