You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Here no training is done. Actually, they have used a pre-trained FaceNet model which is designed to learn how to distinguish between two faces in Euclidean Space. The main idea behind this is Siamese Network and Triplet Loss
So now when you input a face image it produces a 128D embedding(vector) that represents that particular face. You can repeat it same for the other images and find the Euclidean distance between them it will give you the closeness score.
Hi David,I was wondering if you could explain the code to me and how the training works.
Thanks
The text was updated successfully, but these errors were encountered: