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face_det.py
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face_det.py
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# -*- coding: utf-8 -*-
import cv2
import numpy as np
#import time
#import matplotlib.pyplot as plt
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
face_cascade.load('haarcascade_frontalface_default.xml')
videocapture = cv2.VideoCapture(0)
scale_factor = 1.3
#Stime.sleep(2)
while 1:
ret_,pic = videocapture.read()
#Detects objects of different sizes in the input image.
#The detected objects are returned as a list of rectangles.
faces = face_cascade.detectMultiScale(pic,scale_factor,5)
for (x,y,w,h) in faces:
cv2.rectangle(pic,(x,y),(x+w,y+h),(255,0,0),2)
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(pic,'Me',(x,y),font,2,(255,255,255),2,cv2.LINE_AA)
print("no of faces{}".format(len(faces)))
cv2.imshow('face',pic)
k=cv2.waitKey(30) & 0xff
if k==2:
break
videocapture.release()
cv2.destroyAllWindows()