Real Time Face Detection Using OpenCV & python - By ShadBox

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Blog Status: publish

Created By: swazahmad Created at: 07-15-2021

Tags: python basicprogramming web development shadbox face detection software engineering

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()

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swazahmad

Swaz is Practice Lead of ROR Developer. he's a Blogger, Mentor, and Rubyst. He has expertise in Javascript also . he's highly skilled in designing, developing and testing web applications. He enjoys being challenged and interesting with projects that need him to

Comments

swazahmad | almost 4 years ago

Awesome Information Thanks For Sharing

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	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()