app.py

#!/usr/bin/env python
# coding: utf-8

# ## Dogs v Cats

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#/default_exp app


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get_ipython().system('pip install gradio')


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#/export
from fastai.vision.all import *
import gradio as gr

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


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im = PILImage.create('dog.jpg')
im.thumbnail((192,192))
im


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#/export
learn = load_learner('model.pkl')


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learn.predict(im)


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#/export
categories = ('Dog', 'Cat')

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


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classify_image(im)


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#/export
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)


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m = learn.model


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ps = list(m.parameters())


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ps[1]


# # Exporting

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get_ipython().system('pip install nbdev')


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import nbdev
#nbdev.export.nb_export('Dogs v Cats.ipynb', 'app')
nbdev.export.nb_export('Dogs v Cats.ipynb', './')
print('Export successful')


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