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

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

#temp = pathlib.PosixPath
#pathlib.PosixPath = pathlib.WindowsPath
learn=load_learner('model.pkl')
#pathlib.PosixPath=temp

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

image = gr.components.Image()
label = gr.components.Label()
examples=['dog.jpg', 'cat.jpg','dunno.jpg']

a='v'

interface = gr.Interface(fn=classify_image, inputs=[image], outputs=[label], examples=examples)
interface.launch()