app.py

import gradio as gr
import subprocess

# Function to run Wav2Lip model
def run_wav2lip(video, audio):
    # Define the command to run the Wav2Lip model
    command = f"python inference.py --checkpoint_path checkpoints/wav2lip_gan.pth --face '{video}' --audio '{audio}' --outfile output_result.mp4"
    
    # Execute the command
    subprocess.run(command, shell=True, check=True)

    # Return the output video file path
    return "output_result.mp4"

# Gradio Interface
with gr.Blocks() as interface:
    gr.Markdown("# Wav2Lip Model")
    gr.Markdown("Upload a video and an audio file to generate a lip-synced video.")

    # Input components
    video_input = gr.Video(label="Input Video")
    audio_input = gr.Audio(label="Input Audio")

    # Output component
    output_video = gr.Video(label="Output Video")

    # Button to trigger Wav2Lip processing
    run_button = gr.Button("Run Wav2Lip")

    # Define the button click action
    run_button.click(run_wav2lip, inputs=[video_input, audio_input], outputs=output_video)

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