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

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

import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath

learner = load_learner('cat.pkl')

categories = ['Dog', 'Cat']

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

image = gr.Image(height=192, width=192)
labels = gr.Label()
examples = ['dog.jpg', 'cat.jpg']

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