Datasets:
image imagewidth (px) 1.15k 3.44k | image_id stringlengths 11 17 | book_id stringclasses 44
values | width int32 1.15k 3.44k | height int32 1.93k 5.29k | objects dict | columns dict | segments dict |
|---|---|---|---|---|---|---|---|
100241706_00005_1 | 100241706 | 2,392 | 3,874 | {
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[
"COL0001",
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]
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} | |
100241706_00005_2 | 100241706 | 2,416 | 3,874 | {
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"column_ids": [
[
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]
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} | |
100241706_00006_1 | 100241706 | 2,362 | 3,886 | {
"bbox": [
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"column_ids": [
[
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"COL0004",
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]
]
} | |
100241706_00007_2 | 100241706 | 2,392 | 3,868 | {
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[
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0.08695652335... | |
100241706_00008_1 | 100241706 | 2,350 | 3,874 | {
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],
"column_ids": [
[
"COL0001",
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"COL0004",
"COL0005",
"COL0006",
"COL0007",
... | |
100241706_00008_2 | 100241706 | 2,410 | 3,868 | {
"bbox": [
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],
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0.8060166239738464,
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0.04... | {
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],
[
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],
[
0.6091286540031433,
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0.0663... | {
"bbox": [
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]
],
"segment_id": [
"SEG0001"
],
"column_ids": [
[
"COL0001",
"COL0002",
"COL0003",
"COL0004",
"COL0005",
"COL0006",
"COL0007",
"... | |
100241706_00009_1 | 100241706 | 2,362 | 3,880 | {
"bbox": [
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],
[
0.8803979754447937,
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0.... | {
"bbox": [
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],
[
0.6820490956306458,
0.5931701064109802,
0.06096... | {
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]
],
"segment_id": [
"SEG0001"
],
"column_ids": [
[
"COL0001",
"COL0002",
"COL0003",
"COL0004",
"COL0005",
"COL0006",
"COL0007",
... | |
100241706_00009_2 | 100241706 | 2,374 | 3,880 | {
"bbox": [
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],
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],
[
0.8125526309013367,
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0.026... | {
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0.069924... | {
"bbox": [],
"segment_id": [],
"column_ids": []
} | |
100241706_00010_1 | 100241706 | 2,369 | 3,872 | {
"bbox": [
[
0.8862389326095581,
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0.0426340214908123,
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],
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0.03125
],
[
0.7777543067932129,
0.25038740038871765,
0.041789785027503... | {
"bbox": [
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0.6766568422317505,
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0.05825... | {
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"segment_id": [],
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} | |
100241706_00010_2 | 100241706 | 2,380 | 3,868 | {
"bbox": [
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0.8132352828979492,
0.3453981280326843,
0.0306... | {
"bbox": [
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[
0.7142857313156128,
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0.6791623830795288
],
[
0.6096638441085815,
0.5963029861450195,
0.0588235... | {
"bbox": [],
"segment_id": [],
"column_ids": []
} | |
100241706_00011_1 | 100241706 | 2,350 | 3,867 | {
"bbox": [
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0.8797872066497803,
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0.0... | {
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0.7755318880081177,
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0.6721276640892029,
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0.05829... | {
"bbox": [],
"segment_id": [],
"column_ids": []
} | |
100241706_00011_2 | 100241706 | 2,386 | 3,874 | {
"bbox": [
[
0.8093042969703674,
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0.8067895770072937,
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[
0.8072087168693542,
0.3395715057849884,
0.040... | {
"bbox": [
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],
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0.7085079550743103,
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0.6817243099212646
],
[
0.608340322971344,
0.5983479619026184,
0.0616093... | {
"bbox": [],
"segment_id": [],
"column_ids": []
} |
End of preview. Expand in Data Studio
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 mappingid2label.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).
- Provider: National Institute of Japanese Literature and other institutions (国文学研究資料館ほか所蔵)
- Processing: ROIS-DS Center for Open Data in the Humanities (CODH)
- DOI: 10.20676/00000340
- Website: https://codh.rois.ac.jp/char-shape/
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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