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| title: LabelStudio | |
| emoji: π§ | |
| colorFrom: grey | |
| colorTo: yellow | |
| sdk: docker | |
| pinned: true | |
| license: apache-2.0 | |
| app_port: 8080 | |
| <img src="https://user-images.githubusercontent.com/12534576/192582340-4c9e4401-1fe6-4dbb-95bb-fdbba5493f61.png"/> | |
| [Website](https://hubs.ly/Q01CNgsd0) β’ [Docs](https://hubs.ly/Q01CN9Yq0) β’ [12K+ GitHub βοΈ!](https://hubs.ly/Q01CNbPQ0) β’ [Slack Community](https://hubs.ly/Q01CNb9H0) | |
| ## What is Label Studio? | |
| Label Studio is an open source data labeling platform. It lets you label audio, | |
| text, images, videos, and time series data with a simple, straightforward, and | |
| highly-configurable user interface. Label Studio can prepare new data or | |
| improve existing training data to get more accurate ML models. | |
| ## Label Studio in Hugging Face Spaces | |
| The Label Studio community is thrilled to offer Label Studio as a Hugging Face | |
| Spaces application. You can try the data-annotation interface, connect popular | |
| machine learning models, and share the application with collaborators. You can | |
| start immediately by creating an account or replicate the space and work in | |
| your own environment. | |
| ## Creating a Use Account and Logging In | |
| Begin by creating a new account in the Label Studio space, then log in with your | |
| credentials. | |
| **By default, these spaces permit anyone to create a new login | |
| account, allowing them to view and modify project configuration, data sets, and | |
| annotations. Without any modifications, treat this space like a demo environment.** | |
| ## Creating a Labeling Project | |
| After logging in, Label Studio will present you with a project view. Here you | |
| can create a new project with prompts to upload data and set up a custom | |
| configuration interface. | |
| **Note that in the default configuration, storage is local and temporary. Any | |
| projects, annotations, and configurations will be lost if the space is restarted.** | |
| ## Next Steps and Additional Resources | |
| To help with getting started, the Label Studio community curated a list of | |
| resources including tutorials and documentation. | |
| - π [Zero to One with Label Studio Tutorial](https://hubs.ly/Q01CN93R0) | |
| - π [Try Label Studio Enterprise](https://hubs.ly/Q01CMLll0) | |
| - π€ [Tutorial: Using Label Studio with Hugging Face Datasets Hub](https://danielvanstrien.xyz/huggingface/huggingface-datasets/annotation/full%20stack%20deep%20learning%20notes/2022/09/07/label-studio-annotations-hub.html) | |
| - π‘ [Label Studio Docs](https://hubs.ly/Q01CN9Yq0) | |
|  | |
| Have a custom dataset? You can customize Label Studio to fit your needs. Read | |
| an [introductory blog post](https://towardsdatascience.com/introducing-label-studio-a-swiss-army-knife-of-data-labeling-140c1be92881) | |
| to learn more. | |
| ### Configuring Label Studio Spaces for Secure Use | |
| By default this space allows for the unrestricted creation of new accounts | |
| will full access to all projects and data. This is great for trying out | |
| Label Studio and collaborating on projects, but you may want to restrict | |
| access to your space to only authorized users. Add the following environment | |
| variable to your spaces Dockerfile to disable public account creation for | |
| this space. | |
| ENV LABEL_STUDIO_DISABLE_SIGNUP_WITHOUT_LINK=true | |
| Set secrets in your space to create an inital user, and log in with your | |
| provided username and password. Do not set these in your Dockerfile, as they | |
| globally visible on a public space. | |
| LABEL_STUDIO_USERNAME | |
| LABEL_STUDIO_PASSWORD | |
| You will need to provide new users with an invitation link to join the space, | |
| which can be found in the Organizations interface of Label Studio | |
| By default this space stores all project configuration and data annotations | |
| in local storage with Sqlite. If the space is reset, all configuration and | |
| annotation data in the space will be lost. You can enable configuration | |
| persistence by connecting an external Postgres database to your space, | |
| guaranteeing that all project and annotation settings are preserved. | |
| Set the following secret variables to match your own hosted instance of | |
| Postgres. We strongly recommend setting these as secrets to prevent leaking | |
| information about your database service to the public in your spaces | |
| definition. | |
| ENV DJANGO_DB=default | |
| ENV POSTGRE_NAME=<postgres_name> | |
| ENV POSTGRE_PORT=<db_port> | |
| ENV POSTGRE_USER=<postgres_user> | |
| ENV POSTGRE_PASSWORD=<password> | |
| ENV POSTGRE_PORT=<db_port> | |
| ENV POSTGRE_HOST=<db_host> | |
| Add the following environment variable to remove the warning about ephemeral | |
| storage. | |
| ENV STORAGE_PERSISTENCE=1 | |
| Note that you will need to connect cloud storage to host data items that you | |
| want to annotate, as local storage will not be preserved across a space reset. | |
| ## Questions? Concerns? Want to get involved? | |
| Email the community team at [[email protected]](mailto:[email protected]) | |
| </body> | |