from PIL import Image, ImageTk

import PIL.Image

from window_about import open_window_about

from bar import bar

from Tkinter import *

from tkinter import ttk

from window_symptoms import open_window_get_symptoms

from model import open_window_model

global feature_list

def get_symptoms():

return

def model():

open_window_model()

return

def open_about():

return

# splash_window

splash_window = Tk()

splash_window.geometry("1240x590")

splash_window.title("LIVER DISEASE PREDICTION USING ML")

img = ImageTk.PhotoImage(PIL.Image.open('UI-Materials/sd2.png'))

panel = Label(splash_window, image=img)

panel.pack(side="top", fill="both", expand="yes")

splash_window.after(3000, lambda: splash_window.destroy())

progress = ttk.Progressbar(splash_window, orient=HORIZONTAL, length=1280, mode='determinate')

progress.pack(ipady=45)

bar(progress, splash_window)

splash_window.mainloop()

# root_window

root = Tk()

global i

root.geometry("1100x840")

root.title("LIVER DISEASE PREDICTION USING ML")

root.config(bg="#ffffff")

Heading = Label(root, text="LIVER DISEASE PREDICTION USING MACHINE LEARNING", font="Cooper 30", bg="#ffffff", padx=10)

Heading.pack(fill='x', pady=10)

MainFrame = Frame(root, padx=40, pady=60, bg="#ffffff")

Frame1 = Frame(MainFrame, bg="#ffffff")

button_record = Button(Frame1, text="ENTER SYMPTOMS", width=20, font="times 20", padx=40, pady=20, command=get_symptoms)

button_record.pack(pady=20)

button_process = Button(Frame1, text="PREDICT", width=20, font="times 20", padx=40, pady=20, command=model)

button_process.pack(pady=20)

button_recognise = Button(Frame1, text="ABOUT", width=20, font="times 20", padx=40, pady=20, command=open_about)

button_recognise.pack(pady=20)

Frame1.pack()

MainFrame.pack(side="left")

liver_img = ImageTk.PhotoImage(PIL.Image.open('UI-Materials/l.jpg'))

panel = Label(root, image=liver_img, borderwidth=0, highlightthickness=0)

panel.pack(side="right")

root.mainloop()