Hi
First of all - thanks for making this extremely useful extension available.
I have installed the app without issues and ran it on my own trained nnUNet. It works very well. I just have a question about if/how it does the ensembling? I usually train 2d and 3d_fullres models and use nnUNet's "find best configuration" option before inference. But I don't think the nnUNet Slicer extension uses the 3d_fullres model for inferencing, even though it is available in my folder structure. To test this out, I changed the name of one of the 3d_fullres fold's foldernames from fold_0 to fold_xxx, expecting it to return an error but it didn't so I suspect it only uses my trained 2d models. Just wondering if someone could clarify how it does the inferencing when multiple models are available.
Bart
Hi
First of all - thanks for making this extremely useful extension available.
I have installed the app without issues and ran it on my own trained nnUNet. It works very well. I just have a question about if/how it does the ensembling? I usually train 2d and 3d_fullres models and use nnUNet's "find best configuration" option before inference. But I don't think the nnUNet Slicer extension uses the 3d_fullres model for inferencing, even though it is available in my folder structure. To test this out, I changed the name of one of the 3d_fullres fold's foldernames from fold_0 to fold_xxx, expecting it to return an error but it didn't so I suspect it only uses my trained 2d models. Just wondering if someone could clarify how it does the inferencing when multiple models are available.
Bart