Face detection using openCV python.

Face detection is really fun, attractive and it has its own use.

Without going in much definition let's jump to our implementation.

What is openCV?

openCV stands for Open source computer vision. it is a library of programming functions mainly aimed at real-time computer vision.

For making task easier they have pretrained model name haarcascade
which provides good accuracy.

Approach.

• install opencv at first.

pip install opencv-python

• Import libraries

import cv2

• Attach frontal-face and apply basic logic.

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# Read the input image
img = cv2.imread('your-image')
# convert it into gray code from BGR
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# apply a scale of 1.1 and 4
faces = face_cascade.detectMultiScale(gray, 1.1, 4)

# Make rectangle around face of green colour and thickness of 3.
for (x, y , w ,h) in faces:
  cv2.rectangle(img, (x,y), (x+w, y+h), (0, 255 , 0), 3)

# Display the output
cv2.imshow('img', img)
cv2.waitKey()

• And here you are done.... Output image

This code will detect multiple faces on any image with great accuracy.

It is also possible to detect multiple faces in realtime in videos.
That will be a part of my next blog.
(You can ask doubt in comment section.)

Thanks for reading.
Rishabh Dwivedi.