app.py

import gradio as gr
from fastai.vision.all import *
import skimage

learn = load_learner('model.pkl')

labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Scientist vs. Programmer Classifier"
article="""<p style='text-align: center'><a href='https://www.instagram.com/casey.solvberg/' target='_blank'>Author's Instagram</a></p>"""
examples = ['data_scientist.jpg']
interpretation='default'
enable_queue=True

gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(),
    title=title,
    article=article,
    examples=examples
).launch(share=True)