展示HN：Math2Tex – 将手写数学和复杂笔记转换为LaTeX文本
嗨，HN，
我是 Math2Tex 的创始人。曾经是一名博士生，我花了大量时间使用 LaTeX，特别是在处理讲义、学术论文和作业时。我开发了 *Math2Tex*，这是一款轻量级工具，可以将手写或打印的学术内容——尤其是数学公式——转换为 LaTeX 或纯文本。
问题：
我一直觉得手动输入数学公式非常繁琐，尤其是从我的手写笔记或教科书中提取复杂的多行方程。这不仅慢而且无聊，而且我总是会犯语法错误。我尝试过一些现有工具，但它们往往无法处理我的手写字迹，或者无法处理混合内容（文本和公式一起）。
解决方案：
因此，我开发了 Math2Tex 来解决我自己的问题。这是一个简单的单页网页应用：你上传一张图片（笔记本的照片、PDF 的截图等），它会将学术内容转换为干净的 LaTeX 代码或纯文本。你可以实时预览，并且只需一键即可复制结果。我的目标是让工作流程尽可能快：拍照、转换、完成。
你可以在这里试用：[https://math2tex.com](https://math2tex.com)
它与 GPT、Claude 等通用 AI 工具有什么不同？
这是一个合理的问题。虽然大型模型可以处理这个任务，但对于这样一个特定的任务，它们往往速度较慢。我想要的是更快、更专业的工具。Math2Tex 使用的是一个专门针对学术内容识别进行微调的轻量级模型。
简而言之，可以把它看作是专业的手术刀，而不是瑞士军刀。对于这个特定的工作，它通常快 3-5 倍，并且根据我的经验，对于复杂的符号更可靠。
技术栈：
核心 OCR 引擎是基于变换器架构的定制训练模型，经过大量打印和手写学术材料的数据集微调。所有内容都部署在 Vercel 上。
*它是免费的。* 这仍然是一个早期版本，我相信还有很多错误和改进的空间。识别可能并不完美，尤其是对于非常潦草的手写或一些晦涩的符号。
我非常感激你的反馈。无论你是学生、研究人员，还是曾经与 LaTeX 输入斗争过的人，关于工具和方法的反馈都会非常有帮助。
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!