Update app.py

app.py

@@ -3,7 +3,8 @@ from diffusers import StableVideoDiffusionPipeline, EulerDiscreteScheduler
 import torch
 from PIL import Image
 import tempfile
-import spaces
+import imageio
+
 # Load the Stable Video Diffusion model
 model_id = "stabilityai/stable-video-diffusion-img2vid-xt"
 try:
@@ -13,7 +14,6 @@ try:
 except Exception as e:
     raise RuntimeError(f"Failed to load the model: {e}")
 
-@spaces.GPU(duration=300)
 def generate_video(image, num_frames=25, height=576, width=1024):
     try:
         # Convert the image to a format suitable for the pipeline
@@ -23,8 +23,8 @@ def generate_video(image, num_frames=25, height=576, width=1024):
         # Save the video frames to a temporary file
         with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as temp_video:
             video_path = temp_video.name
-            # Assuming video_frames is a list of PIL images
-            video_frames[0].save(video_path, save_all=True, append_images=video_frames[1:], duration=100, loop=0)
+            # Save the frames as a video using imageio
+            imageio.mimsave(video_path, video_frames, fps=30)
         return video_path
     except Exception as e:
         raise RuntimeError(f"Failed to generate the video: {e}")
@@ -50,5 +50,4 @@ with gr.Blocks() as demo:
 
 # Launch the interface
 if __name__ == "__main__":
-    demo.launch()
-    
+    demo.launch()