Update app.py

app.py

@@ -1 +1,47 @@
-python scripts/demo.py --config_file ./config/LS3DCG.json --infer --audio_file ./demo_audio/style.wav --body_model_name s2g_LS3DCG --body_model_path experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth --id 0
+import gradio as gr
+import subprocess
+import os
+
+def run_talkshow_model(audio_file):
+    # Path to the TalkSHOW demo script
+    demo_script = 'scripts/demo.py'
+    
+    # Configuration and model parameters
+    config_file = './config/LS3DCG.json'
+    body_model_name = 's2g_LS3DCG'
+    body_model_path = 'experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth'
+    
+    # Temporary path to store the uploaded audio file
+    audio_file_path = './demo_audio/uploaded_audio.wav'
+    
+    # Save the uploaded audio file to the expected location
+    audio_file.save(audio_file_path)
+    
+    # Run the demo.py script with the necessary arguments
+    command = [
+        'python', demo_script,
+        '--config_file', config_file,
+        '--infer',
+        '--audio_file', audio_file_path,
+        '--body_model_name', body_model_name,
+        '--body_model_path', body_model_path,
+        '--id', '0'
+    ]
+    
+    # Run the subprocess and capture any output
+    try:
+        subprocess.run(command, check=True)
+        return "Mesh generated successfully!"
+    except subprocess.CalledProcessError as e:
+        return f"Error running the model: {str(e)}"
+
+# Set up the Gradio interface
+interface = gr.Interface(
+    fn=run_ttalkshow_model, 
+    inputs=gr.Audio(source="upload", type="filepath"), 
+    outputs="text",
+    title="TalkSHOW: Audio to Mesh"
+)
+
+# Launch the interface
+interface.launch()