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

learn = load_learner("model/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 = ['sample_imgs/aeropress_go.jpg', 
            'sample_imgs/delonghi_espresso.jpg', 
            'sample_imgs/moka_pot_red.jpeg']

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