// Code generated by smithy-go-codegen DO NOT EDIT.

package types

import (
	smithydocument "github.com/aws/smithy-go/document"
	"time"
)

// 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.
type AgeRange struct {

	// The highest estimated age.
	High *int32

	// The lowest estimated age.
	Low *int32

	noSmithyDocumentSerde
}

// 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.
type Asset struct {

	// The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest
	// file.
	GroundTruthManifest *GroundTruthManifest

	noSmithyDocumentSerde
}

// Provides face metadata for the faces that are associated to a specific UserID.
type AssociatedFace struct {

	// Unique identifier assigned to the face.
	FaceId *string

	noSmithyDocumentSerde
}

// Metadata information about an audio stream. An array of AudioMetadata objects
// for the audio streams found in a stored video is returned by GetSegmentDetection
// .
type AudioMetadata struct {

	// The audio codec used to encode or decode the audio stream.
	Codec *string

	// The duration of the audio stream in milliseconds.
	DurationMillis *int64

	// The number of audio channels in the segment.
	NumberOfChannels *int64

	// The sample rate for the audio stream.
	SampleRate *int64

	noSmithyDocumentSerde
}

// An image that is picked from the Face Liveness video and returned for audit
// trail purposes, returned as Base64-encoded bytes.
type AuditImage struct {

	// 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. 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.
	BoundingBox *BoundingBox

	// The Base64-encoded bytes representing an image selected from the Face Liveness
	// video and returned for audit purposes.
	Bytes []byte

	// 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.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Indicates whether or not the face has a beard, and the confidence level in the
// determination.
type Beard struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the face has beard or not.
	Value bool

	noSmithyDocumentSerde
}

// 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 .
type BlackFrame struct {

	// 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.
	MaxPixelThreshold *float32

	// 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.
	MinCoveragePercentage *float32

	noSmithyDocumentSerde
}

// 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. 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.
type BoundingBox struct {

	// Height of the bounding box as a ratio of the overall image height.
	Height *float32

	// Left coordinate of the bounding box as a ratio of overall image width.
	Left *float32

	// Top coordinate of the bounding box as a ratio of overall image height.
	Top *float32

	// Width of the bounding box as a ratio of the overall image width.
	Width *float32

	noSmithyDocumentSerde
}

// Provides information about a celebrity recognized by the RecognizeCelebrities
// operation.
type Celebrity struct {

	// Provides information about the celebrity's face, such as its location on the
	// image.
	Face *ComparedFace

	// A unique identifier for the celebrity.
	Id *string

	// The known gender identity for the celebrity that matches the provided ID. The
	// known gender identity can be Male, Female, Nonbinary, or Unlisted.
	KnownGender *KnownGender

	// The confidence, in percentage, that Amazon Rekognition has that the recognized
	// face is the celebrity.
	MatchConfidence *float32

	// The name of the celebrity.
	Name *string

	// An array of URLs pointing to additional information about the celebrity. If
	// there is no additional information about the celebrity, this list is empty.
	Urls []string

	noSmithyDocumentSerde
}

// Information about a recognized celebrity.
type CelebrityDetail struct {

	// Bounding box around the body of a celebrity.
	BoundingBox *BoundingBox

	// The confidence, in percentage, that Amazon Rekognition has that the recognized
	// face is the celebrity.
	Confidence *float32

	// Face details for the recognized celebrity.
	Face *FaceDetail

	// The unique identifier for the celebrity.
	Id *string

	// Retrieves the known gender for the celebrity.
	KnownGender *KnownGender

	// The name of the celebrity.
	Name *string

	// An array of URLs pointing to additional celebrity information.
	Urls []string

	noSmithyDocumentSerde
}

// 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.
type CelebrityRecognition struct {

	// Information about a recognized celebrity.
	Celebrity *CelebrityDetail

	// 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.
	Timestamp int64

	noSmithyDocumentSerde
}

// Provides face metadata for target image faces that are analyzed by CompareFaces
// and RecognizeCelebrities .
type ComparedFace struct {

	// Bounding box of the face.
	BoundingBox *BoundingBox

	// Level of confidence that what the bounding box contains is a face.
	Confidence *float32

	// 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".
	Emotions []Emotion

	// An array of facial landmarks.
	Landmarks []Landmark

	// Indicates the pose of the face as determined by its pitch, roll, and yaw.
	Pose *Pose

	// Identifies face image brightness and sharpness.
	Quality *ImageQuality

	// Indicates whether or not the face is smiling, and the confidence level in the
	// determination.
	Smile *Smile

	noSmithyDocumentSerde
}

// 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.
type ComparedSourceImageFace struct {

	// Bounding box of the face.
	BoundingBox *BoundingBox

	// Confidence level that the selected bounding box contains a face.
	Confidence *float32

	noSmithyDocumentSerde
}

// 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.
type CompareFacesMatch struct {

	// Provides face metadata (bounding box and confidence that the bounding box
	// actually contains a face).
	Face *ComparedFace

	// Level of confidence that the faces match.
	Similarity *float32

	noSmithyDocumentSerde
}

// 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.
type ConnectedHomeSettings struct {

	// 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".
	//
	// This member is required.
	Labels []string

	// The minimum confidence required to label an object in the video.
	MinConfidence *float32

	noSmithyDocumentSerde
}

// 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.
type ConnectedHomeSettingsForUpdate struct {

	// 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".
	Labels []string

	// The minimum confidence required to label an object in the video.
	MinConfidence *float32

	noSmithyDocumentSerde
}

// Information about an inappropriate, unwanted, or offensive content label
// detection in a stored video.
type ContentModerationDetection struct {

	// The time duration of a segment in milliseconds, I.e. time elapsed from
	// StartTimestampMillis to EndTimestampMillis.
	DurationMillis *int64

	// The time in milliseconds defining the end of the timeline segment containing a
	// continuously detected moderation label.
	EndTimestampMillis *int64

	// The content moderation label detected by in the stored video.
	ModerationLabel *ModerationLabel

	// The time in milliseconds defining the start of the timeline segment containing
	// a continuously detected moderation label.
	StartTimestampMillis *int64

	// 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.
	Timestamp int64

	noSmithyDocumentSerde
}

// Information about an item of Personal Protective Equipment covering a
// corresponding body part. For more information, see DetectProtectiveEquipment .
type CoversBodyPart struct {

	// The confidence that Amazon Rekognition has in the value of Value .
	Confidence *float32

	// True if the PPE covers the corresponding body part, otherwise false.
	Value bool

	noSmithyDocumentSerde
}

// A session settings object. It contains settings for the operation to be
// performed. It accepts arguments for OutputConfig and AuditImagesLimit.
type CreateFaceLivenessSessionRequestSettings struct {

	// Number of audit images to be returned back. Takes an integer between 0-4. Any
	// integer less than 0 will return 0, any integer above 4 will return 4 images in
	// the response. By default, it is set to 0. The limit is best effort and is based
	// on the actual duration of the selfie-video.
	AuditImagesLimit *int32

	// Can specify the location of an Amazon S3 bucket, where reference and audit
	// images will be stored. Note that the Amazon S3 bucket must be located in the
	// caller's AWS account and in the same region as the Face Liveness end-point.
	// Additionally, the Amazon S3 object keys are auto-generated by the Face Liveness
	// system. Requires that the caller has the s3:PutObject permission on the Amazon
	// S3 bucket.
	OutputConfig *LivenessOutputConfig

	noSmithyDocumentSerde
}

// Feature specific configuration for the training job. Configuration provided for
// the job must match the feature type parameter associated with project. If
// configuration and feature type do not match an InvalidParameterException is
// returned.
type CustomizationFeatureConfig struct {

	// Configuration options for Custom Moderation training.
	ContentModeration *CustomizationFeatureContentModerationConfig

	noSmithyDocumentSerde
}

// Configuration options for Content Moderation training.
type CustomizationFeatureContentModerationConfig struct {

	// The confidence level you plan to use to identify if unsafe content is present
	// during inference.
	ConfidenceThreshold *float32

	noSmithyDocumentSerde
}

// A custom label detected in an image by a call to DetectCustomLabels .
type CustomLabel struct {

	// 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.
	Confidence *float32

	// 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.
	Geometry *Geometry

	// The name of the custom label.
	Name *string

	noSmithyDocumentSerde
}

// 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.
type DatasetChanges struct {

	// 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.
	//
	// This member is required.
	GroundTruth []byte

	noSmithyDocumentSerde
}

// A description for a dataset. For more information, see DescribeDataset . The
// status fields Status , StatusMessage , and StatusMessageCode reflect the last
// operation on the dataset.
type DatasetDescription struct {

	// The Unix timestamp for the time and date that the dataset was created.
	CreationTimestamp *time.Time

	// The status message code for the dataset.
	DatasetStats *DatasetStats

	// The Unix timestamp for the date and time that the dataset was last updated.
	LastUpdatedTimestamp *time.Time

	// The status of the dataset.
	Status DatasetStatus

	// The status message for the dataset.
	StatusMessage *string

	// 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.
	StatusMessageCode DatasetStatusMessageCode

	noSmithyDocumentSerde
}

// Describes a dataset label. For more information, see ListDatasetLabels .
type DatasetLabelDescription struct {

	// The name of the label.
	LabelName *string

	// Statistics about the label.
	LabelStats *DatasetLabelStats

	noSmithyDocumentSerde
}

// Statistics about a label used in a dataset. For more information, see
// DatasetLabelDescription .
type DatasetLabelStats struct {

	// The total number of images that have the label assigned to a bounding box.
	BoundingBoxCount *int32

	// The total number of images that use the label.
	EntryCount *int32

	noSmithyDocumentSerde
}

// Summary information for an Amazon Rekognition Custom Labels dataset. For more
// information, see ProjectDescription .
type DatasetMetadata struct {

	// The Unix timestamp for the date and time that the dataset was created.
	CreationTimestamp *time.Time

	// The Amazon Resource Name (ARN) for the dataset.
	DatasetArn *string

	// The type of the dataset.
	DatasetType DatasetType

	// The status for the dataset.
	Status DatasetStatus

	// The status message for the dataset.
	StatusMessage *string

	// 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.
	StatusMessageCode DatasetStatusMessageCode

	noSmithyDocumentSerde
}

// 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 .
type DatasetSource struct {

	// The ARN of an Amazon Rekognition Custom Labels dataset that you want to copy.
	DatasetArn *string

	// The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest
	// file.
	GroundTruthManifest *GroundTruthManifest

	noSmithyDocumentSerde
}

// Provides statistics about a dataset. For more information, see DescribeDataset .
type DatasetStats struct {

	// The total number of entries that contain at least one error.
	ErrorEntries *int32

	// The total number of images in the dataset that have labels.
	LabeledEntries *int32

	// The total number of images in the dataset.
	TotalEntries *int32

	// The total number of labels declared in the dataset.
	TotalLabels *int32

	noSmithyDocumentSerde
}

// A set of parameters that allow you to filter out certain results from your
// returned results.
type DetectionFilter struct {

	// 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.
	MinBoundingBoxHeight *float32

	// 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.
	MinBoundingBoxWidth *float32

	// 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.
	MinConfidence *float32

	noSmithyDocumentSerde
}

// The background of the image with regard to image quality and dominant colors.
type DetectLabelsImageBackground struct {

	// 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).
	DominantColors []DominantColor

	// The quality of the image background as defined by brightness and sharpness.
	Quality *DetectLabelsImageQuality

	noSmithyDocumentSerde
}

// The foreground of the image with regard to image quality and dominant colors.
type DetectLabelsImageForeground struct {

	// 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).
	DominantColors []DominantColor

	// The quality of the image foreground as defined by brightness and sharpness.
	Quality *DetectLabelsImageQuality

	noSmithyDocumentSerde
}

// Information about the quality and dominant colors of an input image. Quality
// and color information is returned for the entire image, foreground, and
// background.
type DetectLabelsImageProperties struct {

	// 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.
	Background *DetectLabelsImageBackground

	// 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).
	DominantColors []DominantColor

	// 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.
	Foreground *DetectLabelsImageForeground

	// 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.
	Quality *DetectLabelsImageQuality

	noSmithyDocumentSerde
}

// Settings for the IMAGE_PROPERTIES feature type.
type DetectLabelsImagePropertiesSettings struct {

	// The maximum number of dominant colors to return when detecting labels in an
	// image. The default value is 10.
	MaxDominantColors int32

	noSmithyDocumentSerde
}

// The quality of an image provided for label detection, with regard to
// brightness, sharpness, and contrast.
type DetectLabelsImageQuality struct {

	// The brightness of an image provided for label detection.
	Brightness *float32

	// The contrast of an image provided for label detection.
	Contrast *float32

	// The sharpness of an image provided for label detection.
	Sharpness *float32

	noSmithyDocumentSerde
}

// 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.
type DetectLabelsSettings struct {

	// Contains the specified filters for GENERAL_LABELS.
	GeneralLabels *GeneralLabelsSettings

	// Contains the chosen number of maximum dominant colors in an image.
	ImageProperties *DetectLabelsImagePropertiesSettings

	noSmithyDocumentSerde
}

// 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.
type DetectTextFilters struct {

	// A Filter focusing on a certain area of the image. Uses a BoundingBox object to
	// set the region of the image.
	RegionsOfInterest []RegionOfInterest

	// A set of parameters that allow you to filter out certain results from your
	// returned results.
	WordFilter *DetectionFilter

	noSmithyDocumentSerde
}

// Provides face metadata for the faces that are disassociated from a specific
// UserID.
type DisassociatedFace struct {

	// Unique identifier assigned to the face.
	FaceId *string

	noSmithyDocumentSerde
}

// A training dataset or a test dataset used in a dataset distribution operation.
// For more information, see DistributeDatasetEntries .
type DistributeDataset struct {

	// The Amazon Resource Name (ARN) of the dataset that you want to use.
	//
	// This member is required.
	Arn *string

	noSmithyDocumentSerde
}

// A description of the dominant colors in an image.
type DominantColor struct {

	// The Blue RGB value for a dominant color.
	Blue *int32

	// The CSS color name of a dominant color.
	CSSColor *string

	// The Green RGB value for a dominant color.
	Green *int32

	// The Hex code equivalent of the RGB values for a dominant color.
	HexCode *string

	// The percentage of image pixels that have a given dominant color.
	PixelPercent *float32

	// The Red RGB value for a dominant color.
	Red *int32

	// One of 12 simplified color names applied to a dominant color.
	SimplifiedColor *string

	noSmithyDocumentSerde
}

// 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.
type Emotion struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Type of emotion detected.
	Type EmotionName

	noSmithyDocumentSerde
}

// Information about an item of Personal Protective Equipment (PPE) detected by
// DetectProtectiveEquipment . For more information, see DetectProtectiveEquipment .
type EquipmentDetection struct {

	// A bounding box surrounding the item of detected PPE.
	BoundingBox *BoundingBox

	// The confidence that Amazon Rekognition has that the bounding box ( BoundingBox )
	// contains an item of PPE.
	Confidence *float32

	// Information about the body part covered by the detected PPE.
	CoversBodyPart *CoversBodyPart

	// The type of detected PPE.
	Type ProtectiveEquipmentType

	noSmithyDocumentSerde
}

// The evaluation results for the training of a model.
type EvaluationResult struct {

	// 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.
	F1Score *float32

	// The S3 bucket that contains the training summary.
	Summary *Summary

	noSmithyDocumentSerde
}

// Indicates the direction the eyes are gazing in (independent of the head pose)
// as determined by its pitch and yaw.
type EyeDirection struct {

	// The confidence that the service has in its predicted eye direction.
	Confidence *float32

	// Value representing eye direction on the pitch axis.
	Pitch *float32

	// Value representing eye direction on the yaw axis.
	Yaw *float32

	noSmithyDocumentSerde
}

// Indicates whether or not the face is wearing eye glasses, and the confidence
// level in the determination.
type Eyeglasses struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the face is wearing eye glasses or not.
	Value bool

	noSmithyDocumentSerde
}

// Indicates whether or not the eyes on the face are open, and the confidence
// level in the determination.
type EyeOpen struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the eyes on the face are open.
	Value bool

	noSmithyDocumentSerde
}

// Describes the face properties such as the bounding box, face ID, image ID of
// the input image, and external image ID that you assigned.
type Face struct {

	// Bounding box of the face.
	BoundingBox *BoundingBox

	// Confidence level that the bounding box contains a face (and not a different
	// object such as a tree).
	Confidence *float32

	// Identifier that you assign to all the faces in the input image.
	ExternalImageId *string

	// Unique identifier that Amazon Rekognition assigns to the face.
	FaceId *string

	// Unique identifier that Amazon Rekognition assigns to the input image.
	ImageId *string

	// The version of the face detect and storage model that was used when indexing
	// the face vector.
	IndexFacesModelVersion *string

	// Unique identifier assigned to the user.
	UserId *string

	noSmithyDocumentSerde
}

// 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.
type FaceDetail struct {

	// The estimated age range, in years, for the face. Low represents the lowest
	// estimated age and High represents the highest estimated age.
	AgeRange *AgeRange

	// Indicates whether or not the face has a beard, and the confidence level in the
	// determination.
	Beard *Beard

	// Bounding box of the face. Default attribute.
	BoundingBox *BoundingBox

	// Confidence level that the bounding box contains a face (and not a different
	// object such as a tree). Default attribute.
	Confidence *float32

	// 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.
	Emotions []Emotion

	// Indicates the direction the eyes are gazing in, as defined by pitch and yaw.
	EyeDirection *EyeDirection

	// Indicates whether or not the face is wearing eye glasses, and the confidence
	// level in the determination.
	Eyeglasses *Eyeglasses

	// Indicates whether or not the eyes on the face are open, and the confidence
	// level in the determination.
	EyesOpen *EyeOpen

	// FaceOccluded should return "true" with a high confidence score if a detected
	// face’s eyes, nose, and mouth are partially captured or if they are covered by
	// masks, dark sunglasses, cell phones, hands, or other objects. FaceOccluded
	// should return "false" with a high confidence score if common occurrences that do
	// not impact face verification are detected, such as eye glasses, lightly tinted
	// sunglasses, strands of hair, and others.
	FaceOccluded *FaceOccluded

	// The predicted gender of a detected face.
	Gender *Gender

	// Indicates the location of landmarks on the face. Default attribute.
	Landmarks []Landmark

	// Indicates whether or not the mouth on the face is open, and the confidence
	// level in the determination.
	MouthOpen *MouthOpen

	// Indicates whether or not the face has a mustache, and the confidence level in
	// the determination.
	Mustache *Mustache

	// Indicates the pose of the face as determined by its pitch, roll, and yaw.
	// Default attribute.
	Pose *Pose

	// Identifies image brightness and sharpness. Default attribute.
	Quality *ImageQuality

	// Indicates whether or not the face is smiling, and the confidence level in the
	// determination.
	Smile *Smile

	// Indicates whether or not the face is wearing sunglasses, and the confidence
	// level in the determination.
	Sunglasses *Sunglasses

	noSmithyDocumentSerde
}

// Information about a face detected in a video analysis request and the time the
// face was detected in the video.
type FaceDetection struct {

	// The face properties for the detected face.
	Face *FaceDetail

	// 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.
	Timestamp int64

	noSmithyDocumentSerde
}

// Provides face metadata. In addition, it also provides the confidence in the
// match of this face with the input face.
type FaceMatch struct {

	// Describes the face properties such as the bounding box, face ID, image ID of
	// the source image, and external image ID that you assigned.
	Face *Face

	// Confidence in the match of this face with the input face.
	Similarity *float32

	noSmithyDocumentSerde
}

// FaceOccluded should return "true" with a high confidence score if a detected
// face’s eyes, nose, and mouth are partially captured or if they are covered by
// masks, dark sunglasses, cell phones, hands, or other objects. FaceOccluded
// should return "false" with a high confidence score if common occurrences that do
// not impact face verification are detected, such as eye glasses, lightly tinted
// sunglasses, strands of hair, and others. You can use FaceOccluded to determine
// if an obstruction on a face negatively impacts using the image for face
// matching.
type FaceOccluded struct {

	// The confidence that the service has detected the presence of a face occlusion.
	Confidence *float32

	// True if a detected face’s eyes, nose, and mouth are partially captured or if
	// they are covered by masks, dark sunglasses, cell phones, hands, or other
	// objects. False if common occurrences that do not impact face verification are
	// detected, such as eye glasses, lightly tinted sunglasses, strands of hair, and
	// others.
	Value bool

	noSmithyDocumentSerde
}

// Object containing both the face metadata (stored in the backend database), and
// facial attributes that are detected but aren't stored in the database.
type FaceRecord struct {

	// Describes the face properties such as the bounding box, face ID, image ID of
	// the input image, and external image ID that you assigned.
	Face *Face

	// Structure containing attributes of the face that the algorithm detected.
	FaceDetail *FaceDetail

	noSmithyDocumentSerde
}

// 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 .
type FaceSearchSettings struct {

	// The ID of a collection that contains faces that you want to search for.
	CollectionId *string

	// 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.
	FaceMatchThreshold *float32

	noSmithyDocumentSerde
}

// 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.
type Gender struct {

	// Level of confidence in the prediction.
	Confidence *float32

	// The predicted gender of the face.
	Value GenderType

	noSmithyDocumentSerde
}

// 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
// labels or entire label categories. To see a list of label categories, see
// Detecting Labels (https://docs.aws.amazon.com/rekognition/latest/dg/labels.html)
// .
type GeneralLabelsSettings struct {

	// The label categories that should be excluded from the return from DetectLabels.
	LabelCategoryExclusionFilters []string

	// The label categories that should be included in the return from DetectLabels.
	LabelCategoryInclusionFilters []string

	// The labels that should be excluded from the return from DetectLabels.
	LabelExclusionFilters []string

	// The labels that should be included in the return from DetectLabels.
	LabelInclusionFilters []string

	noSmithyDocumentSerde
}

// Information about where an object ( DetectCustomLabels ) or text ( DetectText )
// is located on an image.
type Geometry struct {

	// An axis-aligned coarse representation of the detected item's location on the
	// image.
	BoundingBox *BoundingBox

	// Within the bounding box, a fine-grained polygon around the detected item.
	Polygon []Point

	noSmithyDocumentSerde
}

// Contains metadata about a content moderation request, including the SortBy and
// AggregateBy options.
type GetContentModerationRequestMetadata struct {

	// The aggregation method chosen for a GetContentModeration request.
	AggregateBy ContentModerationAggregateBy

	// The sorting method chosen for a GetContentModeration request.
	SortBy ContentModerationSortBy

	noSmithyDocumentSerde
}

// Contains metadata about a label detection request, including the SortBy and
// AggregateBy options.
type GetLabelDetectionRequestMetadata struct {

	// The aggregation method chosen for a GetLabelDetection request.
	AggregateBy LabelDetectionAggregateBy

	// The sorting method chosen for a GetLabelDetection request.
	SortBy LabelDetectionSortBy

	noSmithyDocumentSerde
}

// The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest
// file.
type GroundTruthManifest struct {

	// 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.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Shows the results of the human in the loop evaluation. If there is no
// HumanLoopArn, the input did not trigger human review.
type HumanLoopActivationOutput struct {

	// Shows the result of condition evaluations, including those conditions which
	// activated a human review.
	//
	// This value conforms to the media type: application/json
	HumanLoopActivationConditionsEvaluationResults *string

	// Shows if and why human review was needed.
	HumanLoopActivationReasons []string

	// The Amazon Resource Name (ARN) of the HumanLoop created.
	HumanLoopArn *string

	noSmithyDocumentSerde
}

// 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.
type HumanLoopConfig struct {

	// The Amazon Resource Name (ARN) of the flow definition. You can create a flow
	// definition by using the Amazon Sagemaker CreateFlowDefinition (https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateFlowDefinition.html)
	// Operation.
	//
	// This member is required.
	FlowDefinitionArn *string

	// The name of the human review used for this image. This should be kept unique
	// within a region.
	//
	// This member is required.
	HumanLoopName *string

	// Sets attributes of the input data.
	DataAttributes *HumanLoopDataAttributes

	noSmithyDocumentSerde
}

// Allows you to set attributes of the image. Currently, you can declare an image
// as free of personally identifiable information.
type HumanLoopDataAttributes struct {

	// Sets whether the input image is free of personally identifiable information.
	ContentClassifiers []ContentClassifier

	noSmithyDocumentSerde
}

// 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.
type Image struct {

	// Blob of image bytes up to 5 MBs. Note that the maximum image size you can pass
	// to DetectCustomLabels is 4MB.
	Bytes []byte

	// Identifies an S3 object as the image source.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Identifies face image brightness and sharpness.
type ImageQuality struct {

	// Value representing brightness of the face. The service returns a value between
	// 0 and 100 (inclusive). A higher value indicates a brighter face image.
	Brightness *float32

	// Value representing sharpness of the face. The service returns a value between 0
	// and 100 (inclusive). A higher value indicates a sharper face image.
	Sharpness *float32

	noSmithyDocumentSerde
}

// An instance of a label returned by Amazon Rekognition Image ( DetectLabels ) or
// by Amazon Rekognition Video ( GetLabelDetection ).
type Instance struct {

	// The position of the label instance on the image.
	BoundingBox *BoundingBox

	// The confidence that Amazon Rekognition has in the accuracy of the bounding box.
	Confidence *float32

	// The dominant colors found in an individual instance of a label.
	DominantColors []DominantColor

	noSmithyDocumentSerde
}

// 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.
type KinesisDataStream struct {

	// ARN of the output Amazon Kinesis Data Streams stream.
	Arn *string

	noSmithyDocumentSerde
}

// 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.
type KinesisVideoStream struct {

	// ARN of the Kinesis video stream stream that streams the source video.
	Arn *string

	noSmithyDocumentSerde
}

// 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 (https://docs.aws.amazon.com/kinesisvideostreams/latest/dg/API_reader_Fragment.html)
// .
type KinesisVideoStreamStartSelector struct {

	// The unique identifier of the fragment. This value monotonically increases based
	// on the ingestion order.
	FragmentNumber *string

	// The timestamp from the producer corresponding to the fragment, in milliseconds,
	// expressed in unix time format.
	ProducerTimestamp *int64

	noSmithyDocumentSerde
}

// The known gender identity for the celebrity that matches the provided ID. The
// known gender identity can be Male, Female, Nonbinary, or Unlisted.
type KnownGender struct {

	// A string value of the KnownGender info about the Celebrity.
	Type KnownGenderType

	noSmithyDocumentSerde
}

// Structure containing details about the detected label, including the name,
// detected instances, parent labels, and level of confidence.
type Label struct {

	// A list of potential aliases for a given label.
	Aliases []LabelAlias

	// A list of the categories associated with a given label.
	Categories []LabelCategory

	// Level of confidence.
	Confidence *float32

	// 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.
	Instances []Instance

	// The name (label) of the object or scene.
	Name *string

	// The parent labels for a label. The response includes all ancestor labels.
	Parents []Parent

	noSmithyDocumentSerde
}

// A potential alias of for a given label.
type LabelAlias struct {

	// The name of an alias for a given label.
	Name *string

	noSmithyDocumentSerde
}

// The category that applies to a given label.
type LabelCategory struct {

	// The name of a category that applies to a given label.
	Name *string

	noSmithyDocumentSerde
}

// Information about a label detected in a video analysis request and the time the
// label was detected in the video.
type LabelDetection struct {

	// The time duration of a segment in milliseconds, I.e. time elapsed from
	// StartTimestampMillis to EndTimestampMillis.
	DurationMillis *int64

	// The time in milliseconds defining the end of the timeline segment containing a
	// continuously detected label.
	EndTimestampMillis *int64

	// Details about the detected label.
	Label *Label

	// The time in milliseconds defining the start of the timeline segment containing
	// a continuously detected label.
	StartTimestampMillis *int64

	// 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.
	Timestamp int64

	noSmithyDocumentSerde
}

// Contains the specified filters that should be applied to a list of returned
// GENERAL_LABELS.
type LabelDetectionSettings struct {

	// 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
	// labels or entire label categories. To see a list of label categories, see
	// Detecting Labels (https://docs.aws.amazon.com/rekognition/latest/dg/labels.html)
	// .
	GeneralLabels *GeneralLabelsSettings

	noSmithyDocumentSerde
}

// Indicates the location of the landmark on the face.
type Landmark struct {

	// Type of landmark.
	Type LandmarkType

	// 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.
	X *float32

	// 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.
	Y *float32

	noSmithyDocumentSerde
}

// Contains settings that specify the location of an Amazon S3 bucket used to
// store the output of a Face Liveness session. Note that the S3 bucket must be
// located in the caller's AWS account and in the same region as the Face Liveness
// end-point. Additionally, the Amazon S3 object keys are auto-generated by the
// Face Liveness system.
type LivenessOutputConfig struct {

	// The path to an AWS Amazon S3 bucket used to store Face Liveness session results.
	//
	// This member is required.
	S3Bucket *string

	// The prefix prepended to the output files for the Face Liveness session results.
	S3KeyPrefix *string

	noSmithyDocumentSerde
}

// Contains metadata for a UserID matched with a given face.
type MatchedUser struct {

	// A provided ID for the UserID. Unique within the collection.
	UserId *string

	// The status of the user matched to a provided FaceID.
	UserStatus UserStatus

	noSmithyDocumentSerde
}

// Configuration for Moderation Labels Detection.
type MediaAnalysisDetectModerationLabelsConfig struct {

	// Specifies the minimum confidence level for the moderation labels to return.
	// Amazon Rekognition doesn't return any labels with a confidence level lower than
	// this specified value.
	MinConfidence *float32

	// Specifies the custom moderation model to be used during the label detection
	// job. If not provided the pre-trained model is used.
	ProjectVersion *string

	noSmithyDocumentSerde
}

// Contains input information for a media analysis job.
type MediaAnalysisInput struct {

	// 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.
	//
	// This member is required.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Description for a media analysis job.
type MediaAnalysisJobDescription struct {

	// The Unix date and time when the job was started.
	//
	// This member is required.
	CreationTimestamp *time.Time

	// Reference to the input manifest that was provided in the job creation request.
	//
	// This member is required.
	Input *MediaAnalysisInput

	// The identifier for a media analysis job.
	//
	// This member is required.
	JobId *string

	// Operation configurations that were provided during job creation.
	//
	// This member is required.
	OperationsConfig *MediaAnalysisOperationsConfig

	// Output configuration that was provided in the creation request.
	//
	// This member is required.
	OutputConfig *MediaAnalysisOutputConfig

	// The status of the media analysis job being retrieved.
	//
	// This member is required.
	Status MediaAnalysisJobStatus

	// The Unix date and time when the job finished.
	CompletionTimestamp *time.Time

	// Details about the error that resulted in failure of the job.
	FailureDetails *MediaAnalysisJobFailureDetails

	// The name of a media analysis job.
	JobName *string

	// KMS Key that was provided in the creation request.
	KmsKeyId *string

	// Provides statistics on input manifest and errors identified in the input
	// manifest.
	ManifestSummary *MediaAnalysisManifestSummary

	// Output manifest that contains prediction results.
	Results *MediaAnalysisResults

	noSmithyDocumentSerde
}

// Details about the error that resulted in failure of the job.
type MediaAnalysisJobFailureDetails struct {

	// Error code for the failed job.
	Code MediaAnalysisJobFailureCode

	// Human readable error message.
	Message *string

	noSmithyDocumentSerde
}

// Summary that provides statistics on input manifest and errors identified in the
// input manifest.
type MediaAnalysisManifestSummary struct {

	// 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.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Configuration options for a media analysis job. Configuration is
// operation-specific.
type MediaAnalysisOperationsConfig struct {

	// Contains configuration options for a DetectModerationLabels job.
	DetectModerationLabels *MediaAnalysisDetectModerationLabelsConfig

	noSmithyDocumentSerde
}

// Output configuration provided in the job creation request.
type MediaAnalysisOutputConfig struct {

	// Specifies the Amazon S3 bucket to contain the output of the media analysis job.
	//
	// This member is required.
	S3Bucket *string

	// Specifies the Amazon S3 key prefix that comes after the name of the bucket you
	// have designated for storage.
	S3KeyPrefix *string

	noSmithyDocumentSerde
}

// Contains the results for a media analysis job created with
// StartMediaAnalysisJob.
type MediaAnalysisResults struct {

	// 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.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// 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.
type ModerationLabel struct {

	// 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.
	Confidence *float32

	// The label name for the type of unsafe content detected in the image.
	Name *string

	// The name for the parent label. Labels at the top level of the hierarchy have
	// the parent label "" .
	ParentName *string

	noSmithyDocumentSerde
}

// Indicates whether or not the mouth on the face is open, and the confidence
// level in the determination.
type MouthOpen struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the mouth on the face is open or not.
	Value bool

	noSmithyDocumentSerde
}

// Indicates whether or not the face has a mustache, and the confidence level in
// the determination.
type Mustache struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the face has mustache or not.
	Value bool

	noSmithyDocumentSerde
}

// 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 (https://docs.aws.amazon.com/rekognition/latest/dg/api-video.html)
// . 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 (https://docs.aws.amazon.com/rekognition/latest/dg/api-video-roles.html#api-video-roles-all-topics)
// .
type NotificationChannel struct {

	// The ARN of an IAM role that gives Amazon Rekognition publishing permissions to
	// the Amazon SNS topic.
	//
	// This member is required.
	RoleArn *string

	// The Amazon SNS topic to which Amazon Rekognition posts the completion status.
	//
	// This member is required.
	SNSTopicArn *string

	noSmithyDocumentSerde
}

// The S3 bucket and folder location where training output is placed.
type OutputConfig struct {

	// The S3 bucket where training output is placed.
	S3Bucket *string

	// The prefix applied to the training output files.
	S3KeyPrefix *string

	noSmithyDocumentSerde
}

// A parent label for a label. A label can have 0, 1, or more parents.
type Parent struct {

	// The name of the parent label.
	Name *string

	noSmithyDocumentSerde
}

// Details about a person detected in a video analysis request.
type PersonDetail struct {

	// Bounding box around the detected person.
	BoundingBox *BoundingBox

	// Face details for the detected person.
	Face *FaceDetail

	// 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.
	Index int64

	noSmithyDocumentSerde
}

// 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.
type PersonDetection struct {

	// Details about a person whose path was tracked in a video.
	Person *PersonDetail

	// 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.
	Timestamp int64

	noSmithyDocumentSerde
}

// 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 .
type PersonMatch struct {

	// Information about the faces in the input collection that match the face of a
	// person in the video.
	FaceMatches []FaceMatch

	// Information about the matched person.
	Person *PersonDetail

	// The time, in milliseconds from the beginning of the video, that the person was
	// matched in the video.
	Timestamp int64

	noSmithyDocumentSerde
}

// 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.
type Point struct {

	// The value of the X coordinate for a point on a Polygon .
	X *float32

	// The value of the Y coordinate for a point on a Polygon .
	Y *float32

	noSmithyDocumentSerde
}

// Indicates the pose of the face as determined by its pitch, roll, and yaw.
type Pose struct {

	// Value representing the face rotation on the pitch axis.
	Pitch *float32

	// Value representing the face rotation on the roll axis.
	Roll *float32

	// Value representing the face rotation on the yaw axis.
	Yaw *float32

	noSmithyDocumentSerde
}

// A description of an Amazon Rekognition Custom Labels project. For more
// information, see DescribeProjects .
type ProjectDescription struct {

	// Indicates whether automatic retraining will be attempted for the versions of
	// the project. Applies only to adapters.
	AutoUpdate ProjectAutoUpdate

	// The Unix timestamp for the date and time that the project was created.
	CreationTimestamp *time.Time

	// Information about the training and test datasets in the project.
	Datasets []DatasetMetadata

	// Specifies the project that is being customized.
	Feature CustomizationFeature

	// The Amazon Resource Name (ARN) of the project.
	ProjectArn *string

	// The current status of the project.
	Status ProjectStatus

	noSmithyDocumentSerde
}

// Describes a project policy in the response from ListProjectPolicies .
type ProjectPolicy struct {

	// The Unix datetime for the creation of the project policy.
	CreationTimestamp *time.Time

	// The Unix datetime for when the project policy was last updated.
	LastUpdatedTimestamp *time.Time

	// The JSON document for the project policy.
	PolicyDocument *string

	// The name of the project policy.
	PolicyName *string

	// The revision ID of the project policy.
	PolicyRevisionId *string

	// The Amazon Resource Name (ARN) of the project to which the project policy is
	// attached.
	ProjectArn *string

	noSmithyDocumentSerde
}

// A description of a version of a Amazon Rekognition project version.
type ProjectVersionDescription struct {

	// The base detection model version used to create the project version.
	BaseModelVersion *string

	// 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.
	BillableTrainingTimeInSeconds *int64

	// The Unix datetime for the date and time that training started.
	CreationTimestamp *time.Time

	// The training results. EvaluationResult is only returned if training is
	// successful.
	EvaluationResult *EvaluationResult

	// The feature that was customized.
	Feature CustomizationFeature

	// Feature specific configuration that was applied during training.
	FeatureConfig *CustomizationFeatureConfig

	// The identifer for the AWS Key Management Service key (AWS KMS key) that was
	// used to encrypt the model during training.
	KmsKeyId *string

	// The location of the summary manifest. The summary manifest provides aggregate
	// data validation results for the training and test datasets.
	ManifestSummary *GroundTruthManifest

	// The maximum number of inference units Amazon Rekognition uses to auto-scale the
	// model. Applies only to Custom Labels projects. For more information, see
	// StartProjectVersion .
	MaxInferenceUnits *int32

	// The minimum number of inference units used by the model. Applies only to Custom
	// Labels projects. For more information, see StartProjectVersion .
	MinInferenceUnits *int32

	// The location where training results are saved.
	OutputConfig *OutputConfig

	// The Amazon Resource Name (ARN) of the project version.
	ProjectVersionArn *string

	// If the model version was copied from a different project,
	// SourceProjectVersionArn contains the ARN of the source model version.
	SourceProjectVersionArn *string

	// The current status of the model version.
	Status ProjectVersionStatus

	// A descriptive message for an error or warning that occurred.
	StatusMessage *string

	// Contains information about the testing results.
	TestingDataResult *TestingDataResult

	// Contains information about the training results.
	TrainingDataResult *TrainingDataResult

	// The Unix date and time that training of the model ended.
	TrainingEndTimestamp *time.Time

	// A user-provided description of the project version.
	VersionDescription *string

	noSmithyDocumentSerde
}

// Information about a body part detected by DetectProtectiveEquipment that
// contains PPE. An array of ProtectiveEquipmentBodyPart objects is returned for
// each person detected by DetectProtectiveEquipment .
type ProtectiveEquipmentBodyPart struct {

	// The confidence that Amazon Rekognition has in the detection accuracy of the
	// detected body part.
	Confidence *float32

	// An array of Personal Protective Equipment items detected around a body part.
	EquipmentDetections []EquipmentDetection

	// The detected body part.
	Name BodyPart

	noSmithyDocumentSerde
}

// A person detected by a call to DetectProtectiveEquipment . The API returns all
// persons detected in the input image in an array of ProtectiveEquipmentPerson
// objects.
type ProtectiveEquipmentPerson struct {

	// An array of body parts detected on a person's body (including body parts
	// without PPE).
	BodyParts []ProtectiveEquipmentBodyPart

	// A bounding box around the detected person.
	BoundingBox *BoundingBox

	// The confidence that Amazon Rekognition has that the bounding box contains a
	// person.
	Confidence *float32

	// The identifier for the detected person. The identifier is only unique for a
	// single call to DetectProtectiveEquipment .
	Id *int32

	noSmithyDocumentSerde
}

// 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 .
type ProtectiveEquipmentSummarizationAttributes struct {

	// 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%.
	//
	// This member is required.
	MinConfidence *float32

	// 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 .
	//
	// This member is required.
	RequiredEquipmentTypes []ProtectiveEquipmentType

	noSmithyDocumentSerde
}

// 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 .
type ProtectiveEquipmentSummary struct {

	// An array of IDs for persons where it was not possible to determine if they are
	// wearing personal protective equipment.
	PersonsIndeterminate []int32

	// An array of IDs for persons who are wearing detected personal protective
	// equipment.
	PersonsWithRequiredEquipment []int32

	// 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.
	PersonsWithoutRequiredEquipment []int32

	noSmithyDocumentSerde
}

// 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.
type RegionOfInterest struct {

	// The box representing a region of interest on screen.
	BoundingBox *BoundingBox

	// Specifies a shape made up of up to 10 Point objects to define a region of
	// interest.
	Polygon []Point

	noSmithyDocumentSerde
}

// 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.
type S3Destination struct {

	// 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.
	Bucket *string

	// The prefix value of the location within the bucket that you want the
	// information to be published to. For more information, see Using prefixes (https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-prefixes.html)
	// .
	KeyPrefix *string

	noSmithyDocumentSerde
}

// 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.
type S3Object struct {

	// Name of the S3 bucket.
	Bucket *string

	// S3 object key name.
	Name *string

	// If the bucket is versioning enabled, you can specify the object version.
	Version *string

	noSmithyDocumentSerde
}

// Provides face metadata such as FaceId, BoundingBox, Confidence of the input
// face used for search.
type SearchedFace struct {

	// Unique identifier assigned to the face.
	FaceId *string

	noSmithyDocumentSerde
}

// Contains data regarding the input face used for a search.
type SearchedFaceDetails struct {

	// 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.
	FaceDetail *FaceDetail

	noSmithyDocumentSerde
}

// Contains metadata about a User searched for within a collection.
type SearchedUser struct {

	// A provided ID for the UserID. Unique within the collection.
	UserId *string

	noSmithyDocumentSerde
}

// 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 .
type SegmentDetection struct {

	// The duration of a video segment, expressed in frames.
	DurationFrames *int64

	// The duration of the detected segment in milliseconds.
	DurationMillis *int64

	// The duration of the timecode for the detected segment in SMPTE format.
	DurationSMPTE *string

	// The frame number at the end of a video segment, using a frame index that starts
	// with 0.
	EndFrameNumber *int64

	// 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).
	EndTimecodeSMPTE *string

	// The end time of the detected segment, in milliseconds, from the start of the
	// video. This value is rounded down.
	EndTimestampMillis int64

	// If the segment is a shot detection, contains information about the shot
	// detection.
	ShotSegment *ShotSegment

	// The frame number of the start of a video segment, using a frame index that
	// starts with 0.
	StartFrameNumber *int64

	// 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).
	StartTimecodeSMPTE *string

	// 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.
	StartTimestampMillis int64

	// If the segment is a technical cue, contains information about the technical cue.
	TechnicalCueSegment *TechnicalCueSegment

	// The type of the segment. Valid values are TECHNICAL_CUE and SHOT .
	Type SegmentType

	noSmithyDocumentSerde
}

// 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 .
type SegmentTypeInfo struct {

	// The version of the model used to detect segments.
	ModelVersion *string

	// The type of a segment (technical cue or shot detection).
	Type SegmentType

	noSmithyDocumentSerde
}

// Information about a shot detection segment detected in a video. For more
// information, see SegmentDetection .
type ShotSegment struct {

	// The confidence that Amazon Rekognition Video has in the accuracy of the
	// detected segment.
	Confidence *float32

	// An Identifier for a shot detection segment detected in a video.
	Index *int64

	noSmithyDocumentSerde
}

// Indicates whether or not the face is smiling, and the confidence level in the
// determination.
type Smile struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the face is smiling or not.
	Value bool

	noSmithyDocumentSerde
}

// Filters applied to the technical cue or shot detection segments. For more
// information, see StartSegmentDetection .
type StartSegmentDetectionFilters struct {

	// Filters that are specific to shot detections.
	ShotFilter *StartShotDetectionFilter

	// Filters that are specific to technical cues.
	TechnicalCueFilter *StartTechnicalCueDetectionFilter

	noSmithyDocumentSerde
}

// Filters for the shot detection segments returned by GetSegmentDetection . For
// more information, see StartSegmentDetectionFilters .
type StartShotDetectionFilter struct {

	// 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.
	MinSegmentConfidence *float32

	noSmithyDocumentSerde
}

// Filters for the technical segments returned by GetSegmentDetection . For more
// information, see StartSegmentDetectionFilters .
type StartTechnicalCueDetectionFilter struct {

	// 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.
	BlackFrame *BlackFrame

	// 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.
	MinSegmentConfidence *float32

	noSmithyDocumentSerde
}

// 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.
type StartTextDetectionFilters struct {

	// Filter focusing on a certain area of the frame. Uses a BoundingBox object to
	// set the region of the screen.
	RegionsOfInterest []RegionOfInterest

	// Filters focusing on qualities of the text, such as confidence or size.
	WordFilter *DetectionFilter

	noSmithyDocumentSerde
}

// This is a required parameter for label detection stream processors and should
// not be used to start a face search stream processor.
type StreamProcessingStartSelector struct {

	// 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.
	KVSStreamStartSelector *KinesisVideoStreamStartSelector

	noSmithyDocumentSerde
}

// Specifies when to stop processing the stream. You can specify a maximum amount
// of time to process the video.
type StreamProcessingStopSelector struct {

	// 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.
	MaxDurationInSeconds *int64

	noSmithyDocumentSerde
}

// 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.
type StreamProcessor struct {

	// Name of the Amazon Rekognition stream processor.
	Name *string

	// Current status of the Amazon Rekognition stream processor.
	Status StreamProcessorStatus

	noSmithyDocumentSerde
}

// 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.
type StreamProcessorDataSharingPreference struct {

	// If this option is set to true, you choose to share data with Rekognition to
	// improve model performance.
	//
	// This member is required.
	OptIn bool

	noSmithyDocumentSerde
}

// Information about the source streaming video.
type StreamProcessorInput struct {

	// The Kinesis video stream input stream for the source streaming video.
	KinesisVideoStream *KinesisVideoStream

	noSmithyDocumentSerde
}

// 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.
type StreamProcessorNotificationChannel struct {

	// The Amazon Resource Number (ARN) of the Amazon Amazon Simple Notification
	// Service topic to which Amazon Rekognition posts the completion status.
	//
	// This member is required.
	SNSTopicArn *string

	noSmithyDocumentSerde
}

// 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.
type StreamProcessorOutput struct {

	// The Amazon Kinesis Data Streams stream to which the Amazon Rekognition stream
	// processor streams the analysis results.
	KinesisDataStream *KinesisDataStream

	// The Amazon S3 bucket location to which Amazon Rekognition publishes the
	// detailed inference results of a video analysis operation.
	S3Destination *S3Destination

	noSmithyDocumentSerde
}

// 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.
type StreamProcessorSettings struct {

	// 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.
	ConnectedHome *ConnectedHomeSettings

	// Face search settings to use on a streaming video.
	FaceSearch *FaceSearchSettings

	noSmithyDocumentSerde
}

// The stream processor settings that you want to update. ConnectedHome settings
// can be updated to detect different labels with a different minimum confidence.
type StreamProcessorSettingsForUpdate struct {

	// The label detection settings you want to use for your stream processor.
	ConnectedHomeForUpdate *ConnectedHomeSettingsForUpdate

	noSmithyDocumentSerde
}

// 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 .
type Summary struct {

	// 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.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Indicates whether or not the face is wearing sunglasses, and the confidence
// level in the determination.
type Sunglasses struct {

	// Level of confidence in the determination.
	Confidence *float32

	// Boolean value that indicates whether the face is wearing sunglasses or not.
	Value bool

	noSmithyDocumentSerde
}

// Information about a technical cue segment. For more information, see
// SegmentDetection .
type TechnicalCueSegment struct {

	// The confidence that Amazon Rekognition Video has in the accuracy of the
	// detected segment.
	Confidence *float32

	// The type of the technical cue.
	Type TechnicalCueType

	noSmithyDocumentSerde
}

// The dataset used for testing. Optionally, if AutoCreate is set, Amazon
// Rekognition uses the training dataset to create a test dataset with a temporary
// split of the training dataset.
type TestingData struct {

	// The assets used for testing.
	Assets []Asset

	// If specified, Rekognition splits training dataset to create a test dataset for
	// the training job.
	AutoCreate bool

	noSmithyDocumentSerde
}

// Sagemaker Groundtruth format manifest files for the input, output and
// validation datasets that are used and created during testing.
type TestingDataResult struct {

	// The testing dataset that was supplied for training.
	Input *TestingData

	// The subset of the dataset that was actually tested. Some images (assets) might
	// not be tested due to file formatting and other issues.
	Output *TestingData

	// The location of the data validation manifest. The data validation manifest is
	// created for the test dataset during model training.
	Validation *ValidationData

	noSmithyDocumentSerde
}

// 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.
type TextDetection struct {

	// The confidence that Amazon Rekognition has in the accuracy of the detected text
	// and the accuracy of the geometry points around the detected text.
	Confidence *float32

	// The word or line of text recognized by Amazon Rekognition.
	DetectedText *string

	// 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.
	Geometry *Geometry

	// The identifier for the detected text. The identifier is only unique for a
	// single call to DetectText .
	Id *int32

	// 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 .
	ParentId *int32

	// The type of text that was detected.
	Type TextTypes

	noSmithyDocumentSerde
}

// 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.
type TextDetectionResult struct {

	// Details about text detected in a video.
	TextDetection *TextDetection

	// 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.
	Timestamp int64

	noSmithyDocumentSerde
}

// The dataset used for training.
type TrainingData struct {

	// A manifest file that contains references to the training images and
	// ground-truth annotations.
	Assets []Asset

	noSmithyDocumentSerde
}

// The data validation manifest created for the training dataset during model
// training.
type TrainingDataResult struct {

	// The training data that you supplied.
	Input *TrainingData

	// Reference to images (assets) that were actually used during training with
	// trained model predictions.
	Output *TrainingData

	// A manifest that you supplied for training, with validation results for each
	// line.
	Validation *ValidationData

	noSmithyDocumentSerde
}

// A face that IndexFaces detected, but didn't index. Use the Reasons response
// attribute to determine why a face wasn't indexed.
type UnindexedFace struct {

	// The structure that contains attributes of a face that IndexFaces detected, but
	// didn't index.
	FaceDetail *FaceDetail

	// 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.
	Reasons []Reason

	noSmithyDocumentSerde
}

// Face details inferred from the image but not used for search. The response
// attribute contains reasons for why a face wasn't used for Search.
type UnsearchedFace struct {

	// 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.
	FaceDetails *FaceDetail

	// Reasons why a face wasn't used for Search.
	Reasons []UnsearchedFaceReason

	noSmithyDocumentSerde
}

// Contains metadata like FaceId, UserID, and Reasons, for a face that was
// unsuccessfully associated.
type UnsuccessfulFaceAssociation struct {

	// Match confidence with the UserID, provides information regarding if a face
	// association was unsuccessful because it didn't meet UserMatchThreshold.
	Confidence *float32

	// A unique identifier assigned to the face.
	FaceId *string

	// The reason why the association was unsuccessful.
	Reasons []UnsuccessfulFaceAssociationReason

	// A provided ID for the UserID. Unique within the collection.
	UserId *string

	noSmithyDocumentSerde
}

// Contains metadata like FaceId, UserID, and Reasons, for a face that was
// unsuccessfully deleted.
type UnsuccessfulFaceDeletion struct {

	// A unique identifier assigned to the face.
	FaceId *string

	// The reason why the deletion was unsuccessful.
	Reasons []UnsuccessfulFaceDeletionReason

	// A provided ID for the UserID. Unique within the collection.
	UserId *string

	noSmithyDocumentSerde
}

// Contains metadata like FaceId, UserID, and Reasons, for a face that was
// unsuccessfully disassociated.
type UnsuccessfulFaceDisassociation struct {

	// A unique identifier assigned to the face.
	FaceId *string

	// The reason why the deletion was unsuccessful.
	Reasons []UnsuccessfulFaceDisassociationReason

	// A provided ID for the UserID. Unique within the collection.
	UserId *string

	noSmithyDocumentSerde
}

// Metadata of the user stored in a collection.
type User struct {

	// A provided ID for the User. Unique within the collection.
	UserId *string

	// Communicates if the UserID has been updated with latest set of faces to be
	// associated with the UserID.
	UserStatus UserStatus

	noSmithyDocumentSerde
}

// Provides UserID metadata along with the confidence in the match of this UserID
// with the input face.
type UserMatch struct {

	// Describes the UserID metadata.
	Similarity *float32

	// Confidence in the match of this UserID with the input face.
	User *MatchedUser

	noSmithyDocumentSerde
}

// 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.
type ValidationData struct {

	// The assets that comprise the validation data.
	Assets []Asset

	noSmithyDocumentSerde
}

// 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.
type Video struct {

	// The Amazon S3 bucket name and file name for the video.
	S3Object *S3Object

	noSmithyDocumentSerde
}

// Information about a video that Amazon Rekognition analyzed. Videometadata is
// returned in every page of paginated responses from a Amazon Rekognition video
// operation.
type VideoMetadata struct {

	// Type of compression used in the analyzed video.
	Codec *string

	// A description of the range of luminance values in a video, either LIMITED (16
	// to 235) or FULL (0 to 255).
	ColorRange VideoColorRange

	// Length of the video in milliseconds.
	DurationMillis *int64

	// Format of the analyzed video. Possible values are MP4, MOV and AVI.
	Format *string

	// Vertical pixel dimension of the video.
	FrameHeight *int64

	// Number of frames per second in the video.
	FrameRate *float32

	// Horizontal pixel dimension of the video.
	FrameWidth *int64

	noSmithyDocumentSerde
}

type noSmithyDocumentSerde = smithydocument.NoSerde