haareyfac.py

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'''

import numpy as np
import cv2

#Written with help from the tutorial on haar cascades on pythonprogramming.net by sentdex
#multiple cascades: https://github.com/Itseez/opencv/tree/master/data/haarcascades

#https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_frontalface_default.xml


face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
#https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_eye.xml
#eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')

cap = cv2.VideoCapture(0) #0 for the webcam, 1 for the primary camera and so on
flag = 100
while True:
        ret, img = cap.read()
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5) #The figures 1.3 and 5 depend on the size of the image and the likelihood of finding a face in the image



        for(x, y, w, h) in faces: #x, y Cartesian Co-ordinates, width and height
                cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2) #Drawing a rectangle

                #roi_gray = gray[y:y+h, x:x+w] #Cropping the Gray Region Of Interest, always Y:X
                #roi_color = img[y:y+h, x:x+w]
                #eyes = eye_cascade.detectMultiScale(roi_gray) #Relying on default values

                #for(ex, ey, ew, eh) in eyes:
                #cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)

        #ser.write("5")
        cv2.imshow('img', img)
        k = cv2.waitKey(30) & 0xff

        if k == 27:
                break


cap.release()
cv2.destroyAllWindows()