Added logic to normalize tensors if needed

cspnodes.py

@@ -79,6 +79,10 @@ class Modelscopet2v:
         if not isinstance(video_frames, torch.Tensor):
             video_frames = torch.tensor(video_frames, dtype=torch.float32)
 
+        # Normalize the tensor to have values between 0 and 1 if they are in the range 0-255
+        if video_frames.max() > 1.0:
+            video_frames = video_frames / 255.0
+
         # Remove the unnecessary batch dimension explicitly and permute the dimensions
         # The expected shape is (num_frames, height, width, channels)
         video_frames = video_frames.squeeze(0).permute(0, 1, 2, 3)
@@ -140,6 +144,10 @@ class Modelscopev2v:
         if not isinstance(video_frames, torch.Tensor):
             video_frames = torch.tensor(video_frames, dtype=torch.float32)
 
+        # Normalize the tensor to have values between 0 and 1 if they are in the range 0-255
+        if video_frames.max() > 1.0:
+            video_frames = video_frames / 255.0
+        
         # The expected shape is (num_frames, height, width, channels)
         video_frames = video_frames.squeeze(0).permute(0, 1, 2, 3)