| --- |
| pretty_name: DD1 PB VQA Grounding |
| tags: |
| - visual-question-answering |
| - visual-grounding |
| - industrial |
| - additive-manufacturing |
| - sft |
| task_categories: |
| - visual-question-answering |
| --- |
| |
| # DD1 PB VQA Grounding |
|
|
| Answer-only VQA-style grounding data derived deterministically from the PB |
| portion of `DD1_cleaned_grounding`. |
|
|
| ## Schema |
|
|
| | field | type | meaning | |
| |---|---|---| |
| | `query` | string | one of 34 deterministic LPBF PB grounding prompts | |
| | `image` | Image | original 1280×1024 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. Width and height are |
| `xmax-xmin` and `ymax-ymin`. |
|
|
| ## Counts |
|
|
| - Records: 2637 |
| - Positive images: 1529 |
| - Good/negative images: 1108 |
| - Total boxes: 5000 |
| - 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_pb_vqa.py \ |
| --source /path/to/DD1_cleaned_grounding \ |
| --output /path/to/DD1_PB_VQA_grounding |
| ``` |
|
|
| ## Disclosure |
|
|
| The source uses the generic class label `defects` without a subtype taxonomy. |
| `Good` means no author-annotated PB defect under the source labeling rule; it |
| does not guarantee absence of every possible manufacturing defect. |
|
|
