app.py

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

learn = load_learner('export.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 Classifier'
description = 'A bear classifier trained on random images from internet with fastai. Created as a demo for Gradio and HuggingFace Spaces.'
examples = ['GrizzlyBearJeanBeaufort.jpg']

gr.Interface(fn = predict,
inputs = 'image',
outputs = 'label',
title = title,
description = description,
examples = examples).launch()