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MobileFaceNet

Introduction

Requirements

Usage

Part 1: Preprocessing

Part 2: Train

  1. Change the CAISIA_DATA_DIR and LFW_DATA_DAR in config.py to your data path.

  2. Train the mobilefacenet model.

    Note: The default settings set the batch size of 512, use 2 gpus and train the model on 70 epochs. You can change the settings in config.py

    python3 train.py
    

Part 3: Test

  1. Test the model on LFW.

    Note: I have tested lfw_eval.py on the caffe model at SphereFace, it gets the same result.

    python3 lfw_eval.py --resume --feature_save_dir
    
    • --resume: path of saved model
    • --feature_save_dir: path to save the extracted features (must be .mat file)

Results

Fold12345678910AVE(ours)Paper(112x96)
ACC99.0099.0099.0098.6799.3399.6799.1799.50100.0099.6799.3099.18

Reference resources