Face Recognition Attendance System

Version: v1.0

This is the first version of the AI-powered Face Recognition Attendance System. It captures faces in real-time, matches them with stored identities, and marks attendance automatically in an Excel file.

Features

• ✅ Real-time face detection using OpenCV
• ✅ Face recognition with high accuracy
• ✅ Automatic attendance marking in an Excel file

Important Points

• Visual Studio C++ Build Tools: Required for installing dlib, which is essential for face recognition.
• Conda Environment: The setup is done using a Conda environment with Python installed(Python 3.11.11).

Installation & Setup

Step 1: Clone the Repository

git clone https://github.com/Raghulskr12/Smart-Face-Attendance.git  
cd Smart-Face-Attendance  

Step 2: Set Up a Conda Environment

It is recommended to use a virtual environment to manage dependencies.

# Create and activate a new Conda environment
conda create --name face-attendance python=3.9 -y  
conda activate face-attendance  

Step 3: Install Dependencies

All required dependencies are listed in the requirements file. Install them using:

pip install -r requirements/requirements.txt  

How to Use

Add Photos for Training:

• Place training images inside the Training_images folder.
• Each image should be named after the person's identity (e.g., Raghul.jpg).
• The more images you add, the better the accuracy.

Run the Face Recognition System:

python main.py

Adjust Threshold for Better Accuracy:

• Modify the face distance threshold in the script (main.py) as needed.
• Lower values increase strictness, while higher values make recognition more flexible.

Attendance Output:

• The system will detect and recognize faces, marking attendance in attendance.xlsx.

Contribute & Support

Feel free to fork this repository, contribute, and suggest new features.

If you find this project useful, consider giving it a ⭐ on GitHub.