Unsupervised face clustering using MTCnn face detection, Facenet 512d embeddings. Also through Dlib frontal face detection and then ReSNet 128d embeddings.
Given some images containing human faces, this model is able to detect faces and implement unsupervised clustering to group same faces into one folder. It is capable of using various clustering algorithms such as Chinese whispers graph, Kmeans and others can also be added.