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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 nnunet.experiment_planning.utils import split_4d, crop, analyze_dataset, plan_and_preprocess
from batchgenerators.utilities.file_and_folder_operations import *
from nnunet.paths import nnUNet_raw_data
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-t', '--task', type=str, help="task name. There must be a matching folder in "
"raw_dataset_dir", required=True)
parser.add_argument('-pl', '--processes_lowres', type=int, default=8, help='number of processes used for '
'preprocessing 3d_lowres data, image '
'splitting and image cropping '
'Default: 8. The distinction between '
'processes_lowres and processes_fullres '
'is necessary because preprocessing '
'at full resolution needs a lot of '
'RAM', required=False)
parser.add_argument('-pf', '--processes_fullres', type=int, default=8, help='number of processes used for '
'preprocessing 2d and 3d_fullres '
'data. Default: 3', required=False)
parser.add_argument('-o', '--override', type=int, default=0, help="set this to 1 if you want to override "
"cropped data and intensityproperties. Default: 0",
required=False)
parser.add_argument('-s', '--use_splitted', type=int, default=1, help='1 = use splitted data if already present ('
'skip split_4d). 0 = do splitting again. '
'It is save to set this to 1 at all times '
'unless the dataset was updated in the '
'meantime. Default: 1', required=False)
parser.add_argument('-no_preprocessing', type=int, default=0, help='debug only. If set to 1 this will run only'
'experiment planning and not run the '
'preprocessing')
args = parser.parse_args()
task = args.task
processes_lowres = args.processes_lowres
processes_fullres = args.processes_fullres
override = args.override
use_splitted = args.use_splitted
no_preprocessing = args.no_preprocessing
if override == 0:
override = False
elif override == 1:
override = True
else:
raise ValueError("only 0 or 1 allowed for override")
if no_preprocessing == 0:
no_preprocessing = False
elif no_preprocessing == 1:
no_preprocessing = True
else:
raise ValueError("only 0 or 1 allowed for override")
if use_splitted == 0:
use_splitted = False
elif use_splitted == 1:
use_splitted = True
else:
raise ValueError("only 0 or 1 allowed for use_splitted")
if task == "all":
all_tasks = subdirs(nnUNet_raw_data, prefix="Task", join=False)
for t in all_tasks:
crop(t, override=override, num_threads=processes_lowres)
analyze_dataset(t, override=override, collect_intensityproperties=True, num_processes=processes_lowres)
plan_and_preprocess(t, processes_lowres, processes_fullres, no_preprocessing)
else:
if not use_splitted or not isdir(join(nnUNet_raw_data, task)):
print("splitting task ", task)
split_4d(task)
crop(task, override=override, num_threads=processes_lowres)
analyze_dataset(task, override, collect_intensityproperties=True, num_processes=processes_lowres)
plan_and_preprocess(task, processes_lowres, processes_fullres, no_preprocessing)
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