Delete app.py

app.py

@@ -1,58 +0,0 @@
-import gradio as gr
-import subprocess
-import os
-import json
-
-def get_log_name(config_file):
-    """Load the JSON configuration file to extract the log name."""
-    with open(config_file, 'r') as f:
-        config = json.load(f)
-    return config['Log']['name']  # Adjust this if the structure is different
-
-def run_inference(audio_file):
-    # Extract the audio filename
-    audio_filename = os.path.basename(audio_file)
-
-    # Load the configuration to get the log name
-    config_file = './config/LS3DCG.json'
-    config_log_name = get_log_name(config_file)
-
-    # Define the command to run your script
-    command = [
-        "python", "scripts/demo.py",
-        "--config_file", config_file,
-        "--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"
-    ]
-    
-    # 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}"
-
-    # Construct the output video filename based on the log name
-    output_video_path = f'visualise/video/{config_log_name}/{audio_filename.rsplit(".", 1)[0]}.mp4'
-    
-    # Check if the video file exists and return the path
-    if os.path.exists(output_video_path):
-        return output_video_path
-    else:
-        return "Video file not found."
-
-# 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()