base on Refine high-quality datasets and visual AI models <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"> &nbsp; <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} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"3050","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"