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D24
BeanTech anomaly detection & localization. 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
2,540 records (test=741 · train=1799). 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 (BTAD is binary ok/ko — no fine-grained defect types). Pixel-level localization is a separate task whose target is the mask column — 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
This dataset supports two levels of the anomaly task:
- Image-level detection —
queryasks only whether the pictured product is good or anomalous, andannotis the plain-text answergoodoranomalous. - Pixel-level localization / segmentation — for every anomalous image the
maskcolumn carries the ground-truth defect mask: a binary image (pixel1= defect,0= background) at the input resolution. Normal images have no defect and therefore no mask (null). A model addressing the localization task is expected to output a binary mask image of the same height×width (1= defect pixel,0= background); this repo ships that mask as the localization target.
Split. train = normal images only (the ok folders; no anomalies, no masks); test =
normal + anomalous (ok + ko), with a mask on each anomalous image (see the exact counts under
Records). BTAD ships a single anomaly detection-and-localization protocol (no supervised / few-shot
variants); the three products are 01 / 02 / 03.
Provenance
Underlying dataset: BTAD. Upstream license: CC-BY-SA (this card is license: other; respect the upstream terms). Converted read-only from the raw source into the unified schema; conversion script: D24/convert_d24.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.
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