[KDD 2026] PipeMFL-240K: A Large-scale Dataset and Benchmark for Object Detection in Pipeline Magnetic Flux Leakage Imaging

Update

• [2026-05-17] Our dataset and benchmark paper has been accpeted by The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026).

Dataset Card for PipeMFL-240K

Benchmark code is available in https://github.com/TQSAIS/PipeMFL-240K.

Paper: https://arxiv.org/abs/2602.07044

Citation

If you find our dataset helpful for your research, please consider citing the following BibTeX entry.

@inproceedings{qu2026mfl240k,
  title     = {PipeMFL-240K: A Large-scale Dataset and Benchmark for Object Detection in Pipeline Magnetic Flux Leakage Imaging},
  author    = {Tianyi Qu and Songxiao Yang and Haolin Wang and Huadong Song and Xiaoting Guo and Wenguang Hu and Guanlin Liu and Honghe Chen and Yafei Ou},
  booktitle = {Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (KDD 2026)},
  year      = {2026},
  address   = {Jeju Island, Republic of Korea},
  publisher = {ACM},
  doi       = {10.1145/3770855.3817449}
}

Download

Please run the following command to download PipeMFL-240K:

HTTPS:

git clone https://huggingface.co/datasets/PipeMFL/PipeMFL-240K

SSH:

git clone git@hf.co:datasets/PipeMFL/PipeMFL-240K

Unzip the dataset

cd train_data
cat train_part_* | tar -xvf - -C ../

cd val_data
cat train_part_* | tar -xvf - -C ../

cd test_data
cat train_part_* | tar -xvf - -C ../