D4Net: De-Deformation Defect Detection Network for Non-Rigid Products with Large Patterns

by Xuemiao Xu^, Jiaxing Chen^, Huaidong Zhang*, and Wing~W. Y. Ng* (^ joint 1st author, * joint corresponding author)[paper link]

This implementation is written by Jiaxing Chen at the South China University of Technology.

Citation

@article{xu2020d4net,
     title={D4Net: De-Deformation Defect Detection Network for Non-Rigid Products with Large Patterns},
     author={Xuemiao Xu, Jiaxing Chen, Huaidong Zhang, and Wing~W. Y. Ng},
     journal={Information Sciences},
     volume={547},
     pages={763--776},
     year={2021},
     publisher={Elsevier}
}

LFLP Dataset

Due to the influence of COVID-19, the LFLP dataset will be released after the author returns to school. [LFLP dataset link]

The testing set of LFLP is updated(2021/04/22), the training set of LFLP is coming soon.

Trained Model

You can download the trained model which is reported in our paper at Google Drive.

Requirement

Python 2.7
PyTorch 0.4.0
torchvision
numpy

Training

Set the path of pretrained ResNeXt model in resnext/config.py
Set the path of LFLP dataset in config.py
Run by python train.py

Hyper-parameters of training were gathered at the beginning of train.py and you can conveniently change them as you need.

Testing

Put the trained model in ckpt/d4net
Run by python infer.py

Settings of testing were gathered at the beginning of infer.py and you can conveniently change them as you need.

githubBingoChen/D4Net