diff --git a/codes/scripts/extract_subimages_with_ref.py b/codes/scripts/extract_subimages_with_ref.py
index 706a5164..7fbaf998 100644
--- a/codes/scripts/extract_subimages_with_ref.py
+++ b/codes/scripts/extract_subimages_with_ref.py
@@ -19,10 +19,10 @@ def main():
     # compression time. If read raw images during training, use 0 for faster IO speed.
 
     opt['dest'] = 'file'
-    opt['input_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\images'
-    opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\256_with_ref_v3'
+    opt['input_folder'] = 'F:\\4k6k\\datasets\\images\youtube\\4k_quote_unquote\\images_1'
+    opt['save_folder'] = 'F:\\4k6k\\datasets\\images\\youtube_massive'
     opt['crop_sz'] = [512, 1024, 2048]  # the size of each sub-image
-    opt['step'] = [256, 512, 1024]  # step of the sliding crop window
+    opt['step'] = [512, 1024, 2048]  # step of the sliding crop window
     opt['exclusions'] = [[],[],[]] # image names matching these terms wont be included in the processing.
     opt['thres_sz'] = 256  # size threshold
     opt['resize_final_img'] = [.5, .25, .125]
diff --git a/codes/utils/util.py b/codes/utils/util.py
index 0f01326f..146a880c 100644
--- a/codes/utils/util.py
+++ b/codes/utils/util.py
@@ -45,7 +45,10 @@ def OrderedYaml():
 
 # Conditionally uses torch's checkpoint functionality if it is enabled in the opt file.
 def checkpoint(fn, *args):
-    enabled = loaded_options['checkpointing_enabled'] if 'checkpointing_enabled' in loaded_options.keys() else True
+    if loaded_options is None:
+        enabled = False
+    else:
+        enabled = loaded_options['checkpointing_enabled'] if 'checkpointing_enabled' in loaded_options.keys() else True
     if enabled:
         return torch.utils.checkpoint.checkpoint(fn, *args)
     else: