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100241706_00005_1
100241706
2,392
3,874
{ "bbox": [ [ 0.8827341198921204, 0.2590346038341522, 0.05058528482913971, 0.030201341956853867 ], [ 0.8739548325538635, 0.3202116787433624, 0.0681438148021698, 0.04052658751606941 ], [ 0.8722826242446899, 0.3613835871219635, 0.0229...
{ "bbox": [ [ 0.8743728995323181, 0.584537923336029, 0.08068561553955078, 0.681208074092865 ], [ 0.7362040281295776, 0.5804078578948975, 0.07692307978868484, 0.6760454177856445 ], [ 0.6143394708633423, 0.5731801986694336, 0.08821070...
{ "bbox": [ [ 0.5369983315467834, 0.5832473039627075, 0.7554348111152649, 0.6837893724441528 ] ], "segment_id": [ "SEG0001" ], "column_ids": [ [ "COL0001", "COL0002", "COL0003", "COL0004", "COL0005", "COL0006" ] ] }
100241706_00005_2
100241706
2,416
3,874
{ "bbox": [ [ 0.7785596251487732, 0.26690760254859924, 0.0678807944059372, 0.04026845470070839 ], [ 0.7901490330696106, 0.32253485918045044, 0.06622516363859177, 0.036396488547325134 ], [ 0.7855960130691528, 0.37622612714767456, 0.0...
{ "bbox": [ [ 0.784147322177887, 0.5757614970207214, 0.07905629277229309, 0.6579762697219849 ], [ 0.6637003421783447, 0.5764068365097046, 0.08485099673271179, 0.6597831845283508 ], [ 0.5260761380195618, 0.5782137513160706, 0.0794702...
{ "bbox": [ [ 0.45923012495040894, 0.5862157940864563, 0.7288907170295715, 0.6835312247276306 ] ], "segment_id": [ "SEG0001" ], "column_ids": [ [ "COL0001", "COL0002", "COL0003", "COL0004", "COL0005", "COL0006" ] ] }
100241706_00006_1
100241706
2,362
3,886
{ "bbox": [ [ 0.8604995608329773, 0.26891404390335083, 0.06392887234687805, 0.04426145181059837 ], [ 0.8590177893638611, 0.32822954654693604, 0.06096528470516205, 0.03731343150138855 ], [ 0.8655800223350525, 0.38407102227211, 0.0639...
{ "bbox": [ [ 0.8592294454574585, 0.5864642262458801, 0.08001693338155746, 0.6793618202209473 ], [ 0.729043185710907, 0.5811888575553894, 0.08382726460695267, 0.6662377715110779 ], [ 0.5984335541725159, 0.5814462304115295, 0.0901778...
{ "bbox": [ [ 0.518204927444458, 0.5828615427017212, 0.7620660662651062, 0.6865671873092651 ] ], "segment_id": [ "SEG0001" ], "column_ids": [ [ "COL0001", "COL0002", "COL0003", "COL0004", "COL0005", "COL0006" ] ] }
100241706_00007_2
100241706
2,392
3,868
{ "bbox": [ [ 0.8005852699279785, 0.26357290148735046, 0.07023411244153976, 0.04317476600408554 ], [ 0.8005852699279785, 0.31217682361602783, 0.045150503516197205, 0.04317476600408554 ], [ 0.7991220951080322, 0.3571613132953644, 0.0...
{ "bbox": [ [ 0.8047658801078796, 0.56540846824646, 0.07859531790018082, 0.6468459367752075 ], [ 0.7071488499641418, 0.5466649532318115, 0.0798494964838028, 0.4051189124584198 ], [ 0.6105769276618958, 0.29782834649086, 0.07399665564...
{ "bbox": [ [ 0.7556437849998474, 0.56540846824646, 0.17683947086334229, 0.6468459367752075 ], [ 0.6105769276618958, 0.29782834649086, 0.0739966556429863, 0.11375387758016586 ], [ 0.610785961151123, 0.6637797355651855, 0.08695652335...
100241706_00008_1
100241706
2,350
3,874
{ "bbox": [ [ 0.8789361715316772, 0.26264843344688416, 0.03957446664571762, 0.02555498108267784 ], [ 0.8814893364906311, 0.281879186630249, 0.05234042555093765, 0.01135776937007904 ], [ 0.8814893364906311, 0.30924108624458313, 0.039...
{ "bbox": [ [ 0.8819149136543274, 0.4705730378627777, 0.06425531953573227, 0.44140422344207764 ], [ 0.7799999713897705, 0.3581569492816925, 0.04595744609832764, 0.21140938997268677 ], [ 0.6797872185707092, 0.5811822414398193, 0.0659...
{ "bbox": [ [ 0.5248936414718628, 0.5858286023139954, 0.7782979011535645, 0.6925657987594604 ] ], "segment_id": [ "SEG0001" ], "column_ids": [ [ "COL0001", "COL0002", "COL0003", "COL0004", "COL0005", "COL0006", "COL0007", ...
100241706_00008_2
100241706
2,410
3,868
{ "bbox": [ [ 0.8029045462608337, 0.25064632296562195, 0.039834026247262955, 0.011633919551968575 ], [ 0.8064315319061279, 0.2854188084602356, 0.04522821679711342, 0.0372285433113575 ], [ 0.8060166239738464, 0.3669855296611786, 0.04...
{ "bbox": [ [ 0.8047717809677124, 0.4831954538822174, 0.05186722055077553, 0.47673216462135315 ], [ 0.7093361020088196, 0.48422956466674805, 0.06929460912942886, 0.4746639132499695 ], [ 0.6091286540031433, 0.5891934037208557, 0.0663...
{ "bbox": [ [ 0.4533194899559021, 0.591261625289917, 0.7547717690467834, 0.6964839696884155 ] ], "segment_id": [ "SEG0001" ], "column_ids": [ [ "COL0001", "COL0002", "COL0003", "COL0004", "COL0005", "COL0006", "COL0007", "...
100241706_00009_1
100241706
2,362
3,880
{ "bbox": [ [ 0.8848433494567871, 0.26481959223747253, 0.04064352065324783, 0.02654639258980751 ], [ 0.8787044882774353, 0.29085052013397217, 0.03767993301153183, 0.025515463203191757 ], [ 0.8803979754447937, 0.32203608751296997, 0....
{ "bbox": [ [ 0.8814563751220703, 0.5930412411689758, 0.058425065129995346, 0.6829897165298462 ], [ 0.7783657908439636, 0.5931701064109802, 0.06308213621377945, 0.6796391606330872 ], [ 0.6820490956306458, 0.5931701064109802, 0.06096...
{ "bbox": [ [ 0.5222269296646118, 0.5930412411689758, 0.7768840193748474, 0.6829897165298462 ] ], "segment_id": [ "SEG0001" ], "column_ids": [ [ "COL0001", "COL0002", "COL0003", "COL0004", "COL0005", "COL0006", "COL0007", ...
100241706_00009_2
100241706
2,374
3,880
{ "bbox": [ [ 0.8102359175682068, 0.2786082327365875, 0.03580455109477043, 0.0402061864733696 ], [ 0.8142375946044922, 0.31842783093452454, 0.03875315934419632, 0.037371132522821426 ], [ 0.8125526309013367, 0.3573453724384308, 0.026...
{ "bbox": [ [ 0.8192923069000244, 0.5960051417350769, 0.059814658015966415, 0.675000011920929 ], [ 0.7243049740791321, 0.5965206027030945, 0.06781803071498871, 0.6775773167610168 ], [ 0.6187868714332581, 0.5949742197990417, 0.069924...
{ "bbox": [], "segment_id": [], "column_ids": [] }
100241706_00010_1
100241706
2,369
3,872
{ "bbox": [ [ 0.8862389326095581, 0.2707902789115906, 0.0426340214908123, 0.02763429842889309 ], [ 0.8830730319023132, 0.3007489740848541, 0.027015618979930878, 0.03125 ], [ 0.7777543067932129, 0.25038740038871765, 0.041789785027503...
{ "bbox": [ [ 0.8862389326095581, 0.28667354583740234, 0.0426340214908123, 0.05940082669258118 ], [ 0.7756437063217163, 0.5875516533851624, 0.07133811712265015, 0.6880165338516235 ], [ 0.6766568422317505, 0.5949121713638306, 0.05825...
{ "bbox": [], "segment_id": [], "column_ids": [] }
100241706_00010_2
100241706
2,380
3,868
{ "bbox": [ [ 0.8149159550666809, 0.27598240971565247, 0.0432773120701313, 0.03541881963610649 ], [ 0.8128151297569275, 0.3112719655036926, 0.0357142873108387, 0.033092036843299866 ], [ 0.8132352828979492, 0.3453981280326843, 0.0306...
{ "bbox": [ [ 0.8128151297569275, 0.5948810577392578, 0.05504201725125313, 0.6732161045074463 ], [ 0.7142857313156128, 0.595785915851593, 0.05378151312470436, 0.6791623830795288 ], [ 0.6096638441085815, 0.5963029861450195, 0.0588235...
{ "bbox": [], "segment_id": [], "column_ids": [] }
100241706_00011_1
100241706
2,350
3,867
{ "bbox": [ [ 0.8823404312133789, 0.24359968304634094, 0.048085104674100876, 0.013447117060422897 ], [ 0.8848935961723328, 0.28161364793777466, 0.0770212784409523, 0.04551331698894501 ], [ 0.8797872066497803, 0.3140677511692047, 0.0...
{ "bbox": [ [ 0.8848935961723328, 0.5817170739173889, 0.0770212784409523, 0.6896819472312927 ], [ 0.7755318880081177, 0.44504785537719727, 0.057446807622909546, 0.3785880506038666 ], [ 0.6721276640892029, 0.5832687020301819, 0.05829...
{ "bbox": [], "segment_id": [], "column_ids": [] }
100241706_00011_2
100241706
2,386
3,874
{ "bbox": [ [ 0.8093042969703674, 0.2719411551952362, 0.04694048687815666, 0.04052658751606941 ], [ 0.8067895770072937, 0.3101445436477661, 0.05029337853193283, 0.028136292472481728 ], [ 0.8072087168693542, 0.3395715057849884, 0.040...
{ "bbox": [ [ 0.8074182868003845, 0.5937016010284424, 0.06663872301578522, 0.684047520160675 ], [ 0.7085079550743103, 0.5953794717788696, 0.052388936281204224, 0.6817243099212646 ], [ 0.608340322971344, 0.5983479619026184, 0.0616093...
{ "bbox": [], "segment_id": [], "column_ids": [] }
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Kuzushiji Dataset (YOLO format)

This dataset contains page images from historical Japanese documents (Kotenseki) with character-level bounding box annotations for Kuzushiji (cursive Japanese) recognition.

Dataset Structure

{
    "image": Image(),                    # Page image
    "image_id": str,                     # Image ID (e.g., 100241706_00004_2)
    "book_id": str,                      # Book ID (e.g., 100241706)
    "width": int,                        # Image width in pixels
    "height": int,                       # Image height in pixels
    "objects": {
        "bbox": List[List[float]],       # Bounding boxes ([x_center, y_center, width, height] (normalized 0-1))
        "category": List[str],           # Unicode strings (e.g., U+3042)
        "category_id": List[int],        # Category IDs
        "char": List[str],               # Actual characters (e.g., あ)
    },
    "columns": {
        "bbox": List[List[float]],       # Column boxes
        "column_id": List[str],          # Column IDs (e.g., COL0001)
        "char_ids": List[List[str]],     # Member Char IDs
        "segment_id": List[str],         # Parent Segment IDs if available
    },
    "segments": {
        "bbox": List[List[float]],       # Segment boxes
        "segment_id": List[str],         # Segment IDs (e.g., SEG0001)
        "column_ids": List[List[str]],   # Member Column IDs
    }
}

Bounding Box Formats

Format Description Normalized
COCO [x_min, y_min, width, height] No (pixels)
YOLO [x_center, y_center, width, height] Yes (0-1)

Usage

from datasets import load_dataset
import json

dataset = load_dataset("Kotomiya07/kuzushiji-dataset-yolo")

# Access first example
example = dataset["train"][0]
print(f"Image ID: {example['image_id']}")
print(f"Number of characters: {len(example['objects']['bbox'])}")

# Load label mappings
from huggingface_hub import hf_hub_download

label2id_path = hf_hub_download(
    repo_id="Kotomiya07/kuzushiji-dataset-yolo",
    filename="label2id.json",
    repo_type="dataset"
)
with open(label2id_path) as f:
    label2id = json.load(f)

print(f"Number of categories: {len(label2id)}")

Label Mappings

This dataset includes the following mapping files:

  • label2id.json: Unicode string (e.g., "U+3042") to category ID mapping
  • id2label.json: Category ID to Unicode string mapping

License

This dataset is licensed under CC BY-SA 4.0.

Data Source

This dataset is derived from the 日本古典籍くずし字データセット (Japanese Historical Character Dataset).

Citation

If you use this dataset, please cite:

『日本古典籍くずし字データセット』(国文研ほか所蔵/CODH加工)doi:10.20676/00000340

English:

"Japanese Historical Character Dataset" (Owned by NIJL and others, Processed by CODH) doi:10.20676/00000340

Acknowledgments

Data provided by: ROIS-DS Center for Open Data in the Humanities (人文学オープンデータ共同利用センター)

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