from transformers import pipeline
import gradio as gr
def alz_mri_classification(image):
    classifier = pipeline("image-classification", model="dewifaj/alzheimer_mri_classification")
    result = classifier(image)
    # extract the highest score
    prediction = result[0]
    score = prediction['score']
    label = prediction['label']
    return {"score": score, "label": label}
example_image_paths = ["example_image1.jpg", "example_image2.jpg", "example_image3.jpg", "example_image4.jpg"]

image_input = gr.Image(type="pil", label="Upload Image")
iface = gr.Interface(fn=alz_mri_classification, 
                     inputs=image_input, 
                     outputs="json", 
                     example = example_image_paths,
                     title="Alzheimer Recognition from MRI")
iface.launch()