face-recognition-iai

Implementation with deep learning methods like CosineFace, SphereFace, ArcFace for face recognition task in pattern recognition class in IAI, BUAA.

Features

• Various backbones and modules (SEResNet, SEResNet-IR, ResidualAttentionNetwork and CBAM...)
• Various metrics (Softmax, ArcFace, CosineFace, ShpereFace and combination...)
• Easy to use command to train model
• available for customized dataset

Installation

Install required dependencies with following shell command:

pip install -r requirements.txt

Examples

Prepare dataset

Prepare your dataset according to documentations for torchvision.ImageFolder. For example, split train set and validation(test) set under faces95 as following:

├── faces95
   ├── train
   ├── val

Train

For example, to train SeResNet100-IR with ArcFace method and data under faces95 on gpu:0:

python train.py faces95 \
                --epochs 8000 \
                --backbone SERes100_IR \
                --metric ArcFace \
                --workers 4 \
                --feature-dim 512 \
                --n-classes 152 \
                --scale 8 \
                --batch-size 64 \
                --lr 1e-7 \
                --momentum 0.9 \
                --save-dir ./model/SeRes100_IR_ArcFace \
                --print-freq 10 \
                --save-freq 100 \
                --gpu 0

Evaluation

For example, evaluate trained model under SeRes100_IR_ArcFace/checkpoint-6000.pth.tar with data under faces95/val on gpu:0 :

python train.py faces95 \
                    --resume SeRes100_IR_ArcFace/checkpoint-6000.pth.tar \
                    --evaluate \
                    --epochs 8000 \
                    --backbone SERes100_IR \
                    --metric ArcFace \
                    --workers 4 \
                    --feature-dim 512 \
                    --n-classes 152 \
                    --scale 8 \
                    --batch-size 64 \
                    --lr 1e-7 \
                    --momentum 0.9 \
                    --save-dir ./model/SeRes100_IR_ArcFace \
                    --print-freq 10 \
                    --save-freq 100 \
                    --gpu 0