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 = 'Bear Type Classifier'
description = 'FasiAI Example on how to classify types of bears.'
article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Tutorial</a></p>"
interpretation='default'
enable_queue = True
examples = ['./black_bear.jpeg']

iface = gr.Interface(fn=predict, inputs=gr.Image(shape=(512, 512)), outputs="label", title=title, description=description, article=article, examples=examples, interpretation=interpretation, enable_queue=enable_queue)
iface.launch()