askarikzm/hixray-security-xray
HiXray Security X-ray Dataset Overview High-quality X-ray security screening dataset used for BYOL (Bootstrap Your Own Latent) self-supervised pretraining. This dataset is part of an FYP research project on X-ray baggage screening segmentation, in collaboration with Wancom Communications (Pvt) Ltd, Karachi, Pakistan. Dataset Summary Split Images Train 36,295 Test 9,069 Total 45,364 Image Details Format: JPEG… See the full description on the dataset page: https://huggingface.co/datasets/askarikzm/hixray-security-xray.
HiXray Security X-ray Dataset
Overview
High-quality X-ray security screening dataset used for BYOL (Bootstrap Your Own Latent) self-supervised pretraining.
This dataset is part of an FYP research project on X-ray baggage screening segmentation, in collaboration with Wancom Communications (Pvt) Ltd, Karachi, Pakistan.
Dataset Summary
Image Details
- Format: JPEG
- Content: X-ray scans of passenger bags at security checkpoints
- Objects: Everyday and prohibited items scanned through X-ray machines
Classes (8 categories)
Usage — BYOL Pretraining
This upload contains images only (no annotations). BYOL is self-supervised — labels are not used during pretraining.
from huggingface_hub import snapshot_download
path = snapshot_download(
repo_id="askarikzm/hixray-security-xray",
repo_type="dataset"
)Training Setup
- Method: BYOL (Bootstrap Your Own Latent)
- Backbone: ResNet-50 (ImageNet pretrained)
- Platform: RunPod GPU cloud
- Epochs: 200
- Framework: PyTorch + byol-pytorch
Citation
If you use this dataset, please cite the original HiXray paper:
@inproceedings{tao2021hixray,
title={Towards Real-World X-ray Security Inspection},
author={Tao, Renshuai and others},
booktitle={ICCV},
year={2021}
}License
CC BY-NC 4.0 — Non-commercial research use only.