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[Towards]

This repository is the official HiXray dataset.

Download link

(China mainland, BaiduNetdisk) https://pan.baidu.com/s/1ugMhHtEp4G7yEF_WbLt8DA password: buaa

(Other area, Google Drive) https://drive.google.com/file/d/1jEk-h5Uv0-d3RdLf8cSHKXhuhalqD3l4/view?usp=sharing

HiXray dataset:

<div align=center> <img src="images/samples.png"/> </div>

LIM framework:

MuBo

Table of Contents

Dataset

In this project, we build the largest High-quality X-ray Security Inspection dataset.

Install

  1. If you want to train your model, execute the following command: change root to MuBo

    cd MuBo
    

    Change the value of HiXray_ROOT variable in MuBo/data/HiXray.py file to the path where the training set is located, for example,

    HiXray_ROOT = "/mnt/cvpr_dataset/train/"
    

    run train.py

    python train.py --save_folder /mnt/model/Mubo/save/ --image_sets /mnt/cvpr_dataset/train/train_name.txt --transfer /mnt/ssd300_mAP_77.43_v2.pth
    

    save_folder is used to save the weight file obtained by training the model,

    image_sets is the path to a TXT file that saves all the picture names used for training,

    transfer indicates the pre-trained weight of SSD on VOC0712 (available at here).

  2. If you want to test our model, execute the following command: change root to MuBo

    cd MuBo
    

    Change the value of HiXray_ROOT variable in MuBo/data/HiXray.py file to the path where the testing set is located, for example,

    HiXray_ROOT = "/mnt/cvpr_dataset/test/"
    

    run test.py

    python test.py --trained_model /mnt/model/Mubo/weights/Mubo.pth --imagesetfile /mnt/cvpr_dataset/test/test_name.txt
    

    trained_model is the weight file you want to test, our model is available at here, password is ectq

Results

Comparing with Feature Pyramid Mechanisms:

<div align=center> <img src="images/results_table5.png"/> </div>

Visualization of the performance of both the baseline SSD and the MuBo-integrated model:

<div align=center> <img src="images/performance.png"/> </div>

Citation

If this work helps your research, please cite the following paper.

@inproceedings{Tao:ICCV21,
  author    = {Renshuai Tao and Yanlu Wei and Xiangjian Jiang and Hainan Li and Haotong Qin and Jiakai Wang and Yuqing Ma and Libo Zhang and Xianglong Liu*},
  title     = {Towards Real-world X-ray Security Inspection: A High-quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection},
  booktitle = {IEEE ICCV},
  year      = {2021},
  }