Train a model from image database and create a .yml file.

facetrain.py

import os
import cv2
import numpy as np
from PIL import Image

#recognizer=cv2.createLBPHFaceRecognizer();
recognizer = cv2.face.LBPHFaceRecognizer_create()
path='dataSet'

def getImagesWithID(path):
    imagepaths=[os.path.join(path,f) for f in os.listdir(path)]
    faces=[]
    IDs=[]
    for imagepath in imagepaths:
        if ".DS_Store" in imagepath:
            print("Junk!")
        else:
            faceImg=Image.open(imagepath).convert('L');
            faceNp=np.array(faceImg,'uint8')
            ID=int(os.path.split(imagepath)[-1].split('.')[1])
            faces.append(faceNp)
            IDs.append(ID)
            cv2.imshow("training",faceNp)
            cv2.waitKey(10)
    return np.array(IDs),faces

IDs,faces=getImagesWithID(path)
recognizer.train(faces,IDs)
recognizer.save('recognizer/trainningData.yml')
cv2.destroyAllWindows()