TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
Paper
β’
2109.10282
β’
Published
β’
12
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
π°π· (kr)νκ΅μ΄λ‘ 보기
My github link
Hand-Written images
cos\theta=\frac{x}{\sqrt{x^{2}+y^{2}}}
Hand-Written images
e^{i\pi}+1=0.
-MacTex: If you're on macOS, you'll need to install MacTeX.
brew install --cask mactex
-Python Dependencies
pip install torch torchvision torchaudio
Model:
TrOCR_Math_handwritten 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}
}
Base model
microsoft/trocr-base-handwritten