Unofficial Tensorflow 2 implementation of SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder

Requirements

• python 3
• opencv-python
• numpy
• tensorflow >=2.3.1
• albumentations

Model

SINet (paper) Accepted in WACV2020

Hyojin Park, Lars Lowe Sjösund, YoungJoon Yoo, Nicolas Monet, Jihwan Bang, Nojun Kwak

SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder

Run example

• Preparing dataset

if you use custom dataset, fix the code and parms in data_loader.py(DatasetLoader's "Load" call).

• Train

nohup python3 distributed_train.py>train.log 2>&1 &

• View Log

tail -f train.log

• TensorBoard

tensorboard --logdir ./training/

Citation

@article{park2019sinet,
  title={SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder},
  author={Park, Hyojin and Sj{\"o}sund, Lars Lowe and Monet, Nicolas and Yoo, YoungJoon and Kwak, Nojun},
  journal={arXiv preprint arXiv:1911.09099},
  year={2019}
}
@article{heo2020adamp,
    title={Slowing Down the Weight Norm Increase in Momentum-based Optimizers},
    author={Heo, Byeongho and Chun, Sanghyuk and Oh, Seong Joon and Han, Dongyoon and Yun, Sangdoo and Uh, Youngjung and Ha, Jung-Woo},
    year={2020},
    journal={arXiv preprint arXiv:2006.08217},
}

The meaning of this repository

Try to provide you with a relatively concise and standardized TensorFlow 2 custom training code example.

Related discussion post

TensorFlow 2.X，会是它走下神坛的开始？