Mosaic the face part of the picture

Premise
install face_recognition library May refer to here
opencv 4.2
numpy

# Mosaic the picture 
import cv2
import numpy as np
import pandas as pd
import os
from matplotlib import pyplot as plt
import face_recognition
img2=cv2.imread("3333.jpg")
img=cv2.imread("9k_.jpg")
# Convert to grayscale 

img2_gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
img2_face=face_recognition.face_locations(img2,number_of_times_to_upsample = 0,model ='cnn')
for (top,right,bottom,left) in img2_face:
# Mark the position of the eyes with a rectangular box   Detecting multiscale images , The return value is a list of facial region information （x,y, wide , high ）
# cv2.rectangle(img2,(left,top),(right,bottom),(255,0,0),2)
    roi_gray = img2_gray[top:bottom, left:right]
    roi_color= img2[top:bottom, left:right]

img2=img2[top:bottom, left:right]
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces=face_recognition.face_locations(img,number_of_times_to_upsample = 0,model ='cnn')
#x left y top x+w right y+h bottom
for (top,right,bottom,left) in faces:
# Mark the position of the eyes with a rectangular box   Detecting multiscale images , The return value is a list of facial region information （x,y, wide , high ）
 # cv2.rectangle(img,(left,top),(right,bottom),(255,0,0),2)
    height,width =[bottom-top,right-left]
    img2 = cv2.resize(img2,(height , width),interpolation=cv2.INTER_AREA)
    roi_gray = gray[top:bottom, left:right]
    roi_color = img[top:bottom, left:right]   
    img[top:bottom, left:right]=img2
cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

The effect is as follows ：