The open-source tool for building high-quality datasets and computer vision models.
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FiftyOne is an open source ML tool created by Voxel51 that helps you build high-quality datasets and computer vision models.
With FiftyOne, you can search, sort, filter, visualize, analyze, and improve your datasets without excess wrangling or writing custom scripts. It also provides powerful functionality for analyzing your models, allowing you to understand their strengths and weaknesses, visualize, diagnose, and correct their failure modes, and more. FiftyOne is designed to be lightweight and easily integrate into your existing CV/ML workflows.
You can get involved by joining our Slack community, reading our blog on Medium, and following us on social media:
Installation
You can install the latest stable version of FiftyOne via pip
:
pip install fiftyone
Consult the installation guide for troubleshooting and other information about getting up-and-running with FiftyOne.
Quickstart
Dive right into FiftyOne by launching the quickstart:
fiftyone quickstart
This command will download a small dataset, launch the App, and print some suggestions for exploring the dataset.
You can also check out this Colab notebook to try some common workflows with the quickstart dataset, or run through this Colab notebok for a more detailed overview of FiftyOne.
Documentation
Full documentation for FiftyOne is available online. In particular, see these resources:
Examples
Check out the fiftyone-examples repository for open source and community-contributed examples of using FiftyOne.
Contributing to FiftyOne
FiftyOne is open source and community contributions are welcome!
Check out the contribution guide to learn how to get involved.
Installing from source
This section explains how to install the latest development version of FiftyOne from source.
The instructions below are for macOS and Linux systems. Windows users may need to make adjustments.
Prerequisites
You will need:
- Python (3.6 or newer)
- Node.js - on Linux, we recommend using nvm to install an up-to-date version.
- Yarn - once Node.js is installed, you can install Yarn via
npm install -g yarn
- On Linux, you will need at least the
openssl
andlibcurl
packages. On Debian-based distributions, you will need to installlibcurl4
orlibcurl3
instead oflibcurl
, depending on the age of your distribution. For example:
# Ubuntu 18.04
sudo apt install libcurl4 openssl
# Fedora 32
sudo dnf install libcurl openssl
Installation
We strongly recommend that you install FiftyOne in a virtual environment to maintain a clean workspace. The install script is only supported in POSIX-based systems (e.g. Mac and Linux).
- Clone the repository:
git clone --recursive https://github.com/voxel51/fiftyone
cd fiftyone
- Run the installation script:
bash install.bash
NOTE: The install script adds to your nvm
settings in your ~/.bashrc
or ~/.bash_profile
, which is needed for installing and building the App. When you pull in new changes to the App, you will need to run yarn build-web
in the ./app
directory.
- If you want to use the
fiftyone.brain
package, you will need to install it separately after installing FiftyOne:
pip install fiftyone-brain
Customizing your ETA installation
Installing FiftyOne from source includes an ETA lite installation, which should be sufficient for most users. If you want a full ETA installation, or wish to otherwise customize your ETA installation, see here.
Developer installation
If you would like to contribute to FiftyOne, you should perform a developer installation using the -d
flag of the install script:
bash install.bash -d
Upgrading your source installation
To upgrade an existing source installation to the bleeding edge, simply pull the latest develop
branch and rerun the install script:
git checkout develop
git pull
bash install.bash [-d]
Generating documentation
See the docs guide for information on building and contributing to the documentation.
Uninstallation
You can uninstall FiftyOne as follows:
pip uninstall fiftyone fiftyone-brain fiftyone-db fiftyone-desktop
Citation
If you use FiftyOne in your research, feel free to cite the project (but only if you love it
@article{moore2020fiftyone,
title={FiftyOne},
author={Moore, B. E. and Corso, J. J.},
journal={GitHub. Note: https://github.com/voxel51/fiftyone},
year={2020}
}