python opencv pytesseract 验证码识别的实现

时间:2021-12-26 20:14:14

一、环境配置

需要 pillow 和 pytesseract 这两个库,pip install 安装就好了。

install pillow -i http://pypi.douban.com/simple --trusted-host pypi.douban.com
pip install pytesseract -i http://pypi.douban.com/simple --trusted-host pypi.douban.com

安装好Tesseract-OCR.exe

pytesseract 库的配置:搜索找到pytesseract.py,打开该.py文件,找到 tesseract_cmd,改变它的值为刚才安装 tesseract.exe 的路径。

python opencv pytesseract 验证码识别的实现

二、验证码识别

识别验证码,需要先对图像进行预处理,去除会影响识别准确度的线条或噪点,提高识别准确度。

实例1

import cv2 as cv
import pytesseract
from PIL import Image


def recognize_text(image):
  # 边缘保留滤波 去噪
  dst = cv.pyrMeanShiftFiltering(image, sp=10, sr=150)
  # 灰度图像
  gray = cv.cvtColor(dst, cv.COLOR_BGR2GRAY)
  # 二值化
  ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)
  # 形态学操作  腐蚀 膨胀
  erode = cv.erode(binary, None, iterations=2)
  dilate = cv.dilate(erode, None, iterations=1)
  cv.imshow('dilate', dilate)
  # 逻辑运算 让背景为白色 字体为黑 便于识别
  cv.bitwise_not(dilate, dilate)
  cv.imshow('binary-image', dilate)
  # 识别
  test_message = Image.fromarray(dilate)
  text = pytesseract.image_to_string(test_message)
  print(f'识别结果:{text}')


src = cv.imread(r'./test/044.png')
cv.imshow('input image', src)
recognize_text(src)
cv.waitKey(0)
cv.destroyAllWindows()

运行效果如下:

识别结果:3n3D

Process finished with exit code 0

python opencv pytesseract 验证码识别的实现

实例2

import cv2 as cv
import pytesseract
from PIL import Image


def recognize_text(image):
  # 边缘保留滤波 去噪
  blur =cv.pyrMeanShiftFiltering(image, sp=8, sr=60)
  cv.imshow('dst', blur)
  # 灰度图像
  gray = cv.cvtColor(blur, cv.COLOR_BGR2GRAY)
  # 二值化
  ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)
  print(f'二值化自适应阈值:{ret}')
  cv.imshow('binary', binary)
  # 形态学操作 获取结构元素 开操作
  kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 2))
  bin1 = cv.morphologyEx(binary, cv.MORPH_OPEN, kernel)
  cv.imshow('bin1', bin1)
  kernel = cv.getStructuringElement(cv.MORPH_OPEN, (2, 3))
  bin2 = cv.morphologyEx(bin1, cv.MORPH_OPEN, kernel)
  cv.imshow('bin2', bin2)
  # 逻辑运算 让背景为白色 字体为黑 便于识别
  cv.bitwise_not(bin2, bin2)
  cv.imshow('binary-image', bin2)
  # 识别
  test_message = Image.fromarray(bin2)
  text = pytesseract.image_to_string(test_message)
  print(f'识别结果:{text}')


src = cv.imread(r'./test/045.png')
cv.imshow('input image', src)
recognize_text(src)
cv.waitKey(0)
cv.destroyAllWindows()

运行效果如下:

二值化自适应阈值:181.0
识别结果:8A62N1

Process finished with exit code 0

python opencv pytesseract 验证码识别的实现

实例3

import cv2 as cv
import pytesseract
from PIL import Image


def recognize_text(image):
  # 边缘保留滤波 去噪
  blur = cv.pyrMeanShiftFiltering(image, sp=8, sr=60)
  cv.imshow('dst', blur)
  # 灰度图像
  gray = cv.cvtColor(blur, cv.COLOR_BGR2GRAY)
  # 二值化 设置阈值 自适应阈值的话 黄色的4会提取不出来
  ret, binary = cv.threshold(gray, 185, 255, cv.THRESH_BINARY_INV)
  print(f'二值化设置的阈值:{ret}')
  cv.imshow('binary', binary)
  # 逻辑运算 让背景为白色 字体为黑 便于识别
  cv.bitwise_not(binary, binary)
  cv.imshow('bg_image', binary)
  # 识别
  test_message = Image.fromarray(binary)
  text = pytesseract.image_to_string(test_message)
  print(f'识别结果:{text}')


src = cv.imread(r'./test/045.jpg')
cv.imshow('input image', src)
recognize_text(src)
cv.waitKey(0)
cv.destroyAllWindows()

运行效果如下:

二值化设置的阈值:185.0
识别结果:7364

Process finished with exit code 0

python opencv pytesseract 验证码识别的实现

到此这篇关于python opencv pytesseract 验证码识别的实现的文章就介绍到这了,更多相关opencv pytesseract 验证码识别内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家!

原文链接:https://blog.csdn.net/fyfugoyfa/article/details/108160915