Identity Gaurd
Facial Recognition system aimed at capturing and recognising user's face and diplaying their name.
Face Recognition Attendance System
About the Project
This project is a face recognition-based attendance system designed to detect and recognize faces in real-time using a webcam. The system marks attendance by identifying known faces from a pre-encoded dataset and records the attendance details into a CSV file.
Features
- Real-time Face Detection: Utilizes a webcam to detect faces in real-time.
- Face Recognition: Matches detected faces with a pre-encoded dataset to recognize known individuals.
- Attendance Marking: Records attendance details such as name and time into a CSV file for each recognized individual.
- Historical Data: Saves attendance data in a daily CSV file.
How It Works
- Encoding Faces: Pre-processes and encodes faces from a dataset of images.
- Face Detection: Uses the webcam to detect faces in real-time.
- Face Recognition: Compares detected faces with the encoded dataset to identify known individuals.
- Mark Attendance: Records the attendance by saving the name and time in a CSV file.
Tech Stack
- Python
- OpenCV
- Face Recognition Library
- CVZone
- Pickle
- NumPy
GitHub Repository
Explore the source code and contribute to the project on GitHub: View on GitHub