diff --git a/kaldi_data_generator.py b/kaldi_data_generator.py
index c8a2cc0add99135971d940d747d9a8321cf84281..98f7420ddca81ac72f7e26d5e69f62a5e3ff33be 100644
--- a/kaldi_data_generator.py
+++ b/kaldi_data_generator.py
@@ -9,7 +9,7 @@ from enum import Enum
 from io import BytesIO
 from pathlib import Path
 from typing import Tuple
-import time
+
 import cv2
 import numpy as np
 import requests
@@ -99,20 +99,20 @@ class KaldiDataGenerator:
         lines = []
         try:
             if self.should_filter_by_class:
-                    accepted_zones = []
-                    for elt in api_client.paginate('ListElementChildren',id=page_id, with_best_classes=True):
-                        printed = True
-                        for classification in elt['best_classes']:
-                            if classification['ml_class']['name'] == 'handwritten':
-                                printed = False
-                        for classification in elt['best_classes']:
-                            if classification['ml_class']['name'] in self.accepted_classes:
-                                if self.should_filter_printed:
-                                    if not printed:
-                                        accepted_zones.append(elt['zone']['id'])
-                                else:
+                accepted_zones = []
+                for elt in api_client.paginate('ListElementChildren', id=page_id, with_best_classes=True):
+                    printed = True
+                    for classification in elt['best_classes']:
+                        if classification['ml_class']['name'] == 'handwritten':
+                            printed = False
+                    for classification in elt['best_classes']:
+                        if classification['ml_class']['name'] in self.accepted_classes:
+                            if self.should_filter_printed:
+                                if not printed:
                                     accepted_zones.append(elt['zone']['id'])
-                    logger.info('Number of accepted zone for page {} : {}'.format(page_id,len(accepted_zones)))
+                            else:
+                                accepted_zones.append(elt['zone']['id'])
+                logger.info('Number of accepted zone for page {} : {}'.format(page_id, len(accepted_zones)))
 
             for res in api_client.paginate('ListTranscriptions', id=page_id, type='line', recursive=True):
                 if self.should_filter_by_slug and res['source']['slug'] not in self.accepted_slugs:
@@ -120,7 +120,7 @@ class KaldiDataGenerator:
 
                 if self.should_filter_by_class and res['zone']['id'] not in accepted_zones:
                     continue
-                
+
                 text = res['text']
                 if not text or not text.strip():
                     continue
@@ -224,7 +224,8 @@ class Split(Enum):
 
 class KaldiPartitionSplitter:
 
-    def __init__(self, out_dir_base='/tmp/kaldi_data', split_train_ratio=0.8, split_test_ratio=0.1, use_existing_split=False):
+    def __init__(self, out_dir_base='/tmp/kaldi_data', split_train_ratio=0.8, split_test_ratio=0.1,
+                 use_existing_split=False):
         self.out_dir_base = out_dir_base
         self.split_train_ratio = split_train_ratio
         self.split_test_ratio = split_test_ratio
@@ -331,7 +332,7 @@ def create_parser():
                         help='List of accepted ml_class names. Filter lines by class of related elements')
 
     parser.add_argument('--filter_printed', action='store_true',
-    help='Filter lines annotated as printed')
+                        help='Filter lines annotated as printed')
     return parser
 
 
@@ -341,13 +342,14 @@ def main():
     logger.info(f"ARGS {args} \n")
 
     if not args.split_only:
-        kaldi_data_generator = KaldiDataGenerator(dataset_name=args.dataset_name,
-                                                  out_dir_base=args.out_dir,
-                                                  grayscale=args.grayscale,
-                                                  extraction=args.extraction_mode,
-                                                  accepted_slugs=args.accepted_slugs,
-                                                  accepted_classes=args.accepted_classes,
-                                                  filter_printed=args.filter_printed)
+        kaldi_data_generator = KaldiDataGenerator(
+            dataset_name=args.dataset_name,
+            out_dir_base=args.out_dir,
+            grayscale=args.grayscale,
+            extraction=args.extraction_mode,
+            accepted_slugs=args.accepted_slugs,
+            accepted_classes=args.accepted_classes,
+            filter_printed=args.filter_printed)
 
         # extract all the lines and transcriptions
         # if args.pages:
@@ -361,10 +363,11 @@ def main():
     else:
         logger.info("Creating a split from already downloaded files")
 
-    kaldi_partitioner = KaldiPartitionSplitter(out_dir_base=args.out_dir,
-                                               split_train_ratio=args.train_ratio,
-                                               split_test_ratio=args.test_ratio,
-                                               use_existing_split=args.use_existing_split)
+    kaldi_partitioner = KaldiPartitionSplitter(
+        out_dir_base=args.out_dir,
+        split_train_ratio=args.train_ratio,
+        split_test_ratio=args.test_ratio,
+        use_existing_split=args.use_existing_split)
 
     # create partitions from all the extracted data
     kaldi_partitioner.create_partitions()