-
Notifications
You must be signed in to change notification settings - Fork 26
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
About the final prediction head #21
Comments
Can you please send link on code with line? |
the code is from this script : segmentation_models_3D/models/unet.py model head (define number of output classes)
|
It's the same in 2D version: |
Thanks, as I have seen, most of the prediction head in Unet have implemented Conv2D with kernel size 1. So I am not sure if the kernel size 3 or 1 will affect the final prediction. |
Hi , when reading your code about the model head (define number of output classes) ,I have some question about this. In 2D segmentation task , we usually use Conv2D with kernel size 1 to get the final segmentaion mask. However, in this library, I notice that Conv3D with kernel size 3 has been used to get the final prediction rather than kernel size 1. I'm just wondering is there difference between Conv3D with kernel size 3 and 1 to get the prediction in 3D segmentation task?
The text was updated successfully, but these errors were encountered: