import gradio as gr from subprocess import call # UI Components Setup 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(video, audio, checkpoint, no_smooth, resize_factor, pad_top, pad_bottom, pad_left, pad_right): if video is None or audio is None or checkpoint is None: return smooth = "--nosmooth" if no_smooth else "" cmd = [ "python", "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) return "results/output.mp4" # Click event for the Generate button generate_btn.click( generate, [video, audio, checkpoint, no_smooth, resize_factor, pad_top, pad_bottom, pad_left, pad_right], result) # Create the interface iface = gr.Interface(ui.queue(), "web", debug=True) # Launch the interface iface.launch()