pyfacy — Face Recognition and Face Clustering part-II

This blog only talk about Face Clustering…

Face Cluster

The Face Clustering is unsupervised learning concept. Collected the faces and apply the cluster to grouping the faces and store to directory with unique directory name.

Face Encodings

The face encodings concept used in the pyfacy- face clustering. I have collected the encodings points from face image and apply to cluster.

Cluster Algorithm

I have used the DBSCAN cluster algorithm. DBSCAN — Density-Based Spatial Clustering of Applications with Noise. Finds core samples of high density and expands clusters from them. Good for data which contains clusters of similar density.

Installation Steps and Examples:

Installation Steps:

pip install pyfacy

If you have any problem when install pyfacy package, please use the installation steps in github repo.

Examples:

Run the pyfacy-cluster.py file and store the faces to Output directory
pyfacy-cluster.py

from pyfacy import face_clust
mdl = face_clust.Face_Clust_Algorithm('./Dataset')
mdl.load_faces()
mdl.save_faces('./Output')

OUTPUT:

Please use this github link for pyfacy cluster example.

Ref:

Part-I : pyfacy-Face Recogntion details here