Repository navigation
3D augmentation and 2.1D U-Net - #27
Merged
Merged
Conversation
* readme + dependencies tested with python 3.10 * match package description with README * cellpose (metrics -> required) * misc formatting and language edits * fix optional dependency on cellpose --------- Co-authored-by: Ziwen Liu <ziwen.liu@czbiohub.org>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Implemented the Z-scaling augmentation in #23.
To test the large input stack depth I also made a new hybrid network using a 3D-to-2D projection stem followed by any off-the-shelf ResNet-like feature encoder (from
timm, default toconvnextv2_femto) and a plain 2D U-Net decoder. This is temporarily named 2.1D U-Net. We can decide on whether to keep it after seeing some training results.