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from fastai import *
import gradio as gr
__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
def is_cat(x): return x[0].issuper()
learn = load_learner('model.pkl')
categories = ('Cat', 'Dog')
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 = ['dog.jpg', 'cat.jpg', 'random.jpg']
intf = gr.Interface(fn = classify_image, inputs = image, outputs = label, examples = examples)
intf.launch(inline=False)
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