import gradio as gr
from tensorflow.keras.models import load_model
from PIL import Image
import numpy as np

model = load_model('xray_image_classifier_model.keras')

def predict_image(img):
    img = img.resize((150, 150))
    img = np.array(img) / 255.0
    img = np.expand_dims(img, axis=0)
    prediction = model.predict(img)
    label = 'Pneumonia' if prediction > 0.5 else 'Normal'
    return label

iface = gr.Interface(
    fn=predict_image, 
    inputs=gr.inputs.Image(type="pil"), 
    outputs="text",
    title="X-ray Image Classifier",
    description="Upload an X-ray image to classify it as 'Pneumonia' or 'Normal'."
)

iface.launch()