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

learn = load_learner("what_brew_machine_v1.pkl")

categories = tuple(learn.dls.vocab)

def what_machine(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 = ['aeropress_go.jpg', 
            'delonghi_espresso.jpg', 
            'moka_pot_red.jpeg']

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