cavaface: A Pytorch Training Framework for Deep Face Recognition

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By Yaobin Li and Liying Chi

Introduction

This repo provides a high-performance distribute parallel training framework for face recognition with pytorch, including various backbones (e.g., ResNet, IR, IR-SE, ResNeXt, AttentionNet-IR-SE, ResNeSt, HRNet, etc.), various losses (e.g., Softmax, Focal, SphereFace, CosFace, AmSoftmax, ArcFace, ArcNegFace, CurricularFace, Li-Arcface, QAMFace, etc.), various data augmentation(e.g., RandomErasing, Mixup, RandAugment, Cutout, CutMix, etc.) and bags of tricks for improving performance (e.g., FP16 training(apex), Label smooth, LR warmup, etc)

Features

(click to collapse)

• Backbone
  • ResNet(IR-SE)
  • ResNeXt
  • DenseNet
  • MobileFaceNet
  • MobileNetV3
  • EfficientNet
  • ProxylessNas
  • GhostNet
  • AttentionNet-IRSE
  • ResNeSt
  • ReXNet
  • MobileNetV2
  • MobileNeXt
• Attention Module
  • SE
  • CBAM
  • ECA
  • GCT
• Loss
  • Softmax
  • SphereFace
  • AMSoftmax
  • CosFace
  • ArcFace
  • Combined Loss
  • AdaCos
  • SV-X-Softmax
  • CurricularFace
  • ArcNegFace
  • Li-Arcface
  • QAMFace
  • Circle Loss
• Parallel Training
  • DDP
  • Model Parallel
• Automatic Mixed Precision
  • AMP
• Optimizer
  • LRScheduler(faireq,rwightman)
  • Optim(SGD,Adam,RAdam,LookAhead,Ranger,AdamP,SGDP)
  • ZeRO
• [Data Augmentation
  • RandomErasing
  • Mixup
  • RandAugment
  • Cutout
  • CutMix
  • Colorjitter
• Distillation
  • KnowledgeDistillation
  • Multi Feature KD
• Bag of Tricks
  • Label smooth
  • LR warmup

Installation

See INSTALL.md.

Quick start

See GETTING_STARTED.md.

Model Zoo and Benchmark

See MODEL_ZOO.md.

License

cavaface is released under the MIT license.

Acknowledgement

• This repo is modified and adapted on these great repositories face.evoLVe.PyTorch, CurricularFace, insightface and imgclsmob
• The evaluation tools is developed by Charrin

Contact

[email protected]