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TexTeller is a ViT-based model designed for end-to-end formula recognition. It can recognize formulas in natural images and convert them into LaTeX-style formulas.
TexTeller is trained on a larger dataset of image-formula pairs (a 550K dataset available [here](https://huggingface.co/datasets/OleehyO/latex-formulas)), **exhibits superior generalization ability and higher accuracy compared to [LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)**, which uses approximately 100K data points. This larger dataset enables TexTeller to cover most usage scenarios more effectively.
TexTeller is trained on a larger dataset of image-formula pairs (a 550K dataset available [here](https://huggingface.co/datasets/OleehyO/latex-formulas)), **exhibits superior generalization ability and higher accuracy compared to [LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)**, which uses approximately 100K data points. This larger dataset enables TexTeller to cover most usage scenarios more effectively( **excluding scanned images and handwritten formulas** ).
> A TexTeller checkpoint trained on a 5.5M dataset will be released soon.
## Prerequisites

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TexTeller是一个基于ViT的端到端公式识别模型，可以把图片转换为对应的latex公式
TexTeller用了550K的图片-公式对进行训练(数据集可以在[这里](https://huggingface.co/datasets/OleehyO/latex-formulas)获取)，相比于[LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)(使用了一个100K的数据集)，TexTeller具有**更强的泛化能力**以及**更高的准确率**，可以**覆盖大部分的使用场景**。
TexTeller用了550K的图片-公式对进行训练(数据集可以在[这里](https://huggingface.co/datasets/OleehyO/latex-formulas)获取)，相比于[LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)(使用了一个100K的数据集)，TexTeller具有**更强的泛化能力**以及**更高的准确率**，可以覆盖大部分的使用场景(**扫描图片，手写公式除外**)。
> 我们马上就会发布一个使用5.5M数据集进行训练的TexTeller checkpoint
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> 注意: 只有CUDA版本>= 12.0被完全测试过，所以最好使用>= 12.0的CUDA版本
## Getting Started
1. 克隆本仓库: