# import the necessary packages
from PIL import Image
import pytesseract
import argparse
import cv2
import os
# 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('data\\test5.PNG')
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
pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files\\Tesseract-OCR\\tesseract'
text = pytesseract.image_to_string(Image.open(filename))
os.remove(filename)
print(text)
# show the output images
cv2.imshow("Image", image)
cv2.imshow("Output", gray)
cv2.waitKey(0)