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PyTorch re-implementation of 'A comprehensive study on cross-view gait based human identification with deep CNNs'

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Gait Recognition

PyTorch re-implementation of some models in the paper A comprehensive study on cross-view gait based human identification with deep CNNs.

Usage

  1. Download our prepared Casia-B data.

  2. Install the fastai library.

  3. Clone this repo.

  4. Extract the data and arrange the directories as follows.

    somedir
    |-- data
    |   `-- casiab-nm
    `-- gaitrecog
        |-- train_on_gei.py
        `-- ...
    
  5. Go to somedir/gaitrecog, and either use the jupyter notebook train_on_gei.ipynb or run the following from a terminal.

    python train_on_gei.py --model lb --task tr --split tv
    python train_on_gei.py --model lb --task ts --split ts --trained casiab-nm_lb_sgd-0.01-0.9-0.0005_st-14-96_bs128_tv_239

Note

Sometimes the training never converges due to bad initialization. In this case, stop the training and restart it.

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