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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)