Face Detection

What is Face Detection?

Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.

What are Haar Cascades?

Haar Cascade classifiers are an effective way for object detection.
Proposed by Paul Viola and Michael Jones in their paper Rapid Object Detection using a Boosted Cascade of Simple Features ↗
It is a machine learning-based approach where a lot of positive and negative images are used to train the classifier.
- Positive images – These images contain the images which we want our classifier to identify.
- Negative Images – Images of everything else, which do not contain the object we want to detect.

(Know more here ↗).

Haar-cascade Detection in Python(OpenCV)

OpenCV comes as a detector which uses Haar Cascade.
In face detection, we use the Haarcascade Frontal Face which is in xml format.

Let's jump into the code

What are the requirements you need to have before running the code (all latest version)

--- python
--- opencv-python
--- haarcascade_frontalface_default.xml

Download the haar cascade files here ↗

First we need to load the required XML classifiers. Then load our input image (or video) in grayscale mode.

import numpy as np
#importing the OpenCV Lib
import cv2

#Loading the haarcascade front face file
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

#Reading the face image
img = cv2.imread('testFace.jpg')

#Converting the image into grayscale image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

Now we find the faces in the image. If faces are found, it returns the positions of detected faces as Rect(x,y,w,h).

#Detecting the face
face = faceCascade.detectMultiScale(gray, 1.1,4)

#Draw rectangle around the face
for(x,y,w,h) in face:
    cv2.rectangle(img, (x,y),(x+w, y+h), (255,0,0),2)

Now we will show the output

#Display the result with face detected
cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

saswatsamal/faceDetection