Face Recognition Attendance System using OpenCV and Face_Recognition Library

This program recognizes faces from the live video feed and marks the attendance of recognized faces in a CSV file. The face recognition algorithm is implemented using the 'face_recognition' library in Python.

Requirements

• Python 3.x
• OpenCV (pip install opencv-python)
• Face_Recognition (pip install face-recognition)
• numpy (pip install numpy)

Usage

1. Store images of people to be recognized in a folder named 'ImagesAttendance'.
2. Run the program. It opens the webcam and starts recognizing faces.
3. When a recognized face is detected, the program marks the attendance of that person in a CSV file named 'CEO_Attendance.csv'.

Functionality

• find_encodings(images): This function takes a list of images as input and returns the facial encodings of each image. It uses the face_recognition library to detect facial features and generate the encodings.
• mark_attendance(name): This function marks the attendance of the person whose face is recognised. It reads from and writes to a CSV file named 'CEO_Attendance.csv'. If the person is not already marked present in the CSV file, it appends a new line with the person's name and current timestamp.

How it works

1. The program reads the images from the 'ImagesAttendance' folder and generates facial encodings for each image using the find_encodings() function.
2. It then opens the webcam and starts reading frames.
3. For each frame, the program detects the location of all faces using the face_recognition library.
4. It then compares the facial encodings of all detected faces with the encodings generated earlier from the images in the 'ImagesAttendance' folder using the compare_faces() function.
5. If a match is found, the person's name is retrieved from the list of image file names using the classNames list.
6. A rectangle is drawn around the detected face, and the person's name is displayed above the rectangle.
7. The mark_attendance() function is called to mark the attendance of the recognized person in the 'CEO_Attendance.csv' file.

Note:

The accuracy of the face recognition algorithm depends on the quality of the images stored in the 'ImagesAttendance' folder and the lighting conditions during recognition.