diff --git a/hd_gliomouse/__pycache__/__init__.cpython-36.pyc b/hd_gliomouse/__pycache__/__init__.cpython-36.pyc
index 5db5f36..68cdc11 100644
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diff --git a/hd_gliomouse/__pycache__/hd_gliomouse_predict_folder.cpython-36.pyc b/hd_gliomouse/__pycache__/hd_gliomouse_predict_folder.cpython-36.pyc
index 70f8748..0eadc8c 100644
Binary files a/hd_gliomouse/__pycache__/hd_gliomouse_predict_folder.cpython-36.pyc and b/hd_gliomouse/__pycache__/hd_gliomouse_predict_folder.cpython-36.pyc differ
diff --git a/hd_gliomouse/hd_gliomouse_predict_folder.py b/hd_gliomouse/hd_gliomouse_predict_folder.py
index 2760220..676cdc1 100644
--- a/hd_gliomouse/hd_gliomouse_predict_folder.py
+++ b/hd_gliomouse/hd_gliomouse_predict_folder.py
@@ -1,60 +1,60 @@
 #    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 subfiles, join
 from hd_gliomouse.utils import blockPrint, enablePrint
 blockPrint()
 from nnunet.inference.predict import predict_cases
 enablePrint()
 import argparse
 from hd_gliomouse.paths import folder_with_parameter_files
 from hd_gliomouse.setup_hd_gliomouse import maybe_download_weights
 
 
 def main():
     parser = argparse.ArgumentParser()
     parser.add_argument("-i", "--input_folder", type=str, required=True,
                         help="folder with input files. All .nii.gz files in this folder will be processed.")
     parser.add_argument("-o", "--output_folder", type=str, required=True,
                         help="output folder. This is there the resulting segmentations will be saved. Cannot be the "
                              "same folder as the input folder. If output_folder does not exist "
                              "it will be created")
     parser.add_argument("-p", "--processes", default=4, type=str, required=False,
                         help="number of processes for data preprocessing and nifti export. You should not have to "
                              "touch this. So don't unless there is a clear indication that it is required. Default: 4")
-    parser.add_argument('--keep_existing', default=True, type=str, required=False, action='store_false',
+    parser.add_argument('--keep_existing', default=True, required=False, action='store_false',
                         help="set to False to keep segmentations in output_folder and continue where you left off "
                              "(useful if something crashes). If this flag is not set, all segmentations that may "
                              "already be present in output_folder will be overwritten.")
 
     args = parser.parse_args()
     input_folder = args.input_folder
     output_folder = args.output_folder
     processes = args.processes
     keep_existing = args.keep_existing
 
     maybe_download_weights()
 
     # we must generate a list of input filenames
     nii_files = subfiles(input_folder, suffix='.nii.gz', join=False)
     input_list_of_lists = [[join(input_folder, i)] for i in nii_files]
 
     output_filenames = [join(output_folder, i) for i in nii_files]
 
     predict_cases(folder_with_parameter_files, input_list_of_lists, output_filenames, (0, 1, 2, 3, 4), False, processes,
                   processes, None, True, None, not keep_existing, False, 2, None, 3, 0)
 
 
 if __name__ == "__main__":
     main()
diff --git a/setup.py b/setup.py
index a0e8912..80cdee2 100644
--- a/setup.py
+++ b/setup.py
@@ -1,33 +1,33 @@
 from setuptools import setup
 
 
 setup(name='hd_gliomouse',
-      version='1.0',
+      version='1.1',
       packages=["hd_gliomouse"],
       description='Tool for brain tumor segmentation in mice. This is the result of a joint project between the Department of '
                   'Neuroradiology at the Heidelberg University Hospital and the Division of Medical Image Computing at '
                   'the German Cancer Research Center (DKFZ). See readme.md for more information',
       url='https://github.com/NeuroAI-HD/HD-GLIOMOUSE',
       python_requires='>=3.5',
       author='Fabian Isensee',
       author_email='f.isensee@dkfz.de',
       license='Apache 2.0',
       zip_safe=False,
       install_requires=[
           'torch',
           'nnunet>1.0', 'batchgenerators'
       ],
       entry_points={
           'console_scripts': [
                 'hd_gliomouse_predict = hd_gliomouse.hd_gliomouse_predict:main',
                 'hd_gliomouse_predict_folder = hd_gliomouse.hd_gliomouse_predict_folder:main',
         ],
       },
       classifiers=[
           'Intended Audience :: Science/Research',
           'Programming Language :: Python',
           'Topic :: Scientific/Engineering',
           'Operating System :: Unix'
       ]
       )