Fix: use torchvision.transforms.functional.gaussian_blur

app.py

@@ -228,15 +228,15 @@ def apply_gaussian_blur(video_tensor: torch.Tensor, blur_amount: int) -> torch.T
     if blur_amount <= 0:
         return video_tensor
 
-    import torch.nn.functional as F
+    from torchvision.transforms.functional import gaussian_blur
 
     # Ensure kernel size is odd and at least 3
     kernel_size = blur_amount * 2 + 1
     sigma = blur_amount / 2.0
 
-    # F.gaussian_blur expects [batch, channels, H, W]
+    # gaussian_blur expects [batch, channels, H, W] or [channels, H, W]
     # Our video is [frames, channels, H, W] which works directly
-    blurred = F.gaussian_blur(video_tensor, kernel_size=[kernel_size, kernel_size], sigma=[sigma, sigma])
+    blurred = gaussian_blur(video_tensor, kernel_size=[kernel_size, kernel_size], sigma=[sigma, sigma])
 
     return blurred