超级黑科技代码！用 Python 打造电脑人脸屏幕解锁神器附带接头暗号！

2020-04-26 13:49:20 +08:00
 Liulang007

前言

最近突然有个奇妙的想法，就是当我对着电脑屏幕的时候，电脑会先识别屏幕上的人脸是否是本人，如果识别是本人的话需要回答电脑说的暗语，答对了才会解锁并且有三次机会。如果都没答对就会发送邮件给我，通知有人在动我的电脑并上传该人头像。

过程

环境是win10代码我使用的是python3所以在开始之前需要安装一些依赖包，请按顺序安装否者会报错

pip install cmake -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install dlib -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install face_recognition -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install opencv-python -i https://pypi.tuna.tsinghua.edu.cn/simple

接下来是构建识别人脸以及对比人脸的代码

import face_recognition
import cv2
import numpy as np

video_capture = cv2.VideoCapture(0)
my_image = face_recognition.load_image_file("my.jpg")
my_face_encoding = face_recognition.face_encodings(my_image)[0]
known_face_encodings = [
    my_face_encoding
]
known_face_names = [
    "Admin"
]

face_names = []
face_locations = []
face_encodings = []
process_this_frame = True

while True:
    ret, frame = video_capture.read()
    small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
    rgb_small_frame = small_frame[:, :, ::-1]
    if process_this_frame:
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
        face_names = []
        for face_encoding in face_encodings:
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Unknown"
            face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
            best_match_index = np.argmin(face_distances)
            if matches[best_match_index]:
                name = known_face_names[best_match_index]
            face_names.append(name)

    process_this_frame = not process_this_frame
    for (top, right, bottom, left), name in zip(face_locations, face_names):
        top *= 4
        left *= 4
        right *= 4
        bottom *= 4
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    cv2.imshow('Video', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

video_capture.release()
cv2.destroyAllWindows()

其中my.jpg需要你自己拍摄上传，运行可以发现在你脸上会出现Admin的框框，我去网上找了张图片类似这样子

识别功能已经完成了接下来就是语音识别和语音合成，这需要使用到百度 AI 来实现了，去登录百度 AI 的官网到控制台选择左边的语音技术，然后点击面板的创建应用按钮，来到创建应用界面

创建后会得到 AppID 、API Key 、Secret Key 记下来，然后开始写语音合成的代码。安装百度 AI 提供的依赖包

pip install baidu-aip -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install playsound -i https://pypi.tuna.tsinghua.edu.cn/simple

然后是简单的语音播放代码，运行下面代码可以听到萌妹子的声音

import sys
from aip import AipSpeech
from playsound import playsound

APP_ID = ''
API_KEY = ''
SECRET_KEY = ''

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
result = client.synthesis('你好吖', 'zh', 1, {'vol': 5, 'per': 4, 'spd': 5, })

if not isinstance(result, dict):
    with open('auido.mp3', 'wb') as file:
        file.write(result)

filepath = eval(repr(sys.path[0]).replace('\\', '/')) + '//auido.mp3'
playsound(filepath)

有了上面的代码就完成了检测是否在电脑前（人脸识别）以及电脑念出暗语（语音合成）然后我们还需要回答暗号给电脑，所以还需要完成语音识别。

import wave
import pyaudio
from aip import AipSpeech

APP_ID = ''
API_KEY = ''
SECRET_KEY = ''

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 1
RATE = 8000
RECORD_SECONDS = 3
WAVE_OUTPUT_FILENAME = "output.wav"

p = pyaudio.PyAudio()
stream = p.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK)

print("* recording")
frames = []
for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
    data = stream.read(CHUNK)
    frames.append(data)
print("* done recording")

stream.stop_stream()
stream.close()
p.terminate()
wf = wave.open(WAVE_OUTPUT_FILENAME, 'wb')
wf.setnchannels(CHANNELS)
wf.setsampwidth(p.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))


def get_file_content():
    with open(WAVE_OUTPUT_FILENAME, 'rb') as fp:
        return fp.read()


result = client.asr(get_file_content(), 'wav', 8000, {'dev_pid': 1537, })
print(result)

运行此代码之前需要安装pyaudio依赖包，由于在 win10 系统上安装会报错所以可以通过如下方式安装。到这个链接 https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyaudio 去下载对应的安装包然后安装即可。

运行后我说了你好，可以看到识别出来了。那么我们的小模块功能就都做好了接下来就是如何去整合它们。可以发现在人脸识别代码中if matches[best_match_index]这句判断代码就是判断是否为电脑主人，所以我们把这个判断语句当作 main 函数的入口。

if matches[best_match_index]:
        # 在这里写识别到之后的功能
        name = known_face_names[best_match_index]

那么识别到后我们应该让电脑发出询问暗号，也就是语音合成代码，然我们将它封装成一个函数，顺便重构下人脸识别的代码。

import cv2
import time
import numpy as np
import face_recognition

video_capture = cv2.VideoCapture(0)
my_image = face_recognition.load_image_file("my.jpg")
my_face_encoding = face_recognition.face_encodings(my_image)[0]
known_face_encodings = [
    my_face_encoding
]
known_face_names = [
    "Admin"
]

face_names = []
face_locations = []
face_encodings = []
process_this_frame = True


def speak(content):
    import sys
    from aip import AipSpeech
    from playsound import playsound
    APP_ID = ''
    API_KEY = ''
    SECRET_KEY = ''
    client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
    result = client.synthesis(content, 'zh', 1, {'vol': 5, 'per': 0, 'spd': 5, })
    if not isinstance(result, dict):
        with open('auido.mp3', 'wb') as file:
            file.write(result)
    filepath = eval(repr(sys.path[0]).replace('\\', '/')) + '//auido.mp3'
    playsound(filepath)


try:
    while True:
        ret, frame = video_capture.read()
        small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
        rgb_small_frame = small_frame[:, :, ::-1]
        if process_this_frame:
            face_locations = face_recognition.face_locations(rgb_small_frame)
            face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
            face_names = []
            for face_encoding in face_encodings:
                matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
                name = "Unknown"
                face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
                best_match_index = np.argmin(face_distances)
                if matches[best_match_index]:
                    speak("识别到人脸，开始询问暗号，请回答接下来我说的问题")
                    time.sleep(1)
                    speak("天王盖地虎")
                    error = 1 / 0
                    name = known_face_names[best_match_index]
                face_names.append(name)
        process_this_frame = not process_this_frame
        for (top, right, bottom, left), name in zip(face_locations, face_names):
            top *= 4
            left *= 4
            right *= 4
            bottom *= 4
            font = cv2.FONT_HERSHEY_DUPLEX
            cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
            cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
            cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

        cv2.imshow('Video', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
except Exception as e:
    print(e)
finally:
    video_capture.release()
    cv2.destroyAllWindows()

这里有一点需要注意，由于playsound播放音乐的时候会一直占用这个资源，所以播放下一段音乐的时候会报错，解决方法是修改~\Python37\Lib\site-packages下的playsound.py文件，找到如下代码

在sleep函数下面添加winCommand('close', alias)这句代码，保存下就可以了。运行发现可以正常将两句话都说出来。那么说出来之后就要去监听了，我们还要打包一个函数。

def record():
    import wave
    import json
    import pyaudio
    from aip import AipSpeech

    APP_ID = ''
    API_KEY = ''
    SECRET_KEY = ''

    client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
    CHUNK = 1024
    FORMAT = pyaudio.paInt16
    CHANNELS = 1
    RATE = 8000
    RECORD_SECONDS = 3
    WAVE_OUTPUT_FILENAME = "output.wav"

    p = pyaudio.PyAudio()
    stream = p.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK)

    print("* recording")
    frames = []
    for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
        data = stream.read(CHUNK)
        frames.append(data)
    print("* done recording")

    stream.stop_stream()
    stream.close()
    p.terminate()
    wf = wave.open(WAVE_OUTPUT_FILENAME, 'wb')
    wf.setnchannels(CHANNELS)
    wf.setsampwidth(p.get_sample_size(FORMAT))
    wf.setframerate(RATE)
    wf.writeframes(b''.join(frames))

    def get_file_content():
        with open(WAVE_OUTPUT_FILENAME, 'rb') as fp:
            return fp.read()

    result = client.asr(get_file_content(), 'wav', 8000, {'dev_pid': 1537, })
    result = json.loads(str(result).replace("'", '"'))
    return result["result"][0]

将识别到人脸后的代码修改成如下

if matches[best_match_index]:
        speak("识别到人脸，开始询问暗号，请回答接下来我说的问题")
        time.sleep(1)
        speak("天王盖地虎")

        flag = False
        for times in range(0, 3):
                content = record()
                if "小鸡炖蘑菇" in content:
                        speak("暗号通过")
                        flag = True
                        break
                else:
                        speak("暗号不通过，再试一次")
        if flag:
                print("解锁")
        else:
                print("发送邮件并将坏人人脸图片上传！")
        error = 1 / 0
        name = known_face_names[best_match_index]

运行看看效果，回答电脑小鸡炖蘑菇，电脑回答暗号通过。这样功能就基本上完成了。

结语

至于发送邮件的功能和锁屏解锁的功能我就不一一去实现了，我想这应该难不倒在座的各位吧。如果在上面的教程中有什么疑问可以在下面留言或者在我的博客上留言。还有本文纯属原创，转载请注明出处！

我的博客地址

https://www.meitubk.com/

上文有需要解决的问题可以到博客去留言，有邮件通知我会及时去回复。感谢 V2 盆友们支持！

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1 条回复
xuxyuan158
2020-04-26 14:07:38 +08:00
人才啊，学习了。。。

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