faceattend 0.0.5

An attendance system using face recognition

Face Attend

Whats working?

• Adding face data of a person to the database
• Detect face of known person using video feed
• Mark attendance of a valid person when detected
• Generating a csv file with attendance for a particalar date or a particular employee

Todo

• Further improve the face recognition model

Instructions 📝

• Create a virtual environment: python3 -m venv .venv

• Activate the virtual environment: source .venv/bin/activate or .\.venv\Scripts\Activate.ps1

• On Windows make sure to do set this environment variable using powershell [Environment]::SetEnvironmentVariable("PYTHONUTF8", "1", "User")

• Install the package: pip install faceattend

Windows specific issues

• Creating virtual environments see here
  
• For issues with installation of the face-recognition package see here

Database setup 🛢

Create the database

• Import the create_database() function from create_database module
  from faceattend.create_datebase import create_database

• Then just use the create_database() function to create the database create_database()

• When database is successfully created it displays
  Database created!

Add valid faces in database

• Import the Face class from face module
  from faceattend.face import Face

• Now use the Face class's add_face method to add face data and name of the person
  Face.add_face("Person's Name","Path to the Person's image file")

• If the face was added successfully it displays
  Face Added

Generating CSV file

For a particular date

• Import the Attendance class from attendance module
  from faceattend.attendance import Attendance
• Now use Attendance class's generate_csv_date() function
  Attendance.generate_csv_date("sample_date")

For a particular employee

• Use Attendance class's generate_csv_emp() function
  Attendance.generate_csv_emp("emp_id")

If CSV file was generated it displays

CSV file generated!

How to run?

• Import the detect_face() function from the detect module
  from faceattend.detect import detect_face
• Then just call the detect_face() function
  detect_face()