Create app.py

app.py

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+import gradio as gr
+from diffusers import StableVideoDiffusionPipeline
+from diffusers.utils import load_image, export_to_video
+import torch
+import tempfile
+import os
+
+# Load the model
+pipe = StableVideoDiffusionPipeline.from_pretrained(
+    "stabilityai/stable-video-diffusion-img2vid-xt",
+    torch_dtype=torch.float16,
+    variant="fp16"
+)
+pipe.enable_model_cpu_offload()  # Optimize for low memory
+
+# Function to generate video
+def generate_video(image, num_frames=14, fps=7):
+    if image is None:
+        return None
+    frames = pipe(image, num_frames=num_frames, fps=fps).frames[0]
+    with tempfile.TemporaryDirectory() as tmpdirname:
+        temp_video_path = os.path.join(tmpdirname, "output.mp4")
+        export_to_video(frames, temp_video_path, fps=fps)
+        return temp_video_path
+
+# Gradio interface
+iface = gr.Interface(
+    fn=generate_video,
+    inputs=[
+        gr.Image(type="pil", label="Upload an Image"),
+        gr.Slider(5, 25, value=14, label="Number of Frames"),
+        gr.Slider(5, 10, value=7, label="FPS")
+    ],
+    outputs=gr.Video(label="Generated Video"),
+    title="AI Video Generator",
+    description="Turn an image into a short video using Stable Video Diffusion!"
+)
+
+if __name__ == "__main__":
+    iface.launch()