--- a
+++ b/utils.py
@@ -0,0 +1,53 @@
+import argparse
+import numpy as np
+import nibabel as nib
+from skimage.transform import resize as skires
+import csv
+import yaml
+import numpy as np
+
+def str2bool(v):
+    if v.lower() in ['true', 1]:
+        return True
+    elif v.lower() in ['false', 0]:
+        return False
+    else:
+        raise argparse.ArgumentTypeError('Boolean value expected.')
+    
+class DotDict:
+    def __init__(self, dictionary):
+        self._dict = dictionary
+
+    def __getattr__(self, attr):
+        value = self._dict[attr]
+        if isinstance(value, dict):
+            return DotDict(value)
+        return value
+    
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--network', default=None, help='architecture name')
+    parser.add_argument('--name', default=None, help='model name')
+    parser = parser.parse_args()
+    with open(f'outputs/{parser.network}/{parser.name}/config.yml', 'r') as f:
+        config = yaml.load(f, Loader=yaml.FullLoader)
+    config = DotDict(config)
+    return config
+        
+def save_vol(vol, type, path):
+    vol = np.transpose(vol, (2, 1, 0))
+    affine = np.eye(4)
+    nifti_file = nib.Nifti1Image(vol.astype(np.int8), affine) if type=='labels' else nib.Nifti1Image(vol, affine)
+    nib.save(nifti_file, path)    
+    
+def resize_vol(vol, new_size):
+    return skires(vol, new_size, order=1, preserve_range=True, anti_aliasing=False)
+
+
+def write_csv(path, data):
+    with open(path, mode='a', newline='') as file:
+        iteration = csv.writer(file)
+        iteration.writerow(data)
+    file.close()
+    
+