---
pretty_name: DD1 OT VQA Grounding
tags:
  - visual-question-answering
  - visual-grounding
  - industrial
  - additive-manufacturing
  - sft
task_categories:
  - visual-question-answering
---

# DD1 OT VQA Grounding

Answer-only VQA-style grounding data derived deterministically from the OT
portion of `DD1_cleaned_grounding`.

## Schema

| field | type | meaning |
|---|---|---|
| `query` | string | one of 34 deterministic LPBF OT grounding prompts |
| `image` | Image | original 2000×2000 JPEG bytes; never cropped |
| `annot` | string | JSON list `[{"bbox_xywh":[x,y,w,h]}]`, or `[]` |
| `reasoning` | null | answer-only dataset |
| `cate` | string | `B` |
| `task` | string | `T-B1` |
| `metadata` | string | JSON provenance, hashes, boxes and disclosures |

Coordinates use native pixels with top-left origin. Boxes are sorted by `x`,
then `y`. Width and height are derived as `xmax-xmin` and `ymax-ymin`.

## Counts

- Records: 2667
- Positive images: 1122
- Good/negative images: 1545
- Total boxes: 4339
- Query variants: 34
- Split: train only

## Load

```python
from datasets import load_dataset

ds = load_dataset(
    "parquet",
    data_files={"train": "data/train-00000-of-00001.parquet"},
)
```

`annot` is the direct SFT answer. `reasoning` is null on every row.

## Reproduce

```bash
python3 -m pip install -r requirements.txt
python3 build_dd1_ot_vqa.py \
  --source /path/to/DD1_cleaned_grounding \
  --output /path/to/DD1_OT_VQA_grounding
```

The build is deterministic and refuses to overwrite an existing output.

## Disclosure

`Good` means no author-annotated overheated region under the source labeling
rule; it does not claim absence of every possible manufacturing defect. OT
bbox scale varies across layers and may mix local and larger-region
annotations.