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

Hey - it doesn't make sense to train segnet on a single class. In this situation, segnet will simply learn to predict every pixel as this class, and you will see loss=0. #145

Open
ArunJ1 opened this issue Mar 19, 2019 · 1 comment

Comments

@ArunJ1
Copy link

ArunJ1 commented Mar 19, 2019

Hey - it doesn't make sense to train segnet on a single class. In this situation, segnet will simply learn to predict every pixel as this class, and you will see loss=0.

Instead, you need to have a background class that isn't ignored. It is essential to have a background class to learn what isn't your object of interest.

Therefore you should set num_output: 2, label your object and background classes as 0 and 1 and have no ignore label.

Cheers.

Originally posted by @alexgkendall in #31 (comment)

@ArunJ1
Copy link
Author

ArunJ1 commented Mar 19, 2019

Thanks for your advice @alexgkendall ....I have found this after searching around for long time....Thanks Again..

Pls could you confirm whether it is mandatory to calculate the class weighting and add??

As mentioned above, I have only single class to predict. That's why i would like to confirm whether it is mandatory.

Thanks in advance

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

1 participant