detect.py

# facerec.py
import cv2, sys, numpy, os

def facereco():

    size = 4
    datasets = 'datasets'

# Part 1: Create fisherRecognizer

    print('Recognizing Face Please Be in sufficient Light Conditions...')

# 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) = (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.LBPHFaceRecognizer_create()
    model.train(images, lables)

# Part 2: Use fisherRecognizer on camera stream

    face_cascade =  cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')



    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]<70:
               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))


       cv2.imshow('OpenCV', im)
       key = cv2.waitKey(10)
       if key == 5:
           break
    webcam.release()
    cv2.destroyAllWindows()