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

learn = load_learner('model.pkl')

#! export
categories = ('Ahrend Result Chair', 'Borge Mogenson J39 Chair', 'Breuer Cesca Chair', 'Jean prouve Vitra Standard Chair', 'PK22 Chair Poul Kjærholm', 'Series 7 Chair Arne Jacobsen', )
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 = ['chair1.jpg', 'chair2.jpg', 'chair3.jpg']

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