app.py

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

# # Dog v Cat

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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('dog1.jpg')
im.thumbnail((192, 192))
im


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#/export
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath

learn = load_learner('model.pkl')


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learn.predict(im)


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

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


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classify_images(im)


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#/export
image = gr.inputs.Image(shape = (192,192))
label = gr.outputs.Label()
examples = ['dog1.jpg', 'cat1.jpg']

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