| Name | fiftyone JSON |
| Version |
1.0.2
JSON |
| download |
| home_page | https://github.com/voxel51/fiftyone |
| Summary | FiftyOne: the open-source tool for building high-quality datasets and computer vision models |
| upload_time | 2024-11-08 11:38:54 |
| maintainer | None |
| docs_url | None |
| author | Voxel51, Inc. |
| requires_python | >=3.9 |
| license | Apache |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div align="center">
<p align="center">
<!-- prettier-ignore -->
<img src="https://user-images.githubusercontent.com/25985824/106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png" height="55px">
<img src="https://user-images.githubusercontent.com/25985824/106288518-24bb7680-6216-11eb-8f10-60052c519586.png" height="50px">
**The open-source tool for building high-quality datasets and computer vision
models**
---
<!-- prettier-ignore -->
<a href="https://voxel51.com/fiftyone">Website</a> •
<a href="https://voxel51.com/docs/fiftyone">Docs</a> •
<a href="https://colab.research.google.com/github/voxel51/fiftyone-examples/blob/master/examples/quickstart.ipynb">Try it Now</a> •
<a href="https://voxel51.com/docs/fiftyone/tutorials/index.html">Tutorials</a> •
<a href="https://github.com/voxel51/fiftyone-examples">Examples</a> •
<a href="https://voxel51.com/blog/">Blog</a> •
<a href="https://slack.voxel51.com">Community</a>
[](https://pypi.org/project/fiftyone)
[](https://pypi.org/project/fiftyone)
[](https://pepy.tech/project/fiftyone)
[](https://hub.docker.com/r/voxel51/fiftyone/)
[](https://github.com/voxel51/fiftyone/actions?query=workflow%3ABuild)
[](LICENSE)
[](https://slack.voxel51.com)
[](https://medium.com/voxel51)
[](https://share.hsforms.com/1zpJ60ggaQtOoVeBqIZdaaA2ykyk)
[](https://twitter.com/voxel51)
[](https://fiftyone.ai)
</p>
</div>
---
Nothing hinders the success of machine learning systems more than poor quality
data. And without the right tools, improving a model can be time-consuming and
inefficient.
[FiftyOne](https://fiftyone.ai) supercharges your machine learning workflows by
enabling you to visualize datasets and interpret models faster and more
effectively.
Use FiftyOne to get hands-on with your data, including visualizing complex
labels, evaluating your models, exploring scenarios of interest, identifying
failure modes, finding annotation mistakes, and much more!
You can get involved by joining our Slack community, reading our blog on
Medium, and following us on social media:
[](https://slack.voxel51.com)
[](https://medium.com/voxel51)
[](https://twitter.com/voxel51)
[](https://www.linkedin.com/company/voxel51)
[](https://www.facebook.com/voxel51)
## Installation
You can install the latest stable version of FiftyOne via `pip`:
```shell
pip install fiftyone
```
Consult the
[installation guide](https://voxel51.com/docs/fiftyone/getting_started/install.html)
for troubleshooting and other information about getting up-and-running with
FiftyOne.
## Quickstart
Dive right into FiftyOne by opening a Python shell and running the snippet
below, which downloads a
[small dataset](https://voxel51.com/docs/fiftyone/user_guide/dataset_zoo/datasets.html#quickstart)
and launches the
[FiftyOne App](https://voxel51.com/docs/fiftyone/user_guide/app.html) so you
can explore it:
```py
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](https://colab.research.google.com/github/voxel51/fiftyone-examples/blob/master/examples/quickstart.ipynb)
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](https://voxel51.com/docs/fiftyone/user_guide/app.html#creating-a-session)
for more information.
## Documentation
Full documentation for FiftyOne is available at
[fiftyone.ai](https://fiftyone.ai). In particular, see these resources:
- [Tutorials](https://voxel51.com/docs/fiftyone/tutorials/index.html)
- [Recipes](https://voxel51.com/docs/fiftyone/recipes/index.html)
- [User Guide](https://voxel51.com/docs/fiftyone/user_guide/index.html)
- [CLI Documentation](https://voxel51.com/docs/fiftyone/cli/index.html)
- [API Reference](https://voxel51.com/docs/fiftyone/api/fiftyone.html)
## Examples
Check out the [fiftyone-examples](https://github.com/voxel51/fiftyone-examples)
repository for open source and community-contributed examples of using
FiftyOne.
## Contributing to FiftyOne
FiftyOne and [FiftyOne Brain](https://github.com/voxel51/fiftyone-brain) are
open source and community contributions are welcome!
Check out the
[contribution guide](https://github.com/voxel51/fiftyone/blob/develop/CONTRIBUTING.md)
to learn how to get involved.
## Installing from source
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](#source-installs-in-google-colab).
### Prerequisites
You will need:
- [Python](https://www.python.org) (3.9 - 3.11)
- [Node.js](https://nodejs.org) - on Linux, we recommend using
[nvm](https://github.com/nvm-sh/nvm) to install an up-to-date version.
- [Yarn](https://yarnpkg.com) - once Node.js is installed, you can
[enable Yarn](https://yarnpkg.com/getting-started/install) via
`corepack enable`
- 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.
For example:
```shell
# Ubuntu
sudo apt install libcurl4 openssl
# Fedora
sudo dnf install libcurl openssl
```
### Installation
We strongly recommend that you install FiftyOne in a
[virtual environment](https://voxel51.com/docs/fiftyone/getting_started/virtualenv.html)
to maintain a clean workspace.
First, clone the repository:
```shell
git clone https://github.com/voxel51/fiftyone
cd fiftyone
```
Then run the install script:
```shell
# Mac or Linux
bash install.bash
# Windows
.\install.bat
```
**NOTE:** If you run into issues importing FiftyOne, you may need to add the
path to the cloned repository to your `PYTHONPATH`:
```shell
export PYTHONPATH=$PYTHONPATH:/path/to/fiftyone
```
**NOTE:** 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.
### 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:
```shell
git checkout develop
git pull
bash install.bash
```
### Developer installation
If you would like to
[contribute to FiftyOne](https://github.com/voxel51/fiftyone/blob/develop/CONTRIBUTING.md),
you should perform a developer installation using the `-d` flag of the install
script:
```shell
# 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](https://docs.voxel51.com/user_guide/config.html#configuring-a-mongodb-connection).
### Source installs in Google Colab
You can install from source in
[Google Colab](https://colab.research.google.com) by running the following in a
cell and then **restarting the runtime**:
```shell
%%shell
git clone --depth 1 https://github.com/voxel51/fiftyone.git
cd fiftyone
# Mac or Linux
bash install.bash
# Windows
.\install.bat
```
### Docker installs
Refer to
[these instructions](https://voxel51.com/docs/fiftyone/environments/index.html#docker)
to see how to build and run Docker images containing source or release builds
of FiftyOne.
### Generating documentation
See the
[docs guide](https://github.com/voxel51/fiftyone/blob/develop/docs/README.md)
for information on building and contributing to the documentation.
## Uninstallation
You can uninstall FiftyOne as follows:
```shell
pip uninstall fiftyone fiftyone-brain fiftyone-db
```
## Contributors
Special thanks to these amazing people for contributing to FiftyOne! 🙌
<a href="https://github.com/voxel51/fiftyone/graphs/contributors">
<img src="https://contrib.rocks/image?repo=voxel51/fiftyone" />
</a>
## Citation
If you use FiftyOne in your research, feel free to cite the project (but only
if you love it 😊):
```bibtex
@article{moore2020fiftyone,
title={FiftyOne},
author={Moore, B. E. and Corso, J. J.},
journal={GitHub. Note: https://github.com/voxel51/fiftyone},
year={2020}
}
```
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"description": "<div align=\"center\">\n<p align=\"center\">\n\n<!-- prettier-ignore -->\n<img src=\"https://user-images.githubusercontent.com/25985824/106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"55px\"> \n<img src=\"https://user-images.githubusercontent.com/25985824/106288518-24bb7680-6216-11eb-8f10-60052c519586.png\" height=\"50px\">\n\n**The open-source tool for building high-quality datasets and computer vision\nmodels**\n\n---\n\n<!-- prettier-ignore -->\n<a href=\"https://voxel51.com/fiftyone\">Website</a> \u2022\n<a href=\"https://voxel51.com/docs/fiftyone\">Docs</a> \u2022\n<a href=\"https://colab.research.google.com/github/voxel51/fiftyone-examples/blob/master/examples/quickstart.ipynb\">Try it Now</a> \u2022\n<a href=\"https://voxel51.com/docs/fiftyone/tutorials/index.html\">Tutorials</a> \u2022\n<a href=\"https://github.com/voxel51/fiftyone-examples\">Examples</a> \u2022\n<a href=\"https://voxel51.com/blog/\">Blog</a> \u2022\n<a href=\"https://slack.voxel51.com\">Community</a>\n\n[](https://pypi.org/project/fiftyone)\n[](https://pypi.org/project/fiftyone)\n[](https://pepy.tech/project/fiftyone)\n[](https://hub.docker.com/r/voxel51/fiftyone/)\n[](https://github.com/voxel51/fiftyone/actions?query=workflow%3ABuild)\n[](LICENSE)\n[](https://slack.voxel51.com)\n[](https://medium.com/voxel51)\n[](https://share.hsforms.com/1zpJ60ggaQtOoVeBqIZdaaA2ykyk)\n[](https://twitter.com/voxel51)\n\n[](https://fiftyone.ai)\n\n</p>\n</div>\n\n---\n\nNothing hinders the success of machine learning systems more than poor quality\ndata. And without the right tools, improving a model can be time-consuming and\ninefficient.\n\n[FiftyOne](https://fiftyone.ai) supercharges your machine learning workflows by\nenabling you to visualize datasets and interpret models faster and more\neffectively.\n\nUse FiftyOne to get hands-on with your data, including visualizing complex\nlabels, evaluating your models, exploring scenarios of interest, identifying\nfailure modes, finding annotation mistakes, and much more!\n\nYou can get involved by joining our Slack community, reading our blog on\nMedium, and following us on social media:\n\n[](https://slack.voxel51.com)\n[](https://medium.com/voxel51)\n[](https://twitter.com/voxel51)\n[](https://www.linkedin.com/company/voxel51)\n[](https://www.facebook.com/voxel51)\n\n## Installation\n\nYou can install the latest stable version of FiftyOne via `pip`:\n\n```shell\npip install fiftyone\n```\n\nConsult the\n[installation guide](https://voxel51.com/docs/fiftyone/getting_started/install.html)\nfor troubleshooting and other information about getting up-and-running with\nFiftyOne.\n\n## Quickstart\n\nDive right into FiftyOne by opening a Python shell and running the snippet\nbelow, which downloads a\n[small dataset](https://voxel51.com/docs/fiftyone/user_guide/dataset_zoo/datasets.html#quickstart)\nand launches the\n[FiftyOne App](https://voxel51.com/docs/fiftyone/user_guide/app.html) so you\ncan explore it:\n\n```py\nimport fiftyone as fo\nimport fiftyone.zoo as foz\n\ndataset = foz.load_zoo_dataset(\"quickstart\")\nsession = fo.launch_app(dataset)\n```\n\nThen check out\n[this Colab notebook](https://colab.research.google.com/github/voxel51/fiftyone-examples/blob/master/examples/quickstart.ipynb)\nto see some common workflows on the quickstart dataset.\n\nNote that if you are running the above code in a script, you must include\n`session.wait()` to block execution until you close the App. See\n[this page](https://voxel51.com/docs/fiftyone/user_guide/app.html#creating-a-session)\nfor more information.\n\n## Documentation\n\nFull documentation for FiftyOne is available at\n[fiftyone.ai](https://fiftyone.ai). In particular, see these resources:\n\n- [Tutorials](https://voxel51.com/docs/fiftyone/tutorials/index.html)\n- [Recipes](https://voxel51.com/docs/fiftyone/recipes/index.html)\n- [User Guide](https://voxel51.com/docs/fiftyone/user_guide/index.html)\n- [CLI Documentation](https://voxel51.com/docs/fiftyone/cli/index.html)\n- [API Reference](https://voxel51.com/docs/fiftyone/api/fiftyone.html)\n\n## Examples\n\nCheck out the [fiftyone-examples](https://github.com/voxel51/fiftyone-examples)\nrepository for open source and community-contributed examples of using\nFiftyOne.\n\n## Contributing to FiftyOne\n\nFiftyOne and [FiftyOne Brain](https://github.com/voxel51/fiftyone-brain) are\nopen source and community contributions are welcome!\n\nCheck out the\n[contribution guide](https://github.com/voxel51/fiftyone/blob/develop/CONTRIBUTING.md)\nto learn how to get involved.\n\n## Installing from source\n\nThe instructions below are for macOS and Linux systems. Windows users may need\nto make adjustments. If you are working in Google Colab,\n[skip to here](#source-installs-in-google-colab).\n\n### Prerequisites\n\nYou will need:\n\n- [Python](https://www.python.org) (3.9 - 3.11)\n- [Node.js](https://nodejs.org) - on Linux, we recommend using\n [nvm](https://github.com/nvm-sh/nvm) to install an up-to-date version.\n- [Yarn](https://yarnpkg.com) - once Node.js is installed, you can\n [enable Yarn](https://yarnpkg.com/getting-started/install) via\n `corepack enable`\n- On Linux, you will need at least the `openssl` and `libcurl` packages. On\n Debian-based distributions, you will need to install `libcurl4` or\n `libcurl3` instead of `libcurl`, depending on the age of your distribution.\n For example:\n\n```shell\n# Ubuntu\nsudo apt install libcurl4 openssl\n\n# Fedora\nsudo dnf install libcurl openssl\n```\n\n### Installation\n\nWe strongly recommend that you install FiftyOne in a\n[virtual environment](https://voxel51.com/docs/fiftyone/getting_started/virtualenv.html)\nto maintain a clean workspace.\n\nFirst, clone the repository:\n\n```shell\ngit clone https://github.com/voxel51/fiftyone\ncd fiftyone\n```\n\nThen run the install script:\n\n```shell\n# Mac or Linux\nbash install.bash\n\n# Windows\n.\\install.bat\n```\n\n**NOTE:** If you run into issues importing FiftyOne, you may need to add the\npath to the cloned repository to your `PYTHONPATH`:\n\n```shell\nexport PYTHONPATH=$PYTHONPATH:/path/to/fiftyone\n```\n\n**NOTE:** The install script adds to your `nvm` settings in your `~/.bashrc` or\n`~/.bash_profile`, which is needed for installing and building the App\n\n**NOTE:** When you pull in new changes to the App, you will need to rebuild it,\nwhich you can do either by rerunning the install script or just running\n`yarn build` in the `./app` directory.\n\n### Upgrading your source installation\n\nTo upgrade an existing source installation to the bleeding edge, simply pull\nthe latest `develop` branch and rerun the install script:\n\n```shell\ngit checkout develop\ngit pull\nbash install.bash\n```\n\n### Developer installation\n\nIf you would like to\n[contribute to FiftyOne](https://github.com/voxel51/fiftyone/blob/develop/CONTRIBUTING.md),\nyou should perform a developer installation using the `-d` flag of the install\nscript:\n\n```shell\n# Mac or Linux\nbash install.bash -d\n\n# Windows\n.\\install.bat -d\n```\n\nAlthough not required, developers typically prefer to configure their FiftyOne\ninstallation to connect to a self-installed and managed instance of MongoDB,\nwhich you can do by following\n[these simple steps](https://docs.voxel51.com/user_guide/config.html#configuring-a-mongodb-connection).\n\n### Source installs in Google Colab\n\nYou can install from source in\n[Google Colab](https://colab.research.google.com) by running the following in a\ncell and then **restarting the runtime**:\n\n```shell\n%%shell\n\ngit clone --depth 1 https://github.com/voxel51/fiftyone.git\ncd fiftyone\n\n# Mac or Linux\nbash install.bash\n\n# Windows\n.\\install.bat\n```\n\n### Docker installs\n\nRefer to\n[these instructions](https://voxel51.com/docs/fiftyone/environments/index.html#docker)\nto see how to build and run Docker images containing source or release builds\nof FiftyOne.\n\n### Generating documentation\n\nSee the\n[docs guide](https://github.com/voxel51/fiftyone/blob/develop/docs/README.md)\nfor information on building and contributing to the documentation.\n\n## Uninstallation\n\nYou can uninstall FiftyOne as follows:\n\n```shell\npip uninstall fiftyone fiftyone-brain fiftyone-db\n```\n\n## Contributors\n\nSpecial thanks to these amazing people for contributing to FiftyOne! \ud83d\ude4c\n\n<a href=\"https://github.com/voxel51/fiftyone/graphs/contributors\">\n <img src=\"https://contrib.rocks/image?repo=voxel51/fiftyone\" />\n</a>\n\n## Citation\n\nIf you use FiftyOne in your research, feel free to cite the project (but only\nif you love it \ud83d\ude0a):\n\n```bibtex\n@article{moore2020fiftyone,\n title={FiftyOne},\n author={Moore, B. E. and Corso, J. J.},\n journal={GitHub. Note: https://github.com/voxel51/fiftyone},\n year={2020}\n}\n```\n",
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