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

learn = load_learner('model.pkl')

categories = ('air chair','hollowback','airflare','airbaby','headspin')

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

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['air_chair.jpg','hollowback.jpeg','airbaby.jpeg','airflare.jpeg','headspin.jpeg']

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