LabelGPT - ai tOOler
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LabelGPT
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Data labeling (3)

LabelGPT

Label a million images in just a few minutes.

Tool Information

LabelGPT is a smart tool that automatically generates labels for images, making the annotation process much easier and faster for users.

LabelGPT is powered by an advanced generative AI model, which enables it to quickly produce labels on raw images. This is especially helpful for teams working in machine learning, as it streamlines the often tedious task of image annotation.

Users can easily bring their data into LabelGPT from a variety of sources. Whether you're pulling images from your local drive or using cloud services like AWS, GCP, or Azure, this tool can handle it all, and it even has options for integration through APIs.

One of the standout features of LabelGPT is its zero-shot label generation engine. This means that you can provide just the class or object names as a text prompt, and the tool will detect and segment the labels for you. This automation not only saves time but also helps ensure consistency across your labeled data.

LabelGPT also includes a quick review process, allowing users to filter labels based on confidence scores. This lets you verify the accuracy of the labels visually and seamlessly incorporate them into your machine learning pipeline.

The annotations produced by LabelGPT can significantly enhance your vision model training, cutting down on annotation costs while speeding up the overall labeling process. It’s designed to help machine learning teams work more efficiently, allowing them to focus on what really matters: developing better models.

Pros and Cons

Pros

  • Provides solutions based on use cases
  • Uses multiple foundation models
  • API for importing data
  • Automates labeling of raw images
  • local)
  • Validation by filtering high confidence scores
  • GCP
  • Automated image labeling
  • Option to book a demo
  • Quick review process
  • Availability of pre-labeled datasets
  • Flexible pricing plans
  • Zero-shot learning
  • Text prompts for labeling
  • Quality check with high confidence scores
  • Data organizing functions
  • Labeling powered by foundation models
  • Access data on multiple platforms (cloud
  • Supports video labeling
  • Accelerates the labeling process
  • Prompts for class/object labeling
  • Can segment images
  • Enables data uploads
  • Azure)
  • Allows choosing datasets
  • Quick label creation
  • Generates high-quality labels
  • Supports text labeling
  • Features for capturing and collecting
  • Creates a lot of labeled data
  • Direct integration with ML workflows
  • Dedicated knowledge resource
  • Detects classes/objects using prompts
  • Visual validation of labels
  • Expert discussions and articles
  • Saves time in labeling
  • Imports from local and cloud (AWS
  • Smart feedback technology
  • Exports to ML training systems
  • Uses many open-source datasets
  • Lowers labeling costs
  • Visual check of results
  • Easy labeling of classes/objects
  • No manual labeling needed

Cons

  • Few types of labels
  • No offline use
  • No option for manual labeling
  • No clear user access control
  • No free trial stated
  • No function for data curation
  • Unclear history of changes
  • Can't change confidence score
  • No support for multiple languages

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