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MesoNet-Pytorch


The is a personal Reimplemention of MesoNet[1] using Pytorch. If you make use of this work, please cite the paper accordingly.

For the original version of this work using Keras, please see: DariusAf/MesoNet

Install & Requirements

The code has been test on pytorch 1.3.1, torchvision 0.4.2 and python 3.6.9, please refer to requirements.txt for more details.

To install the python packges

python -m pip install -r requiremnets.txt

Usage

To train the normal MesoNet

python train_Meso.py -n 'Mesonet' -tp './data/train' -vp './data/val' -bz 64 -e 100 -mn 'meso4.pkl'

To train the MesoInceptionNet

python train_MesoInception.py -n 'MesoInception' -tp './data/train' -vp './data/val' -bz 64 -e 100 -mn 'mesoinception.pkl'

If you continue training a pretrained model, you should use --continue_train True -mp ./pretrained_models/model.pkl

To test the trained Model

python test.py -bz 64 -tp './data/test' -mp './Mesonet/best.pkl'

License

The provided implementation is strictly for academic purposes only. Should you be interested in using our technology for any commercial use, please feel free to contact us.

Reference

[1] Afchar, D., Nozick, V., Yamagishi, J., & Echizen, I. (2018, September). MesoNet: a Compact Facial Video Forgery Detection Network. In IEEE Workshop on Information Forensics and Security, WIFS 2018.

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