import numpy as np
import streamlit as st
from fastai.vision.core import *
from fastai.vision.all import *
import pathlib
import platform

if platform.system() == 'Windows':
    temp = pathlib.PosixPath
    pathlib.PosixPath = pathlib.WindowsPath
def is_cat(x): return x[0].isupper()
if __name__=='__main__':
    learn = load_learner(pathlib.Path()/'model.pkl')
    uploaded_file = st.file_uploader("Choose an image of a dog or cat")
    if uploaded_file is not None:
        im = PILImage.create((uploaded_file))
        st.image(im.to_thumb(500, 500), caption='Uploaded Image')
        if st.button('Classify'):
            pred, ix, probs = learn.predict(im.convert('RGB'))
            data = dict(zip(('Dog', 'Cat'), map(float, probs)))
            st.bar_chart(data=data)
        else:
            st.write(f'Click the button to classify')