Awesome
cavaface: A Pytorch Training Framework for Deep Face Recognition
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
<details open> <summary>(click to collapse)</summary>- 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
- [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
cavallyb@gmail.com