app.py

from model import model
import gradio as gr
import numpy as np

def classify_image(image):
    probabilities = model.predict(image)  # Call prediction function
    return probabilities


with gr.Blocks(title="Brain tumor image MRI classification") as demo:
    gr.Markdown("""
    # Brain tumor image MRI classification
    Convolutional neural network proprietary model made in Keras to classify brain MRI images in 4 categories: Glioma, Meningioma, Pituitary and No tumor. AI model and interface built by Eng. Michael Leonardo Aguas.
    """)
    
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="pil", label="Upload MRI Image")
            submit_btn = gr.Button("Classify", variant="primary")
        
        with gr.Column():
            output_label = gr.Label(num_top_classes=4, label="Classification Results")
    
    submit_btn.click(
        fn=classify_image,
        inputs=image_input,
        outputs=output_label
    )

demo.launch(server_name="0.0.0.0", server_port=7860, share=True)