[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9662":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":43,"readmeContent":44,"aiSummary":45,"trendingCount":16,"starSnapshotCount":16,"syncStatus":46,"lastSyncTime":47,"discoverSource":48},9662,"fiftyone","voxel51\u002Ffiftyone","voxel51","Refine high-quality datasets and visual AI models","https:\u002F\u002Ffiftyone.ai",null,"Python",10771,768,64,512,0,3,13,74,11,43.66,"Apache License 2.0",false,"develop",[26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"active-learning","artificial-intelligence","computer-vision","data-centric-ai","data-cleaning","data-curation","data-quality","data-science","deep-learning","developer-tools","image-classification","machine-learning","object-detection","python","unstructured-data","vector-search","visualization","2026-06-12 02:02:10","\u003Cdiv align=\"center\">\n\u003Cp align=\"center\">\n\n\u003C!-- prettier-ignore -->\n\u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"55px\">  \n\u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288518-24bb7680-6216-11eb-8f10-60052c519586.png\" height=\"50px\">\n\n**The open-source tool for building high-quality datasets and computer vision\nmodels**\n\n---\n\n\u003C!-- prettier-ignore -->\n\u003Ca href=\"https:\u002F\u002Fvoxel51.com\u002Ffiftyone\">Website\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fdocs.voxel51.com\">Docs\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fcolab.research.google.com\u002Fgithub\u002Fvoxel51\u002Ffiftyone-examples\u002Fblob\u002Fmaster\u002Fexamples\u002Fquickstart.ipynb\">Try it Now\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fdocs.voxel51.com\u002Fgetting_started_guides\u002Findex.html\">Getting Started Guides\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fdocs.voxel51.com\u002Ftutorials\u002Findex.html\">Tutorials\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fvoxel51.com\u002Fblog\u002F\">Blog\u003C\u002Fa> •\n\u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002Ffiftyone-community\">Community\u003C\u002Fa>\n\n[![PyPI python](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fpyversions\u002Ffiftyone)](https:\u002F\u002Fpypi.org\u002Fproject\u002Ffiftyone)\n[![PyPI version](https:\u002F\u002Fbadge.fury.io\u002Fpy\u002Ffiftyone.svg)](https:\u002F\u002Fpypi.org\u002Fproject\u002Ffiftyone)\n[![Downloads](https:\u002F\u002Fstatic.pepy.tech\u002Fbadge\u002Ffiftyone)](https:\u002F\u002Fpepy.tech\u002Fproject\u002Ffiftyone)\n[![Docker Pulls](https:\u002F\u002Fbadgen.net\u002Fdocker\u002Fpulls\u002Fvoxel51\u002Ffiftyone?icon=docker&label=pulls)](https:\u002F\u002Fhub.docker.com\u002Fr\u002Fvoxel51\u002Ffiftyone\u002F)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-Apache%202.0-blue.svg)](LICENSE)\n\n[![Discord](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-7289DA?logo=discord&logoColor=white)](https:\u002F\u002Fdiscord.gg\u002Ffiftyone-community)\n[![Hugging Face](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FHugging_Face-purple?style=flat&logo=huggingface)](https:\u002F\u002Fhuggingface.co\u002FVoxel51)\n[![Voxel51 Blog](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVoxel51_Blog-ff6d04?style=flat)](https:\u002F\u002Fvoxel51.com\u002Fblog)\n[![Newsletter](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNewsletter-BE5B25?logo=mail.ru&logoColor=white)](https:\u002F\u002Fshare.hsforms.com\u002F1zpJ60ggaQtOoVeBqIZdaaA2ykyk)\n[![LinkedIn](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIn-white?style=flat&label=Linked&labelColor=blue)](https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fvoxel51)\n[![Twitter](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FTwitter-000000?logo=x&logoColor=white)](https:\u002F\u002Fx.com\u002Fvoxel51)\n[![Medium](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMedium-12100E?logo=medium&logoColor=white)](https:\u002F\u002Fmedium.com\u002Fvoxel51)\n\n\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n# 👋 hey there!\n\nWe created **[FiftyOne](https:\u002F\u002Ffiftyone.ai)** to supercharge your visual AI\ndevelopment by enabling you to visualize and label your data, evaluate your\nmodels, and maximize data and model quality more efficiently than ever before\n🤝\n\nIf you're looking to scale to production-grade, collaborative, cloud-native\nenterprise workloads, check out\n**[FiftyOne Enterprise](http:\u002F\u002Fvoxel51.com\u002Fenterprise)** 🚀\n\n\u003Cdiv id='installation'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   installation   💻\n\nAs simple as:\n\n```shell\npip install fiftyone\n```\n\n\u003Cdetails>\n\u003Csummary>More details\u003C\u002Fsummary>\n\n### Installation options\n\nFiftyOne supports Python 3.9 - 3.12.\n\nFor most users, we recommend installing the latest release version of FiftyOne\nvia `pip` as shown above.\n\nIf you want to contribute to FiftyOne or install the latest development\nversion, then you can also perform a [source install](#source-install).\n\nSee the [prerequisites section](#prerequisites) for system-specific setup\ninformation.\n\nWe strongly recommend that you install FiftyOne in a\n[virtual environment](https:\u002F\u002Fdocs.voxel51.com\u002Finstallation\u002Fvirtualenv.html) to\nmaintain a clean workspace.\n\nConsult the\n[installation guide](https:\u002F\u002Fdocs.voxel51.com\u002Finstallation\u002Findex.html) for\ntroubleshooting and other information about getting up-and-running with\nFiftyOne.\n\n\u003C\u002Fdetails>\n\n\u003Cdiv id='source-install'\u002F>\n\n\u003Cdetails>\n\u003Csummary>Install from source\u003C\u002Fsummary>\n\n### Source installations\n\nFollow the instructions below to install FiftyOne from source and build the\nApp.\n\nYou'll need the following tools installed:\n\n-   [Python](https:\u002F\u002Fwww.python.org) (3.9 - 3.12)\n-   [Node.js](https:\u002F\u002Fnodejs.org) - on Linux, we recommend using\n    [nvm](https:\u002F\u002Fgithub.com\u002Fnvm-sh\u002Fnvm) to install an up-to-date version.\n-   [Yarn](https:\u002F\u002Fyarnpkg.com) - once Node.js is installed, you can\n    [enable Yarn](https:\u002F\u002Fyarnpkg.com\u002Fgetting-started\u002Finstall) via\n    `corepack enable`\n\nWe strongly recommend that you install FiftyOne in a\n[virtual environment](https:\u002F\u002Fdocs.voxel51.com\u002Finstallation\u002Fvirtualenv.html) to\nmaintain a clean workspace.\n\nIf you are working in Google Colab,\n[skip to here](#source-installs-in-google-colab).\n\nFirst, clone the repository:\n\n```shell\ngit clone https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone\ncd fiftyone\n```\n\nThen run the install script:\n\n```shell\n# Mac or Linux\nbash install.sh\n\n# Windows\n.\\install.bat\n```\n\nIf you run into issues importing FiftyOne, you may need to add the path to the\ncloned repository to your `PYTHONPATH`:\n\n```shell\nexport PYTHONPATH=$PYTHONPATH:\u002Fpath\u002Fto\u002Ffiftyone\n```\n\nNote that the install script adds to your `nvm` settings in your `~\u002F.bashrc` or\n`~\u002F.bash_profile`, which is needed for installing and building the App.\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\n\n# Mac or Linux\nbash install.sh\n\n# Windows\n.\\install.bat\n```\n\n### Rebuilding the App\n\nWhen you pull in new changes to the App, you will need to rebuild it, which you\ncan do either by rerunning the install script or just running `yarn build` in\nthe `.\u002Fapp` directory.\n\n### Developer installation\n\nIf you would like to\n[contribute to FiftyOne](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone\u002Fblob\u002Fdevelop\u002FCONTRIBUTING.md),\nyou should perform a developer installation using the `-d` flag of the install\nscript:\n\n```shell\n# Mac or Linux\nbash install.sh -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:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fconfig.html#configuring-a-mongodb-connection).\n\n### Source installs in Google Colab\n\nYou can install from source in\n[Google Colab](https:\u002F\u002Fcolab.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:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone.git\ncd fiftyone\n\n# Mac or Linux\nbash install.sh\n\n# Windows\n.\\install.bat\n```\n\n### Generating documentation\n\nSee the\n[docs guide](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone\u002Fblob\u002Fdevelop\u002Fdocs\u002FREADME.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\u003C\u002Fdetails>\n\n\u003Cdiv id='prerequisites'\u002F>\n\n\u003Cdetails>\n\u003Csummary>Prerequisites for beginners\u003C\u002Fsummary>\n\n### System-specific setup\n\nFollow the instructions for your operating system or environment to perform\nbasic system setup before [installing FiftyOne](#installation).\n\nIf you're an experienced developer, you've likely already done this.\n\n\u003Cdetails>\n\u003Csummary>Linux\u003C\u002Fsummary>\n\n\u003Cdiv id='prerequisites-linux'\u002F>\n\n#### 1. Install Python and other dependencies\n\nThese steps work on a clean install of Ubuntu Desktop 24.04, and should also\nwork on Ubuntu 24.04 and 22.04, and on Ubuntu Server:\n\n```shell\nsudo apt-get update\nsudo apt-get upgrade\nsudo apt-get install python3-venv python3-dev build-essential git-all libgl1-mesa-dev\n```\n\n-   On Linux, you will need at least the `openssl` and `libcurl` packages\n-   On Debian-based distributions, you will need to install `libcurl4` or\n    `libcurl3` instead of `libcurl`, depending on the age of your distribution\n\n```shell\n# Ubuntu\nsudo apt install libcurl4 openssl\n\n# Fedora\nsudo dnf install libcurl openssl\n```\n\n#### 2. Create and activate a virtual environment\n\n```shell\npython3 -m venv fiftyone_env\nsource fiftyone_env\u002Fbin\u002Factivate\n```\n\n#### 3. Install FFmpeg (optional)\n\nIf you plan to work with video datasets, you'll need to install\n[FFmpeg](https:\u002F\u002Fffmpeg.org):\n\n```shell\nsudo apt-get install ffmpeg\n```\n\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n\u003Csummary>MacOS\u003C\u002Fsummary>\n\n\u003Cdiv id='prerequisites-macos'\u002F>\n\n#### 1. Install Xcode Command Line Tools\n\n```shell\nxcode-select --install\n```\n\n#### 2. Install Homebrew\n\n```shell\n\u002Fbin\u002Fbash -c \"$(curl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002FHomebrew\u002Finstall\u002FHEAD\u002Finstall.sh)\"\n```\n\nAfter running the above command, follow the instructions in your terminal to\ncomplete the Homebrew installation.\n\n#### 3. Install Python\n\n```shell\nbrew install python@3.9\nbrew install protobuf\n```\n\n#### 4. Create and activate a virtual environment\n\n```shell\npython3 -m venv fiftyone_env\nsource fiftyone_env\u002Fbin\u002Factivate\n```\n\n#### 5. Install FFmpeg (optional)\n\nIf you plan to work with video datasets, you'll need to install\n[FFmpeg](https:\u002F\u002Fffmpeg.org):\n\n```shell\nbrew install ffmpeg\n```\n\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n\u003Csummary>Windows\u003C\u002Fsummary>\n\n\u003Cdiv id='prerequisites-windows'\u002F>\n\n#### 1. Install Python\n\n⚠️ The version of Python that is available in the Microsoft Store is **not\nrecommended** ⚠️\n\nDownload a Python 3.9 - 3.12 installer from\n[python.org](https:\u002F\u002Fwww.python.org\u002Fdownloads\u002F). Make sure to pick a 64-bit\nversion. For example, this\n[Python 3.10.11 installer](https:\u002F\u002Fwww.python.org\u002Fftp\u002Fpython\u002F3.10.11\u002Fpython-3.10.11-amd64.exe).\n\nDouble-click on the installer to run it, and follow the steps in the installer.\n\n-   Check the box to add Python to your `PATH`\n-   At the end of the installer, there is an option to disable the `PATH`\n    length limit. It is recommended to click this\n\n#### 2. Install Microsoft Visual C++\n\nDownload\n[Microsoft Visual C++ Redistributable](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fcpp\u002Fwindows\u002Flatest-supported-vc-redist).\nDouble-click on the installer to run it, and follow the steps in the installer.\n\n#### 3. Install Git\n\nDownload Git from [this link](https:\u002F\u002Fgit-scm.com\u002Fdownload\u002Fwin). Double-click\non the installer to run it, and follow the steps in the installer.\n\n#### 4. Create and activate a virtual environment\n\n-   Press `Win + R`. type `cmd`, and press `Enter`. Alternatively, search\n    **Command Prompt** in the Start Menu.\n-   Navigate to your project. `cd C:\\path\\to\\your\\project`\n-   Create the environment `python -m venv fiftyone_env`\n-   Activate the environment typing this in the command line window\n    `fiftyone_env\\Scripts\\activate`\n-   After activation, your command prompt should change and show the name of\n    the virtual environment `(fiftyone_env) C:\\path\\to\\your\\project`\n\n#### 5. Install FFmpeg (optional)\n\nIf you plan to work with video datasets, you'll need to install\n[FFmpeg](https:\u002F\u002Fffmpeg.org).\n\nDownload an FFmpeg binary from [here](https:\u002F\u002Fffmpeg.org\u002Fdownload.html). Add\nFFmpeg's path (e.g., `C:\\ffmpeg\\bin`) to your `PATH` environmental variable.\n\n\u003C\u002Fdetails>\n\n\u003Cdetails>\n\u003Csummary>Docker\u003C\u002Fsummary>\n\n\u003Cdiv id='prerequisites-docker'\u002F>\n\u003Cbr>\n\nRefer to\n[these instructions](https:\u002F\u002Fdocs.voxel51.com\u002Fenvironments\u002Findex.html#docker)\nto see how to build and run Docker images containing release or source builds\nof FiftyOne.\n\n\u003C\u002Fdetails>\n\n\u003C\u002Fdetails>\n\n\u003Cdiv id='quickstart'>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   quickstart   🚀\n\nDive right into FiftyOne by opening a Python shell and running the snippet\nbelow, which downloads a\n[small dataset](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fdataset_zoo\u002Fdatasets.html#quickstart)\nand launches the [FiftyOne App](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fapp.html)\nso you can 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:\u002F\u002Fcolab.research.google.com\u002Fgithub\u002Fvoxel51\u002Ffiftyone-examples\u002Fblob\u002Fmaster\u002Fexamples\u002Fquickstart.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:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fapp.html#creating-a-session)\nfor more information.\n\n\u003Cdiv id='key-features'>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   key features   🔑\n\n-   **[Native Annotation:](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fannotation.html)**\n    Create and edit 2D and 3D labels directly in the App or integrate with your\n    favorite annotation tools — then curate, QA, and iterate, all in one\n    platform.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fb06bcdac-d64f-4465-8668-12007dc0eeaa\n\n-   **[Visualize Complex Datasets:](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fapp.html)**\n    Easily explore images, videos, and associated labels in a powerful visual\n    interface.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F9dc2db88-967d-43fa-bda0-85e4d5ab6a7a\n\n-   **[Explore Embeddings:](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fapp.html#embeddings-panel)**\n    Select points of interest and view the corresponding samples\u002Flabels.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F246faeb7-dcab-4e01-9357-e50f6b106da7\n\n-   **[Analyze and Improve Models:](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Fevaluation.html)**\n    Evaluate model performance, identify failure modes, and fine-tune your\n    models.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F8c32d6c4-51e7-4fea-9a3c-2ffd9690f5d6\n\n-   **[Advanced Data Curation:](https:\u002F\u002Fdocs.voxel51.com\u002Fbrain.html)** Quickly\n    find and fix data issues, annotation errors, and edge cases.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F24fa1960-c2dd-46ae-ae5f-d58b3b84cfe4\n\n-   **[Rich Integrations:](https:\u002F\u002Fdocs.voxel51.com\u002Fintegrations\u002Findex.html)**\n    Works with popular deep learning libraries like PyTorch, Hugging Face,\n    Ultralytics, and more.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fde5f25e1-a967-4362-9e04-616449e745e5\n\n-   **[Open and Extensible:](https:\u002F\u002Fdocs.voxel51.com\u002Fplugins\u002Findex.html)**\n    Customize and extend FiftyOne to fit your specific needs.\n\nhttps:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fc7ed496d-0cf7-45d6-9853-e349f1abd6f8\n\n\u003Cdiv id='getting-started'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   documentation   🪪\n\nCheck out these resources to get up and running with FiftyOne:\n\n| [Getting Started Guides](https:\u002F\u002Fdocs.voxel51.com\u002Fgetting_started_guides\u002Findex.html) | [Tutorials](https:\u002F\u002Fdocs.voxel51.com\u002Ftutorials\u002Findex.html) | [Recipes](https:\u002F\u002Fdocs.voxel51.com\u002Frecipes\u002Findex.html) | [User Guide](https:\u002F\u002Fdocs.voxel51.com\u002Fuser_guide\u002Findex.html) | [Examples](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone-examples) | [API Reference](https:\u002F\u002Fdocs.voxel51.com\u002Fapi\u002Ffiftyone.html) | [CLI Reference](https:\u002F\u002Fdocs.voxel51.com\u002Fcli\u002Findex.html) |\n| ------------------------------------------------------------------------------------ | ---------------------------------------------------------- | ------------------------------------------------------ | ------------------------------------------------------------ | -------------------------------------------------------- | ----------------------------------------------------------- | -------------------------------------------------------- |\n\nFull documentation is available at [fiftyone.ai](https:\u002F\u002Ffiftyone.ai).\n\n\u003C\u002Fdiv>\n\n\u003Cdiv id='additional-resources'>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   additional resources   🚁\n\n| [FiftyOne Enterprise](https:\u002F\u002Fvoxel51.com\u002Fenterprise) | [Building Plugins](https:\u002F\u002Fdocs.voxel51.com\u002Fplugins\u002Findex.html) | [Vector Search](https:\u002F\u002Fvoxel51.com\u002Fblog\u002Fthe-computer-vision-interface-for-vector-search) | [Dataset Zoo](https:\u002F\u002Fdocs.voxel51.com\u002Fdataset_zoo\u002Findex.html) | [Model Zoo](https:\u002F\u002Fdocs.voxel51.com\u002Fmodel_zoo\u002Findex.html) | [FiftyOne Brain](https:\u002F\u002Fdocs.voxel51.com\u002Fbrain.html) | [VoxelGPT](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Fvoxelgpt) |\n| ----------------------------------------------------- | --------------------------------------------------------------- | ----------------------------------------------------------------------------------------- | -------------------------------------------------------------- | ---------------------------------------------------------- | ----------------------------------------------------- | ----------------------------------------------- |\n\n\u003C\u002Fdiv>\n\n\u003Cdiv id='fiftyone-enterprise'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   FiftyOne Enterprise   🏎️\n\nWant to securely collaborate on billions of samples in the cloud and connect to\nyour compute resources to automate your workflows? Check out\n[FiftyOne Enterprise](https:\u002F\u002Fvoxel51.com\u002Fenterprise).\n\n\u003Cdiv id='faq'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   faq & troubleshooting   ⛓️‍💥\n\nRefer to our\n[common issues](https:\u002F\u002Fdocs.voxel51.com\u002Finstallation\u002Ftroubleshooting.html)\npage to troubleshoot installation issues. If you're still stuck, check our\n[frequently asked questions](https:\u002F\u002Fdocs.voxel51.com\u002Ffaq\u002Findex.html) page for\nmore answers.\n\nIf you encounter an issue that the above resources don't help you resolve, feel\nfree to [open an issue on GitHub](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone\u002Fissues)\nor contact us on [Discord](https:\u002F\u002Fdiscord.gg\u002Ffiftyone-community).\n\n\u003C\u002Fdiv>\n\n\u003Cdiv id='community'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   join our community   🤝\n\nConnect with us through your preferred channels:\n\n[![Discord](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-7289DA?logo=discord&logoColor=white)](https:\u002F\u002Fdiscord.gg\u002Ffiftyone-community)\n[![Hugging Face](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FHugging_Face-purple?style=flat&logo=huggingface)](https:\u002F\u002Fhuggingface.co\u002FVoxel51)\n[![Newsletter](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FNewsletter-BE5B25?logo=mail.ru&logoColor=white)](https:\u002F\u002Fshare.hsforms.com\u002F1zpJ60ggaQtOoVeBqIZdaaA2ykyk)\n[![LinkedIn](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIn-white?style=flat&label=Linked&labelColor=blue)](https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fvoxel51)\n[![Medium](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FMedium-12100E?logo=medium&logoColor=white)](https:\u002F\u002Fmedium.com\u002Fvoxel51)\n\n🎊 **Share how FiftyOne makes your visual AI projects a reality on social media\nand tag us with @Voxel51 and #FiftyOne** 🎊\n\n\u003C\u002Fdiv>\n\n\u003Cdiv id='contributors'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   contributors   🧡\n\nFiftyOne and [FiftyOne Brain](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone-brain) are\nopen source and community contributions are welcome! Check out the\n[contribution guide](https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone\u002Fblob\u002Fdevelop\u002FCONTRIBUTING.md)\nto learn how to get involved.\n\nSpecial thanks to these amazing people for contributing to FiftyOne!\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg src=\"https:\u002F\u002Fcontrib.rocks\u002Fimage?repo=voxel51\u002Ffiftyone\" \u002F>\n\u003C\u002Fa>\n\n\u003Cdiv id='citation'\u002F>\n\n## \u003Cimg src=\"https:\u002F\u002Fuser-images.githubusercontent.com\u002F25985824\u002F106288517-2422e000-6216-11eb-871d-26ad2e7b1e59.png\" height=\"20px\">   citation   📖\n\nIf you use FiftyOne in your research, feel free to cite the project (but only\nif you love it 😊):\n\n```bibtex\n@article{moore2020fiftyone,\n  title={FiftyOne},\n  author={Moore, B. E. and Corso, J. J.},\n  journal={GitHub. Note: https:\u002F\u002Fgithub.com\u002Fvoxel51\u002Ffiftyone},\n  year={2020}\n}\n```\n","FiftyOne 是一个用于构建高质量数据集和计算机视觉模型的开源工具。它支持数据可视化、标注、模型评估等功能，帮助用户更高效地提升数据和模型质量。基于 Python 开发，FiftyOne 提供了丰富的功能，如主动学习、图像分类、目标检测等，并且能够处理非结构化数据。该工具非常适合需要进行大规模数据清洗、管理和模型训练的场景，尤其适用于人工智能开发者和数据科学家在开发和优化视觉AI项目时使用。",2,"2026-06-11 03:24:03","top_topic"]