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https://github.com/cavalleria/cavaface

face recognition training project(pytorch)
https://github.com/cavalleria/cavaface

amsoftmax apex arcface arcnegface attention-irse circleloss cosface curricularface dataparallel efficientnet face-recognition ghostnet loss mixup model-parallel network pytorch randaugment resnest resnet-irse

Last synced: 16 days ago
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face recognition training project(pytorch)

Host: GitHub
URL: https://github.com/cavalleria/cavaface
Owner: cavalleria
License: mit
Created: 2020-04-15T07:39:58.000Z (over 4 years ago)
Default Branch: master
Last Pushed: 2021-11-12T08:01:36.000Z (about 3 years ago)
Last Synced: 2024-08-01T03:45:09.234Z (3 months ago)
Topics: amsoftmax, apex, arcface, arcnegface, attention-irse, circleloss, cosface, curricularface, dataparallel, efficientnet, face-recognition, ghostnet, loss, mixup, model-parallel, network, pytorch, randaugment, resnest, resnet-irse
Language: Python
Homepage:
Size: 305 KB
Stars: 457
Watchers: 24
Forks: 88
Open Issues: 31
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # cavaface: A Pytorch Training Framework for Deep Face Recognition

[![python-url](https://img.shields.io/badge/Python-3.x-red.svg)](https://www.python.org/)

[![pytorch-url](https://img.shields.io/badge/Pytorch-1.9-blue.svg)](https://pytorch.org/)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

![Docker Pulls](https://img.shields.io/docker/pulls/cavall/cavaface_env?logo=docker).

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](https://github.com/pytorch/fairseq/tree/master/fairseq/optim/lr_scheduler),[rwightman](https://github.com/rwightman/pytorch-image-models/tree/master/timm/scheduler))

  * [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](https://github.com/cavalleria/cavaface.pytorch/blob/master/docs/INSTALL.md).

## Quick start

See [GETTING_STARTED.md](https://github.com/cavalleria/cavaface.pytorch/blob/master/docs/GETTING_STARTED.md).

## Model Zoo and Benchmark

See [MODEL_ZOO.md](https://github.com/cavalleria/cavaface.pytorch/blob/master/docs/MODEL_ZOO.md).

## License

cavaface is released under the [MIT license](https://github.com/cavalleria/cavaface.pytorch/blob/master/docs/LICENSE).

## Acknowledgement

* This repo is modified and adapted on these great repositories [face.evoLVe.PyTorch](https://github.com/ZhaoJ9014/face.evoLVe.PyTorch), [CurricularFace](https://github.com/HuangYG123/CurricularFace), [insightface](https://github.com/deepinsight/insightface) and [imgclsmob](https://github.com/osmr/imgclsmob/)

* The evaluation tools is developed by [Charrin](https://github.com/Charrin)

## Contact

```markdown

[email protected]

```