import gradio as gr
from age_service import AgeService
import numpy as np

# Initialize the AgeService
service = AgeService()

def predict_age(image):
    if image is None:
        return "Please upload an image."
    
    # Perform prediction
    result = service.detect_and_predict(image)
    
    if result and result.get("error"):
        return f"Error: {result['error']}"
    elif result:
        return f"Predicted Age: {result['age']}\nAge Group: {result['age_group']}\nConfidence: {result['confidence']}"
    else:
        return "An unknown error occurred."

# Create the Gradio interface
iface = gr.Interface(
    fn=predict_age,
    inputs=gr.Image(label="Upload Image"),
    outputs=gr.Text(label="Prediction Result"),
    title="Age Prediction Model",
    description="Upload an image containing a face to predict the person's age. This model uses a custom-trained ResNet18 and an OpenCV face detector.",
    allow_flagging="never"
)

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