nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
Apache License 2.0
542
stars
94
forks
source link
[Question] Defining "test_labels" and "target_class" for custom dataset.json #233
Hi,
I have a custom dataset for brain metastasis detection. It is a binary task, in the original dataset "1" is the FG and "0" is BG.
I brought it to the nnDetection format, with the instances in the masks and the new FG class being "0".
In this context, how should I set "test_labels" and "target_class" in dataset.json?
mibaumgartner
commented
6 months ago
Hi, I have a custom dataset for brain metastasis detection. It is a binary task, in the original dataset "1" is the FG and "0" is BG. I brought it to the nnDetection format, with the instances in the masks and the new FG class being "0".
In this context, how should I set "test_labels" and "target_class" in dataset.json?
Thanks a lot! Best, Sara