ImageRepositorySUPFrameLevelEmbeddings

AI Overview😉

  • The potential purpose of this module is to analyze and understand the content of videos by extracting frame-level embeddings, which are compact numerical representations of each frame in the video. This allows Google to better comprehend the visual aspects of the video and its relevance to a user's search query.
  • This module could impact search results by allowing Google to more accurately rank videos based on their visual content, rather than just relying on metadata such as titles and descriptions. This could lead to more relevant video results for users, especially for searches where the visual content is important (e.g. "how to" tutorials or product reviews).
  • To be more favorable for this function, a website could focus on optimizing their video content by ensuring that the visual aspects of the video are relevant to the search query, using descriptive and accurate titles and descriptions, and providing high-quality thumbnails that accurately represent the video's content. Additionally, using schema markup to provide additional context about the video, such as the video's duration, upload date, and description, could also be beneficial.

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

Attributes

  • embeddings (type: list(GoogleApi.ContentWarehouse.V1.Model.ImageRepositorySUPFrameLevelEmbedding.t), default: nil) - All the frame-level embeddings of the video.

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.ImageRepositorySUPFrameLevelEmbeddings{
    embeddings:
      [
        GoogleApi.ContentWarehouse.V1.Model.ImageRepositorySUPFrameLevelEmbedding.t()
      ]
      | nil
  }

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.