app.py

__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']

import gradio as gr

def classify_image(img):
    from fastai.vision.all import load_learner
    learn = load_learner('lego-bricks-model.pkl')
    categories = (
    '11214 Bush 3M friction with Cross axle',
    '18651 Cross Axle 2M with Snap friction',
    '2357 Brick corner 1x2x2',
    '3003 Brick 2x2',
    '3004 Brick 1x2', 
    '3005 Brick 1x1',
    '3022 Plate 2x2',
    '3023 Plate 1x2',
    '3024 Plate 1x1',
    '3040 Roof Tile 1x2x45deg',
    '3069 Flat Tile 1x2',
    '32123 half Bush',
    '3673 Peg 2M',
    '3713 Bush for Cross Axle',
    '3794 Plate 1X2 with 1 Knob',
    '6632 Technic Lever 3M',
)
    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 = ['0002.png', '201706161606-0002.png', '201706161906-0001.png']

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