SIXray:A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images
Conda virtual environment is recommended: conda env create -f environment.yml
and then pip install -r requirements.txt
- Python3.5
- PyTorch: 0.3.1
- Packages: torch, numpy, tqdm
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Clone the CHR repository:
git clone https://github.com/MeioJane/CHR.git
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Run the training demo:
bash CHR/runme.sh
If you only want to test images, you can download here. Resnet101-CHR
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}
}
In this project, we reimplemented CHR on PyTorch based on wildcat.pytorch.