face_recognize.py

# facerec.py
import cv2, sys, numpy, os, smtplib
size = 4
haar_file = 'haarcascade_frontalface_default.xml'
datasets = 'database'
# Part 1: Create fisherRecognizer
print('Training...')
# Create a list of images and a list of corresponding names
(images, lables, names, id) = ([], [], {}, 0)
for (subdirs, dirs, files) in os.walk(datasets):
    for subdir in dirs:
        names[id] = subdir
        subjectpath = os.path.join(datasets, subdir)
        for filename in os.listdir(subjectpath):
            path = subjectpath + '/' + filename
            lable = id
            images.append(cv2.imread(path, 0))
            lables.append(int(lable))
        id += 1
(width, height) = (112, 92)
#(width, height) = (130, 100)
# Create a Numpy array from the two lists above
(images, lables) = [numpy.array(lis) for lis in [images, lables]]

# OpenCV trains a model from the images
# NOTE FOR OpenCV2: remove '.face'
model = cv2.face.createFisherFaceRecognizer()
model.train(images, lables)

# Part 2: Use fisherRecognizer on camera stream
face_cascade = cv2.CascadeClassifier(haar_file)
webcam = cv2.VideoCapture(0)
while True:
    (_, im) = webcam.read()
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in faces:
        cv2.rectangle(im,(x,y),(x+w,y+h),(255,0,0),2)
        face = gray[y:y + h, x:x + w]
        face_resize = cv2.resize(face, (width, height))
        # Try to recognize the face
        prediction = model.predict(face_resize)
        cv2.rectangle(im, (x, y), (x + w, y + h), (0, 255, 0), 3)

        if prediction[1]<500:

	       cv2.putText(im,'%s - %.0f' % (names[prediction[0]],prediction[1]),(x-10, y-10), cv2.FONT_HERSHEY_PLAIN,1,(0, 255, 0))
    	else:
    	  cv2.putText(im,'not recognized',(x-10, y-10), cv2.FONT_HERSHEY_PLAIN,1,(0, 255, 0))
          # creates SMTP session
          s = smtplib.SMTP('smtp.gmail.com', 587)
 
          # start TLS for security
          s.starttls()
 
          # Authentication
          s.login("your_email_id", "your_password")
 
          # message to be sent
          message = ""
 
          # sending the mail
          s.sendmail("your_email_id", "receiver_email_id", message)
 
          # terminating the session
          s.quit()

    cv2.imshow('OpenCV', im)
    key = cv2.waitKey(10)
    if key == 27:
        break