app.py

import gradio as gr
from fastai.vision.all import *
from os import listdir
import random

learn = load_learner('hockey_model.pkl')

categories = ('Hockey Goalie', 'Hockey Player', "Hockey Referee")
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
skater_example = 'assets/skaters/' + random.choice(listdir('assets/skaters')) 
ref_example = 'assets/referees/' + random.choice(listdir('assets/referees'))
goalie_example = 'assets/goalies/' + random.choice(listdir('assets/goalies'))

def classify_image(img):
    pred,idx,prob = learn.predict(img)
    return dict(zip(categories, map(float, prob)))

iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, theme=gr.themes.Glass(), 
                    examples=[skater_example, ref_example, goalie_example])
iface.launch(share=False, debug=True)