import streamlit as st

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

from fastai import *
from fastai.basics import *
from fastai.callback.all import *
from fastai.vision.all import *
from fastai.vision import *
from fastai.metrics import *

col1, col2 = st.columns([3, 1])
# right column
col1.title('Emotion Detector')
col1.subheader('Let your emotion flow...')

# left column
pic = col2.camera_input('Take a Picture')
if pic:
    col2.success('Picture Successfully Uploaded')
    col1.text('This is the picture you have taken')
    col1.image(pic)
    with open ('resource/pic.jpg','wb') as file:
        file.write(pic.getbuffer())
    
    learner = load_learner('resource/this.pkl')
    result = learner.predict(item='resource/pic.jpg')[0]
    col2.text(result)