Module aws_sdk_lookoutvision::types

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Expand description

Data structures used by operation inputs/outputs.

Modules§

  • builders
    Builders
  • error
    Error types that Amazon Lookout for Vision can respond with.

Structs§

  • Anomaly

    Information about an anomaly type found on an image by an image segmentation model. For more information, see DetectAnomalies.

  • DatasetDescription

    The description for a dataset. For more information, see DescribeDataset.

  • DatasetGroundTruthManifest

    Location information about a manifest file. You can use a manifest file to create a dataset.

  • DatasetImageStats

    Statistics about the images in a dataset.

  • DatasetMetadata

    Summary information for an Amazon Lookout for Vision dataset. For more information, see DescribeDataset and ProjectDescription.

  • DatasetSource

    Information about the location of a manifest file that Amazon Lookout for Vision uses to to create a dataset.

  • DetectAnomalyResult

    The prediction results from a call to DetectAnomalies. DetectAnomalyResult includes classification information for the prediction (IsAnomalous and Confidence). If the model you use is an image segementation model, DetectAnomalyResult also includes segmentation information (Anomalies and AnomalyMask). Classification information is calculated separately from segmentation information and you shouldn't assume a relationship between them.

  • GreengrassConfiguration

    Configuration information for the AWS IoT Greengrass component created in a model packaging job. For more information, see StartModelPackagingJob.

    You can't specify a component with the same ComponentName and Componentversion as an existing component with the same component name and component version.

  • GreengrassOutputDetails

    Information about the AWS IoT Greengrass component created by a model packaging job.

  • ImageSource

    The source for an image.

  • InputS3Object

    Amazon S3 Location information for an input manifest file.

  • ModelDescription

    Describes an Amazon Lookout for Vision model.

  • ModelMetadata

    Describes an Amazon Lookout for Vision model.

  • ModelPackagingConfiguration

    Configuration information for a Amazon Lookout for Vision model packaging job. For more information, see StartModelPackagingJob.

  • ModelPackagingDescription

    Information about a model packaging job. For more information, see DescribeModelPackagingJob.

  • ModelPackagingJobMetadata

    Metadata for a model packaging job. For more information, see ListModelPackagingJobs.

  • ModelPackagingOutputDetails

    Information about the output from a model packaging job.

  • ModelPerformance

    Information about the evaluation performance of a trained model.

  • OutputConfig

    The S3 location where Amazon Lookout for Vision saves model training files.

  • OutputS3Object

    The S3 location where Amazon Lookout for Vision saves training output.

  • PixelAnomaly

    Information about the pixels in an anomaly mask. For more information, see Anomaly. PixelAnomaly is only returned by image segmentation models.

  • ProjectDescription

    Describe an Amazon Lookout for Vision project. For more information, see DescribeProject.

  • ProjectMetadata

    Metadata about an Amazon Lookout for Vision project.

  • S3Location

    Information about the location of training output or the output of a model packaging job.

  • Tag

    A key and value pair that is attached to the specified Amazon Lookout for Vision model.

  • TargetPlatform

    The platform on which a model runs on an AWS IoT Greengrass core device.

Enums§

  • DatasetStatus
    When writing a match expression against DatasetStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • ModelHostingStatus
    When writing a match expression against ModelHostingStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • ModelPackagingJobStatus
    When writing a match expression against ModelPackagingJobStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • ModelStatus
    When writing a match expression against ModelStatus, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • ResourceType
    When writing a match expression against ResourceType, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • TargetDevice
    When writing a match expression against TargetDevice, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • TargetPlatformAccelerator
    When writing a match expression against TargetPlatformAccelerator, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • TargetPlatformArch
    When writing a match expression against TargetPlatformArch, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.
  • TargetPlatformOs
    When writing a match expression against TargetPlatformOs, it is important to ensure your code is forward-compatible. That is, if a match arm handles a case for a feature that is supported by the service but has not been represented as an enum variant in a current version of SDK, your code should continue to work when you upgrade SDK to a future version in which the enum does include a variant for that feature.