Pytorch-Face-recongition-state-of-the-art-Qmul-surveface-

Implementation state of the art for face recognition algorithm.

In my repos, I use timm module to quickly create model ( efficienet, resnet ...) and reference some notebook from kaggle.

Implementation some SOTA algorithm for recognition: Arcface, adaptive arcface, adacos, additive margin,...

Optimizer: SAM optimizer

We only config on class CFG in file train.py:

  path_train: train struture = train/ class1
                                    / class2
                                    ....


  path_valid: train struture = valid/ class1
                                    / class2
                                    ....
  and some config for optimizer , loss, ...

How to run repos?

  - pip install -r requirements.txt
  - python train.py

tks1998/Pytorch-Face-recongition-state-of-the-art-Qmul-surveface-

Pytorch-Face-recongition-state-of-the-art-Qmul-surveface-