Datasets:

Tuyuanpeng
/

Draw2Explain

---
pretty_name: Draw2Explain
language:
- en
- zh
license: other
annotations_creators:
- machine-generated
task_categories:
- text-to-image
tags:
- engineering
- cutaway
- cross-section
- technical-illustration
- webdataset
size_categories:
- 100K<n<1M
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*.tar
---
# Draw2Explain

Draw2Explain is an object-centric engineering illustration dataset for generating
cutaways, cross-sections, and other structure-explaining technical drawings. The
released training split contains **150,720 image-caption pairs** in
**151 WebDataset shards**. Each image keeps its source URL, creator,
attribution, per-item rights metadata, and SHA-256 digest.

## Representative examples

These are actual records from the released training split, not benchmark cases.
The text below each image is the sample's `caption_short_en`; complete bilingual
captions, generation prompts, component constraints, and relation constraints are
stored in the paired `.json` member.

<table>
  <tr>
    <td width="50%" valign="top">
      <img src="assets/examples/r4360_engine_cutaway.jpg" alt="Pratt &amp; Whitney R-4360 aero engine cutaway" width="100%"><br>
      <b>Pratt &amp; Whitney R-4360 engine cutaway</b> · Level 4<br>
      <sub><code>commons:107825147</code> · <a href="https://commons.wikimedia.org/wiki/File:20-09-072-R_4360.jpg">source · CC0</a></sub>
    </td>
    <td width="50%" valign="top">
      <img src="assets/examples/turbofan_cutaway.gif" alt="Labeled turbofan engine cutaway" width="100%"><br>
      <b>A detailed cutaway of a turbofan engine highlighting key components.</b> · Level 4<br>
      <sub><code>commons:12365146</code> · Richard Wheeler (Zephyris) · <a href="https://commons.wikimedia.org/wiki/File:Turbofan3_Labelled.gif">source · CC BY-SA 3.0</a></sub>
    </td>
  </tr>
  <tr>
    <td width="50%" valign="top">
      <img src="assets/examples/digital_camera_exploded.png" alt="Exploded digital camera with labeled internal components" width="100%"><br>
      <b>Exploded view of a digital camera showing internal components.</b> · Level 4<br>
      <sub><code>commons:12030060</code> · Shigeru23 · <a href="https://commons.wikimedia.org/wiki/File:Digital_camera_cut_model_1.PNG">source · CC BY-SA 3.0</a></sub>
    </td>
    <td width="50%" valign="top">
      <img src="assets/examples/lunar_module_cutaway.png" alt="Lunar Module cutaway with component callouts" width="100%"><br>
      <b>Cutaway illustration of the Lunar Module.</b> · Level 4<br>
      <sub><code>commons:14623428</code> · NASA-MSFC / Adert · <a href="https://commons.wikimedia.org/wiki/File:LM_illustration_02-IT.png">source · public domain</a></sub>
    </td>
  </tr>
  <tr>
    <td width="50%" valign="top">
      <img src="assets/examples/steamship_baltic_section.jpg" alt="Cross-section of the steamship Baltic" width="100%"><br>
      <b>Cross section of the steamship “Baltic”.</b> · Level 5<br>
      <sub><code>internet_archive:everettsencyclop00ever:n289</code> · <a href="https://archive.org/details/everettsencyclop00ever/page/n289/mode/1up">source · public domain</a></sub>
    </td>
    <td width="50%" valign="top">
      <img src="assets/examples/hydro_turbine_section.jpg" alt="Sectional hydro turbine with generator above" width="100%"><br>
      <b>Sectional view of a turbine showing the electric generator above.</b> · Level 5<br>
      <sub><code>internet_archive:pickshovelpluckf00bond:n171</code> · <a href="https://archive.org/details/pickshovelpluckf00bond/page/n171/mode/1up">source · public domain</a></sub>
    </td>
  </tr>
  <tr>
    <td width="50%" valign="top">
      <img src="assets/examples/four_cylinder_engine_section.jpg" alt="Four-cylinder internal combustion engine cross-section" width="100%"><br>
      <b>Cross-sectional view of a four-cylinder internal combustion engine.</b> · Level 5<br>
      <sub><code>internet_archive:ourwonderworldal02unse:n145</code> · <a href="https://archive.org/details/ourwonderworldal02unse/page/n145/mode/1up">source · public domain</a></sub>
    </td>
    <td width="50%" valign="top">
      <img src="assets/examples/evans_klepetko_furnace_plate.jpg" alt="Multi-view engineering plate of the Evans-Klepetko furnace" width="100%"><br>
      <b>Evans-Klepetko furnace details.</b> · Level 5<br>
      <sub><code>internet_archive:cu31924004606608:n117</code> · <a href="https://archive.org/details/cu31924004606608/page/n117/mode/1up">source · public domain</a></sub>
    </td>
  </tr>
</table>
The target visual semantics are: a recognizable physical engineered object,
normally hidden internal structure, meaningful component relationships, and an
explanatory technical presentation. Ordinary product photos, software diagrams,
flowcharts, plots, circuit schematics, and decorative technical-looking art are
outside the intended distribution.

## 中文简介

Draw2Explain 面向结构解释型工程图生成，重点覆盖剖视图、剖面图和展示内部
构造的技术插图。发布版包含 **150,720 组图像—标注对**；每条标注
提供中英文描述、英文生成提示词、可见部件与空间/机械关系约束，以及来源、
许可和哈希信息。标注由视觉语言模型生成并通过结构与绑定校验，目前仍属于
“待独立人工图像核验”状态；使用者必须按每条样本自己的许可字段履行署名或
相同方式共享等义务。

## What is included

Each sample has two members with one shared key:

- `.image`: the original encoded image bytes. The original extension and MIME
  type are recorded in metadata.
- `.json`: English/Chinese descriptions, a generation prompt, component and
  relationship contracts, image-grounded evidence, layout attributes, source
  provenance, license metadata, and integrity hashes.

Important fields include `prompt_t2i_en`, `caption_detailed_en`,
`caption_detailed_zh`, `required_elements`, `required_relations`,
`component_evidence`, `relation_evidence`, `visible_text`, `layout_attributes`,
`source_page_url`, `license_tier`, `license_url`, `image_sha256`, and
`caption_prompt_sha256`.

## Loading

```python
from datasets import load_dataset
ds = load_dataset(
    "webdataset",
    data_files={
        "train": "hf://datasets/Tuyuanpeng/Draw2Explain/data/train-*.tar"
    },
    split="train",
    streaming=True,
)
sample = next(iter(ds))
image_bytes = sample["image"]
metadata = sample["json"]
prompt = metadata["prompt_t2i_en"]
```

The neutral `.image` suffix deliberately keeps the WebDataset column schema
uniform across JPEG, PNG, WebP, GIF, TIFF, and BMP sources. Decode the bytes with
Pillow or your training pipeline using `original_image_extension`/`mime_type`.

## Caption construction and status

Captions were produced with Qwen2.5-VL-7B-Instruct at revision
`cc594898137f460bfe9f0759e9844b3ce807cfb5` using deterministic decoding from
the image plus hash-bound source hints. Outputs were normalized only for
schema-preserving format repairs, then checked for exact ID/hash binding, required
field structure, length constraints, component/relation evidence coverage, and
duplicate text. Quality rejections were excluded from this release.

These captions are **machine-generated and pending independent human audit**.
They must not be described as human-verified annotations. The release exposes
this status in `caption_review`:

| Value | Samples | Share |
|---|---:|---:|
| vlm_image_grounded_pending_human_audit | 150,720 | 100.00% |
## Data distribution
### Providers
| Value | Samples | Share |
|---|---:|---:|
| uspto_patents | 58,508 | 38.82% |
| google_patents_us | 52,984 | 35.15% |
| internet_archive | 34,586 | 22.95% |
| wikimedia_commons | 4,180 | 2.77% |
| openverse | 243 | 0.16% |
| library_of_congress | 142 | 0.09% |
| smithsonian_open_access | 56 | 0.04% |
| wellcome_collection | 13 | 0.01% |
| nasa_images | 8 | 0.01% |

### License tiers

| Value | Samples | Share |
|---|---:|---:|
| public_domain | 147,859 | 98.10% |
| sharealike | 1,822 | 1.21% |
| attribution | 541 | 0.36% |
| cc0 | 498 | 0.33% |
### Visual match levels
Level 5 denotes a rich engineering explanation plate, level 4 a strong
object-centric cutaway/cross-section, and level 3 a useful but simpler structural
illustration. `model_audited` identifies accepted records awaiting assignment to
one of the numbered human-review levels.

| Value | Samples | Share |
|---|---:|---:|
| 3 | 97,459 | 64.66% |
| unknown | 35,852 | 23.79% |
| 4 | 17,338 | 11.50% |
| 5 | 71 | 0.05% |

## Rights and attribution

This is a mixed-license dataset, so the repository-level license is `other`.
Rights must be evaluated per sample using `license_tier`, `license_raw`,
`license_url`, `creator`, and `attribution`. The collection includes public-domain,
CC0, attribution-required, and share-alike material. Users are responsible for
following the applicable attribution and share-alike terms; this card is not
legal advice.

## Integrity and benchmark isolation

- Every released image passed decode checks during curation and was SHA-256
  rechecked while the WebDataset shards were built.
- IDs and image hashes are unique in the frozen training manifest.
- A separate **300-case** benchmark is withheld from training.
- Training/benchmark leakage checks cover record ID, exact image hash, source
  family, and confirmed perceptual duplicates.
- `SHARDS.json` records every shard's byte size, sample count, and SHA-256 digest.

The benchmark is not included in this training release. Its reference images and
contracts remain gated on two independent review files before public benchmark
publication; this prevents unreviewed evaluation targets from being presented as
final ground truth.

## Limitations

The distribution is dominated by public-domain patent drawings and therefore is
not a balanced census of all engineering illustration styles. Fine printed text,
small callout numbers, and visually ambiguous parts can be transcribed or named
incorrectly. Source metadata may be incomplete, and machine-generated captions
can contain grounding errors despite schema and evidence checks. Users should run
a task-specific human audit before safety-critical, educational, or commercial
deployment.

## Citation

Paper and citation metadata will be added with the benchmark paper. Until then,
please cite this Hugging Face dataset repository and the exact revision used.

	---
	pretty_name: Draw2Explain
	language:
	- en
	- zh
	license: other
	annotations_creators:
	- machine-generated
	task_categories:
	- text-to-image
	tags:
	- engineering
	- cutaway
	- cross-section
	- technical-illustration
	- webdataset
	size_categories:
	- 100K<n<1M
	configs:
	- config_name: default
	data_files:
	- split: train
	path: data/train-*.tar
	---

	# Draw2Explain

	Draw2Explain is an object-centric engineering illustration dataset for generating
	cutaways, cross-sections, and other structure-explaining technical drawings. The
	released training split contains 150,720 image-caption pairs in
	151 WebDataset shards. Each image keeps its source URL, creator,
	attribution, per-item rights metadata, and SHA-256 digest.

	## Representative examples

	These are actual records from the released training split, not benchmark cases.
	The text below each image is the sample's `caption_short_en`; complete bilingual
	captions, generation prompts, component constraints, and relation constraints are
	stored in the paired `.json` member.

	<table>
	<tr>
	<td width="50%" valign="top">
	<img src="assets/examples/r4360_engine_cutaway.jpg" alt="Pratt & Whitney R-4360 aero engine cutaway" width="100%"><br>
	<b>Pratt & Whitney R-4360 engine cutaway</b> · Level 4<br>
	<sub><code>commons:107825147</code> · <a href="https://commons.wikimedia.org/wiki/File:20-09-072-R_4360.jpg">source · CC0</a></sub>
	</td>
	<td width="50%" valign="top">
	<img src="assets/examples/turbofan_cutaway.gif" alt="Labeled turbofan engine cutaway" width="100%"><br>
	<b>A detailed cutaway of a turbofan engine highlighting key components.</b> · Level 4<br>
	<sub><code>commons:12365146</code> · Richard Wheeler (Zephyris) · <a href="https://commons.wikimedia.org/wiki/File:Turbofan3_Labelled.gif">source · CC BY-SA 3.0</a></sub>
	</td>
	</tr>
	<tr>
	<td width="50%" valign="top">
	<img src="assets/examples/digital_camera_exploded.png" alt="Exploded digital camera with labeled internal components" width="100%"><br>
	<b>Exploded view of a digital camera showing internal components.</b> · Level 4<br>
	<sub><code>commons:12030060</code> · Shigeru23 · <a href="https://commons.wikimedia.org/wiki/File:Digital_camera_cut_model_1.PNG">source · CC BY-SA 3.0</a></sub>
	</td>
	<td width="50%" valign="top">
	<img src="assets/examples/lunar_module_cutaway.png" alt="Lunar Module cutaway with component callouts" width="100%"><br>
	<b>Cutaway illustration of the Lunar Module.</b> · Level 4<br>
	<sub><code>commons:14623428</code> · NASA-MSFC / Adert · <a href="https://commons.wikimedia.org/wiki/File:LM_illustration_02-IT.png">source · public domain</a></sub>
	</td>
	</tr>
	<tr>
	<td width="50%" valign="top">
	<img src="assets/examples/steamship_baltic_section.jpg" alt="Cross-section of the steamship Baltic" width="100%"><br>
	<b>Cross section of the steamship “Baltic”.</b> · Level 5<br>
	<sub><code>internet_archive:everettsencyclop00ever:n289</code> · <a href="https://archive.org/details/everettsencyclop00ever/page/n289/mode/1up">source · public domain</a></sub>
	</td>
	<td width="50%" valign="top">
	<img src="assets/examples/hydro_turbine_section.jpg" alt="Sectional hydro turbine with generator above" width="100%"><br>
	<b>Sectional view of a turbine showing the electric generator above.</b> · Level 5<br>
	<sub><code>internet_archive:pickshovelpluckf00bond:n171</code> · <a href="https://archive.org/details/pickshovelpluckf00bond/page/n171/mode/1up">source · public domain</a></sub>
	</td>
	</tr>
	<tr>
	<td width="50%" valign="top">
	<img src="assets/examples/four_cylinder_engine_section.jpg" alt="Four-cylinder internal combustion engine cross-section" width="100%"><br>
	<b>Cross-sectional view of a four-cylinder internal combustion engine.</b> · Level 5<br>
	<sub><code>internet_archive:ourwonderworldal02unse:n145</code> · <a href="https://archive.org/details/ourwonderworldal02unse/page/n145/mode/1up">source · public domain</a></sub>
	</td>
	<td width="50%" valign="top">
	<img src="assets/examples/evans_klepetko_furnace_plate.jpg" alt="Multi-view engineering plate of the Evans-Klepetko furnace" width="100%"><br>
	<b>Evans-Klepetko furnace details.</b> · Level 5<br>
	<sub><code>internet_archive:cu31924004606608:n117</code> · <a href="https://archive.org/details/cu31924004606608/page/n117/mode/1up">source · public domain</a></sub>
	</td>
	</tr>
	</table>

	The target visual semantics are: a recognizable physical engineered object,
	normally hidden internal structure, meaningful component relationships, and an
	explanatory technical presentation. Ordinary product photos, software diagrams,
	flowcharts, plots, circuit schematics, and decorative technical-looking art are
	outside the intended distribution.

	## 中文简介

	Draw2Explain 面向结构解释型工程图生成，重点覆盖剖视图、剖面图和展示内部
	构造的技术插图。发布版包含 150,720 组图像—标注对；每条标注
	提供中英文描述、英文生成提示词、可见部件与空间/机械关系约束，以及来源、
	许可和哈希信息。标注由视觉语言模型生成并通过结构与绑定校验，目前仍属于
	“待独立人工图像核验”状态；使用者必须按每条样本自己的许可字段履行署名或
	相同方式共享等义务。

	## What is included

	Each sample has two members with one shared key:

	- `.image`: the original encoded image bytes. The original extension and MIME
	type are recorded in metadata.
	- `.json`: English/Chinese descriptions, a generation prompt, component and
	relationship contracts, image-grounded evidence, layout attributes, source
	provenance, license metadata, and integrity hashes.

	Important fields include `prompt_t2i_en`, `caption_detailed_en`,
	`caption_detailed_zh`, `required_elements`, `required_relations`,
	`component_evidence`, `relation_evidence`, `visible_text`, `layout_attributes`,
	`source_page_url`, `license_tier`, `license_url`, `image_sha256`, and
	`caption_prompt_sha256`.

	## Loading

	```python
	from datasets import load_dataset

	ds = load_dataset(
	"webdataset",
	data_files={
	"train": "hf://datasets/Tuyuanpeng/Draw2Explain/data/train-*.tar"
	},
	split="train",
	streaming=True,
	)

	sample = next(iter(ds))
	image_bytes = sample["image"]
	metadata = sample["json"]
	prompt = metadata["prompt_t2i_en"]
	```

	The neutral `.image` suffix deliberately keeps the WebDataset column schema
	uniform across JPEG, PNG, WebP, GIF, TIFF, and BMP sources. Decode the bytes with
	Pillow or your training pipeline using `original_image_extension`/`mime_type`.

	## Caption construction and status

	Captions were produced with Qwen2.5-VL-7B-Instruct at revision
	`cc594898137f460bfe9f0759e9844b3ce807cfb5` using deterministic decoding from
	the image plus hash-bound source hints. Outputs were normalized only for
	schema-preserving format repairs, then checked for exact ID/hash binding, required
	field structure, length constraints, component/relation evidence coverage, and
	duplicate text. Quality rejections were excluded from this release.

	These captions are machine-generated and pending independent human audit.
	They must not be described as human-verified annotations. The release exposes
	this status in `caption_review`:

	\| Value \| Samples \| Share \|
	\|---\|---:\|---:\|
	\| vlm_image_grounded_pending_human_audit \| 150,720 \| 100.00% \|

	## Data distribution

	### Providers

	\| Value \| Samples \| Share \|
	\|---\|---:\|---:\|
	\| uspto_patents \| 58,508 \| 38.82% \|
	\| google_patents_us \| 52,984 \| 35.15% \|
	\| internet_archive \| 34,586 \| 22.95% \|
	\| wikimedia_commons \| 4,180 \| 2.77% \|
	\| openverse \| 243 \| 0.16% \|
	\| library_of_congress \| 142 \| 0.09% \|
	\| smithsonian_open_access \| 56 \| 0.04% \|
	\| wellcome_collection \| 13 \| 0.01% \|
	\| nasa_images \| 8 \| 0.01% \|

	### License tiers

	\| Value \| Samples \| Share \|
	\|---\|---:\|---:\|
	\| public_domain \| 147,859 \| 98.10% \|
	\| sharealike \| 1,822 \| 1.21% \|
	\| attribution \| 541 \| 0.36% \|
	\| cc0 \| 498 \| 0.33% \|

	### Visual match levels

	Level 5 denotes a rich engineering explanation plate, level 4 a strong
	object-centric cutaway/cross-section, and level 3 a useful but simpler structural
	illustration. `model_audited` identifies accepted records awaiting assignment to
	one of the numbered human-review levels.

	\| Value \| Samples \| Share \|
	\|---\|---:\|---:\|
	\| 3 \| 97,459 \| 64.66% \|
	\| unknown \| 35,852 \| 23.79% \|
	\| 4 \| 17,338 \| 11.50% \|
	\| 5 \| 71 \| 0.05% \|

	## Rights and attribution

	This is a mixed-license dataset, so the repository-level license is `other`.
	Rights must be evaluated per sample using `license_tier`, `license_raw`,
	`license_url`, `creator`, and `attribution`. The collection includes public-domain,
	CC0, attribution-required, and share-alike material. Users are responsible for
	following the applicable attribution and share-alike terms; this card is not
	legal advice.

	## Integrity and benchmark isolation

	- Every released image passed decode checks during curation and was SHA-256
	rechecked while the WebDataset shards were built.
	- IDs and image hashes are unique in the frozen training manifest.
	- A separate 300-case benchmark is withheld from training.
	- Training/benchmark leakage checks cover record ID, exact image hash, source
	family, and confirmed perceptual duplicates.
	- `SHARDS.json` records every shard's byte size, sample count, and SHA-256 digest.

	The benchmark is not included in this training release. Its reference images and
	contracts remain gated on two independent review files before public benchmark
	publication; this prevents unreviewed evaluation targets from being presented as
	final ground truth.

	## Limitations

	The distribution is dominated by public-domain patent drawings and therefore is
	not a balanced census of all engineering illustration styles. Fine printed text,
	small callout numbers, and visually ambiguous parts can be transcribed or named
	incorrectly. Source metadata may be incomplete, and machine-generated captions
	can contain grounding errors despite schema and evidence checks. Users should run
	a task-specific human audit before safety-critical, educational, or commercial
	deployment.

	## Citation

	Paper and citation metadata will be added with the benchmark paper. Until then,
	please cite this Hugging Face dataset repository and the exact revision used.