app.py

import torch
from PIL import Image
import imageio
from diffusers import StableVideoDiffusionPipeline
import gradio as gr

# Load the pipeline
pipe = StableVideoDiffusionPipeline.from_pretrained(
    "stabilityai/stable-video-diffusion-img2vid-xt", torch_dtype=torch.float16, variant="fp16"
)
pipe.enable_model_cpu_offload()

def generate_video(image, seed=42, fps=7):
    # Resize the image
    image = image.resize((1024, 576))

    # Set the generator seed
    generator = torch.manual_seed(seed)

    # Generate the frames
    frames = pipe(image, decode_chunk_size=8, generator=generator).frames[0]

    # Export the frames to a video
    output_path = "generated.mp4"
    imageio.mimwrite(output_path, frames, fps=fps)

    return output_path

# Create the Gradio interface
iface = gr.Interface(
    fn=generate_video,
    inputs=[
        gr.Image(type="pil", label="Upload Image"),
        gr.Number(label="Seed", value=42),
        gr.Number(label="FPS", value=7)
    ],
    outputs=gr.Video(label="Generated Video"),
    title="Stable Video Diffusion",
    description="Generate a video from an uploaded image using Stable Video Diffusion."
)

# Launch the interface
iface.launch()