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

How to test other datasets #7

Closed
Stephanie-ustc opened this issue Nov 5, 2021 · 3 comments
Closed

How to test other datasets #7

Stephanie-ustc opened this issue Nov 5, 2021 · 3 comments

Comments

@Stephanie-ustc
Copy link

Hi,how to test other datasets? change the datasets/pretrained/metadata.json?

@PeterouZh
Copy link
Owner

At present, I only provide models for two datasets. More models will be provided later.

I do not quite understand what you mean.

Do you want to train on other datasets?

@Stephanie-ustc
Copy link
Author

I want test some other image on your model. But I dont konw how to do it.
If I have image sequence with pose data,how to test?

@PeterouZh
Copy link
Owner

I want test some other image on your model. But I dont konw how to do it. If I have image sequence with pose data,how to test?

  1. Align the images in the way of StyleGAN. You can refer to this script align_images.py.
  2. Project the aligned images into the W space, also known as GAN inversion. Different from the common 2D inversion, you'd better set an appropriate yaw/pitch/fov for the CIPS-3D generator to make the initial pose of G(w) and the image to be inverted consistent.
  3. After you get the w of the image, you can reconstruct images of different styles using G'(w). G' can be obtained by interpolating generators of different domains.

Hope this helps.

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