The open-source tool for building high-quality datasets and computer vision models
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We created an open-source tool that supercharges your computer vision and machine learning workflows by enabling you to visualize datasets, analyze models, and improve data quality more efficiently than ever before. Embark with us in this adventure 🤝. FiftyOne.
As simple as:
pip install fiftyoneMore details here
FiftyOne supports Python 3.9 - 3.11. See the prerequisites section for system specific information. We provide two ways for being installed. The first one is through PyPI, and the second is through a local installation. PyPI is the straight forward installation method if you are not looking for any changes in the source code, if you want to make changes to the source code, then a local installation is recommended.
We strongly recommend that you install FiftyOne in a virtual environment to maintain a clean workspace. The prerequisites section also contains instructions for creating system specific virtual environments.
Installing the library from PyPI with pip is the easiest way to get started
with fiftyone. You can install the latest stable version of fiftyone via
pip:
Consult the installation guide for troubleshooting and other information about getting up-and-running with FiftyOne.
Install from source
To install from source, you need to clone the repository and install the
library using pip with editable mode enabled. The instructions below are for
macOS and Linux systems. Windows users may need to make adjustments. 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.bash
# Windows
.\install.batNOTE: 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/fiftyoneNOTE: The install script adds to your nvm settings in your ~/.bashrc or
~/.bash_profile, which is needed for installing and building the App
NOTE: 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.
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.bashIf 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 -dAlthough 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.
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.batSee the docs guide for information on building and contributing to the documentation.
You can uninstall FiftyOne as follows:
pip uninstall fiftyone fiftyone-brain fiftyone-dbPrerequisites for beginners
FiftyOne supports Python 3.9 - 3.11. To get started, select the guide for your operating system or environment, if you are an experienced developer you can skip this section. If you are looking for scaling solution to be installed in Cloud Enterprise Systems, please take a look of FiftyOne Teams here
Windows
Note:
Download a Python installer from python.org. Choose Python 3.9, 3.10, or 3.11 and 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, and to install py.
- At the end of the installer, there is an option to disable the PATH length limit. It is recommended to click this.
Download Git from this link. Double-click on the installer to run it, and follow the steps in the installer.
Download Microsoft Visual C++ Redistributable. Double-click on the installer to run it, and follow the steps in the installer.
Download FFmpeg binary from here. Set FFmpeg's path (e.g., C:\ffmpeg\bin) to the PATH environmental variable on Windows.
- 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
(fiftyon_env) C:\path\to\your\project - Now you are ready to install FiftyOne. Full instructions can be found here.
- Once you want to deactivate your environment, just type
deactivate
Linux
You may need to install some additional libraries on Ubuntu Linux. 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 build-essential python3-dev git-all libgl1-mesa-dev ffmpeg-
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.For example:
# Ubuntu
sudo apt install libcurl4 openssl
# Fedora
sudo dnf install libcurl opensslpython3 -m venv fiftyone_env
source fiftyone_env/bin/activateNow you are ready to install FiftyOne. Full instructions can be found here
MacOS
xcode-select --install/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"After you install it, follow the instructions from the Homebrew installation to set it up.
brew install python@3.9
brew install protobuf
# optional but recommendeded for full video dataset support
brew install ffmpegpython3 -m venv fiftyone_env
source fiftyone_env/bin/activateNow you are ready to install FiftyOne. Full instructions can be found here.
Docker
Refer to these instructions to see how to build and run Docker images containing source or release builds of FiftyOne.
Important Notes: Remember, you will need...
- 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
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.
- 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.
fiftyone_model_eval.mp4
- Advanced Data Curation: Quickly find and fix data issues, annotation errors, and edge cases.
fiftyone_uniqueness.mp4
fiftyone_similarity_search.mp4
- Rich Integration: Works with popular deep learning libraries like TensorFlow, PyTorch, Keras, and more.
zeroshot.mp4
- Open and Extensible Customize and extend FiftyOne to fit your specific needs.
fiftyone_dashboards.mp4
Full documentation for FiftyOne is available at fiftyone.ai. In particular, see these resources:
Do you need to securely collaborate on datasets with millions of samples in the cloud and leverage built-in workflow automations? Check out FiftyOne Teams.
This page lists common issues encountered when installing FiftyOne and possible solutions. If you encounter an issue that this page doesn’t help you resolve, feel free to open an issue on GitHub or contact us on Slack or Discord.
FAQ: Maybe you are facing a situation already solved, take a look of the frequently asked questions.
FiftyOne and FiftyOne Brain are open source and community contributions are welcome!
Check out the contribution guide to learn how to get involved.
Connect with us through your preferred channels:
Share your workflow improvements on social media and tag us @Voxel51 and #FiftyOne!.
🎊 You will be in our rewarded list. 🎊
Special thanks to these amazing people for contributing to FiftyOne! 🙌
