TrOCR (🖊️ to 💻 Model, Fine-Tuned on IAM)

Turn handwritten notes into typed text with this TrOCR model 📝➡️🔡, crafted using the IAM dataset. Inspired by the research from TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models.

📖 Model Description

A blend of visual and language Transformers 🤖—BEiT feeds the image and RoBERTa spells out the text. It sees pictures as chunks (16x16 bits) and turns them into words.

🔍 Intended Use

Perfect for reading 🕵️‍♂️ handwritten lines and bringing them to your screen. Check out model hub for more specialized versions.

🤔 Ethical Considerations

Think ethically ✨: respect privacy when converting handwritten pieces and avoid using this tech for snooping around.

⚠️ Caveats and Recommendations

• Best with single lines 📏 of handwriting.
• Get permission before you digitize! 📜

📚 BibTeX Citation

@misc{li2021trocr,
      title={TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models}, 
      author={Minghao Li et al.},
      year={2021},
      eprint={2109.10282},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}