from fastai.vision.all import *
import gradio as gr
from gradio.components import Image, Label
import pathlib

plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath

modelPath = Path('model.pkl')
learn = load_learner(modelPath)
categories = ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')

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

image = Image(shape=(192,192))
label = Label()
examples = ['img_0.jpg', 'img_1.jpg', 'img_2.jpg', 'img_4.jpg', 'img_7.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)