wizmap

poloclubMIT更新放缓

在浏览器里交互式探索和解读大规模嵌入向量，用可视化方式直观理解高维数据的分布与结构。

Explore and interpret large embeddings in your browser with interactive visualization! 📍

v0.1.6发布于 2025-07-14 07:23 UTC539star35fork同步于 2026-11-07 07:31 UTC

嵌入可视化交互式可视化高维数据 WebGL 向量分析

对比 GitHub 官网 embeddings interactive-visualizations machine-learning visualization webgl

怎么上手

由 README 提炼，执行前请确认

原文

pip install wizmap
npm install
npm run dev

硬件要求按 README 说明

README 未说明，仅需浏览器运行前端，无 GPU 或显存要求说明

下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼

没人工点评？写下你的经验

在浏览器里交互式探索和解读大规模机器学习嵌入的可视化工具

在浏览器里交互式探索和解读大规模嵌入向量，用可视化方式直观理解高维数据的分布与结构。

核心能力

用多分辨率嵌入摘要支持百万级嵌入点浏览
提供地图式交互导航与快速嵌入搜索
支持文本与图像多模态数据可视化
可播放嵌入演化动画并生成可分享 URL
提供 Python 库在 Jupyter、Colab 等笔记本中直接可视化

容易踩的坑

需先用 wizmap Python 库生成两个 JSON 文件（嵌入摘要与原始数据）才能加载自己的数据；本地开发默认访问 localhost:3000；浏览器方式需手动在弹窗中填入 JSON 文件 URL

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

用户点评

登录用户的真实使用记录，可按版本和硬件筛选

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还没有人点评。第一个说出真实体验的人最有价值。

README 原文

未翻译

在 GitHub 打开

WizMap

Exploring and interpreting large embeddings in your browser!

What is WizMap?

WizMap is a scalable interactive visualization tool to help you easily explore large machine learning embeddings. With a novel multi-resolution embedding summarization method and a familiar map-like interaction design, WizMap allows you to navigate and interpret embedding spaces with ease.

WizMap Gallery

Submit a PR to add your WizMap here! You can share your WizMap using a unique URL.

Web Demo

For a live web demo, visit: https://poloclub.github.io/wizmap.

Get Started

Clone or download this repository:

git clone [email protected]:poloclub/wizmap.git

Install the dependencies:

npm install

Then run WizMap:

npm run dev

Navigate to localhost:3000. You should see WizMap running in your browser :)

Use My Own Embeddings

To use WizMap with your embeddings, you first need to install the wizmap Python library.

pip install wizmap

Then take a look at this notebook for a detailed guide. If your dataset includes images, take a look at this notebook.

Spoiler alert: You'll be up and running with just two function calls from the wizmap library. These two JSON files contain pre-computed embedding summaries, distributions, and the original embedding data.

After generating the JSON files, you have two options to use WizMap.

Browser: You can click the folder icon on the bottom right of the WizMap demo and enter the URLs to the JSON files in the pop-up window.
Notebook: If you are familiar with computational notebooks (e.g., Jupyter Notebook, VSCode Notebook, Colab), you can directly use WizMap in your favorite notebook platform with wizmap.visualize().

Share My WizMap

You can easily share your embedding maps with collaborators by copying the unique URL of WizMap from your browser. For example, the URL below points to an IMDB embedding in WizMap.

https://poloclub.github.io/wizmap/?dataURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Fxiaohk%2Fembeddings%2Fresolve%2Fmain%2Fimdb%2Fdata.ndjson&gridURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Fxiaohk%2Fembeddings%2Fresolve%2Fmain%2Fimdb%2Fgrid.json

Credits

WizMap is created by Jay Wang, Fred Hohman, and Polo Chau.

Citation

To learn more about WizMap, please read our research paper (published at ACL'23 System Demonstration).

@article{wangWizMapScalableInteractive2023,
  title = {{{WizMap}}: {{Scalable Interactive Visualization}} for {{Exploring Large Machine Learning Embeddings}}},
  shorttitle = {{{WizMap}}},
  author = {Wang, Zijie J. and Hohman, Fred and Chau, Duen Horng},
  year = {2023},
  url = {http://arxiv.org/abs/2306.09328},
  urldate = {2023-06-16},
  archiveprefix = {arxiv},
  journal = {arXiv 2306.09328}
}

License

The software is available under the MIT License.

Contact

If you have any questions, feel free to open an issue or contact Jay Wang.