Face-Attendance System for Classroom

This project is a face recognition-based attendance system designed for classrooms. It is built using Python, OpenCV, and the face_recognition library to streamline attendance tracking efficiently.

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Features

• Student Dataset Creation:
  • Capture and store images of students with their Roll Numbers.
  • Save student data in JSON format for easy management.
• Face Recognition:
  • Real-time face recognition using the face_recognition library.
• Gesture-Based Validation:
  • Prevents false attendance using gesture recognition.
  • Simple gestures like stone, paper, and scissors are used in random order to confirm attendance.
• Attendance Logging:
  • Attendance is marked and stored in Class_Name/attendance.csv.

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Requirements

• Python 3.10
• OpenCV
• Libraries mentioned in requirements.txt

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Setup Instructions

1. Clone the Repository

git clone https://github.com/Nishant2009/Face-Attendance
cd Face-Attendance

2. Install Dependencies

pip install -r requirements.txt

3. Prepare the Dataset

• Images:
  • Store images of students in the Class_Name/New_Faces folder.
  • Ensure each image file is named with the Roll Number of the respective student.
• Attendance File:
  • Populate the Class_Name/attendance.csv file with the following format:

    Registration No.,Name
    1, Name1
    2, Name2
    

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Usage Instructions

Running the Program

1. Execute the main script:

   python main.py

2. Follow the on-screen instructions:
   • Show faces to the camera to mark attendance.
   • Perform the prompted gestures to confirm attendance.
3. Press q to exit the program.

Notes

• Ensure the camera is functional and accessible.
• The program has been tested on Windows 11 with Python 3.10. Compatibility with other platforms may vary.

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Key Functionalities

Dataset Creation

• Automatically encodes faces from the images stored in the dataset folder (Class_Name/New_Faces).
• Saves face encodings and Roll Numbers in a JSON file for quick lookup.

Real-Time Recognition

• Uses the camera feed to detect and recognize faces.
• Matches detected faces with the stored dataset to identify students.

Gesture-Based Validation

• Implements a rock-paper-scissors gesture game to prevent misuse (e.g., showing photos for attendance).
• Randomly prompts gestures and validates the input before marking attendance.

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License

This project is licensed under the MIT License. See the LICENSE file for more details.

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Contact

For any issues or suggestions, please raise an issue in the GitHub repository.