👩 Face AI

We will use Face Detection, Face Recognition and some other related offline AI technologies to build our open-source, cross-platform app. This will provide security without the need of an active Internet connection.

Overview: The app uses KivyMD and Kivy mainly for the UI. The app uses NumPy, OpenCV & OnnxRuntime as the logic backbone.

🤔 Why would you choose our app? (Features)

👉 Offline Face Detection and Recognition.
👉 Store secret files which can only be unlocked by your face. On non-android platform, files will be encrypted.
👉 Cross-platform and Open Source.

💰 Sponsor Me

You can buy me a coffee via this link or tap on below image. Thank you 🙏.

📽️ Demo

To be added later...

🖧 Our Scematic Architecture

Model	Source Link	Size	Remarks
det_10g.onnx	buffalo_l	17MB	Face Detection
arc.onnx	arcface-onnx	137MB	Face Recognition

🧑‍💻 Quickstart Guide

📱 Download & Run the Android App

You can check the Releases and downlaod the latest version of the android app on your phone.

If you use the Download button from the app, you can save the images in one of the mentioned folders: Downloads, Pictures and videos in Downloads, Movies, Videos due android file access restrictions on Android 11+.

💻 Download & Run the Windows or Linux App

You can check the Releases and downlaod the latest version of the app on your Linux or Windows platform. The Linux app has no extension, you may need to change the permission of the file to run it. The Windows app will have an exe extension, just double click & run it (You may need to create an exception for Antivirus if there is any detection).

🐍 Run with Python

1. Clone the repo

git clone https://github.com/daslearning-org/face-ai.git

2. Run the application

cd face-ai/app
pip install -r requirements.txt # virtual environment is recommended
python main.py

🦾 Build your own App

The Kivy project has a great tool named Buildozer which can make mobile apps for Android & iOS

📱 Build Android App

A Linux environment is recommended for the app development. If you are on Windows, you may use WSL or any Virtual Machine.

# add the python repository
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt update

# install all dependencies.
sudo apt install -y ant autoconf automake ccache cmake g++ gcc lbzip2 libffi-dev libltdl-dev libtool libssl-dev make openjdk-17-jdk patch patchelf pkg-config unzip wget zip git python3.14 python3.14-venv python3.14-dev # python3-dev python3-pip (if required)

# optionally you may check the java installation with below commands
java -version
javac -version

# install python modules
git clone https://github.com/daslearning-org/face-ai.git
cd face-ai/app
python3.11 -m venv .env # create python virtual environment
source .env/bin/activate
pip install -r req_android.txt

# build the android apk
buildozer android debug # this may take a good amount of time for the first time & will generate the apk in the bin directory

🖳 Build Computer Application (Windows / Linux / MacOS)

A Python virtual environment is recommended and please follow the same steps from above till the pip module installations (do not require buildozer for desktop apps). It builds a native app depending on the OS type i.e. .exe if you are running PyInstaller from a Windows machine. Build computer apps from docker image for any OS type.

# install pyinstaller
pip install pyinstaller

# generate the spec file <<OPTIONAL>>
pyinstaller --name "dlDesktop" --windowed --onefile main.py # optional as it is already created in the repo

# then update the spec file as needed
# then build your app which will be native to the OS i.e. Linux or Windows or MAC
pyinstaller dlDesktop.spec