MobileFaceNet_TF

Tensorflow implementation for MobileFaceNet.

dependencies

• tensorflow >= r1.5
• opencv-python 3.x
• python 3.x
• scipy
• sklearn
• numpy
• mxnet
• pickle

Prepare dataset

1. choose one of the following links to download dataset which is provide by insightface. (Special Recommend MS1M-refine-v2)

• MS1M-refine-v2@BaiduDrive, MS1M-refine-v2@GoogleDrive
• Refined-MS1M@BaiduDrive, Refined-MS1M@GoogleDrive
• VGGFace2@BaiduDrive, VGGFace2@GoogleDrive
• Insightface Dataset Zoo

2. move dataset to ${MobileFaceNet_TF_ROOT}/datasets.
3. run ${MobileFaceNet_TF_ROOT}/utils/data_process.py.

pretrained model

• pretrained_model

training

1. refined super parameters by yourself special project.
2. run script ${MobileFaceNet_TF_ROOT}/train_nets.py
3. have a snapshot result at ${MobileFaceNet_TF_ROOT}/output.

performance

size	LFW(%)	Val@1e-3(%)	inference@MSM8976-cpu(ms)
5.7M	99.4+	98.4+	260-

References

1. facenet
2. InsightFace mxnet
3. InsightFace_TF
4. MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
5. CosFace: Large Margin Cosine Loss for Deep Face Recognition
6. InsightFace : Additive Angular Margin Loss for Deep Face Recognition