import pytesseract
import cv2
import collections

def recognise(img):
    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    ret, img_thresh = cv2.threshold(img_gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    _, ctrs, hier = cv2.findContours(img_thresh, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
    ctrs = sorted(ctrs, key=lambda x: (cv2.boundingRect(x)[1], cv2.boundingRect(x)[0]))
    heights = []
    for ctr in ctrs:
        x, y, w, h = cv2.boundingRect(ctr)
        if abs(w-h)<2 and h>10:
            heights.append(h)
    height_common = collections.Counter(heights).most_common(1)
    digits = []
    if height_common[0][1]>=8:
        height = height_common[0][0]
        for ctr in ctrs:
            x, y, w, h = cv2.boundingRect(ctr)
            if abs(w-h)<=2 and h==height:
                if len(digits)<8:
                    digits.append(img[y:(y+h), x:(x+w)])
    digits_text = ''
    for digit in digits:
        h, w, c = digit.shape
        digit_text = pytesseract.image_to_string(digit)
        digits_text += digit_text
    return digits_text