Technology Used

⮚ We are using our core platform as python which is one of the best and easiest programming languages.

⮚ We used supporting editors such as PyCharm. It is one of the best editors for most of the programming processes.

Open CV:

      ⮚ This is a library used for image recognition, image processing and video capture. Thus, the main function of the 
         system i.e., face detection is carried out using this library.

Pillow:

     ⮚ This module collectively helps in making GUI. The interface that we see on running the program is built with help 
        of this module.

Face-recognition:

    ⮚ This module is mainly used to detect the various kinds of faces. This module compares and identifies the 
       faces using in-built python libraries.

Wheel:

    ⮚ It allow for faster installation in the package distribution process. Whenever we install anything in python wheel 
       makes its faster and efficient
       It inhance the speed of the package installation of package.

Dlib:

    ⮚ This machine learning package is used to detect the faces. It functions same as that of OpenCV and helps in image 
       processing.

NumPy:

    ⮚ This module is used for working in domain of linear algebra, Fourier transformations and matrices. It also helps in 
       working with multi-directional arrays.

os:

    ⮚ This is a basic module used for interacting with operating system. It simply connects the user and computer and thus, 
       conveys our commands to computer on which results are displayed.

harrcascade:

    ⮚ This is another element used for face detection process. It is used for training of positive and negative images 
       which plays major role in face differentiating process.

detectMultiScale:

    ⮚ When any face is detected in the image provided to system or in the webcam, we see a rectangle around 
       the face. Thus, this module returns that rectangle with coordinates(x,y,w,h).