/face-attributes-mxnet

The project mainly forcus on using recordIO to pack images and transforming learning for object classification.

Primary LanguagePython

Reproduction of MobileNetV2 using MXNet for Face Anti Spoofing

Project Descriptions

  • created by : lxy and shj
  • Time: 2018/12/10 15:09
  • project Face Anti Spoofing
  • company:
  • rversion: 0.1
  • tools: python 2.7
  • modified:
  • description: The codes for training and testing

Requests

  • mxnet >= 1.2.0
  • python >= 2.7.15
  • opencv >= 3.4.0

Training Data

  • The training datas are downloaded from internet,using the tool BaiduDownload
  • We have created the dataset including 4 classes (Mobilephone:1 TV:2 telectroller:3 background:0).

Run Train and Test demo

Configuration parameters lies in Root/src/configs/config.py

  1. directory
  • data is used to store training and testing data.
  • log is used to store traing logs.
  • models is used to store network parameters.
  • src is used to store training and testing codes.
  1. train
  • get image list : running Root/src/utils/run.sh to generate traing and testing data list.
  • pack training images: running Root/src/prepare_data/convert2data.sh to pack training data.
  • to train on packed images: running Root/src/train/train_faceanti.py
  1. test
  • test one image: python Root/src/test/demo.py --img-path1 test.jpg --gpu 0 --load-epoch 10 --cmd-type imgtest
  • test a video: python Root/src/test/demo.py --file-in test.mp4 --gpu 0 --load-epoch 10 --cmd-type videotest
  • test on a test dataset: python demo.py --file-in ../../data/test.lst --out-file ./output/record.txt --base-dir .../test_imgs/ --load-epoch 25 --cmd-type txtlisttest

HS Demo and Properties

Results on Test data

class TPR FPR Precision
Mobilephone 0.631 0.026 0.856
TV 0.954 0.120 0.700
Teleconrtoller 0.827 0.013 0.929
background 0.809 0.106 0.812