Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from diffusers import DiffusionPipeline
 import torch
+import numpy as np
 from PIL import Image
 import time
 import warnings
@@ -30,23 +31,27 @@ def generate_video(prompt, num_frames=8, num_inference_steps=20):
     
     # Generate with lower resolution and fewer frames for CPU
     with torch.no_grad():
-        video_frames = generate_video.pipe(
+        output = generate_video.pipe(
             prompt,
             num_frames=min(num_frames, 8),  # Keep frames low for CPU
             num_inference_steps=min(num_inference_steps, 20),
             height=256,  # Lower resolution
             width=256
-        ).frames
+        )
     
-    # Create GIF (simpler than video for CPU)
+    # Convert numpy arrays to PIL Images
+    frames = [Image.fromarray((frame * 255).astype(np.uint8)) for frame in output.frames]
+    
+    # Create GIF
     gif_path = "output.gif"
     duration = max(1000 // 3, 100)  # Minimum 100ms per frame
-    video_frames[0].save(
+    frames[0].save(
         gif_path,
         save_all=True,
-        append_images=video_frames[1:],
+        append_images=frames[1:],
         duration=duration,
-        loop=0
+        loop=0,
+        save_format='GIF'
     )
     
     gen_time = time.time() - start_time