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nnUNet_calvingfront_detection / nnunet /utilities /folder_names.py
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# Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from batchgenerators.utilities.file_and_folder_operations import *
from nnunet.paths import network_training_output_dir
def get_output_folder_name(model: str, task: str = None, trainer: str = None, plans: str = None, fold: int = None,
overwrite_training_output_dir: str = None):
"""
Retrieves the correct output directory for the nnU-Net model described by the input parameters
:param model:
:param task:
:param trainer:
:param plans:
:param fold:
:param overwrite_training_output_dir:
:return:
"""
assert model in ["2d", "3d_cascade_fullres", '3d_fullres', '3d_lowres']
if overwrite_training_output_dir is not None:
tr_dir = overwrite_training_output_dir
else:
tr_dir = network_training_output_dir
current = join(tr_dir, model)
if task is not None:
current = join(current, task)
if trainer is not None and plans is not None:
current = join(current, trainer + "__" + plans)
if fold is not None:
current = join(current, "fold_%d" % fold)
return current