python2

import cv2
import numpy as np
from os import listdir
from os.path import isfile, join
print(cv2.__version__)
# Get the training data we previously made
data_path = './sami'
# a=listdir('d:/faces')
# print(a)
# """
onlyfiles = [f for f in listdir(data_path) if isfile(join(data_path,
f))]

# Create arrays for training data and labels
Training_Data, Labels = [], []

# Open training images in our datapath
# Create a numpy array for training data
for i, files in enumerate(onlyfiles):
     image_path = data_path + "/" + onlyfiles[i]
     images = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
     Training_Data.append(np.asarray(images, dtype=np.uint8))
     Labels.append(i)
#
# Create a numpy array for both training data and labels
Labels = np.asarray(Labels, dtype=np.int32)
sami_model=cv2.face_LBPHFaceRecognizer.create()
# Initialize facial recognizer
# model = cv2.face_LBPHFaceRecognizer.create()
# model=cv2.f
# NOTE: For OpenCV 3.0 use cv2.face.createLBPHFaceRecognizer()

# Let's train our model
sami_model.train(np.asarray(Training_Data), np.asarray(Labels))
print("Model trained sucessefully")