Occluded Prohibited Items Detection: An X-ray Security Inspection Benchmark and De-occlusion Attention Module

Requirements

Python3.5

Pytorch:1.3.1

Dataset

Download OPIXray dataset from here. The password is rntm. Here are some sample images in the dataset.

Checkpoint

If you want to test the performance of DOAM, you can download our model from here. The password is m9zk.

If you want to train your own model, you can download pre-trained weight of SSD on VOC0712 here. The password is 3fbo.

Usage

1. Clone the OPIXray repository

   git clone https://github.com/xl4533/OPIXray.git

2. If you want to train your model, execute the following command:

   (1) cd DOAM

   (2) Change the value of OPIXray_ROOT variable in DOAM/data/OPIXray.py file to the path where the training set is located, for example, OPIXray_ROOT = "/mnt/OPIXray_Dataset/train/"

   (3) python train.py --save_folder /mnt/model/DOAM/weights/ --image_sets /mnt/OPIXray_Dataset/train/train_knife.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

3. If you want to test our model, execute the following command:

   (1) cd DOAM

   (2) Change the value of OPIXray_ROOT variable in DOAM/data/OPIXray.py file to the path where the testing set is located, for example, OPIXray_ROOT = "/mnt/OPIXray_Dataset/test/"

   (3) python test.py --trained_model /mnt/model/SSD/weights/DOAM.pth --imagesetfile /mnt/OPIXray_Dataset/test/test_knife.txt

   trained_model is the weight file you want to test

4. If you want to test our model with different occlusion level, execute the following command:

   (1) cd DOAM

   (2) Change the value of OPIXray_ROOT variable in DOAM/data/OPIXray.py file to the path where the testing set is located, for example, OPIXray_ROOT = "/mnt/OPIXray_Dataset/test/"

   (3) python test.py --trained_model /mnt/model/SSD/weights/DOAM.pth --imagesetfile /mnt/OPIXray_Dataset/test/test_knife-1.txt （occlusion level 1）

   (4) python test.py --trained_model /mnt/model/SSD/weights/DOAM.pth --imagesetfile /mnt/OPIXray_Dataset/test/test_knife-2.txt （occlusion level 2）

   (5) python test.py --trained_model /mnt/model/SSD/weights/DOAM.pth --imagesetfile /mnt/OPIXray_Dataset/test/test_knife-4.txt （occlusion level 3）

Acknowledgement

In this project, we implemented DOAM on PyTorch based on amdegroot