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

When will you release a hugging face demo ,THANK YOU IN ADVANCE ♡♡♡ #87

Open
Sarthak-999 opened this issue Apr 21, 2024 · 8 comments
Assignees

Comments

@Sarthak-999
Copy link

No description provided.

@Inferencer
Copy link

they have one on replicate while you wait
https://replicate.com/camenduru/champ

@zhou-linpeng
Copy link

zhou-linpeng commented Apr 23, 2024

A preliminary Champ was implemented, including aligning the 3D pose with the input image. The entire forward process took about 6 minutes.
https://c933b786ceedee6c17.gradio.live

grid_wguidance_demo.mp4

@nitinmukesh
Copy link

@zhou-linpeng
Awesome. How did you got smooth animation? Please post quick guide (steps).

@sonodaatom
Copy link

Great work!
I would also like to know how you make the video smooth without flickering!

@Leoooo333
Copy link
Member

Hi @nitinmukesh @sonodaatom, the Blender smooth script is released. Update and Check the doc.

@sonodaatom
Copy link

@Leoooo333
Thank you for your great work and reply!

I would also appreciate an answer to the bug that is not generated when using figure_transfer.
#84

Also, like --view_transfer, I would like the balance of the body to be aligned with the reference image, but to be moved when the video is moved from back to front, do you have any idea how to handle such a request?

@Leoooo333
Copy link
Member

Leoooo333 commented May 1, 2024

Hi @sonodaatom, so now cam_t, which is the global location of the SMPL, is fixed as Reference when using view-transfer. To transfer with moving locations, I recommend to edit this line.

result_dict["cam_t"] = reference_dict["cam_t"]

For a very simple example, you can translate the mean of your motion sequence's cam_t to reference's. Here's the pseudo code.

motion_loc_mean = result_dict_list["camera"].mean()
ref_loc = reference_dict["cam_t"] 
smooth_factor = 1
rescale_loc_list = result_dict_list["camera"] - motion_loc_mean 
rescale_loc_list *= ref_loc / motion_loc_mean  # simple perspective transform
rescale_loc_list *= smooth_factor
rescale_loc_list += ref_loc # move motion's mean to ref_loc
for i in range() :
    result_dict["cam_t"] = rescale_loc_list [i]

@sonodaatom
Copy link

@Leoooo333
Thank you for the pseudo code.
I will try it.

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

7 participants