Create app.py

app.py

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+import gradio as gr
+import os
+import subprocess
+import gdown
+
+# Auto-download the Wav2Lip pretrained model if it doesn't exist
+def download_model():
+    model_url = 'https://drive.google.com/uc?id=1rwXzZ1R5RkAqpKfx-9k3dxC5Pp1fSzJv'
+    model_path = "wav2lip.pth"
+    if not os.path.exists(model_path):
+        gdown.download(model_url, model_path, quiet=False)
+    return model_path
+
+# Main lipsync function
+def sync_lips(video, audio):
+    model_path = download_model()
+    output_path = "results/result_voice.mp4"
+    os.makedirs("results", exist_ok=True)
+    command = f"python3 inference.py --checkpoint_path {model_path} --face {video} --audio {audio} --outfile {output_path}"
+    subprocess.call(command, shell=True)
+    return output_path
+
+# Gradio Interface
+demo = gr.Interface(
+    fn=sync_lips,
+    inputs=["video", "audio"],
+    outputs="video",
+    title="Lip Sync Generator",
+    description="Upload a face video (.mp4) and an audio file (.wav) to get a lip-synced output using Wav2Lip model."
+)
+
+demo.launch()