PhotosVisionObjectrecLocalDescriptor

AI Overview😉

  • The potential purpose of this module is to analyze and process image features, specifically interest points, and their corresponding descriptors. This includes information about the image patch, such as scale, orientation, and affine matrix, as well as the local descriptor vector. This module is likely used in image recognition, object detection, and other computer vision tasks.
  • This module could impact search results by influencing the ranking of images in image search queries. For example, if an image has a high-quality local descriptor vector, it may be considered more relevant or informative, and thus ranked higher in search results. Conversely, images with low-quality or missing local descriptors may be ranked lower.
  • To be more favorable for this function, a website could ensure that its images are of high quality, with clear and distinct features. Additionally, optimizing image metadata, such as alt tags and descriptions, could provide more context for the image features and improve the local descriptor vector. Furthermore, using image compression techniques that preserve feature information, such as JPEG-LS, could also improve the quality of the local descriptor vector.

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

LocalDescriptor holds interest point data and an optional local descriptor vector.

Attributes

  • affineMatrix (type: GoogleApi.ContentWarehouse.V1.Model.PhotosVisionObjectrecMatrix2D.t, default: nil) - Optional affine matrix. Supersedes scale and orientation if present. r' = affine_matrix.r + (x,y) defines an affine transform from the normalized image patch (in which the interest point is centered at the origin with scale 1) to the image. If the affine matrix is set, the following approximations are recommended: scale = sqrt(0.5 (xxxx + xyxy + yxyx + yyyy)); orientation = atan2(yx - xy, xx + yy); If not present, the affine matrix can be computed from scale and orientation as: xx = scale cos(orientation); xy = scale -sin(orientation); yx = scale sin(orientation); yy = scale * cos(orientation);
  • data (type: String.t, default: nil) -
  • dataFactor (type: number(), default: nil) - data_factor and data represent the local descriptor vector in a compressed format, using only 8 bit per value. Each byte of the data string yields one component of the local descriptor by bit-casting it to an int8 and multiplying it by data_factor. Protocol buffers do not support int8 directly.
  • featureVector (type: GoogleApi.ContentWarehouse.V1.Model.PhotosVisionObjectrecFeatureVector.t, default: nil) - Unquantized feature vector (float).
  • opaqueData (type: String.t, default: nil) - Opaque descriptor data. May be used to pass through descriptor data from descriptor sources to processing modules, that is not already covered by data/data_factor and/or cannot be expressed as a vector of numbers. It is the responsibility of processing modules to verify that the data is in a compatible format.
  • orientation (type: number(), default: nil) - Orientation is optional, as some interest point detectors don't compute it. The range of orientation is [-pi,pi).
  • scale (type: number(), default: nil) - Each interest point must have a characteristic scale > 0.
  • strength (type: number(), default: nil) - The strength or weight, indicating the relative significance of this point.
  • x (type: number(), default: nil) - The position in the image with sub-pixel accuracy. The center of the upper left pixel has coordinates (0.0, 0.0). Thus the range for x and y is (-0.5, width - 0.5) x (-0.5, height - 0.5).
  • y (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.PhotosVisionObjectrecLocalDescriptor{
    affineMatrix:
      GoogleApi.ContentWarehouse.V1.Model.PhotosVisionObjectrecMatrix2D.t()
      | nil,
    data: String.t() | nil,
    dataFactor: number() | nil,
    featureVector:
      GoogleApi.ContentWarehouse.V1.Model.PhotosVisionObjectrecFeatureVector.t()
      | nil,
    opaqueData: String.t() | nil,
    orientation: number() | nil,
    scale: number() | nil,
    strength: number() | nil,
    x: number() | nil,
    y: number() | nil
  }

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.