前言

最近突然有個奇妙的想法，就是當我對著電腦屏幕的時候，電腦會先識別屏幕上的人臉是否是本人，如果識別是本人的話需要回答電腦說的暗語，答對了才會解鎖并且有三次機會。如果都沒答對就會發送郵件給我，通知有人在動我的電腦并上傳該人頭像。

過程

環境是win10代碼我使用的是python3所以在開始之前需要安裝一些依賴包，請按順序安裝否者會報錯

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

接下來是構建識別人臉以及對比人臉的代碼

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需要你自己拍攝上傳，運行可以發現在你臉上會出現Admin的框框，我去網上找了張圖片類似這樣子

識別功能已經完成了接下來就是語音識別和語音合成，這需要使用到百度AI來實現了，去登錄百度AI的官網到控制臺選擇左邊的語音技術，然后點擊面板的創建應用按鈕，來到創建應用界面

創建后會得到AppID、API Key、Secret Key記下來，然后開始寫語音合成的代碼。安裝百度AI提供的依賴包

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

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

然后是簡單的語音播放代碼，運行下面代碼可以聽到萌妹子的聲音

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)

有了上面的代碼就完成了檢測是否在電腦前（人臉識別）以及電腦念出暗語（語音合成）然后我們還需要回答暗號給電腦，所以還需要完成語音識別。

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)

運行此代碼之前需要安裝pyaudio依賴包，由于在win10系統上安裝會報錯所以可以通過如下方式安裝。到這個鏈接 https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyaudio 去下載對應的安裝包然后安裝即可。

運行后我說了你好，可以看到識別出來了。那么我們的小模塊功能就都做好了接下來就是如何去整合它們?？梢园l現在人臉識別代碼中if matches[best_match_index]這句判斷代碼就是判斷是否為電腦主人，所以我們把這個判斷語句當作main函數的入口。

if matches[best_match_index]:

# 在這里寫識別到之后的功能

name = known_face_names[best_match_index]

那么識別到后我們應該讓電腦發出詢問暗號，也就是語音合成代碼，然我們將它封裝成一個函數，順便重構下人臉識別的代碼。

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("識別到人臉，開始詢問暗號，請回答接下來我說的問題")

time.sleep(1)

speak("天王蓋地虎")

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()

這里有一點需要注意，由于playsound播放音樂的時候會一直占用這個資源，所以播放下一段音樂的時候會報錯，解決方法是修改~\Python37\Lib\site-packages下的playsound.py文件，找到如下代碼

在sleep函數下面添加winCommand('close', alias)這句代碼，保存下就可以了。運行發現可以正常將兩句話都說出來。那么說出來之后就要去監聽了，我們還要打包一個函數。

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]

將識別到人臉后的代碼修改成如下

if matches[best_match_index]:

speak("識別到人臉，開始詢問暗號，請回答接下來我說的問題")

time.sleep(1)

speak("天王蓋地虎")

flag = False

for times in range(0, 3):

content = record()

if "小雞燉蘑菇" in content:

speak("暗號通過")

flag = True

break

else:

speak("暗號不通過，再試一次")

if flag:

print("解鎖")

else:

print("發送郵件并將壞人人臉圖片上傳！")

error = 1 / 0

name = known_face_names[best_match_index]

運行看看效果，回答電腦小雞燉蘑菇，電腦回答暗號通過。這樣功能就基本上完成了。

結語

至于發送郵件的功能和鎖屏解鎖的功能我就不一一去實現了，我想這應該難不倒在座的各位吧。如果在上面的教程中有什么疑問可以在下面留言或者在我的博客上留言。還有本文純屬原創，轉載請注明出處！

我的博客地址

上文有需要解決的問題可以到博客去留言，有郵件通知我會及時去回復。感謝吾愛的盆友們支持！

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