tags:
- smart-manufacturing
- sft
- industrial
- vision
license: other
pretty_name: '185'
extra_gated_fields:
Name: text
Affiliation: text
Intended use: text
extra_gated_prompt: >-
This dataset is released for **research use**. Access is reviewed and granted
**manually** by the maintainers. Please state your name, affiliation, and
intended use.
185
Production-surface defect binary detection (segmentation GT; official train/test). Category B, task T-B1, in the unified Smart-Manufacturing SFT schema.
The repository name is an internal task code. See Provenance below for the underlying dataset.
Records
3,335 records (test=1004 · train=2331). Pixel masks are embedded as a mask image column.
Unified SFT schema
| field | type | meaning |
|---|---|---|
query |
str | the question / instruction (model input) |
image |
Image | the input image (bytes embedded) |
annot |
str | the answer — for this dataset: the plain-text image-level label good or anomalous (binary; no defect types — derived from the pixel mask). The binary segmentation mask is deferred localization GT, with seg info (mask_path, defect_area_fraction) in metadata — see Task, mask & split below |
reasoning |
null | no native CoT in these datasets |
cate |
"B" | SFT category |
task |
"T-xx" | unified task id |
metadata |
str (JSON) | split, provenance, image_path, image_sha256 (dedup key) |
mask |
Image | null | (T-B1/T-B2 only) the pixel ground-truth mask, bytes embedded |
masks |
list[Image] | (D21 only) multi-region masks |
Task, mask & split
What this is. KolektorSDD2 (Bozic et al., "Mixed supervision for surface-defect detection: from weakly to fully supervised learning", Computers in Industry 2021) — colour images of production-part surfaces with pixel-level defect masks and an official train/test split. 356 defective / 2,979 defect-free.
Task & label. Surface-defect detection: image-level binary (defect vs OK) + pixel-level segmentation under
mixed supervision. The image-level label is derived from the mask (nonzero -> anomalous). query asks only
good vs anomalous; annot is the plain-text good/anomalous. The query does not ask for a mask.
Segmentation (deferred GT). Binary mask kept in the mask column (anomalous only; good = null); seg info
(mask_path, defect_area_fraction) in metadata. Segmentation is deferred (a text model can't emit a pixel mask).
Split. Official train (2,331: 246 anomalous + 2,085 good) + test (1,004: 110 anomalous + 894 good). Two
train images ship no GT mask and are skipped.
Provenance
Underlying dataset: KolektorSDD2. Upstream license: CC BY-NC-SA 4.0 (this card is license: other; respect the upstream terms). Converted read-only from the raw source into the unified schema; conversion script: 185/convert_d85.py, published with publish/push_to_hf.py, both in AI4Manufacturing/forge_model.
Overlap / de-duplication (§8)
None notable. Each record carries metadata.image_sha256 so overlapping images can be kept entirely on one side of a train/eval split.