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Face_Detection.py
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Face_Detection.py
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import numpy as np
import cv2
faceCascade = cv2.CascadeClassifier('Cascades/haarcascade_frontalface_default.xml')
video = cv2.VideoCapture(0)
video.set(3,1920) # The width of the screen
video.set(4,1080) # The height of the screen
while True:
ret, img = video.read() #get a frame from the video
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #convert to grayscale for the model
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(20, 20)
) #find faces in the video frame
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) #draw a rectangle from bottom left (x,y) to top right (x+h, y+h) of detected face
cv2.imshow('video',img) #display the frames as a video
k = cv2.waitKey(30) & 0xff
if k == 27: # press 'ESC' to quit
break
video.release()
cv2.destroyAllWindows()