nnunet_mini

Usage

1. use the original nnUNet to do data processing and generate training planning.
1. change the path in configuration.py to your own.
1. use your own network to replace the original Generic_UNet in "nnUNetTrainer.py", line 275, function "initialize_network()".
1. train your own network using the "train_shell.py".

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
.idea		.idea
.gitignore		.gitignore
Inference2D.py		Inference2D.py
Inference3D.py		Inference3D.py
LICENSE		LICENSE
README.md		README.md
attention.py		attention.py
attention_unet.py		attention_unet.py
configuration.py		configuration.py
connected_components.py		connected_components.py
custom_transforms.py		custom_transforms.py
data_augmentation.py		data_augmentation.py
data_augmentation_moreDA.py		data_augmentation_moreDA.py
dataset_loading.py		dataset_loading.py
default_configuration.py		default_configuration.py
default_data_augmentation.py		default_data_augmentation.py
downsampling.py		downsampling.py
evaluator.py		evaluator.py
generic_UNet.py		generic_UNet.py
grid_attention_layer.py		grid_attention_layer.py
lcovnet.py		lcovnet.py
loss_functions.py		loss_functions.py
model_restore.py		model_restore.py
network_trainer.py		network_trainer.py
networks_other.py		networks_other.py
neural_network.py		neural_network.py
nnUNetTrainer.py		nnUNetTrainer.py
nnUNetTrainerV2.py		nnUNetTrainerV2.py
nnunet.py		nnunet.py
predict.py		predict.py
predict_simple.py		predict_simple.py
preprocessing.py		preprocessing.py
pyramid_augmentations.py		pyramid_augmentations.py
run_training.py		run_training.py
segmentation_export.py		segmentation_export.py
train_shell.sh		train_shell.sh
unet.py		unet.py
unet_nested.py		unet_nested.py
utils.py		utils.py
vnet.py		vnet.py