main.py

from PIL import Image
import pytesseract
import argparse
import cv2
import os

pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
                help="path to input image to be OCR'd")
ap.add_argument("-p", "--preprocess", type=str, default="thresh",
                help="type of preprocessing to be done")
args = vars(ap.parse_args())
# load the example image and convert it to grayscale
image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# check to see if we should apply thresholding to preprocess the
# image
if args["preprocess"] == "thresh":
    gray = cv2.threshold(gray, 0, 255,
                         cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]

# make a check to see if median blurring should be done to remove
# noise
elif args["preprocess"] == "blur":
    gray = cv2.medianBlur(gray, 3)

# write the grayscale image to disk as a temporary file so we can
# apply OCR to it
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, gray)

# load the image as a PIL/Pillow image, apply OCR, and then delete
# the temporary file
text = pytesseract.image_to_string(Image.open(filename),lang='e13b')
os.remove(filename)
print(text)