gui.py

import tkinter as tk
from tkinter import filedialog
from tkinter import *
from PIL import ImageTk, Image

import numpy
#load the trained model to classify sign
from keras.models import load_model
model = load_model('traffic_classifier.h5')

#dictionary to label all traffic signs class.
classes = { 1:'Speed limit (20km/h)',
            2:'Speed limit (30km/h)',      
            3:'Speed limit (50km/h)',       
            4:'Speed limit (60km/h)',      
            5:'Speed limit (70km/h)',    
            6:'Speed limit (80km/h)',      
            7:'End of speed limit (80km/h)',     
            8:'Speed limit (100km/h)',    
            9:'Speed limit (120km/h)',     
           10:'No passing',   
           11:'No passing veh over 3.5 tons',     
           12:'Right-of-way at intersection',     
           13:'Priority road',    
           14:'Yield',     
           15:'Stop',       
           16:'No vehicles',       
           17:'Veh > 3.5 tons prohibited',       
           18:'No entry',       
           19:'General caution',     
           20:'Dangerous curve left',      
           21:'Dangerous curve right',   
           22:'Double curve',      
           23:'Bumpy road',     
           24:'Slippery road',       
           25:'Road narrows on the right',  
           26:'Road work',    
           27:'Traffic signals',      
           28:'Pedestrians',     
           29:'Children crossing',     
           30:'Bicycles crossing',       
           31:'Beware of ice/snow',
           32:'Wild animals crossing',      
           33:'End speed + passing limits',      
           34:'Turn right ahead',     
           35:'Turn left ahead',       
           36:'Ahead only',      
           37:'Go straight or right',      
           38:'Go straight or left',      
           39:'Keep right',     
           40:'Keep left',      
           41:'Roundabout mandatory',     
           42:'End of no passing',      
           43:'End no passing veh > 3.5 tons' }
                 
#initialise GUI
top = tk.Tk()  # Create the main window
top.geometry('800x600')  # Set the window dimensions
top.title('Traffic sign classification')  # Set the window title
top.configure(background='#CDCDCD')  # Set the background color of the window

label = Label(top, background='#CDCDCD', font=('arial', 15, 'bold'))  # Create a label widget to display the traffic sign classification
sign_image = Label(top)  # Create a label widget to display the uploaded image

def classify(file_path):
    global label_packed

    image = Image.open(file_path)  # Open and preprocess the image
    image = image.resize((30, 30))
    image = numpy.expand_dims(image, axis=0)
    image = numpy.array(image)
    print(image.shape)

    pred_probabilities = model.predict([image])  # Predict the class label
    pred = pred_probabilities.argmax(axis=-1)[0]
    sign = classes[pred + 1]

    print(sign)
    label.configure(foreground='#011638', text=sign)  # Update the label with the predicted sign

def show_classify_button(file_path):
    classify_b = Button(top, text="Classify Image", command=lambda: classify(file_path), padx=10, pady=5)  # Show the "Classify Image" button
    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)))  # Upload and resize the image
        im = ImageTk.PhotoImage(uploaded)

        sign_image.configure(image=im)  # Display the uploaded image
        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)  # Create the "Upload an image" button
upload.configure(background='#364156', foreground='white', font=('arial', 10, 'bold'))
upload.pack(side=BOTTOM, pady=50)  # Position and display the "Upload an image" button

sign_image.pack(side=BOTTOM, expand=True)  # Position and display the image label
label.pack(side=BOTTOM, expand=True)  # Position and display the classification label

heading = Label(top, text="Know Your Traffic Sign", pady=20, font=('arial', 20, 'bold'))  # Create a heading label
heading.configure(background='#CDCDCD', foreground='#364156')  # Set the heading label properties
heading.pack()  # Position and display the heading label

top.mainloop()  # Start the Tkinter event loop