In this README is explained how to get the project running. In the wiki is eplained how the project works.

With this package it's possible to do realtime face clustering! With this project it's possible to do face clustering using chinese whisps clustering.

Chinese Whispers

In this chapter is explained how to get the project up and running. The project is tested on Ubuntu 16.04.

There are a few packages you'll need to run the code:

• OpenCV
• dlib
• numpy
• pillow

If you have a NVIDIA GPU that's CUDA compatible, you can install dlib with CUDA support. In this way it's possible to run dlib on GPU, which probably will increase performance. To compile dlib with CUDA support you'll need to install the following packages:

• CUDA
• cuDNN

The project is tested with CUDA 10.1. But you'll need to find out which version of CUDA is compatible with your system, information about this can be found here. Important is that the CUDA and cuDNN versions are matching.

To install the project on your own computer you just need to clone this repository in your preffered folder.

git clone https://github.com/RemcoKuijpers/face_clustering.git

You'll need to change the paths in the code, so they will match with your system. You also need two empty directories in the face_clustering repository. One is named 'dataset' and the other one is named 'output_folder'.

To run the project you'll need to run two programs. The fisrt program that's need to run first is the faceRecognition.py file. If you don't have a "dataset" folder and a "output_folder", create them.

python face_recognition/faceRecognition.py

This codes fills the database for the clustering. The code uses OpenCV haarcascades to detect faces. When a face is detected it takes images and saves it into the database.

To use the Chinese Whispers clustering method, you'll need to run the runChineseWhispersClustering.sh shell script.

./runChineseWhispersClustering.sh

This program saves one image of each unique face that's detected, in the output_folder folder.