Visualizing characters in an Optical Character Recognition database

Artificial neural networks can use optical character recognition. It is perhaps one of the most commonly sited examples. Optical Character Recognition (OCR) is the process of recognizing handwritten characters in images. Before we jump into building that model, we need to familiarize ourselves with the dataset. We will be using the dataset available at  http://ai.stanford.edu/~btaskar/ocr . You will be downloading a file called letter.data. For convenience, this file has been provided to you in the code bundle. Let's see how to load that data and visualize the characters.

Create a new python file and import the following packages:

import os 
import sys 
 
import cv2 
import numpy as np 

Define the input file containing the OCR data:

# Define the input file  
input_file = 'letter.data'  

Define the visualization and other parameters required to load the data from that file:

# Define the visualization parameters...