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

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

intf = gr.Interface(fn=classify_image,inputs=gr.Image(),outputs=gr.Label(),examples=examples)

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

# def greet(name):
#     return "Hello " + name + " have a wonderful day"

# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()