--- license: other license_name: see-license-file-upstream-unstated license_link: LICENSE task_categories: - object-detection language: - en tags: - neu-det - steel-surface-defect - hot-rolled-steel - industrial-inspection - object-detection - pascal-voc - yolo size_categories: - 1K ⚠️ **Upstream license: none stated.** The original authors have never declared a license > for NEU-DET. See [License & attribution](#license--attribution) — verify before commercial use. ### Corrections vs. the official release | # | Correction | Detail | |---|---|---| | 1 | **Removed 1 exact-duplicate image** | `patches_105.jpg` is pixel-identical to `patches_101.jpg` (the same image annotated twice, with slightly different boxes). | | 2 | **Removed 2 near-duplicate images** | `scratches_247.jpg` is a 90°-rotated copy of `scratches_232.jpg`; `pitted_surface_292.jpg` is a 2-px-shifted copy of `pitted_surface_171.jpg`. Both show a sharp, isolated minimum in the alignment profile (random same-class pairs never drop below MAE ≈ 13). | | 3 | **Removed 3 duplicate boxes** | `crazing_120`, `inclusion_62`, `patches_198` each contained one bounding box listed twice verbatim. | | 4 | **Added a reproducible split** | Upstream has no split. This release provides a seeded, class-stratified 80/10/10 split. | | 5 | **Dual format** | Upstream is Pascal VOC only. This release ships **VOC + YOLO** from a single verified conversion. | | 6 | **Packaging** | `classes.txt`, `data.yaml`, `ImageSets/` added. | **Image pixels are never modified.** All 1,797 images are byte-for-byte identical to the upstream files. **Scope — structural clean-up only.** This is **not** a re-annotation. We remove duplicates and re-package the data; we do **not** re-verify individual boxes (missed defects, wrong class labels, box tightness) — that requires domain expertise and is left untouched. **Structural checks performed** on the released 1,797-image set: | Check | Method | Result | |---|---|---| | Exact duplicate images | byte-wise MD5 | **1** found → removed | | Rotation / mirror duplicates | 8 dihedral transforms, perceptual hash | **1** found → removed | | Shifted duplicates | aligned pixel MAE + sharp-minimum test | **1** found → removed | | Near-duplicate images | 32×32/64×64 MAE + full aligned scan | **0** remaining | | Duplicate boxes within an image | verbatim box comparison | **3** found → removed | | Empty / invalid labels | 0-box files, out-of-range, zero-area boxes | **0** | | Image ↔ label ↔ XML pairing | bidirectional | **0** orphans | | Class-name consistency | unique label set | 6 classes, no anomalies | | Split leakage | train/val/test intersection | **0** | ### Dataset at a glance | Property | Value | |---|---| | Images | **1,797** (200 × 200, grayscale) | | Classes | **6** — `crazing`, `inclusion`, `patches`, `pitted_surface`, `rolled-in_scale`, `scratches` | | Bounding boxes | **4,177** (≈ 2.32 per image) | | Formats | Pascal VOC XML · YOLO TXT | | Split | train 1,437 / val 180 / test 180 (seeded, class-stratified) | **Boxes per class:** `inclusion` 1,010 · `patches` 875 · `crazing` 688 · `rolled-in_scale` 628 · `scratches` 546 · `pitted_surface` 430 ### Structure ``` NEU-DET-corrected/ ├── images/{train,val,test}/ # 200x200 grayscale JPG ├── labels/{train,val,test}/ # YOLO: cls cx cy w h (normalized) ├── annotations/ # Pascal VOC XML (flat, cleaned) ├── ImageSets/{train,val,test}.txt ├── classes.txt ├── data.yaml # YOLO dataset config ├── LICENSE └── README.md ``` `annotations/*.xml` and `labels/**/*.txt` are two representations of the **same** cleaned annotations and are verified to agree. ### Citation **1. The original dataset — please always cite this.** ```bibtex @article{he2020neudet, title = {An End-to-end Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features}, author = {He, Yu and Song, Kechen and Meng, Qinggang and Yan, Yunhui}, journal = {IEEE Transactions on Instrumentation and Measurement}, volume = {69}, number = {4}, pages = {1493--1504}, year = {2020}, doi = {10.1109/TIM.2019.2915404} } ``` ```bibtex @article{song2013neudet, title = {A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects}, author = {Song, Kechen and Yan, Yunhui}, journal = {Applied Surface Science}, volume = {285}, pages = {858--864}, year = {2013}, doi = {10.1016/j.apsusc.2013.08.123} } ``` **2. This corrected release — please cite it as well.** It is not identical to the official release: 3 duplicate images (1 exact, 2 near-duplicates under rotation / shift) and 3 duplicate boxes were removed, a reproducible split was added, and the data was re-packaged, so a citation to the papers alone does not describe this version. ```bibtex @misc{neudet_corrected, author = {KeenForgeAI}, title = {NEU-DET-corrected: a cleaned release of the NEU Surface Defect Database}, year = {2026}, version = {1.0}, publisher = {KeenForgeAI}, url = {https://huggingface.co/datasets/KeenForgeAI/NEU-DET-corrected}, note = {Curated by Lu Gan and Sam Li. Derived from He et al. (2020), doi:10.1109/TIM.2019.2915404. Upstream licence unstated.} } ``` **3. The annotation tool (optional).** ```bibtex @software{keenforge, author = {KeenForgeAI}, title = {KeenForge: a local-first, offline image annotation and model-training desktop tool}, year = {2026}, publisher = {KeenForgeAI}, url = {https://github.com/KeenForgeAI/KeenForge}, note = {MIT licensed. Developed by Lu Gan and Sam Li.} } ``` ### License & attribution **The upstream NEU-DET dataset states no license.** The original authors provide it for research use via their [official page](https://faculty.neu.edu.cn/songkc/en/zdylm/263265/) (Google Drive / Baidu Netdisk) and only request a citation. The copyright status of the original images and annotations is therefore **undetermined** — verify it before any commercial use. See `LICENSE` in this repository. Our modifications (de-duplication, re-packaging, split, documentation) are released openly. Image pixels are unmodified and remain subject to the upstream terms. ### Provenance - Source: official NEU-DET release (Google Drive), retrieved 2026-09-21. - Upstream: 1,800 images + 1,800 Pascal VOC XML, no split. - Verified: 1,797 images retained, byte-identical to upstream; 4,177 boxes after removing 3 duplicate boxes and 3 duplicate images (1 exact, 2 near-duplicates). --- ## 中文 ### 这是什么？ **NEU 表面缺陷数据库（NEU-DET）**（东北大学，宋克臣、颜云辉）的**清理、补全、规范化打包版**。 上游发布是扁平的 `IMAGES/` + `ANNOTATIONS/`（Pascal VOC），**无官方划分**，且存在少量标注缺陷。 本版**不修改任何图像像素**，仅删除少量重复项，并以 **Pascal VOC + YOLO 双格式**打包， 附带可复现的 train/val/test 划分。 > ⚠️ **上游未声明许可证。** 原作者从未为 NEU-DET 声明许可证。详见 > [许可证与署名](#许可证与署名)——商用前请自行确认。 ### 相对官方版的修正 | # | 修正 | 说明 | |---|---|---| | 1 | **删除 1 张完全重复图** | `patches_105.jpg` 与 `patches_101.jpg` 像素完全相同（同一张图被标注两次，框略有差异）。 | | 2 | **删除 2 张近似重复图** | `scratches_247.jpg` 是 `scratches_232.jpg` 旋转 90° 的副本；`pitted_surface_292.jpg` 是 `pitted_surface_171.jpg` 平移 2px 的副本。两者在对齐剖面中都呈**尖锐唯一极小值**（随机同类对从未低于 MAE ≈ 13）。 | | 3 | **删除 3 个重复框** | `crazing_120`、`inclusion_62`、`patches_198` 各有 1 个边界框**逐字重复出现两次**。 | | 4 | **补充可复现划分** | 上游无划分；本版提供固定随机种子、按类别分层的 80/10/10 划分。 | | 5 | **双格式** | 上游仅有 Pascal VOC；本版同时提供 **VOC + YOLO**（由同一次转换生成并校验一致）。 | | 6 | **规范化打包** | 新增 `classes.txt`、`data.yaml`、`ImageSets/`。 | **图像像素从不修改**——1,797 张图与上游文件逐字节一致。 **本版范围——仅结构化清理。** 这是**结构性清理，不是重新标注**。我们只去重、重新打包； **不**重新核对单个标注框（漏标、类别标错、框松紧）——那需要领域专业知识，一律保持原样。 **已执行的结构化检查**（针对发布的 1,797 张）： | 检查 | 方法 | 结果 | |---|---|---| | 样本重复 · 精确 | 逐字节 MD5 | **1 组** → 已删 | | 样本重复 · 旋转/镜像 | 8 种二面体变换感知哈希 | **1 组** → 已删 | | 样本重复 · 平移 | 对齐像素 MAE + 尖锐极小值判定 | **1 组** → 已删 | | 样本重复 · 近似 | 32×32/64×64 MAE + 全库对齐扫描 | **0 剩余** | | 标签重复 · 图内 | 逐字比对同一图内的框 | **3 个** → 已删 | | 空/非法标签 | 0 框文件、越界框、零面积框 | **0** | | 图片↔标签↔XML 配对 | 双向 | **0 孤儿** | | 类别名一致性 | 唯一类别名集合 | 6 类，无杂名 | | 划分泄漏 | train/val/test 交集 | **0** | ### 数据集概览 | 属性 | 值 | |---|---| | 图片 | **1,797**（200 × 200 灰度） | | 类别 | **6** —— `crazing`、`inclusion`、`patches`、`pitted_surface`、`rolled-in_scale`、`scratches` | | 标注框 | **4,177**（约 2.32 框/图） | | 格式 | Pascal VOC XML · YOLO TXT | | 划分 | train 1,437 / val 180 / test 180（固定种子、类别分层） | **各类框数**：`inclusion` 1,010 · `patches` 875 · `crazing` 688 · `rolled-in_scale` 628 · `scratches` 546 · `pitted_surface` 430 ### 目录结构 ``` NEU-DET-corrected/ ├── images/{train,val,test}/ # 200x200 灰度 JPG ├── labels/{train,val,test}/ # YOLO：cls cx cy w h（归一化） ├── annotations/ # Pascal VOC XML（扁平，已清理） ├── ImageSets/{train,val,test}.txt ├── classes.txt ├── data.yaml # YOLO 配置 ├── LICENSE └── README.md ``` `annotations/*.xml` 与 `labels/**/*.txt` 是**同一份**清理后标注的两种表示，已校验一致。 ### 引用 使用本数据集请**同时引用**原始工作与本修正版： **1. 原始数据集（请务必引用）** ```bibtex @article{he2020neudet, title = {An End-to-end Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features}, author = {He, Yu and Song, Kechen and Meng, Qinggang and Yan, Yunhui}, journal = {IEEE Transactions on Instrumentation and Measurement}, volume = {69}, number = {4}, pages = {1493--1504}, year = {2020}, doi = {10.1109/TIM.2019.2915404} } ``` ```bibtex @article{song2013neudet, title = {A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects}, author = {Song, Kechen and Yan, Yunhui}, journal = {Applied Surface Science}, volume = {285}, pages = {858--864}, year = {2013}, doi = {10.1016/j.apsusc.2013.08.123} } ``` **2. 本修正版（请一并引用）** —— 本版**与官方发布并不相同**：删除了 1 张重复图与 3 个重复框， 补充了可复现划分，并重新打包，因此**只引用论文无法描述本版本**。 ```bibtex @misc{neudet_corrected, author = {KeenForgeAI}, title = {NEU-DET-corrected: a cleaned release of the NEU Surface Defect Database}, year = {2026}, version = {1.0}, publisher = {KeenForgeAI}, url = {https://huggingface.co/datasets/KeenForgeAI/NEU-DET-corrected}, note = {Curated by Lu Gan and Sam Li. Derived from He et al. (2020), doi:10.1109/TIM.2019.2915404. Upstream licence unstated.} } ``` **3. 标注工具（可选）** ```bibtex @software{keenforge, author = {KeenForgeAI}, title = {KeenForge: a local-first, offline image annotation and model-training desktop tool}, year = {2026}, publisher = {KeenForgeAI}, url = {https://github.com/KeenForgeAI/KeenForge}, note = {MIT licensed. Developed by Lu Gan and Sam Li.} } ``` ### 许可证与署名 **上游 NEU-DET 未声明许可证。** 原作者通过 [官方主页](https://faculty.neu.edu.cn/songkc/en/zdylm/263265/)（Google Drive / 百度网盘） 以研究用途提供，仅要求引用。因此原始图像与标注的**版权状态未定**——**商用前请自行确认**。 详见本仓库 `LICENSE`。 我们对数据集的修改部分（去重、重新打包、划分、文档）开源发布。图像像素未修改， 仍受上游条款约束。 ### 来源 - 来源：官方 NEU-DET 发布（Google Drive），获取于 2026-09-21 - 上游：1,800 图 + 1,800 Pascal VOC XML，无划分 - 已校验：保留 1,797 图，与上游逐字节一致；删除 3 个重复框与 3 张重复图（1 张完全重复 + 2 张近似重复）后共 4,177 框