chanhanyang/Easy-to-use-OCR-Handwritten-Mathmatics

📄 Easy OCR Tool

This tool is designed to easily convert images and scanned documents into editable text using Optical Character Recognition (OCR).

Using fhswf/TrOCR_Math_handwritten Model

🇰🇷 (kr)한국어로 보기

My github link

Input

Hand-Written images

Output

cos\theta=\frac{x}{\sqrt{x^{2}+y^{2}}}

<img src="https://github.com/user-attachments/assets/eb36d27a-f247-4848-b922-1b67fb6bee91" width="400">

Input

Hand-Written images

Output

e^{i\pi}+1=0.

<img src="https://github.com/user-attachments/assets/373f8046-da29-46d4-8e95-c7547c0b5196" width="400">

✨ Features

• —✅ Simple drag-and-drop interface.
• —📷 Supports multiple image formats.
• —⚡ Quick and accurate text extraction.

🔧 Installation

-MacTex: If you're on macOS, you'll need to install MacTeX.

brew install --cask mactex

• —Windows: Install MiKTeX or TeX Live. Follow their respective installation guides.

-Python Dependencies

pip install torch torchvision torchaudio

🚀 Getting Started

1. 1.Copy and put your image file path.
2. 2.Click the Run.
3. 3.Download the extracted text!

Reference

Model:

TrOCRMathhandwritten by fhswf License: afl-3.0

Paper:

Li, M., Lv, T., Cui, L., Lu, Y., Florencio, D., Zhang, C., Li, Z., & Wei, F. (2021). TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models. arXiv preprint arXiv:2109.10282.

BibTeX:

text
@misc{li2021trocr,
  title={TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models},
  author={Minghao Li and Tengchao Lv and Lei Cui and Yijuan Lu and Dinei Florencio and Cha Zhang and Zhoujun Li and Furu Wei},
  year={2021},
  eprint={2109.10282},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}