如何用C++实现以下Python的codes功能（相邻轮廓合并）

import numpy as np

import cv2

src = cv2.imread('A.jpg')

cv2.imshow('src', src)

split_res = src.copy()#显示每个轮廓结构

merge_res = src.copy()#显示合并后轮廓结构

# 记录开始时间

start = cv2.getTickCount()

hsvImg = cv2.cvtColor(src,cv2.COLOR_BGR2HSV)

H,S,V = cv2.split(hsvImg)

ret, thresImg= cv2.threshold(S, 138, 255, cv2.THRESH_BINARY)

cv2.imshow('threshold', thresImg)

blurImg = cv2.medianBlur(thresImg,5)

cv2.imshow('blur', blurImg)

contours,hierarchy = cv2.findContours(blurImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

merge_list = []

for cnt in contours:

   rect = cv2.minAreaRect(cnt)

   box = cv2.boxPoints(rect)

   box = np.int0(box)

   split_res = cv2.drawContours(split_res,[box],0,(0,0,255),2)

   merge_list.append(cnt)

cv2.imshow('split_res', split_res)

cv2.imwrite('split_res.jpg', split_res)

contours_merge = np.vstack([merge_list[0],merge_list[1]])

for i in range(2, len(merge_list)):

  contours_merge = np.vstack([contours_merge,merge_list[i]])

rect2 = cv2.minAreaRect(contours_merge)

box2 = cv2.boxPoints(rect2)

box2 = np.int0(box2)

merge_res = cv2.drawContours(merge_res,[box2],0,(0,255,0),2)

cv2.imshow('merge_res', merge_res)

cv2.imwrite('merge_res.jpg', merge_res)

# 记录结束时间 end = cv2.getTickCount()

# 运行耗时 use_time = (end - start) / cv2.getTickFrequency()

print('use-time: %.3fs' % use_time)

cv2.waitKey(0)

cv2.destroyAllWindows()

print ('finish')