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face recognition training project(pytorch)

cavaface: A Pytorch Training Framework for Deep Face Recognition

python-url pytorch-url License: MIT Docker Pulls.

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

Contact

[email protected]