Python OpenCV错误MagicMirror AttributeError:&x27；cv2.人脸识别器&x27；对象没有属性'；写'；

配置：

#!/usr/bin/env python
# coding: utf8 
"""MMMM-Facial-Recognition-OCV3 - MagicMirror Module The MIT License (MIT)

Copyright (c) 2018 Mathieu Goulène (MIT License) Based on work by Paul-Vincent Roll (Copyright 2016) (MIT License) """

# to install builtins run `pip install future` from builtins import input

import cv2 import numpy as np import os

from lib.tools.config import ToolsConfig from lib.common.face import FaceDetection

class ToolsTrain:
    def __init__(self):

        self.face = ToolsConfig.getFaceDetection()

    def prepareImage(self, filename):
        """Read an image as grayscale and resize it to the appropriate size for
        training the face recognition model.
        """
        return self.face.resize(cv2.imread(filename, cv2.IMREAD_GRAYSCALE),ToolsConfig.FACE_WIDTH, ToolsConfig.FACE_HEIGHT)


    def train(self):
        print("Reading training images...")
        print('-' * 20)
        faces = []
        labels = []
        imageDirsWithLabel = [[0, "negative"]]
        imageDirs = os.listdir(ToolsConfig.TRAINING_DIR)
        imageDirs = [x for x in imageDirs if not x.startswith('.') and not x.startswith('negative')]
        pos_count = 0

        for i in range(len(imageDirs)):
            print("Assign label " + str(i + 1) + " to " + imageDirs[i])
            imageDirsWithLabel.append([i + 1, imageDirs[i]])
        print('-' * 20)
        print('')

        # Für jedes Label/Namen Paar:
        # for every label/name pair:
        for j in range(0, len(imageDirsWithLabel)):
            # Label zu den Labels hinzufügen / Bilder zu den Gesichtern
            for filename in ToolsConfig.walkFiles(ToolsConfig.TRAINING_DIR + str(imageDirsWithLabel[j][1]), '*.pgm'):
                faces.append(self.prepareImage(filename))
                labels.append(imageDirsWithLabel[j][0])
                if imageDirsWithLabel[j][0] != 0:
                    pos_count += 1

        # Print statistic on how many pictures per person we have collected
        print('Read '  + str(pos_count) + ' positive images and ' + str(labels.count(0)) + ' negative images.')
        print('')
        for j in range(1, max(labels) + 1):
            print(str(labels.count(j)) + " images from subject " + imageDirs[j - 1])

        # Train model
        print('-' * 20)
        print('')

CMD:

sudo python tools.train.py

错误/输出

记住设置名称列表环境变量FACE\u user Reading
训练图像。。。
--------------------将标签1指定给Jorick
--------------------
阅读7张正面图像和0张负面图像。
受试者Jorick的7幅图像
--------------------
具有阈值80回溯的培训模型（最近一次呼叫最后一次）：
文件“tools.train.py”，第14行，在
ToolsTrain（）.train（）文件“/home/pi/MagicMirror/modules/MMM-face-Recognition-OCV3/lib/tools/train.py”，
74号线，火车上
model.write（ToolsConfig.TRAINING\u文件）AttributeError:'cv2.face\u LBPHFaceRecognizer'对象没有属性'write'

Git包：

Python版本：

---

Python 2.7.16

您似乎正在使用旧版本的OpenCV，为了运行MMM-face-Recognition-OCV3，您将需要OpenCV 3.3，任何旧版本都将失败，因为cv:：face:：FaceRecognitizer的接口在3.2和3.3之间更改。阅读MMM-face-Recognition-OCV3存储库自述文件-它解释了如何安装该软件包dependencies@Black0ut我找不到它。