Update app.py

app.py

@@ -1,14 +1,42 @@
-import pyrender
-import numpy as np
-import trimesh
+import gradio as gr
+import subprocess
+import os
 
-# Create a simple mesh
-mesh = trimesh.Sphere(radius=1.0)
-mesh = pyrender.Mesh.from_trimesh(mesh)
+def run_inference(audio_file):
+    # Define the output video filename
+    output_video = "output_video.mp4"  # Change this to your desired output filename
 
-# Create a scene and add the mesh
-scene = pyrender.Scene()
-scene.add(mesh)
+    # Define the command to run your script
+    command = [
+        "python", "scripts/demo.py",
+        "--config_file", "./config/LS3DCG.json",
+        "--infer",
+        "--audio_file", audio_file,
+        "--body_model_name", "s2g_LS3DCG",
+        "--body_model_path", "experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth",
+        "--id", "0",
+        "--output_video", output_video  # Ensure demo.py saves to this filename
+    ]
+    
+    # Run the command and capture the output
+    result = subprocess.run(command, capture_output=True, text=True)
+    
+    # Check for errors
+    if result.returncode != 0:
+        return f"Error: {result.stderr}"
+    
+    # Return the generated video file path
+    return output_video
 
-# Create a viewer
-pyrender.Viewer(scene, use_raymond_lights=True)
+# Create Gradio interface
+interface = gr.Interface(
+    fn=run_inference,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs=gr.Video(type="file"),
+    title="Audio to Video Inference",
+    description="Upload an audio file to generate a video."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch()