https://medium.com/jungletronics/advanced-python-technologies-ii-33d2d6888583

blurring_faces_office.py

# https://stackoverflow.com/questions/65827830/disabledfunctionerror-cv2-imshow-is-disabled-in-colab-because-it-causes-jupy

from google.colab.patches import cv2_imshow
from PIL import Image
import face_recognition
import cv2
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

# Load the jpg file into a numpy array
image = face_recognition.load_image_file("office.jpg")
new_img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

# Find all the faces in the image using the default HOG-based model.
# This method is fairly accurate, but not as accurate as the CNN model and not GPU accelerated.
# See also: find_faces_in_picture_cnn.py
face_locations = face_recognition.face_locations(image)

for face_location in face_locations:

    # Print the location of each face in this image
    top, right, bottom, left = face_location

    # You can access the actual face itself like this:
    face_image = image[top:bottom, left:right]
    pil_image = Image.fromarray(face_image)
    face_image = cv2.GaussianBlur(face_image, (99, 99), 30)
    new_img[top:bottom, left:right] = face_image

# Display the resulting image
cv2_imshow(new_img)