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Supported annotation tasks

Overview​

H2O Label Genie supports various annotation tasks in computer vision (CV) (image), natural language processing (NLP) (text), and audio.

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To learn how to create an annotation task, see Create an annotation task.

Text annotation tasks​

Text classification​

  • Description: A text classification annotation task specifies one or more categorical target labels for each input text.
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  • H2O Label Genie supports multi-label text classification annotation tasks.
  • To accelerate the labeling process for text classification annotation tasks, H2O Label Genie offers the ability to utilize a zero-shot learning model. To learn more, see Zero-shot learning models.

Text regression​

  • Description: A text regression annotation task specifies one continuous target label for each input text.

Text-entity recognition​

  • Description: A text-entity recognition annotation task specifies one or more defined entities for each unstructured input text.

Text summarization​

  • Description: A text summarization annotation task specifies a summary for each input text.
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To accelerate the labeling process, H2O Label Genie offers the ability to utilize pretrained text summarization models. To learn more, see Zero-shot learning models.

Text-generative AI​

  • Description: A text-generative AI annotation task specifies a particular text response for the text column(s).
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  • Zero-shot learning models: To accelerate the labeling process for a text-generative AI annotation tasks, H2O Label Genie offers the ability to utilize several zero-shot learning models. To learn more, see Zero-shot learning models: Text-generative AI
    • The available zero-shot learning models for a text-generative AI annotation task are from the large language model (LLM) h2oGPT family
  • Bring your own model: For text-generative AI annotation tasks, H2O Label Genie enables you to bring your own model
    • To learn how to specify the path to your own model in H2O Label Genie, see Custom model URL

Image annotation tasks​

Image classification​

  • Description: An image classification annotation task specifies one or more categorical target labels for each input image.
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  • H2O Label Genie supports multi-label image classification annotation tasks.
  • To accelerate the labeling process for image classification annotation tasks, H2O Label Genie offers the ability to utilize a zero-shot learning model. To learn more, see Zero-shot learning models.

Image regression​

  • Description: An image regression annotation task specifies one continuous target label for each input image.

Object detection​

  • Description: An object detection annotation task specifies one or more object classes (labels) for each input image.
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To accelerate the labeling process for object detection annotation tasks, H2O Label Genie offers the ability to utilize a zero-shot learning model. To learn more, see Zero-shot learning models.

Image instance segmentation​

In H2O Label Genie, for an image instance segmentation annotation task, you need to assign one or more object classes (labels) to each input image.

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To accelerate the labeling process for image instance segmentation annotation tasks, H2O Label Genie offers the ability to utilize a zero-shot learning model. To learn more, see Zero-shot learning models.

Audio annotation tasks​

Audio classification​

  • Description: An audio classification annotation task specifies one or more categorical target labels for each input audio.
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H2O Label Genie supports multi-label audio classification annotation tasks.

Audio regression​

  • Description: An audio regression annotation task specifies one continuous target label for each input audio.
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