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 development by enabling you to visualize and label your data, evaluate your models, and maximize data and model quality more efficiently than ever before 🤝
If you're looking to scale to production-grade, collaborative, cloud-native enterprise workloads, check out FiftyOne Enterprise 🚀
installation 💻
As simple as:
pip install fiftyone
More details
Installation options
FiftyOne supports Python 3.10 - 3.13.
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 (3.10 - 3.13)
- 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 fiftyoneThen run the install script:
# Mac or Linux bash install.sh # 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 main branch and rerun the install script:
git checkout main git pull # Mac or Linux bash install.sh # 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.sh -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.sh # 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
opensslandlibcurlpackages - On Debian-based distributions, you will need to install
libcurl4orlibcurl3instead oflibcurl, 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/activate3. 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 python@3.10 brew install protobuf
4. Create and activate a virtual environment
python3 -m venv fiftyone_env
source fiftyone_env/bin/activate5. 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 3.10 - 3.13 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
PATHlength 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. typecmd, and pressEnter. 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
(fiftyone_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.
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.
key features 🔑
- Native Annotation: Create and edit 2D and 3D labels directly in the App or integrate with your favorite annotation tools — then curate, QA, and iterate, all in one platform.
native_annotation.mp4
- Visualize Complex Datasets: Easily explore images, videos, and associated labels in a powerful visual interface.
slicendice.mp4
- Explore Embeddings: Select points of interest and view the corresponding samples/labels.
embeddings.mp4
- Analyze and Improve Models: Evaluate model performance, identify failure modes, and fine-tune your models.
model_eval.mp4
- Advanced Data Curation: Quickly find and fix data issues, annotation errors, and edge cases.
compute_mistakenness.mp4
- Rich Integrations: Works with popular deep learning libraries like PyTorch, Hugging Face, Ultralytics, and more.
similarity_search.mp4
- Open and Extensible: Customize and extend FiftyOne to fit your specific needs.
dashboards.mp4
documentation 🪪
Check out these resources to get up and running with FiftyOne:
| Getting Started Guides | Tutorials | Recipes | User Guide | Examples | API Reference | CLI Reference |
|---|
Full documentation is available at fiftyone.ai.
additional resources 🚁
| FiftyOne Enterprise | Building Plugins | Vector Search | Dataset Zoo | Model Zoo | FiftyOne Brain | VoxelGPT |
|---|
FiftyOne Enterprise 🏎️
Want to securely collaborate on billions of samples in the cloud and connect to your compute resources to automate your workflows? Check out FiftyOne Enterprise.
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 Discord.
join our community 🤝
Connect with us through your preferred channels:
🎊 Share how FiftyOne makes your visual AI projects a reality on social media and tag us with @Voxel51 and #FiftyOne 🎊
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!
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} }