Detecting and tracking faces
OpenCV provides a nice face detection framework. We just need to load the cascade file and use it to detect the faces in an image. Let's see how to do it:
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('./cascade_files/haarcascade_frontalface_alt.xml')
cap = cv2.VideoCapture(0)
scaling_factor = 0.5
while True:
ret, frame = cap.read()
frame = cv2.resize(frame, None, fx=scaling_factor,
fy=scaling_factor, interpolation=cv2.INTER_AREA)
face_rects = face_cascade.detectMultiScale(frame, scaleFactor=1.3, minNeighbors=3)
for (x,y,w,h) in face_rects:
cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 3)
cv2.imshow('Face Detector', frame)
c = cv2.waitKey(1)
if c == 27:
break
cap.release()
cv2.destroyAllWindows()If you run the preceding code, the result will look something like the following image:
Understanding it better
We need a classifier model that can be used to detect faces...
