train1.py

import cv2
import numpy as np
from os import listdir
from os.path import isfile, join

# Get the training data we previously made
data_path = './face/'
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)

# Initialize facial recognizer
model = cv2.face.LBPHFaceRecognizer_create()

# NOTE: For OpenCV 3.0 use cv2.face.createLBPHFaceRecognizer()

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