Update app.py

app.py

@@ -12,8 +12,11 @@ def run_talkshow_model(audio_file):
     body_model_path = 'experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth'
     
     # Path of the uploaded audio file
-    audio_file_path = audio_file  # This is the file path returned by Gradio
-
+    audio_file_path = audio_file
+    
+    # Path where the output .mp4 video will be saved
+    output_video_path = './output_video/result.mp4'
+    
     # Run the demo.py script with the necessary arguments
     command = [
         'python', demo_script,
@@ -22,24 +25,31 @@ def run_talkshow_model(audio_file):
         '--audio_file', audio_file_path,
         '--body_model_name', body_model_name,
         '--body_model_path', body_model_path,
-        '--id', '0'
+        '--id', '0',
+        '--output', output_video_path  # Assuming demo.py has an argument to specify output
     ]
     
-    # Run the subprocess and capture any output
     try:
-        subprocess.run(command, check=True)
-        return "Mesh generated successfully!"
+        # Run the subprocess and capture output
+        subprocess.run(command, check=True, capture_output=True, text=True)
+        
+        # Check if the .mp4 file is generated
+        if os.path.exists(output_video_path):
+            return output_video_path  # Return the path of the generated video
+        else:
+            return "Error: Output video not generated."
+    
     except subprocess.CalledProcessError as e:
-        return f"Error running the model: {str(e)}"
+        return f"Error running the model: {e.stderr}"  # Return the error message
 
 # Set up the Gradio interface
 interface = gr.Interface(
     fn=run_talkshow_model, 
     inputs=gr.Audio(source="upload", type="filepath"), 
-    outputs="text",
+    outputs=gr.Video(),  # Use gr.Video to output the generated .mp4 video
     title="TalkSHOW: Audio to Mesh"
 )
 
 # Launch the interface
 if __name__ == "__main__":
-    interface.launch()
+    interface.launch()