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

Loss is considerably worse on custom data set with different mean and standard deviation #179

Open
bpmsilva opened this issue Sep 29, 2023 · 3 comments

Comments

@bpmsilva
Copy link

I am using this repo to train on a custom data set. My images are grayscale, but the final reconstruction was bluish. I hypothesized that was because of the use of the Imagenet mean and standard deviation (blue is the one with the lowest mean value). I proved that correct because I changed the mean and standard deviations of the code, and the final images were gray. However, it came with the cost of lowering my performance as the loss became higher than usual. I even tried to change the mean and standard deviation of the timm package, but that was no good. Is there anyone who can lend a hand?

@ChoCumsky
Copy link

I am having the same problem, did you ever figure out the solution?

@Mirzyaaliii
Copy link

I am also working with grayscale images and my result (reconstruction) is horrible.

Can anyone suggest some strategies to get better results for grayscale images?

@hugoWR
Copy link

hugoWR commented Jun 20, 2024

Can you provide more details ? In my experience it's possible to obtain good reconstruction results even with Gray scale images

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

4 participants