import requests
import gradio as gr
from transformers import pipeline

# make the image classification pipeline
def classify_image(test_sample):
    img_class= pipeline(
        "image-classification", model="AMfeta99/vit-base-oxford-brain-tumor"
    )
    results = img_class(our_dataset['test']['image'][0])
    max_score_result = max(results, key=lambda x: x['score'])

    predictions = max_score_result['label']
    
    return predictions



image = gr.Image()
label = gr.Label(num_top_classes=1)
title = "Brain Tumor X-ray Classification"
description="Worried about whether your brain scan is normal or not? Upload your x-ray and the algorithm will give you an expert opinion.  Check out [the original algorithm](https://huggingface.co/AMfeta99/vit-base-oxford-brain-tumor) that this demo is based off of."
article="<p style='text-align: center'>Image Classification | Demo Model</p>"
demo = gr.Interface(fn=classify_image, inputs=image , outputs=label, description=description,article=article,title=title)

demo.launch(share=True)