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 = "Bike or Car?"
description = "Simple demo to determine if an image contains a bike or a car."
examples = ['car.jpg', 'bike.jpg']
interpretation='default'

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(shape=(512, 512)),
             outputs=gr.outputs.Label(num_top_classes=2),
             title=title,
             description=description,
             examples=examples,
             interpretation=interpretation).launch()