Michael Baumgartner

Dear @aldemirfilho , the error indicates insufficient memory on the GPU, so deleting case files won't solve the Issue. The error you posted is generated because the split was automatically...

Dear @aldemirfilho , I think the best way to downscale nnDetection when a limited amount of memory is available is the reduction of the number of channels. This can be...

Hi @JiaminRen , the transformation intends to provide a generic bounding box representation and no special handling of image borders is done here on purpose, i.e. if the object starts...

Dear @dalbis , it is theoretically possible to export the learned segmentations (during inference) as well but this is considered a highly experimental feature since we neither evaluated nor tested...

Dear @Zouxxyy , thanks for the bug report, I'll look into it in more detail after my vacation. Best, Michael

Dear @midya2020 , can you check that your env is correctly setup (see the FAQ section of the readme for more info)? The error message without trace is rather uninformative,...

Hi, yes, it should be possible to rerun the evaluation with the predictions and preprocessed data (especially the prepared labels). The error indicates that nndet can not find the model...

If the model was consolidated correctly there should be an additional folder `val_predictions` which are the predictions from each model on its respective fold. With the checkpoint, config and plan...

Hi @zoliseress , thanks for your interest in nnDetection. The current version does not implement a 2D pipeline because all of our data sets in the training/validation pool were 3D....

Dear @orouskhani, we only submitted nnDetection to the ADAM leaderboard, so there is no code available to compute the coordinates from the segmentations. The code to run the postprocessing from...