#OpenCV – Detect and blur faces 😁 using haar cascades in Python πŸ

Hi !

Quick post today: detect a face using haar cascades and blur the face area. Easy to implement, and also easy to read:

face blur on a camera view

Code below

# Copyright (c) 2022
# Author : Bruno Capuano
# Create Time : 2022 Feb
# Change Log :
# – Open a camera feed from a local webcam and analyze each frame to detect faces using haar cascades
# – When a face is detected, the app will blur the face zone
# – Press [Q] to quit the app
#
# The MIT License (MIT)
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
import cv2
import time
video_capture = cv2.VideoCapture(0)
time.sleep(2)
# enable face detection
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# open
while True:
try:
_, frameOrig = video_capture.read()
frame = cv2.resize(frameOrig, (640, 480))
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (top, right, bottom, left) in faces:
cv2.rectangle(frame,(top,right),(top+bottom,right+left),(0,0,255),2)
face = frame[right:right+left, top:top+bottom]
face = cv2.GaussianBlur(face,(23, 23), 30)
# merge this blurry rectangle to our final image
frame[right:right+face.shape[0], top:top+face.shape[1]] = face
cv2.imshow('@elbruno – Face Blur', frame)
except Exception as e:
print(f'exc: {e}')
pass
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()

Important: Haar cascades are easy to implement and learn, however, not recommented as a good solution to detect faces.

Happy coding!

Greetings

El Bruno

More posts in my blog ElBruno.com.


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