app.py

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

learn = load_learner('construction2.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 = "Construction Vehicle Classifier"
description = "Try an image of a (real not toy) dump truck, excavator, or bulldozer."
article="<p style='text-align: center'>by Marshall Grinstead</p><p style='text-align: center'><a href='https://medium.com/@marsgrins' target='_blank'>Blog</a></p><p style='text-align: center'><a href='https://twitter.com/msteadsays' target='_blank'>Twitter</a></p>"
examples = ['dumptruck.jpg']
gr.Interface(fn=predict, inputs=gr.Image(height=512, width=512), outputs=gr.Label(num_top_classes=3), title=title, description=description, examples=examples, article=article).launch()