Face Detection using OpenCV and Python | Code Epic

December 03, 2020

Photo by Marily Torres from Pexels

In this post, I wanted to share a very easy and popular way of face detecting using Haar cascades in OpenCV and python.

First, install python on your computer

To download python [click here]

Now install OpenCV. You can install it by using the pip command in python

pip install opencv-python

Face detection using Haar cascades is a machine learning-based approach where a cascade function is trained with a group of the input file. OpenCV has many classifiers for face, eyes, smiles, etc. Today we'll be using the face classifier. You'll be able to experiment with other classifiers also.

You need to download the trained classifier XML file (haarcascade_frontalface_default.xml), which is out there in OpenCV's GitHub repository. Save it to your working location.

Our setup is done now let's start to code

Don't worry, just paste this code into Notepad

Code for detect face in the image


import cv2
  
# Load the cascade
  
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
  
# Read the input image
  
img = cv2.imread('test.jpg')
  
# Convert into grayscale
  
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  
# Detect faces
  
faces = face_cascade.detectMultiScale(gray, 1.1, 4)
  
# Draw rectangle around the faces
  
for (x, y, w, h) in faces:
  
    cv2.rectangle(img, (x, y), (x+w, y+h), (10, 55, 255), 6)
  
# Display the output
  
cv2.imshow('img', img)
  
cv2.waitKey()

save your file as yourname.py

Place the image in your workspace which you want to detect face it must be in "PNG" format, and it must be named as "test"

Just double-click the file to run your program

If you want to use a JPG format image, you can change this line to "image name.jpg"