Real time face detection

Real Time Face Detection Using OpenCV & python

In this post i wanted to share face detection using  using Haar cascades in OpenCV and Python

 

Haar Cascade is a machine learning object detection algorithm used to identify objects in an image or video and based on the concept of ​​ features.

-First install OpenCV library using command 

                               pip install opencv-python                                          

- You need to download Haa cascade XML (haarcascade_frontalface_default.xml ) which is available on OpenCv’s GitHub repository. 

- we can detect faces in videos. As you know videos are basically made up of frames, which are still images. So we perform the face detection for each frame in a video. Here is the code:

	import cv2
	# Load the cascade
	face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
	# To capture video from webcam.
	cap = cv2.VideoCapture(0)
	# To use a video file as input
	# cap = cv2.VideoCapture('filename.mp4')
	while True:
	# Read the frame
	_, img = cap.read()
	# Convert to grayscale
	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
	# Detect the faces
	faces = face_cascade.detectMultiScale(gray, 1.1, 4)
	# Draw the rectangle around each face
	for (x, y, w, h) in faces:
	cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
	# Display
	cv2.imshow('img', img)
	# Stop if escape key is pressed
	k = cv2.waitKey(30) & 0xff
	if k==27:
	break
	# Release the VideoCapture object
	cap.release()