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

[misc] support High-Resolution Canonical Avatars && image-to-avatars #3

Closed
xdobetter opened this issue Apr 7, 2024 · 3 comments
Closed

Comments

@xdobetter
Copy link

Hello, great job on your work! I have a couple of questions regarding it:

  1. Can the current codebase support High-Resolution Canonical Avatars? What is its computational overhead compared to 64x64 avatars?

  2. Can the current task accommodate image-to-avatar conversion?

@huanngzh
Copy link
Owner

huanngzh commented May 2, 2024

  1. I check the improvement of DreamWaltz about resolution. I think it can be easily reproduced in the current codebase by changing the resolution. I'm not sure about the specific computing resource consumption, and I haven't reproduced it yet :)
  2. Maybe you can introduce some methods like zero123, IP-Adapter as guidance?

@xdobetter
Copy link
Author

xdobetter commented May 2, 2024 via email

@huanngzh
Copy link
Owner

huanngzh commented May 3, 2024

I think you need to adjust some parameters such as guidance_scale, weighting_strategy etc. In addition, in my code, there is a parameter guidance_eval in the config, which indicates how many steps to verify the image inference results. You can judge whether lora works based on this.

@huanngzh huanngzh closed this as completed May 6, 2024
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