You need to agree to share your contact information to access this dataset
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
This dataset is released for research use. Access is reviewed and granted manually by the maintainers. Please state your name, affiliation, and intended use.
Log in or Sign Up to review the conditions and access this dataset content.
187-region
Region-conditioned defect QA on metal part — 1604 items, derived deterministically from the
binary segmentation masks of AI4Manufacturing/187. Exact-match gradable → SFT and
RLVR-ready.
Task
"A region is indicated — what defect, if any, is there?" One item per defect instance
(402 positives: scratches 102, anomalous 82, parts mismatch 80, bend and parts mismatch 59, defective painting 26, total rust 23, hole 17, major rust 13) plus 1202 clean-region negatives teaching rejection
(every good record + ~half of defective records). The region is conveyed in one of two modes
(metadata.region_mode; overlay 762 / bbox_text 842):
overlay— a red rectangular ring drawn on the image around the region.bbox_text— the raw image plus the region as a pixel box[x, y, w, h]in the query text.
Clean boxes sample size AND position from the emitted positive population, so box geometry
separates nothing. Gold = the type name (closed list) or no defect. Verified: zero defect pixels inside any clean box; positive
gold matches the source type on every row.
Blind baseline. 75% of items are clean-region negatives, so a blind "always
no defect" guesser scores 75%; the task is defeated only by inspecting the
indicated region (402 positives carry a real defect there).
| field | meaning |
|---|---|
query |
region prompt (overlay or bbox-text) |
image |
photo, or photo with ONE red ring (overlay mode) |
annot |
the type name (closed list) or no defect |
reasoning |
null — deterministic |
cate / task |
B / T-B2 |
metadata |
source, image_sha256, image_wh, region_mode, bbox_xywh, instance_index, gold |
Provenance
Built deterministically (no LLM/teacher; reasoning is null) from AI4Manufacturing/187
— MPDD metal-parts surface inspection — 1,346 photos over 6 part categories, 8 defect types + good; each anomalous image has a paired binary pixel segmentation mask (binarized at gray>127 (the source masks are clean 0/255); the defect TYPE comes from metadata (one type per image, raw underscores normalized to spaces — raw label kept in metadata.defect_type_raw)).
Generator: annotate/187/build_187_derived.py in forge_model; machine gates
annotate/187/verify_187.py (all green at build: boxes/gold re-derived byte-identical, clean
regions contain zero defect pixels, mcq gold = the true panel, no leaked-artifact vocabulary, image
set sha256-disjoint from all other cached AI4Manufacturing datasets).
Resolution. Images are native 1024×1024; all coordinates live in that pixel space (see metadata.image_wh).
Query diversity. query is drawn from a fixed pool of surface variants (paraphrases preserving
the task + answer format), selected by an independent per-record hash; a machine gate confirms no
template correlates with the gold.
The repository name is an internal task code (the source dataset's code is
187).
- Downloads last month
- 2