--- a
+++ b/bash_app.py
@@ -0,0 +1,54 @@
+import argparse
+import os
+import cv2
+from src.production import make_masks, data_to_paths, create_folder, get_setup, make_legend
+
+# parser arguments
+parser = argparse.ArgumentParser()
+parser.add_argument("--data",
+                    help="image or folder with CT-images,"
+                         "supported image formats: png, jpg, jpeg"
+                         "also you can use .nii or .nii.gz formats",
+                    required=True)
+parser.add_argument("--save_folder",
+                    help="folder to save segmentations and images",
+                    default="example",
+                    required=True)
+parser.add_argument("--multi",
+                    action="store_true",
+                    default=False,
+                    help="if \"multi\" shows ground-glass opacities and consolidation")
+parser.add_argument("--show_legend",
+                    action="store_true",
+                    default=False,
+                    help="if \"show_legend\" legend shows on image")
+
+# parsing
+args = parser.parse_args()
+save_folder = args.save_folder
+
+# setup
+models, transforms = get_setup()
+
+# reformatting all data to png format and getting paths
+paths = data_to_paths(args.data, args.save_folder)
+
+# preparing place for segmentation
+for x in ['segmentations', 'annotations']:
+    create_folder(os.path.join(save_folder, x))
+
+# prediction
+for img, annotation, path in make_masks(paths, models, transforms, args.multi):
+    # annotation saving
+    print(path)
+    name = path.split('\\')[-1].split('.')[0].split('/')[-1]
+    print(name)
+    with open(os.path.join(save_folder, 'annotations', name + '_annotation.txt'), mode='w') as f:
+        f.write(annotation)
+
+    # image saving
+    path = os.path.join(save_folder, 'segmentations', name + '_mask.png')
+    if args.show_legend:
+        img = make_legend(img, annotation)
+    cv2.imwrite(path, img)
+    print(path, annotation, '', sep='\n')