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

Black image result #5

Open
Liampour opened this issue Oct 2, 2024 · 3 comments
Open

Black image result #5

Liampour opened this issue Oct 2, 2024 · 3 comments

Comments

@Liampour
Copy link

Liampour commented Oct 2, 2024

Hello,
congratulations for your awesome work!
When I am trying to insert my own tif files I am getting a black image as result.
Am I missing something?
Thank you for your effort, and I look forward to your reply.

@ltkong218
Copy link
Owner

Thanks for your attention!

I think there are many reasons to generate black images result:

  1. The predicted .hdr file is saved in linear domain, a tone mapping method is need to visualize. 2. The provided code is based on fusion coefficients in Kalantari 17. If you change the fusion coefficients, you need to train your specific SAFNet model from scratch on your data with your fusion method. 3. The provided checkpoints on Kalantari 17 and Challenge123 may be overfitted on these small datasets to some extent, which can not generalize well to real data in visualization.

@Liampour
Copy link
Author

Liampour commented Oct 7, 2024

The test conducted without changing the exposure coefficients but probably the value of zero exposure of the inputted image doesn't match to the zero value of Kalantari's dataset.
So a potential solution may be to retrain the model on larger dataset?
I tried some tone mapping methods but the results were not like the example results. Actually the image remained black with some different shades in some regions.
Could you please suggest some tone mapping method whose results match and highlight the capabilities of this model?

@ltkong218
Copy link
Owner

ltkong218 commented Oct 9, 2024

Yes, I think you need to retrain the model on training dataset containing enough dynamic and lighting scenes. Exposure coefficients and HDR fusion methods can be adjust to your data.

For diverse tone mapping methods, you can refer to OpenCV High Dynamic Range Imaging Document.

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