SIXray：A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images

[Paper] [dataset]

Requirements

Conda virtual environment is recommended: conda env create -f environment.yml

• Python3.5
• PyTorch: 0.3.1
• Packages: torch, numpy, tqdm

Usage

1. Clone the CHR repository:

   git clone https://github.com/MeioJane/CHR.git

2. Run the training demo:

   cd CHR/
   bash CHR/runme.sh

Checkpoint

If you only want to test images, you can download here. Resnet101-CHR

Citation

If you use the code in your research, please cite:

@INPROCEEDINGS{Miao2019SIXray,
    author = {Miao, Caijing and Xie, Lingxi and Wan, Fang and Su, chi and Liu, Hongye and Jiao, jianbin and Ye, Qixiang },
    title = {SIXray: A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images},
    booktitle = {CVPR},
    year = {2019}
}

Acknowledgement

In this project, we reimplemented CHR on PyTorch based on wildcat.pytorch.