app.py

import gradio as gr
from subprocess import call

# UI Components Setup with the generate function
with gr.Blocks() as ui:
    with gr.Row():
        video = gr.File(label="Video or Image", info="Filepath of video/image that contains faces to use")
        audio = gr.File(label="Audio", info="Filepath of video/audio file to use as raw audio source")
        with gr.Column():
            checkpoint = gr.Radio(["wav2lip", "wav2lip_gan"], label="Checkpoint", info="Name of saved checkpoint to load weights from")
            no_smooth = gr.Checkbox(label="No Smooth", info="Prevent smoothing face detections over a short temporal window")
            resize_factor = gr.Slider(minimum=1, maximum=4, step=1, label="Resize Factor", info="Reduce the resolution by this factor. Sometimes, best results are obtained at 480p or 720p")
    with gr.Row():
        with gr.Column():
            pad_top = gr.Slider(minimum=0, maximum=50, step=1, value=0, label="Pad Top", info="Padding above")
            pad_bottom = gr.Slider(minimum=0, maximum=50, step=1, value=10, label="Pad Bottom (Often increasing this to 20 allows chin to be included)", info="Padding below lips")
            pad_left = gr.Slider(minimum=0, maximum=50, step=1, value=0, label="Pad Left", info="Padding to the left of lips")
            pad_right = gr.Slider(minimum=0, maximum=50, step=1, value=0, label="Pad Right", info="Padding to the right of lips")
            generate_btn = gr.Button("Generate")
        with gr.Column():
           result = gr.Video()
        
        # Define the generate function
        def generate():
            if video is None or audio is None or checkpoint is None:
                return
        
            smooth = "--nosmooth" if no_smooth else ""
        
            cmd = [
                "python3.8",  # Use Python 3.8
                "inference.py",
                "--checkpoint_path", f"checkpoints/{checkpoint}.pth",
                "--segmentation_path", "checkpoints/face_segmentation.pth",
                "--enhance_face", "gfpgan",
                "--face", video.name,
                "--audio", audio.name,
                "--outfile", "results/output.mp4",
            ]

            call(cmd)
            result.value = "results/output.mp4"

# Create the interface
iface = gr.Interface(ui.queue(), generate_btn, "web", debug=True)

# Launch the interface
iface.launch(share=True)