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

results are strange while testing on whole img #29

Closed
tachikoma777 opened this issue Jul 29, 2021 · 7 comments
Closed

results are strange while testing on whole img #29

tachikoma777 opened this issue Jul 29, 2021 · 7 comments

Comments

@tachikoma777
Copy link

Hi, I'm using pretrain model for testing, while testing on align cropped faces, the results are promising.
However, while testing as whole img the results are wrong, seems the detection is not working well because in results cmp folder there is no faces or sereval faces in one img.

I didn't change the code, is there anything wrong the whole img testing? Thanks in advance.

@xinntao
Copy link
Member

xinntao commented Aug 3, 2021

  1. If no face is detected, it will restore it.
  2. As the current model also enhances colors, when putting faces back to the whole image, the results are not good. We will release a model w/o changing colors.

@tachikoma777
Copy link
Author

  1. If no face is detected, it will restore it.
  2. As the current model also enhances colors, when putting faces back to the whole image, the results are not good. We will release a model w/o changing colors.

But I use default test img in original project, it will be strange if no face is detected. results are as follows:
image

@tachikoma777
Copy link
Author

By the way, I have i small question about the Channel-Split SFT, which is how the F_prior is splited in chanels? How many channel F_prior have? Thanks!

@xinntao
Copy link
Member

xinntao commented Aug 4, 2021

  1. If no face is detected, it will restore it.
  2. As the current model also enhances colors, when putting faces back to the whole image, the results are not good. We will release a model w/o changing colors.

But I use default test img in original project, it will be strange if no face is detected. results are as follows:
image

Did you use the colab demo?
It seems that there must be something wrong with face detection.~

@xinntao
Copy link
Member

xinntao commented Aug 4, 2021

By the way, I have i small question about the Channel-Split SFT, which is how the F_prior is splited in chanels? How many channel F_prior have? Thanks!

Half the original channels~

@tachikoma777
Copy link
Author

tachikoma777 commented Aug 5, 2021

  1. If no face is detected, it will restore it.
  2. As the current model also enhances colors, when putting faces back to the whole image, the results are not good. We will release a model w/o changing colors.

But I use default test img in original project, it will be strange if no face is detected. results are as follows:
image

Did you use the colab demo?
It seems that there must be something wrong with face detection.~

No, I tested on local side. After I recheck the crop region and found that for every input the detection region is always the left up 512*512 block. I tested on both moblienet and resnet detection model.
Is there something wrong with facexlib? I tested both v0.1.3.1 and v0.1

@xinntao
Copy link
Member

xinntao commented Aug 6, 2021

I have updated the model without colorization. Colab demo: https://colab.research.google.com/drive/1sVsoBd9AjckIXThgtZhGrHRfFI6UUYOo

For your problem, I have not encountered this issue on my side.

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