@@ -244,7 +244,7 @@ Eachs of this commands is explained below and more detailt information can be ob
### Planning & Preprocessing
Before training the networks, nnDetection needs to preprocess and analyze the data.
The preprocessing stage noramlizaes and resamples the data while the analyzed properties are used to create a plan which will be used for configuring the training.
The preprocessing stage normalizes and resamples the data while the analyzed properties are used to create a plan which will be used for configuring the training.
nnDetectionV0 requires a GPU with approximately the same amount of VRAM you are planning to use for training (i.e. we used a RTX2080TI; no monitor attached to it) to perform live estimation of the VRAM used by the network.
After the planning and preprocessing stage is finished the training phase can be started.
The default setup of nnDetection is trained in a 5 fold cross-validation scheme.
First, check which plans were generated during planning by checken the preprocessing folder and looking for the pickled plan files. In most cases only the defaul plan will be generated (`D3V001_3d`) but there might be instances (e.g. Kits) where the low resolution plan will be generated too (`D3V001LR1_3d`).
First, check which plans were generated during planning by checking the preprocessing folder and looking for the pickled plan files. In most cases only the defaul plan will be generated (`D3V001_3d`) but there might be instances (e.g. Kits) where the low resolution plan will be generated too (`D3V001LR1_3d`).
