| --- |
| title: FastCDM |
| emoji: ⚡️ |
| colorFrom: blue |
| colorTo: indigo |
| sdk: docker |
| pinned: false |
| short_description: High-performance LaTeX formula evaluation tool using KaTeX. |
| tags: |
| - latex |
| - formula-recognition |
| - evaluation |
| - katex |
| --- |
| |
| <div align="center"> |
|
|
| # ⚡️FastCDM |
|
|
| [**[GitHub Repo]**](https://github.com/SoMarkAI/FastCDM) | [**[HuggingFace Spaces]**](https://huggingface.co/spaces/SoMark/FastCDM) |
|
|
| <p> |
| <a href="https://pypi.org/project/fastcdm/"> |
| <img src="https://img.shields.io/badge/pypi-v0.1.1-blue" |
| alt="PyPI package version"> |
| </a> |
| <a href="https://www.python.org"> |
| <img src="https://img.shields.io/badge/python-3.8%2B-blue" |
| alt="Python versions"> |
| </a> |
| <a href="#"> |
| <img src="https://img.shields.io/badge/license-Apache%202.0-blue" |
| alt="GitHub license"> |
| </a> |
| </p> |
| |
| </div> |
|
|
| ## 🚀 Introduction |
|
|
| [CDM](https://github.com/opendatalab/UniMERNet/tree/main/cdm) ensures the objectivity and accuracy of evaluation by rendering predicted and ground-truth LaTeX formulas into images, and then using visual feature extraction and localization techniques to perform precise character-level matching, combined with spatial position information. |
|
|
| **FastCDM** aims to address performance issues. As a high-performance optimized version of the original [CDM](https://github.com/opendatalab/UniMERNet/tree/main/cdm), FastCDM employs the browser-based KaTeX rendering engine instead of traditional LaTeX compilation, resulting in significantly improved speed. |
|
|
| ### 🎯 Project Goals |
|
|
| The core objective of FastCDM is to **provide a convenient user experience during the training process**, helping to advance formula recognition tasks. We are committed to: |
| - Providing simple and easy-to-use API interfaces for convenient integration of evaluation within the training loop. |
| - Supporting both real-time evaluation and batch evaluation modes. |
| - Providing visualization tools for evaluation metrics during the training process. |
|
|
| ### Why Choose FastCDM? |
|
|
| 1. **Extreme Performance**: Based on the KaTeX rendering engine, it is tens of times faster than the traditional LaTeX compilation process. |
| 2. **Simplified Deployment**: No need to install complex LaTeX environments (ImageMagick, texlive-full, etc.). |
| 3. **Accurate Evaluation**: Adopts character detection matching methods to avoid the unfairness issues associated with traditional text metrics. |
| 4. **Continuous Optimization**: Supplements and refines CDM symbol support, with continuous iterative improvements. |
| 5. **Easy Integration**: Provides a unified API interface for easy integration into various training frameworks. Future integration with mainstream training frameworks such as PyTorch and Transformers is planned. |
|
|
| ### ⚠️ Note |
|
|
| Although KaTeX is extremely fast, it is a lightweight solution optimized for the Web and cannot support **100%** of all obscure LaTeX syntax. |
|
|
| For the vast majority of standard formulas, it performs perfectly. This is a reasonable and sustainable technical choice. |
|
|
| You can check KaTeX's support coverage here: 🔗 [KaTeX Support Table](https://katex.org/docs/support_table) |
|
|
| --- |
|
|
| ## Usage |
|
|
| ### Installation |
|
|
| You need to install `node.js` and `chromedriver` in advance. |
| * For `node.js` installation, please refer to [here](https://nodejs.org/). |
| * For `chromedriver` installation, please refer to [here](docs/chromedriver_installation.md). |
|
|
| ```bash |
| pip install fastcdm |
| ``` |
|
|
| ### Quick Start |
|
|
| ```python |
| from fastcdm import FastCDM |
| |
| chromedriver_path = "driver/chromedriver" |
| |
| # Initialize FastCDM evaluator |
| evaluator = FastCDM(chromedriver_path=chromedriver_path) |
| |
| # Evaluate |
| cdm_score, recall, precision = evaluator.compute(gt="E = mc^2", pred="E + 1 = mc^2", visualize=False) |
| |
| # Evaluate and visualize |
| cdm_score, recall, precision, vis_img = evaluator.compute(gt="E = mc^2", pred="E + 1 = mc^2", visualize=True) |
| ``` |
|
|
| ### Interactive Demo |
|
|
| We provide a visualization Demo developed with Gradio, which you can try on [HuggingFace Spaces](https://huggingface.co/spaces/SoMark/FastCDM). You can also launch it locally: |
|
|
| ```bash |
| python3 scripts/app.py |
| ``` |
|
|
| ## Contribution and Feedback |
|
|
| We welcome all forms of contribution, including but not limited to: |
| - Submitting issue reports |
| - Suggesting improvements |
| - Submitting code changes (please open an issue for discussion first) |
|
|
| Please contact us via the project's [issues](https://github.com/SoMarkAI/FastCDM/issues). |
|
|
| --- |
|
|
| ## License |
|
|
| This project is open-sourced under the Apache 2.0 license. You are free to use, modify, and distribute the code of this project under the terms of the license. |
|
|
