# WizMap <a href="https://poloclub.github.io/wizmap/"><img align="right" src="../src/imgs/icon-wizmap.svg" height="38"></img></a>
[](https://github.com/poloclub/wizmap/actions/workflows/build.yml)
[](https://github.com/poloclub/wizmap/blob/main/LICENSE)
[](https://www.npmjs.com/package/wizmap)
[](https://pypi.python.org/pypi/wizmap)
[](https://colab.research.google.com/drive/1GNdmBnc5UA7OYBZPtHu244eiAN-0IMZA?usp=sharing)
[](https://mybinder.org/v2/gh/poloclub/wizmap/master?urlpath=lab/tree/example/imdb.ipynb)
[](https://arxiv.org/abs/2306.09328)
<!-- [](https://doi.org/10.1145/3491101.3519653) -->
Exploring and interpreting large embeddings in your browser!
<table>
<tr>
<td colspan="3"><video width="100%" src='https://github.com/poloclub/wizmap/assets/15007159/26d26336-e611-4d00-b535-8837da59be82'></td>
</tr>
<tr></tr>
<tr>
<td><a href="https://poloclub.github.io/wizmap">🚀 Live Demo</a></td>
<td><a href="https://youtu.be/8fJG87QVceQ">📺 Demo Video</a></td>
<td><a href="https://arxiv.org/abs/2306.09328">📖 Research Paper</a></td>
</tr>
</table>
## 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.
<table>
<tr>
<td>✅</td>
<td>Scalable to <strong>millions</strong> of embedding point</td>
</tr>
<tr></tr>
<tr>
<td>✅</td>
<td><strong>Multi-resolution</strong> embedding summaries</td>
</tr>
<tr></tr>
<tr>
<td>✅</td>
<td><strong>Fast</strong> embedding search</td>
</tr>
<tr></tr>
<tr>
<td>✅</td>
<td><strong>Multimodal</strong> data (text and image)</td>
</tr>
<tr></tr>
<tr>
<td>✅</td>
<td>Animated <strong>embedding evolution</strong></td>
</tr>
<tr></tr>
<tr>
<td>✅</td>
<td>Support <strong>computational notebooks</strong> (e.g., Jupyter, Colab, VS Code)</td>
</tr>
<tr></tr>
<tr>
<td>✅</td>
<td><strong>Sharable URLs</strong></td>
</tr>
<tr></tr>
</table>
## WizMap Gallery
<table>
<tr>
<td><a href="https://poloclub.github.io/wizmap/?dataset=diffusiondb"><img src="https://i.imgur.com/hTcu3rJ.jpg" width="100%"></a></td>
<td><a href="https://poloclub.github.io/wizmap/?dataset=diffusiondb"><img src="https://i.imgur.com/AYUEHWz.png" width="100%"></a></td>
<td><a href="https://poloclub.github.io/wizmap/?dataset=diffusiondb"><img src="https://i.imgur.com/iyBzqHQ.png" width="100%"></a></td>
</tr>
<tr></tr>
<tr>
<td><a href="https://poloclub.github.io/wizmap/?dataset=diffusiondb">DiffusionDB Prompts + Images</a></td>
<td><a href="https://poloclub.github.io/wizmap/?dataset=acl-abstracts">ACL Paper Abstracts</a></td>
<td><a href="https://poloclub.github.io/wizmap/?dataset=imdb">IMDB Review Comments</a></td>
</tr>
<tr></tr>
<tr>
<td>1.8M text + 1.8M images</a></td>
<td>63k text</td>
<td>25k text</td>
</tr>
<tr></tr>
<tr>
<td><code>CLIP</code> Embedding</td>
<td><code>all-MiniLM-L6-v2</code> Embedding</td>
<td><code>all-MiniLM-L6-v2</code> Embedding</td>
</tr>
<tr></tr>
</table>
[Submit a PR](https://github.com/poloclub/wizmap/pulls) to add your WizMap here! You can share your WizMap using a [unique URL](#share-my-wizmap).
## Web Demo
For a live web demo, visit: <https://poloclub.github.io/wizmap>.
## Get Started
Clone or download this repository:
```bash
git clone git@github.com:poloclub/wizmap.git
```
Install the dependencies:
```bash
npm install
```
Then run WizMap:
```bash
npm run dev
```
Navigate to [localhost:3000](https://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.
```bash
pip install wizmap
```
Then take a look at this [notebook](./example/imdb.ipynb) for a detailed guide. 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.
1. **Browser**: You can click the folder icon on the bottom right of the [WizMap demo](https://poloclub.github.io/wizmap/) and enter the URLs to the JSON files in the pop-up window.
2. **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](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) 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 <a href='https://zijie.wang/' target='_blank'>Jay Wang</a>, <a href='http://fredhohman.com/' target='_blank'>Fred Hohman</a>, and <a href='https://poloclub.github.io/polochau/' target='_blank'>Polo Chau</a>.
## Citation
To learn more about WizMap, please read our [research paper](https://arxiv.org/abs/2306.09328) (published at [ACL'23 System Demonstration](https://2023.aclweb.org/program/accepted_system_demonstration/)).
```bibtex
@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](https://github.com/poloclub/wizmap/blob/master/LICENSE).
## Contact
If you have any questions, feel free to [open an issue](https://github.com/poloclub/wizmap/issues/new) or contact [Jay Wang](https://zijie.wang).
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"description": "# WizMap <a href=\"https://poloclub.github.io/wizmap/\"><img align=\"right\" src=\"../src/imgs/icon-wizmap.svg\" height=\"38\"></img></a>\n\n[](https://github.com/poloclub/wizmap/actions/workflows/build.yml)\n[](https://github.com/poloclub/wizmap/blob/main/LICENSE)\n[](https://www.npmjs.com/package/wizmap)\n[](https://pypi.python.org/pypi/wizmap)\n[](https://colab.research.google.com/drive/1GNdmBnc5UA7OYBZPtHu244eiAN-0IMZA?usp=sharing)\n[](https://mybinder.org/v2/gh/poloclub/wizmap/master?urlpath=lab/tree/example/imdb.ipynb)\n[](https://arxiv.org/abs/2306.09328)\n\n<!-- [](https://doi.org/10.1145/3491101.3519653) -->\n\nExploring and interpreting large embeddings in your browser!\n\n<table>\n <tr>\n <td colspan=\"3\"><video width=\"100%\" src='https://github.com/poloclub/wizmap/assets/15007159/26d26336-e611-4d00-b535-8837da59be82'></td>\n </tr>\n <tr></tr>\n <tr>\n <td><a href=\"https://poloclub.github.io/wizmap\">\ud83d\ude80 Live Demo</a></td>\n <td><a href=\"https://youtu.be/8fJG87QVceQ\">\ud83d\udcfa Demo Video</a></td>\n <td><a href=\"https://arxiv.org/abs/2306.09328\">\ud83d\udcd6 Research Paper</a></td>\n </tr>\n</table>\n\n## What is WizMap?\n\nWizMap 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.\n\n<table>\n <tr>\n <td>\u2705</td>\n <td>Scalable to <strong>millions</strong> of embedding point</td>\n </tr>\n <tr></tr>\n <tr>\n <td>\u2705</td>\n <td><strong>Multi-resolution</strong> embedding summaries</td>\n </tr>\n <tr></tr>\n <tr>\n <td>\u2705</td>\n <td><strong>Fast</strong> embedding search</td>\n </tr>\n <tr></tr>\n <tr>\n <td>\u2705</td>\n <td><strong>Multimodal</strong> data (text and image)</td>\n </tr>\n <tr></tr>\n <tr>\n <td>\u2705</td>\n <td>Animated <strong>embedding evolution</strong></td>\n </tr>\n <tr></tr>\n <tr>\n <td>\u2705</td>\n <td>Support <strong>computational notebooks</strong> (e.g., Jupyter, Colab, VS Code)</td>\n </tr>\n <tr></tr>\n <tr>\n <td>\u2705</td>\n <td><strong>Sharable URLs</strong></td>\n </tr>\n <tr></tr>\n</table>\n\n## WizMap Gallery\n\n<table>\n <tr>\n <td><a href=\"https://poloclub.github.io/wizmap/?dataset=diffusiondb\"><img src=\"https://i.imgur.com/hTcu3rJ.jpg\" width=\"100%\"></a></td>\n <td><a href=\"https://poloclub.github.io/wizmap/?dataset=diffusiondb\"><img src=\"https://i.imgur.com/AYUEHWz.png\" width=\"100%\"></a></td>\n <td><a href=\"https://poloclub.github.io/wizmap/?dataset=diffusiondb\"><img src=\"https://i.imgur.com/iyBzqHQ.png\" width=\"100%\"></a></td>\n </tr>\n <tr></tr>\n <tr>\n <td><a href=\"https://poloclub.github.io/wizmap/?dataset=diffusiondb\">DiffusionDB Prompts + Images</a></td>\n <td><a href=\"https://poloclub.github.io/wizmap/?dataset=acl-abstracts\">ACL Paper Abstracts</a></td>\n <td><a href=\"https://poloclub.github.io/wizmap/?dataset=imdb\">IMDB Review Comments</a></td>\n </tr>\n <tr></tr>\n <tr>\n <td>1.8M text + 1.8M images</a></td>\n <td>63k text</td>\n <td>25k text</td>\n </tr>\n <tr></tr>\n <tr>\n <td><code>CLIP</code> Embedding</td>\n <td><code>all-MiniLM-L6-v2</code> Embedding</td>\n <td><code>all-MiniLM-L6-v2</code> Embedding</td>\n </tr>\n <tr></tr>\n</table>\n\n[Submit a PR](https://github.com/poloclub/wizmap/pulls) to add your WizMap here! You can share your WizMap using a [unique URL](#share-my-wizmap).\n\n## Web Demo\n\nFor a live web demo, visit: <https://poloclub.github.io/wizmap>.\n\n## Get Started\n\nClone or download this repository:\n\n```bash\ngit clone git@github.com:poloclub/wizmap.git\n```\n\nInstall the dependencies:\n\n```bash\nnpm install\n```\n\nThen run WizMap:\n\n```bash\nnpm run dev\n```\n\nNavigate to [localhost:3000](https://localhost:3000). You should see WizMap running in your browser :)\n\n## Use My Own Embeddings\n\nTo use WizMap with your embeddings, you first need to install the `wizmap` Python library.\n\n```bash\npip install wizmap\n```\n\nThen take a look at this [notebook](./example/imdb.ipynb) for a detailed guide. 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.\n\nAfter generating the JSON files, you have two options to use WizMap.\n\n1. **Browser**: You can click the folder icon on the bottom right of the [WizMap demo](https://poloclub.github.io/wizmap/) and enter the URLs to the JSON files in the pop-up window.\n2. **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()`.\n\n## Share My WizMap\n\nYou can easily share your embedding maps with collaborators by copying the unique URL of WizMap from your browser. For example, the [URL below](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) points to an IMDB embedding in WizMap.\n\n```\nhttps://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\n```\n\n## Credits\n\nWizMap is created by <a href='https://zijie.wang/' target='_blank'>Jay Wang</a>, <a href='http://fredhohman.com/' target='_blank'>Fred Hohman</a>, and <a href='https://poloclub.github.io/polochau/' target='_blank'>Polo Chau</a>.\n\n## Citation\n\nTo learn more about WizMap, please read our [research paper](https://arxiv.org/abs/2306.09328) (published at [ACL'23 System Demonstration](https://2023.aclweb.org/program/accepted_system_demonstration/)).\n\n```bibtex\n@article{wangWizMapScalableInteractive2023,\n title = {{{WizMap}}: {{Scalable Interactive Visualization}} for {{Exploring Large Machine Learning Embeddings}}},\n shorttitle = {{{WizMap}}},\n author = {Wang, Zijie J. and Hohman, Fred and Chau, Duen Horng},\n year = {2023},\n url = {http://arxiv.org/abs/2306.09328},\n urldate = {2023-06-16},\n archiveprefix = {arxiv},\n journal = {arXiv 2306.09328}\n}\n```\n\n## License\n\nThe software is available under the [MIT License](https://github.com/poloclub/wizmap/blob/master/LICENSE).\n\n## Contact\n\nIf you have any questions, feel free to [open an issue](https://github.com/poloclub/wizmap/issues/new) or contact [Jay Wang](https://zijie.wang).\n",
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