环境安装与配置（Windows 10）
步骤一：安装以下Python库
scipy、OpenCV、numpy、imutils、pyglet
建议用Anaconda 3。上面的库都可以用pip install XXX来安装，OpenCV的安装教程参考：Install OpenCV3 on Windows。
步骤二：安装Dlib（Python 3）
在安装Dlib之前，需要确保已经安装好Visual Studio 2015（update 3）和CMake。
这里附上资源下载链接：
Visual Studio 2015：https://pan.baidu.com/s/1kF3gQv3C0OKwIPAXcB-lvQ；提取码：9e8n
VS2015 update 3：https://pan.baidu.com/s/1KdpGtIsTB4x3WaiKHhib9Q；提取码：vh5e
备注：在VS2015 update 3中安装C++编译模块。
CMake安装：pip install cmake==3.8.2
下载Dlib-19.6压缩包：http://dlib.net/files/dlib-19.6.zip
cd dlib-19.6\
mkdir build
cd build
# This is a single command. Backticks are used for line continuation
cmake -G "Visual Studio 14 2015 Win64" `
-DJPEG_INCLUDE_DIR=..\dlib\external\libjpeg `
-DJPEG_LIBRARY=..\dlib\external\libjpeg `
-DPNG_PNG_INCLUDE_DIR=..\dlib\external\libpng `
-DPNG_LIBRARY_RELEASE=..\dlib\external\libpng `
-DZLIB_INCLUDE_DIR=..\dlib\external\zlib `
-DZLIB_LIBRARY_RELEASE=..\dlib\external\zlib `
-DCMAKE_INSTALL_PREFIX=install ..
cmake --build . --config Release --target INSTALL
cd ..或者通过pip install dlib==19.16安装：
代码资源下载与运行
Github开源项目：driver-fatigue-detection-system
1. git clone https://github.com/raja434/driver-fatigue-detection-system.git
2. 下载预训练好的脸部标志检测器：dlib’s pre-trained facial landmark detector。把下载好的数据放在项目文件夹中（与alarm.wav同一目录下）。
3. 运行项目：python drowsiness detection.py
实验运行结果展示
左图为清醒-睁眼状态，EAR值为0.33；右图为疲劳-眯眼状态，EAR值为0.19，促发警报“Drowsiness Alert”并发出警报声音。
原理解析
这个简单的疲劳监测系统是通过计算眼睛纵横比（Eye Aspect Ratio）来估计疲劳程度的，源码如下：
def eye_aspect_ratio(eye):
# compute the euclidean distances between the two sets of
# vertical eye landmarks (x, y)-coordinates
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
# compute the euclidean distance between the horizon
# eye landmark (x, y)-coordinates
C = dist.euclidean(eye[0], eye[3])
# compute the eye aspect ratio
ear = (A + B) / (2.0 * C)
# return the eye aspect ratio
return ear代码中eye[0] -> eye[5]就是下图中的P1 -> P6，纵横比就是“眼睛宽度 / 眼睛高度”，这个也很好理解。
下面设置预警的阈值为0.3，即EAR < 0.3时表示眨眼（blink）了一次或者处于闭眼状态，当闭眼帧数超过48时，触发警报。
# define two constants, one for the eye aspect ratio to indicate
# blink and then a second constant for the number of consecutive
# frames the eye must be below the threshold for to set off the
# alarm
EYE_AR_THRESH = 0.3
EYE_AR_CONSEC_FRAMES = 48下面代码中把左眼和右眼的EAR值做平均，得到最终的EAR值。
# extract the left and right eye coordinates, then use the
# coordinates to compute the eye aspect ratio for both eyes
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
# average the eye aspect ratio together for both eyes
ear = (leftEAR + rightEAR) / 2.0参考资料
1. Github开源项目：https://github.com/raja434/driver-fatigue-detection-system
2. Learn OpenCV：Install Dlib on Windows
