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Dataset Creation
LabelStudio

LabelStudio

Label data efficiently with ease

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What is LabelStudio ?

LabelStudio is an open-source tool designed for efficient data labeling and dataset creation. It simplifies the process of annotating data for machine learning models, supporting various data types such as text, images, and audio. With its intuitive interface and customizable workflows, LabelStudio is a popular choice for data scientists and annotators.

Features

• Support for multiple data types: Label text, images, audio, and more in a single platform.
• Customizable templates: Define your own labeling templates to fit specific project requirements.
• Collaboration features: Work with teams and manage annotations efficiently.
• Integration capabilities: Easily integrate with machine learning pipelines and workflows.
• Open-source flexibility: Customize and extend the tool to meet your needs.

How to use LabelStudio ?

  1. Install LabelStudio: Download and install the tool from its official repository or use a Docker container.
  2. Set up a project: Create a new project and configure your labeling task with custom templates.
  3. Import data: Upload your dataset to LabelStudio for annotation.
  4. Label data: Use the interface to annotate your data with labels, tags, or other markers.
  5. Export annotations: Save and export your annotated data in formats compatible with machine learning frameworks.
  6. Manage workflows: Track progress, collaborate with team members, and refine your annotations as needed.

Frequently Asked Questions

What is LabelStudio primarily used for?
LabelStudio is primarily used for annotating and labeling data to prepare it for machine learning model training.

Can LabelStudio handle different types of data?
Yes, LabelStudio supports labeling for text, images, audio, and other data types, making it versatile for various projects.

Where can I download LabelStudio?
LabelStudio is open-source and can be downloaded from its official GitHub repository or used via Docker.

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