# -*- coding: utf-8 -*-

"""

Created on Wed May 23 12:12:53 2018

@author: Administrator

"""

import cv2

import os

import numpy as np

from PIL import Image

# recognizer = cv2.createLBPHFaceRecognizer()

detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

recognizer = cv2.face.LBPHFaceRecognizer_create()

def get_images_and_labels(path):

image_paths = [os.path.join(path, f) for f in os.listdir(path)]

face_samples = []

ids = []

for image_path in image_paths:

image = Image.open(image_path).convert('L')

image_np = np.array(image, 'uint8')

if os.path.split(image_path)[-1].split(".")[-1] != 'jpg':

continue

image_id = int(os.path.split(image_path)[-1].split(".")[1])

faces = detector.detectMultiScale(image_np)

for (x, y, w, h) in faces:

face_samples.append(image_np[y:y + h, x:x + w])

ids.append(image_id)

return face_samples, ids

faces, Ids = get_images_and_labels("D:\\picture\\face")

recognizer.train(faces, np.array(Ids))

recognizer.save("trainner.yml")