---
license: apache-2.0
language:
- vi
- en
size_categories:
- 10M<n<100M
---

# Combined OCR Dataset for Text Recognition

## Dataset Description

This is a large-scale dataset (~11M training, ~0.9M validation images) for Optical Character Recognition (OCR), aggregated from several common benchmarks and sources (see Sources below). It includes scene text, handwritten text, and synthetic images with corresponding text labels.

**Training Code:** [https://github.com/ducto489/lib_ocr](https://github.com/ducto489/lib_ocr)

## Dataset Structure

```
./data/
├── train/
│   ├── images/*.jpg  # Training images
│   └── tgt.csv       # Training filenames and labels
└── val/
    ├── images/*.jpg  # Validation images
    └── tgt.csv       # Validation filenames and labels
```
*   `tgt.csv`: Comma-separated `image_name,label`. Labels are pre-normalized (see below).

## Data Details

*   **Sources:** Aggregated from [vietocr](https://github.com/pbcquoc/vietocr), [Deep Text Rec. Benchmark](https://github.com/clovaai/deep-text-recognition-benchmark), [Synth90k](https://www.robots.ox.ac.uk/~vgg/data/text/), and [Cinnamon AI Handwritten](https://www.kaggle.com/datasets/hariwh0/cinnamon-ai-handwritten-addresses).
*   **Normalization:** Text labels have undergone character normalization (e.g., smart quotes to `"` , various dashes to `-`, accented chars simplified like `Ö`->`O`). This simplifies the vocabulary. See the [training repo README](https://github.com/AnyGlow/lib_ocr#data-preprocessing-character-normalization) for the full list.
*   **Language:** Predominantly English. Vietnamese samples (1.76%) are included but limited.
*   **Licensing:** Combines multiple sources. **Users must verify compliance with original dataset licenses** before use.

## Citation

Please cite the original source datasets if you use this data. Citing this aggregation is also appreciated:

```bibtex
@misc{ducto489_ocr_datasets,
  author       = {Nguyễn Minh Đức},
  title        = {Combined OCR Dataset},
  year         = {2024}, # Update year as needed
  howpublished = {Hugging Face Datasets},
  url          = {https://huggingface.co/datasets/ducto489/ocr_datasets}
}
```

## Dataset Curators

Aggregated by [ducto489](https://github.com/ducto489/) / Nguyễn Minh Đức.