Facial recognition on offline images I want to do facial recognition on wide varieties of images captured at various ages of my family members. Below are some of the questions I have.


If a person uses glasses of different types, do I need to feed images with each glasses type in the training dataset ? What if the eyes are not visible after wearing sunglasses. ?
There are many pics which ranges from childhood to current age of approx 30. Do I need to train my model with pics of various ages to get good accuracy ?
Do I need to align the images of train dataset for better accuracy ?
Do I need to crop the background of the images in the training dataset just to keep the faces OR background doesn't matter ?


The idea behind my requirement is to scan through all the images on my hard disk (around 100 GB images) and classify the images in different folders for each person. I know similar thing is done on iphone and other mobile phones but I wanted to do it for the offline images stored on my external hard disk.

I was exploring facenet model from google, opencv face recognition. But stuck in the first step of dataset creation.
Glasses matter. So you will need those photos in the training dataset.
Yes. You will need to feed images of all ages for multiple people. This will help the model generalize how people age
Alignment should not matter
Background should not matter