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---
language: ru
license: mit
task_categories:
- image-to-text
- document-question-answering
- visual-document-retrieval
size_categories:
- 1K<n<10K
annotations_creators:
- human
- machine-assisted
---
# Russian Receipts OCR (Semantic)
## Overview
This repository contains a dataset of Russian retail receipts with semantic OCR annotations.
⚠️ **Important note**
This repository is used primarily as a **data storage and distribution location**.
The dataset is consumed by **external inference, evaluation and training pipelines** and is **not intended to be loaded directly via `datasets.load_dataset()`** without a custom loader.
---
## Description
Each sample consists of:
- a receipt image
- a corresponding JSON annotation with structured OCR information
The dataset is designed for:
- OCR and document understanding
- semantic information extraction
- evaluation of receipt parsing pipelines
---
## Dataset structure
The data is organized as a simple and explicit file-based structure:
images/
├── train/
├── validation/
└── test/
annotations/
├── train/
├── validation/
└── test/
For each image file:
images/<split>/<image_id>.jpg
there exists a corresponding annotation file:
annotations/<split>/<image_id>.json
## Annotations format
Each annotation JSON contains structured information extracted from a receipt, including:
- `seller`
- `inn`
- `date`
- `total`
- `items` (list of line items, if available)
Fields may be missing and are represented as `null`.
Bounding boxes are taken directly from OCR output and are not manually corrected.
---
## Completeness rule
A receipt is considered **complete** if:
- `total` is present
- `date` is present
- **either** `seller` **or** `inn` is present
## Usage notes
This dataset is intentionally stored in a **file-based format** and is consumed by custom pipelines that:
- explicitly load images from disk
- load annotation JSON files by filename
- perform OCR and semantic parsing separately
This design ensures:
- transparent data loading
- reproducible evaluation
- full control over preprocessing and inference steps
---
## Related resources
- OCR model checkpoint:
https://huggingface.co/SvetaLana25/dek-receipt-donut-stage1
- Evaluation and inference code:
Provided as part of the project submission.
---
## Disclaimer
This dataset is provided for educational and research purposes.
Sensitive information is anonymized or originates from user-provided examples. |