Update app.py

app.py

@@ -12,25 +12,27 @@ pipe.enable_model_cpu_offload()
 
 @spaces.GPU(duration=250)
 def generate(prompt, num_inference_steps=25):
-    video_frames = pipe(prompt, num_inference_steps).frames
-    resized_frames = []
-    for frame in video_frames:
-        height, width, _ = frame.shape
-        new_height = (height // 8) * 8
-        new_width = (width // 8) * 8
-        resized_frame = cv2.resize(frame, (new_width, new_height))
-        resized_frames.append(resized_frame)
-    video_path = export_to_video(np.array(resized_frames))
-    return video_path
+  video_frames = pipe(prompt, num_inference_steps).frames
+  resized_frames = []
+  allowed_resolutions = [16, 24, 32, 40, 48, 56, 64, 128, 256, 512]  # Define allowed resolutions (multiples of 8)
+  for frame in video_frames:
+    height, width, _ = frame.shape
+    # Find the closest allowed resolution smaller than the original
+    new_height = max(res for res in allowed_resolutions if res < height)
+    new_width = max(res for res in allowed_resolutions if res < width)
+    resized_frame = cv2.resize(frame, (new_width, new_height))
+    resized_frames.append(resized_frame)
+  video_path = export_to_video(np.array(resized_frames))
+  return video_path
 
 prompt = gr.Textbox("Enter prompt to generate a video")
 num_inference_steps = gr.Slider(10, 50, value=25)
 
 interface = gr.Interface(
-    generate,
-    inputs=[prompt, num_inference_steps],
-    examples=[["Astronaut riding a horse", 25], ["Darth vader surfing in waves", 20]],
-    outputs="video",
-    cache_examples=False,
-    theme="soft"
-).launch()
+  generate,
+  inputs=[prompt, num_inference_steps],
+  examples=[["Astronaut riding a horse", 25], ["Darth vader surfing in waves", 20]],
+  outputs="video",
+  cache_examples=False,
+  theme="soft"
+).launch()