face-recognition-test

• Test project to create images, train and recognize faces in video using Haar Cascade face and eye classifiers.

Prerequisites

• Python 3.7

Install (Windows)

1. Create virtual environment:

   python -m venv venv
   

2. Activate virtual environment:

   venv\Scripts\activate
   venv\Scripts\deactivate :: to deactivate
   

3. Install packages from requirements:

   pip install -r requirements.txt
   

Usage

• From the inner face-recognition-test directory

• Creating image data can be done in 2 ways:

  1. Create image data via recording

     • Run command

       python create-data.py
       

     • This will try to capture your face and eyes from camera and will create images in the ./data/face_data/[DIRECTORY_NAME] directory.
     • DIRECTORY_NAME is found in the script.
     • [R] to record and [Q] to quit.

  2. Extract image data from existing images

     • Run command

       python extract-images.py
       

     • This will get faces from images in ./data/images/ and extract it to ./data/face_data directory. Refer to Directories section.

• Train the image data

  • Run command to train the images in the faces folder and create the trained data file

    python train-data.py
    

• Run the face recognition program

  python face-recognition.py
  

  • [Q] to quit.

Directories

• Root directory of images ./data/images/[name_of_person] (must be inside the folder with the identifier's name)
• Root directory of created or extracted images to train: ./data/images/face_data

Tools used

• VSCode
• Python v3.7
• OpenCV