kalixlouiis/MyanmarOCR-ImageText

🇲🇲 MyanmarOCR-ImageText Dataset

A clean and diverse Burmese Image-to-Text dataset for OCR and multimodal AI research.

📌 Summary

• —Total images: 41,664
• —Unique Burmese text entries: 1,139
• —Styles per text: 32 variations each
• —Resolution: 512 × 512
• —File types: PNG/JPG images
• —Dataset split: train only
• —Use cases: OCR, I2T (image-to-text), VLM pretrain/fine-tune

All text is Burmese only. No English words and no punctuation like: ? , ' " -

🔡 Text Content

Includes:

• —Common words & Pali words
• —Signs and short phrases
• —Full Myanmar Unicode support

Variety of Myanmar spellings and writings are included (မြန်မာအက္ခရာတွေနဲ့ စကားလုံးမျိုးစုံပါဝင်ပါတယ်)

🎨 Style Variations

Each text appears in 32 visual styles with differences in:

• —font
• —color
• —texture
• —rotation (small angle)
• —background patterns

This helps models generalize across real-world environments.

🧩 Data Format

Each sample includes:

Example record:

{
  "image": "<image>",
  "text": "မြန်မာနိုင်ငံ",
  "style": "style_07"
}

🧪 Usage

from datasets import load_dataset

ds = load_dataset("kalixlouiis/MyanmarOCR-ImageText", split="train")
print(ds[0])

ds[0]["image"].show()

🎯 Intended Purposes

• —Burmese OCR training
• —Scene text model finetuning
• —Vision-language pretraining
• —Synthetic-to-real text recognition research
• —Benchmark for Myanmar multimodal AI

⚠️ Limitations

• —Synthetic images only — not real photos/signboards
• —No English text or punctuation
• —No complex layout structures (single word/short text per image)

📄 License

This dataset is released under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license.

You are free to:

• —✔ Share — copy and redistribute for any purpose
• —✔ Adapt — modify, transform, and build upon the data

As long as you:

• —Give appropriate credit
• —Indicate changes
• —Provide a link to the license

📌 License Text: https://creativecommons.org/licenses/by/4.0/

✨ Acknowledgment

Created by [@kalixlouiis](https://huggingface.co/kalixlouiis) with the goal of improving Myanmar OCR and AI research.

If you use this dataset in your research or applications, please cite and provide a link to the dataset page on Hugging Face:

🔗 https://huggingface.co/datasets/kalixlouiis/MyanmarOCR-ImageText

📚 Citation

@dataset{kalixlouiis2025myanmarocr,
  title        = {MyanmarOCR-ImageText},
  author       = {Kalix Louis},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/kalixlouiis/MyanmarOCR-ImageText}},
  license      = {CC-BY-4.0}
}

About the Author

Khant Sint Heinn, working under the name Kalix Louis, is a Machine Learning Engineer focused on Natural Language Processing (NLP), data foundations, and open-source AI development. His work is centered on improving support for the Burmese (Myanmar) language in modern AI systems by building high-quality datasets, practical tools, and scalable infrastructure for language technology.

He is currently the Lead Developer at DatarrX, where he develops data pipelines, manages large-scale data collection workflows, and helps create open-source resources for researchers, developers, and organizations. His experience includes data engineering, web scripting, dataset curation, and building systems that support real-world machine learning applications.

Khant Sint Heinn is especially interested in advancing low-resource languages and making AI more accessible to underrepresented communities. Through his open-source contributions, he works to strengthen the Burmese (Myanmar) tech ecosystem and provide reliable building blocks for future language models, search systems, and intelligent applications.

His goal is simple: to turn limited language resources into practical opportunities through clean data, useful tools, and community-driven innovation.

Connect with the Author: GitHub | Hugging Face | Kaggle