MIC-DKFZ/nnUNet
选择Linux环境运行该项目,Windows环境需要更改较多的参数,暂不支持。
可以查看另一篇
2D数据转成伪3D数据,即z轴层数为1或3(灰度图为1,彩图为3)。
参考:nnUNet/nnunet/dataset_conversion/Task120_Massachusetts_RoadSegm.py
直接转换数据,将数据存放到nnUNet_raw_data_base/nnUNet_raw_data/Task120_MassRoadsSeg
文件夹目录
└─Task120_MassRoadsSeg│ dataset.json│ ├─imagesTr│ img-1_0000.nii.gz│ img-1_0001.nii.gz│ img-1_0002.nii.gz│ img-2_0000.nii.gz│ img-2_0001.nii.gz│ img-2_0002.nii.gz│ img-3_0000.nii.gz│ img-3_0001.nii.gz│ img-3_0002.nii.gz│ img-4_0000.nii.gz│ img-4_0001.nii.gz│ img-4_0002.nii.gz│ img-5_0000.nii.gz│ img-5_0001.nii.gz│ img-5_0002.nii.gz│ ...├─imagesTs│ img-10.nii.gz│ img-11.nii.gz│ ...└─labelsTrimg-1.nii.gzimg-2.nii.gzimg-3.nii.gzimg-4.nii.gzimg-5.nii.gz...
json文件信息
nnUNet/nnunet/dataset_conversion/utils.py
里面的函数generate_dataset_json
可以生成相应任务的json
文件。
{
"name": "MassRoadsSeg",
"description": "MassRoadsSeg",
"reference": "https://www.kaggle.com/insaff/massachusetts-roads-dataset",
"licence":'hands off!',
"release":"1.0 06/08/2018",
"tensorImageSize": "4D",
"modality": { "0": "Red","1": "Green","2": "Blue"}, "labels": { "0": "background", "1": "street"}, "numTraining": 804, "numTest": 13,"training":[{"image":"./imagesTr/img-1.nii.gz","label":"./labelsTr/img-1.nii.gz"},{"image":"./imagesTr/img-2.nii.gz","label":"./labelsTr/img-2.nii.gz"},{"image":"./imagesTr/img-3.nii.gz","label":"./labelsTr/img-3.nii.gz"},{"image":"./imagesTr/img-4.nii.gz","label":"./labelsTr/img-4.nii.gz"},{"image":"./imagesTr/img-5.nii.gz","label":"./labelsTr/img-5.nii.gz"},...],"test":["./imagesTs/img-10.nii.gz","./imagesTs/img-11.nii.gz",...]}
# 只进行2d预处理,不进行3d预处理
nnUNet_plan_and_preprocess -t 120 -pl3d None
nnUNet_train 2d nnUNetTrainerV2 120 0
nnUNet_predict -i /root/nnUNet_raw_data_base/nnUNet_raw_data/Task120_MassRoadsSeg/imagesTs -o /root/nnUNet_trained_models/nnUNet/2d/Task120_MassRoadsSeg/nnUNetTrainerV2__nnUNetPlansv2.1/fold_0/infer -t 120 -m 2d