OpenCV搞定腾讯滑块验证码的实现代码

import cv2 as cv
import numpy as np

if __name__ == '__main__':
 img = np.ones((200, 200, 3), np.uint8) * 255
 cv.rectangle(img, (50, 50), (150, 150), (0, 0, 255), 2)
 cv.imshow('test', img)
 cv.waitKey(0)
 cv.destroyAllWindows()

# encoding:utf-8
import cv2 as cv
import numpy as np


# 对滑块进行二值化处理
def handle_img1(image):
  kernel = np.ones((8, 8), np.uint8) # 去滑块的前景噪声内核
  gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
  width, heigth = gray.shape
  for h in range(heigth):
    for w in range(width):
      if gray[w, h] == 0:
        gray[w, h] = 96
  # cv.imshow('gray', gray)
  binary = cv.inRange(gray, 96, 96)
  res = cv.morphologyEx(binary, cv.MORPH_OPEN, kernel) # 开运算去除白色噪点
  # cv.imshow('res', res)
  return res


# 模板匹配(用于寻找缺口有点误差)
def template_match(img_target, img_template):
  tpl = handle_img1(img_template) # 误差来源就在于滑块的背景图为白色
  blurred = cv.GaussianBlur(img_target, (3, 3), 0) # 目标图高斯滤波
  gray = cv.cvtColor(blurred, cv.COLOR_BGR2GRAY)
  ret, target = cv.threshold(gray, 127, 255, cv.THRESH_BINARY) # 目标图二值化
  # cv.imshow("template", tpl)
  # cv.imshow("target", target)
  method = cv.TM_CCOEFF_NORMED
  width, height = tpl.shape[:2]
  result = cv.matchTemplate(target, tpl, method)
  min_val, max_val, min_loc, max_loc = cv.minMaxLoc(result)
  left_up = max_loc
  right_down = (left_up[0] + height, left_up[1] + width)
  cv.rectangle(img_target, left_up, right_down, (0, 0, 255), 2)
  cv.imshow('res', img_target)


if __name__ == '__main__':
  img0 = cv.imread('./demo/3/hycdn_3.jpg')
  img1 = cv.imread('./demo/3/hycdn_3_2.png')
  template_match(img0, img1)
  cv.waitKey(0)
  cv.destroyAllWindows()

# encoding:utf-8
import cv2 as cv


def get_pos(image):
  blurred = cv.GaussianBlur(image, (5, 5), 0)
  canny = cv.Canny(blurred, 200, 400)
  contours, hierarchy = cv.findContours(canny, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
  for i, contour in enumerate(contours):
    M = cv.moments(contour)
    if M['m00'] == 0:
      cx = cy = 0
    else:
      cx, cy = M['m10'] / M['m00'], M['m01'] / M['m00']
    if 6000 < cv.contourArea(contour) < 8000 and 370 < cv.arcLength(contour, True) < 390:
      if cx < 400:
        continue
      x, y, w, h = cv.boundingRect(contour) # 外接矩形
      cv.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2)
      cv.imshow('image', image)
      return x
  return 0


if __name__ == '__main__':
  img0 = cv.imread('./demo/4/hycdn_4.jpg')
  get_pos(img0)
  cv.waitKey(0)
  cv.destroyAllWindows()