# C:\Program Files\Tesseract-OCR\tesseract.exe
import os
os.environ['path'] += ";C:\\Program Files\\Tesseract-OCR"

import cv2
import pytesseract
import numpy as np
import re

# https://towardsdatascience.com/optical-character-recognition-ocr-with-less-than-12-lines-of-code-using-python-48404218cccb
def recognize_text(img_pil):
    #img = cv2.imread('ocr_test.png')
    img = np.asarray(img_pil)
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    gray, img_bin = cv2.threshold(gray,128,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    gray = cv2.bitwise_not(img_bin)

    kernel = np.ones((2, 1), np.uint8)
    img = cv2.erode(gray, kernel, iterations=1)
    img = cv2.dilate(img, kernel, iterations=1)
    out_below = pytesseract.image_to_string(img)
    out_below = re.sub(r'[^a-zA-Z0-9_\s]', '', out_below)
    out_below = re.sub(r'[\s]', ' ', out_below).strip()
    
    #print("OCR OUTPUT:", out_below)
    return out_below

#recognize_text(cv2.imread('ocr_test.png'))

import random
def recognize_number(img_pil):
    #img = cv2.imread('ocr_test.png')
    img = np.asarray(img_pil)
    bordersize = 5
    row, col = img.shape[:2]
    bottom = img[row-2:row, 0:col]
    mean = cv2.mean(bottom)[0]
    img = cv2.copyMakeBorder(
        img,
        top=bordersize,
        bottom=bordersize,
        left=bordersize,
        right=bordersize,
        borderType=cv2.BORDER_CONSTANT,
        value=[mean, mean, mean]
    )

    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    gray, img_bin = cv2.threshold(gray,128,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    gray = cv2.bitwise_not(img_bin)

    tesseract_config = "-c tessedit_char_whitelist=0123456789/"
    kernel = np.ones((2, 1), np.uint8)
    img = cv2.erode(gray, kernel, iterations=1)
    img = cv2.dilate(img, kernel, iterations=1)
    #cv2.imwrite(f"OCR_{random.randint(0,9999)}.png", img)
    out_below = pytesseract.image_to_string(img, config=tesseract_config)
    out_below = out_below.strip()
    #print("OCR OUTPUT:", out_below)
    return out_below