app.py

import gradio as gr
import numpy as np
import tensorflow as tf
from tensorflow import keras

model = keras.models.load_model("brainTumor_classification.h5")

class_names = ['glioma', 'meningioma', 'notumor', 'pituitary']

img_height = 180
img_width = 180

def classify_image(image):
    image = tf.image.resize(image, (img_height, img_width))
    image = np.expand_dims(image, axis=0)
    predictions = model.predict(image)
    scores = tf.nn.softmax(predictions[0])
    predicted_class = class_names[np.argmax(scores)]
    confidence = 100 * np.max(scores)
    return f"This image most likely belongs to {predicted_class} with a {confidence:.2f} percent confidence."

input_image = gr.inputs.Image(shape=(img_height, img_width))
output_text = gr.outputs.Textbox()

gr.Interface(
    fn=classify_image,
    inputs=input_image,
    outputs=output_text,
    examples=[["bt1.jpg"], ["bt2.jpg"], ["bt3.jpg"], ["br1.jpg"], ["br2.jpg"], ["br3.jpg"]],
    live=True,
    title = '<h1 style="text-align: center;">Brain Tumor Image Classification! 🧠 </h1>',
    description=(
        "<h2><b> 👉 Try Brain Tumor Image Classification Now!</b></h2>"
        "<p>Don't miss out on this incredible opportunity to "
        "shape the future of medical diagnostics. Embrace innovation, <br>"
        "empower medical professionals, and make a real difference in <br>"
        "the lives of countless individuals. 🌍🩺🤝(ผลงานชิ้นนี้เป็นของ นาวสาวสุวีรยา เนินทราย ผู้เดียวเท่านั้น หากมีผู้อื่นนำไปคัดลอกผลงานต่อ หรือนำผลงานนี้ลงแฟ้มผลงาน(Portfolio) นอกเหนือจากนี้ ถือเป็นความผิด)</p>"
    ),
    theme="emoji", 
    theme_css=(".g-button { background-color: #FF5733; }")
).launch()