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

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

TITLE = Path("docs/title.txt").read_text()
DESCRIPTION = Path("docs/description.md").read_text()

learn = load_learner('model.pkl')

categories = ('airbaby', 'airchair', 'airflare', 'headspin', 'hollow back')


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 = ['example1.jpg', 'example5.jpg',
            'example3.jpg', 'example8.jpg', 'example4.jpg',
            'example6.jpg', 'example2.jpg', 'example7.JPG']

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