Show HN: Math2Tex – 将手写数学公式和复杂笔记转换为 LaTeX 文本
5 分•作者: leoyixing•8 个月前
Hi HN，
我是 Math2Tex 的创建者。我曾是一名博士生，花大量时间使用 LaTeX，尤其是在处理讲义、学术论文和作业时。我开发了 *Math2Tex*，这是一个轻量级工具，可以将手写或印刷的学术内容——尤其是数学公式——转换成 LaTeX 或文本。
问题：
我一直觉得手动输入数学公式非常繁琐，尤其是从手写笔记或教科书中输入复杂的、多行公式。这既慢又无聊，而且我总是会犯语法错误。我试过一些现有的工具，但它们常常难以识别我的手写内容，或者无法处理混合内容（文本和公式混合）。
解决方案：
因此，我开发了 Math2Tex 来解决我自己的问题。它是一个简单直接的单页 Web 应用程序：您上传一张图片（笔记本的照片、PDF 的截图等），它就会将学术内容转换成干净的 LaTeX 代码或纯文本。您可以实时预览结果，并一键复制。我的目标是尽可能加快工作流程：拍照。转换。完成。
您可以在这里试用：[https://math2tex.com](https://math2tex.com/)
它与 GPT、Claude 等通用 AI 工具有何不同？
这是一个合理的问题。虽然大型模型可以处理这个问题，但对于这种特定任务，它们通常速度较慢。我想要一些更快、更专业的东西。Math2Tex 使用一个轻量级模型，该模型经过专门针对学术内容识别的微调。
简而言之，可以把它想象成一把专业的解剖刀，而不是一把瑞士军刀。对于这项特定工作，它通常快 3-5 倍，而且根据我的经验，对于复杂的符号，它更可靠。
技术栈：
核心 OCR 引擎是一个基于 Transformer 架构的定制训练模型，该模型在大量印刷和手写学术材料的数据集上进行了微调。它全部部署在 Vercel 上。
*免费使用。* 这仍然是一个早期版本，我确信还有很多错误和需要改进的地方。识别可能并不完美，尤其是在非常潦草的字迹或一些晦涩的符号的情况下。
我非常感谢您的反馈。无论您是学生、研究人员，还是与 LaTeX 输入作斗争的人。对该工具和方法的反馈都将非常有帮助。
谢谢！
查看原文
Hi HN,<p>I’m the creator of Math2Tex. I was a PhD student, I spend a huge amount of my time working with LaTeX, especially when dealing with lecture notes, academic papers, and homework. I built *Math2Tex*, a lightweight tool that converts handwritten or printed academic content — especially math formulas — into LaTeX or text<p>The Problem:<p>I've always found it incredibly tedious to manually type out mathematical formulas, especially complex, multi-line equations from my handwritten notes or from a textbook. It's slow, boring, and I always make syntax errors. I tried some existing tools, but they often struggled with my handwriting or couldn't handle mixed content (text and formulas together).<p>The Solution:<p>So, I built Math2Tex to solve my own problem. It’s a straightforward, single-page web app: you upload an image (a photo of your notebook, a screenshot of a PDF, etc.), and it converts the academic content into clean LaTeX code or plain text. You get a real-time preview and can copy the result with one click. My goal was to make the workflow as fast as possible: Snap. Convert. Done.<p>You can try it here: [<a href="https://math2tex.com" rel="nofollow">https://math2tex.com</a>](<a href="https://math2tex.com/" rel="nofollow">https://math2tex.com/</a>)<p>How is it different from general AI tools like GPT, Claude, etc?<p>This is a fair question. While large models can handle this, they are often slow for such a specific task. I wanted something faster and more specialized. Math2Tex uses a lightweight model fine-tuned specifically for academic content recognition.<p>In short, think of it as a specialized scalpel versus a Swiss Army knife. For this particular job, it's generally 3-5x faster and, in my experience, more reliable for complex notations.<p>Tech Stack:<p>The core OCR engine is a custom-trained model based on a transformer architecture, fine-tuned on a large dataset of both printed and handwritten academic material. It's all deployed on Vercel.<p>*It's free to use.* This is still an early version, and I'm sure there are plenty of bugs and areas for improvement. The recognition might not be perfect, especially with very messy handwriting or some obscure symbols.<p>I would be incredibly grateful for your feedback. Whether you’re a student, researcher, or someone who’s fought with LaTeX input. Feedback on both the tool and the approach would be really helpful.<p>Thanks!