jaddai/openart-portraits-classical

OpenArt — Portraits & the Classical Figure

openart-portraits-classical is the portraits classical subject collection of the OpenArt family of open, public-domain art datasets: 28,011 works (13,868 paintings/illustrations · 13,970 photographed objects · 173 unclassified), each paired with a structured VLM caption plus medium, attribution and inscription metadata.

The human figure and portraiture across the full range of media — painted and drawn portraits alongside photographic portraits, portrait textiles and costume, engraved and sculpted likenesses. A near-even split between 2-D portraiture and photographed/object portraiture.

Dataset Description

OpenArt draws from the open-access APIs of major museums and libraries (the Metropolitan Museum of Art, Rijksmuseum, Cleveland Museum of Art, Art Institute of Chicago, Smithsonian, and other open-access museum/library sources). Unlike the painting-only OpenBrush corpus, each OpenArt subject collection is mixed-medium: it contains both 2-D art (paintings, prints, drawings) and photographs of three-dimensional objects (sculpture, ceramics, metalwork, textiles). A brand column splits every row so you can take exactly the slice you want.

Key features

• —28,011 public-domain images, all passing a rights_status: safe gate
• —Structured v2 captions — 9 semantic sections per image (same schema as OpenBrush)
• —`brand` split — openbrush (13,868, 2-D art) vs openartifacts (13,970, photographed objects)
• —Medium-tagged and attribution-aware: 6,648 rows carry a named artist; 5,600 of those are signature-verified against the pixels
• —CC0-1.0 — public-domain dedication, no rights reserved (every row is museum CC0 / Smithsonian Open Access)
• —Full provenance per row: source, landing_page, sha256

The OpenArt brand model

OpenArt is an umbrella with two medium-based brands plus subject collections:

• —`openbrush` — 2-D art (paintings, prints, drawings). The standalone OpenBrush datasets are the painting-pure expression of this brand.
• —`openartifacts` — photographs of real objects (sculpture, ceramics, metalwork, textiles).
• —`openart-<subject>` — like this one: a subject collection that mixes both brands. Use the brand column to separate them.

Dataset structure

Caption structure

Each image has a v2 structured caption (identical schema to OpenBrush). **STYLE:** maps to the style_description column; the other eight map to like-named columns:

**TAGS:** bronze, animal, lion, relief, patina, profile_view...

**SUBJECT:** A crouching lion modelled in bronze, head turned to the left...

**ACTION:** The animal is poised mid-stride, one forepaw lifted...

**SETTING:** Isolated object study against a neutral museum ground...

**MOOD:** Watchful, taut, restrained power...

**STYLE:** Cast bronze with chased detail and a dark green patina...

**LIGHTING:** Raking light from the upper left picks out the mane...

**COLOR:** Warm metallic browns and greens over a grey field...

**COMPOSITION:** Centered profile, the lifted paw breaking the silhouette...

Captioning methodology

Captions were generated with a two-model vision pipeline (distinct from OpenBrush's Qwen3-VL):

1. 1.Caption + routing — Gemma 4 31B (google/gemma-4-31b-it): the full 9-section caption, identity-preserving subject description, inscription reading, and off-target routing (non-art / contaminated images were flagged and removed).
2. 2.Verification — Gemini 3 Flash (google/gemini-3-flash-preview): a targeted second pass that re-grounded medium, attribution (artist / signature) and inscription claims against the actual pixels. signature_verified / inscription_verified come from this pass.

Tags were then normalized (lowercase, underscore, intensity/suffix stripping, *_lighting → *_light) to match the OpenBrush tag conventions.

Provenance & licensing

License: CC0 1.0 — public-domain dedication, no rights reserved (citation appreciated, not required).

Every image is public domain / CC0, pulled from museum & library open-access programs and verified at ingest (rights_status: safe):

• —cc0 (the Met, Rijksmuseum, Cleveland, Art Institute of Chicago) — 24,757
• —Smithsonian Open Access — itself a CC0 dedication — 3,254

Aggregator-sourced rows (Europeana, Wikimedia), whose upstream rights are less certain, were removed so the CC0 dedication holds for every row. Faithful photographic reproductions of 2-D public-domain works carry no new copyright (Bridgeman Art Library v. Corel Corp.); object photographs are released under the holding institution's CC0 / open-access program. Each row keeps source, landing_page and sha256 for traceability.

Statistics

Top media: textile (3,237), photograph (3,229), drawing (2,368), engraving (2,150), etching (1,873), oil painting (1,839), sculpture (1,810), woodcut (1,023)

Top tags: portrait, monochrome, textile, man, woman, 19th_century, engraving, clothing, historical_clothing, embroidery, male, lace, dress, mannequin, jewelry

Top sources: met openaccess (17,980), rijksmuseum oai (6,044), smithsonian art (3,254), aic (366), cleveland (184)

Usage

from datasets import load_dataset

ds = load_dataset("jaddai/openart-portraits-classical", split="train")
print(len(ds))  # 28,011

# Just the 2-D paintings/prints (the openbrush brand)
paintings = ds.filter(lambda r: r["brand"] == "openbrush")

# Just photographed objects (the openartifacts brand)
objects = ds.filter(lambda r: r["brand"] == "openartifacts")

# Only trust attribution where the signature was verified
attributed = ds.filter(lambda r: r["signature_verified"])

# Filter by medium
sculpture = ds.filter(lambda r: r["medium"] == "sculpture")

Use cases

• —Image-generation training — fine-tune diffusion models on a specific medium or subject
• —VLM fine-tuning — object/art description grounded in museum provenance
• —Classification — medium, brand, or subject recognition
• —Cross-medium study — compare how a subject is treated in paint vs. in three dimensions

Limitations

• —Captions are AI-generated best-effort metadata, not curatorial ground truth.
• —Attribution is authoritative only where signature_verified = true. Other named artists are scholarly/unverified catalog attributions.
• —Inscriptions: trust inscription_verified = true; some claimed inscriptions could not be re-confirmed legibly, and catalog labels/accession numbers can appear as inscription text.
• —Source-institution and Western-canon collection biases are present.

Citation

@dataset{openart_portraits_classical,
  title={OpenArt: Portraits & the Classical Figure},
  author={jaddai},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/jaddai/openart-portraits-classical},
  note={Subject collection of the OpenArt family}
}

<!-- OPENART-FAMILY:START -->

Related datasets

Part of the OpenArt family of open, public-domain art datasets — the whole family is CC0-1.0 (public-domain dedication, no rights reserved; citation appreciated, not required). License shown beside each name for clarity.

OpenBrush — 2-D fine art (paintings, prints, drawings), WikiArt-sourced (curated public domain), CC0:

• —openbrush — flagship — 75,313 public-domain paintings · CC0
• —openbrush-anonymous-masters — unattributed old masters · CC0
• —openbrush-impressionism — Impressionist movement · CC0
• —openbrush-landscapes — landscape genre · CC0
• —openbrush-portraits — portrait genre · CC0
• —openbrush-religious-art — religious / biblical · CC0
• —openbrush-renaissance — Renaissance period · CC0
• —openbrush-baroque — Baroque period · CC0
• —openbrush-impressionist-landscapes — Impressionist landscapes (cross-cut) · CC0
• —openbrush-van-gogh — Vincent van Gogh · CC0
• —openbrush-ukiyo-e — Japanese woodblock prints · CC0
• —openbrush-monet — Claude Monet · CC0
• —openbrush-rembrandt — Rembrandt · CC0
• —openbrush-renoir — Pierre-Auguste Renoir · CC0

OpenArt — mixed-medium subject collections (paintings + photographed objects), museum/library-sourced, CC0:

• —openart-animals — animals & the natural world · CC0
• —openart-items-artifacts — human-made objects & decorative arts · CC0
• —openart-mythic-creatures — mythological & fantastical beings · CC0
• —openart-painterly-foundations — painting-forward fine-art core · CC0

Feedback & collaboration

I'm always open to feedback and to suggestions for other datasets worth publishing — open a discussion on this repo or reach out on the Hub. I'm also open to collaborations with others in the community. <!-- OPENART-FAMILY:END -->

Acknowledgments

• —Images sourced from the open-access programs of the Met, Rijksmuseum, Cleveland Museum of Art, Art Institute of Chicago, Smithsonian, and other open-access museum/library sources.
• —Captions generated by Gemma 4 31B; attribution & inscription verification by Gemini 3 Flash.