python 电表辨认

Python是一种高级编程语言，具有简洁、易读、易于学习和使用的特点。它有着广泛的利用场景，包括电表辨认。电表辨认是一项基于数字图象处理的技术，可以自动辨认电表读数并精确抄表，提高抄表效力和减少误差。

import cv2
import numpy as np
from PIL import Image
image_file = 'meter.jpg'
#print("正在读取文件夹 %s 中的图片......" % image_file)
img = cv2.imread(image_file)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(gray,127,255,cv2.THRESH_BINARY_INV)
kernel = np.ones((5,5),np.uint8)
opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 2)
sure_bg = cv2.dilate(opening,kernel,iterations=3)
dist_transform = cv2.distanceTransform(opening,cv2.DIST_L2,5)
ret, sure_fg = cv2.threshold(dist_transform, 0.7*dist_transform.max(),255,0)
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg,sure_fg)
ret, markers = cv2.connectedComponents(sure_fg)
markers = markers+1
markers[unknown==255] = 0
markers = cv2.watershed(img,markers)
img[markers == ⑴] = [255,0,0]
#cv2.imshow('Segmented Meter', img)
region = [(500, 194), (1236, 144), (1270, 306), (504, 356)]
crop = img[region[1][1]:region[3][1], region[0][0]:region[2][0]]
im = Image.fromarray(crop)
#im.show()
im2 = im.convert(mode='1')
#im2.show()
print("正在分析图片中的数字......")
text = pytesseract.image_to_string(im2, lang = 'eng', config='--psm 10 --oem 3 -c tessedit_char_whitelist=0123456789')
print(text)

以上是辨认电表读数的Python代码，其中使用到了OpenCV库和Pillow库，也调用了tesseract-ocr引擎来辨认数字。通过读取电表图片，先进行图象处理，再进行分割和辨认，最后得到电表读数，实现了电表自动抄表的功能。