README.md

---
pretty_name: czech-synth-text-2025
size_categories:
- 100K<n<1M
dataset_info:
  features:
  - name: image
    dtype: image
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 2156337658.4
    num_examples: 454820
  download_size: 2117123960
  dataset_size: 2156337658.4
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
language:
- cs
license: mit
---
# Czech Synthetic Text Recognition Dataset

A large-scale synthetic dataset for Czech text recognition, containing 454,820 text images with corresponding transcriptions. Created using [SynthTiger](https://github.com/clovaai/synthtiger).

## Dataset Description

This dataset consists of synthetically generated images of Czech text, designed for training optical character recognition (OCR) models. Each image contains a single word or short phrase rendered with various visual effects to simulate real-world text appearance.

### Dataset Statistics
- **Total samples**: 454,820 image-text pairs
- **Language**: Czech (cs_CZ)
- **Image format**: JPEG
- **Storage format**: Parquet files (5 shards in data/ folder)
- **Total size**: ~1.96 GB

## Dataset Structure

The dataset is stored in HuggingFace's optimized format with automatic image display support:

```
data/
├── train-00000-of-00005-*.parquet
├── train-00001-of-00005-*.parquet
├── train-00002-of-00005-*.parquet
├── train-00003-of-00005-*.parquet
└── train-00004-of-00005-*.parquet
```

Each Parquet file contains two columns:
- `image`: PIL Image object (JPEG format, automatically displayed in dataset viewer)
- `text`: Ground truth text transcription

## Usage

### Loading with Hugging Face Datasets

```python
from datasets import load_dataset

# Load the entire dataset
dataset = load_dataset("Empatixx/synth-text-recognition-cs")

# Access samples
sample = dataset['train'][0]
image = sample['image']  # PIL Image object
text = sample['text']    # Text transcription

# Load specific splits or streaming
dataset = load_dataset("Empatixx/synth-text-recognition-cs", split="train[:1000]")  # First 1000 samples
dataset = load_dataset("Empatixx/synth-text-recognition-cs", streaming=True)  # Stream the dataset
```

### Direct Loading from Repository

The dataset now has proper Image type support, so images will display automatically in the HuggingFace dataset viewer!

```python
# Images are automatically loaded as PIL Image objects
sample = dataset['train'][0]
image = sample['image']  # Already a PIL Image, not bytes!
image.show()  # Display the image

# Get the text transcription
text = sample['text']
print(f"Text: {text}")
```

### PyTorch DataLoader Example

```python
from datasets import load_dataset
from torch.utils.data import DataLoader
from torchvision import transforms

# Load dataset
dataset = load_dataset("Empatixx/synth-text-recognition-cs")

# Define transforms
transform = transforms.Compose([
    transforms.Resize((32, 128)),
    transforms.ToTensor(),
])

# Create DataLoader
def collate_fn(batch):
    images = [transform(sample['image']) for sample in batch]
    texts = [sample['text'] for sample in batch]
    return torch.stack(images), texts

dataloader = DataLoader(
    dataset['train'],
    batch_size=32,
    shuffle=True,
    collate_fn=collate_fn
)
```

## Generation Details

The dataset was generated using SynthTiger with the following characteristics:

### Text Sources
- Czech words from [czech-cc0-dictionaries](https://gitlab.com/czech-cc0-dictionaries/czech-cc0-dictionaries) (CC0 licensed)
- Text lengths: 1-25 characters
- Character set: Czech alphabet including diacritics (ěščřžýáíéůú)

### Visual Variations
- **Fonts**: Arimo-Regular, OpenSans-Regular, Roboto-Regular, Tinos-Regular (sizes 40-80px)
- **Colors**: Diverse color schemes from predefined colormaps
- **Effects**: Borders, shadows, and 3D extrusion effects
- **Transformations**: Perspective, rotation, shearing, and elastic distortions
- **Backgrounds**: Textured backgrounds with varying complexity
- **Quality**: JPEG compression with quality 50-95

### Text Rendering Styles
- Horizontal text layout
- Both curved and straight text
- Various text effects including:
  - Border effects (25% probability)
  - Shadow effects (50% probability)  
  - Extrusion effects (10% probability)

## Dataset Creation

The dataset was created using the following process:

1. **Text Generation**: Czech words selected from corpus files
2. **Visual Rendering**: Text rendered with random fonts, colors, and effects
3. **Background Generation**: Synthetic backgrounds with textures and patterns
4. **Post-processing**: Geometric transformations, noise, and compression
5. **Format Conversion**: Original files converted to Parquet format for efficiency


## Citation

If you use this dataset, please cite:

```bibtex
@misc{czech-synth-text-2025,
  title={Czech Synthetic Text Recognition Dataset},
  author={Empatixx},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/Empatixx/synth-text-recognition-cs}
}
```

Also cite the SynthTiger paper:

```bibtex
@inproceedings{yoo2021synthtiger,
  title={SynthTiger: Synthetic Text Image Generator Towards Better Text Recognition Models},
  author={Yoo, Moonbin and Shin, Yoonsik and Paek, Seunghyun},
  booktitle={ICDAR},
  year={2021}
}
```

## License

This dataset is released under the same license as SynthTiger. Please refer to the original [SynthTiger repository](https://github.com/clovaai/synthtiger) for license details.

## Acknowledgments

- Dataset generated using [SynthTiger](https://github.com/clovaai/synthtiger)
- Czech word corpus from [czech-cc0-dictionaries](https://gitlab.com/czech-cc0-dictionaries/czech-cc0-dictionaries) (CC0 license)