Create app.py

app.py

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+import gradio as gr
+from subprocess import call
+
+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()
+
+    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"
+
+    generate_btn.click(
+        generate, 
+        [video, audio, checkpoint, pad_top, pad_bottom, pad_left, pad_right, resize_factor], 
+        result)
+
+ui.queue().launch(share=True, debug=True, inline=False)