import gradio as gr
import numpy as np
import time

def process_image(img):
    """Placeholder function - replace with your backend integration"""
    if img is None:
        return "No image provided", "", ""
    time.sleep(1)  # Simulate processing
    return "Processing Complete", "Real Face", "Confidence: 95%"

with gr.Blocks() as demo:
    gr.Markdown("# Face Spoofing Detection System")
    
    with gr.Tabs():
        with gr.Tab("Webcam Detection"):
            webcam = gr.Image(label="Webcam Feed")
            webcam_status = gr.Textbox(label="Status", value="Ready")
            webcam_result = gr.Textbox(label="Detection Result")
            webcam_conf = gr.Textbox(label="Confidence Score")
            webcam_button = gr.Button("Analyze")
            
            webcam_button.click(
                fn=process_image,
                inputs=webcam,
                outputs=[webcam_status, webcam_result, webcam_conf]
            )

        with gr.Tab("Image Upload"):
            image_input = gr.Image(label="Upload Image")
            image_status = gr.Textbox(label="Status", value="Ready")
            image_result = gr.Textbox(label="Detection Result")
            image_conf = gr.Textbox(label="Confidence Score")
            image_button = gr.Button("Analyze")
            
            image_button.click(
                fn=process_image,
                inputs=image_input,
                outputs=[image_status, image_result, image_conf]
            )

    gr.Markdown("""
    ### Instructions:
    1. Choose either Webcam or Image Upload tab
    2. For webcam: Allow camera access and take a photo
    3. For images: Upload an image from your device
    4. Click Analyze to process the image
    """)

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