Qbicz/Android-Face-Recognition-with-Deep-Learning-Test-Framework

Face Recognition framework for Android devices can be used to test different face recognition methods.

Android Face Recognition with Deep Learning - Test Framework

Continuous integration

Acknowledgements

This app was developed by Michael Sladoje and Mike Schälchli during a bachelor thesis at the Zurich University of Applied Sciences.

Acknowledgements go to the thesis supervisors Dr. Martin Loeser, Dr. Oliver Dürr, Diego Browarnik and all the contributors of our code sources.

Code has been derived from the following sources:

• OpenCV - https://github.com/opencv/opencv
• LIBSVM - https://github.com/cjlin1/libsvm
• AndroidLibSvm - https://github.com/yctung/AndroidLibSvm
• TensorFlow - https://github.com/tensorflow/tensorflow
• facenet - davidsandberg/facenet#240
• Caffe - https://github.com/BVLC/caffe
• caffe-android-demo - https://github.com/sh1r0/caffe-android-demo
• caffe-android-lib - https://github.com/sh1r0/caffe-android-lib

Library

The core functions have been moved to a separate repository which can be used as an Android library (module).

App architecture

Usage

Clone

git clone https://github.com/Qualeams/Android-Face-Recognition-with-Deep-Learning-Test-Framework.git

Compilation

APK - Package

The app can be downloaded directly from the Google Play Store - Face Recognition.

Android SDK - Java

The source can be compiled using Android Studio (common gradle scripts).

User manual

The user manual can be found here