app.py

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

learn = load_learner('bookjudge.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 = "Judge a book by its cover? Why of course!"
description = "Who says you can't judge a book by its cover? "
examples = ["children.jpg", "romance.jpg", "science-fiction.jpg"]
article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article, interpretation=interpretation,enable_queue=enable_queue, examples=examples).launch()