app.py

import gradio as gr
from PIL import Image
from backend.predict import predict_image

def infer(image):
    result = predict_image(image)
    return result["label_name"], float(result["confidence"])

demo = gr.Interface(
    fn=infer,
    inputs=gr.Image(type="pil"),
    outputs=[
        gr.Text(label="Prediction"),
        gr.Number(label="Confidence")
    ],
    title="X-Ray Multi-Class Classifier",
    description="Upload an X-ray image to get the predicted class and confidence."
)

demo.launch()