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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.
import argparse
from nnunet.postprocessing.consolidate_postprocessing import consolidate_folds
from nnunet.utilities.folder_names import get_output_folder_name
from nnunet.utilities.task_name_id_conversion import convert_id_to_task_name
from nnunet.paths import default_cascade_trainer, default_trainer, default_plans_identifier
def main():
argparser = argparse.ArgumentParser(usage="Used to determine the postprocessing for a trained model. Useful for "
"when the best configuration (2d, 3d_fullres etc) as selected manually.")
argparser.add_argument("-m", type=str, required=True, help="U-Net model (2d, 3d_lowres, 3d_fullres or "
"3d_cascade_fullres)")
argparser.add_argument("-t", type=str, required=True, help="Task name or id")
argparser.add_argument("-tr", type=str, required=False, default=None,
help="nnUNetTrainer class. Default: %s, unless 3d_cascade_fullres "
"(then it's %s)" % (default_trainer, default_cascade_trainer))
argparser.add_argument("-pl", type=str, required=False, default=default_plans_identifier,
help="Plans name, Default=%s" % default_plans_identifier)
argparser.add_argument("-val", type=str, required=False, default="validation_raw",
help="Validation folder name. Default: validation_raw")
args = argparser.parse_args()
model = args.m
task = args.t
trainer = args.tr
plans = args.pl
val = args.val
if not task.startswith("Task"):
task_id = int(task)
task = convert_id_to_task_name(task_id)
if trainer is None:
if model == "3d_cascade_fullres":
trainer = "nnUNetTrainerV2CascadeFullRes"
else:
trainer = "nnUNetTrainerV2"
folder = get_output_folder_name(model, task, trainer, plans, None)
consolidate_folds(folder, val, folds=(0,))
if __name__ == "__main__":
main()
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