Skip to main content

Hover

Explore and label on a map of raw data.

Get enough to feed your model in no time.

PyPI Version Conda Version Downloads Main Build Status Nightly Build Status Codacy Grade Codacy Coverage

hover speeds up data labeling through embedding + visualization + callbacks.

  • You just need raw data and an embedding to get a map.
  • Explore the map to find "zones" that are easy and those that are tricky.
  • Start the conquest of your data by coloring the zones through wisdom!

GIF Demo

🚀 Live Demos

With code

  • edit & run code in your browser to get a labeling interface, with guides along the way.

Without code

  • go directly to a labeling interface, pre-coded and hosted on Binder.

✨ Features (click bullets to show GIF)

It's fast because it labels data in bulk.

🔭 A semantic scatter plot of your data for labeling, equipped with

  • Tooltip for each point on mouse hover
  • Table view for inspecting all selected points
  • Toggle buttons that clearly distinguish data subsets
  • Search widgets for ad-hoc data highlight

It's accurate because multiple angles work together.

🔬 Supplementary views to use in conjunction with the annotator, including

  • Finder: filter data by search criteria
  • Softlabel: active learning by in-the-loop model prediction score
  • Snorkel: custom functions for labeling and filtering

It's flexible (and fun!) because the process never gets old.

🧰 Additional tools and options that allow you to

  • Go to higher dimensions (3D? 4D?) and choose your xy-axes
  • Consecutively select across areas, dimensions, and views
  • Kick outliers and fix mistakes

💡 Click on the bullet points above to view GIFs!

📦 Install

Python: 3.8+

OS: Linux & Mac & Windows

PyPI (for all releases): pip install hover

Conda-forge (for 0.6.0 and above): conda install -c conda-forge hover

For Windows users, we recommend Windows Subsystem for Linux.

📖 Resources

🎏 Announcements

  • Jan 21, 2023 version 0.8.0 is now available. Check out the changelog for details 🥳.

🔔 Remarks

Shoutouts

  • Thanks to Bokeh because hover would not exist without linked plots and callbacks, or be nearly as good without embeddable server apps.
  • Thanks to Philip Vollet for sharing hover with the community even when it was really green.

Contributing

  • All feedbacks are welcome, especially what you find lacking and want it fixed!
  • ./requirements-dev.txt lists required packages for development.
  • Pull requests are advised to use a superset of the pre-commit hooks listed in .pre-commit-config.yaml.

Citation

If you have found hover useful to your work, please let us know 🤗

@misc{hover,
  title={{hover}: label data at scale},
  url={https://github.com/phurwicz/hover},
  note={Open software from https://github.com/phurwicz/hover},
  author={
    Pavel Hurwicz and
    Haochuan Wei},
  year={2021},
}

Metadata

Release files for hover 0.8.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for hover 0.8.1
File Size Uploaded
hover-0.8.1.tar.gz 57.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for hover 0.8.1
File Interpreter ABI Platform
hover-0.8.1-py3-none-any.whl Python 3 none any Details

Total release size: 122.3 kB

Release files / hover-0.8.1.tar.gz

Download URL hover-0.8.1.tar.gz
Size 57.7 kB
Tags Source
SHA-256 checksum
How to use checksums
3852ea8ab36f1f4d50f9ab649e2bda3ec2b78ffda8d7a0ba0e3590b5fa2a35fc
BLAKE2b-256 checksum
How to use checksums
c6f0abd2eaaca4538dcab4a9cc7502031079bf6f1082112cdc92a25e7713125a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.15

Release files / hover-0.8.1-py3-none-any.whl

Download URL hover-0.8.1-py3-none-any.whl
Size 64.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f9ab3ff6ce77d328302d32de9c755858b1c23f93550a973e69c5572196de39db
BLAKE2b-256 checksum
How to use checksums
f973c882a4d900947955627af28cbab94d1312f38240aabdaf739ea6a936b6ba
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.15

Release history Release notifications | RSS feed

This release

0.8.1 This release

2 release files

0.7.0

2 release files

0.6.0

2 release files

0.5.0

2 release files

0.4.1

2 release files

0.3.2

2 release files

0.2.4

2 release files

0.0.1

2 release files

0.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page