Update app.py

app.py

@@ -2,18 +2,23 @@ import torch
 import gradio as gr
 from diffusers import StableVideoDiffusionPipeline
 from diffusers.utils import load_image, export_to_video
+import os
 import spaces
 
 # Check if GPU is available
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-# Load the pipeline
+# Load the pipeline with optimizations
 pipeline = StableVideoDiffusionPipeline.from_pretrained(
     "stabilityai/stable-video-diffusion-img2vid-xt", torch_dtype=torch.float16, variant="fp16"
 )
 pipeline.to(device)
 
-@spaces.GPU(duration=120)
+# Enable forward chunking to reduce memory usage
+pipeline.unet.enable_forward_chunking(chunk_size=1)
+
+@spaces.GPU
+# Define the video generation function
 def generate_video(image_path, seed):
     # Load and preprocess the image
     image = load_image(image_path)
@@ -40,11 +45,13 @@ iface = gr.Interface(
     ],
     outputs=gr.Video(label="Generated Video"),
     title="Stable Video Diffusion",
+    description="Generate a video from an uploaded image using Stable Video Diffusion.",
     examples=[
-        ["image.jpeg"],
-        ["generated.mp4"]
+        ["example.jpeg", 666666]
     ],
-    description="Generate a video from an uploaded image using Stable Video Diffusion.",
+    cache_examples=True  # Enable caching of examples
 )
+
 # Launch the interface
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()