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Reproduction of MobileNetV2 using tensorflow for insightface fast training


Project Descriptions

  • created by : lxy
  • Time: 2019/1/22 15:09
  • project Face Recognition
  • company:
  • rversion: 0.1
  • tools: python 2.7
  • modified:
  • description: The codes for training and testing

Requests

  • tensorflow >= 1.5.0
  • python >= 2.7.15
  • opencv >= 3.4.0
  • imgaug

Training Data

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/prepare_data/run_script.sh to generate traing and testing data list.
  • image augmentation: running Root/src/utils/transform.py for image augmentation, applying for images and images with boxes and images with keypoints
  • pack training images: running Root/src/prepare_data/run.sh to pack training data.
  • to train on packed images: running Root/src/train/run.sh
  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 ../prepare_data/output/test.txt --out-file ./output/record.txt --base-dir .../test_imgs/ --load-epoch 25 --cmd-type filetest
  1. video demo for face anti-spoofing
  • run Root/src/face_test/run.sh

HS Demo and Properties

Results on Test data

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tensorflow trianing code for insightface-face

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  • Python 99.6%
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