Class Vision: Face Recognition Attendance System

A simple and intuitive attendance management system that uses facial recognition to automatically track and record student attendance.

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Features

• User-Friendly Interface: A clean and simple UI for easy navigation.
• Face Registration: Easily enroll new students by capturing their facial images.
• AI-Powered Training: Uses OpenCV to train a recognition model based on the registered faces.
• Automatic Attendance: Marks attendance automatically by recognizing faces from a live camera feed.
• Attendance Tracking: Records attendance in organized CSV files, categorized by subject.
• View Records: Allows users to view the attendance records in a clean, tabular format.

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Usage

There are two ways to run this application:

1. For End-Users (Running the Executable)

This is the simplest way to use the application without any setup.

1. Download the ClassVision.exe file from the project's Releases page.
2. Run the executable file. The application is pre-trained and ready to use.
3. Use the "Take Attendance" feature to start recognizing faces.

Note: The pre-built executable comes with a pre-trained model. The "Register" and "Train" features will not permanently save new faces in the executable version.

2. For Developers (Running from Source)

This method allows you to run, modify, and retrain the application.

1. Clone the Repository:

   git clone https://github.com/your-username/Attendance-Management-system-using-face-recognition.git
   cd Attendance-Management-system-using-face-recognition

2. Install Dependencies: Make sure you have Python 3.9+ installed, then run:

   pip install -r requirements.txt

3. Run the Application:

   python attendance.py

4. Train Your Own Model:

   • Use the "Register a new student" button to capture images of a new person.
   • Click the "Train Image" button to build the recognition model (Trainner.yml).
   • Once training is complete, you can use the "Take Attendance" feature.

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Building from Source

To create your own standalone executable (.exe) after making changes or training with new faces:

1. Ensure the Model is Trained: Follow step 4 above to ensure the Trainner.yml file exists.

2. Run PyInstaller: Use the following command to bundle the application and all its assets into a single executable file. The result will be in the dist folder.

   pyinstaller --noconfirm --onefile --windowed --icon="AMS.ico" --add-data="AMS.ico;." --add-data="haarcascade_frontalface_default.xml;." --add-data="haarcascade_frontalface_alt.xml;." --add-data="StudentDetails;StudentDetails" --add-data="UI_Image;UI_Image" --add-data="TrainingImageLabel;TrainingImageLabel" attendance.py