Facial Recognition Attendance System
Project Overview
This project is a real-time attendance system using facial recognition technology. It identifies and records attendance for known faces from a live video feed, with separate logs for unknown faces.
Key Features Real-Time Face Recognition: Identifies faces from a live webcam feed in real-time. Attendance Logging: Logs recognized faces along with the time of attendance in attendance.csv. Unknown Face Logging: Logs unidentified faces in unknown.csv for future reference. Attendance Folders: Automatically creates a folder with the current date to store attendance records. Dynamic Face Addition: Easily add new faces to the system by placing images in the Faces folder.
Project Outputs Attendance Records: A CSV file named attendance.csv containing the names and times of recognized attendees. Unknown Face Logs: A CSV file named unknown.csv containing entries for faces that were not recognized. Date-Based Storage: Each day’s attendance data is saved in a separate folder named with the current date.
Visualizations Name Overlays: Each detected face is labeled with its corresponding name or marked as "Unknown" in the video feed. Bounding Box: Displays a rectangular box around detected faces to indicate successful face recognition.
Benefits Automation: Automates attendance-taking, saving time and reducing manual effort. Accuracy: Ensures accurate attendance recording with facial recognition. Security: Logs unknown faces for review, enhancing system security.
Usage Instructions Prerequisites: -->Install Python 3.7 or higher. -->Ensure cmake is installed on your system.
Data Preparation: -->Create a folder named Faces in the project directory. -->Add face images to the Faces folder, with the image name matching the person’s name (e.g., Rudraksh.jpg).
Run the System: -->Execute the following command to start the attendance system: face_regocnition_system.py OR by click run the py file. Stopping the System: -->Press q to stop the system and save attendance records.
Contributions Contributions are welcome! Here's how you can contribute:
Fork the Repository: Create a fork to make changes without affecting the main repository. Create a Branch: Create a new branch for each feature or bug fix. Submit a Pull Request: Once changes are complete, submit a pull request with a clear description. Coding Standards: Follow PEP 8 for Python code style. Documentation: Update the documentation if your changes affect project usage.
Additional Notes Data Privacy: Ensure compliance with privacy laws and policies when using personal face images. Customization: The project can be extended or modified to meet specific business or personal requirements. Collaboration: We encourage collaboration to improve and expand the project. By leveraging this facial recognition attendance system, organizations can improve attendance management, enhance accuracy, and streamline operations.
Thankyou. Enjoy Coding! -Rudraksh Gupta