PhotosVisionObjectrecQuantizedFeatureVector

AI Overview😉

  • The potential purpose of this module is to compress and store feature vectors related to image recognition and object detection in a compact format, allowing for efficient storage and processing of visual data.
  • This module could impact search results by enabling Google to more accurately identify and rank images based on their visual content, potentially leading to more relevant and accurate image search results. It may also improve the performance of image-based search features, such as Google Lens.
  • A website may optimize for this function by ensuring that their images are properly tagged and annotated with relevant metadata, such as alt text and descriptive captions, and by using high-quality, visually distinct images that can be effectively analyzed by Google's image recognition algorithms. Additionally, websites may consider using image compression techniques to reduce the file size of their images, making them easier to process and analyze.

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

Quantized/compressed feature vector (8 bit per value). Can be decoded by multiplying data_factor to each data byte.

Attributes

  • data (type: String.t, default: nil) -
  • dataFactor (type: number(), default: nil) -

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.PhotosVisionObjectrecQuantizedFeatureVector{
    data: String.t() | nil,
    dataFactor: number() | nil
  }

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.