river-zhang / sifu Goto Github PK

Glad to see this project!Can cuda=11.4 environment deploy this project?

Hi authors, could you provide some details on your evaluation protocol for Table 6? Specifically,

1. what is the rendering size?
2. how many views per subject?
3. which backbone for lpips?

Thank you very much!

Fantastic job! Could you please tell me when will you release the code?

Body Fitting --- normal: 0.104 | silhouette: 0.054 | Total: 0.158
d5acc65c50a71c7c54eb38323966f6c1_smpl.obj correct.

ICON infer error.
d5acc65c50a71c7c54eb38323966f6c1_recon.obj view：

Cloth Refinement --- cloth:3.38728 | stiffness:0.66788 | rigid:0.04957 | laplacian:0.28668 | Total: 4.39141

d5acc65c50a71c7c54eb38323966f6c1_cloth.gif view：

thanks greate work!

GOOD JOB. several questions about the code.

1. The Values of default "mcube_res" is incosistent in two codes.
   https://github.com/River-Zhang/SIFU/blob/ca76e36e929da7dd0f0d7e617bee19867bcfb046/README.md?plain=1#L87
   https://github.com/River-Zhang/SIFU/blob/ca76e36e929da7dd0f0d7e617bee19867bcfb046/configs/train/sifu.yaml#L68

2. I noticed that you modified the rendering script for the dataset. Based on your script, I re-rendered the dataset. I think you modified the script mainly to obtain side-view data of the human body. I want to know if the texture training data was rendered using the script from ICON or from the PIFU training data.

'uv_render_path': osp.join(self.root, render_folder, 'uv_color', f'{rotation:03d}.png'),
'uv_mask_path': uv_mask_path,
'uv_pos_path': uv_pos_path,
'uv_normal_path': osp.join(self.root, render_folder, 'uv_normal', '%02d.png' % (0)),
'image_mask_path':image_mask_path,
'param_path':param_path,

3.Are the geometric and texture stages trained together?
error=BCEloss+color_loss

4. Will there be a detailed document about the training, as well as the the code of texure reconstruction, including test and inference?

Hi, thank you for releasing the code. I tried the demo code but got this error.

FileNotFoundError: [Errno 2] No such file or directory: './data/smpl_related/smpl_data/smplx_vertex_lmkid.npy'

Could you please share this file?

Thanks!

sifu.ckpt load success
normal.ckpt load failed
EOFError: Ran out of input

Hello, I have successfully tested the pre-trained model, but I found that the results do not match the data in the benchmark, especially for CAPE-NFP. Is this normal? Looking forward to your reply.

https://www.dropbox.com/s/aeulffqzb3zmh8x/pare-github-data.zip