README.md

---
language:
- zh
language_bcp47:
- zh-tw
license: mit
task_categories:
- image-to-text
- document-question-answering
pretty_name: SynthDoG Traditional Chinese Dataset
size_categories:
- 10K<n<100K
tags:
- ocr
- synthetic-data
- traditional-chinese
---

# SynthDoG Traditional Chinese Dataset

This dataset contains synthetic document-ground truth pairs for Traditional Chinese text recognition training. The dataset is generated using the SynthDoG (Synthetic Document Generation) framework, which creates realistic document images with Traditional Chinese text.

## Dataset Structure

The dataset is organized into three splits:
- `train/`: Training data
- `validation/`: Validation data
- `test/`: Test data

Each split contains:
- Image files (*.jpg): Synthetic document images with Traditional Chinese text
- metadata.jsonl: Ground truth annotations for each image in JSONL format

## File Format

### Images
- Format: JPEG
- Resolution: Various sizes, optimized for document recognition
- Content: Synthetic documents with Traditional Chinese text
- Features: Includes various document layouts, fonts, and text styles

### Annotations (metadata.jsonl)
The metadata file contains annotations for each image in JSONL format, including:
- Text content
- Text regions
- Layout information

## Usage

This dataset is designed for:
1. Training OCR models for Traditional Chinese text recognition
2. Fine-tuning document understanding models
3. Testing document layout analysis systems

### Loading the Dataset
You can load this dataset using the Hugging Face datasets library:
```python
from datasets import load_dataset

dataset = load_dataset("LeeTung/synthdoc-zh-tw-dataset")
```

## License

MIT License. Please refer to the original SynthDoG repository for additional license information.

## Citation

If you use this dataset in your research, please cite the original SynthDoG paper and this dataset:

```bibtex
@misc{synthdoc-zh-tw-dataset,
  title={SynthDoG Traditional Chinese Dataset},
  author={Lee Tung},
  year={2024},
  publisher={Hugging Face}
}
```