face_detection.py

# face detection in python
# kindly download xml files from github

import cv2

face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades +'haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades +'haarcascade_eye.xml')
smile_cascade = cv2.CascadeClassifier(cv2.data.haarcascades +'haarcascade_smile.xml')
# faces  = face_cascade.detectMultiScale(gray, 1.3, 5)
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
def detect(gray, frame):
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), ((x + w), (y + h)), (255, 0, 0), 2)
        roi_gray = gray[y:y + h, x:x + w]
        roi_color = frame[y:y + h, x:x + w]
        smiles = smile_cascade.detectMultiScale(roi_gray, 1.8, 20)
        
        for (sx, sy, sw, sh) in smiles:
            cv2.rectangle(roi_color, (sx, sy), ((sx + sw), (sy + sh)), (0, 0, 255), 2)
    return frame

video_capture = cv2.VideoCapture(0)
while video_capture.isOpened():
# Captures video_capture frame by frame
	_, frame = video_capture.read()

	# To capture image in monochrome				
	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
	
	# calls the detect() function
	canvas = detect(gray, frame)

	# Displays the result on camera feed					
	cv2.imshow('Video', canvas)

	# The control breaks once q key is pressed					
	if cv2.waitKey(1) & 0xff == ord('q'):			
		break

# Release the capture once all the processing is done.
video_capture.release()								
cv2.destroyAllWindows()