FRAS - Face Recognition Attendance System

FRAS is a Server-Node based small attendance system using face recognition.

This application is a small use case of the face_recognition library which is based on dlib.

Requirements:

Make sure you have the necessary packages by doing this:

pip install -r requirements.txt 

Note: please refer to dlib site for instructions on how to compile it.

How to use:

First, you need to have a folder that contains either video files or image folders of the faces you want to encode, so you can use them in the application, Like this for example:

C:\USERS\ZERAX\DESKTOP\FRAS\TRAIN
│   6669.mp4
│
└───6669
        0.jpeg
        1.jpeg
        10.jpeg
        100.jpeg

Then you can use Encode.py script with -d [train_directory] parameter taking the train directory that include the files you want to encode, and -v or -i parameters for videos and images respectivley (you may use both of them).

This will create an encoding file called enc.dat file containing the encodings (you may change the name of the file by adding -o [OUT] parameter but then you will need to modify the MainDialog.py script to account for that).

NOTE: There are other useful options in Encode.py script you can find them in the -h help parameter.

Here's an example:

python Encode.py -d Train -i -v

After that, you can run the main programe by calling Main.py.

The first run of the application will require you to set up a config file, You will be welcomed by the configuration window where you can add an ip camera, an internal camera, or a node.

Add Camera: will add 3 fileds:

• Camera Name: display name and will be used as the folder name where the logs will be saved.
• Camera IP: accept an ip, or the number of the camera.
• Arduino IP: this filed is optional, if you want to use it you need and arduino connected to the network and accept http requests, the application will send it a request whenever a face gets recognized.

Add Node: will add 2 fields:

• Node Name: display name and will be used as the folder name where the logs will be saved.
• Node Port: used by the server to listen on (each node must have a unique port).

NOTE: Node is reffered to a small computer with a camera like raspberry pi for example running the Node.py script.

The rest of documentation is under construction but if you want to try, the application is self-explanatory with hints for the ambigous control options.

Licence:

MIT