你好。我正试着从下面的支票页上辨认出印刷和手写的文本

这里是预处理后的图像，下面使用的代码

import cv2 
import pytesseract
import numpy as np

img = cv2.imread('Images/cheque_leaf.jpg')

# Rescaling the image (it's recommended if you’re working with images that have a DPI of less than 300 dpi)
img = cv2.resize(img, None, fx=1.2, fy=1.2, interpolation=cv2.INTER_CUBIC)
h, w = img.shape[:2]

# By default OpenCV stores images in BGR format and since pytesseract assumes RGB format,
# we need to convert from BGR to RGB format/mode:
# it to reduce noise
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]  # perform OTSU threhold
thresh = cv2.rectangle(thresh, (0, 0), (w, h), (0, 0, 0), 2) # draw a rectangle around regions of interest in an image

# Dilates an image by using a specific structuring element.
# enrich the charecters(to large)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2,2))

# The function erodes the source image using the specified structuring element that determines 
# the shape of a pixel neighborhood over which the minimum is taken
erode = cv2.erode(thresh, kernel, iterations = 1)

# To extract the text
custom_config = r'--oem 3 --psm 6'
pytesseract.image_to_string(thresh, config=custom_config)

现在使用pytesseract.image_to_string（）方法将图像转换为文本。我得到的是无关输出。在上面的图像中，我想确定日期，分支收款人，数字和文字的金额以及数字签名名称，然后是帐号。
任何OCR技术通过提取如上所述的精确数据来解决上述问题。先谢谢你了