app

import gradio as gr
import cv2
import numpy as np
from PIL import Image
import os
import warnings

# Suppress warnings
warnings.filterwarnings('ignore')

def create_gui():
    # Create the main interface
    with gr.Blocks(theme=gr.themes.Base(
        primary_hue=gr.themes.colors.red,
        font=gr.themes.GoogleFont('Open Sans')
    )) as interface:
        gr.Markdown("# FaceFusion")
        
        with gr.Tab("Swap"):
            with gr.Row():
                with gr.Column():
                    source_image = gr.Image(label="Source Face", type="pil")
                    target_image = gr.Image(label="Target Image/Video", type="pil")
                
                with gr.Column():
                    output_image = gr.Image(label="Result")
                    
            with gr.Row():
                process_button = gr.Button("Process", variant="primary")
                clear_button = gr.Button("Clear")
                
        with gr.Tab("Settings"):
            with gr.Row():
                face_detection_threshold = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    value=0.5,
                    step=0.01,
                    label="Face Detection Threshold"
                )
                output_quality = gr.Slider(
                    minimum=1,
                    maximum=100,
                    value=90,
                    step=1,
                    label="Output Quality"
                )
            
            with gr.Row():
                enable_face_enhancement = gr.Checkbox(
                    label="Enable Face Enhancement",
                    value=True
                )
                preserve_original_resolution = gr.Checkbox(
                    label="Preserve Original Resolution",
                    value=True
                )

        # Placeholder function for processing
        def process_images(source, target):
            # This is where you'd implement the actual face fusion logic
            # For now, just return the target image
            return target

        def clear_outputs():
            return None, None, None

        # Connect the interface elements
        process_button.click(
            fn=process_images,
            inputs=[source_image, target_image],
            outputs=[output_image]
        )
        
        clear_button.click(
            fn=clear_outputs,
            inputs=[],
            outputs=[source_image, target_image, output_image]
        )

    return interface

# Create and launch the interface
demo = create_gui()

# For deployments
if __name__ == "__main__":
    demo.launch()