Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from diffusers import StableVideoDiffusionPipeline, EulerDiscreteScheduler
 import torch
+from PIL import Image
 import spaces
 
 # Load the Stable Video Diffusion model
@@ -11,8 +12,10 @@ pipe.to("cuda")
 
 @spaces.GPU
 def generate_video(image, prompt, num_frames=25, height=576, width=1024):
+    # Convert the image to a format suitable for the pipeline
+    image = Image.open(image)
     # Generate the video
-    video_frames = pipe(prompt, image=image, num_frames=num_frames, height=height, width=width).frames
+    video_frames = pipe(prompt=prompt, init_image=image, num_frames=num_frames, height=height, width=width).frames
     return video_frames
 
 # Create the Gradio interface
@@ -20,7 +23,7 @@ with gr.Blocks() as demo:
     gr.Markdown("## Image to Video with Stable Diffusion XT")
     with gr.Row():
         with gr.Column():
-            image_input = gr.Image(type="pil", label="Upload Image")
+            image_input = gr.Image(type="filepath", label="Upload Image")
             prompt_input = gr.Textbox(lines=2, placeholder="Enter prompt...", label="Prompt")
             num_frames_input = gr.Slider(1, 50, step=1, value=25, label="Number of Frames")
             height_input = gr.Number(label="Resolution Height", value=576)
@@ -37,5 +40,4 @@ with gr.Blocks() as demo:
 
 # Launch the interface
 if __name__ == "__main__":
-    demo.launch()
-    
+    demo.launch()