我在使用OpenCV（cv2）时遇到以下问题。我不知道如何解决。 我正在使用VS 2019，最新的OpenCV和最新的Python环境

错误代码： OpenCV（4.1.1）C：\ projects \ opencv-python \ opencv \ modules \ highgui \ src \ window.cpp：627：错误：（-2：未指定错误）该功能未实现。在Windows，GTK + 2.x或Cocoa支持下重建库。如果您使用的是Ubuntu或Debian，请安装libgtk2.0-dev和pkg-config，然后重新运行cmake或在功能'cvShowImage'中配置脚本

'''
    Copyright 2017 by Satya Mallick ( Big Vision LLC )
    http://www.learnopencv.com
'''

import cv2
import numpy as np


def fillHoles(mask):
    '''
        This hole filling algorithm is decribed in this post
        https://www.learnopencv.com/filling-holes-in-an-image-using-opencv-python-c/
    '''
    maskFloodfill = mask.copy()
    h,w = maskFloodfill.shape[:2]
    maskTemp = np.zeros((h+2,w+2),np.uint8)
    cv2.floodFill(maskFloodfill,maskTemp,(0,0),255)
    mask2 = cv2.bitwise_not(maskFloodfill)
    return mask2 | mask

if __name__ == '__main__' :

    # Read image
    img = cv2.imread("red_eyes.jpg",cv2.IMREAD_COLOR)

    # Output image
    imgOut = img.copy()

    # Load HAAR cascade
    eyesCascade = cv2.Cascadeclassifier("haarcascade_eye.xml")

    # Detect eyes
    eyes = eyesCascade.detectMultiScale(img,scaleFactor=1.3,minNeighbors=4,minSize=(100,100))

    # For every detected eye
    for (x,y,w,h) in eyes:

        # Extract eye from the image
        eye = img[y:y+h,x:x+w]

        # Split eye image into 3 channels
        b = eye[:,:,0]
        g = eye[:,1]
        r = eye[:,2]

        # Add the green and blue channels.
        bg = cv2.add(b,g)

        # Simple red eye detector.
        mask = (r > 150) &  (r > bg)

        # Convert the mask to uint8 format.
        mask = mask.astype(np.uint8)*255

        # Clean mask -- 1) File holes 2) Dilate (expand) mask.
        mask = fillHoles(mask)
        mask = cv2.dilate(mask,None,anchor=(-1,-1),iterations=3,borderType=1,borderValue=1)

        # Calculate the mean channel by averaging
        # the green and blue channels
        mean = bg / 2
        mask = mask.astype(np.bool)[:,np.newaxis]
        mean = mean[:,np.newaxis]

        # Copy the eye from the original image.
        eyeOut = eye.copy()

        # Copy the mean image to the output image.
        #np.copyto(eyeOut,mean,where=mask)
        eyeOut = np.where(mask,eyeOut)

        # Copy the fixed eye to the output image.
        imgOut[y:y+h,x:x+w,:] = eyeOut

    # Display Result
    cv2.imshow('Red Eyes',img)
    cv2.imshow('Red Eyes Removed',imgOut)
    cv2.waitKey(0)