Update app.py

app.py

@@ -18,23 +18,19 @@ interface = gr.Interface(
 )
 
 @spaces.GPU(duration=200)
-def generate_video(img):
-    # Convert the input image to a tensor
-    img_tensor = torch.tensor(img).unsqueeze(0) / 255.0
-    
-    # Run the pipeline to generate the video
-    output = pipeline(img_tensor)
-    
-    # Extract the video frames from the output
-    video_frames = output["video_frames"]
-    
-    # Convert the video frames to a video
-    video = []
-    for frame in video_frames:
-        video.append(Image.fromarray(frame.detach().cpu().numpy()))
-    
-    # Return the generated video
-    return video
+def generate_video(image):
+  """
+  Generates a video from an input image using the pipeline.
+
+  Args:
+      image: A PIL Image object representing the input image.
+
+  Returns:
+      A list of PIL Images representing the video frames.
+  """
+  video_frames = pipeline(image=image).images
+
+  return video_frames
 
 # Launch the Gradio app
 interface.launch()