4. Get Started! Handwritting Recognition, Simple Object Classification & OpenCV Demo/preprocessors.py

import numpy as np
import cv2

def x_cord_contour(contour):
    # This function take a contour from findContours
    # it then outputs the x centroid coordinates
    M = cv2.moments(contour)
    return (int(M['m10']/M['m00']))


def makeSquare(not_square):
    # This function takes an image and makes the dimenions square
    # It adds black pixels as the padding where needed
    
    BLACK = [0,0,0]
    img_dim = not_square.shape
    height = img_dim[0]
    width = img_dim[1]
    #print("Height = ", height, "Width = ", width)
    if (height == width):
        square = not_square
        return square
    else:
        doublesize = cv2.resize(not_square,(2*width, 2*height), interpolation = cv2.INTER_CUBIC)
        height = height * 2
        width = width * 2
        #print("New Height = ", height, "New Width = ", width)
        if (height > width):
            pad = int((height - width)/2)
            #print("Padding = ", pad)
            doublesize_square = cv2.copyMakeBorder(doublesize,0,0,pad,pad,cv2.BORDER_CONSTANT,value=BLACK)
        else:
            pad = (width - height)/2
            #print("Padding = ", pad)
            doublesize_square = cv2.copyMakeBorder(doublesize,pad,pad,0,0,\
                                                   cv2.BORDER_CONSTANT,value=BLACK)
    doublesize_square_dim = doublesize_square.shape
    #print("Sq Height = ", doublesize_square_dim[0], "Sq Width = ", doublesize_square_dim[1])
    return doublesize_square


def resize_to_pixel(dimensions, image):
    # This function then re-sizes an image to the specificied dimenions
    
    buffer_pix = 4
    dimensions  = dimensions - buffer_pix
    squared = image
    r = float(dimensions) / squared.shape[1]
    dim = (dimensions, int(squared.shape[0] * r))
    resized = cv2.resize(image, dim, interpolation = cv2.INTER_AREA)
    img_dim2 = resized.shape
    height_r = img_dim2[0]
    width_r = img_dim2[1]
    BLACK = [0,0,0]
    if (height_r > width_r):
        resized = cv2.copyMakeBorder(resized,0,0,0,1,cv2.BORDER_CONSTANT,value=BLACK)
    if (height_r < width_r):
        resized = cv2.copyMakeBorder(resized,1,0,0,0,cv2.BORDER_CONSTANT,value=BLACK)
    p = 2
    ReSizedImg = cv2.copyMakeBorder(resized,p,p,p,p,cv2.BORDER_CONSTANT,value=BLACK)
    img_dim = ReSizedImg.shape
    height = img_dim[0]
    width = img_dim[1]
    #print("Padded Height = ", height, "Width = ", width)
    return ReSizedImg