diff --git a/examples/YOLOv8-Action-Recognition/action_recognition.py b/examples/YOLOv8-Action-Recognition/action_recognition.py
index d5fa6da721..40a237f339 100644
--- a/examples/YOLOv8-Action-Recognition/action_recognition.py
+++ b/examples/YOLOv8-Action-Recognition/action_recognition.py
@@ -212,7 +212,9 @@ class HuggingFaceVideoClassifier:
                 [
                     v2.ToDtype(torch.float32, scale=True),
                     v2.Resize(input_size, antialias=True),
-                    v2.Normalize(mean=self.processor.image_processor.image_mean, std=self.processor.image_processor.image_std),
+                    v2.Normalize(
+                        mean=self.processor.image_processor.image_mean, std=self.processor.image_processor.image_std
+                    ),
                 ]
             )
         else:
diff --git a/ultralytics/solutions/action_recognition.py b/ultralytics/solutions/action_recognition.py
index 8db57e32af..b0623ca540 100644
--- a/ultralytics/solutions/action_recognition.py
+++ b/ultralytics/solutions/action_recognition.py
@@ -207,9 +207,7 @@ class TorchVisionVideoClassifier:
     supports_r3d = check_requirements("torchvision>=0.8.1", install=False)
     supports_transforms_v2 = check_requirements("torchvision>=0.16.0", install=False)
     supports_mvitv1b = supports_s3d = check_requirements("torchvision>=0.14.0", install=False)
-    supports_mvitv2s = supports_swin3dt = supports_swin3db = check_requirements(
-        "torchvision>=0.15.0", install=False
-    )
+    supports_mvitv2s = supports_swin3dt = supports_swin3db = check_requirements("torchvision>=0.15.0", install=False)
 
     model_name_to_model_and_weights = {}
     if supports_r3d:
@@ -396,7 +394,9 @@ class HuggingFaceVideoClassifier:
                 [
                     v2.ToDtype(torch.float32, scale=True),
                     v2.Resize(input_size, antialias=True),
-                    v2.Normalize(mean=self.processor.image_processor.image_mean, std=self.processor.image_processor.image_std),
+                    v2.Normalize(
+                        mean=self.processor.image_processor.image_mean, std=self.processor.image_processor.image_std
+                    ),
                 ]
             )
         else: