# frozen_string_literal: true
# WARNING ABOUT GENERATED CODE
#
# This file is generated. See the contributing guide for more information:
# https://github.com/aws/aws-sdk-ruby/blob/version-3/CONTRIBUTING.md
#
# WARNING ABOUT GENERATED CODE
module Aws::Rekognition
module Types
# You are not authorized to perform the action.
#
class AccessDeniedException < Aws::EmptyStructure; end
# Structure containing the estimated age range, in years, for a face.
#
# Amazon Rekognition estimates an age range for faces detected in the
# input image. Estimated age ranges can overlap. A face of a 5-year-old
# might have an estimated range of 4-6, while the face of a 6-year-old
# might have an estimated range of 4-8.
#
# @!attribute [rw] low
# The lowest estimated age.
# @return [Integer]
#
# @!attribute [rw] high
# The highest estimated age.
# @return [Integer]
#
class AgeRange < Struct.new(
:low,
:high)
SENSITIVE = []
include Aws::Structure
end
# Assets are the images that you use to train and evaluate a model
# version. Assets can also contain validation information that you use
# to debug a failed model training.
#
# @note When making an API call, you may pass Asset
# data as a hash:
#
# {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# }
#
# @!attribute [rw] ground_truth_manifest
# The S3 bucket that contains an Amazon Sagemaker Ground Truth format
# manifest file.
# @return [Types::GroundTruthManifest]
#
class Asset < Struct.new(
:ground_truth_manifest)
SENSITIVE = []
include Aws::Structure
end
# Metadata information about an audio stream. An array of
# `AudioMetadata` objects for the audio streams found in a stored video
# is returned by GetSegmentDetection.
#
# @!attribute [rw] codec
# The audio codec used to encode or decode the audio stream.
# @return [String]
#
# @!attribute [rw] duration_millis
# The duration of the audio stream in milliseconds.
# @return [Integer]
#
# @!attribute [rw] sample_rate
# The sample rate for the audio stream.
# @return [Integer]
#
# @!attribute [rw] number_of_channels
# The number of audio channels in the segment.
# @return [Integer]
#
class AudioMetadata < Struct.new(
:codec,
:duration_millis,
:sample_rate,
:number_of_channels)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the face has a beard, and the confidence
# level in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the face has beard or not.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class Beard < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# A filter that allows you to control the black frame detection by
# specifying the black levels and pixel coverage of black pixels in a
# frame. As videos can come from multiple sources, formats, and time
# periods, they may contain different standards and varying noise levels
# for black frames that need to be accounted for. For more information,
# see StartSegmentDetection.
#
# @note When making an API call, you may pass BlackFrame
# data as a hash:
#
# {
# max_pixel_threshold: 1.0,
# min_coverage_percentage: 1.0,
# }
#
# @!attribute [rw] max_pixel_threshold
# A threshold used to determine the maximum luminance value for a
# pixel to be considered black. In a full color range video, luminance
# values range from 0-255. A pixel value of 0 is pure black, and the
# most strict filter. The maximum black pixel value is computed as
# follows: max\_black\_pixel\_value = minimum\_luminance +
# MaxPixelThreshold *luminance\_range.
#
# For example, for a full range video with BlackPixelThreshold = 0.1,
# max\_black\_pixel\_value is 0 + 0.1 * (255-0) = 25.5.
#
# The default value of MaxPixelThreshold is 0.2, which maps to a
# max\_black\_pixel\_value of 51 for a full range video. You can lower
# this threshold to be more strict on black levels.
# @return [Float]
#
# @!attribute [rw] min_coverage_percentage
# The minimum percentage of pixels in a frame that need to have a
# luminance below the max\_black\_pixel\_value for a frame to be
# considered a black frame. Luminance is calculated using the BT.709
# matrix.
#
# The default value is 99, which means at least 99% of all pixels in
# the frame are black pixels as per the `MaxPixelThreshold` set. You
# can reduce this value to allow more noise on the black frame.
# @return [Float]
#
class BlackFrame < Struct.new(
:max_pixel_threshold,
:min_coverage_percentage)
SENSITIVE = []
include Aws::Structure
end
# Identifies the bounding box around the label, face, text, object of
# interest, or personal protective equipment. The `left` (x-coordinate)
# and `top` (y-coordinate) are coordinates representing the top and left
# sides of the bounding box. Note that the upper-left corner of the
# image is the origin (0,0).
#
# The `top` and `left` values returned are ratios of the overall image
# size. For example, if the input image is 700x200 pixels, and the
# top-left coordinate of the bounding box is 350x50 pixels, the API
# returns a `left` value of 0.5 (350/700) and a `top` value of 0.25
# (50/200).
#
# The `width` and `height` values represent the dimensions of the
# bounding box as a ratio of the overall image dimension. For example,
# if the input image is 700x200 pixels, and the bounding box width is 70
# pixels, the width returned is 0.1.
#
# <note markdown="1"> The bounding box coordinates can have negative values. For example, if
# Amazon Rekognition is able to detect a face that is at the image edge
# and is only partially visible, the service can return coordinates that
# are outside the image bounds and, depending on the image edge, you
# might get negative values or values greater than 1 for the `left` or
# `top` values.
#
# </note>
#
# @note When making an API call, you may pass BoundingBox
# data as a hash:
#
# {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# }
#
# @!attribute [rw] width
# Width of the bounding box as a ratio of the overall image width.
# @return [Float]
#
# @!attribute [rw] height
# Height of the bounding box as a ratio of the overall image height.
# @return [Float]
#
# @!attribute [rw] left
# Left coordinate of the bounding box as a ratio of overall image
# width.
# @return [Float]
#
# @!attribute [rw] top
# Top coordinate of the bounding box as a ratio of overall image
# height.
# @return [Float]
#
class BoundingBox < Struct.new(
:width,
:height,
:left,
:top)
SENSITIVE = []
include Aws::Structure
end
# Provides information about a celebrity recognized by the
# RecognizeCelebrities operation.
#
# @!attribute [rw] urls
# An array of URLs pointing to additional information about the
# celebrity. If there is no additional information about the
# celebrity, this list is empty.
# @return [Array<String>]
#
# @!attribute [rw] name
# The name of the celebrity.
# @return [String]
#
# @!attribute [rw] id
# A unique identifier for the celebrity.
# @return [String]
#
# @!attribute [rw] face
# Provides information about the celebrity's face, such as its
# location on the image.
# @return [Types::ComparedFace]
#
# @!attribute [rw] match_confidence
# The confidence, in percentage, that Amazon Rekognition has that the
# recognized face is the celebrity.
# @return [Float]
#
# @!attribute [rw] known_gender
# The known gender identity for the celebrity that matches the
# provided ID. The known gender identity can be Male, Female,
# Nonbinary, or Unlisted.
# @return [Types::KnownGender]
#
class Celebrity < Struct.new(
:urls,
:name,
:id,
:face,
:match_confidence,
:known_gender)
SENSITIVE = []
include Aws::Structure
end
# Information about a recognized celebrity.
#
# @!attribute [rw] urls
# An array of URLs pointing to additional celebrity information.
# @return [Array<String>]
#
# @!attribute [rw] name
# The name of the celebrity.
# @return [String]
#
# @!attribute [rw] id
# The unique identifier for the celebrity.
# @return [String]
#
# @!attribute [rw] confidence
# The confidence, in percentage, that Amazon Rekognition has that the
# recognized face is the celebrity.
# @return [Float]
#
# @!attribute [rw] bounding_box
# Bounding box around the body of a celebrity.
# @return [Types::BoundingBox]
#
# @!attribute [rw] face
# Face details for the recognized celebrity.
# @return [Types::FaceDetail]
#
# @!attribute [rw] known_gender
# Retrieves the known gender for the celebrity.
# @return [Types::KnownGender]
#
class CelebrityDetail < Struct.new(
:urls,
:name,
:id,
:confidence,
:bounding_box,
:face,
:known_gender)
SENSITIVE = []
include Aws::Structure
end
# Information about a detected celebrity and the time the celebrity was
# detected in a stored video. For more information, see
# GetCelebrityRecognition in the Amazon Rekognition Developer Guide.
#
# @!attribute [rw] timestamp
# The time, in milliseconds from the start of the video, that the
# celebrity was recognized. Note that `Timestamp` is not guaranteed to
# be accurate to the individual frame where the celebrity first
# appears.
# @return [Integer]
#
# @!attribute [rw] celebrity
# Information about a recognized celebrity.
# @return [Types::CelebrityDetail]
#
class CelebrityRecognition < Struct.new(
:timestamp,
:celebrity)
SENSITIVE = []
include Aws::Structure
end
# Provides information about a face in a target image that matches the
# source image face analyzed by `CompareFaces`. The `Face` property
# contains the bounding box of the face in the target image. The
# `Similarity` property is the confidence that the source image face
# matches the face in the bounding box.
#
# @!attribute [rw] similarity
# Level of confidence that the faces match.
# @return [Float]
#
# @!attribute [rw] face
# Provides face metadata (bounding box and confidence that the
# bounding box actually contains a face).
# @return [Types::ComparedFace]
#
class CompareFacesMatch < Struct.new(
:similarity,
:face)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CompareFacesRequest
# data as a hash:
#
# {
# source_image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# target_image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# similarity_threshold: 1.0,
# quality_filter: "NONE", # accepts NONE, AUTO, LOW, MEDIUM, HIGH
# }
#
# @!attribute [rw] source_image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes is not supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] target_image
# The target image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes is not supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] similarity_threshold
# The minimum level of confidence in the face matches that a match
# must meet to be included in the `FaceMatches` array.
# @return [Float]
#
# @!attribute [rw] quality_filter
# A filter that specifies a quality bar for how much filtering is done
# to identify faces. Filtered faces aren't compared. If you specify
# `AUTO`, Amazon Rekognition chooses the quality bar. If you specify
# `LOW`, `MEDIUM`, or `HIGH`, filtering removes all faces that don’t
# meet the chosen quality bar. The quality bar is based on a variety
# of common use cases. Low-quality detections can occur for a number
# of reasons. Some examples are an object that's misidentified as a
# face, a face that's too blurry, or a face with a pose that's too
# extreme to use. If you specify `NONE`, no filtering is performed.
# The default value is `NONE`.
#
# To use quality filtering, the collection you are using must be
# associated with version 3 of the face model or higher.
# @return [String]
#
class CompareFacesRequest < Struct.new(
:source_image,
:target_image,
:similarity_threshold,
:quality_filter)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_image_face
# The face in the source image that was used for comparison.
# @return [Types::ComparedSourceImageFace]
#
# @!attribute [rw] face_matches
# An array of faces in the target image that match the source image
# face. Each `CompareFacesMatch` object provides the bounding box, the
# confidence level that the bounding box contains a face, and the
# similarity score for the face in the bounding box and the face in
# the source image.
# @return [Array<Types::CompareFacesMatch>]
#
# @!attribute [rw] unmatched_faces
# An array of faces in the target image that did not match the source
# image face.
# @return [Array<Types::ComparedFace>]
#
# @!attribute [rw] source_image_orientation_correction
# The value of `SourceImageOrientationCorrection` is always null.
#
# If the input image is in .jpeg format, it might contain exchangeable
# image file format (Exif) metadata that includes the image's
# orientation. Amazon Rekognition uses this orientation information to
# perform image correction. The bounding box coordinates are
# translated to represent object locations after the orientation
# information in the Exif metadata is used to correct the image
# orientation. Images in .png format don't contain Exif metadata.
#
# Amazon Rekognition doesn’t perform image correction for images in
# .png format and .jpeg images without orientation information in the
# image Exif metadata. The bounding box coordinates aren't translated
# and represent the object locations before the image is rotated.
# @return [String]
#
# @!attribute [rw] target_image_orientation_correction
# The value of `TargetImageOrientationCorrection` is always null.
#
# If the input image is in .jpeg format, it might contain exchangeable
# image file format (Exif) metadata that includes the image's
# orientation. Amazon Rekognition uses this orientation information to
# perform image correction. The bounding box coordinates are
# translated to represent object locations after the orientation
# information in the Exif metadata is used to correct the image
# orientation. Images in .png format don't contain Exif metadata.
#
# Amazon Rekognition doesn’t perform image correction for images in
# .png format and .jpeg images without orientation information in the
# image Exif metadata. The bounding box coordinates aren't translated
# and represent the object locations before the image is rotated.
# @return [String]
#
class CompareFacesResponse < Struct.new(
:source_image_face,
:face_matches,
:unmatched_faces,
:source_image_orientation_correction,
:target_image_orientation_correction)
SENSITIVE = []
include Aws::Structure
end
# Provides face metadata for target image faces that are analyzed by
# `CompareFaces` and `RecognizeCelebrities`.
#
# @!attribute [rw] bounding_box
# Bounding box of the face.
# @return [Types::BoundingBox]
#
# @!attribute [rw] confidence
# Level of confidence that what the bounding box contains is a face.
# @return [Float]
#
# @!attribute [rw] landmarks
# An array of facial landmarks.
# @return [Array<Types::Landmark>]
#
# @!attribute [rw] pose
# Indicates the pose of the face as determined by its pitch, roll, and
# yaw.
# @return [Types::Pose]
#
# @!attribute [rw] quality
# Identifies face image brightness and sharpness.
# @return [Types::ImageQuality]
#
# @!attribute [rw] emotions
# The emotions that appear to be expressed on the face, and the
# confidence level in the determination. Valid values include
# "Happy", "Sad", "Angry", "Confused", "Disgusted",
# "Surprised", "Calm", "Unknown", and "Fear".
# @return [Array<Types::Emotion>]
#
# @!attribute [rw] smile
# Indicates whether or not the face is smiling, and the confidence
# level in the determination.
# @return [Types::Smile]
#
class ComparedFace < Struct.new(
:bounding_box,
:confidence,
:landmarks,
:pose,
:quality,
:emotions,
:smile)
SENSITIVE = []
include Aws::Structure
end
# Type that describes the face Amazon Rekognition chose to compare with
# the faces in the target. This contains a bounding box for the selected
# face and confidence level that the bounding box contains a face. Note
# that Amazon Rekognition selects the largest face in the source image
# for this comparison.
#
# @!attribute [rw] bounding_box
# Bounding box of the face.
# @return [Types::BoundingBox]
#
# @!attribute [rw] confidence
# Confidence level that the selected bounding box contains a face.
# @return [Float]
#
class ComparedSourceImageFace < Struct.new(
:bounding_box,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Label detection settings to use on a streaming video. Defining the
# settings is required in the request parameter for
# CreateStreamProcessor. Including this setting in the
# `CreateStreamProcessor` request enables you to use the stream
# processor for label detection. You can then select what you want the
# stream processor to detect, such as people or pets. When the stream
# processor has started, one notification is sent for each object class
# specified. For example, if packages and pets are selected, one SNS
# notification is published the first time a package is detected and one
# SNS notification is published the first time a pet is detected, as
# well as an end-of-session summary.
#
# @note When making an API call, you may pass ConnectedHomeSettings
# data as a hash:
#
# {
# labels: ["ConnectedHomeLabel"], # required
# min_confidence: 1.0,
# }
#
# @!attribute [rw] labels
# Specifies what you want to detect in the video, such as people,
# packages, or pets. The current valid labels you can include in this
# list are: "PERSON", "PET", "PACKAGE", and "ALL".
# @return [Array<String>]
#
# @!attribute [rw] min_confidence
# The minimum confidence required to label an object in the video.
# @return [Float]
#
class ConnectedHomeSettings < Struct.new(
:labels,
:min_confidence)
SENSITIVE = []
include Aws::Structure
end
# The label detection settings you want to use in your stream processor.
# This includes the labels you want the stream processor to detect and
# the minimum confidence level allowed to label objects.
#
# @note When making an API call, you may pass ConnectedHomeSettingsForUpdate
# data as a hash:
#
# {
# labels: ["ConnectedHomeLabel"],
# min_confidence: 1.0,
# }
#
# @!attribute [rw] labels
# Specifies what you want to detect in the video, such as people,
# packages, or pets. The current valid labels you can include in this
# list are: "PERSON", "PET", "PACKAGE", and "ALL".
# @return [Array<String>]
#
# @!attribute [rw] min_confidence
# The minimum confidence required to label an object in the video.
# @return [Float]
#
class ConnectedHomeSettingsForUpdate < Struct.new(
:labels,
:min_confidence)
SENSITIVE = []
include Aws::Structure
end
# Information about an inappropriate, unwanted, or offensive content
# label detection in a stored video.
#
# @!attribute [rw] timestamp
# Time, in milliseconds from the beginning of the video, that the
# content moderation label was detected. Note that `Timestamp` is not
# guaranteed to be accurate to the individual frame where the
# moderated content first appears.
# @return [Integer]
#
# @!attribute [rw] moderation_label
# The content moderation label detected by in the stored video.
# @return [Types::ModerationLabel]
#
class ContentModerationDetection < Struct.new(
:timestamp,
:moderation_label)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CopyProjectVersionRequest
# data as a hash:
#
# {
# source_project_arn: "ProjectArn", # required
# source_project_version_arn: "ProjectVersionArn", # required
# destination_project_arn: "ProjectArn", # required
# version_name: "VersionName", # required
# output_config: { # required
# s3_bucket: "S3Bucket",
# s3_key_prefix: "S3KeyPrefix",
# },
# tags: {
# "TagKey" => "TagValue",
# },
# kms_key_id: "KmsKeyId",
# }
#
# @!attribute [rw] source_project_arn
# The ARN of the source project in the trusting AWS account.
# @return [String]
#
# @!attribute [rw] source_project_version_arn
# The ARN of the model version in the source project that you want to
# copy to a destination project.
# @return [String]
#
# @!attribute [rw] destination_project_arn
# The ARN of the project in the trusted AWS account that you want to
# copy the model version to.
# @return [String]
#
# @!attribute [rw] version_name
# A name for the version of the model that's copied to the
# destination project.
# @return [String]
#
# @!attribute [rw] output_config
# The S3 bucket and folder location where the training output for the
# source model version is placed.
# @return [Types::OutputConfig]
#
# @!attribute [rw] tags
# The key-value tags to assign to the model version.
# @return [Hash<String,String>]
#
# @!attribute [rw] kms_key_id
# The identifier for your AWS Key Management Service key (AWS KMS
# key). You can supply the Amazon Resource Name (ARN) of your KMS key,
# the ID of your KMS key, an alias for your KMS key, or an alias ARN.
# The key is used to encrypt training results and manifest files
# written to the output Amazon S3 bucket (`OutputConfig`).
#
# If you choose to use your own KMS key, you need the following
# permissions on the KMS key.
#
# * kms:CreateGrant
#
# * kms:DescribeKey
#
# * kms:GenerateDataKey
#
# * kms:Decrypt
#
# If you don't specify a value for `KmsKeyId`, images copied into the
# service are encrypted using a key that AWS owns and manages.
# @return [String]
#
class CopyProjectVersionRequest < Struct.new(
:source_project_arn,
:source_project_version_arn,
:destination_project_arn,
:version_name,
:output_config,
:tags,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_version_arn
# The ARN of the copied model version in the destination project.
# @return [String]
#
class CopyProjectVersionResponse < Struct.new(
:project_version_arn)
SENSITIVE = []
include Aws::Structure
end
# Information about an item of Personal Protective Equipment covering a
# corresponding body part. For more information, see
# DetectProtectiveEquipment.
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition has in the value of `Value`.
# @return [Float]
#
# @!attribute [rw] value
# True if the PPE covers the corresponding body part, otherwise false.
# @return [Boolean]
#
class CoversBodyPart < Struct.new(
:confidence,
:value)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CreateCollectionRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# tags: {
# "TagKey" => "TagValue",
# },
# }
#
# @!attribute [rw] collection_id
# ID for the collection that you are creating.
# @return [String]
#
# @!attribute [rw] tags
# A set of tags (key-value pairs) that you want to attach to the
# collection.
# @return [Hash<String,String>]
#
class CreateCollectionRequest < Struct.new(
:collection_id,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] status_code
# HTTP status code indicating the result of the operation.
# @return [Integer]
#
# @!attribute [rw] collection_arn
# Amazon Resource Name (ARN) of the collection. You can use this to
# manage permissions on your resources.
# @return [String]
#
# @!attribute [rw] face_model_version
# Version number of the face detection model associated with the
# collection you are creating.
# @return [String]
#
class CreateCollectionResponse < Struct.new(
:status_code,
:collection_arn,
:face_model_version)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CreateDatasetRequest
# data as a hash:
#
# {
# dataset_source: {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# dataset_arn: "DatasetArn",
# },
# dataset_type: "TRAIN", # required, accepts TRAIN, TEST
# project_arn: "ProjectArn", # required
# }
#
# @!attribute [rw] dataset_source
# The source files for the dataset. You can specify the ARN of an
# existing dataset or specify the Amazon S3 bucket location of an
# Amazon Sagemaker format manifest file. If you don't specify
# `datasetSource`, an empty dataset is created. To add labeled images
# to the dataset, You can use the console or call
# UpdateDatasetEntries.
# @return [Types::DatasetSource]
#
# @!attribute [rw] dataset_type
# The type of the dataset. Specify `train` to create a training
# dataset. Specify `test` to create a test dataset.
# @return [String]
#
# @!attribute [rw] project_arn
# The ARN of the Amazon Rekognition Custom Labels project to which you
# want to asssign the dataset.
# @return [String]
#
class CreateDatasetRequest < Struct.new(
:dataset_source,
:dataset_type,
:project_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] dataset_arn
# The ARN of the created Amazon Rekognition Custom Labels dataset.
# @return [String]
#
class CreateDatasetResponse < Struct.new(
:dataset_arn)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CreateProjectRequest
# data as a hash:
#
# {
# project_name: "ProjectName", # required
# }
#
# @!attribute [rw] project_name
# The name of the project to create.
# @return [String]
#
class CreateProjectRequest < Struct.new(
:project_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the new project. You can use the
# ARN to configure IAM access to the project.
# @return [String]
#
class CreateProjectResponse < Struct.new(
:project_arn)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CreateProjectVersionRequest
# data as a hash:
#
# {
# project_arn: "ProjectArn", # required
# version_name: "VersionName", # required
# output_config: { # required
# s3_bucket: "S3Bucket",
# s3_key_prefix: "S3KeyPrefix",
# },
# training_data: {
# assets: [
# {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# },
# ],
# },
# testing_data: {
# assets: [
# {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# },
# ],
# auto_create: false,
# },
# tags: {
# "TagKey" => "TagValue",
# },
# kms_key_id: "KmsKeyId",
# }
#
# @!attribute [rw] project_arn
# The ARN of the Amazon Rekognition Custom Labels project that manages
# the model that you want to train.
# @return [String]
#
# @!attribute [rw] version_name
# A name for the version of the model. This value must be unique.
# @return [String]
#
# @!attribute [rw] output_config
# The Amazon S3 bucket location to store the results of training. The
# S3 bucket can be in any AWS account as long as the caller has
# `s3:PutObject` permissions on the S3 bucket.
# @return [Types::OutputConfig]
#
# @!attribute [rw] training_data
# Specifies an external manifest that the services uses to train the
# model. If you specify `TrainingData` you must also specify
# `TestingData`. The project must not have any associated datasets.
# @return [Types::TrainingData]
#
# @!attribute [rw] testing_data
# Specifies an external manifest that the service uses to test the
# model. If you specify `TestingData` you must also specify
# `TrainingData`. The project must not have any associated datasets.
# @return [Types::TestingData]
#
# @!attribute [rw] tags
# A set of tags (key-value pairs) that you want to attach to the
# model.
# @return [Hash<String,String>]
#
# @!attribute [rw] kms_key_id
# The identifier for your AWS Key Management Service key (AWS KMS
# key). You can supply the Amazon Resource Name (ARN) of your KMS key,
# the ID of your KMS key, an alias for your KMS key, or an alias ARN.
# The key is used to encrypt training and test images copied into the
# service for model training. Your source images are unaffected. The
# key is also used to encrypt training results and manifest files
# written to the output Amazon S3 bucket (`OutputConfig`).
#
# If you choose to use your own KMS key, you need the following
# permissions on the KMS key.
#
# * kms:CreateGrant
#
# * kms:DescribeKey
#
# * kms:GenerateDataKey
#
# * kms:Decrypt
#
# If you don't specify a value for `KmsKeyId`, images copied into the
# service are encrypted using a key that AWS owns and manages.
# @return [String]
#
class CreateProjectVersionRequest < Struct.new(
:project_arn,
:version_name,
:output_config,
:training_data,
:testing_data,
:tags,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_version_arn
# The ARN of the model version that was created. Use
# `DescribeProjectVersion` to get the current status of the training
# operation.
# @return [String]
#
class CreateProjectVersionResponse < Struct.new(
:project_version_arn)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass CreateStreamProcessorRequest
# data as a hash:
#
# {
# input: { # required
# kinesis_video_stream: {
# arn: "KinesisVideoArn",
# },
# },
# output: { # required
# kinesis_data_stream: {
# arn: "KinesisDataArn",
# },
# s3_destination: {
# bucket: "S3Bucket",
# key_prefix: "S3KeyPrefix",
# },
# },
# name: "StreamProcessorName", # required
# settings: { # required
# face_search: {
# collection_id: "CollectionId",
# face_match_threshold: 1.0,
# },
# connected_home: {
# labels: ["ConnectedHomeLabel"], # required
# min_confidence: 1.0,
# },
# },
# role_arn: "RoleArn", # required
# tags: {
# "TagKey" => "TagValue",
# },
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# },
# kms_key_id: "KmsKeyId",
# regions_of_interest: [
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# },
# ],
# data_sharing_preference: {
# opt_in: false, # required
# },
# }
#
# @!attribute [rw] input
# Kinesis video stream stream that provides the source streaming
# video. If you are using the AWS CLI, the parameter name is
# `StreamProcessorInput`. This is required for both face search and
# label detection stream processors.
# @return [Types::StreamProcessorInput]
#
# @!attribute [rw] output
# Kinesis data stream stream or Amazon S3 bucket location to which
# Amazon Rekognition Video puts the analysis results. If you are using
# the AWS CLI, the parameter name is `StreamProcessorOutput`. This
# must be a S3Destination of an Amazon S3 bucket that you own for a
# label detection stream processor or a Kinesis data stream ARN for a
# face search stream processor.
# @return [Types::StreamProcessorOutput]
#
# @!attribute [rw] name
# An identifier you assign to the stream processor. You can use `Name`
# to manage the stream processor. For example, you can get the current
# status of the stream processor by calling DescribeStreamProcessor.
# `Name` is idempotent. This is required for both face search and
# label detection stream processors.
# @return [String]
#
# @!attribute [rw] settings
# Input parameters used in a streaming video analyzed by a stream
# processor. You can use `FaceSearch` to recognize faces in a
# streaming video, or you can use `ConnectedHome` to detect labels.
# @return [Types::StreamProcessorSettings]
#
# @!attribute [rw] role_arn
# The Amazon Resource Number (ARN) of the IAM role that allows access
# to the stream processor. The IAM role provides Rekognition read
# permissions for a Kinesis stream. It also provides write permissions
# to an Amazon S3 bucket and Amazon Simple Notification Service topic
# for a label detection stream processor. This is required for both
# face search and label detection stream processors.
# @return [String]
#
# @!attribute [rw] tags
# A set of tags (key-value pairs) that you want to attach to the
# stream processor.
# @return [Hash<String,String>]
#
# @!attribute [rw] notification_channel
# The Amazon Simple Notification Service topic to which Amazon
# Rekognition publishes the object detection results and completion
# status of a video analysis operation.
#
# Amazon Rekognition publishes a notification the first time an object
# of interest or a person is detected in the video stream. For
# example, if Amazon Rekognition detects a person at second 2, a pet
# at second 4, and a person again at second 5, Amazon Rekognition
# sends 2 object class detected notifications, one for a person at
# second 2 and one for a pet at second 4.
#
# Amazon Rekognition also publishes an an end-of-session notification
# with a summary when the stream processing session is complete.
# @return [Types::StreamProcessorNotificationChannel]
#
# @!attribute [rw] kms_key_id
# The identifier for your AWS Key Management Service key (AWS KMS
# key). This is an optional parameter for label detection stream
# processors and should not be used to create a face search stream
# processor. You can supply the Amazon Resource Name (ARN) of your KMS
# key, the ID of your KMS key, an alias for your KMS key, or an alias
# ARN. The key is used to encrypt results and data published to your
# Amazon S3 bucket, which includes image frames and hero images. Your
# source images are unaffected.
# @return [String]
#
# @!attribute [rw] regions_of_interest
# Specifies locations in the frames where Amazon Rekognition checks
# for objects or people. You can specify up to 10 regions of interest,
# and each region has either a polygon or a bounding box. This is an
# optional parameter for label detection stream processors and should
# not be used to create a face search stream processor.
# @return [Array<Types::RegionOfInterest>]
#
# @!attribute [rw] data_sharing_preference
# Shows whether you are sharing data with Rekognition to improve model
# performance. You can choose this option at the account level or on a
# per-stream basis. Note that if you opt out at the account level this
# setting is ignored on individual streams.
# @return [Types::StreamProcessorDataSharingPreference]
#
class CreateStreamProcessorRequest < Struct.new(
:input,
:output,
:name,
:settings,
:role_arn,
:tags,
:notification_channel,
:kms_key_id,
:regions_of_interest,
:data_sharing_preference)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] stream_processor_arn
# Amazon Resource Number for the newly created stream processor.
# @return [String]
#
class CreateStreamProcessorResponse < Struct.new(
:stream_processor_arn)
SENSITIVE = []
include Aws::Structure
end
# A custom label detected in an image by a call to DetectCustomLabels.
#
# @!attribute [rw] name
# The name of the custom label.
# @return [String]
#
# @!attribute [rw] confidence
# The confidence that the model has in the detection of the custom
# label. The range is 0-100. A higher value indicates a higher
# confidence.
# @return [Float]
#
# @!attribute [rw] geometry
# The location of the detected object on the image that corresponds to
# the custom label. Includes an axis aligned coarse bounding box
# surrounding the object and a finer grain polygon for more accurate
# spatial information.
# @return [Types::Geometry]
#
class CustomLabel < Struct.new(
:name,
:confidence,
:geometry)
SENSITIVE = []
include Aws::Structure
end
# Describes updates or additions to a dataset. A Single update or
# addition is an entry (JSON Line) that provides information about a
# single image. To update an existing entry, you match the `source-ref`
# field of the update entry with the `source-ref` filed of the entry
# that you want to update. If the `source-ref` field doesn't match an
# existing entry, the entry is added to dataset as a new entry.
#
# @note When making an API call, you may pass DatasetChanges
# data as a hash:
#
# {
# ground_truth: "data", # required
# }
#
# @!attribute [rw] ground_truth
# A Base64-encoded binary data object containing one or JSON lines
# that either update the dataset or are additions to the dataset. You
# change a dataset by calling UpdateDatasetEntries. If you are using
# an AWS SDK to call `UpdateDatasetEntries`, you don't need to encode
# `Changes` as the SDK encodes the data for you.
#
# For example JSON lines, see Image-Level labels in manifest files and
# and Object localization in manifest files in the *Amazon Rekognition
# Custom Labels Developer Guide*.
# @return [String]
#
class DatasetChanges < Struct.new(
:ground_truth)
SENSITIVE = []
include Aws::Structure
end
# A description for a dataset. For more information, see
# DescribeDataset.
#
# The status fields `Status`, `StatusMessage`, and `StatusMessageCode`
# reflect the last operation on the dataset.
#
# @!attribute [rw] creation_timestamp
# The Unix timestamp for the time and date that the dataset was
# created.
# @return [Time]
#
# @!attribute [rw] last_updated_timestamp
# The Unix timestamp for the date and time that the dataset was last
# updated.
# @return [Time]
#
# @!attribute [rw] status
# The status of the dataset.
# @return [String]
#
# @!attribute [rw] status_message
# The status message for the dataset.
# @return [String]
#
# @!attribute [rw] status_message_code
# The status message code for the dataset operation. If a service
# error occurs, try the API call again later. If a client error
# occurs, check the input parameters to the dataset API call that
# failed.
# @return [String]
#
# @!attribute [rw] dataset_stats
# The status message code for the dataset.
# @return [Types::DatasetStats]
#
class DatasetDescription < Struct.new(
:creation_timestamp,
:last_updated_timestamp,
:status,
:status_message,
:status_message_code,
:dataset_stats)
SENSITIVE = []
include Aws::Structure
end
# Describes a dataset label. For more information, see
# ListDatasetLabels.
#
# @!attribute [rw] label_name
# The name of the label.
# @return [String]
#
# @!attribute [rw] label_stats
# Statistics about the label.
# @return [Types::DatasetLabelStats]
#
class DatasetLabelDescription < Struct.new(
:label_name,
:label_stats)
SENSITIVE = []
include Aws::Structure
end
# Statistics about a label used in a dataset. For more information, see
# DatasetLabelDescription.
#
# @!attribute [rw] entry_count
# The total number of images that use the label.
# @return [Integer]
#
# @!attribute [rw] bounding_box_count
# The total number of images that have the label assigned to a
# bounding box.
# @return [Integer]
#
class DatasetLabelStats < Struct.new(
:entry_count,
:bounding_box_count)
SENSITIVE = []
include Aws::Structure
end
# Summary information for an Amazon Rekognition Custom Labels dataset.
# For more information, see ProjectDescription.
#
# @!attribute [rw] creation_timestamp
# The Unix timestamp for the date and time that the dataset was
# created.
# @return [Time]
#
# @!attribute [rw] dataset_type
# The type of the dataset.
# @return [String]
#
# @!attribute [rw] dataset_arn
# The Amazon Resource Name (ARN) for the dataset.
# @return [String]
#
# @!attribute [rw] status
# The status for the dataset.
# @return [String]
#
# @!attribute [rw] status_message
# The status message for the dataset.
# @return [String]
#
# @!attribute [rw] status_message_code
# The status message code for the dataset operation. If a service
# error occurs, try the API call again later. If a client error
# occurs, check the input parameters to the dataset API call that
# failed.
# @return [String]
#
class DatasetMetadata < Struct.new(
:creation_timestamp,
:dataset_type,
:dataset_arn,
:status,
:status_message,
:status_message_code)
SENSITIVE = []
include Aws::Structure
end
# The source that Amazon Rekognition Custom Labels uses to create a
# dataset. To use an Amazon Sagemaker format manifest file, specify the
# S3 bucket location in the `GroundTruthManifest` field. The S3 bucket
# must be in your AWS account. To create a copy of an existing dataset,
# specify the Amazon Resource Name (ARN) of an existing dataset in
# `DatasetArn`.
#
# You need to specify a value for `DatasetArn` or `GroundTruthManifest`,
# but not both. if you supply both values, or if you don't specify any
# values, an InvalidParameterException exception occurs.
#
# For more information, see CreateDataset.
#
# @note When making an API call, you may pass DatasetSource
# data as a hash:
#
# {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# dataset_arn: "DatasetArn",
# }
#
# @!attribute [rw] ground_truth_manifest
# The S3 bucket that contains an Amazon Sagemaker Ground Truth format
# manifest file.
# @return [Types::GroundTruthManifest]
#
# @!attribute [rw] dataset_arn
# The ARN of an Amazon Rekognition Custom Labels dataset that you want
# to copy.
# @return [String]
#
class DatasetSource < Struct.new(
:ground_truth_manifest,
:dataset_arn)
SENSITIVE = []
include Aws::Structure
end
# Provides statistics about a dataset. For more information, see
# DescribeDataset.
#
# @!attribute [rw] labeled_entries
# The total number of images in the dataset that have labels.
# @return [Integer]
#
# @!attribute [rw] total_entries
# The total number of images in the dataset.
# @return [Integer]
#
# @!attribute [rw] total_labels
# The total number of labels declared in the dataset.
# @return [Integer]
#
# @!attribute [rw] error_entries
# The total number of entries that contain at least one error.
# @return [Integer]
#
class DatasetStats < Struct.new(
:labeled_entries,
:total_entries,
:total_labels,
:error_entries)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DeleteCollectionRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# }
#
# @!attribute [rw] collection_id
# ID of the collection to delete.
# @return [String]
#
class DeleteCollectionRequest < Struct.new(
:collection_id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] status_code
# HTTP status code that indicates the result of the operation.
# @return [Integer]
#
class DeleteCollectionResponse < Struct.new(
:status_code)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DeleteDatasetRequest
# data as a hash:
#
# {
# dataset_arn: "DatasetArn", # required
# }
#
# @!attribute [rw] dataset_arn
# The ARN of the Amazon Rekognition Custom Labels dataset that you
# want to delete.
# @return [String]
#
class DeleteDatasetRequest < Struct.new(
:dataset_arn)
SENSITIVE = []
include Aws::Structure
end
class DeleteDatasetResponse < Aws::EmptyStructure; end
# @note When making an API call, you may pass DeleteFacesRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# face_ids: ["FaceId"], # required
# }
#
# @!attribute [rw] collection_id
# Collection from which to remove the specific faces.
# @return [String]
#
# @!attribute [rw] face_ids
# An array of face IDs to delete.
# @return [Array<String>]
#
class DeleteFacesRequest < Struct.new(
:collection_id,
:face_ids)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] deleted_faces
# An array of strings (face IDs) of the faces that were deleted.
# @return [Array<String>]
#
class DeleteFacesResponse < Struct.new(
:deleted_faces)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DeleteProjectPolicyRequest
# data as a hash:
#
# {
# project_arn: "ProjectArn", # required
# policy_name: "ProjectPolicyName", # required
# policy_revision_id: "ProjectPolicyRevisionId",
# }
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project that the project
# policy you want to delete is attached to.
# @return [String]
#
# @!attribute [rw] policy_name
# The name of the policy that you want to delete.
# @return [String]
#
# @!attribute [rw] policy_revision_id
# The ID of the project policy revision that you want to delete.
# @return [String]
#
class DeleteProjectPolicyRequest < Struct.new(
:project_arn,
:policy_name,
:policy_revision_id)
SENSITIVE = []
include Aws::Structure
end
class DeleteProjectPolicyResponse < Aws::EmptyStructure; end
# @note When making an API call, you may pass DeleteProjectRequest
# data as a hash:
#
# {
# project_arn: "ProjectArn", # required
# }
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project that you want to
# delete.
# @return [String]
#
class DeleteProjectRequest < Struct.new(
:project_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] status
# The current status of the delete project operation.
# @return [String]
#
class DeleteProjectResponse < Struct.new(
:status)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DeleteProjectVersionRequest
# data as a hash:
#
# {
# project_version_arn: "ProjectVersionArn", # required
# }
#
# @!attribute [rw] project_version_arn
# The Amazon Resource Name (ARN) of the model version that you want to
# delete.
# @return [String]
#
class DeleteProjectVersionRequest < Struct.new(
:project_version_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] status
# The status of the deletion operation.
# @return [String]
#
class DeleteProjectVersionResponse < Struct.new(
:status)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DeleteStreamProcessorRequest
# data as a hash:
#
# {
# name: "StreamProcessorName", # required
# }
#
# @!attribute [rw] name
# The name of the stream processor you want to delete.
# @return [String]
#
class DeleteStreamProcessorRequest < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
class DeleteStreamProcessorResponse < Aws::EmptyStructure; end
# @note When making an API call, you may pass DescribeCollectionRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# }
#
# @!attribute [rw] collection_id
# The ID of the collection to describe.
# @return [String]
#
class DescribeCollectionRequest < Struct.new(
:collection_id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] face_count
# The number of faces that are indexed into the collection. To index
# faces into a collection, use IndexFaces.
# @return [Integer]
#
# @!attribute [rw] face_model_version
# The version of the face model that's used by the collection for
# face detection.
#
# For more information, see Model versioning in the Amazon Rekognition
# Developer Guide.
# @return [String]
#
# @!attribute [rw] collection_arn
# The Amazon Resource Name (ARN) of the collection.
# @return [String]
#
# @!attribute [rw] creation_timestamp
# The number of milliseconds since the Unix epoch time until the
# creation of the collection. The Unix epoch time is 00:00:00
# Coordinated Universal Time (UTC), Thursday, 1 January 1970.
# @return [Time]
#
class DescribeCollectionResponse < Struct.new(
:face_count,
:face_model_version,
:collection_arn,
:creation_timestamp)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DescribeDatasetRequest
# data as a hash:
#
# {
# dataset_arn: "DatasetArn", # required
# }
#
# @!attribute [rw] dataset_arn
# The Amazon Resource Name (ARN) of the dataset that you want to
# describe.
# @return [String]
#
class DescribeDatasetRequest < Struct.new(
:dataset_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] dataset_description
# The description for the dataset.
# @return [Types::DatasetDescription]
#
class DescribeDatasetResponse < Struct.new(
:dataset_description)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DescribeProjectVersionsRequest
# data as a hash:
#
# {
# project_arn: "ProjectArn", # required
# version_names: ["VersionName"],
# next_token: "ExtendedPaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project that contains the
# models you want to describe.
# @return [String]
#
# @!attribute [rw] version_names
# A list of model version names that you want to describe. You can add
# up to 10 model version names to the list. If you don't specify a
# value, all model descriptions are returned. A version name is part
# of a model (ProjectVersion) ARN. For example,
# `my-model.2020-01-21T09.10.15` is the version name in the following
# ARN.
# `arn:aws:rekognition:us-east-1:123456789012:project/getting-started/version/my-model.2020-01-21T09.10.15/1234567890123`.
# @return [Array<String>]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return per paginated call. The
# largest value you can specify is 100. If you specify a value greater
# than 100, a ValidationException error occurs. The default value is
# 100.
# @return [Integer]
#
class DescribeProjectVersionsRequest < Struct.new(
:project_arn,
:version_names,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_version_descriptions
# A list of model descriptions. The list is sorted by the creation
# date and time of the model versions, latest to earliest.
# @return [Array<Types::ProjectVersionDescription>]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
class DescribeProjectVersionsResponse < Struct.new(
:project_version_descriptions,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DescribeProjectsRequest
# data as a hash:
#
# {
# next_token: "ExtendedPaginationToken",
# max_results: 1,
# project_names: ["ProjectName"],
# }
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return per paginated call. The
# largest value you can specify is 100. If you specify a value greater
# than 100, a ValidationException error occurs. The default value is
# 100.
# @return [Integer]
#
# @!attribute [rw] project_names
# A list of the projects that you want Amazon Rekognition Custom
# Labels to describe. If you don't specify a value, the response
# includes descriptions for all the projects in your AWS account.
# @return [Array<String>]
#
class DescribeProjectsRequest < Struct.new(
:next_token,
:max_results,
:project_names)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_descriptions
# A list of project descriptions. The list is sorted by the date and
# time the projects are created.
# @return [Array<Types::ProjectDescription>]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
class DescribeProjectsResponse < Struct.new(
:project_descriptions,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DescribeStreamProcessorRequest
# data as a hash:
#
# {
# name: "StreamProcessorName", # required
# }
#
# @!attribute [rw] name
# Name of the stream processor for which you want information.
# @return [String]
#
class DescribeStreamProcessorRequest < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name
# Name of the stream processor.
# @return [String]
#
# @!attribute [rw] stream_processor_arn
# ARN of the stream processor.
# @return [String]
#
# @!attribute [rw] status
# Current status of the stream processor.
# @return [String]
#
# @!attribute [rw] status_message
# Detailed status message about the stream processor.
# @return [String]
#
# @!attribute [rw] creation_timestamp
# Date and time the stream processor was created
# @return [Time]
#
# @!attribute [rw] last_update_timestamp
# The time, in Unix format, the stream processor was last updated. For
# example, when the stream processor moves from a running state to a
# failed state, or when the user starts or stops the stream processor.
# @return [Time]
#
# @!attribute [rw] input
# Kinesis video stream that provides the source streaming video.
# @return [Types::StreamProcessorInput]
#
# @!attribute [rw] output
# Kinesis data stream to which Amazon Rekognition Video puts the
# analysis results.
# @return [Types::StreamProcessorOutput]
#
# @!attribute [rw] role_arn
# ARN of the IAM role that allows access to the stream processor.
# @return [String]
#
# @!attribute [rw] settings
# Input parameters used in a streaming video analyzed by a stream
# processor. You can use `FaceSearch` to recognize faces in a
# streaming video, or you can use `ConnectedHome` to detect labels.
# @return [Types::StreamProcessorSettings]
#
# @!attribute [rw] notification_channel
# The Amazon Simple Notification Service topic to which Amazon
# Rekognition publishes the object detection results and completion
# status of a video analysis operation.
#
# Amazon Rekognition publishes a notification the first time an object
# of interest or a person is detected in the video stream. For
# example, if Amazon Rekognition detects a person at second 2, a pet
# at second 4, and a person again at second 5, Amazon Rekognition
# sends 2 object class detected notifications, one for a person at
# second 2 and one for a pet at second 4.
#
# Amazon Rekognition also publishes an an end-of-session notification
# with a summary when the stream processing session is complete.
# @return [Types::StreamProcessorNotificationChannel]
#
# @!attribute [rw] kms_key_id
# The identifier for your AWS Key Management Service key (AWS KMS
# key). This is an optional parameter for label detection stream
# processors.
# @return [String]
#
# @!attribute [rw] regions_of_interest
# Specifies locations in the frames where Amazon Rekognition checks
# for objects or people. This is an optional parameter for label
# detection stream processors.
# @return [Array<Types::RegionOfInterest>]
#
# @!attribute [rw] data_sharing_preference
# Shows whether you are sharing data with Rekognition to improve model
# performance. You can choose this option at the account level or on a
# per-stream basis. Note that if you opt out at the account level this
# setting is ignored on individual streams.
# @return [Types::StreamProcessorDataSharingPreference]
#
class DescribeStreamProcessorResponse < Struct.new(
:name,
:stream_processor_arn,
:status,
:status_message,
:creation_timestamp,
:last_update_timestamp,
:input,
:output,
:role_arn,
:settings,
:notification_channel,
:kms_key_id,
:regions_of_interest,
:data_sharing_preference)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DetectCustomLabelsRequest
# data as a hash:
#
# {
# project_version_arn: "ProjectVersionArn", # required
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# max_results: 1,
# min_confidence: 1.0,
# }
#
# @!attribute [rw] project_version_arn
# The ARN of the model version that you want to use.
# @return [String]
#
# @!attribute [rw] image
# Provides the input image either as bytes or an S3 object.
#
# You pass image bytes to an Amazon Rekognition API operation by using
# the `Bytes` property. For example, you would use the `Bytes`
# property to pass an image loaded from a local file system. Image
# bytes passed by using the `Bytes` property must be base64-encoded.
# Your code may not need to encode image bytes if you are using an AWS
# SDK to call Amazon Rekognition API operations.
#
# For more information, see Analyzing an Image Loaded from a Local
# File System in the Amazon Rekognition Developer Guide.
#
# You pass images stored in an S3 bucket to an Amazon Rekognition API
# operation by using the `S3Object` property. Images stored in an S3
# bucket do not need to be base64-encoded.
#
# The region for the S3 bucket containing the S3 object must match the
# region you use for Amazon Rekognition operations.
#
# If you use the AWS CLI to call Amazon Rekognition operations,
# passing image bytes using the Bytes property is not supported. You
# must first upload the image to an Amazon S3 bucket and then call the
# operation using the S3Object property.
#
# For Amazon Rekognition to process an S3 object, the user must have
# permission to access the S3 object. For more information, see How
# Amazon Rekognition works with IAM in the Amazon Rekognition
# Developer Guide.
# @return [Types::Image]
#
# @!attribute [rw] max_results
# Maximum number of results you want the service to return in the
# response. The service returns the specified number of highest
# confidence labels ranked from highest confidence to lowest.
# @return [Integer]
#
# @!attribute [rw] min_confidence
# Specifies the minimum confidence level for the labels to return.
# `DetectCustomLabels` doesn't return any labels with a confidence
# value that's lower than this specified value. If you specify a
# value of 0, `DetectCustomLabels` returns all labels, regardless of
# the assumed threshold applied to each label. If you don't specify a
# value for `MinConfidence`, `DetectCustomLabels` returns labels based
# on the assumed threshold of each label.
# @return [Float]
#
class DetectCustomLabelsRequest < Struct.new(
:project_version_arn,
:image,
:max_results,
:min_confidence)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] custom_labels
# An array of custom labels detected in the input image.
# @return [Array<Types::CustomLabel>]
#
class DetectCustomLabelsResponse < Struct.new(
:custom_labels)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DetectFacesRequest
# data as a hash:
#
# {
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# attributes: ["DEFAULT"], # accepts DEFAULT, ALL
# }
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes is not supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] attributes
# An array of facial attributes you want to be returned. This can be
# the default list of attributes or all attributes. If you don't
# specify a value for `Attributes` or if you specify `["DEFAULT"]`,
# the API returns the following subset of facial attributes:
# `BoundingBox`, `Confidence`, `Pose`, `Quality`, and `Landmarks`. If
# you provide `["ALL"]`, all facial attributes are returned, but the
# operation takes longer to complete.
#
# If you provide both, `["ALL", "DEFAULT"]`, the service uses a
# logical AND operator to determine which attributes to return (in
# this case, all attributes).
# @return [Array<String>]
#
class DetectFacesRequest < Struct.new(
:image,
:attributes)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] face_details
# Details of each face found in the image.
# @return [Array<Types::FaceDetail>]
#
# @!attribute [rw] orientation_correction
# The value of `OrientationCorrection` is always null.
#
# If the input image is in .jpeg format, it might contain exchangeable
# image file format (Exif) metadata that includes the image's
# orientation. Amazon Rekognition uses this orientation information to
# perform image correction. The bounding box coordinates are
# translated to represent object locations after the orientation
# information in the Exif metadata is used to correct the image
# orientation. Images in .png format don't contain Exif metadata.
#
# Amazon Rekognition doesn’t perform image correction for images in
# .png format and .jpeg images without orientation information in the
# image Exif metadata. The bounding box coordinates aren't translated
# and represent the object locations before the image is rotated.
# @return [String]
#
class DetectFacesResponse < Struct.new(
:face_details,
:orientation_correction)
SENSITIVE = []
include Aws::Structure
end
# The background of the image with regard to image quality and dominant
# colors.
#
# @!attribute [rw] quality
# The quality of the image background as defined by brightness and
# sharpness.
# @return [Types::DetectLabelsImageQuality]
#
# @!attribute [rw] dominant_colors
# The dominant colors found in the background of an image, defined
# with RGB values, CSS color name, simplified color name, and
# PixelPercentage (the percentage of image pixels that have a
# particular color).
# @return [Array<Types::DominantColor>]
#
class DetectLabelsImageBackground < Struct.new(
:quality,
:dominant_colors)
SENSITIVE = []
include Aws::Structure
end
# The foreground of the image with regard to image quality and dominant
# colors.
#
# @!attribute [rw] quality
# The quality of the image foreground as defined by brightness and
# sharpness.
# @return [Types::DetectLabelsImageQuality]
#
# @!attribute [rw] dominant_colors
# The dominant colors found in the foreground of an image, defined
# with RGB values, CSS color name, simplified color name, and
# PixelPercentage (the percentage of image pixels that have a
# particular color).
# @return [Array<Types::DominantColor>]
#
class DetectLabelsImageForeground < Struct.new(
:quality,
:dominant_colors)
SENSITIVE = []
include Aws::Structure
end
# Information about the quality and dominant colors of an input image.
# Quality and color information is returned for the entire image,
# foreground, and background.
#
# @!attribute [rw] quality
# Information about the quality of the image foreground as defined by
# brightness, sharpness, and contrast. The higher the value the
# greater the brightness, sharpness, and contrast respectively.
# @return [Types::DetectLabelsImageQuality]
#
# @!attribute [rw] dominant_colors
# Information about the dominant colors found in an image, described
# with RGB values, CSS color name, simplified color name, and
# PixelPercentage (the percentage of image pixels that have a
# particular color).
# @return [Array<Types::DominantColor>]
#
# @!attribute [rw] foreground
# Information about the properties of an image’s foreground, including
# the foreground’s quality and dominant colors, including the quality
# and dominant colors of the image.
# @return [Types::DetectLabelsImageForeground]
#
# @!attribute [rw] background
# Information about the properties of an image’s background, including
# the background’s quality and dominant colors, including the quality
# and dominant colors of the image.
# @return [Types::DetectLabelsImageBackground]
#
class DetectLabelsImageProperties < Struct.new(
:quality,
:dominant_colors,
:foreground,
:background)
SENSITIVE = []
include Aws::Structure
end
# Settings for the IMAGE\_PROPERTIES feature type.
#
# @note When making an API call, you may pass DetectLabelsImagePropertiesSettings
# data as a hash:
#
# {
# max_dominant_colors: 1,
# }
#
# @!attribute [rw] max_dominant_colors
# The maximum number of dominant colors to return when detecting
# labels in an image. The default value is 10.
# @return [Integer]
#
class DetectLabelsImagePropertiesSettings < Struct.new(
:max_dominant_colors)
SENSITIVE = []
include Aws::Structure
end
# The quality of an image provided for label detection, with regard to
# brightness, sharpness, and contrast.
#
# @!attribute [rw] brightness
# The brightness of an image provided for label detection.
# @return [Float]
#
# @!attribute [rw] sharpness
# The sharpness of an image provided for label detection.
# @return [Float]
#
# @!attribute [rw] contrast
# The contrast of an image provided for label detection.
# @return [Float]
#
class DetectLabelsImageQuality < Struct.new(
:brightness,
:sharpness,
:contrast)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DetectLabelsRequest
# data as a hash:
#
# {
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# max_labels: 1,
# min_confidence: 1.0,
# features: ["GENERAL_LABELS"], # accepts GENERAL_LABELS, IMAGE_PROPERTIES
# settings: {
# general_labels: {
# label_inclusion_filters: ["GeneralLabelsFilterValue"],
# label_exclusion_filters: ["GeneralLabelsFilterValue"],
# label_category_inclusion_filters: ["GeneralLabelsFilterValue"],
# label_category_exclusion_filters: ["GeneralLabelsFilterValue"],
# },
# image_properties: {
# max_dominant_colors: 1,
# },
# },
# }
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing image
# bytes is not supported. Images stored in an S3 Bucket do not need to
# be base64-encoded.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] max_labels
# Maximum number of labels you want the service to return in the
# response. The service returns the specified number of highest
# confidence labels.
# @return [Integer]
#
# @!attribute [rw] min_confidence
# Specifies the minimum confidence level for the labels to return.
# Amazon Rekognition doesn't return any labels with confidence lower
# than this specified value.
#
# If `MinConfidence` is not specified, the operation returns labels
# with a confidence values greater than or equal to 55 percent.
# @return [Float]
#
# @!attribute [rw] features
# A list of the types of analysis to perform. Specifying
# GENERAL\_LABELS uses the label detection feature, while specifying
# IMAGE\_PROPERTIES returns information regarding image color and
# quality. If no option is specified GENERAL\_LABELS is used by
# default.
# @return [Array<String>]
#
# @!attribute [rw] settings
# A list of the filters to be applied to returned detected labels and
# image properties. Specified filters can be inclusive, exclusive, or
# a combination of both. Filters can be used for individual labels or
# label categories. The exact label names or label categories must be
# supplied. For a full list of labels and label categories, see LINK
# HERE.
# @return [Types::DetectLabelsSettings]
#
class DetectLabelsRequest < Struct.new(
:image,
:max_labels,
:min_confidence,
:features,
:settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labels
# An array of labels for the real-world objects detected.
# @return [Array<Types::Label>]
#
# @!attribute [rw] orientation_correction
# The value of `OrientationCorrection` is always null.
#
# If the input image is in .jpeg format, it might contain exchangeable
# image file format (Exif) metadata that includes the image's
# orientation. Amazon Rekognition uses this orientation information to
# perform image correction. The bounding box coordinates are
# translated to represent object locations after the orientation
# information in the Exif metadata is used to correct the image
# orientation. Images in .png format don't contain Exif metadata.
#
# Amazon Rekognition doesn’t perform image correction for images in
# .png format and .jpeg images without orientation information in the
# image Exif metadata. The bounding box coordinates aren't translated
# and represent the object locations before the image is rotated.
# @return [String]
#
# @!attribute [rw] label_model_version
# Version number of the label detection model that was used to detect
# labels.
# @return [String]
#
# @!attribute [rw] image_properties
# Information about the properties of the input image, such as
# brightness, sharpness, contrast, and dominant colors.
# @return [Types::DetectLabelsImageProperties]
#
class DetectLabelsResponse < Struct.new(
:labels,
:orientation_correction,
:label_model_version,
:image_properties)
SENSITIVE = []
include Aws::Structure
end
# Settings for the DetectLabels request. Settings can include filters
# for both GENERAL\_LABELS and IMAGE\_PROPERTIES. GENERAL\_LABELS
# filters can be inclusive or exclusive and applied to individual labels
# or label categories. IMAGE\_PROPERTIES filters allow specification of
# a maximum number of dominant colors.
#
# @note When making an API call, you may pass DetectLabelsSettings
# data as a hash:
#
# {
# general_labels: {
# label_inclusion_filters: ["GeneralLabelsFilterValue"],
# label_exclusion_filters: ["GeneralLabelsFilterValue"],
# label_category_inclusion_filters: ["GeneralLabelsFilterValue"],
# label_category_exclusion_filters: ["GeneralLabelsFilterValue"],
# },
# image_properties: {
# max_dominant_colors: 1,
# },
# }
#
# @!attribute [rw] general_labels
# Contains the specified filters for GENERAL\_LABELS.
# @return [Types::GeneralLabelsSettings]
#
# @!attribute [rw] image_properties
# Contains the chosen number of maximum dominant colors in an image.
# @return [Types::DetectLabelsImagePropertiesSettings]
#
class DetectLabelsSettings < Struct.new(
:general_labels,
:image_properties)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DetectModerationLabelsRequest
# data as a hash:
#
# {
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# min_confidence: 1.0,
# human_loop_config: {
# human_loop_name: "HumanLoopName", # required
# flow_definition_arn: "FlowDefinitionArn", # required
# data_attributes: {
# content_classifiers: ["FreeOfPersonallyIdentifiableInformation"], # accepts FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent
# },
# },
# }
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes is not supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] min_confidence
# Specifies the minimum confidence level for the labels to return.
# Amazon Rekognition doesn't return any labels with a confidence
# level lower than this specified value.
#
# If you don't specify `MinConfidence`, the operation returns labels
# with confidence values greater than or equal to 50 percent.
# @return [Float]
#
# @!attribute [rw] human_loop_config
# Sets up the configuration for human evaluation, including the
# FlowDefinition the image will be sent to.
# @return [Types::HumanLoopConfig]
#
class DetectModerationLabelsRequest < Struct.new(
:image,
:min_confidence,
:human_loop_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] moderation_labels
# Array of detected Moderation labels and the time, in milliseconds
# from the start of the video, they were detected.
# @return [Array<Types::ModerationLabel>]
#
# @!attribute [rw] moderation_model_version
# Version number of the moderation detection model that was used to
# detect unsafe content.
# @return [String]
#
# @!attribute [rw] human_loop_activation_output
# Shows the results of the human in the loop evaluation.
# @return [Types::HumanLoopActivationOutput]
#
class DetectModerationLabelsResponse < Struct.new(
:moderation_labels,
:moderation_model_version,
:human_loop_activation_output)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DetectProtectiveEquipmentRequest
# data as a hash:
#
# {
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# summarization_attributes: {
# min_confidence: 1.0, # required
# required_equipment_types: ["FACE_COVER"], # required, accepts FACE_COVER, HAND_COVER, HEAD_COVER
# },
# }
#
# @!attribute [rw] image
# The image in which you want to detect PPE on detected persons. The
# image can be passed as image bytes or you can reference an image
# stored in an Amazon S3 bucket.
# @return [Types::Image]
#
# @!attribute [rw] summarization_attributes
# An array of PPE types that you want to summarize.
# @return [Types::ProtectiveEquipmentSummarizationAttributes]
#
class DetectProtectiveEquipmentRequest < Struct.new(
:image,
:summarization_attributes)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] protective_equipment_model_version
# The version number of the PPE detection model used to detect PPE in
# the image.
# @return [String]
#
# @!attribute [rw] persons
# An array of persons detected in the image (including persons not
# wearing PPE).
# @return [Array<Types::ProtectiveEquipmentPerson>]
#
# @!attribute [rw] summary
# Summary information for the types of PPE specified in the
# `SummarizationAttributes` input parameter.
# @return [Types::ProtectiveEquipmentSummary]
#
class DetectProtectiveEquipmentResponse < Struct.new(
:protective_equipment_model_version,
:persons,
:summary)
SENSITIVE = []
include Aws::Structure
end
# A set of optional parameters that you can use to set the criteria that
# the text must meet to be included in your response. `WordFilter` looks
# at a word’s height, width, and minimum confidence. `RegionOfInterest`
# lets you set a specific region of the image to look for text in.
#
# @note When making an API call, you may pass DetectTextFilters
# data as a hash:
#
# {
# word_filter: {
# min_confidence: 1.0,
# min_bounding_box_height: 1.0,
# min_bounding_box_width: 1.0,
# },
# regions_of_interest: [
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# },
# ],
# }
#
# @!attribute [rw] word_filter
# A set of parameters that allow you to filter out certain results
# from your returned results.
# @return [Types::DetectionFilter]
#
# @!attribute [rw] regions_of_interest
# A Filter focusing on a certain area of the image. Uses a
# `BoundingBox` object to set the region of the image.
# @return [Array<Types::RegionOfInterest>]
#
class DetectTextFilters < Struct.new(
:word_filter,
:regions_of_interest)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DetectTextRequest
# data as a hash:
#
# {
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# filters: {
# word_filter: {
# min_confidence: 1.0,
# min_bounding_box_height: 1.0,
# min_bounding_box_width: 1.0,
# },
# regions_of_interest: [
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# },
# ],
# },
# }
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an Amazon S3 object. If
# you use the AWS CLI to call Amazon Rekognition operations, you
# can't pass image bytes.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] filters
# Optional parameters that let you set the criteria that the text must
# meet to be included in your response.
# @return [Types::DetectTextFilters]
#
class DetectTextRequest < Struct.new(
:image,
:filters)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] text_detections
# An array of text that was detected in the input image.
# @return [Array<Types::TextDetection>]
#
# @!attribute [rw] text_model_version
# The model version used to detect text.
# @return [String]
#
class DetectTextResponse < Struct.new(
:text_detections,
:text_model_version)
SENSITIVE = []
include Aws::Structure
end
# A set of parameters that allow you to filter out certain results from
# your returned results.
#
# @note When making an API call, you may pass DetectionFilter
# data as a hash:
#
# {
# min_confidence: 1.0,
# min_bounding_box_height: 1.0,
# min_bounding_box_width: 1.0,
# }
#
# @!attribute [rw] min_confidence
# Sets the confidence of word detection. Words with detection
# confidence below this will be excluded from the result. Values
# should be between 0 and 100. The default MinConfidence is 80.
# @return [Float]
#
# @!attribute [rw] min_bounding_box_height
# Sets the minimum height of the word bounding box. Words with
# bounding box heights lesser than this value will be excluded from
# the result. Value is relative to the video frame height.
# @return [Float]
#
# @!attribute [rw] min_bounding_box_width
# Sets the minimum width of the word bounding box. Words with bounding
# boxes widths lesser than this value will be excluded from the
# result. Value is relative to the video frame width.
# @return [Float]
#
class DetectionFilter < Struct.new(
:min_confidence,
:min_bounding_box_height,
:min_bounding_box_width)
SENSITIVE = []
include Aws::Structure
end
# A training dataset or a test dataset used in a dataset distribution
# operation. For more information, see DistributeDatasetEntries.
#
# @note When making an API call, you may pass DistributeDataset
# data as a hash:
#
# {
# arn: "DatasetArn", # required
# }
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the dataset that you want to use.
# @return [String]
#
class DistributeDataset < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass DistributeDatasetEntriesRequest
# data as a hash:
#
# {
# datasets: [ # required
# {
# arn: "DatasetArn", # required
# },
# ],
# }
#
# @!attribute [rw] datasets
# The ARNS for the training dataset and test dataset that you want to
# use. The datasets must belong to the same project. The test dataset
# must be empty.
# @return [Array<Types::DistributeDataset>]
#
class DistributeDatasetEntriesRequest < Struct.new(
:datasets)
SENSITIVE = []
include Aws::Structure
end
class DistributeDatasetEntriesResponse < Aws::EmptyStructure; end
# A description of the dominant colors in an image.
#
# @!attribute [rw] red
# The Red RGB value for a dominant color.
# @return [Integer]
#
# @!attribute [rw] blue
# The Blue RGB value for a dominant color.
# @return [Integer]
#
# @!attribute [rw] green
# The Green RGB value for a dominant color.
# @return [Integer]
#
# @!attribute [rw] hex_code
# The Hex code equivalent of the RGB values for a dominant color.
# @return [String]
#
# @!attribute [rw] css_color
# The CSS color name of a dominant color.
# @return [String]
#
# @!attribute [rw] simplified_color
# One of 12 simplified color names applied to a dominant color.
# @return [String]
#
# @!attribute [rw] pixel_percent
# The percentage of image pixels that have a given dominant color.
# @return [Float]
#
class DominantColor < Struct.new(
:red,
:blue,
:green,
:hex_code,
:css_color,
:simplified_color,
:pixel_percent)
SENSITIVE = []
include Aws::Structure
end
# The emotions that appear to be expressed on the face, and the
# confidence level in the determination. The API is only making a
# determination of the physical appearance of a person's face. It is
# not a determination of the person’s internal emotional state and
# should not be used in such a way. For example, a person pretending to
# have a sad face might not be sad emotionally.
#
# @!attribute [rw] type
# Type of emotion detected.
# @return [String]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class Emotion < Struct.new(
:type,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Information about an item of Personal Protective Equipment (PPE)
# detected by DetectProtectiveEquipment. For more information, see
# DetectProtectiveEquipment.
#
# @!attribute [rw] bounding_box
# A bounding box surrounding the item of detected PPE.
# @return [Types::BoundingBox]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition has that the bounding box
# (`BoundingBox`) contains an item of PPE.
# @return [Float]
#
# @!attribute [rw] type
# The type of detected PPE.
# @return [String]
#
# @!attribute [rw] covers_body_part
# Information about the body part covered by the detected PPE.
# @return [Types::CoversBodyPart]
#
class EquipmentDetection < Struct.new(
:bounding_box,
:confidence,
:type,
:covers_body_part)
SENSITIVE = []
include Aws::Structure
end
# The evaluation results for the training of a model.
#
# @!attribute [rw] f1_score
# The F1 score for the evaluation of all labels. The F1 score metric
# evaluates the overall precision and recall performance of the model
# as a single value. A higher value indicates better precision and
# recall performance. A lower score indicates that precision, recall,
# or both are performing poorly.
# @return [Float]
#
# @!attribute [rw] summary
# The S3 bucket that contains the training summary.
# @return [Types::Summary]
#
class EvaluationResult < Struct.new(
:f1_score,
:summary)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the eyes on the face are open, and the
# confidence level in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the eyes on the face are open.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class EyeOpen < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the face is wearing eye glasses, and the
# confidence level in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the face is wearing eye glasses
# or not.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class Eyeglasses < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Describes the face properties such as the bounding box, face ID, image
# ID of the input image, and external image ID that you assigned.
#
# @!attribute [rw] face_id
# Unique identifier that Amazon Rekognition assigns to the face.
# @return [String]
#
# @!attribute [rw] bounding_box
# Bounding box of the face.
# @return [Types::BoundingBox]
#
# @!attribute [rw] image_id
# Unique identifier that Amazon Rekognition assigns to the input
# image.
# @return [String]
#
# @!attribute [rw] external_image_id
# Identifier that you assign to all the faces in the input image.
# @return [String]
#
# @!attribute [rw] confidence
# Confidence level that the bounding box contains a face (and not a
# different object such as a tree).
# @return [Float]
#
# @!attribute [rw] index_faces_model_version
# The version of the face detect and storage model that was used when
# indexing the face vector.
# @return [String]
#
class Face < Struct.new(
:face_id,
:bounding_box,
:image_id,
:external_image_id,
:confidence,
:index_faces_model_version)
SENSITIVE = []
include Aws::Structure
end
# Structure containing attributes of the face that the algorithm
# detected.
#
# A `FaceDetail` object contains either the default facial attributes or
# all facial attributes. The default attributes are `BoundingBox`,
# `Confidence`, `Landmarks`, `Pose`, and `Quality`.
#
# GetFaceDetection is the only Amazon Rekognition Video stored video
# operation that can return a `FaceDetail` object with all attributes.
# To specify which attributes to return, use the `FaceAttributes` input
# parameter for StartFaceDetection. The following Amazon Rekognition
# Video operations return only the default attributes. The corresponding
# Start operations don't have a `FaceAttributes` input parameter.
#
# * GetCelebrityRecognition
#
# * GetPersonTracking
#
# * GetFaceSearch
#
# The Amazon Rekognition Image DetectFaces and IndexFaces operations can
# return all facial attributes. To specify which attributes to return,
# use the `Attributes` input parameter for `DetectFaces`. For
# `IndexFaces`, use the `DetectAttributes` input parameter.
#
# @!attribute [rw] bounding_box
# Bounding box of the face. Default attribute.
# @return [Types::BoundingBox]
#
# @!attribute [rw] age_range
# The estimated age range, in years, for the face. Low represents the
# lowest estimated age and High represents the highest estimated age.
# @return [Types::AgeRange]
#
# @!attribute [rw] smile
# Indicates whether or not the face is smiling, and the confidence
# level in the determination.
# @return [Types::Smile]
#
# @!attribute [rw] eyeglasses
# Indicates whether or not the face is wearing eye glasses, and the
# confidence level in the determination.
# @return [Types::Eyeglasses]
#
# @!attribute [rw] sunglasses
# Indicates whether or not the face is wearing sunglasses, and the
# confidence level in the determination.
# @return [Types::Sunglasses]
#
# @!attribute [rw] gender
# The predicted gender of a detected face.
# @return [Types::Gender]
#
# @!attribute [rw] beard
# Indicates whether or not the face has a beard, and the confidence
# level in the determination.
# @return [Types::Beard]
#
# @!attribute [rw] mustache
# Indicates whether or not the face has a mustache, and the confidence
# level in the determination.
# @return [Types::Mustache]
#
# @!attribute [rw] eyes_open
# Indicates whether or not the eyes on the face are open, and the
# confidence level in the determination.
# @return [Types::EyeOpen]
#
# @!attribute [rw] mouth_open
# Indicates whether or not the mouth on the face is open, and the
# confidence level in the determination.
# @return [Types::MouthOpen]
#
# @!attribute [rw] emotions
# The emotions that appear to be expressed on the face, and the
# confidence level in the determination. The API is only making a
# determination of the physical appearance of a person's face. It is
# not a determination of the person’s internal emotional state and
# should not be used in such a way. For example, a person pretending
# to have a sad face might not be sad emotionally.
# @return [Array<Types::Emotion>]
#
# @!attribute [rw] landmarks
# Indicates the location of landmarks on the face. Default attribute.
# @return [Array<Types::Landmark>]
#
# @!attribute [rw] pose
# Indicates the pose of the face as determined by its pitch, roll, and
# yaw. Default attribute.
# @return [Types::Pose]
#
# @!attribute [rw] quality
# Identifies image brightness and sharpness. Default attribute.
# @return [Types::ImageQuality]
#
# @!attribute [rw] confidence
# Confidence level that the bounding box contains a face (and not a
# different object such as a tree). Default attribute.
# @return [Float]
#
class FaceDetail < Struct.new(
:bounding_box,
:age_range,
:smile,
:eyeglasses,
:sunglasses,
:gender,
:beard,
:mustache,
:eyes_open,
:mouth_open,
:emotions,
:landmarks,
:pose,
:quality,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Information about a face detected in a video analysis request and the
# time the face was detected in the video.
#
# @!attribute [rw] timestamp
# Time, in milliseconds from the start of the video, that the face was
# detected. Note that `Timestamp` is not guaranteed to be accurate to
# the individual frame where the face first appears.
# @return [Integer]
#
# @!attribute [rw] face
# The face properties for the detected face.
# @return [Types::FaceDetail]
#
class FaceDetection < Struct.new(
:timestamp,
:face)
SENSITIVE = []
include Aws::Structure
end
# Provides face metadata. In addition, it also provides the confidence
# in the match of this face with the input face.
#
# @!attribute [rw] similarity
# Confidence in the match of this face with the input face.
# @return [Float]
#
# @!attribute [rw] face
# Describes the face properties such as the bounding box, face ID,
# image ID of the source image, and external image ID that you
# assigned.
# @return [Types::Face]
#
class FaceMatch < Struct.new(
:similarity,
:face)
SENSITIVE = []
include Aws::Structure
end
# Object containing both the face metadata (stored in the backend
# database), and facial attributes that are detected but aren't stored
# in the database.
#
# @!attribute [rw] face
# Describes the face properties such as the bounding box, face ID,
# image ID of the input image, and external image ID that you
# assigned.
# @return [Types::Face]
#
# @!attribute [rw] face_detail
# Structure containing attributes of the face that the algorithm
# detected.
# @return [Types::FaceDetail]
#
class FaceRecord < Struct.new(
:face,
:face_detail)
SENSITIVE = []
include Aws::Structure
end
# Input face recognition parameters for an Amazon Rekognition stream
# processor. Includes the collection to use for face recognition and the
# face attributes to detect. Defining the settings is required in the
# request parameter for CreateStreamProcessor.
#
# @note When making an API call, you may pass FaceSearchSettings
# data as a hash:
#
# {
# collection_id: "CollectionId",
# face_match_threshold: 1.0,
# }
#
# @!attribute [rw] collection_id
# The ID of a collection that contains faces that you want to search
# for.
# @return [String]
#
# @!attribute [rw] face_match_threshold
# Minimum face match confidence score that must be met to return a
# result for a recognized face. The default is 80. 0 is the lowest
# confidence. 100 is the highest confidence. Values between 0 and 100
# are accepted, and values lower than 80 are set to 80.
# @return [Float]
#
class FaceSearchSettings < Struct.new(
:collection_id,
:face_match_threshold)
SENSITIVE = []
include Aws::Structure
end
# The predicted gender of a detected face.
#
# Amazon Rekognition makes gender binary (male/female) predictions based
# on the physical appearance of a face in a particular image. This kind
# of prediction is not designed to categorize a person’s gender
# identity, and you shouldn't use Amazon Rekognition to make such a
# determination. For example, a male actor wearing a long-haired wig and
# earrings for a role might be predicted as female.
#
# Using Amazon Rekognition to make gender binary predictions is best
# suited for use cases where aggregate gender distribution statistics
# need to be analyzed without identifying specific users. For example,
# the percentage of female users compared to male users on a social
# media platform.
#
# We don't recommend using gender binary predictions to make decisions
# that impact an individual's rights, privacy, or access to services.
#
# @!attribute [rw] value
# The predicted gender of the face.
# @return [String]
#
# @!attribute [rw] confidence
# Level of confidence in the prediction.
# @return [Float]
#
class Gender < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Contains filters for the object labels returned by DetectLabels.
# Filters can be inclusive, exclusive, or a combination of both and can
# be applied to individual l abels or entire label categories.
#
# @note When making an API call, you may pass GeneralLabelsSettings
# data as a hash:
#
# {
# label_inclusion_filters: ["GeneralLabelsFilterValue"],
# label_exclusion_filters: ["GeneralLabelsFilterValue"],
# label_category_inclusion_filters: ["GeneralLabelsFilterValue"],
# label_category_exclusion_filters: ["GeneralLabelsFilterValue"],
# }
#
# @!attribute [rw] label_inclusion_filters
# The labels that should be included in the return from DetectLabels.
# @return [Array<String>]
#
# @!attribute [rw] label_exclusion_filters
# The labels that should be excluded from the return from
# DetectLabels.
# @return [Array<String>]
#
# @!attribute [rw] label_category_inclusion_filters
# The label categories that should be included in the return from
# DetectLabels.
# @return [Array<String>]
#
# @!attribute [rw] label_category_exclusion_filters
# The label categories that should be excluded from the return from
# DetectLabels.
# @return [Array<String>]
#
class GeneralLabelsSettings < Struct.new(
:label_inclusion_filters,
:label_exclusion_filters,
:label_category_inclusion_filters,
:label_category_exclusion_filters)
SENSITIVE = []
include Aws::Structure
end
# Information about where an object (DetectCustomLabels) or text
# (DetectText) is located on an image.
#
# @!attribute [rw] bounding_box
# An axis-aligned coarse representation of the detected item's
# location on the image.
# @return [Types::BoundingBox]
#
# @!attribute [rw] polygon
# Within the bounding box, a fine-grained polygon around the detected
# item.
# @return [Array<Types::Point>]
#
class Geometry < Struct.new(
:bounding_box,
:polygon)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetCelebrityInfoRequest
# data as a hash:
#
# {
# id: "RekognitionUniqueId", # required
# }
#
# @!attribute [rw] id
# The ID for the celebrity. You get the celebrity ID from a call to
# the RecognizeCelebrities operation, which recognizes celebrities in
# an image.
# @return [String]
#
class GetCelebrityInfoRequest < Struct.new(
:id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] urls
# An array of URLs pointing to additional celebrity information.
# @return [Array<String>]
#
# @!attribute [rw] name
# The name of the celebrity.
# @return [String]
#
# @!attribute [rw] known_gender
# Retrieves the known gender for the celebrity.
# @return [Types::KnownGender]
#
class GetCelebrityInfoResponse < Struct.new(
:urls,
:name,
:known_gender)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetCelebrityRecognitionRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# sort_by: "ID", # accepts ID, TIMESTAMP
# }
#
# @!attribute [rw] job_id
# Job identifier for the required celebrity recognition analysis. You
# can get the job identifer from a call to
# `StartCelebrityRecognition`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000. If you specify a value greater than
# 1000, a maximum of 1000 results is returned. The default value is
# 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# recognized celebrities to retrieve), Amazon Rekognition Video
# returns a pagination token in the response. You can use this
# pagination token to retrieve the next set of celebrities.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort to use for celebrities returned in `Celebrities` field. Specify
# `ID` to sort by the celebrity identifier, specify `TIMESTAMP` to
# sort by the time the celebrity was recognized.
# @return [String]
#
class GetCelebrityRecognitionRequest < Struct.new(
:job_id,
:max_results,
:next_token,
:sort_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# The current status of the celebrity recognition job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition Video analyzed.
# `Videometadata` is returned in every page of paginated responses
# from a Amazon Rekognition Video operation.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of celebrities.
# @return [String]
#
# @!attribute [rw] celebrities
# Array of celebrities recognized in the video.
# @return [Array<Types::CelebrityRecognition>]
#
class GetCelebrityRecognitionResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:next_token,
:celebrities)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetContentModerationRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# sort_by: "NAME", # accepts NAME, TIMESTAMP
# }
#
# @!attribute [rw] job_id
# The identifier for the inappropriate, unwanted, or offensive content
# moderation job. Use `JobId` to identify the job in a subsequent call
# to `GetContentModeration`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000. If you specify a value greater than
# 1000, a maximum of 1000 results is returned. The default value is
# 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more data
# to retrieve), Amazon Rekognition returns a pagination token in the
# response. You can use this pagination token to retrieve the next set
# of content moderation labels.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort to use for elements in the `ModerationLabelDetections` array.
# Use `TIMESTAMP` to sort array elements by the time labels are
# detected. Use `NAME` to alphabetically group elements for a label
# together. Within each label group, the array element are sorted by
# detection confidence. The default sort is by `TIMESTAMP`.
# @return [String]
#
class GetContentModerationRequest < Struct.new(
:job_id,
:max_results,
:next_token,
:sort_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# The current status of the content moderation analysis job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition analyzed.
# `Videometadata` is returned in every page of paginated responses
# from `GetContentModeration`.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] moderation_labels
# The detected inappropriate, unwanted, or offensive content
# moderation labels and the time(s) they were detected.
# @return [Array<Types::ContentModerationDetection>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of content moderation labels.
# @return [String]
#
# @!attribute [rw] moderation_model_version
# Version number of the moderation detection model that was used to
# detect inappropriate, unwanted, or offensive content.
# @return [String]
#
class GetContentModerationResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:moderation_labels,
:next_token,
:moderation_model_version)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetFaceDetectionRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# }
#
# @!attribute [rw] job_id
# Unique identifier for the face detection job. The `JobId` is
# returned from `StartFaceDetection`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000. If you specify a value greater than
# 1000, a maximum of 1000 results is returned. The default value is
# 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there are more
# faces to retrieve), Amazon Rekognition Video returns a pagination
# token in the response. You can use this pagination token to retrieve
# the next set of faces.
# @return [String]
#
class GetFaceDetectionRequest < Struct.new(
:job_id,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# The current status of the face detection job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition Video analyzed.
# `Videometadata` is returned in every page of paginated responses
# from a Amazon Rekognition video operation.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition returns this token
# that you can use in the subsequent request to retrieve the next set
# of faces.
# @return [String]
#
# @!attribute [rw] faces
# An array of faces detected in the video. Each element contains a
# detected face's details and the time, in milliseconds from the
# start of the video, the face was detected.
# @return [Array<Types::FaceDetection>]
#
class GetFaceDetectionResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:next_token,
:faces)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetFaceSearchRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# sort_by: "INDEX", # accepts INDEX, TIMESTAMP
# }
#
# @!attribute [rw] job_id
# The job identifer for the search request. You get the job identifier
# from an initial call to `StartFaceSearch`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000. If you specify a value greater than
# 1000, a maximum of 1000 results is returned. The default value is
# 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# search results to retrieve), Amazon Rekognition Video returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of search results.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort to use for grouping faces in the response. Use `TIMESTAMP` to
# group faces by the time that they are recognized. Use `INDEX` to
# sort by recognized faces.
# @return [String]
#
class GetFaceSearchRequest < Struct.new(
:job_id,
:max_results,
:next_token,
:sort_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# The current status of the face search job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of search results.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition analyzed.
# `Videometadata` is returned in every page of paginated responses
# from a Amazon Rekognition Video operation.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] persons
# An array of persons, PersonMatch, in the video whose face(s) match
# the face(s) in an Amazon Rekognition collection. It also includes
# time information for when persons are matched in the video. You
# specify the input collection in an initial call to
# `StartFaceSearch`. Each `Persons` element includes a time the person
# was matched, face match details (`FaceMatches`) for matching faces
# in the collection, and person information (`Person`) for the matched
# person.
# @return [Array<Types::PersonMatch>]
#
class GetFaceSearchResponse < Struct.new(
:job_status,
:status_message,
:next_token,
:video_metadata,
:persons)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetLabelDetectionRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# sort_by: "NAME", # accepts NAME, TIMESTAMP
# }
#
# @!attribute [rw] job_id
# Job identifier for the label detection operation for which you want
# results returned. You get the job identifer from an initial call to
# `StartlabelDetection`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000. If you specify a value greater than
# 1000, a maximum of 1000 results is returned. The default value is
# 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there are more
# labels to retrieve), Amazon Rekognition Video returns a pagination
# token in the response. You can use this pagination token to retrieve
# the next set of labels.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort to use for elements in the `Labels` array. Use `TIMESTAMP` to
# sort array elements by the time labels are detected. Use `NAME` to
# alphabetically group elements for a label together. Within each
# label group, the array element are sorted by detection confidence.
# The default sort is by `TIMESTAMP`.
# @return [String]
#
class GetLabelDetectionRequest < Struct.new(
:job_id,
:max_results,
:next_token,
:sort_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# The current status of the label detection job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition Video analyzed.
# `Videometadata` is returned in every page of paginated responses
# from a Amazon Rekognition video operation.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of labels.
# @return [String]
#
# @!attribute [rw] labels
# An array of labels detected in the video. Each element contains the
# detected label and the time, in milliseconds from the start of the
# video, that the label was detected.
# @return [Array<Types::LabelDetection>]
#
# @!attribute [rw] label_model_version
# Version number of the label detection model that was used to detect
# labels.
# @return [String]
#
class GetLabelDetectionResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:next_token,
:labels,
:label_model_version)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetPersonTrackingRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# sort_by: "INDEX", # accepts INDEX, TIMESTAMP
# }
#
# @!attribute [rw] job_id
# The identifier for a job that tracks persons in a video. You get the
# `JobId` from a call to `StartPersonTracking`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000. If you specify a value greater than
# 1000, a maximum of 1000 results is returned. The default value is
# 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there are more
# persons to retrieve), Amazon Rekognition Video returns a pagination
# token in the response. You can use this pagination token to retrieve
# the next set of persons.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort to use for elements in the `Persons` array. Use `TIMESTAMP` to
# sort array elements by the time persons are detected. Use `INDEX` to
# sort by the tracked persons. If you sort by `INDEX`, the array
# elements for each person are sorted by detection confidence. The
# default sort is by `TIMESTAMP`.
# @return [String]
#
class GetPersonTrackingRequest < Struct.new(
:job_id,
:max_results,
:next_token,
:sort_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# The current status of the person tracking job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition Video analyzed.
# `Videometadata` is returned in every page of paginated responses
# from a Amazon Rekognition Video operation.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of persons.
# @return [String]
#
# @!attribute [rw] persons
# An array of the persons detected in the video and the time(s) their
# path was tracked throughout the video. An array element will exist
# for each time a person's path is tracked.
# @return [Array<Types::PersonDetection>]
#
class GetPersonTrackingResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:next_token,
:persons)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetSegmentDetectionRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# }
#
# @!attribute [rw] job_id
# Job identifier for the text detection operation for which you want
# results returned. You get the job identifer from an initial call to
# `StartSegmentDetection`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of text.
# @return [String]
#
class GetSegmentDetectionRequest < Struct.new(
:job_id,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# Current status of the segment detection job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Currently, Amazon Rekognition Video returns a single object in the
# `VideoMetadata` array. The object contains information about the
# video stream in the input file that Amazon Rekognition Video chose
# to analyze. The `VideoMetadata` object includes the video codec,
# video format and other information. Video metadata is returned in
# each page of information returned by `GetSegmentDetection`.
# @return [Array<Types::VideoMetadata>]
#
# @!attribute [rw] audio_metadata
# An array of objects. There can be multiple audio streams. Each
# `AudioMetadata` object contains metadata for a single audio stream.
# Audio information in an `AudioMetadata` objects includes the audio
# codec, the number of audio channels, the duration of the audio
# stream, and the sample rate. Audio metadata is returned in each page
# of information returned by `GetSegmentDetection`.
# @return [Array<Types::AudioMetadata>]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there are more
# labels to retrieve), Amazon Rekognition Video returns a pagination
# token in the response. You can use this pagination token to retrieve
# the next set of text.
# @return [String]
#
# @!attribute [rw] segments
# An array of segments detected in a video. The array is sorted by the
# segment types (TECHNICAL\_CUE or SHOT) specified in the
# `SegmentTypes` input parameter of `StartSegmentDetection`. Within
# each segment type the array is sorted by timestamp values.
# @return [Array<Types::SegmentDetection>]
#
# @!attribute [rw] selected_segment_types
# An array containing the segment types requested in the call to
# `StartSegmentDetection`.
# @return [Array<Types::SegmentTypeInfo>]
#
class GetSegmentDetectionResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:audio_metadata,
:next_token,
:segments,
:selected_segment_types)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass GetTextDetectionRequest
# data as a hash:
#
# {
# job_id: "JobId", # required
# max_results: 1,
# next_token: "PaginationToken",
# }
#
# @!attribute [rw] job_id
# Job identifier for the text detection operation for which you want
# results returned. You get the job identifer from an initial call to
# `StartTextDetection`.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to return per paginated call. The largest
# value you can specify is 1000.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there are more
# labels to retrieve), Amazon Rekognition Video returns a pagination
# token in the response. You can use this pagination token to retrieve
# the next set of text.
# @return [String]
#
class GetTextDetectionRequest < Struct.new(
:job_id,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_status
# Current status of the text detection job.
# @return [String]
#
# @!attribute [rw] status_message
# If the job fails, `StatusMessage` provides a descriptive error
# message.
# @return [String]
#
# @!attribute [rw] video_metadata
# Information about a video that Amazon Rekognition analyzed.
# `Videometadata` is returned in every page of paginated responses
# from a Amazon Rekognition video operation.
# @return [Types::VideoMetadata]
#
# @!attribute [rw] text_detections
# An array of text detected in the video. Each element contains the
# detected text, the time in milliseconds from the start of the video
# that the text was detected, and where it was detected on the screen.
# @return [Array<Types::TextDetectionResult>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of text.
# @return [String]
#
# @!attribute [rw] text_model_version
# Version number of the text detection model that was used to detect
# text.
# @return [String]
#
class GetTextDetectionResponse < Struct.new(
:job_status,
:status_message,
:video_metadata,
:text_detections,
:next_token,
:text_model_version)
SENSITIVE = []
include Aws::Structure
end
# The S3 bucket that contains an Amazon Sagemaker Ground Truth format
# manifest file.
#
# @note When making an API call, you may pass GroundTruthManifest
# data as a hash:
#
# {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# }
#
# @!attribute [rw] s3_object
# Provides the S3 bucket name and object name.
#
# The region for the S3 bucket containing the S3 object must match the
# region you use for Amazon Rekognition operations.
#
# For Amazon Rekognition to process an S3 object, the user must have
# permission to access the S3 object. For more information, see How
# Amazon Rekognition works with IAM in the Amazon Rekognition
# Developer Guide.
# @return [Types::S3Object]
#
class GroundTruthManifest < Struct.new(
:s3_object)
SENSITIVE = []
include Aws::Structure
end
# Shows the results of the human in the loop evaluation. If there is no
# HumanLoopArn, the input did not trigger human review.
#
# @!attribute [rw] human_loop_arn
# The Amazon Resource Name (ARN) of the HumanLoop created.
# @return [String]
#
# @!attribute [rw] human_loop_activation_reasons
# Shows if and why human review was needed.
# @return [Array<String>]
#
# @!attribute [rw] human_loop_activation_conditions_evaluation_results
# Shows the result of condition evaluations, including those
# conditions which activated a human review.
# @return [String]
#
class HumanLoopActivationOutput < Struct.new(
:human_loop_arn,
:human_loop_activation_reasons,
:human_loop_activation_conditions_evaluation_results)
SENSITIVE = []
include Aws::Structure
end
# Sets up the flow definition the image will be sent to if one of the
# conditions is met. You can also set certain attributes of the image
# before review.
#
# @note When making an API call, you may pass HumanLoopConfig
# data as a hash:
#
# {
# human_loop_name: "HumanLoopName", # required
# flow_definition_arn: "FlowDefinitionArn", # required
# data_attributes: {
# content_classifiers: ["FreeOfPersonallyIdentifiableInformation"], # accepts FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent
# },
# }
#
# @!attribute [rw] human_loop_name
# The name of the human review used for this image. This should be
# kept unique within a region.
# @return [String]
#
# @!attribute [rw] flow_definition_arn
# The Amazon Resource Name (ARN) of the flow definition. You can
# create a flow definition by using the Amazon Sagemaker
# [CreateFlowDefinition][1] Operation.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateFlowDefinition.html
# @return [String]
#
# @!attribute [rw] data_attributes
# Sets attributes of the input data.
# @return [Types::HumanLoopDataAttributes]
#
class HumanLoopConfig < Struct.new(
:human_loop_name,
:flow_definition_arn,
:data_attributes)
SENSITIVE = []
include Aws::Structure
end
# Allows you to set attributes of the image. Currently, you can declare
# an image as free of personally identifiable information.
#
# @note When making an API call, you may pass HumanLoopDataAttributes
# data as a hash:
#
# {
# content_classifiers: ["FreeOfPersonallyIdentifiableInformation"], # accepts FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent
# }
#
# @!attribute [rw] content_classifiers
# Sets whether the input image is free of personally identifiable
# information.
# @return [Array<String>]
#
class HumanLoopDataAttributes < Struct.new(
:content_classifiers)
SENSITIVE = []
include Aws::Structure
end
# The number of in-progress human reviews you have has exceeded the
# number allowed.
#
# @!attribute [rw] resource_type
# The resource type.
# @return [String]
#
# @!attribute [rw] quota_code
# The quota code.
# @return [String]
#
# @!attribute [rw] service_code
# The service code.
# @return [String]
#
class HumanLoopQuotaExceededException < Struct.new(
:resource_type,
:quota_code,
:service_code)
SENSITIVE = []
include Aws::Structure
end
# A `ClientRequestToken` input parameter was reused with an operation,
# but at least one of the other input parameters is different from the
# previous call to the operation.
#
class IdempotentParameterMismatchException < Aws::EmptyStructure; end
# Provides the input image either as bytes or an S3 object.
#
# You pass image bytes to an Amazon Rekognition API operation by using
# the `Bytes` property. For example, you would use the `Bytes` property
# to pass an image loaded from a local file system. Image bytes passed
# by using the `Bytes` property must be base64-encoded. Your code may
# not need to encode image bytes if you are using an AWS SDK to call
# Amazon Rekognition API operations.
#
# For more information, see Analyzing an Image Loaded from a Local File
# System in the Amazon Rekognition Developer Guide.
#
# You pass images stored in an S3 bucket to an Amazon Rekognition API
# operation by using the `S3Object` property. Images stored in an S3
# bucket do not need to be base64-encoded.
#
# The region for the S3 bucket containing the S3 object must match the
# region you use for Amazon Rekognition operations.
#
# If you use the AWS CLI to call Amazon Rekognition operations, passing
# image bytes using the Bytes property is not supported. You must first
# upload the image to an Amazon S3 bucket and then call the operation
# using the S3Object property.
#
# For Amazon Rekognition to process an S3 object, the user must have
# permission to access the S3 object. For more information, see How
# Amazon Rekognition works with IAM in the Amazon Rekognition Developer
# Guide.
#
# @note When making an API call, you may pass Image
# data as a hash:
#
# {
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# }
#
# @!attribute [rw] bytes
# Blob of image bytes up to 5 MBs.
# @return [String]
#
# @!attribute [rw] s3_object
# Identifies an S3 object as the image source.
# @return [Types::S3Object]
#
class Image < Struct.new(
:bytes,
:s3_object)
SENSITIVE = []
include Aws::Structure
end
# Identifies face image brightness and sharpness.
#
# @!attribute [rw] brightness
# Value representing brightness of the face. The service returns a
# value between 0 and 100 (inclusive). A higher value indicates a
# brighter face image.
# @return [Float]
#
# @!attribute [rw] sharpness
# Value representing sharpness of the face. The service returns a
# value between 0 and 100 (inclusive). A higher value indicates a
# sharper face image.
# @return [Float]
#
class ImageQuality < Struct.new(
:brightness,
:sharpness)
SENSITIVE = []
include Aws::Structure
end
# The input image size exceeds the allowed limit. If you are calling
# DetectProtectiveEquipment, the image size or resolution exceeds the
# allowed limit. For more information, see Guidelines and quotas in
# Amazon Rekognition in the Amazon Rekognition Developer Guide.
#
class ImageTooLargeException < Aws::EmptyStructure; end
# @note When making an API call, you may pass IndexFacesRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# external_image_id: "ExternalImageId",
# detection_attributes: ["DEFAULT"], # accepts DEFAULT, ALL
# max_faces: 1,
# quality_filter: "NONE", # accepts NONE, AUTO, LOW, MEDIUM, HIGH
# }
#
# @!attribute [rw] collection_id
# The ID of an existing collection to which you want to add the faces
# that are detected in the input images.
# @return [String]
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes isn't supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] external_image_id
# The ID you want to assign to all the faces detected in the image.
# @return [String]
#
# @!attribute [rw] detection_attributes
# An array of facial attributes that you want to be returned. This can
# be the default list of attributes or all attributes. If you don't
# specify a value for `Attributes` or if you specify `["DEFAULT"]`,
# the API returns the following subset of facial attributes:
# `BoundingBox`, `Confidence`, `Pose`, `Quality`, and `Landmarks`. If
# you provide `["ALL"]`, all facial attributes are returned, but the
# operation takes longer to complete.
#
# If you provide both, `["ALL", "DEFAULT"]`, the service uses a
# logical AND operator to determine which attributes to return (in
# this case, all attributes).
# @return [Array<String>]
#
# @!attribute [rw] max_faces
# The maximum number of faces to index. The value of `MaxFaces` must
# be greater than or equal to 1. `IndexFaces` returns no more than 100
# detected faces in an image, even if you specify a larger value for
# `MaxFaces`.
#
# If `IndexFaces` detects more faces than the value of `MaxFaces`, the
# faces with the lowest quality are filtered out first. If there are
# still more faces than the value of `MaxFaces`, the faces with the
# smallest bounding boxes are filtered out (up to the number that's
# needed to satisfy the value of `MaxFaces`). Information about the
# unindexed faces is available in the `UnindexedFaces` array.
#
# The faces that are returned by `IndexFaces` are sorted by the
# largest face bounding box size to the smallest size, in descending
# order.
#
# `MaxFaces` can be used with a collection associated with any version
# of the face model.
# @return [Integer]
#
# @!attribute [rw] quality_filter
# A filter that specifies a quality bar for how much filtering is done
# to identify faces. Filtered faces aren't indexed. If you specify
# `AUTO`, Amazon Rekognition chooses the quality bar. If you specify
# `LOW`, `MEDIUM`, or `HIGH`, filtering removes all faces that don’t
# meet the chosen quality bar. The default value is `AUTO`. The
# quality bar is based on a variety of common use cases. Low-quality
# detections can occur for a number of reasons. Some examples are an
# object that's misidentified as a face, a face that's too blurry,
# or a face with a pose that's too extreme to use. If you specify
# `NONE`, no filtering is performed.
#
# To use quality filtering, the collection you are using must be
# associated with version 3 of the face model or higher.
# @return [String]
#
class IndexFacesRequest < Struct.new(
:collection_id,
:image,
:external_image_id,
:detection_attributes,
:max_faces,
:quality_filter)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] face_records
# An array of faces detected and added to the collection. For more
# information, see Searching Faces in a Collection in the Amazon
# Rekognition Developer Guide.
# @return [Array<Types::FaceRecord>]
#
# @!attribute [rw] orientation_correction
# If your collection is associated with a face detection model that's
# later than version 3.0, the value of `OrientationCorrection` is
# always null and no orientation information is returned.
#
# If your collection is associated with a face detection model that's
# version 3.0 or earlier, the following applies:
#
# * If the input image is in .jpeg format, it might contain
# exchangeable image file format (Exif) metadata that includes the
# image's orientation. Amazon Rekognition uses this orientation
# information to perform image correction - the bounding box
# coordinates are translated to represent object locations after the
# orientation information in the Exif metadata is used to correct
# the image orientation. Images in .png format don't contain Exif
# metadata. The value of `OrientationCorrection` is null.
#
# * If the image doesn't contain orientation information in its Exif
# metadata, Amazon Rekognition returns an estimated orientation
# (ROTATE\_0, ROTATE\_90, ROTATE\_180, ROTATE\_270). Amazon
# Rekognition doesn’t perform image correction for images. The
# bounding box coordinates aren't translated and represent the
# object locations before the image is rotated.
#
# Bounding box information is returned in the `FaceRecords` array. You
# can get the version of the face detection model by calling
# DescribeCollection.
# @return [String]
#
# @!attribute [rw] face_model_version
# The version number of the face detection model that's associated
# with the input collection (`CollectionId`).
# @return [String]
#
# @!attribute [rw] unindexed_faces
# An array of faces that were detected in the image but weren't
# indexed. They weren't indexed because the quality filter identified
# them as low quality, or the `MaxFaces` request parameter filtered
# them out. To use the quality filter, you specify the `QualityFilter`
# request parameter.
# @return [Array<Types::UnindexedFace>]
#
class IndexFacesResponse < Struct.new(
:face_records,
:orientation_correction,
:face_model_version,
:unindexed_faces)
SENSITIVE = []
include Aws::Structure
end
# An instance of a label returned by Amazon Rekognition Image
# (DetectLabels) or by Amazon Rekognition Video (GetLabelDetection).
#
# @!attribute [rw] bounding_box
# The position of the label instance on the image.
# @return [Types::BoundingBox]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition has in the accuracy of the
# bounding box.
# @return [Float]
#
# @!attribute [rw] dominant_colors
# The dominant colors found in an individual instance of a label.
# @return [Array<Types::DominantColor>]
#
class Instance < Struct.new(
:bounding_box,
:confidence,
:dominant_colors)
SENSITIVE = []
include Aws::Structure
end
# Amazon Rekognition experienced a service issue. Try your call again.
#
class InternalServerError < Aws::EmptyStructure; end
# The provided image format is not supported.
#
class InvalidImageFormatException < Aws::EmptyStructure; end
# Pagination token in the request is not valid.
#
class InvalidPaginationTokenException < Aws::EmptyStructure; end
# Input parameter violated a constraint. Validate your parameter before
# calling the API operation again.
#
class InvalidParameterException < Aws::EmptyStructure; end
# The supplied revision id for the project policy is invalid.
#
class InvalidPolicyRevisionIdException < Aws::EmptyStructure; end
# Amazon Rekognition is unable to access the S3 object specified in the
# request.
#
class InvalidS3ObjectException < Aws::EmptyStructure; end
# The Kinesis data stream Amazon Rekognition to which the analysis
# results of a Amazon Rekognition stream processor are streamed. For
# more information, see CreateStreamProcessor in the Amazon Rekognition
# Developer Guide.
#
# @note When making an API call, you may pass KinesisDataStream
# data as a hash:
#
# {
# arn: "KinesisDataArn",
# }
#
# @!attribute [rw] arn
# ARN of the output Amazon Kinesis Data Streams stream.
# @return [String]
#
class KinesisDataStream < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Kinesis video stream stream that provides the source streaming video
# for a Amazon Rekognition Video stream processor. For more information,
# see CreateStreamProcessor in the Amazon Rekognition Developer Guide.
#
# @note When making an API call, you may pass KinesisVideoStream
# data as a hash:
#
# {
# arn: "KinesisVideoArn",
# }
#
# @!attribute [rw] arn
# ARN of the Kinesis video stream stream that streams the source
# video.
# @return [String]
#
class KinesisVideoStream < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Specifies the starting point in a Kinesis stream to start processing.
# You can use the producer timestamp or the fragment number. One of
# either producer timestamp or fragment number is required. If you use
# the producer timestamp, you must put the time in milliseconds. For
# more information about fragment numbers, see [Fragment][1].
#
#
#
# [1]: https://docs.aws.amazon.com/kinesisvideostreams/latest/dg/API_reader_Fragment.html
#
# @note When making an API call, you may pass KinesisVideoStreamStartSelector
# data as a hash:
#
# {
# producer_timestamp: 1,
# fragment_number: "KinesisVideoStreamFragmentNumber",
# }
#
# @!attribute [rw] producer_timestamp
# The timestamp from the producer corresponding to the fragment, in
# milliseconds, expressed in unix time format.
# @return [Integer]
#
# @!attribute [rw] fragment_number
# The unique identifier of the fragment. This value monotonically
# increases based on the ingestion order.
# @return [String]
#
class KinesisVideoStreamStartSelector < Struct.new(
:producer_timestamp,
:fragment_number)
SENSITIVE = []
include Aws::Structure
end
# The known gender identity for the celebrity that matches the provided
# ID. The known gender identity can be Male, Female, Nonbinary, or
# Unlisted.
#
# @!attribute [rw] type
# A string value of the KnownGender info about the Celebrity.
# @return [String]
#
class KnownGender < Struct.new(
:type)
SENSITIVE = []
include Aws::Structure
end
# Structure containing details about the detected label, including the
# name, detected instances, parent labels, and level of confidence.
#
# @!attribute [rw] name
# The name (label) of the object or scene.
# @return [String]
#
# @!attribute [rw] confidence
# Level of confidence.
# @return [Float]
#
# @!attribute [rw] instances
# If `Label` represents an object, `Instances` contains the bounding
# boxes for each instance of the detected object. Bounding boxes are
# returned for common object labels such as people, cars, furniture,
# apparel or pets.
# @return [Array<Types::Instance>]
#
# @!attribute [rw] parents
# The parent labels for a label. The response includes all ancestor
# labels.
# @return [Array<Types::Parent>]
#
# @!attribute [rw] aliases
# A list of potential aliases for a given label.
# @return [Array<Types::LabelAlias>]
#
# @!attribute [rw] categories
# A list of the categories associated with a given label.
# @return [Array<Types::LabelCategory>]
#
class Label < Struct.new(
:name,
:confidence,
:instances,
:parents,
:aliases,
:categories)
SENSITIVE = []
include Aws::Structure
end
# A potential alias of for a given label.
#
# @!attribute [rw] name
# The name of an alias for a given label.
# @return [String]
#
class LabelAlias < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# The category that applies to a given label.
#
# @!attribute [rw] name
# The name of a category that applies to a given label.
# @return [String]
#
class LabelCategory < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# Information about a label detected in a video analysis request and the
# time the label was detected in the video.
#
# @!attribute [rw] timestamp
# Time, in milliseconds from the start of the video, that the label
# was detected. Note that `Timestamp` is not guaranteed to be accurate
# to the individual frame where the label first appears.
# @return [Integer]
#
# @!attribute [rw] label
# Details about the detected label.
# @return [Types::Label]
#
class LabelDetection < Struct.new(
:timestamp,
:label)
SENSITIVE = []
include Aws::Structure
end
# Indicates the location of the landmark on the face.
#
# @!attribute [rw] type
# Type of landmark.
# @return [String]
#
# @!attribute [rw] x
# The x-coordinate of the landmark expressed as a ratio of the width
# of the image. The x-coordinate is measured from the left-side of the
# image. For example, if the image is 700 pixels wide and the
# x-coordinate of the landmark is at 350 pixels, this value is 0.5.
# @return [Float]
#
# @!attribute [rw] y
# The y-coordinate of the landmark expressed as a ratio of the height
# of the image. The y-coordinate is measured from the top of the
# image. For example, if the image height is 200 pixels and the
# y-coordinate of the landmark is at 50 pixels, this value is 0.25.
# @return [Float]
#
class Landmark < Struct.new(
:type,
:x,
:y)
SENSITIVE = []
include Aws::Structure
end
# An Amazon Rekognition service limit was exceeded. For example, if you
# start too many Amazon Rekognition Video jobs concurrently, calls to
# start operations (`StartLabelDetection`, for example) will raise a
# `LimitExceededException` exception (HTTP status code: 400) until the
# number of concurrently running jobs is below the Amazon Rekognition
# service limit.
#
class LimitExceededException < Aws::EmptyStructure; end
# @note When making an API call, you may pass ListCollectionsRequest
# data as a hash:
#
# {
# next_token: "PaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] next_token
# Pagination token from the previous response.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of collection IDs to return.
# @return [Integer]
#
class ListCollectionsRequest < Struct.new(
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] collection_ids
# An array of collection IDs.
# @return [Array<String>]
#
# @!attribute [rw] next_token
# If the result is truncated, the response provides a `NextToken` that
# you can use in the subsequent request to fetch the next set of
# collection IDs.
# @return [String]
#
# @!attribute [rw] face_model_versions
# Version numbers of the face detection models associated with the
# collections in the array `CollectionIds`. For example, the value of
# `FaceModelVersions[2]` is the version number for the face detection
# model used by the collection in `CollectionId[2]`.
# @return [Array<String>]
#
class ListCollectionsResponse < Struct.new(
:collection_ids,
:next_token,
:face_model_versions)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass ListDatasetEntriesRequest
# data as a hash:
#
# {
# dataset_arn: "DatasetArn", # required
# contains_labels: ["DatasetLabel"],
# labeled: false,
# source_ref_contains: "QueryString",
# has_errors: false,
# next_token: "ExtendedPaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] dataset_arn
# The Amazon Resource Name (ARN) for the dataset that you want to use.
# @return [String]
#
# @!attribute [rw] contains_labels
# Specifies a label filter for the response. The response includes an
# entry only if one or more of the labels in `ContainsLabels` exist in
# the entry.
# @return [Array<String>]
#
# @!attribute [rw] labeled
# Specify `true` to get only the JSON Lines where the image is
# labeled. Specify `false` to get only the JSON Lines where the image
# isn't labeled. If you don't specify `Labeled`,
# `ListDatasetEntries` returns JSON Lines for labeled and unlabeled
# images.
# @return [Boolean]
#
# @!attribute [rw] source_ref_contains
# If specified, `ListDatasetEntries` only returns JSON Lines where the
# value of `SourceRefContains` is part of the `source-ref` field. The
# `source-ref` field contains the Amazon S3 location of the image. You
# can use `SouceRefContains` for tasks such as getting the JSON Line
# for a single image, or gettting JSON Lines for all images within a
# specific folder.
# @return [String]
#
# @!attribute [rw] has_errors
# Specifies an error filter for the response. Specify `True` to only
# include entries that have errors.
# @return [Boolean]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return per paginated call. The
# largest value you can specify is 100. If you specify a value greater
# than 100, a ValidationException error occurs. The default value is
# 100.
# @return [Integer]
#
class ListDatasetEntriesRequest < Struct.new(
:dataset_arn,
:contains_labels,
:labeled,
:source_ref_contains,
:has_errors,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] dataset_entries
# A list of entries (images) in the dataset.
# @return [Array<String>]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
class ListDatasetEntriesResponse < Struct.new(
:dataset_entries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass ListDatasetLabelsRequest
# data as a hash:
#
# {
# dataset_arn: "DatasetArn", # required
# next_token: "ExtendedPaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] dataset_arn
# The Amazon Resource Name (ARN) of the dataset that you want to use.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return per paginated call. The
# largest value you can specify is 100. If you specify a value greater
# than 100, a ValidationException error occurs. The default value is
# 100.
# @return [Integer]
#
class ListDatasetLabelsRequest < Struct.new(
:dataset_arn,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] dataset_label_descriptions
# A list of the labels in the dataset.
# @return [Array<Types::DatasetLabelDescription>]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
class ListDatasetLabelsResponse < Struct.new(
:dataset_label_descriptions,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass ListFacesRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# next_token: "PaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] collection_id
# ID of the collection from which to list the faces.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more data
# to retrieve), Amazon Rekognition returns a pagination token in the
# response. You can use this pagination token to retrieve the next set
# of faces.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of faces to return.
# @return [Integer]
#
class ListFacesRequest < Struct.new(
:collection_id,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] faces
# An array of `Face` objects.
# @return [Array<Types::Face>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition returns this token
# that you can use in the subsequent request to retrieve the next set
# of faces.
# @return [String]
#
# @!attribute [rw] face_model_version
# Version number of the face detection model associated with the input
# collection (`CollectionId`).
# @return [String]
#
class ListFacesResponse < Struct.new(
:faces,
:next_token,
:face_model_version)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass ListProjectPoliciesRequest
# data as a hash:
#
# {
# project_arn: "ProjectArn", # required
# next_token: "ExtendedPaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] project_arn
# The ARN of the project for which you want to list the project
# policies.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there is more
# results to retrieve), Amazon Rekognition Custom Labels returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return per paginated call. The
# largest value you can specify is 5. If you specify a value greater
# than 5, a ValidationException error occurs. The default value is 5.
# @return [Integer]
#
class ListProjectPoliciesRequest < Struct.new(
:project_arn,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_policies
# A list of project policies attached to the project.
# @return [Array<Types::ProjectPolicy>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition returns this token
# that you can use in the subsequent request to retrieve the next set
# of project policies.
# @return [String]
#
class ListProjectPoliciesResponse < Struct.new(
:project_policies,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass ListStreamProcessorsRequest
# data as a hash:
#
# {
# next_token: "PaginationToken",
# max_results: 1,
# }
#
# @!attribute [rw] next_token
# If the previous response was incomplete (because there are more
# stream processors to retrieve), Amazon Rekognition Video returns a
# pagination token in the response. You can use this pagination token
# to retrieve the next set of stream processors.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of stream processors you want Amazon Rekognition
# Video to return in the response. The default is 1000.
# @return [Integer]
#
class ListStreamProcessorsRequest < Struct.new(
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the response is truncated, Amazon Rekognition Video returns this
# token that you can use in the subsequent request to retrieve the
# next set of stream processors.
# @return [String]
#
# @!attribute [rw] stream_processors
# List of stream processors that you have created.
# @return [Array<Types::StreamProcessor>]
#
class ListStreamProcessorsResponse < Struct.new(
:next_token,
:stream_processors)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass ListTagsForResourceRequest
# data as a hash:
#
# {
# resource_arn: "ResourceArn", # required
# }
#
# @!attribute [rw] resource_arn
# Amazon Resource Name (ARN) of the model, collection, or stream
# processor that contains the tags that you want a list of.
# @return [String]
#
class ListTagsForResourceRequest < Struct.new(
:resource_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] tags
# A list of key-value tags assigned to the resource.
# @return [Hash<String,String>]
#
class ListTagsForResourceResponse < Struct.new(
:tags)
SENSITIVE = []
include Aws::Structure
end
# The format of the project policy document that you supplied to
# `PutProjectPolicy` is incorrect.
#
class MalformedPolicyDocumentException < Aws::EmptyStructure; end
# Provides information about a single type of inappropriate, unwanted,
# or offensive content found in an image or video. Each type of
# moderated content has a label within a hierarchical taxonomy. For more
# information, see Content moderation in the Amazon Rekognition
# Developer Guide.
#
# @!attribute [rw] confidence
# Specifies the confidence that Amazon Rekognition has that the label
# has been correctly identified.
#
# If you don't specify the `MinConfidence` parameter in the call to
# `DetectModerationLabels`, the operation returns labels with a
# confidence value greater than or equal to 50 percent.
# @return [Float]
#
# @!attribute [rw] name
# The label name for the type of unsafe content detected in the image.
# @return [String]
#
# @!attribute [rw] parent_name
# The name for the parent label. Labels at the top level of the
# hierarchy have the parent label `""`.
# @return [String]
#
class ModerationLabel < Struct.new(
:confidence,
:name,
:parent_name)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the mouth on the face is open, and the
# confidence level in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the mouth on the face is open
# or not.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class MouthOpen < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the face has a mustache, and the confidence
# level in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the face has mustache or not.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class Mustache < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# The Amazon Simple Notification Service topic to which Amazon
# Rekognition publishes the completion status of a video analysis
# operation. For more information, see [Calling Amazon Rekognition Video
# operations][1]. Note that the Amazon SNS topic must have a topic name
# that begins with *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy to access the topic.
# For more information, see [Giving access to multiple Amazon SNS
# topics][2].
#
#
#
# [1]: https://docs.aws.amazon.com/rekognition/latest/dg/api-video.html
# [2]: https://docs.aws.amazon.com/rekognition/latest/dg/api-video-roles.html#api-video-roles-all-topics
#
# @note When making an API call, you may pass NotificationChannel
# data as a hash:
#
# {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# }
#
# @!attribute [rw] sns_topic_arn
# The Amazon SNS topic to which Amazon Rekognition posts the
# completion status.
# @return [String]
#
# @!attribute [rw] role_arn
# The ARN of an IAM role that gives Amazon Rekognition publishing
# permissions to the Amazon SNS topic.
# @return [String]
#
class NotificationChannel < Struct.new(
:sns_topic_arn,
:role_arn)
SENSITIVE = []
include Aws::Structure
end
# The S3 bucket and folder location where training output is placed.
#
# @note When making an API call, you may pass OutputConfig
# data as a hash:
#
# {
# s3_bucket: "S3Bucket",
# s3_key_prefix: "S3KeyPrefix",
# }
#
# @!attribute [rw] s3_bucket
# The S3 bucket where training output is placed.
# @return [String]
#
# @!attribute [rw] s3_key_prefix
# The prefix applied to the training output files.
# @return [String]
#
class OutputConfig < Struct.new(
:s3_bucket,
:s3_key_prefix)
SENSITIVE = []
include Aws::Structure
end
# A parent label for a label. A label can have 0, 1, or more parents.
#
# @!attribute [rw] name
# The name of the parent label.
# @return [String]
#
class Parent < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# Details about a person detected in a video analysis request.
#
# @!attribute [rw] index
# Identifier for the person detected person within a video. Use to
# keep track of the person throughout the video. The identifier is not
# stored by Amazon Rekognition.
# @return [Integer]
#
# @!attribute [rw] bounding_box
# Bounding box around the detected person.
# @return [Types::BoundingBox]
#
# @!attribute [rw] face
# Face details for the detected person.
# @return [Types::FaceDetail]
#
class PersonDetail < Struct.new(
:index,
:bounding_box,
:face)
SENSITIVE = []
include Aws::Structure
end
# Details and path tracking information for a single time a person's
# path is tracked in a video. Amazon Rekognition operations that track
# people's paths return an array of `PersonDetection` objects with
# elements for each time a person's path is tracked in a video.
#
# For more information, see GetPersonTracking in the Amazon Rekognition
# Developer Guide.
#
# @!attribute [rw] timestamp
# The time, in milliseconds from the start of the video, that the
# person's path was tracked. Note that `Timestamp` is not guaranteed
# to be accurate to the individual frame where the person's path
# first appears.
# @return [Integer]
#
# @!attribute [rw] person
# Details about a person whose path was tracked in a video.
# @return [Types::PersonDetail]
#
class PersonDetection < Struct.new(
:timestamp,
:person)
SENSITIVE = []
include Aws::Structure
end
# Information about a person whose face matches a face(s) in an Amazon
# Rekognition collection. Includes information about the faces in the
# Amazon Rekognition collection (FaceMatch), information about the
# person (PersonDetail), and the time stamp for when the person was
# detected in a video. An array of `PersonMatch` objects is returned by
# GetFaceSearch.
#
# @!attribute [rw] timestamp
# The time, in milliseconds from the beginning of the video, that the
# person was matched in the video.
# @return [Integer]
#
# @!attribute [rw] person
# Information about the matched person.
# @return [Types::PersonDetail]
#
# @!attribute [rw] face_matches
# Information about the faces in the input collection that match the
# face of a person in the video.
# @return [Array<Types::FaceMatch>]
#
class PersonMatch < Struct.new(
:timestamp,
:person,
:face_matches)
SENSITIVE = []
include Aws::Structure
end
# The X and Y coordinates of a point on an image or video frame. The X
# and Y values are ratios of the overall image size or video resolution.
# For example, if an input image is 700x200 and the values are X=0.5 and
# Y=0.25, then the point is at the (350,50) pixel coordinate on the
# image.
#
# An array of `Point` objects makes up a `Polygon`. A `Polygon` is
# returned by DetectText and by DetectCustomLabels `Polygon` represents
# a fine-grained polygon around a detected item. For more information,
# see Geometry in the Amazon Rekognition Developer Guide.
#
# @note When making an API call, you may pass Point
# data as a hash:
#
# {
# x: 1.0,
# y: 1.0,
# }
#
# @!attribute [rw] x
# The value of the X coordinate for a point on a `Polygon`.
# @return [Float]
#
# @!attribute [rw] y
# The value of the Y coordinate for a point on a `Polygon`.
# @return [Float]
#
class Point < Struct.new(
:x,
:y)
SENSITIVE = []
include Aws::Structure
end
# Indicates the pose of the face as determined by its pitch, roll, and
# yaw.
#
# @!attribute [rw] roll
# Value representing the face rotation on the roll axis.
# @return [Float]
#
# @!attribute [rw] yaw
# Value representing the face rotation on the yaw axis.
# @return [Float]
#
# @!attribute [rw] pitch
# Value representing the face rotation on the pitch axis.
# @return [Float]
#
class Pose < Struct.new(
:roll,
:yaw,
:pitch)
SENSITIVE = []
include Aws::Structure
end
# A description of an Amazon Rekognition Custom Labels project. For more
# information, see DescribeProjects.
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project.
# @return [String]
#
# @!attribute [rw] creation_timestamp
# The Unix timestamp for the date and time that the project was
# created.
# @return [Time]
#
# @!attribute [rw] status
# The current status of the project.
# @return [String]
#
# @!attribute [rw] datasets
# Information about the training and test datasets in the project.
# @return [Array<Types::DatasetMetadata>]
#
class ProjectDescription < Struct.new(
:project_arn,
:creation_timestamp,
:status,
:datasets)
SENSITIVE = []
include Aws::Structure
end
# Describes a project policy in the response from ListProjectPolicies.
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project to which the project
# policy is attached.
# @return [String]
#
# @!attribute [rw] policy_name
# The name of the project policy.
# @return [String]
#
# @!attribute [rw] policy_revision_id
# The revision ID of the project policy.
# @return [String]
#
# @!attribute [rw] policy_document
# The JSON document for the project policy.
# @return [String]
#
# @!attribute [rw] creation_timestamp
# The Unix datetime for the creation of the project policy.
# @return [Time]
#
# @!attribute [rw] last_updated_timestamp
# The Unix datetime for when the project policy was last updated.
# @return [Time]
#
class ProjectPolicy < Struct.new(
:project_arn,
:policy_name,
:policy_revision_id,
:policy_document,
:creation_timestamp,
:last_updated_timestamp)
SENSITIVE = []
include Aws::Structure
end
# A description of a version of an Amazon Rekognition Custom Labels
# model.
#
# @!attribute [rw] project_version_arn
# The Amazon Resource Name (ARN) of the model version.
# @return [String]
#
# @!attribute [rw] creation_timestamp
# The Unix datetime for the date and time that training started.
# @return [Time]
#
# @!attribute [rw] min_inference_units
# The minimum number of inference units used by the model. For more
# information, see StartProjectVersion.
# @return [Integer]
#
# @!attribute [rw] status
# The current status of the model version.
# @return [String]
#
# @!attribute [rw] status_message
# A descriptive message for an error or warning that occurred.
# @return [String]
#
# @!attribute [rw] billable_training_time_in_seconds
# The duration, in seconds, that you were billed for a successful
# training of the model version. This value is only returned if the
# model version has been successfully trained.
# @return [Integer]
#
# @!attribute [rw] training_end_timestamp
# The Unix date and time that training of the model ended.
# @return [Time]
#
# @!attribute [rw] output_config
# The location where training results are saved.
# @return [Types::OutputConfig]
#
# @!attribute [rw] training_data_result
# Contains information about the training results.
# @return [Types::TrainingDataResult]
#
# @!attribute [rw] testing_data_result
# Contains information about the testing results.
# @return [Types::TestingDataResult]
#
# @!attribute [rw] evaluation_result
# The training results. `EvaluationResult` is only returned if
# training is successful.
# @return [Types::EvaluationResult]
#
# @!attribute [rw] manifest_summary
# The location of the summary manifest. The summary manifest provides
# aggregate data validation results for the training and test
# datasets.
# @return [Types::GroundTruthManifest]
#
# @!attribute [rw] kms_key_id
# The identifer for the AWS Key Management Service key (AWS KMS key)
# that was used to encrypt the model during training.
# @return [String]
#
# @!attribute [rw] max_inference_units
# The maximum number of inference units Amazon Rekognition Custom
# Labels uses to auto-scale the model. For more information, see
# StartProjectVersion.
# @return [Integer]
#
# @!attribute [rw] source_project_version_arn
# If the model version was copied from a different project,
# `SourceProjectVersionArn` contains the ARN of the source model
# version.
# @return [String]
#
class ProjectVersionDescription < Struct.new(
:project_version_arn,
:creation_timestamp,
:min_inference_units,
:status,
:status_message,
:billable_training_time_in_seconds,
:training_end_timestamp,
:output_config,
:training_data_result,
:testing_data_result,
:evaluation_result,
:manifest_summary,
:kms_key_id,
:max_inference_units,
:source_project_version_arn)
SENSITIVE = []
include Aws::Structure
end
# Information about a body part detected by DetectProtectiveEquipment
# that contains PPE. An array of `ProtectiveEquipmentBodyPart` objects
# is returned for each person detected by `DetectProtectiveEquipment`.
#
# @!attribute [rw] name
# The detected body part.
# @return [String]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition has in the detection accuracy
# of the detected body part.
# @return [Float]
#
# @!attribute [rw] equipment_detections
# An array of Personal Protective Equipment items detected around a
# body part.
# @return [Array<Types::EquipmentDetection>]
#
class ProtectiveEquipmentBodyPart < Struct.new(
:name,
:confidence,
:equipment_detections)
SENSITIVE = []
include Aws::Structure
end
# A person detected by a call to DetectProtectiveEquipment. The API
# returns all persons detected in the input image in an array of
# `ProtectiveEquipmentPerson` objects.
#
# @!attribute [rw] body_parts
# An array of body parts detected on a person's body (including body
# parts without PPE).
# @return [Array<Types::ProtectiveEquipmentBodyPart>]
#
# @!attribute [rw] bounding_box
# A bounding box around the detected person.
# @return [Types::BoundingBox]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition has that the bounding box
# contains a person.
# @return [Float]
#
# @!attribute [rw] id
# The identifier for the detected person. The identifier is only
# unique for a single call to `DetectProtectiveEquipment`.
# @return [Integer]
#
class ProtectiveEquipmentPerson < Struct.new(
:body_parts,
:bounding_box,
:confidence,
:id)
SENSITIVE = []
include Aws::Structure
end
# Specifies summary attributes to return from a call to
# DetectProtectiveEquipment. You can specify which types of PPE to
# summarize. You can also specify a minimum confidence value for
# detections. Summary information is returned in the `Summary`
# (ProtectiveEquipmentSummary) field of the response from
# `DetectProtectiveEquipment`. The summary includes which persons in an
# image were detected wearing the requested types of person protective
# equipment (PPE), which persons were detected as not wearing PPE, and
# the persons in which a determination could not be made. For more
# information, see ProtectiveEquipmentSummary.
#
# @note When making an API call, you may pass ProtectiveEquipmentSummarizationAttributes
# data as a hash:
#
# {
# min_confidence: 1.0, # required
# required_equipment_types: ["FACE_COVER"], # required, accepts FACE_COVER, HAND_COVER, HEAD_COVER
# }
#
# @!attribute [rw] min_confidence
# The minimum confidence level for which you want summary information.
# The confidence level applies to person detection, body part
# detection, equipment detection, and body part coverage. Amazon
# Rekognition doesn't return summary information with a confidence
# than this specified value. There isn't a default value.
#
# Specify a `MinConfidence` value that is between 50-100% as
# `DetectProtectiveEquipment` returns predictions only where the
# detection confidence is between 50% - 100%. If you specify a value
# that is less than 50%, the results are the same specifying a value
# of 50%.
# @return [Float]
#
# @!attribute [rw] required_equipment_types
# An array of personal protective equipment types for which you want
# summary information. If a person is detected wearing a required
# requipment type, the person's ID is added to the
# `PersonsWithRequiredEquipment` array field returned in
# ProtectiveEquipmentSummary by `DetectProtectiveEquipment`.
# @return [Array<String>]
#
class ProtectiveEquipmentSummarizationAttributes < Struct.new(
:min_confidence,
:required_equipment_types)
SENSITIVE = []
include Aws::Structure
end
# Summary information for required items of personal protective
# equipment (PPE) detected on persons by a call to
# DetectProtectiveEquipment. You specify the required type of PPE in the
# `SummarizationAttributes` (ProtectiveEquipmentSummarizationAttributes)
# input parameter. The summary includes which persons were detected
# wearing the required personal protective equipment
# (`PersonsWithRequiredEquipment`), which persons were detected as not
# wearing the required PPE (`PersonsWithoutRequiredEquipment`), and the
# persons in which a determination could not be made
# (`PersonsIndeterminate`).
#
# To get a total for each category, use the size of the field array. For
# example, to find out how many people were detected as wearing the
# specified PPE, use the size of the `PersonsWithRequiredEquipment`
# array. If you want to find out more about a person, such as the
# location (BoundingBox) of the person on the image, use the person ID
# in each array element. Each person ID matches the ID field of a
# ProtectiveEquipmentPerson object returned in the `Persons` array by
# `DetectProtectiveEquipment`.
#
# @!attribute [rw] persons_with_required_equipment
# An array of IDs for persons who are wearing detected personal
# protective equipment.
# @return [Array<Integer>]
#
# @!attribute [rw] persons_without_required_equipment
# An array of IDs for persons who are not wearing all of the types of
# PPE specified in the `RequiredEquipmentTypes` field of the detected
# personal protective equipment.
# @return [Array<Integer>]
#
# @!attribute [rw] persons_indeterminate
# An array of IDs for persons where it was not possible to determine
# if they are wearing personal protective equipment.
# @return [Array<Integer>]
#
class ProtectiveEquipmentSummary < Struct.new(
:persons_with_required_equipment,
:persons_without_required_equipment,
:persons_indeterminate)
SENSITIVE = []
include Aws::Structure
end
# The number of requests exceeded your throughput limit. If you want to
# increase this limit, contact Amazon Rekognition.
#
class ProvisionedThroughputExceededException < Aws::EmptyStructure; end
# @note When making an API call, you may pass PutProjectPolicyRequest
# data as a hash:
#
# {
# project_arn: "ProjectArn", # required
# policy_name: "ProjectPolicyName", # required
# policy_revision_id: "ProjectPolicyRevisionId",
# policy_document: "ProjectPolicyDocument", # required
# }
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project that the project
# policy is attached to.
# @return [String]
#
# @!attribute [rw] policy_name
# A name for the policy.
# @return [String]
#
# @!attribute [rw] policy_revision_id
# The revision ID for the Project Policy. Each time you modify a
# policy, Amazon Rekognition Custom Labels generates and assigns a new
# `PolicyRevisionId` and then deletes the previous version of the
# policy.
# @return [String]
#
# @!attribute [rw] policy_document
# A resource policy to add to the model. The policy is a JSON
# structure that contains one or more statements that define the
# policy. The policy must follow the IAM syntax. For more information
# about the contents of a JSON policy document, see [IAM JSON policy
# reference][1].
#
#
#
# [1]: https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies.html
# @return [String]
#
class PutProjectPolicyRequest < Struct.new(
:project_arn,
:policy_name,
:policy_revision_id,
:policy_document)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] policy_revision_id
# The ID of the project policy.
# @return [String]
#
class PutProjectPolicyResponse < Struct.new(
:policy_revision_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass RecognizeCelebritiesRequest
# data as a hash:
#
# {
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# }
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes is not supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
class RecognizeCelebritiesRequest < Struct.new(
:image)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] celebrity_faces
# Details about each celebrity found in the image. Amazon Rekognition
# can detect a maximum of 64 celebrities in an image. Each celebrity
# object includes the following attributes: `Face`, `Confidence`,
# `Emotions`, `Landmarks`, `Pose`, `Quality`, `Smile`, `Id`,
# `KnownGender`, `MatchConfidence`, `Name`, `Urls`.
# @return [Array<Types::Celebrity>]
#
# @!attribute [rw] unrecognized_faces
# Details about each unrecognized face in the image.
# @return [Array<Types::ComparedFace>]
#
# @!attribute [rw] orientation_correction
# <note markdown="1"> Support for estimating image orientation using the the
# OrientationCorrection field has ceased as of August 2021. Any
# returned values for this field included in an API response will
# always be NULL.
#
# </note>
#
# The orientation of the input image (counterclockwise direction). If
# your application displays the image, you can use this value to
# correct the orientation. The bounding box coordinates returned in
# `CelebrityFaces` and `UnrecognizedFaces` represent face locations
# before the image orientation is corrected.
#
# <note markdown="1"> If the input image is in .jpeg format, it might contain exchangeable
# image (Exif) metadata that includes the image's orientation. If so,
# and the Exif metadata for the input image populates the orientation
# field, the value of `OrientationCorrection` is null. The
# `CelebrityFaces` and `UnrecognizedFaces` bounding box coordinates
# represent face locations after Exif metadata is used to correct the
# image orientation. Images in .png format don't contain Exif
# metadata.
#
# </note>
# @return [String]
#
class RecognizeCelebritiesResponse < Struct.new(
:celebrity_faces,
:unrecognized_faces,
:orientation_correction)
SENSITIVE = []
include Aws::Structure
end
# Specifies a location within the frame that Rekognition checks for
# objects of interest such as text, labels, or faces. It uses a
# `BoundingBox` or `Polygon` to set a region of the screen.
#
# A word, face, or label is included in the region if it is more than
# half in that region. If there is more than one region, the word, face,
# or label is compared with all regions of the screen. Any object of
# interest that is more than half in a region is kept in the results.
#
# @note When making an API call, you may pass RegionOfInterest
# data as a hash:
#
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# }
#
# @!attribute [rw] bounding_box
# The box representing a region of interest on screen.
# @return [Types::BoundingBox]
#
# @!attribute [rw] polygon
# Specifies a shape made up of up to 10 `Point` objects to define a
# region of interest.
# @return [Array<Types::Point>]
#
class RegionOfInterest < Struct.new(
:bounding_box,
:polygon)
SENSITIVE = []
include Aws::Structure
end
# A resource with the specified ID already exists.
#
class ResourceAlreadyExistsException < Aws::EmptyStructure; end
# The specified resource is already being used.
#
class ResourceInUseException < Aws::EmptyStructure; end
# The resource specified in the request cannot be found.
#
class ResourceNotFoundException < Aws::EmptyStructure; end
# The requested resource isn't ready. For example, this exception
# occurs when you call `DetectCustomLabels` with a model version that
# isn't deployed.
#
class ResourceNotReadyException < Aws::EmptyStructure; end
# The Amazon S3 bucket location to which Amazon Rekognition publishes
# the detailed inference results of a video analysis operation. These
# results include the name of the stream processor resource, the session
# ID of the stream processing session, and labeled timestamps and
# bounding boxes for detected labels.
#
# @note When making an API call, you may pass S3Destination
# data as a hash:
#
# {
# bucket: "S3Bucket",
# key_prefix: "S3KeyPrefix",
# }
#
# @!attribute [rw] bucket
# The name of the Amazon S3 bucket you want to associate with the
# streaming video project. You must be the owner of the Amazon S3
# bucket.
# @return [String]
#
# @!attribute [rw] key_prefix
# The prefix value of the location within the bucket that you want the
# information to be published to. For more information, see [Using
# prefixes][1].
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-prefixes.html
# @return [String]
#
class S3Destination < Struct.new(
:bucket,
:key_prefix)
SENSITIVE = []
include Aws::Structure
end
# Provides the S3 bucket name and object name.
#
# The region for the S3 bucket containing the S3 object must match the
# region you use for Amazon Rekognition operations.
#
# For Amazon Rekognition to process an S3 object, the user must have
# permission to access the S3 object. For more information, see How
# Amazon Rekognition works with IAM in the Amazon Rekognition Developer
# Guide.
#
# @note When making an API call, you may pass S3Object
# data as a hash:
#
# {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# }
#
# @!attribute [rw] bucket
# Name of the S3 bucket.
# @return [String]
#
# @!attribute [rw] name
# S3 object key name.
# @return [String]
#
# @!attribute [rw] version
# If the bucket is versioning enabled, you can specify the object
# version.
# @return [String]
#
class S3Object < Struct.new(
:bucket,
:name,
:version)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass SearchFacesByImageRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# image: { # required
# bytes: "data",
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# max_faces: 1,
# face_match_threshold: 1.0,
# quality_filter: "NONE", # accepts NONE, AUTO, LOW, MEDIUM, HIGH
# }
#
# @!attribute [rw] collection_id
# ID of the collection to search.
# @return [String]
#
# @!attribute [rw] image
# The input image as base64-encoded bytes or an S3 object. If you use
# the AWS CLI to call Amazon Rekognition operations, passing
# base64-encoded image bytes is not supported.
#
# If you are using an AWS SDK to call Amazon Rekognition, you might
# not need to base64-encode image bytes passed using the `Bytes`
# field. For more information, see Images in the Amazon Rekognition
# developer guide.
# @return [Types::Image]
#
# @!attribute [rw] max_faces
# Maximum number of faces to return. The operation returns the maximum
# number of faces with the highest confidence in the match.
# @return [Integer]
#
# @!attribute [rw] face_match_threshold
# (Optional) Specifies the minimum confidence in the face match to
# return. For example, don't return any matches where confidence in
# matches is less than 70%. The default value is 80%.
# @return [Float]
#
# @!attribute [rw] quality_filter
# A filter that specifies a quality bar for how much filtering is done
# to identify faces. Filtered faces aren't searched for in the
# collection. If you specify `AUTO`, Amazon Rekognition chooses the
# quality bar. If you specify `LOW`, `MEDIUM`, or `HIGH`, filtering
# removes all faces that don’t meet the chosen quality bar. The
# quality bar is based on a variety of common use cases. Low-quality
# detections can occur for a number of reasons. Some examples are an
# object that's misidentified as a face, a face that's too blurry,
# or a face with a pose that's too extreme to use. If you specify
# `NONE`, no filtering is performed. The default value is `NONE`.
#
# To use quality filtering, the collection you are using must be
# associated with version 3 of the face model or higher.
# @return [String]
#
class SearchFacesByImageRequest < Struct.new(
:collection_id,
:image,
:max_faces,
:face_match_threshold,
:quality_filter)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] searched_face_bounding_box
# The bounding box around the face in the input image that Amazon
# Rekognition used for the search.
# @return [Types::BoundingBox]
#
# @!attribute [rw] searched_face_confidence
# The level of confidence that the `searchedFaceBoundingBox`, contains
# a face.
# @return [Float]
#
# @!attribute [rw] face_matches
# An array of faces that match the input face, along with the
# confidence in the match.
# @return [Array<Types::FaceMatch>]
#
# @!attribute [rw] face_model_version
# Version number of the face detection model associated with the input
# collection (`CollectionId`).
# @return [String]
#
class SearchFacesByImageResponse < Struct.new(
:searched_face_bounding_box,
:searched_face_confidence,
:face_matches,
:face_model_version)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass SearchFacesRequest
# data as a hash:
#
# {
# collection_id: "CollectionId", # required
# face_id: "FaceId", # required
# max_faces: 1,
# face_match_threshold: 1.0,
# }
#
# @!attribute [rw] collection_id
# ID of the collection the face belongs to.
# @return [String]
#
# @!attribute [rw] face_id
# ID of a face to find matches for in the collection.
# @return [String]
#
# @!attribute [rw] max_faces
# Maximum number of faces to return. The operation returns the maximum
# number of faces with the highest confidence in the match.
# @return [Integer]
#
# @!attribute [rw] face_match_threshold
# Optional value specifying the minimum confidence in the face match
# to return. For example, don't return any matches where confidence
# in matches is less than 70%. The default value is 80%.
# @return [Float]
#
class SearchFacesRequest < Struct.new(
:collection_id,
:face_id,
:max_faces,
:face_match_threshold)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] searched_face_id
# ID of the face that was searched for matches in a collection.
# @return [String]
#
# @!attribute [rw] face_matches
# An array of faces that matched the input face, along with the
# confidence in the match.
# @return [Array<Types::FaceMatch>]
#
# @!attribute [rw] face_model_version
# Version number of the face detection model associated with the input
# collection (`CollectionId`).
# @return [String]
#
class SearchFacesResponse < Struct.new(
:searched_face_id,
:face_matches,
:face_model_version)
SENSITIVE = []
include Aws::Structure
end
# A technical cue or shot detection segment detected in a video. An
# array of `SegmentDetection` objects containing all segments detected
# in a stored video is returned by GetSegmentDetection.
#
# @!attribute [rw] type
# The type of the segment. Valid values are `TECHNICAL_CUE` and
# `SHOT`.
# @return [String]
#
# @!attribute [rw] start_timestamp_millis
# The start time of the detected segment in milliseconds from the
# start of the video. This value is rounded down. For example, if the
# actual timestamp is 100.6667 milliseconds, Amazon Rekognition Video
# returns a value of 100 millis.
# @return [Integer]
#
# @!attribute [rw] end_timestamp_millis
# The end time of the detected segment, in milliseconds, from the
# start of the video. This value is rounded down.
# @return [Integer]
#
# @!attribute [rw] duration_millis
# The duration of the detected segment in milliseconds.
# @return [Integer]
#
# @!attribute [rw] start_timecode_smpte
# The frame-accurate SMPTE timecode, from the start of a video, for
# the start of a detected segment. `StartTimecode` is in *HH:MM:SS:fr*
# format (and *;fr* for drop frame-rates).
# @return [String]
#
# @!attribute [rw] end_timecode_smpte
# The frame-accurate SMPTE timecode, from the start of a video, for
# the end of a detected segment. `EndTimecode` is in *HH:MM:SS:fr*
# format (and *;fr* for drop frame-rates).
# @return [String]
#
# @!attribute [rw] duration_smpte
# The duration of the timecode for the detected segment in SMPTE
# format.
# @return [String]
#
# @!attribute [rw] technical_cue_segment
# If the segment is a technical cue, contains information about the
# technical cue.
# @return [Types::TechnicalCueSegment]
#
# @!attribute [rw] shot_segment
# If the segment is a shot detection, contains information about the
# shot detection.
# @return [Types::ShotSegment]
#
# @!attribute [rw] start_frame_number
# The frame number of the start of a video segment, using a frame
# index that starts with 0.
# @return [Integer]
#
# @!attribute [rw] end_frame_number
# The frame number at the end of a video segment, using a frame index
# that starts with 0.
# @return [Integer]
#
# @!attribute [rw] duration_frames
# The duration of a video segment, expressed in frames.
# @return [Integer]
#
class SegmentDetection < Struct.new(
:type,
:start_timestamp_millis,
:end_timestamp_millis,
:duration_millis,
:start_timecode_smpte,
:end_timecode_smpte,
:duration_smpte,
:technical_cue_segment,
:shot_segment,
:start_frame_number,
:end_frame_number,
:duration_frames)
SENSITIVE = []
include Aws::Structure
end
# Information about the type of a segment requested in a call to
# StartSegmentDetection. An array of `SegmentTypeInfo` objects is
# returned by the response from GetSegmentDetection.
#
# @!attribute [rw] type
# The type of a segment (technical cue or shot detection).
# @return [String]
#
# @!attribute [rw] model_version
# The version of the model used to detect segments.
# @return [String]
#
class SegmentTypeInfo < Struct.new(
:type,
:model_version)
SENSITIVE = []
include Aws::Structure
end
# The size of the collection exceeds the allowed limit. For more
# information, see Guidelines and quotas in Amazon Rekognition in the
# Amazon Rekognition Developer Guide.
#
class ServiceQuotaExceededException < Aws::EmptyStructure; end
# Information about a shot detection segment detected in a video. For
# more information, see SegmentDetection.
#
# @!attribute [rw] index
# An Identifier for a shot detection segment detected in a video.
# @return [Integer]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition Video has in the accuracy of
# the detected segment.
# @return [Float]
#
class ShotSegment < Struct.new(
:index,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the face is smiling, and the confidence level
# in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the face is smiling or not.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class Smile < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartCelebrityRecognitionRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# }
#
# @!attribute [rw] video
# The video in which you want to recognize celebrities. The video must
# be stored in an Amazon S3 bucket.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartCelebrityRecognition` requests, the
# same `JobId` is returned. Use `ClientRequestToken` to prevent the
# same job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] notification_channel
# The Amazon SNS topic ARN that you want Amazon Rekognition Video to
# publish the completion status of the celebrity recognition analysis
# to. The Amazon SNS topic must have a topic name that begins with
# *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
class StartCelebrityRecognitionRequest < Struct.new(
:video,
:client_request_token,
:notification_channel,
:job_tag)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# The identifier for the celebrity recognition analysis job. Use
# `JobId` to identify the job in a subsequent call to
# `GetCelebrityRecognition`.
# @return [String]
#
class StartCelebrityRecognitionResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartContentModerationRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# min_confidence: 1.0,
# client_request_token: "ClientRequestToken",
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# }
#
# @!attribute [rw] video
# The video in which you want to detect inappropriate, unwanted, or
# offensive content. The video must be stored in an Amazon S3 bucket.
# @return [Types::Video]
#
# @!attribute [rw] min_confidence
# Specifies the minimum confidence that Amazon Rekognition must have
# in order to return a moderated content label. Confidence represents
# how certain Amazon Rekognition is that the moderated content is
# correctly identified. 0 is the lowest confidence. 100 is the highest
# confidence. Amazon Rekognition doesn't return any moderated content
# labels with a confidence level lower than this specified value. If
# you don't specify `MinConfidence`, `GetContentModeration` returns
# labels with confidence values greater than or equal to 50 percent.
# @return [Float]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartContentModeration` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] notification_channel
# The Amazon SNS topic ARN that you want Amazon Rekognition Video to
# publish the completion status of the content analysis to. The Amazon
# SNS topic must have a topic name that begins with
# *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy to access the topic.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
class StartContentModerationRequest < Struct.new(
:video,
:min_confidence,
:client_request_token,
:notification_channel,
:job_tag)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# The identifier for the content analysis job. Use `JobId` to identify
# the job in a subsequent call to `GetContentModeration`.
# @return [String]
#
class StartContentModerationResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartFaceDetectionRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# face_attributes: "DEFAULT", # accepts DEFAULT, ALL
# job_tag: "JobTag",
# }
#
# @!attribute [rw] video
# The video in which you want to detect faces. The video must be
# stored in an Amazon S3 bucket.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartFaceDetection` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] notification_channel
# The ARN of the Amazon SNS topic to which you want Amazon Rekognition
# Video to publish the completion status of the face detection
# operation. The Amazon SNS topic must have a topic name that begins
# with *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] face_attributes
# The face attributes you want returned.
#
# `DEFAULT` - The following subset of facial attributes are returned:
# BoundingBox, Confidence, Pose, Quality and Landmarks.
#
# `ALL` - All facial attributes are returned.
# @return [String]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
class StartFaceDetectionRequest < Struct.new(
:video,
:client_request_token,
:notification_channel,
:face_attributes,
:job_tag)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# The identifier for the face detection job. Use `JobId` to identify
# the job in a subsequent call to `GetFaceDetection`.
# @return [String]
#
class StartFaceDetectionResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartFaceSearchRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# face_match_threshold: 1.0,
# collection_id: "CollectionId", # required
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# }
#
# @!attribute [rw] video
# The video you want to search. The video must be stored in an Amazon
# S3 bucket.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartFaceSearch` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] face_match_threshold
# The minimum confidence in the person match to return. For example,
# don't return any matches where confidence in matches is less than
# 70%. The default value is 80%.
# @return [Float]
#
# @!attribute [rw] collection_id
# ID of the collection that contains the faces you want to search for.
# @return [String]
#
# @!attribute [rw] notification_channel
# The ARN of the Amazon SNS topic to which you want Amazon Rekognition
# Video to publish the completion status of the search. The Amazon SNS
# topic must have a topic name that begins with *AmazonRekognition* if
# you are using the AmazonRekognitionServiceRole permissions policy to
# access the topic.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
class StartFaceSearchRequest < Struct.new(
:video,
:client_request_token,
:face_match_threshold,
:collection_id,
:notification_channel,
:job_tag)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# The identifier for the search job. Use `JobId` to identify the job
# in a subsequent call to `GetFaceSearch`.
# @return [String]
#
class StartFaceSearchResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartLabelDetectionRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# min_confidence: 1.0,
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# }
#
# @!attribute [rw] video
# The video in which you want to detect labels. The video must be
# stored in an Amazon S3 bucket.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartLabelDetection` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] min_confidence
# Specifies the minimum confidence that Amazon Rekognition Video must
# have in order to return a detected label. Confidence represents how
# certain Amazon Rekognition is that a label is correctly identified.0
# is the lowest confidence. 100 is the highest confidence. Amazon
# Rekognition Video doesn't return any labels with a confidence level
# lower than this specified value.
#
# If you don't specify `MinConfidence`, the operation returns labels
# with confidence values greater than or equal to 50 percent.
# @return [Float]
#
# @!attribute [rw] notification_channel
# The Amazon SNS topic ARN you want Amazon Rekognition Video to
# publish the completion status of the label detection operation to.
# The Amazon SNS topic must have a topic name that begins with
# *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
class StartLabelDetectionRequest < Struct.new(
:video,
:client_request_token,
:min_confidence,
:notification_channel,
:job_tag)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# The identifier for the label detection job. Use `JobId` to identify
# the job in a subsequent call to `GetLabelDetection`.
# @return [String]
#
class StartLabelDetectionResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartPersonTrackingRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# }
#
# @!attribute [rw] video
# The video in which you want to detect people. The video must be
# stored in an Amazon S3 bucket.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartPersonTracking` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] notification_channel
# The Amazon SNS topic ARN you want Amazon Rekognition Video to
# publish the completion status of the people detection operation to.
# The Amazon SNS topic must have a topic name that begins with
# *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
class StartPersonTrackingRequest < Struct.new(
:video,
:client_request_token,
:notification_channel,
:job_tag)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# The identifier for the person detection job. Use `JobId` to identify
# the job in a subsequent call to `GetPersonTracking`.
# @return [String]
#
class StartPersonTrackingResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartProjectVersionRequest
# data as a hash:
#
# {
# project_version_arn: "ProjectVersionArn", # required
# min_inference_units: 1, # required
# max_inference_units: 1,
# }
#
# @!attribute [rw] project_version_arn
# The Amazon Resource Name(ARN) of the model version that you want to
# start.
# @return [String]
#
# @!attribute [rw] min_inference_units
# The minimum number of inference units to use. A single inference
# unit represents 1 hour of processing.
#
# For information about the number of transactions per second (TPS)
# that an inference unit can support, see *Running a trained Amazon
# Rekognition Custom Labels model* in the Amazon Rekognition Custom
# Labels Guide.
#
# Use a higher number to increase the TPS throughput of your model.
# You are charged for the number of inference units that you use.
# @return [Integer]
#
# @!attribute [rw] max_inference_units
# The maximum number of inference units to use for auto-scaling the
# model. If you don't specify a value, Amazon Rekognition Custom
# Labels doesn't auto-scale the model.
# @return [Integer]
#
class StartProjectVersionRequest < Struct.new(
:project_version_arn,
:min_inference_units,
:max_inference_units)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] status
# The current running status of the model.
# @return [String]
#
class StartProjectVersionResponse < Struct.new(
:status)
SENSITIVE = []
include Aws::Structure
end
# Filters applied to the technical cue or shot detection segments. For
# more information, see StartSegmentDetection.
#
# @note When making an API call, you may pass StartSegmentDetectionFilters
# data as a hash:
#
# {
# technical_cue_filter: {
# min_segment_confidence: 1.0,
# black_frame: {
# max_pixel_threshold: 1.0,
# min_coverage_percentage: 1.0,
# },
# },
# shot_filter: {
# min_segment_confidence: 1.0,
# },
# }
#
# @!attribute [rw] technical_cue_filter
# Filters that are specific to technical cues.
# @return [Types::StartTechnicalCueDetectionFilter]
#
# @!attribute [rw] shot_filter
# Filters that are specific to shot detections.
# @return [Types::StartShotDetectionFilter]
#
class StartSegmentDetectionFilters < Struct.new(
:technical_cue_filter,
:shot_filter)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartSegmentDetectionRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# filters: {
# technical_cue_filter: {
# min_segment_confidence: 1.0,
# black_frame: {
# max_pixel_threshold: 1.0,
# min_coverage_percentage: 1.0,
# },
# },
# shot_filter: {
# min_segment_confidence: 1.0,
# },
# },
# segment_types: ["TECHNICAL_CUE"], # required, accepts TECHNICAL_CUE, SHOT
# }
#
# @!attribute [rw] video
# Video file stored in an Amazon S3 bucket. Amazon Rekognition video
# start operations such as StartLabelDetection use `Video` to specify
# a video for analysis. The supported file formats are .mp4, .mov and
# .avi.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartSegmentDetection` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidently started more than once.
# @return [String]
#
# @!attribute [rw] notification_channel
# The ARN of the Amazon SNS topic to which you want Amazon Rekognition
# Video to publish the completion status of the segment detection
# operation. Note that the Amazon SNS topic must have a topic name
# that begins with *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy to access the topic.
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier you specify that's returned in the completion
# notification that's published to your Amazon Simple Notification
# Service topic. For example, you can use `JobTag` to group related
# jobs and identify them in the completion notification.
# @return [String]
#
# @!attribute [rw] filters
# Filters for technical cue or shot detection.
# @return [Types::StartSegmentDetectionFilters]
#
# @!attribute [rw] segment_types
# An array of segment types to detect in the video. Valid values are
# TECHNICAL\_CUE and SHOT.
# @return [Array<String>]
#
class StartSegmentDetectionRequest < Struct.new(
:video,
:client_request_token,
:notification_channel,
:job_tag,
:filters,
:segment_types)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# Unique identifier for the segment detection job. The `JobId` is
# returned from `StartSegmentDetection`.
# @return [String]
#
class StartSegmentDetectionResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# Filters for the shot detection segments returned by
# `GetSegmentDetection`. For more information, see
# StartSegmentDetectionFilters.
#
# @note When making an API call, you may pass StartShotDetectionFilter
# data as a hash:
#
# {
# min_segment_confidence: 1.0,
# }
#
# @!attribute [rw] min_segment_confidence
# Specifies the minimum confidence that Amazon Rekognition Video must
# have in order to return a detected segment. Confidence represents
# how certain Amazon Rekognition is that a segment is correctly
# identified. 0 is the lowest confidence. 100 is the highest
# confidence. Amazon Rekognition Video doesn't return any segments
# with a confidence level lower than this specified value.
#
# If you don't specify `MinSegmentConfidence`, the
# `GetSegmentDetection` returns segments with confidence values
# greater than or equal to 50 percent.
# @return [Float]
#
class StartShotDetectionFilter < Struct.new(
:min_segment_confidence)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartStreamProcessorRequest
# data as a hash:
#
# {
# name: "StreamProcessorName", # required
# start_selector: {
# kvs_stream_start_selector: {
# producer_timestamp: 1,
# fragment_number: "KinesisVideoStreamFragmentNumber",
# },
# },
# stop_selector: {
# max_duration_in_seconds: 1,
# },
# }
#
# @!attribute [rw] name
# The name of the stream processor to start processing.
# @return [String]
#
# @!attribute [rw] start_selector
# Specifies the starting point in the Kinesis stream to start
# processing. You can use the producer timestamp or the fragment
# number. If you use the producer timestamp, you must put the time in
# milliseconds. For more information about fragment numbers, see
# [Fragment][1].
#
# This is a required parameter for label detection stream processors
# and should not be used to start a face search stream processor.
#
#
#
# [1]: https://docs.aws.amazon.com/kinesisvideostreams/latest/dg/API_reader_Fragment.html
# @return [Types::StreamProcessingStartSelector]
#
# @!attribute [rw] stop_selector
# Specifies when to stop processing the stream. You can specify a
# maximum amount of time to process the video.
#
# This is a required parameter for label detection stream processors
# and should not be used to start a face search stream processor.
# @return [Types::StreamProcessingStopSelector]
#
class StartStreamProcessorRequest < Struct.new(
:name,
:start_selector,
:stop_selector)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] session_id
# A unique identifier for the stream processing session.
# @return [String]
#
class StartStreamProcessorResponse < Struct.new(
:session_id)
SENSITIVE = []
include Aws::Structure
end
# Filters for the technical segments returned by GetSegmentDetection.
# For more information, see StartSegmentDetectionFilters.
#
# @note When making an API call, you may pass StartTechnicalCueDetectionFilter
# data as a hash:
#
# {
# min_segment_confidence: 1.0,
# black_frame: {
# max_pixel_threshold: 1.0,
# min_coverage_percentage: 1.0,
# },
# }
#
# @!attribute [rw] min_segment_confidence
# Specifies the minimum confidence that Amazon Rekognition Video must
# have in order to return a detected segment. Confidence represents
# how certain Amazon Rekognition is that a segment is correctly
# identified. 0 is the lowest confidence. 100 is the highest
# confidence. Amazon Rekognition Video doesn't return any segments
# with a confidence level lower than this specified value.
#
# If you don't specify `MinSegmentConfidence`, `GetSegmentDetection`
# returns segments with confidence values greater than or equal to 50
# percent.
# @return [Float]
#
# @!attribute [rw] black_frame
# A filter that allows you to control the black frame detection by
# specifying the black levels and pixel coverage of black pixels in a
# frame. Videos can come from multiple sources, formats, and time
# periods, with different standards and varying noise levels for black
# frames that need to be accounted for.
# @return [Types::BlackFrame]
#
class StartTechnicalCueDetectionFilter < Struct.new(
:min_segment_confidence,
:black_frame)
SENSITIVE = []
include Aws::Structure
end
# Set of optional parameters that let you set the criteria text must
# meet to be included in your response. `WordFilter` looks at a word's
# height, width and minimum confidence. `RegionOfInterest` lets you set
# a specific region of the screen to look for text in.
#
# @note When making an API call, you may pass StartTextDetectionFilters
# data as a hash:
#
# {
# word_filter: {
# min_confidence: 1.0,
# min_bounding_box_height: 1.0,
# min_bounding_box_width: 1.0,
# },
# regions_of_interest: [
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# },
# ],
# }
#
# @!attribute [rw] word_filter
# Filters focusing on qualities of the text, such as confidence or
# size.
# @return [Types::DetectionFilter]
#
# @!attribute [rw] regions_of_interest
# Filter focusing on a certain area of the frame. Uses a `BoundingBox`
# object to set the region of the screen.
# @return [Array<Types::RegionOfInterest>]
#
class StartTextDetectionFilters < Struct.new(
:word_filter,
:regions_of_interest)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StartTextDetectionRequest
# data as a hash:
#
# {
# video: { # required
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# client_request_token: "ClientRequestToken",
# notification_channel: {
# sns_topic_arn: "SNSTopicArn", # required
# role_arn: "RoleArn", # required
# },
# job_tag: "JobTag",
# filters: {
# word_filter: {
# min_confidence: 1.0,
# min_bounding_box_height: 1.0,
# min_bounding_box_width: 1.0,
# },
# regions_of_interest: [
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# },
# ],
# },
# }
#
# @!attribute [rw] video
# Video file stored in an Amazon S3 bucket. Amazon Rekognition video
# start operations such as StartLabelDetection use `Video` to specify
# a video for analysis. The supported file formats are .mp4, .mov and
# .avi.
# @return [Types::Video]
#
# @!attribute [rw] client_request_token
# Idempotent token used to identify the start request. If you use the
# same token with multiple `StartTextDetection` requests, the same
# `JobId` is returned. Use `ClientRequestToken` to prevent the same
# job from being accidentaly started more than once.
# @return [String]
#
# @!attribute [rw] notification_channel
# The Amazon Simple Notification Service topic to which Amazon
# Rekognition publishes the completion status of a video analysis
# operation. For more information, see [Calling Amazon Rekognition
# Video operations][1]. Note that the Amazon SNS topic must have a
# topic name that begins with *AmazonRekognition* if you are using the
# AmazonRekognitionServiceRole permissions policy to access the topic.
# For more information, see [Giving access to multiple Amazon SNS
# topics][2].
#
#
#
# [1]: https://docs.aws.amazon.com/rekognition/latest/dg/api-video.html
# [2]: https://docs.aws.amazon.com/rekognition/latest/dg/api-video-roles.html#api-video-roles-all-topics
# @return [Types::NotificationChannel]
#
# @!attribute [rw] job_tag
# An identifier returned in the completion status published by your
# Amazon Simple Notification Service topic. For example, you can use
# `JobTag` to group related jobs and identify them in the completion
# notification.
# @return [String]
#
# @!attribute [rw] filters
# Optional parameters that let you set criteria the text must meet to
# be included in your response.
# @return [Types::StartTextDetectionFilters]
#
class StartTextDetectionRequest < Struct.new(
:video,
:client_request_token,
:notification_channel,
:job_tag,
:filters)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_id
# Identifier for the text detection job. Use `JobId` to identify the
# job in a subsequent call to `GetTextDetection`.
# @return [String]
#
class StartTextDetectionResponse < Struct.new(
:job_id)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StopProjectVersionRequest
# data as a hash:
#
# {
# project_version_arn: "ProjectVersionArn", # required
# }
#
# @!attribute [rw] project_version_arn
# The Amazon Resource Name (ARN) of the model version that you want to
# delete.
#
# This operation requires permissions to perform the
# `rekognition:StopProjectVersion` action.
# @return [String]
#
class StopProjectVersionRequest < Struct.new(
:project_version_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] status
# The current status of the stop operation.
# @return [String]
#
class StopProjectVersionResponse < Struct.new(
:status)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass StopStreamProcessorRequest
# data as a hash:
#
# {
# name: "StreamProcessorName", # required
# }
#
# @!attribute [rw] name
# The name of a stream processor created by CreateStreamProcessor.
# @return [String]
#
class StopStreamProcessorRequest < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
class StopStreamProcessorResponse < Aws::EmptyStructure; end
# This is a required parameter for label detection stream processors and
# should not be used to start a face search stream processor.
#
# @note When making an API call, you may pass StreamProcessingStartSelector
# data as a hash:
#
# {
# kvs_stream_start_selector: {
# producer_timestamp: 1,
# fragment_number: "KinesisVideoStreamFragmentNumber",
# },
# }
#
# @!attribute [rw] kvs_stream_start_selector
# Specifies the starting point in the stream to start processing. This
# can be done with a producer timestamp or a fragment number in a
# Kinesis stream.
# @return [Types::KinesisVideoStreamStartSelector]
#
class StreamProcessingStartSelector < Struct.new(
:kvs_stream_start_selector)
SENSITIVE = []
include Aws::Structure
end
# Specifies when to stop processing the stream. You can specify a
# maximum amount of time to process the video.
#
# @note When making an API call, you may pass StreamProcessingStopSelector
# data as a hash:
#
# {
# max_duration_in_seconds: 1,
# }
#
# @!attribute [rw] max_duration_in_seconds
# Specifies the maximum amount of time in seconds that you want the
# stream to be processed. The largest amount of time is 2 minutes. The
# default is 10 seconds.
# @return [Integer]
#
class StreamProcessingStopSelector < Struct.new(
:max_duration_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# An object that recognizes faces or labels in a streaming video. An
# Amazon Rekognition stream processor is created by a call to
# CreateStreamProcessor. The request parameters for
# `CreateStreamProcessor` describe the Kinesis video stream source for
# the streaming video, face recognition parameters, and where to stream
# the analysis resullts.
#
# @!attribute [rw] name
# Name of the Amazon Rekognition stream processor.
# @return [String]
#
# @!attribute [rw] status
# Current status of the Amazon Rekognition stream processor.
# @return [String]
#
class StreamProcessor < Struct.new(
:name,
:status)
SENSITIVE = []
include Aws::Structure
end
# Allows you to opt in or opt out to share data with Rekognition to
# improve model performance. You can choose this option at the account
# level or on a per-stream basis. Note that if you opt out at the
# account level this setting is ignored on individual streams.
#
# @note When making an API call, you may pass StreamProcessorDataSharingPreference
# data as a hash:
#
# {
# opt_in: false, # required
# }
#
# @!attribute [rw] opt_in
# If this option is set to true, you choose to share data with
# Rekognition to improve model performance.
# @return [Boolean]
#
class StreamProcessorDataSharingPreference < Struct.new(
:opt_in)
SENSITIVE = []
include Aws::Structure
end
# Information about the source streaming video.
#
# @note When making an API call, you may pass StreamProcessorInput
# data as a hash:
#
# {
# kinesis_video_stream: {
# arn: "KinesisVideoArn",
# },
# }
#
# @!attribute [rw] kinesis_video_stream
# The Kinesis video stream input stream for the source streaming
# video.
# @return [Types::KinesisVideoStream]
#
class StreamProcessorInput < Struct.new(
:kinesis_video_stream)
SENSITIVE = []
include Aws::Structure
end
# The Amazon Simple Notification Service topic to which Amazon
# Rekognition publishes the object detection results and completion
# status of a video analysis operation.
#
# Amazon Rekognition publishes a notification the first time an object
# of interest or a person is detected in the video stream. For example,
# if Amazon Rekognition detects a person at second 2, a pet at second 4,
# and a person again at second 5, Amazon Rekognition sends 2 object
# class detected notifications, one for a person at second 2 and one for
# a pet at second 4.
#
# Amazon Rekognition also publishes an an end-of-session notification
# with a summary when the stream processing session is complete.
#
# @note When making an API call, you may pass StreamProcessorNotificationChannel
# data as a hash:
#
# {
# sns_topic_arn: "SNSTopicArn", # required
# }
#
# @!attribute [rw] sns_topic_arn
# The Amazon Resource Number (ARN) of the Amazon Amazon Simple
# Notification Service topic to which Amazon Rekognition posts the
# completion status.
# @return [String]
#
class StreamProcessorNotificationChannel < Struct.new(
:sns_topic_arn)
SENSITIVE = []
include Aws::Structure
end
# Information about the Amazon Kinesis Data Streams stream to which a
# Amazon Rekognition Video stream processor streams the results of a
# video analysis. For more information, see CreateStreamProcessor in the
# Amazon Rekognition Developer Guide.
#
# @note When making an API call, you may pass StreamProcessorOutput
# data as a hash:
#
# {
# kinesis_data_stream: {
# arn: "KinesisDataArn",
# },
# s3_destination: {
# bucket: "S3Bucket",
# key_prefix: "S3KeyPrefix",
# },
# }
#
# @!attribute [rw] kinesis_data_stream
# The Amazon Kinesis Data Streams stream to which the Amazon
# Rekognition stream processor streams the analysis results.
# @return [Types::KinesisDataStream]
#
# @!attribute [rw] s3_destination
# The Amazon S3 bucket location to which Amazon Rekognition publishes
# the detailed inference results of a video analysis operation.
# @return [Types::S3Destination]
#
class StreamProcessorOutput < Struct.new(
:kinesis_data_stream,
:s3_destination)
SENSITIVE = []
include Aws::Structure
end
# Input parameters used in a streaming video analyzed by a Amazon
# Rekognition stream processor. You can use `FaceSearch` to recognize
# faces in a streaming video, or you can use `ConnectedHome` to detect
# labels.
#
# @note When making an API call, you may pass StreamProcessorSettings
# data as a hash:
#
# {
# face_search: {
# collection_id: "CollectionId",
# face_match_threshold: 1.0,
# },
# connected_home: {
# labels: ["ConnectedHomeLabel"], # required
# min_confidence: 1.0,
# },
# }
#
# @!attribute [rw] face_search
# Face search settings to use on a streaming video.
# @return [Types::FaceSearchSettings]
#
# @!attribute [rw] connected_home
# Label detection settings to use on a streaming video. Defining the
# settings is required in the request parameter for
# CreateStreamProcessor. Including this setting in the
# `CreateStreamProcessor` request enables you to use the stream
# processor for label detection. You can then select what you want the
# stream processor to detect, such as people or pets. When the stream
# processor has started, one notification is sent for each object
# class specified. For example, if packages and pets are selected, one
# SNS notification is published the first time a package is detected
# and one SNS notification is published the first time a pet is
# detected, as well as an end-of-session summary.
# @return [Types::ConnectedHomeSettings]
#
class StreamProcessorSettings < Struct.new(
:face_search,
:connected_home)
SENSITIVE = []
include Aws::Structure
end
# The stream processor settings that you want to update. `ConnectedHome`
# settings can be updated to detect different labels with a different
# minimum confidence.
#
# @note When making an API call, you may pass StreamProcessorSettingsForUpdate
# data as a hash:
#
# {
# connected_home_for_update: {
# labels: ["ConnectedHomeLabel"],
# min_confidence: 1.0,
# },
# }
#
# @!attribute [rw] connected_home_for_update
# The label detection settings you want to use for your stream
# processor.
# @return [Types::ConnectedHomeSettingsForUpdate]
#
class StreamProcessorSettingsForUpdate < Struct.new(
:connected_home_for_update)
SENSITIVE = []
include Aws::Structure
end
# The S3 bucket that contains the training summary. The training summary
# includes aggregated evaluation metrics for the entire testing dataset
# and metrics for each individual label.
#
# You get the training summary S3 bucket location by calling
# DescribeProjectVersions.
#
# @!attribute [rw] s3_object
# Provides the S3 bucket name and object name.
#
# The region for the S3 bucket containing the S3 object must match the
# region you use for Amazon Rekognition operations.
#
# For Amazon Rekognition to process an S3 object, the user must have
# permission to access the S3 object. For more information, see How
# Amazon Rekognition works with IAM in the Amazon Rekognition
# Developer Guide.
# @return [Types::S3Object]
#
class Summary < Struct.new(
:s3_object)
SENSITIVE = []
include Aws::Structure
end
# Indicates whether or not the face is wearing sunglasses, and the
# confidence level in the determination.
#
# @!attribute [rw] value
# Boolean value that indicates whether the face is wearing sunglasses
# or not.
# @return [Boolean]
#
# @!attribute [rw] confidence
# Level of confidence in the determination.
# @return [Float]
#
class Sunglasses < Struct.new(
:value,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass TagResourceRequest
# data as a hash:
#
# {
# resource_arn: "ResourceArn", # required
# tags: { # required
# "TagKey" => "TagValue",
# },
# }
#
# @!attribute [rw] resource_arn
# Amazon Resource Name (ARN) of the model, collection, or stream
# processor that you want to assign the tags to.
# @return [String]
#
# @!attribute [rw] tags
# The key-value tags to assign to the resource.
# @return [Hash<String,String>]
#
class TagResourceRequest < Struct.new(
:resource_arn,
:tags)
SENSITIVE = []
include Aws::Structure
end
class TagResourceResponse < Aws::EmptyStructure; end
# Information about a technical cue segment. For more information, see
# SegmentDetection.
#
# @!attribute [rw] type
# The type of the technical cue.
# @return [String]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition Video has in the accuracy of
# the detected segment.
# @return [Float]
#
class TechnicalCueSegment < Struct.new(
:type,
:confidence)
SENSITIVE = []
include Aws::Structure
end
# The dataset used for testing. Optionally, if `AutoCreate` is set,
# Amazon Rekognition Custom Labels uses the training dataset to create a
# test dataset with a temporary split of the training dataset.
#
# @note When making an API call, you may pass TestingData
# data as a hash:
#
# {
# assets: [
# {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# },
# ],
# auto_create: false,
# }
#
# @!attribute [rw] assets
# The assets used for testing.
# @return [Array<Types::Asset>]
#
# @!attribute [rw] auto_create
# If specified, Amazon Rekognition Custom Labels temporarily splits
# the training dataset (80%) to create a test dataset (20%) for the
# training job. After training completes, the test dataset is not
# stored and the training dataset reverts to its previous size.
# @return [Boolean]
#
class TestingData < Struct.new(
:assets,
:auto_create)
SENSITIVE = []
include Aws::Structure
end
# Sagemaker Groundtruth format manifest files for the input, output and
# validation datasets that are used and created during testing.
#
# @!attribute [rw] input
# The testing dataset that was supplied for training.
# @return [Types::TestingData]
#
# @!attribute [rw] output
# The subset of the dataset that was actually tested. Some images
# (assets) might not be tested due to file formatting and other
# issues.
# @return [Types::TestingData]
#
# @!attribute [rw] validation
# The location of the data validation manifest. The data validation
# manifest is created for the test dataset during model training.
# @return [Types::ValidationData]
#
class TestingDataResult < Struct.new(
:input,
:output,
:validation)
SENSITIVE = []
include Aws::Structure
end
# Information about a word or line of text detected by DetectText.
#
# The `DetectedText` field contains the text that Amazon Rekognition
# detected in the image.
#
# Every word and line has an identifier (`Id`). Each word belongs to a
# line and has a parent identifier (`ParentId`) that identifies the line
# of text in which the word appears. The word `Id` is also an index for
# the word within a line of words.
#
# For more information, see Detecting text in the Amazon Rekognition
# Developer Guide.
#
# @!attribute [rw] detected_text
# The word or line of text recognized by Amazon Rekognition.
# @return [String]
#
# @!attribute [rw] type
# The type of text that was detected.
# @return [String]
#
# @!attribute [rw] id
# The identifier for the detected text. The identifier is only unique
# for a single call to `DetectText`.
# @return [Integer]
#
# @!attribute [rw] parent_id
# The Parent identifier for the detected text identified by the value
# of `ID`. If the type of detected text is `LINE`, the value of
# `ParentId` is `Null`.
# @return [Integer]
#
# @!attribute [rw] confidence
# The confidence that Amazon Rekognition has in the accuracy of the
# detected text and the accuracy of the geometry points around the
# detected text.
# @return [Float]
#
# @!attribute [rw] geometry
# The location of the detected text on the image. Includes an axis
# aligned coarse bounding box surrounding the text and a finer grain
# polygon for more accurate spatial information.
# @return [Types::Geometry]
#
class TextDetection < Struct.new(
:detected_text,
:type,
:id,
:parent_id,
:confidence,
:geometry)
SENSITIVE = []
include Aws::Structure
end
# Information about text detected in a video. Incudes the detected text,
# the time in milliseconds from the start of the video that the text was
# detected, and where it was detected on the screen.
#
# @!attribute [rw] timestamp
# The time, in milliseconds from the start of the video, that the text
# was detected. Note that `Timestamp` is not guaranteed to be accurate
# to the individual frame where the text first appears.
# @return [Integer]
#
# @!attribute [rw] text_detection
# Details about text detected in a video.
# @return [Types::TextDetection]
#
class TextDetectionResult < Struct.new(
:timestamp,
:text_detection)
SENSITIVE = []
include Aws::Structure
end
# Amazon Rekognition is temporarily unable to process the request. Try
# your call again.
#
class ThrottlingException < Aws::EmptyStructure; end
# The dataset used for training.
#
# @note When making an API call, you may pass TrainingData
# data as a hash:
#
# {
# assets: [
# {
# ground_truth_manifest: {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# },
# },
# ],
# }
#
# @!attribute [rw] assets
# A Sagemaker GroundTruth manifest file that contains the training
# images (assets).
# @return [Array<Types::Asset>]
#
class TrainingData < Struct.new(
:assets)
SENSITIVE = []
include Aws::Structure
end
# Sagemaker Groundtruth format manifest files for the input, output and
# validation datasets that are used and created during testing.
#
# @!attribute [rw] input
# The training assets that you supplied for training.
# @return [Types::TrainingData]
#
# @!attribute [rw] output
# The images (assets) that were actually trained by Amazon Rekognition
# Custom Labels.
# @return [Types::TrainingData]
#
# @!attribute [rw] validation
# The location of the data validation manifest. The data validation
# manifest is created for the training dataset during model training.
# @return [Types::ValidationData]
#
class TrainingDataResult < Struct.new(
:input,
:output,
:validation)
SENSITIVE = []
include Aws::Structure
end
# A face that IndexFaces detected, but didn't index. Use the `Reasons`
# response attribute to determine why a face wasn't indexed.
#
# @!attribute [rw] reasons
# An array of reasons that specify why a face wasn't indexed.
#
# * EXTREME\_POSE - The face is at a pose that can't be detected. For
# example, the head is turned too far away from the camera.
#
# * EXCEEDS\_MAX\_FACES - The number of faces detected is already
# higher than that specified by the `MaxFaces` input parameter for
# `IndexFaces`.
#
# * LOW\_BRIGHTNESS - The image is too dark.
#
# * LOW\_SHARPNESS - The image is too blurry.
#
# * LOW\_CONFIDENCE - The face was detected with a low confidence.
#
# * SMALL\_BOUNDING\_BOX - The bounding box around the face is too
# small.
# @return [Array<String>]
#
# @!attribute [rw] face_detail
# The structure that contains attributes of a face that
# `IndexFaces`detected, but didn't index.
# @return [Types::FaceDetail]
#
class UnindexedFace < Struct.new(
:reasons,
:face_detail)
SENSITIVE = []
include Aws::Structure
end
# @note When making an API call, you may pass UntagResourceRequest
# data as a hash:
#
# {
# resource_arn: "ResourceArn", # required
# tag_keys: ["TagKey"], # required
# }
#
# @!attribute [rw] resource_arn
# Amazon Resource Name (ARN) of the model, collection, or stream
# processor that you want to remove the tags from.
# @return [String]
#
# @!attribute [rw] tag_keys
# A list of the tags that you want to remove.
# @return [Array<String>]
#
class UntagResourceRequest < Struct.new(
:resource_arn,
:tag_keys)
SENSITIVE = []
include Aws::Structure
end
class UntagResourceResponse < Aws::EmptyStructure; end
# @note When making an API call, you may pass UpdateDatasetEntriesRequest
# data as a hash:
#
# {
# dataset_arn: "DatasetArn", # required
# changes: { # required
# ground_truth: "data", # required
# },
# }
#
# @!attribute [rw] dataset_arn
# The Amazon Resource Name (ARN) of the dataset that you want to
# update.
# @return [String]
#
# @!attribute [rw] changes
# The changes that you want to make to the dataset.
# @return [Types::DatasetChanges]
#
class UpdateDatasetEntriesRequest < Struct.new(
:dataset_arn,
:changes)
SENSITIVE = []
include Aws::Structure
end
class UpdateDatasetEntriesResponse < Aws::EmptyStructure; end
# @note When making an API call, you may pass UpdateStreamProcessorRequest
# data as a hash:
#
# {
# name: "StreamProcessorName", # required
# settings_for_update: {
# connected_home_for_update: {
# labels: ["ConnectedHomeLabel"],
# min_confidence: 1.0,
# },
# },
# regions_of_interest_for_update: [
# {
# bounding_box: {
# width: 1.0,
# height: 1.0,
# left: 1.0,
# top: 1.0,
# },
# polygon: [
# {
# x: 1.0,
# y: 1.0,
# },
# ],
# },
# ],
# data_sharing_preference_for_update: {
# opt_in: false, # required
# },
# parameters_to_delete: ["ConnectedHomeMinConfidence"], # accepts ConnectedHomeMinConfidence, RegionsOfInterest
# }
#
# @!attribute [rw] name
# Name of the stream processor that you want to update.
# @return [String]
#
# @!attribute [rw] settings_for_update
# The stream processor settings that you want to update. Label
# detection settings can be updated to detect different labels with a
# different minimum confidence.
# @return [Types::StreamProcessorSettingsForUpdate]
#
# @!attribute [rw] regions_of_interest_for_update
# Specifies locations in the frames where Amazon Rekognition checks
# for objects or people. This is an optional parameter for label
# detection stream processors.
# @return [Array<Types::RegionOfInterest>]
#
# @!attribute [rw] data_sharing_preference_for_update
# Shows whether you are sharing data with Rekognition to improve model
# performance. You can choose this option at the account level or on a
# per-stream basis. Note that if you opt out at the account level this
# setting is ignored on individual streams.
# @return [Types::StreamProcessorDataSharingPreference]
#
# @!attribute [rw] parameters_to_delete
# A list of parameters you want to delete from the stream processor.
# @return [Array<String>]
#
class UpdateStreamProcessorRequest < Struct.new(
:name,
:settings_for_update,
:regions_of_interest_for_update,
:data_sharing_preference_for_update,
:parameters_to_delete)
SENSITIVE = []
include Aws::Structure
end
class UpdateStreamProcessorResponse < Aws::EmptyStructure; end
# Contains the Amazon S3 bucket location of the validation data for a
# model training job.
#
# The validation data includes error information for individual JSON
# Lines in the dataset. For more information, see *Debugging a Failed
# Model Training* in the Amazon Rekognition Custom Labels Developer
# Guide.
#
# You get the `ValidationData` object for the training dataset
# (TrainingDataResult) and the test dataset (TestingDataResult) by
# calling DescribeProjectVersions.
#
# The assets array contains a single Asset object. The
# GroundTruthManifest field of the Asset object contains the S3 bucket
# location of the validation data.
#
# @!attribute [rw] assets
# The assets that comprise the validation data.
# @return [Array<Types::Asset>]
#
class ValidationData < Struct.new(
:assets)
SENSITIVE = []
include Aws::Structure
end
# Video file stored in an Amazon S3 bucket. Amazon Rekognition video
# start operations such as StartLabelDetection use `Video` to specify a
# video for analysis. The supported file formats are .mp4, .mov and
# .avi.
#
# @note When making an API call, you may pass Video
# data as a hash:
#
# {
# s3_object: {
# bucket: "S3Bucket",
# name: "S3ObjectName",
# version: "S3ObjectVersion",
# },
# }
#
# @!attribute [rw] s3_object
# The Amazon S3 bucket name and file name for the video.
# @return [Types::S3Object]
#
class Video < Struct.new(
:s3_object)
SENSITIVE = []
include Aws::Structure
end
# Information about a video that Amazon Rekognition analyzed.
# `Videometadata` is returned in every page of paginated responses from
# a Amazon Rekognition video operation.
#
# @!attribute [rw] codec
# Type of compression used in the analyzed video.
# @return [String]
#
# @!attribute [rw] duration_millis
# Length of the video in milliseconds.
# @return [Integer]
#
# @!attribute [rw] format
# Format of the analyzed video. Possible values are MP4, MOV and AVI.
# @return [String]
#
# @!attribute [rw] frame_rate
# Number of frames per second in the video.
# @return [Float]
#
# @!attribute [rw] frame_height
# Vertical pixel dimension of the video.
# @return [Integer]
#
# @!attribute [rw] frame_width
# Horizontal pixel dimension of the video.
# @return [Integer]
#
# @!attribute [rw] color_range
# A description of the range of luminance values in a video, either
# LIMITED (16 to 235) or FULL (0 to 255).
# @return [String]
#
class VideoMetadata < Struct.new(
:codec,
:duration_millis,
:format,
:frame_rate,
:frame_height,
:frame_width,
:color_range)
SENSITIVE = []
include Aws::Structure
end
# The file size or duration of the supplied media is too large. The
# maximum file size is 10GB. The maximum duration is 6 hours.
#
class VideoTooLargeException < Aws::EmptyStructure; end
end
end