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

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

def is_cat(x): return x[0].isupper()

# cell
learn = load_learner('model.pkl')

# cell
categories = ('Dog', 'Cat')

def classify_image(img):
  preds, idx, probs = learn.predict(img)
  return dict(zip(categories, map(float, probs)))

# cell
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']

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