---
task_categories:
- image-to-text
language:
- et
tags:
- Estonia
- historical-documents
- ocr
- archival-data
- text-recognition
- document-analysis
pretty_name: ArchXAI Estonian
size_categories:
- 1K<n<10K
---

# 🔍 ArchXAI Estonian OCR Dataset

## Dataset Description

This dataset contains 3,255 annotated text regions from Estonian historical documents, designed for optical character recognition (OCR) and document analysis tasks. The dataset includes images of text regions along with their corresponding transcriptions, and source documents.

## 📊 Dataset Summary

- **Total Examples**: 3,255
- **Language**: 🇪🇪 Estonian
- **Dataset Size**: ~758 MB
- **Task**: OCR, Text Detection, Document Analysis
- **Domain**: Historical Documents, Archival Materials

## 🗂️ Dataset Structure

### 📋 Features

- **image**: Image data containing text regions
- **text**: Ground truth transcription of the text in the image
- **document**: Source document name

## 💻 Usage Examples

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Rahvusarhiiv/ArchXAI_textline_OCR")

# Access a sample
sample = dataset['train'][0]
image = sample['image']
text = sample['text']

# Filter by document
ordered_text = dataset['train'].sort('document')
```

## 🎯 Use Cases

This dataset is valuable for:

- **OCR Model Training**: Training optical character recognition systems for Estonian text
- **Document Layout Analysis**: Understanding document structure and reading order
- **Historical Document Digitization**: Processing Estonian archival materials
- **Text Detection**: Locating text regions in document images
- **Multilingual OCR**: Estonian language text recognition research
- **Digital Humanities**: Analysis of Estonian historical documents

## ⚠️ Data Quality Notes

- Images contain text regions extracted from historical Estonian documents
- Text transcriptions follow modern Estonian orthography where applicable
- Some historical texts may contain archaic spellings or formatting
- Coordinate systems may vary depending on source document resolution

## 🚫 Limitations

- Limited to Estonian language content
- Historical document quality may affect image clarity
- Transcription accuracy depends on document preservation state
- Dataset size is relatively small (3,255 examples)