---
license: mit
task_categories:
- image-to-text
- text-generation
language:
- pt
tags:
- portuguese
- ocr
- text-recognition
- synthetic-data
pretty_name: Portuguese OCR Dataset
size_categories:
- 10K<n<100K
---



task_categories:
  - image-to-text
task_ids:
  - optical-character-recognition
  - text-recognition


# Portuguese OCR Dataset

A comprehensive dataset for Portuguese OCR (Optical Character Recognition) generated from classic Portuguese literature with diverse fonts and visual styles.

## Dataset Description

This dataset contains 20000 text images for OCR training, created from Portuguese books from Project Gutenberg. Each image contains a complete Portuguese sentence with proper punctuation, rendered with various fonts, backgrounds, and visual styles.

### Features

- **Multiple Text Sources**: Classic Portuguese literature from Project Gutenberg
- **Complete Sentences**: Full sentences with proper punctuation and grammar
- **Font Variety**: Multiple fonts from Google Fonts collection
- **Visual Diversity**: Various backgrounds, font sizes, colors, and slight rotations
- **High Quality**: 1200×150 pixel images (or taller for wrapped text)

## Dataset Splits

| Split | Number of Samples |
|-------|------------------|
| Train | 16000 |
| Validation | 2000 |
| Test | 2000 |
| **Total** | 20000 |

## Example Sentences

- Ha um cão vadio, sujo e com fome, cuida-se deste cão e ele deixa de ser vadio, deixa de estar sujo e deixa de ter fome.
- Um affago previo tempera as traições.
- Demais, eu tenho algodão nos ouvidos, talvez ouvisse mal, repete o que disseste.  

## Image Specifications

- **Resolution**: 150×1200 pixels
- **Color**: RGB
- **Format in HDF5**: Numpy arrays
- **Average text length**: 82.8 characters

## Usage Example

```python
import h5py
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt

# Load the dataset
with h5py.File('train_dataset.h5', 'r') as f:
    # Access images and texts
    images = f['images'][:]
    texts = [t.decode('utf-8') if isinstance(t, bytes) else t for t in f['texts'][:]]
    
    # Display a sample
    idx = np.random.randint(0, len(images))
    print(f"Text: {texts[idx]}")
    
    plt.figure(figsize=(12, 3))
    plt.imshow(images[idx])
    plt.axis('off')
    plt.show()
```

## Dataset Creation Process

This dataset was created through the following steps:

1. Downloaded and extracted text from Portuguese books via Project Gutenberg
2. Cleaned and extracted complete sentences with proper punctuation
3. Generated images with random:
   - Fonts (from Google Fonts collection)
   - Background styles (solid, gradient, noise, pattern)
   - Text positions and slight rotations
   - Font sizes (30-45px)
   - Text colors (dark tones for readability)
4. Split into train (80%), validation (10%), and test (10%) sets

## License

This dataset is derived from public domain books from Project Gutenberg and open-source fonts from Google Fonts. It is released under the Creative Commons Attribution 4.0 International License (CC-BY 4.0).

## Citation

If you use this dataset in your research, please cite it as:

```
@dataset{portuguese_ocr_dataset,
  author = {mazafard},
  title = {Portuguese OCR Dataset},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/mazafard/portuguese-ocr-dataset}
}
```

## Acknowledgments

- Text sources: Project Gutenberg (https://gutenberg.org/)
- Fonts: Google Fonts (https://fonts.google.com/)