import os default_num_threads = 8 if 'nnUNet_def_n_proc' not in os.environ else int(os.environ['nnUNet_def_n_proc']) RESAMPLING_SEPARATE_Z_ANISO_THRESHOLD = 3 # determines what threshold to use for resampling the low resolution axis # separately (with NN) 1 2 3 4 5While...
environ['nnUNet_def_n_proc']) ANISO_THRESHOLD = 3 # determines when a sample is considered anisotropic (3 means that the spacing in the low # resolution axis must be 3x as large as the next largest spacing)3 changes: 1 addition & 2 deletions 3 nnunetv2/preprocessing/preprocessors/...
class RemoveKeyTransform(AbstractTransform): def __init__(self, key_to_remove: str): self.key_to_remove = key_to_remove def __call__(self, **data_dict): _ = data_dict.pop(self.key_to_remove, None) return data_dict 1.6、LimitedLenWrapper class LimitedLenWrapper(NonDetMultiThreadedAugm...
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def unpack_dataset(folder: str, unpack_segmentation: bool = True, overwrite_existing: bool = False): """ All npz files in this folder belong to the dataset, unpack them all """ npz_files = subfiles(folder, True, None, ".npz", True) ...
def __init__(self, folder_with_cropped_data, preprocessed_output_folder): super(ExperimentPlanner3D_v21_16GB, self).__init__(folder_with_cropped_data, preprocessed_output_folder) self.data_identifier = "nnUNetData_plans_v2.1_16GB" self.plans_fname = join(self.preprocessed_output_folder, ...
import os default_num_threads = 8 if 'nnUNet_def_n_proc' not in os.environ else int(os.environ['nnUNet_def_n_proc']) RESAMPLING_SEPARATE_Z_ANISO_THRESHOLD = 3 # determines what threshold to use for resampling the low resolution axis # separately (with NN) 1 2 3 4 5While...
master documentation nnunet nnunetv2 batch_running dataset_conversion ensembling evaluation experiment_planning imageio inference model_sharing postprocessing preprocessing run tests training utilities __init__.py configuration.py paths.py .gitignore ...
import os from nnunetv2.utilities.default_n_proc_DA import get_allowed_n_proc_DA default_num_processes = 8 if 'nnUNet_def_n_proc' not in os.environ else int(os.environ['nnUNet_def_n_proc']) ANISO_THRESHOLD = 3 # determines when a sample is considered anisotropic (3 means that th...