OpenCV Python - Fixing Broken Text

I am attempting to repair broken text (the images below) so that I can perform OCR on the images. How do I go about repairing the text below? I have already tried dilation, erosion, morphology closing, and using the distance between contours. None of these seem to work. I would appreciate any help, thanks.

Broken Text:

Attempted Solutions (none work):

import cv2
import pytesseract
import numpy as np
img = cv2.imread (“/Users/2020shatgiskessell/Desktop/OpenSlate/FN2.png”)
def OCR (img):

config = (‘-l eng --oem 1 --psm 3’)

text = pytesseract.image_to_string(img, config = config)

return text
def get_countour(img):

try:

output = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

output = output.copy()

except Exception:

output = img.copy()

#imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

#ret, thresh = cv2.threshold(output, 127, 255, 0)

contours, hierarchy = cv2.findContours(output, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

c = max(contours, key = cv2.contourArea)

contours.remove©

cv2.drawContours(output, contours, -1, (0,255,0),-1)
    kernel = np.ones((2,1),np.uint8)
    #eroded = cv2.erode(output, kernel,1)
    output = cv2.dilate(output, kernel,1)
    return output

def strengthen(img):

try:

imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

except Exception:

imgray = img

#ret, thresh = cv2.threshold(imgray,0,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)

#blur1 = cv2.blur(imgray,(5,5))

blur2 = cv2.GaussianBlur(imgray,(5,5),0)

thresh2 = cv2.adaptiveThreshold(blur2, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

kernel = np.ones((2,1),np.uint8)

#eroded = cv2.erode(thresh2, kernel,1)

#opening = cv2.morphologyEx(eroded, cv2.MORPH_CLOSE, kernel)

#closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel)

return thresh2
#MNIST(img)

strengthened= strengthen(img)
contours = get_countour(strengthened)
print("from morphology transformation: "+ OCR(contours))
cv2.imshow(‘img’, img)

cv2.imshow(‘contour’, contours)
cv2.waitKey(0)

cv2.destroyAllWindows()

The above images are recognized as:

Image 1: (CAN ajne oF

Image 2: > AMAR VRAIR

Image 3: STure

#python #opencv