app.py

import gradio as gr
import subprocess
import os

def run_inference(audio_file):
    # Define the output video filename
    output_video = "output_video.mp4"  # Change this to your desired output filename

    # Define the command to run your script
    command = [
        "python", "scripts/demo.py",
        "--config_file", "./config/LS3DCG.json",
        "--infer",
        "--audio_file", audio_file,
        "--body_model_name", "s2g_LS3DCG",
        "--body_model_path", "experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth",
        "--id", "0",
        "--output_video", output_video  # Ensure demo.py saves to this filename
    ]
    
    # Run the command and capture the output
    result = subprocess.run(command, capture_output=True, text=True)
    
    # Check for errors
    if result.returncode != 0:
        return f"Error: {result.stderr}"
    
    # Return the generated video file path
    return output_video

# Create Gradio interface
interface = gr.Interface(
    fn=run_inference,
    inputs=gr.Audio(source="upload", type="filepath"),
    outputs=gr.Video(type="file"),
    title="Audio to Video Inference",
    description="Upload an audio file to generate a video."
)

# Launch the app
if __name__ == "__main__":
    interface.launch()