demo.py

import gradio as gr
import os
import tempfile
import base64
from main import process

def process_image_and_generate_video(image, prompt):
    # Create a temporary directory for intermediate files
    with tempfile.TemporaryDirectory() as temp_dir:
        # Save the uploaded image to a temporary file
        temp_image_path = os.path.join(temp_dir, "input_image.png")
        image.save(temp_image_path)
        
        # Encode the image as base64 and create a data URL
        with open(temp_image_path, "rb") as f:
            encoded_image = base64.b64encode(f.read()).decode("utf-8")
        data_url = f"data:image/png;base64,{encoded_image}"
        
        # Process the image and generate video
        # The process function now handles saving to numbered directories
        result, generated_image_path, video_path = process(data_url, prompt, temp_dir)
        
        if result and video_path:
            return video_path
        else:
            return None

# Create the Gradio interface
with gr.Blocks(title="Character Video Generation") as demo:
    gr.Markdown("# Character Video Generation")
    gr.Markdown("""
    * Upload a high-quality image of a person
    * Enter a prompt to generate a video
    """)
    
    with gr.Row():
        with gr.Column():
            input_image = gr.Image(type="pil", label="Upload Reference Image")
            prompt = gr.Textbox(label="Enter your prompt")
            generate_btn = gr.Button("Generate")
        
        with gr.Column():
            output_video = gr.Video(label="Generated Video")
    
    generate_btn.click(
        fn=process_image_and_generate_video,
        inputs=[input_image, prompt],
        outputs=[output_video]
    )

if __name__ == "__main__":
    demo.launch(share=True)