Digit Recognization System Using Machine Learning


Digit Recognization System using Machine Learning

About this project

The Digit recognization system has the ability of computers to recognize human handwritten digits. It is not easy for the machine because handwritten digits are not the same as actual digits and looks different sometimes. The digit recognization system provides the solution to the problem which uses and recognizes the digit in the image. The Digit recognization system can match handmade digits to their actual values.

 

Instructions and requirements:-
As part of the configuration, it is recommended that you should use Python 3.8.
Need to follow the below steps :-
1> In train_digit_recognization.py file need to add the below libraries
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras.utils.np_utils import to_categorical
Need to run train_digit_recognization.py file first to train data and wait until the training is completed successfully.

2>In gui_digit_recognization file need to add the below libraries
from keras.models import load_model
from tkinter import *
import tkinter as tk
import win32gui
from PIL import ImageGrab, Image
import numpy as np
run gui_digit_recognization file and start using the digit recognization system.