fiftyone

The open-source tool for building high-quality datasets and computer vision models

voxel51
1113
149
Python

 

The open-source tool for building high-quality datasets and computer vision
models

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👋 hey there!

We created FiftyOne to supercharge your visual AI
projects by enabling you to visualize datasets, analyze models, and improve
data quality more efficiently than ever before 🤝

If you’re looking to scale to production-grade, collaborative, cloud-native
enterprise workloads, check out
FiftyOne Teams 🚀

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  installation   💻

As simple as:

pip install fiftyone
More details

Installation options

FiftyOne supports Python 3.9 - 3.11.

For most users, we recommend installing the latest release version of FiftyOne
via pip as shown above.

If you want to contribute to FiftyOne or install the latest development
version, then you can also perform a source install.

See the prerequisites section for system-specific setup
information.

We strongly recommend that you install FiftyOne in a
virtual environment
to maintain a clean workspace.

Consult the
installation guide
for troubleshooting and other information about getting up-and-running with
FiftyOne.

Install from source

Source installations

Follow the instructions below to install FiftyOne from source and build the
App.

You’ll need the following tools installed:

  • Python (3.9 - 3.11)
  • Node.js - on Linux, we recommend using
    nvm to install an up-to-date version.
  • Yarn - once Node.js is installed, you can
    enable Yarn via
    corepack enable

We strongly recommend that you install FiftyOne in a
virtual environment
to maintain a clean workspace.

If you are working in Google Colab,
skip to here.

First, clone the repository:

git clone https://github.com/voxel51/fiftyone
cd fiftyone

Then run the install script:

# Mac or Linux
bash install.bash

# Windows
.\install.bat

If you run into issues importing FiftyOne, you may need to add the path to the
cloned repository to your PYTHONPATH:

export PYTHONPATH=$PYTHONPATH:/path/to/fiftyone

Note that the install script adds to your nvm settings in your ~/.bashrc or
~/.bash_profile, which is needed for installing and building the App.

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

# Mac or Linux
bash install.bash

# Windows
.\install.bat

Rebuilding the App

When you pull in new changes to the App, you will need to rebuild it, which you
can do either by rerunning the install script or just running yarn build in
the ./app directory.

Developer installation

If you would like to
contribute to FiftyOne,
you should perform a developer installation using the -d flag of the install
script:

# Mac or Linux
bash install.bash -d

# Windows
.\install.bat -d

Although not required, developers typically prefer to configure their FiftyOne
installation to connect to a self-installed and managed instance of MongoDB,
which you can do by following
these simple steps.

Source installs in Google Colab

You can install from source in
Google Colab by running the following in a
cell and then restarting the runtime:

%%shell

git clone --depth 1 https://github.com/voxel51/fiftyone.git
cd fiftyone

# Mac or Linux
bash install.bash

# Windows
.\install.bat

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
Prerequisites for beginners

System-specific setup

Follow the instructions for your operating system or environment to perform
basic system setup before installing FiftyOne.

If you’re an experienced developer, you’ve likely already done this.

Linux

1. Install Python and other dependencies

These steps work on a clean install of Ubuntu Desktop 24.04, and should also
work on Ubuntu 24.04 and 22.04, and on Ubuntu Server:

sudo apt-get update
sudo apt-get upgrade
sudo apt-get install python3-venv python3-dev build-essential git-all libgl1-mesa-dev
  • On Linux, you will need at least the openssl and libcurl packages
  • On Debian-based distributions, you will need to install libcurl4 or
    libcurl3 instead of libcurl, depending on the age of your distribution
# Ubuntu
sudo apt install libcurl4 openssl

# Fedora
sudo dnf install libcurl openssl

2. Create and activate a virtual environment

python3 -m venv fiftyone_env
source fiftyone_env/bin/activate

3. Install FFmpeg (optional)

If you plan to work with video datasets, you’ll need to install
FFmpeg:

sudo apt-get install ffmpeg
MacOS

1. Install Xcode Command Line Tools

xcode-select --install

2. Install Homebrew

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

After running the above command, follow the instructions in your terminal to
complete the Homebrew installation.

3. Install Python

brew install [email protected]
brew install protobuf

4. Create and activate a virtual nvironment

python3 -m venv fiftyone_env
source fiftyone_env/bin/activate

5. Install FFmpeg (optional)

If you plan to work with video datasets, you’ll need to install
FFmpeg:

brew install ffmpeg
Windows

1. Install Python

⚠️ The version of Python that is available in the Microsoft Store is not
recommended ⚠️

Download a Python 3.9 - 3.11 installer from
python.org. Make sure to pick a 64-bit
version. For example, this
Python 3.10.11 installer.

Double-click on the installer to run it, and follow the steps in the installer.

  • Check the box to add Python to your PATH
  • At the end of the installer, there is an option to disable the PATH
    length limit. It is recommended to click this

2. Install Microsoft Visual C++

Download
Microsoft Visual C++ Redistributable.
Double-click on the installer to run it, and follow the steps in the installer.

3. Install Git

Download Git from this link. Double-click
on the installer to run it, and follow the steps in the installer.

4. Create and activate a virtual environment

  • Press Win + R. type cmd, and press Enter. Alternatively, search
    Command Prompt in the Start Menu.
  • Navigate to your project. cd C:\path\to\your\project
  • Create the environment python -m venv fiftyone_env
  • Activate the environment typing this in the command line window
    fiftyone_env\Scripts\activate
  • After activation, your command prompt should change and show the name of
    the virtual environment (fiftyon_env) C:\path\to\your\project

5. Install FFmpeg (optional)

If you plan to work with video datasets, you’ll need to install
FFmpeg.

Download an FFmpeg binary from here. Add
FFmpeg’s path (e.g., C:\ffmpeg\bin) to your PATH environmental variable.

Docker

Refer to
these instructions
to see how to build and run Docker images containing release or source builds
of FiftyOne.

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  quickstart   🚀

Dive right into FiftyOne by opening a Python shell and running the snippet
below, which downloads a
small dataset
and launches the
FiftyOne App so you
can explore it:

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")
session = fo.launch_app(dataset)

Then check out
this Colab notebook
to see some common workflows on the quickstart dataset.

Note that if you are running the above code in a script, you must include
session.wait() to block execution until you close the App. See
this page
for more information.

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  key features   🔑

https://github.com/user-attachments/assets/e6815108-aa4c-4021-a188-c93b3b75cc73

https://github.com/user-attachments/assets/261e2098-aace-4e5c-babb-d044d83a9a13

https://github.com/user-attachments/assets/ef6ff28f-8f3e-4a0d-b172-07227559fa91

https://github.com/user-attachments/assets/95f65ffc-b3b0-428a-9d59-64d425e1fe74

  • Rich Integrations:
    Works with popular deep learning libraries like PyTorch, Hugging Face,
    Ultralytics, and more.

https://github.com/user-attachments/assets/2e7e4046-5ec0-43b0-99c5-6cacd4743ed6

https://github.com/user-attachments/assets/7aa906c9-aab3-45c7-bd66-f388cac343e0

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  documentation   🪪

Full documentation for FiftyOne is available at
fiftyone.ai.

Tutorials Recipes Examples User Guide CLI Documentation API Reference

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  FiftyOne Teams   🏎️

Want to securely collaborate on billions of samples in the cloud and connect to
your compute resources to automate your workflows? Check out
FiftyOne Teams.

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  faq & troubleshooting   ⛓️‍💥

Refer to our
common issues
page to troubleshoot installation issues. If you’re still stuck, check our
frequently asked questions page for
more answers.

If you encounter an issue that the above resources don’t help you resolve, feel
free to open an issue on GitHub
or contact us on Slack or
Discord.

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  join our community   🤝

Connect with us through your preferred channels:

Discord
Slack
Medium
Twitter
LinkedIn
Facebook

🎊 Share how FiftyOne makes your visual AI projects a reality on social media
and tag us with @Voxel51 and #FiftyOne 🎊

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  contributors   🧡

FiftyOne and FiftyOne Brain are
open source and community contributions are welcome! Check out the
contribution guide
to learn how to get involved.

Special thanks to these amazing people for contributing to FiftyOne!

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  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}
}