ArchLinux 安装 howdy 实现人脸识别验证

安装 howdy

使用 yay 或者其它包管理工具从 aur 安装 howdy

yay -Syu howdy

找到本机用于识别的摄像头

• 可以通过 vlc 等工具找到本机的前置摄像头

  • 媒体 / Open Capture device / 捕获设备 / Advanced options / 视频捕获设备 中选择对应的设备

  • 点击确定，然后点击播放

  • 重复以上步骤，直到确定前置摄像头的设备位置名称

• 或者通过命令sudo pacman -S v4l-utils安装v4l-utils，然后使用命令v4l2-ctl --list-devices来找到本机所有的媒体设备，一般来说第一个/dev/video0就是你要找的目标

编辑 howdy 配置文件

对应配置文件 /usr/lib/security/howdy/config.ini，以下有中文注释的地方是我认为比较有用的配置选项

# Howdy config file
# Press CTRL + X to save in the nano editor

[core]
# Print that face detection is being attempted
detection_notice = false

# Do not print anything when a face verification succeeds
no_confirmation = false

# When a user without a known face model tries to use this script, don't
# show an error but fail silently
suppress_unknown = false

# Disable Howdy in remote shells
ignore_ssh = true

# Disable Howdy if lid is closed
ignore_closed_lid = true

# Disable howdy in the PAM
# The howdy command will still function
disabled = false

# Use CNN instead of HOG
# CNN model is much more accurate than the HOG based model, but takes much more
# computational power to run, and is meant to be executed on a GPU to attain reasonable speed.
use_cnn = false

[video]
# The certainty of the detected face belonging to the user of the account
# On a scale from 1 to 10, values above 5 are not recommended
# Lower is better
# 检测的确定性，数值越低准确度越高，但是识别率越低
certainty = 5

# The number of seconds to search before timing out
# 认证超时时间
timeout = 10

# The path of the device to capture frames from
# Should be set automatically by an installer if your distro has one
# 前置摄像头位置
device_path = /dev/video0

# Scale down the video feed to this maximum height
# Speeds up face recognition but can make it less precise
max_height = 320

# Set the camera input profile to this width and height
# The largest profile will be used if set to -1
# Automatically ignored if not a valid profile
frame_width = -1
frame_height = -1

# Because of flashing IR emitters, some frames can be completely unlit
# Skip the frame if the lowest 1/8 of the histogram is above this percentage
# of the total
# The lower this setting is, the more dark frames are ignored
# 在黑暗环境下，值越低准确度越高，识别率越低
dark_threshold = 100

# The recorder to use. Can be either opencv (default), ffmpeg or pyv4l2.
# Switching from the default opencv to ffmpeg can help with grayscale issues.
recording_plugin = opencv

# Video format used by ffmpeg. Options include vfwcap or v4l2.
# FFMPEG only.
device_format = v4l2

# Force the use of Motion JPEG when decoding frames, fixes issues with YUYV
# raw frame decoding.
# OPENCV only.
force_mjpeg = false

# Specify exposure value explicitly. This disables autoexposure.
# Use qv4l2 to determine an appropriate value.
# OPENCV only.
exposure = -1

[snapshots]
# Capture snapshots of failed login attempts and save them to disk with metadata
# Snapshots are saved to the "snapshots" folder
# 设置识别用户失败时拍照保存照片
capture_failed = true

# Do the same as the option above but for successful attempts
# 取消识别用户成功时拍照保存照片
capture_successful = false

[debug]
# Show a short but detailed diagnostic report in console
# Enabling this can cause some UI apps to fail, only enable it to debug
end_report = false

修改完配置文件后，可以使用sudo howdy test命令来检验摄像头是否能够正常工作，如果检测界面能够打开并识别到人脸，这说明摄像头配置成功

这里有可能会出现ModuleNotFoundError: No module named 'cv2'的错误，这是缺少python-opencv这个依赖，可以通过使用sudo pacman -S python-opencv来安装依赖

配置认证选项

想要实现对应功能的人脸识别认证，可以在/etc/pam.d文件夹下修改对应的配置文件，在配置文件的首行加入以下配置：auth sufficient pam_python.so /lib/security/howdy/pam.py（针对 howdy 2.x）

一般来说只需要修改桌面环境相关的配置文件，例如在/etc/pam.d/kde首行加入对应配置可以实现被 kde 管理的多个认证选项，包括登录、解锁等

如果需要精准的控制，例如登录时的人脸识别，可以修改/etc/pam.d/system-local-login配置文件；想要在使用 sudo 时实现人脸识别可以修改/etc/pam.d/sudo配置文件等等

此外，一般来说还需要将/usr/lib/security/howdy文件夹下的文件权限更改为 755 以授权普通用户的执行权限，否则 kde 锁屏解锁等功能可能无法使用：sudo chmod -R 755 /usr/lib/security/howdy

添加人脸识别凭证

使用sudo howdy add命令来添加人脸，可以添加多个凭证信息，以达到更好的识别效果

注意事项

• 在进行人脸识别时可能会出现警告，临时的解决办法是修改opencv的日志级别，添加一个环境变量OPENCV_LOG_LEVEL=ERROR：可以在/etc/profile文件底部添加export OPENCV_LOG_LEVEL=ERROR或者在/etc/environment文件中添加OPENCV_LOG_LEVEL=ERROR，注意需要重新启动计算机
• 出现ModuleNotFoundError: No module named 'cv2'的错误，这是缺少python-opencv这个依赖，可以通过使用sudo pacman -S python-opencv来安装依赖