IntroToPyCV.py

# OpenCV program to detect face in real time
# import libraries of python OpenCV 
# where its functionality resides
import cv2 
import numpy as np
 
# load the required trained XML classifiers
# https://github.com/Itseez/opencv/blob/master/
# data/haarcascades/haarcascade_frontalface_default.xml
# Trained XML classifiers describes some features of some
# object we want to detect a cascade function is trained
# from a lot of positive(faces) and negative(non-faces)
# images.
faceDetect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# capture frames from a camera
cap = cv2.VideoCapture(0)
 
# loop runs if capturing has been initialized.
while 1: 
 
    # reads frames from a camera
    ret, img = cap.read() 
 
    # convert to gray scale of each frames
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
    # Detects faces of different sizes in the input image
    faces = faceDetect.detectMultiScale(gray, 1.3, 5)
 
    for (x,y,w,h) in faces:
        # To draw a rectangle in a face 
        cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2) 

    cv2.imshow('img',img)
 
    # Wait for Esc key to stop
    if(cv2.waitKey(1) == ord('q')):
        break;
 
# Close the window
cap.release()
 
# De-allocate any associated memory usage
cv2.destroyAllWindows()