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

How to choose default TEASER algorithm parameters for processing #80

Open
liuyx599 opened this issue Jul 1, 2023 · 1 comment
Open

Comments

@liuyx599
Copy link

liuyx599 commented Jul 1, 2023

In the README file on the homepage, kimimaro provides an example of using the Python interface with a scale of 4 and a const of 500. However, since I'm not very familiar with the TEASER algorithm, I looked at your guide Intuition-for-Setting-Parameters-const-and-scale, which states that "Most of the time, the defaults are fine and you shouldn't need to touch them, with the exception of scale and const which control the detail capture sensitivity of the procedure", meaning that in most cases, the default parameters should be sufficient.

However, in the source code

all_labels, teasar_params=DEFAULT_TEASAR_PARAMS, anisotropy=(1,1,1),
, the DEFAULT_TEASAR_PARAMS specifies a scale of 1.5 and a const of 300. Meanwhile, in the Igneous source code https://github.com/seung-lab/igneous/blob/76a43029642fb5ad9f72b4a89bceecdaa8bb1920/igneous/task_creation/skeleton.py#L44, the scale is set to 10 and the const is set to 10.

It seems that the default parameters in these different locations are not very consistent. As a beginner (like me, lacking some biological background), how should one use these parameters? For example, if I want to process the SNEMI3D dataset, which is 1024x1024x100 (6nm x 6nm x 30nm), what TEASAR parameters should I use?

@william-silversmith
Copy link
Contributor

william-silversmith commented Jul 1, 2023 via email

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

2 participants