facetorch VS deepface

facetorch:

You can use embeddings produced by facetorch library to represent faces. The next step is to build a database of faces and face embedding similarity engine. https://github.com/tomas-gajarsky/facetorch

facetorch is a Python library for analysing faces using TorchScript

You might also want to categorize using either mediapose's holistic model which includes the face mesh or maybe something that gauges emotion like this: https://github.com/serengil/deepface

This is another one I tried but requires programming knowledge. https://github.com/serengil/deepface

It must be a matter of time before we have this, we have so many library's that can detect a face expression. For example: https://github.com/serengil/deepface

I bought a On1 license, but as you point out, it has no facial recognition nor any plans to add it. That also means it has no concept of face regions as implemented in XMP, so that cannot be retrofitted by running face recognition externally, e.g. using an open-source solution like Deepface.

deepface - newer version which has multiple face detectors in it you can mess with, dlib included. Also does face recognition.

If you're looking for models / planning to write some code yourself: Have a look at ArcFace for recognition and RetinaFace for face detection by Insightface. DeepFace repository might also be worth a try.

DeepFace: https://github.com/serengil/deepface

DeepFace utilizes a collection of different face detection models listed here: models = ["VGG-Face", "Facenet", "Facenet512", "OpenFace", "DeepFace", "DeepID", "ArcFace", "Dlib", "SFace"]