A deep learning library that makes face recognition efficient and effective

Related tags

Deep LearningArcFace
Overview

Distributed Arcface Training in Pytorch

This is a deep learning library that makes face recognition efficient, and effective, which can train tens of millions identity on a single server.

Requirements

How to Training

To train a model, run train.py with the path to the configs:

python train.py configs/webface_mbf

Model Zoo

inference

python3 inference_compare.py --img1 input/sajjad_0.jpg --img2 input/sajjad_1.jpg

Test

We tested many versions of PyTorch. Please create an issue if you are having trouble.

  • torch 1.6.0
  • torch 1.7.1
  • torch 1.8.0
  • torch 1.9.0

Citation

@inproceedings{deng2019arcface,
  title={Arcface: Additive angular margin loss for deep face recognition},
  author={Deng, Jiankang and Guo, Jia and Xue, Niannan and Zafeiriou, Stefanos},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={4690--4699},
  year={2019}
}
@inproceedings{an2020partical_fc,
  title={Partial FC: Training 10 Million Identities on a Single Machine},
  author={An, Xiang and Zhu, Xuhan and Xiao, Yang and Wu, Lan and Zhang, Ming and Gao, Yuan and Qin, Bin and
  Zhang, Debing and Fu Ying},
  booktitle={Arxiv 2010.05222},
  year={2020}
}
Owner
Sajjad Aemmi
Machine Learning Engineer - Master of AI from Ferdowsi University of Mashhad - Teacher at Sadjad University - WebDeveloper - Graphist
Sajjad Aemmi
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