-
-
Notifications
You must be signed in to change notification settings - Fork 47
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
"wrap" mode for label #189
Comments
cc @jni |
@jni authored https://github.com/dask/dask-image/blob/main/dask_image/ndmeasure/_utils/_label.py so I'd say he's probably the best person to guide you. |
cc @grlee77 (also in case you have thoughts on how we might consolidate this upstream) |
Hi everyone, I'm sorry that I haven't had the bandwidth to respond here properly, much less consider the code carefully. I do love that code, which @jakirkham and I implemented over a feverish couple of days in 2019 here in Melbourne — remember in-person visits? Anyway, I think your assessment is right @rabernat, the very same code can almost certainly be used to wrap the arrays, modulo some connectivity parameter. It'd be equally fun to implement, should someone have the bandwidth. I'd love to say I would do it but realistically I won't get the chance any time soon. |
Hey, |
Thanks Erik! 🙏 Maybe it is worth opening a PR to discuss the changes? |
Sounds good! See #344. |
Closed by #344. |
Over in scipy/scipy#8218 we are discussing how to implement "wrap" mode (i.e. periodic boundary conditions) for
label
and other morphological functions. (This issue is just aboutlabel
.) We would like to be able to calllabel
and have features that cross the array's periodic boundary (in our case, the date line), be counted as a single feature.I'm opening this issue because
It sounds like the scipy-devs are open to accepting a PR to implement wrap-mode via a relabeling approach. So I am wondering if you folks here have any advice about how to best extract / adapt your relabeling method to live in scipy itself. Thanks in advance for any advice or hints you might be able to share.
And thanks for the amazing dask-image package! It is super helpful for all our work.
cc @hscannell
The text was updated successfully, but these errors were encountered: