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

Guidance about pipeline #15

Open
Abbas009 opened this issue Aug 17, 2021 · 2 comments
Open

Guidance about pipeline #15

Abbas009 opened this issue Aug 17, 2021 · 2 comments

Comments

@Abbas009
Copy link

Thank you for sharing your code. I have learned a lot from this project. I have some queries please answer them when available.

  1. You make the H5 file which contains "image" and "label" although is a label or unlabeled data. Although, you didn't use it later for unlabeled data. So what if I have only "image" for data and do not "label" for it. Datagenrator function will give an error and can you tell me how to solve it.
  2. I am trying on some other data taken from the hospital, based on your knowledge can you please guide what ratio of the label and unlabeled data can be used to get optimal performance . And can we get a dice score more than fully supervised learning with more unlabeled data or it will decrease the performance?
@kimjisoo12
Copy link

Hello, may I ask how to convert the image data without labels into H5 files

@augpotato
Copy link

Hello, I have the same question over the data process, the code doesn't have the part of unlabeled data processing, so how can we train the unlabeled data in the teacher model?

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

3 participants