Hello guys!

I’ve just started working on a small project that involves analyzing a web cam generated image and compare it to images on a dataset folder to try and find a match.

There are some pre-trained models out there, which enables one-shot learning (like this GitHub for example: https://github.com/mohitwildbeast/Facial-Recognition-Using-FaceNet-Siamese-One-Shot-Learning)

However, it is not precise as I wanted, and I don’t really know why.

I was looking the FaceNet model by David Sandberg (https://github.com/davidsandberg/facenet) and it seems promising, however I don’t know how to use it for my case.

So, I was wondering if you guys have any advice for me, any link, that might help me!
The system should be simple, is just a proof of concept, so as long as the algorithm can compare the face it is detecting on the webcam, for example, to one on a images folder and return the embedded distance (distance between the faces, where smaller are similar faces and bigger otherwise).

I’m not sure if I was clear, as it is my first time writing on this sub.

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Thank you all in advance.