# Import libraries
import streamlit as st
import mne
import matplotlib.pyplot as plt
import os
import streamlit as st
import random

from misc import *

import streamlit as st

# Create two columns with st.columns (new way)
col1, col2 = st.columns(2)

# Create the upload button in the first column
# Load the edf file
edf_file = col1.file_uploader("Upload an EEG edf file", type="edf")
# Create the result placeholder button in the second column
col2.button('Result:')


if edf_file is not None:
    
    # Read the file
    raw = read_file(edf_file)

    # Preprocess and plot the data
    preprocessing_and_plotting(raw)

    # Build the model
    clf = build_model(model_name='deep4net', n_classes=2, n_chans=21, input_window_samples=6000)

    output = predict(raw,clf)

    # # Print the output
    set_button_state (output,col2)