kaupane/chinese-painting-collection

Chinese Painting Collection

91,093 images of Chinese paintings with VLM captions (a captions list of one to three texts per image, Chinese and English, short and long), calligraphy OCR transcriptions, view-type classification, and foreign-object detection with a final crop box per image. The image column is already cropped to the artwork; image_original keeps the untouched photograph.

Sources

Component	Source	Images	Image license
npm_tw_c0–npm_tw_c3	National Palace Museum (Taipei) Open Data	86,321	Taiwan Open Government Data License v1 (attribution required)
met_china	The Metropolitan Museum of Art Open Access	1,186	CC0
fsg	Smithsonian Freer Gallery of Art / National Museum of Asian Art	1,782	CC0
princeton	Princeton University Art Museum	1,631	Check source terms; intended for research use
aic_china	Art Institute of Chicago	173	CC0

The four NPM components are quarterly shards of the NPM Open Data release (c0–c3), deduplicated and filtered to usable views. The museum components were harvested through each institution's public API and filtered to China-related Chinese-painting objects.

Production pipeline

1. Harvest — images and tombstone metadata (title, artist, date, object number) fetched from the source APIs / open-data packages.
2. Rule-based cleaning — removal of non-artwork views: rolled scrolls, installation shots, covers, damaged or unreadable images, and near-duplicates. Only full, mounted, and detail views are kept.
3. VLM labeling (gemini-3.5-flash-lite) — for every kept image:
   • caption_zh / caption_en: free-form descriptions of the scene, composition, style, and medium, instructed to avoid boilerplate openings.
   • ocr_text: transcription of visible Chinese calligraphy (inscriptions, colophons) and a description of seal impressions where present.
   • view_type: full (whole artwork), mounted (artwork with mounting visible), or detail (close-up crop).
   • culture: chinese (88,586), japanese (2,253), korean (82), western (10), other (20), uncertain (142). Non-Chinese items are a small minority kept for completeness; filter on this field if unwanted.
4. Foreign-object detection — museum photography of NPM flatworks often includes color charts, rulers, accession labels, or the surrounding desk. A detection pass lists what it sees (artifacts: label, color_chart, ruler, desk, glare, other; non-empty for 39,164 images) and returns a crop box for the artwork.
5. Second cropping round — for the images the first pass flagged, the model was shown the already-cropped view and asked for the artwork box inside it. The two boxes are composed into one box in the coordinates of the original photograph.
6. Third cropping round (DeepSeek V4.1 Flash, grounding-verified before scaling) — every row still flagged with color_chart was re-detected, and the new box was validated against the crop it produces. Boxes that changed invalidated the captions written on the old crop, so those rows were re-captioned from the new crop (see step 8). All rows with any artifact had their short zh/en captions (written on the uncropped or first-crop view) discarded.
7. Text folded into the captions — the transcription from step 3 was moved into the captions as a trailing block, because the caption is what a text-to-image model consumes. Catalogue-label lines (accession numbers, album titles) were dropped in the process, since the crop removes that strip from the training view. ocr_text is kept as the raw field.
8. Long captions and re-captions (DeepSeek V4.1 Flash, reasoning disabled) — 59,850 images received a much longer caption written on the cropped view (what a trainer sees), and the 38,741 rows whose crop changed in round 6 were re-captioned the same way. 616 candidates were discarded for repeating a sentence; length alone was never a reason to discard.
9. Caption aggregation — all surviving captions of a row (short zh, short en, long) are shipped as one captions: list[str]; the separate caption_zh / caption_en / caption_long columns no longer exist. Rows carry 1 caption (39,099), 2 (31,182), or 3 (20,747); 65 rows have none left after the round-6 discards and are kept for their metadata. Caption lengths in characters: median 825, p90 3,181, max 12,992.

Data format

Parquet shards under default/train/part-*.parquet (374 shards, zstd), one row per image, plus a small metadata/metadata.parquet with everything except the image bytes. Both image and image_original use the struct<bytes: binary, path: string> layout of the datasets Image feature, so every image can be previewed in the dataset viewer:

from datasets import load_dataset
ds = load_dataset("kaupane/chinese-painting-collection", split="train")
ds[0]["image"].size          # the cropped artwork view
ds[0]["image_original"].size # the untouched photograph
ds[0]["captions"]            # list of 1-3 captions (zh/en, short and long)

Columns: image (cropped), image_original, captions (list of strings), bbox (list of four floats), artifacts (list of strings), image_id, shard, source, object_no, title, artist, category, culture, view_type, ocr_text.

bbox is a normalised [x_min, y_min, x_max, y_max] in per-mille coordinates (0–1000) of the original photograph, and image is exactly that crop applied (JPEG quality 95). bbox is present for 39,591 rows; an empty bbox means the whole frame is the artwork. previews/ shows twelve before/after pairs so the effect of the crop can be seen without loading the data.

View-type distribution: mounted 43,306 · full 36,150 · detail 11,637.

Suggested filtering

• Training on artwork only: use the image column directly — the crop is already applied. image_original + bbox are there if you want a different crop policy.
• Cleanest subset: drop rows whose artifacts is non-empty.
• Exclude mounting borders: keep view_type == "full" or "detail".
• Chinese paintings only: keep culture == "chinese".
• Long-text training: longer entries in captions are the long captions; short zh/en captions survive only on rows with no detected artifacts.

Caveats

• Captions and OCR are machine-generated by lightweight VLMs; expect occasional errors, especially in cursive-script calligraphy transcription. Where a transcription is quoted in a caption, it is the model's reading, not a scholarly edition.
• The crop box is the model's answer to "where is the artwork". It usually removes the color chart, ruler and label strip, and in most cases leaves a thin strip of the photograph's background along one edge.
• detail views are close-ups of larger works and may duplicate content present in full views of the same object (same object_no).
• 23 rows have flagged artifacts but no reliable box; they are shipped uncropped. 65 rows have no captions after round-6 discards.

Licensing

Images retain the licenses of their sources (see table above). The NPM portion requires attribution to 國立故宮博物院 (National Palace Museum, Taipei) under the Taiwan Open Government Data License v1. Annotations (captions, OCR, classifications, boxes) are released under CC-BY-4.0.