ImageRepositoryNimaOutput

AI Overview😉

  • The potential purpose of this module is to analyze and score images based on their content, quality, and relevance, likely using the NIMA (Neural Image Assessment) algorithm. This module's goal is to provide a quantitative measure of an image's quality and relevance to a search query.
  • This module could impact search results by influencing the ranking of web pages that contain images. Web pages with high-scoring images (i.e., relevant, high-quality, and well-optimized images) may be ranked higher in search engine results pages (SERPs), while those with low-scoring images may be demoted. This could lead to a better user experience, as users are more likely to engage with high-quality and relevant visual content.
  • To be more favorable to this function, a website could:
    • Optimize images by compressing them, using descriptive file names, and adding relevant alt tags.
    • Use high-quality, relevant, and contextual images that align with the content of the web page.
    • Ensure images are properly sized and formatted for various devices and screen sizes.
    • Use schema markup to provide additional context about the images, such as captions, descriptions, and licenses.

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GoogleApi.ContentWarehouse.V1.Model.ImageRepositoryNimaOutput (google_api_content_warehouse v0.4.0)

Attributes

  • score (type: number(), default: nil) - NIMA score.

Summary

Types

t()

Functions

decode(value, options)

Unwrap a decoded JSON object into its complex fields.

Types

Link to this type

t()

@type t() :: %GoogleApi.ContentWarehouse.V1.Model.ImageRepositoryNimaOutput{
  score: number() | nil
}

Functions

Link to this function

decode(value, options)

@spec decode(struct(), keyword()) :: struct()

Unwrap a decoded JSON object into its complex fields.