Datasets:
image imagewidth (px) 1.54k 1.54k | annotation_id stringclasses 5 values | image_width int32 1.54k 1.54k | image_height int32 2.05k 2.05k | question stringclasses 5 values | answers listlengths 1 4 | answer_bbox listlengths 4 4 | document_type stringclasses 1 value | question_type stringclasses 1 value | language stringclasses 1 value |
|---|---|---|---|---|---|---|---|---|---|
3654e497-1688-45ce-a9c4-caa6af357637 | 1,536 | 2,048 | 登録番号は?(番号のみ) | [
"T2011001045931"
] | [
0.3779911976794092,
0.14914054370505148,
0.7824401297609048,
0.1756825048728996
] | RECEIPT | EXTRACTIVE | ja | |
00bf696a-5a05-4c1e-9d82-006e6b45c43c | 1,536 | 2,048 | レシートの日付は? | [
"2026/01/22"
] | [
0.30384222679780176,
0.255308388376444,
0.7217727899486803,
0.29322547575908425
] | RECEIPT | EXTRACTIVE | ja | |
c0064639-a0f3-4f7e-bdcb-2f3670715576 | 1,536 | 2,048 | 購入品目 (上から最大10) は? | [
"デーリーヨーグルッペ200ml",
"レジ袋S",
"高菜明太おにぎり",
"味付海苔海老マヨネーズ"
] | [
0.266767741356998,
0.3665318446988553,
0.779069721993559,
0.4701718835447385
] | RECEIPT | EXTRACTIVE | ja | |
b07c4149-1a75-42bf-a5e9-9f000aca8186 | 1,536 | 2,048 | 合計金額 (10%対象) は? | [
"3"
] | [
0.3510279355406429,
0.5194640971421708,
0.7470508482037738,
0.5472699612227736
] | RECEIPT | EXTRACTIVE | ja | |
1434b218-2ab2-4fdc-b065-0300851784f0 | 1,536 | 2,048 | 合計金額 (8%対象) は? | [
"525"
] | [
0.3695651782610447,
0.5700202136523578,
0.7537916637384655,
0.6028816893839792
] | RECEIPT | EXTRACTIVE | ja |
Business Document VQA Dataset
Visual Question Answering dataset for business document OCR evaluation.
Version: v1.0.1
- Annotations: 5
- Images: 1
- Languages: ja
- Document Types: RECEIPT
Schema
| Field | Type | Description |
|---|---|---|
| image | Image | Document image |
| annotation_id | string | Annotation ID |
| question | string | Question about the document |
| answers | list[string] | Correct answers |
| answer_bbox | list[float] | Bounding box [x0, y0, x1, y1] (0-1 range) |
| document_type | string | Type of business document |
| question_type | string | Category of question |
| language | string | ISO 639-1 language code |
Usage
from datasets import load_dataset
ds = load_dataset("icoxfog417/biz-doc-vqa-test")
print(ds["train"][0])
# Image will be automatically loaded as PIL.Image
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