GUI.py

import tkinter as tk
from tkinter import filedialog
from tkinter import *
from PIL import ImageTk, Image
import numpy
from keras.models import load_model
from keras.preprocessing.image import img_to_array

#load model
model = load_model('cats_and_dogs_small_2.h5')

#dictionary to label all traffic signs class.
classes = { 
    0:'its a cat',
    1:'its a dog',
}

#initialise GUI
top=tk.Tk()
top.geometry('800x600')
top.title('CatsVSDogs Classification')
top.configure(background='#CDCDCD')
label=Label(top,background='#CDCDCD', font=('arial',15,'bold'))
sign_image = Label(top)
def classify(file_path):
    global label_packed
    image = Image.open(file_path)
    image = image.resize((150,150))
    image = img_to_array(image)
    image = numpy.expand_dims(image, axis=0)
    
    image = image/255
    pred = model.predict_classes([image])[0]
    print(pred)
    #sign = classes[pred]
    if(pred== [0]):
        sign='it is a cat'
    else:
        sign='it is a dog'
    
    label.configure(foreground='#011638', text=sign) 
    
def show_classify_button(file_path):
    classify_b=Button(top,text="Classify Image",
   command=lambda: classify(file_path),
   padx=10,pady=5)
    classify_b.configure(background='#364156', foreground='white',
font=('arial',10,'bold'))
    classify_b.place(relx=0.79,rely=0.46)
    
def upload_image():
    try:
        file_path=filedialog.askopenfilename()
        uploaded=Image.open(file_path)
        uploaded.thumbnail(((top.winfo_width()/2.25),
    (top.winfo_height()/2.25)))
        im=ImageTk.PhotoImage(uploaded)
        sign_image.configure(image=im)
        sign_image.image=im
        label.configure(text='')
        show_classify_button(file_path)
    except:
        pass

upload=Button(top,text="Upload an image",command=upload_image,padx=10,pady=5)
upload.configure(background='#364156', foreground='white',font=('arial',10,'bold'))
upload.pack(side=BOTTOM,pady=50)
sign_image.pack(side=BOTTOM,expand=True)
label.pack(side=BOTTOM,expand=True)
heading = Label(top, text="CatsVSDogs Classification",pady=20, font=('arial',20,'bold'))
heading.configure(background='#CDCDCD',foreground='#364156')
heading.pack()
top.mainloop()