Facial Recognition App

Project Structure

.
└── Facial-Recognition-App/
    ├── facial_recognition/
    │   ├── __init__.py
    │   ├── _utils_.py
    │   ├── detect.py
    │   ├── align.py
    │   ├── represent.py
    │   └── identify.py
    ├── webapp/
    │   ├── app.py
    │   ├── static
    │   │   ├── app.js
    │   │   └── styles.css
    │   └── templates
    │       └── index.html
    ├── scripts
    │   ├── cameras.py
    │   ├── preprocess_images.py
    │   ├── demo1.py
    │   └── demo2.py
    ├── data
    │   ├── raw
    │   └── processed
    │   └── vectordb
    ├── models
    │   └── dlib_face_recognition_resnet_model_v1.dat
    ├── Dockerfile
    ├── docker-compose.yaml
    ├── mkdocs.yaml
    ├── pyproject.toml
    └── README.md

Documentation

For technical documentation of code under facial_recognition please refer to github.io. All other code make use of facial_recognition and has internal documentation explaining how it uses it.

Getting Started

Install Basic Requirements

You'll need Python 3.9 and above, and GIT. On Windows, the best way is via the Python website and GIT website. On other operating systems command line options are the easiest:

MacOs:

brew install python git

Linux:

sudo apt install python3 python-is-python3 git

It is recommended that you open the folder where this repository will be cloned with an IDE like VSCode or PyCharm.

Create Environment

First you need to clone this repository, and then create the environment. You can use pyenv, conda or whichever one you want but for this example we are using venv which is included in python.

cd /path/where/you/want/to/clone/repo
git clone https://github.com/smasis001/Facial-Recognition-App.git
python -m venv .venv

Then for managing the packages, this repository comes with pyproject.toml for poetry, but you can use requirements.txt and pip. For poetry, this is how it goes:

pip install poetry
python -m poetry env use .venv/bin/python
python -m poetry install
source .venv/bin/activate

For installing the packages with pip, you must activate the virtual enviroment first.

source .venv/bin/activate
pip install -r requirements.txt

Download Raw Data (optional)

The Vector database (/data/vectordb) has facial biometrics for celebrity faces which was a sample of 5% of the images from here. If you want the raw sources used for the vector DB or to rebuild the vector DB with your own data, get it from here and unzip it into the data/raw folder.

Rebuild Vector DB (optional)

If you want to process the raw images and store corresponding embeddings into Vector DB, run this:

python scripts/preproces_images.py

It assumes that the names of the folders under data/raw are the names of the people. There can only be one face per image in these folders for it to work.

Run Web App (locally)

To see the facial recognition system work via browser, run:

python webapp/app.py

and then go to http://127.0.0.1/ preferably in a Chrome or Chromium-based browser (Edge, Opera, etc). It does work in Safari and some Firefox versions but there's no guarantees.

When the page opens please camera permissions, and press ctrl-C to stop the webapp in your command line.

Run Desktop App (locally)

To demo face detection with Python, run:

python scripts/demo1.py

And for the facial recognition demo:

python scripts/demo2.py

Press esc to close the windows. If for some reason it's using the wrong camera, run:

python scripts/cameras.py

and arrow left and right through your cameras till you find the one you prefer to use. Take note of the camera number. Then, open scripts/demo1.py and scripts/demo2.py and change the line that says CAMERA_ID = 0 for the number you prefer.