Real-Time Face Recognition Attendance System

The Real-Time Face Recognition Attendance System is an automated solution for attendance tracking that utilizes YOLOv8 for face detection and the face_recognition library in Python for identifying individuals. This system marks attendance by matching detected faces with known images and records presence in a CSV file, making it ideal for use in schools and workplaces.

Steps to run the project:

1. Clone the repository using git clone https://github.com/anirudh-248/smart_attendance_system.git
2. Open the cloned repository in the command prompt.
3. Create a virtual environment using py -m venv env
4. Activate the virtual environment using env\Scripts\activate
5. Before installing the requirements, install dlib separately using pip install "dlib_file_path"
6. Install the requirements using pip install -r requirements.txt
7. Run the project using streamlit run image_attendance.py for image input (or) streamlit run video_attendance.py for video input.