| Copyright | (c) 2013-2018 Brendan Hay |
|---|---|
| License | Mozilla Public License, v. 2.0. |
| Maintainer | Brendan Hay <brendan.g.hay+amazonka@gmail.com> |
| Stability | auto-generated |
| Portability | non-portable (GHC extensions) |
| Safe Haskell | None |
| Language | Haskell2010 |
Network.AWS.Rekognition
Contents
- Service Configuration
- Errors
- AccessDeniedException
- VideoTooLargeException
- InvalidParameterException
- InvalidImageFormatException
- ResourceAlreadyExistsException
- InvalidS3ObjectException
- ProvisionedThroughputExceededException
- ImageTooLargeException
- ThrottlingException
- InternalServerError
- IdempotentParameterMismatchException
- ResourceNotFoundException
- InvalidPaginationTokenException
- LimitExceededException
- ResourceInUseException
- Waiters
- Operations
- StartCelebrityRecognition
- GetPersonTracking
- ListCollections (Paginated)
- DeleteCollection
- CreateCollection
- StopStreamProcessor
- DetectLabels
- StartContentModeration
- SearchFacesByImage
- ListStreamProcessors (Paginated)
- RecognizeCelebrities
- GetFaceSearch
- StartLabelDetection
- SearchFaces
- IndexFaces
- GetLabelDetection
- DescribeStreamProcessor
- StartFaceSearch
- StartPersonTracking
- GetCelebrityRecognition
- StartStreamProcessor
- DetectText
- CompareFaces
- DetectFaces
- GetFaceDetection
- ListFaces (Paginated)
- GetContentModeration
- DeleteFaces
- GetCelebrityInfo
- DeleteStreamProcessor
- DetectModerationLabels
- CreateStreamProcessor
- StartFaceDetection
- Types
- Attribute
- CelebrityRecognitionSortBy
- ContentModerationSortBy
- EmotionName
- FaceAttributes
- FaceSearchSortBy
- GenderType
- LabelDetectionSortBy
- LandmarkType
- OrientationCorrection
- PersonTrackingSortBy
- StreamProcessorStatus
- TextTypes
- VideoJobStatus
- AgeRange
- Beard
- BoundingBox
- Celebrity
- CelebrityDetail
- CelebrityRecognition
- CompareFacesMatch
- ComparedFace
- ComparedSourceImageFace
- ContentModerationDetection
- Emotion
- EyeOpen
- Eyeglasses
- Face
- FaceDetail
- FaceDetection
- FaceMatch
- FaceRecord
- FaceSearchSettings
- Gender
- Geometry
- Image
- ImageQuality
- KinesisDataStream
- KinesisVideoStream
- Label
- LabelDetection
- Landmark
- ModerationLabel
- MouthOpen
- Mustache
- NotificationChannel
- PersonDetail
- PersonDetection
- PersonMatch
- Point
- Pose
- S3Object
- Smile
- StreamProcessor
- StreamProcessorInput
- StreamProcessorOutput
- StreamProcessorSettings
- Sunglasses
- TextDetection
- Video
- VideoMetadata
Description
This is the Amazon Rekognition API reference.
Synopsis
- rekognition :: Service
- _AccessDeniedException :: AsError a => Getting (First ServiceError) a ServiceError
- _VideoTooLargeException :: AsError a => Getting (First ServiceError) a ServiceError
- _InvalidParameterException :: AsError a => Getting (First ServiceError) a ServiceError
- _InvalidImageFormatException :: AsError a => Getting (First ServiceError) a ServiceError
- _ResourceAlreadyExistsException :: AsError a => Getting (First ServiceError) a ServiceError
- _InvalidS3ObjectException :: AsError a => Getting (First ServiceError) a ServiceError
- _ProvisionedThroughputExceededException :: AsError a => Getting (First ServiceError) a ServiceError
- _ImageTooLargeException :: AsError a => Getting (First ServiceError) a ServiceError
- _ThrottlingException :: AsError a => Getting (First ServiceError) a ServiceError
- _InternalServerError :: AsError a => Getting (First ServiceError) a ServiceError
- _IdempotentParameterMismatchException :: AsError a => Getting (First ServiceError) a ServiceError
- _ResourceNotFoundException :: AsError a => Getting (First ServiceError) a ServiceError
- _InvalidPaginationTokenException :: AsError a => Getting (First ServiceError) a ServiceError
- _LimitExceededException :: AsError a => Getting (First ServiceError) a ServiceError
- _ResourceInUseException :: AsError a => Getting (First ServiceError) a ServiceError
- module Network.AWS.Rekognition.StartCelebrityRecognition
- module Network.AWS.Rekognition.GetPersonTracking
- module Network.AWS.Rekognition.ListCollections
- module Network.AWS.Rekognition.DeleteCollection
- module Network.AWS.Rekognition.CreateCollection
- module Network.AWS.Rekognition.StopStreamProcessor
- module Network.AWS.Rekognition.DetectLabels
- module Network.AWS.Rekognition.StartContentModeration
- module Network.AWS.Rekognition.SearchFacesByImage
- module Network.AWS.Rekognition.ListStreamProcessors
- module Network.AWS.Rekognition.RecognizeCelebrities
- module Network.AWS.Rekognition.GetFaceSearch
- module Network.AWS.Rekognition.StartLabelDetection
- module Network.AWS.Rekognition.SearchFaces
- module Network.AWS.Rekognition.IndexFaces
- module Network.AWS.Rekognition.GetLabelDetection
- module Network.AWS.Rekognition.DescribeStreamProcessor
- module Network.AWS.Rekognition.StartFaceSearch
- module Network.AWS.Rekognition.StartPersonTracking
- module Network.AWS.Rekognition.GetCelebrityRecognition
- module Network.AWS.Rekognition.StartStreamProcessor
- module Network.AWS.Rekognition.DetectText
- module Network.AWS.Rekognition.CompareFaces
- module Network.AWS.Rekognition.DetectFaces
- module Network.AWS.Rekognition.GetFaceDetection
- module Network.AWS.Rekognition.ListFaces
- module Network.AWS.Rekognition.GetContentModeration
- module Network.AWS.Rekognition.DeleteFaces
- module Network.AWS.Rekognition.GetCelebrityInfo
- module Network.AWS.Rekognition.DeleteStreamProcessor
- module Network.AWS.Rekognition.DetectModerationLabels
- module Network.AWS.Rekognition.CreateStreamProcessor
- module Network.AWS.Rekognition.StartFaceDetection
- data Attribute
- data CelebrityRecognitionSortBy
- data ContentModerationSortBy
- data EmotionName
- data FaceAttributes
- data FaceSearchSortBy
- data GenderType
- data LabelDetectionSortBy
- data LandmarkType
- = EyeLeft
- | EyeRight
- | LeftEyeBrowLeft
- | LeftEyeBrowRight
- | LeftEyeBrowUp
- | LeftEyeDown
- | LeftEyeLeft
- | LeftEyeRight
- | LeftEyeUp
- | LeftPupil
- | MouthDown
- | MouthLeft
- | MouthRight
- | MouthUp
- | Nose
- | NoseLeft
- | NoseRight
- | RightEyeBrowLeft
- | RightEyeBrowRight
- | RightEyeBrowUp
- | RightEyeDown
- | RightEyeLeft
- | RightEyeRight
- | RightEyeUp
- | RightPupil
- data OrientationCorrection
- data PersonTrackingSortBy
- data StreamProcessorStatus
- data TextTypes
- data VideoJobStatus
- data AgeRange
- ageRange :: AgeRange
- arLow :: Lens' AgeRange (Maybe Natural)
- arHigh :: Lens' AgeRange (Maybe Natural)
- data Beard
- beard :: Beard
- bValue :: Lens' Beard (Maybe Bool)
- bConfidence :: Lens' Beard (Maybe Double)
- data BoundingBox
- boundingBox :: BoundingBox
- bbHeight :: Lens' BoundingBox (Maybe Double)
- bbLeft :: Lens' BoundingBox (Maybe Double)
- bbWidth :: Lens' BoundingBox (Maybe Double)
- bbTop :: Lens' BoundingBox (Maybe Double)
- data Celebrity
- celebrity :: Celebrity
- cMatchConfidence :: Lens' Celebrity (Maybe Double)
- cURLs :: Lens' Celebrity [Text]
- cName :: Lens' Celebrity (Maybe Text)
- cId :: Lens' Celebrity (Maybe Text)
- cFace :: Lens' Celebrity (Maybe ComparedFace)
- data CelebrityDetail
- celebrityDetail :: CelebrityDetail
- cdBoundingBox :: Lens' CelebrityDetail (Maybe BoundingBox)
- cdURLs :: Lens' CelebrityDetail [Text]
- cdConfidence :: Lens' CelebrityDetail (Maybe Double)
- cdName :: Lens' CelebrityDetail (Maybe Text)
- cdId :: Lens' CelebrityDetail (Maybe Text)
- cdFace :: Lens' CelebrityDetail (Maybe FaceDetail)
- data CelebrityRecognition
- celebrityRecognition :: CelebrityRecognition
- crCelebrity :: Lens' CelebrityRecognition (Maybe CelebrityDetail)
- crTimestamp :: Lens' CelebrityRecognition (Maybe Integer)
- data CompareFacesMatch
- compareFacesMatch :: CompareFacesMatch
- cfmSimilarity :: Lens' CompareFacesMatch (Maybe Double)
- cfmFace :: Lens' CompareFacesMatch (Maybe ComparedFace)
- data ComparedFace
- comparedFace :: ComparedFace
- cfBoundingBox :: Lens' ComparedFace (Maybe BoundingBox)
- cfPose :: Lens' ComparedFace (Maybe Pose)
- cfConfidence :: Lens' ComparedFace (Maybe Double)
- cfQuality :: Lens' ComparedFace (Maybe ImageQuality)
- cfLandmarks :: Lens' ComparedFace [Landmark]
- data ComparedSourceImageFace
- comparedSourceImageFace :: ComparedSourceImageFace
- csifBoundingBox :: Lens' ComparedSourceImageFace (Maybe BoundingBox)
- csifConfidence :: Lens' ComparedSourceImageFace (Maybe Double)
- data ContentModerationDetection
- contentModerationDetection :: ContentModerationDetection
- cmdModerationLabel :: Lens' ContentModerationDetection (Maybe ModerationLabel)
- cmdTimestamp :: Lens' ContentModerationDetection (Maybe Integer)
- data Emotion
- emotion :: Emotion
- eConfidence :: Lens' Emotion (Maybe Double)
- eType :: Lens' Emotion (Maybe EmotionName)
- data EyeOpen
- eyeOpen :: EyeOpen
- eoValue :: Lens' EyeOpen (Maybe Bool)
- eoConfidence :: Lens' EyeOpen (Maybe Double)
- data Eyeglasses
- eyeglasses :: Eyeglasses
- eyeValue :: Lens' Eyeglasses (Maybe Bool)
- eyeConfidence :: Lens' Eyeglasses (Maybe Double)
- data Face
- face :: Face
- fFaceId :: Lens' Face (Maybe Text)
- fBoundingBox :: Lens' Face (Maybe BoundingBox)
- fExternalImageId :: Lens' Face (Maybe Text)
- fConfidence :: Lens' Face (Maybe Double)
- fImageId :: Lens' Face (Maybe Text)
- data FaceDetail
- faceDetail :: FaceDetail
- fdAgeRange :: Lens' FaceDetail (Maybe AgeRange)
- fdSunglasses :: Lens' FaceDetail (Maybe Sunglasses)
- fdMouthOpen :: Lens' FaceDetail (Maybe MouthOpen)
- fdBoundingBox :: Lens' FaceDetail (Maybe BoundingBox)
- fdEmotions :: Lens' FaceDetail [Emotion]
- fdEyesOpen :: Lens' FaceDetail (Maybe EyeOpen)
- fdPose :: Lens' FaceDetail (Maybe Pose)
- fdConfidence :: Lens' FaceDetail (Maybe Double)
- fdGender :: Lens' FaceDetail (Maybe Gender)
- fdQuality :: Lens' FaceDetail (Maybe ImageQuality)
- fdEyeglasses :: Lens' FaceDetail (Maybe Eyeglasses)
- fdBeard :: Lens' FaceDetail (Maybe Beard)
- fdMustache :: Lens' FaceDetail (Maybe Mustache)
- fdSmile :: Lens' FaceDetail (Maybe Smile)
- fdLandmarks :: Lens' FaceDetail [Landmark]
- data FaceDetection
- faceDetection :: FaceDetection
- fdTimestamp :: Lens' FaceDetection (Maybe Integer)
- fdFace :: Lens' FaceDetection (Maybe FaceDetail)
- data FaceMatch
- faceMatch :: FaceMatch
- fmSimilarity :: Lens' FaceMatch (Maybe Double)
- fmFace :: Lens' FaceMatch (Maybe Face)
- data FaceRecord
- faceRecord :: FaceRecord
- frFaceDetail :: Lens' FaceRecord (Maybe FaceDetail)
- frFace :: Lens' FaceRecord (Maybe Face)
- data FaceSearchSettings
- faceSearchSettings :: FaceSearchSettings
- fssFaceMatchThreshold :: Lens' FaceSearchSettings (Maybe Double)
- fssCollectionId :: Lens' FaceSearchSettings (Maybe Text)
- data Gender
- gender :: Gender
- gValue :: Lens' Gender (Maybe GenderType)
- gConfidence :: Lens' Gender (Maybe Double)
- data Geometry
- geometry :: Geometry
- gBoundingBox :: Lens' Geometry (Maybe BoundingBox)
- gPolygon :: Lens' Geometry [Point]
- data Image
- image :: Image
- iS3Object :: Lens' Image (Maybe S3Object)
- iBytes :: Lens' Image (Maybe ByteString)
- data ImageQuality
- imageQuality :: ImageQuality
- iqSharpness :: Lens' ImageQuality (Maybe Double)
- iqBrightness :: Lens' ImageQuality (Maybe Double)
- data KinesisDataStream
- kinesisDataStream :: KinesisDataStream
- kdsARN :: Lens' KinesisDataStream (Maybe Text)
- data KinesisVideoStream
- kinesisVideoStream :: KinesisVideoStream
- kvsARN :: Lens' KinesisVideoStream (Maybe Text)
- data Label
- label :: Label
- lConfidence :: Lens' Label (Maybe Double)
- lName :: Lens' Label (Maybe Text)
- data LabelDetection
- labelDetection :: LabelDetection
- ldLabel :: Lens' LabelDetection (Maybe Label)
- ldTimestamp :: Lens' LabelDetection (Maybe Integer)
- data Landmark
- landmark :: Landmark
- lType :: Lens' Landmark (Maybe LandmarkType)
- lX :: Lens' Landmark (Maybe Double)
- lY :: Lens' Landmark (Maybe Double)
- data ModerationLabel
- moderationLabel :: ModerationLabel
- mlConfidence :: Lens' ModerationLabel (Maybe Double)
- mlName :: Lens' ModerationLabel (Maybe Text)
- mlParentName :: Lens' ModerationLabel (Maybe Text)
- data MouthOpen
- mouthOpen :: MouthOpen
- moValue :: Lens' MouthOpen (Maybe Bool)
- moConfidence :: Lens' MouthOpen (Maybe Double)
- data Mustache
- mustache :: Mustache
- mValue :: Lens' Mustache (Maybe Bool)
- mConfidence :: Lens' Mustache (Maybe Double)
- data NotificationChannel
- notificationChannel :: Text -> Text -> NotificationChannel
- ncSNSTopicARN :: Lens' NotificationChannel Text
- ncRoleARN :: Lens' NotificationChannel Text
- data PersonDetail
- personDetail :: PersonDetail
- pdBoundingBox :: Lens' PersonDetail (Maybe BoundingBox)
- pdIndex :: Lens' PersonDetail (Maybe Integer)
- pdFace :: Lens' PersonDetail (Maybe FaceDetail)
- data PersonDetection
- personDetection :: PersonDetection
- pdPerson :: Lens' PersonDetection (Maybe PersonDetail)
- pdTimestamp :: Lens' PersonDetection (Maybe Integer)
- data PersonMatch
- personMatch :: PersonMatch
- pmFaceMatches :: Lens' PersonMatch [FaceMatch]
- pmPerson :: Lens' PersonMatch (Maybe PersonDetail)
- pmTimestamp :: Lens' PersonMatch (Maybe Integer)
- data Point
- point :: Point
- pX :: Lens' Point (Maybe Double)
- pY :: Lens' Point (Maybe Double)
- data Pose
- pose :: Pose
- pYaw :: Lens' Pose (Maybe Double)
- pRoll :: Lens' Pose (Maybe Double)
- pPitch :: Lens' Pose (Maybe Double)
- data S3Object
- s3Object :: S3Object
- soBucket :: Lens' S3Object (Maybe Text)
- soName :: Lens' S3Object (Maybe Text)
- soVersion :: Lens' S3Object (Maybe Text)
- data Smile
- smile :: Smile
- smiValue :: Lens' Smile (Maybe Bool)
- smiConfidence :: Lens' Smile (Maybe Double)
- data StreamProcessor
- streamProcessor :: StreamProcessor
- spStatus :: Lens' StreamProcessor (Maybe StreamProcessorStatus)
- spName :: Lens' StreamProcessor (Maybe Text)
- data StreamProcessorInput
- streamProcessorInput :: StreamProcessorInput
- spiKinesisVideoStream :: Lens' StreamProcessorInput (Maybe KinesisVideoStream)
- data StreamProcessorOutput
- streamProcessorOutput :: StreamProcessorOutput
- spoKinesisDataStream :: Lens' StreamProcessorOutput (Maybe KinesisDataStream)
- data StreamProcessorSettings
- streamProcessorSettings :: StreamProcessorSettings
- spsFaceSearch :: Lens' StreamProcessorSettings (Maybe FaceSearchSettings)
- data Sunglasses
- sunglasses :: Sunglasses
- sValue :: Lens' Sunglasses (Maybe Bool)
- sConfidence :: Lens' Sunglasses (Maybe Double)
- data TextDetection
- textDetection :: TextDetection
- tdDetectedText :: Lens' TextDetection (Maybe Text)
- tdConfidence :: Lens' TextDetection (Maybe Double)
- tdGeometry :: Lens' TextDetection (Maybe Geometry)
- tdId :: Lens' TextDetection (Maybe Natural)
- tdType :: Lens' TextDetection (Maybe TextTypes)
- tdParentId :: Lens' TextDetection (Maybe Natural)
- data Video
- video :: Video
- vS3Object :: Lens' Video (Maybe S3Object)
- data VideoMetadata
- videoMetadata :: VideoMetadata
- vmFrameRate :: Lens' VideoMetadata (Maybe Double)
- vmFormat :: Lens' VideoMetadata (Maybe Text)
- vmCodec :: Lens' VideoMetadata (Maybe Text)
- vmFrameHeight :: Lens' VideoMetadata (Maybe Natural)
- vmDurationMillis :: Lens' VideoMetadata (Maybe Natural)
- vmFrameWidth :: Lens' VideoMetadata (Maybe Natural)
Service Configuration
rekognition :: Service #
API version 2016-06-27 of the Amazon Rekognition SDK configuration.
Errors
Error matchers are designed for use with the functions provided by
Control.Exception.Lens.
This allows catching (and rethrowing) service specific errors returned
by Rekognition.
AccessDeniedException
_AccessDeniedException :: AsError a => Getting (First ServiceError) a ServiceError #
You are not authorized to perform the action.
VideoTooLargeException
_VideoTooLargeException :: AsError a => Getting (First ServiceError) a ServiceError #
The file size or duration of the supplied media is too large. The maximum file size is 8GB. The maximum duration is 2 hours.
InvalidParameterException
_InvalidParameterException :: AsError a => Getting (First ServiceError) a ServiceError #
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidImageFormatException
_InvalidImageFormatException :: AsError a => Getting (First ServiceError) a ServiceError #
The provided image format is not supported.
ResourceAlreadyExistsException
_ResourceAlreadyExistsException :: AsError a => Getting (First ServiceError) a ServiceError #
A collection with the specified ID already exists.
InvalidS3ObjectException
_InvalidS3ObjectException :: AsError a => Getting (First ServiceError) a ServiceError #
Amazon Rekognition is unable to access the S3 object specified in the request.
ProvisionedThroughputExceededException
_ProvisionedThroughputExceededException :: AsError a => Getting (First ServiceError) a ServiceError #
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ImageTooLargeException
_ImageTooLargeException :: AsError a => Getting (First ServiceError) a ServiceError #
The input image size exceeds the allowed limit. For more information, see limits .
ThrottlingException
_ThrottlingException :: AsError a => Getting (First ServiceError) a ServiceError #
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InternalServerError
_InternalServerError :: AsError a => Getting (First ServiceError) a ServiceError #
Amazon Rekognition experienced a service issue. Try your call again.
IdempotentParameterMismatchException
_IdempotentParameterMismatchException :: AsError a => Getting (First ServiceError) a ServiceError #
A ClientRequestToken input parameter was reused with an operation, but at least one of the other input parameters is different from the previous call to the operation.
ResourceNotFoundException
_ResourceNotFoundException :: AsError a => Getting (First ServiceError) a ServiceError #
The collection specified in the request cannot be found.
InvalidPaginationTokenException
_InvalidPaginationTokenException :: AsError a => Getting (First ServiceError) a ServiceError #
Pagination token in the request is not valid.
LimitExceededException
_LimitExceededException :: AsError a => Getting (First ServiceError) a ServiceError #
An Amazon Rekognition service limit was exceeded. For example, if you start too many Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection , for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ResourceInUseException
_ResourceInUseException :: AsError a => Getting (First ServiceError) a ServiceError #
Waiters
Waiters poll by repeatedly sending a request until some remote success condition
configured by the Wait specification is fulfilled. The Wait specification
determines how many attempts should be made, in addition to delay and retry strategies.
Operations
Some AWS operations return results that are incomplete and require subsequent
requests in order to obtain the entire result set. The process of sending
subsequent requests to continue where a previous request left off is called
pagination. For example, the ListObjects operation of Amazon S3 returns up to
1000 objects at a time, and you must send subsequent requests with the
appropriate Marker in order to retrieve the next page of results.
Operations that have an AWSPager instance can transparently perform subsequent
requests, correctly setting Markers and other request facets to iterate through
the entire result set of a truncated API operation. Operations which support
this have an additional note in the documentation.
Many operations have the ability to filter results on the server side. See the individual operation parameters for details.
StartCelebrityRecognition
GetPersonTracking
ListCollections (Paginated)
DeleteCollection
CreateCollection
StopStreamProcessor
DetectLabels
StartContentModeration
SearchFacesByImage
ListStreamProcessors (Paginated)
RecognizeCelebrities
GetFaceSearch
StartLabelDetection
SearchFaces
IndexFaces
GetLabelDetection
DescribeStreamProcessor
StartFaceSearch
StartPersonTracking
GetCelebrityRecognition
StartStreamProcessor
DetectText
CompareFaces
DetectFaces
GetFaceDetection
ListFaces (Paginated)
GetContentModeration
DeleteFaces
GetCelebrityInfo
DeleteStreamProcessor
DetectModerationLabels
CreateStreamProcessor
StartFaceDetection
Types
Attribute
Instances
CelebrityRecognitionSortBy
data CelebrityRecognitionSortBy #
Constructors
| CRSBId | |
| CRSBTimestamp |
Instances
ContentModerationSortBy
data ContentModerationSortBy #
Constructors
| CMSBName | |
| CMSBTimestamp |
Instances
EmotionName
data EmotionName #
Instances
FaceAttributes
data FaceAttributes #
Instances
FaceSearchSortBy
data FaceSearchSortBy #
Constructors
| FSSBIndex | |
| FSSBTimestamp |
Instances
GenderType
data GenderType #
Instances
LabelDetectionSortBy
data LabelDetectionSortBy #
Constructors
| LDSBName | |
| LDSBTimestamp |
Instances
LandmarkType
data LandmarkType #
Constructors
Instances
OrientationCorrection
data OrientationCorrection #
Instances
PersonTrackingSortBy
data PersonTrackingSortBy #
Instances
StreamProcessorStatus
data StreamProcessorStatus #
Constructors
| SPSFailed | |
| SPSRunning | |
| SPSStarting | |
| SPSStopped | |
| SPSStopping |
Instances
TextTypes
Instances
VideoJobStatus
data VideoJobStatus #
Constructors
| Failed | |
| InProgress | |
| Succeeded |
Instances
AgeRange
Structure containing the estimated age range, in years, for a face.
Rekognition estimates an age-range for faces detected in the input image. Estimated age ranges can overlap; a face of a 5 year old may have an estimated range of 4-6 whilst the face of a 6 year old may have an estimated range of 4-8.
See: ageRange smart constructor.
Instances
| Eq AgeRange # | |
| Data AgeRange # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> AgeRange -> c AgeRange # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c AgeRange # toConstr :: AgeRange -> Constr # dataTypeOf :: AgeRange -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c AgeRange) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c AgeRange) # gmapT :: (forall b. Data b => b -> b) -> AgeRange -> AgeRange # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> AgeRange -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> AgeRange -> r # gmapQ :: (forall d. Data d => d -> u) -> AgeRange -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> AgeRange -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> AgeRange -> m AgeRange # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> AgeRange -> m AgeRange # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> AgeRange -> m AgeRange # | |
| Read AgeRange # | |
| Show AgeRange # | |
| Generic AgeRange # | |
| Hashable AgeRange # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON AgeRange # | |
| NFData AgeRange # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep AgeRange # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep AgeRange = D1 (MetaData "AgeRange" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "AgeRange'" PrefixI True) (S1 (MetaSel (Just "_arLow") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Nat)) :*: S1 (MetaSel (Just "_arHigh") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Nat)))) | |
Beard
Indicates whether or not the face has a beard, and the confidence level in the determination.
See: beard smart constructor.
Instances
| Eq Beard # | |
| Data Beard # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Beard -> c Beard # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Beard # dataTypeOf :: Beard -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Beard) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Beard) # gmapT :: (forall b. Data b => b -> b) -> Beard -> Beard # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Beard -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Beard -> r # gmapQ :: (forall d. Data d => d -> u) -> Beard -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Beard -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Beard -> m Beard # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Beard -> m Beard # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Beard -> m Beard # | |
| Read Beard # | |
| Show Beard # | |
| Generic Beard # | |
| Hashable Beard # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Beard # | |
| NFData Beard # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Beard # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Beard = D1 (MetaData "Beard" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Beard'" PrefixI True) (S1 (MetaSel (Just "_bValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_bConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Creates a value of Beard with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
bValue- Boolean value that indicates whether the face has beard or not.bConfidence- Level of confidence in the determination.
BoundingBox
data BoundingBox #
Identifies the bounding box around the object, face or text. 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 (350700) and a top value of 0.25 (50200).
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.
See: boundingBox smart constructor.
Instances
Creates a value of BoundingBox with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
bbHeight- Height of the bounding box as a ratio of the overall image height.bbLeft- Left coordinate of the bounding box as a ratio of overall image width.bbWidth- Width of the bounding box as a ratio of the overall image width.bbTop- Top coordinate of the bounding box as a ratio of overall image height.
bbHeight :: Lens' BoundingBox (Maybe Double) #
Height of the bounding box as a ratio of the overall image height.
bbLeft :: Lens' BoundingBox (Maybe Double) #
Left coordinate of the bounding box as a ratio of overall image width.
bbWidth :: Lens' BoundingBox (Maybe Double) #
Width of the bounding box as a ratio of the overall image width.
bbTop :: Lens' BoundingBox (Maybe Double) #
Top coordinate of the bounding box as a ratio of overall image height.
Celebrity
Provides information about a celebrity recognized by the operation.
See: celebrity smart constructor.
Instances
Creates a value of Celebrity with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
cMatchConfidence- The confidence, in percentage, that Rekognition has that the recognized face is the celebrity.cURLs- An array of URLs pointing to additional information about the celebrity. If there is no additional information about the celebrity, this list is empty.cName- The name of the celebrity.cId- A unique identifier for the celebrity.cFace- Provides information about the celebrity's face, such as its location on the image.
cMatchConfidence :: Lens' Celebrity (Maybe Double) #
The confidence, in percentage, that Rekognition has that the recognized face is the celebrity.
cURLs :: Lens' Celebrity [Text] #
An array of URLs pointing to additional information about the celebrity. If there is no additional information about the celebrity, this list is empty.
cFace :: Lens' Celebrity (Maybe ComparedFace) #
Provides information about the celebrity's face, such as its location on the image.
CelebrityDetail
data CelebrityDetail #
Information about a recognized celebrity.
See: celebrityDetail smart constructor.
Instances
celebrityDetail :: CelebrityDetail #
Creates a value of CelebrityDetail with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
cdBoundingBox- Bounding box around the body of a celebrity.cdURLs- An array of URLs pointing to additional celebrity information.cdConfidence- The confidence, in percentage, that Amazon Rekognition has that the recognized face is the celebrity.cdName- The name of the celebrity.cdId- The unique identifier for the celebrity.cdFace- Face details for the recognized celebrity.
cdBoundingBox :: Lens' CelebrityDetail (Maybe BoundingBox) #
Bounding box around the body of a celebrity.
cdURLs :: Lens' CelebrityDetail [Text] #
An array of URLs pointing to additional celebrity information.
cdConfidence :: Lens' CelebrityDetail (Maybe Double) #
The confidence, in percentage, that Amazon Rekognition has that the recognized face is the celebrity.
cdFace :: Lens' CelebrityDetail (Maybe FaceDetail) #
Face details for the recognized celebrity.
CelebrityRecognition
data CelebrityRecognition #
Information about a detected celebrity and the time the celebrity was detected in a stored video. For more information, see .
See: celebrityRecognition smart constructor.
Instances
celebrityRecognition :: CelebrityRecognition #
Creates a value of CelebrityRecognition with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
crCelebrity- Information about a recognized celebrity.crTimestamp- The time, in milliseconds from the start of the video, that the celebrity was recognized.
crCelebrity :: Lens' CelebrityRecognition (Maybe CelebrityDetail) #
Information about a recognized celebrity.
crTimestamp :: Lens' CelebrityRecognition (Maybe Integer) #
The time, in milliseconds from the start of the video, that the celebrity was recognized.
CompareFacesMatch
data CompareFacesMatch #
Provides information about a face in a target image that matches the source image face analysed 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.
See: compareFacesMatch smart constructor.
Instances
compareFacesMatch :: CompareFacesMatch #
Creates a value of CompareFacesMatch with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
cfmSimilarity- Level of confidence that the faces match.cfmFace- Provides face metadata (bounding box and confidence that the bounding box actually contains a face).
cfmSimilarity :: Lens' CompareFacesMatch (Maybe Double) #
Level of confidence that the faces match.
cfmFace :: Lens' CompareFacesMatch (Maybe ComparedFace) #
Provides face metadata (bounding box and confidence that the bounding box actually contains a face).
ComparedFace
data ComparedFace #
Provides face metadata for target image faces that are analysed by CompareFaces and RecognizeCelebrities .
See: comparedFace smart constructor.
Instances
comparedFace :: ComparedFace #
Creates a value of ComparedFace with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
cfBoundingBox- Bounding box of the face.cfPose- Indicates the pose of the face as determined by its pitch, roll, and yaw.cfConfidence- Level of confidence that what the bounding box contains is a face.cfQuality- Identifies face image brightness and sharpness.cfLandmarks- An array of facial landmarks.
cfBoundingBox :: Lens' ComparedFace (Maybe BoundingBox) #
Bounding box of the face.
cfPose :: Lens' ComparedFace (Maybe Pose) #
Indicates the pose of the face as determined by its pitch, roll, and yaw.
cfConfidence :: Lens' ComparedFace (Maybe Double) #
Level of confidence that what the bounding box contains is a face.
cfQuality :: Lens' ComparedFace (Maybe ImageQuality) #
Identifies face image brightness and sharpness.
cfLandmarks :: Lens' ComparedFace [Landmark] #
An array of facial landmarks.
ComparedSourceImageFace
data ComparedSourceImageFace #
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.
See: comparedSourceImageFace smart constructor.
Instances
comparedSourceImageFace :: ComparedSourceImageFace #
Creates a value of ComparedSourceImageFace with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
csifBoundingBox- Bounding box of the face.csifConfidence- Confidence level that the selected bounding box contains a face.
csifBoundingBox :: Lens' ComparedSourceImageFace (Maybe BoundingBox) #
Bounding box of the face.
csifConfidence :: Lens' ComparedSourceImageFace (Maybe Double) #
Confidence level that the selected bounding box contains a face.
ContentModerationDetection
data ContentModerationDetection #
Information about a moderation label detection in a stored video.
See: contentModerationDetection smart constructor.
Instances
contentModerationDetection :: ContentModerationDetection #
Creates a value of ContentModerationDetection with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
cmdModerationLabel- The moderation label detected by in the stored video.cmdTimestamp- Time, in milliseconds from the beginning of the video, that the moderation label was detected.
cmdModerationLabel :: Lens' ContentModerationDetection (Maybe ModerationLabel) #
The moderation label detected by in the stored video.
cmdTimestamp :: Lens' ContentModerationDetection (Maybe Integer) #
Time, in milliseconds from the beginning of the video, that the moderation label was detected.
Emotion
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
See: emotion smart constructor.
Instances
| Eq Emotion # | |
| Data Emotion # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Emotion -> c Emotion # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Emotion # toConstr :: Emotion -> Constr # dataTypeOf :: Emotion -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Emotion) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Emotion) # gmapT :: (forall b. Data b => b -> b) -> Emotion -> Emotion # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Emotion -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Emotion -> r # gmapQ :: (forall d. Data d => d -> u) -> Emotion -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Emotion -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Emotion -> m Emotion # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Emotion -> m Emotion # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Emotion -> m Emotion # | |
| Read Emotion # | |
| Show Emotion # | |
| Generic Emotion # | |
| Hashable Emotion # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Emotion # | |
| NFData Emotion # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Emotion # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Emotion = D1 (MetaData "Emotion" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Emotion'" PrefixI True) (S1 (MetaSel (Just "_eConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_eType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe EmotionName)))) | |
Creates a value of Emotion with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
eConfidence- Level of confidence in the determination.eType- Type of emotion detected.
EyeOpen
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
See: eyeOpen smart constructor.
Instances
| Eq EyeOpen # | |
| Data EyeOpen # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> EyeOpen -> c EyeOpen # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c EyeOpen # toConstr :: EyeOpen -> Constr # dataTypeOf :: EyeOpen -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c EyeOpen) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c EyeOpen) # gmapT :: (forall b. Data b => b -> b) -> EyeOpen -> EyeOpen # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> EyeOpen -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> EyeOpen -> r # gmapQ :: (forall d. Data d => d -> u) -> EyeOpen -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> EyeOpen -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> EyeOpen -> m EyeOpen # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> EyeOpen -> m EyeOpen # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> EyeOpen -> m EyeOpen # | |
| Read EyeOpen # | |
| Show EyeOpen # | |
| Generic EyeOpen # | |
| Hashable EyeOpen # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON EyeOpen # | |
| NFData EyeOpen # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep EyeOpen # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep EyeOpen = D1 (MetaData "EyeOpen" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "EyeOpen'" PrefixI True) (S1 (MetaSel (Just "_eoValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_eoConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Creates a value of EyeOpen with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
eoValue- Boolean value that indicates whether the eyes on the face are open.eoConfidence- Level of confidence in the determination.
eoValue :: Lens' EyeOpen (Maybe Bool) #
Boolean value that indicates whether the eyes on the face are open.
Eyeglasses
data Eyeglasses #
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
See: eyeglasses smart constructor.
Instances
Creates a value of Eyeglasses with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
eyeValue- Boolean value that indicates whether the face is wearing eye glasses or not.eyeConfidence- Level of confidence in the determination.
eyeValue :: Lens' Eyeglasses (Maybe Bool) #
Boolean value that indicates whether the face is wearing eye glasses or not.
eyeConfidence :: Lens' Eyeglasses (Maybe Double) #
Level of confidence in the determination.
Face
Describes the face properties such as the bounding box, face ID, image ID of the input image, and external image ID that you assigned.
See: face smart constructor.
Instances
| Eq Face # | |
| Data Face # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Face -> c Face # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Face # dataTypeOf :: Face -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Face) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Face) # gmapT :: (forall b. Data b => b -> b) -> Face -> Face # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Face -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Face -> r # gmapQ :: (forall d. Data d => d -> u) -> Face -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Face -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Face -> m Face # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Face -> m Face # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Face -> m Face # | |
| Read Face # | |
| Show Face # | |
| Generic Face # | |
| Hashable Face # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Face # | |
| NFData Face # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Face # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Face = D1 (MetaData "Face" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Face'" PrefixI True) ((S1 (MetaSel (Just "_fFaceId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_fBoundingBox") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe BoundingBox))) :*: (S1 (MetaSel (Just "_fExternalImageId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_fConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_fImageId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))) | |
Creates a value of Face with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
fFaceId- Unique identifier that Amazon Rekognition assigns to the face.fBoundingBox- Bounding box of the face.fExternalImageId- Identifier that you assign to all the faces in the input image.fConfidence- Confidence level that the bounding box contains a face (and not a different object such as a tree).fImageId- Unique identifier that Amazon Rekognition assigns to the input image.
fBoundingBox :: Lens' Face (Maybe BoundingBox) #
Bounding box of the face.
fExternalImageId :: Lens' Face (Maybe Text) #
Identifier that you assign to all the faces in the input image.
fConfidence :: Lens' Face (Maybe Double) #
Confidence level that the bounding box contains a face (and not a different object such as a tree).
fImageId :: Lens' Face (Maybe Text) #
Unique identifier that Amazon Rekognition assigns to the input image.
FaceDetail
data FaceDetail #
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 .
is the only 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 . The following Rekognition Video operations return only the default attributes. The corresponding Start operations don't have a FaceAttributes input parameter.
- GetCelebrityRecognition
- GetPersonTracking
- GetFaceSearch
The Rekognition Image and 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.
See: faceDetail smart constructor.
Instances
Creates a value of FaceDetail with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
fdAgeRange- The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.fdSunglasses- Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.fdMouthOpen- Indicates whether or not the mouth on the face is open, and the confidence level in the determination.fdBoundingBox- Bounding box of the face. Default attribute.fdEmotions- The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.fdEyesOpen- Indicates whether or not the eyes on the face are open, and the confidence level in the determination.fdPose- Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.fdConfidence- Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.fdGender- Gender of the face and the confidence level in the determination.fdQuality- Identifies image brightness and sharpness. Default attribute.fdEyeglasses- Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.fdBeard- Indicates whether or not the face has a beard, and the confidence level in the determination.fdMustache- Indicates whether or not the face has a mustache, and the confidence level in the determination.fdSmile- Indicates whether or not the face is smiling, and the confidence level in the determination.fdLandmarks- Indicates the location of landmarks on the face. Default attribute.
fdAgeRange :: Lens' FaceDetail (Maybe AgeRange) #
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
fdSunglasses :: Lens' FaceDetail (Maybe Sunglasses) #
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
fdMouthOpen :: Lens' FaceDetail (Maybe MouthOpen) #
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
fdBoundingBox :: Lens' FaceDetail (Maybe BoundingBox) #
Bounding box of the face. Default attribute.
fdEmotions :: Lens' FaceDetail [Emotion] #
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
fdEyesOpen :: Lens' FaceDetail (Maybe EyeOpen) #
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
fdPose :: Lens' FaceDetail (Maybe Pose) #
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
fdConfidence :: Lens' FaceDetail (Maybe Double) #
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
fdGender :: Lens' FaceDetail (Maybe Gender) #
Gender of the face and the confidence level in the determination.
fdQuality :: Lens' FaceDetail (Maybe ImageQuality) #
Identifies image brightness and sharpness. Default attribute.
fdEyeglasses :: Lens' FaceDetail (Maybe Eyeglasses) #
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
fdBeard :: Lens' FaceDetail (Maybe Beard) #
Indicates whether or not the face has a beard, and the confidence level in the determination.
fdMustache :: Lens' FaceDetail (Maybe Mustache) #
Indicates whether or not the face has a mustache, and the confidence level in the determination.
fdSmile :: Lens' FaceDetail (Maybe Smile) #
Indicates whether or not the face is smiling, and the confidence level in the determination.
fdLandmarks :: Lens' FaceDetail [Landmark] #
Indicates the location of landmarks on the face. Default attribute.
FaceDetection
data FaceDetection #
Information about a face detected in a video analysis request and the time the face was detected in the video.
See: faceDetection smart constructor.
Instances
faceDetection :: FaceDetection #
Creates a value of FaceDetection with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
fdTimestamp- Time, in milliseconds from the start of the video, that the face was detected.fdFace- The face properties for the detected face.
fdTimestamp :: Lens' FaceDetection (Maybe Integer) #
Time, in milliseconds from the start of the video, that the face was detected.
fdFace :: Lens' FaceDetection (Maybe FaceDetail) #
The face properties for the detected face.
FaceMatch
Provides face metadata. In addition, it also provides the confidence in the match of this face with the input face.
See: faceMatch smart constructor.
Instances
| Eq FaceMatch # | |
| Data FaceMatch # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> FaceMatch -> c FaceMatch # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c FaceMatch # toConstr :: FaceMatch -> Constr # dataTypeOf :: FaceMatch -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c FaceMatch) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c FaceMatch) # gmapT :: (forall b. Data b => b -> b) -> FaceMatch -> FaceMatch # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> FaceMatch -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> FaceMatch -> r # gmapQ :: (forall d. Data d => d -> u) -> FaceMatch -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> FaceMatch -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> FaceMatch -> m FaceMatch # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> FaceMatch -> m FaceMatch # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> FaceMatch -> m FaceMatch # | |
| Read FaceMatch # | |
| Show FaceMatch # | |
| Generic FaceMatch # | |
| Hashable FaceMatch # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON FaceMatch # | |
| NFData FaceMatch # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep FaceMatch # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep FaceMatch = D1 (MetaData "FaceMatch" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "FaceMatch'" PrefixI True) (S1 (MetaSel (Just "_fmSimilarity") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_fmFace") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Face)))) | |
Creates a value of FaceMatch with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
fmSimilarity- Confidence in the match of this face with the input face.fmFace- Describes the face properties such as the bounding box, face ID, image ID of the source image, and external image ID that you assigned.
fmSimilarity :: Lens' FaceMatch (Maybe Double) #
Confidence in the match of this face with the input face.
fmFace :: Lens' FaceMatch (Maybe Face) #
Describes the face properties such as the bounding box, face ID, image ID of the source image, and external image ID that you assigned.
FaceRecord
data FaceRecord #
Object containing both the face metadata (stored in the back-end database) and facial attributes that are detected but aren't stored in the database.
See: faceRecord smart constructor.
Instances
Creates a value of FaceRecord with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
frFaceDetail- Structure containing attributes of the face that the algorithm detected.frFace- Describes the face properties such as the bounding box, face ID, image ID of the input image, and external image ID that you assigned.
frFaceDetail :: Lens' FaceRecord (Maybe FaceDetail) #
Structure containing attributes of the face that the algorithm detected.
frFace :: Lens' FaceRecord (Maybe Face) #
Describes the face properties such as the bounding box, face ID, image ID of the input image, and external image ID that you assigned.
FaceSearchSettings
data FaceSearchSettings #
Input face recognition parameters for an Amazon Rekognition stream processor. FaceRecognitionSettings is a request parameter for .
See: faceSearchSettings smart constructor.
Instances
faceSearchSettings :: FaceSearchSettings #
Creates a value of FaceSearchSettings with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
fssFaceMatchThreshold- Minimum face match confidence score that must be met to return a result for a recognized face. Default is 70. 0 is the lowest confidence. 100 is the highest confidence.fssCollectionId- The ID of a collection that contains faces that you want to search for.
fssFaceMatchThreshold :: Lens' FaceSearchSettings (Maybe Double) #
Minimum face match confidence score that must be met to return a result for a recognized face. Default is 70. 0 is the lowest confidence. 100 is the highest confidence.
fssCollectionId :: Lens' FaceSearchSettings (Maybe Text) #
The ID of a collection that contains faces that you want to search for.
Gender
Gender of the face and the confidence level in the determination.
See: gender smart constructor.
Instances
| Eq Gender # | |
| Data Gender # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Gender -> c Gender # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Gender # toConstr :: Gender -> Constr # dataTypeOf :: Gender -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Gender) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Gender) # gmapT :: (forall b. Data b => b -> b) -> Gender -> Gender # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Gender -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Gender -> r # gmapQ :: (forall d. Data d => d -> u) -> Gender -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Gender -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Gender -> m Gender # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Gender -> m Gender # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Gender -> m Gender # | |
| Read Gender # | |
| Show Gender # | |
| Generic Gender # | |
| Hashable Gender # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Gender # | |
| NFData Gender # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Gender # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Gender = D1 (MetaData "Gender" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Gender'" PrefixI True) (S1 (MetaSel (Just "_gValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe GenderType)) :*: S1 (MetaSel (Just "_gConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Creates a value of Gender with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
gValue- Gender of the face.gConfidence- Level of confidence in the determination.
Geometry
Information about where text detected by is located on an image.
See: geometry smart constructor.
Instances
| Eq Geometry # | |
| Data Geometry # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Geometry -> c Geometry # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Geometry # toConstr :: Geometry -> Constr # dataTypeOf :: Geometry -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Geometry) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Geometry) # gmapT :: (forall b. Data b => b -> b) -> Geometry -> Geometry # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Geometry -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Geometry -> r # gmapQ :: (forall d. Data d => d -> u) -> Geometry -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Geometry -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Geometry -> m Geometry # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Geometry -> m Geometry # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Geometry -> m Geometry # | |
| Read Geometry # | |
| Show Geometry # | |
| Generic Geometry # | |
| Hashable Geometry # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Geometry # | |
| NFData Geometry # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Geometry # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Geometry = D1 (MetaData "Geometry" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Geometry'" PrefixI True) (S1 (MetaSel (Just "_gBoundingBox") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe BoundingBox)) :*: S1 (MetaSel (Just "_gPolygon") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe [Point])))) | |
Creates a value of Geometry with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
gBoundingBox- An axis-aligned coarse representation of the detected text's location on the image.gPolygon- Within the bounding box, a fine-grained polygon around the detected text.
gBoundingBox :: Lens' Geometry (Maybe BoundingBox) #
An axis-aligned coarse representation of the detected text's location on the image.
gPolygon :: Lens' Geometry [Point] #
Within the bounding box, a fine-grained polygon around the detected text.
Image
Provides the input image either as bytes or an S3 object.
You pass image bytes to a 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 Rekognition API operations. For more information, see 'images-bytes' .
You pass images stored in an S3 bucket to a 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 Amazon 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 'manage-access-resource-policies' .
See: image smart constructor.
Instances
| Eq Image # | |
| Data Image # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Image -> c Image # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Image # dataTypeOf :: Image -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Image) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Image) # gmapT :: (forall b. Data b => b -> b) -> Image -> Image # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Image -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Image -> r # gmapQ :: (forall d. Data d => d -> u) -> Image -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Image -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Image -> m Image # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Image -> m Image # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Image -> m Image # | |
| Read Image # | |
| Show Image # | |
| Generic Image # | |
| Hashable Image # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| ToJSON Image # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| NFData Image # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Image # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Image = D1 (MetaData "Image" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Image'" PrefixI True) (S1 (MetaSel (Just "_iS3Object") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe S3Object)) :*: S1 (MetaSel (Just "_iBytes") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Base64)))) | |
Creates a value of Image with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
iS3Object- Identifies an S3 object as the image source.iBytes- Blob of image bytes up to 5 MBs.-- Note: ThisLensautomatically encodes and decodes Base64 data. The underlying isomorphism will encode to Base64 representation during serialisation, and decode from Base64 representation during deserialisation. ThisLensaccepts and returns only raw unencoded data.
iBytes :: Lens' Image (Maybe ByteString) #
Blob of image bytes up to 5 MBs.-- Note: This Lens automatically encodes and decodes Base64 data. The underlying isomorphism will encode to Base64 representation during serialisation, and decode from Base64 representation during deserialisation. This Lens accepts and returns only raw unencoded data.
ImageQuality
data ImageQuality #
Identifies face image brightness and sharpness.
See: imageQuality smart constructor.
Instances
imageQuality :: ImageQuality #
Creates a value of ImageQuality with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
iqSharpness- Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.iqBrightness- Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
iqSharpness :: Lens' ImageQuality (Maybe Double) #
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
iqBrightness :: Lens' ImageQuality (Maybe Double) #
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
KinesisDataStream
data KinesisDataStream #
The Kinesis data stream Amazon Rekognition to which the analysis results of a Amazon Rekognition stream processor are streamed. For more information, see .
See: kinesisDataStream smart constructor.
Instances
kinesisDataStream :: KinesisDataStream #
Creates a value of KinesisDataStream with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
kdsARN- ARN of the output Amazon Kinesis Data Streams stream.
kdsARN :: Lens' KinesisDataStream (Maybe Text) #
ARN of the output Amazon Kinesis Data Streams stream.
KinesisVideoStream
data KinesisVideoStream #
Kinesis video stream stream that provides the source streaming video for a Rekognition Video stream processor. For more information, see .
See: kinesisVideoStream smart constructor.
Instances
kinesisVideoStream :: KinesisVideoStream #
Creates a value of KinesisVideoStream with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
kvsARN- ARN of the Kinesis video stream stream that streams the source video.
kvsARN :: Lens' KinesisVideoStream (Maybe Text) #
ARN of the Kinesis video stream stream that streams the source video.
Label
Structure containing details about the detected label, including name, and level of confidence.
See: label smart constructor.
Instances
| Eq Label # | |
| Data Label # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Label -> c Label # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Label # dataTypeOf :: Label -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Label) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Label) # gmapT :: (forall b. Data b => b -> b) -> Label -> Label # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Label -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Label -> r # gmapQ :: (forall d. Data d => d -> u) -> Label -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Label -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Label -> m Label # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Label -> m Label # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Label -> m Label # | |
| Read Label # | |
| Show Label # | |
| Generic Label # | |
| Hashable Label # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Label # | |
| NFData Label # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Label # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Label = D1 (MetaData "Label" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Label'" PrefixI True) (S1 (MetaSel (Just "_lConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_lName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))) | |
Creates a value of Label with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
lConfidence- Level of confidence.lName- The name (label) of the object.
LabelDetection
data LabelDetection #
Information about a label detected in a video analysis request and the time the label was detected in the video.
See: labelDetection smart constructor.
Instances
labelDetection :: LabelDetection #
Creates a value of LabelDetection with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
ldLabel- Details about the detected label.ldTimestamp- Time, in milliseconds from the start of the video, that the label was detected.
ldTimestamp :: Lens' LabelDetection (Maybe Integer) #
Time, in milliseconds from the start of the video, that the label was detected.
Landmark
Indicates the location of the landmark on the face.
See: landmark smart constructor.
Instances
| Eq Landmark # | |
| Data Landmark # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Landmark -> c Landmark # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Landmark # toConstr :: Landmark -> Constr # dataTypeOf :: Landmark -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Landmark) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Landmark) # gmapT :: (forall b. Data b => b -> b) -> Landmark -> Landmark # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Landmark -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Landmark -> r # gmapQ :: (forall d. Data d => d -> u) -> Landmark -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Landmark -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Landmark -> m Landmark # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Landmark -> m Landmark # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Landmark -> m Landmark # | |
| Read Landmark # | |
| Show Landmark # | |
| Generic Landmark # | |
| Hashable Landmark # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Landmark # | |
| NFData Landmark # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Landmark # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Landmark = D1 (MetaData "Landmark" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Landmark'" PrefixI True) (S1 (MetaSel (Just "_lType") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe LandmarkType)) :*: (S1 (MetaSel (Just "_lX") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_lY") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double))))) | |
Creates a value of Landmark with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
lType- Type of the landmark.lX- x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the images is 700x200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.lY- y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the images is 700x200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
lX :: Lens' Landmark (Maybe Double) #
x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the images is 700x200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
lY :: Lens' Landmark (Maybe Double) #
y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the images is 700x200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
ModerationLabel
data ModerationLabel #
Provides information about a single type of moderated content found in an image or video. Each type of moderated content has a label within a hierarchical taxonomy. For more information, see moderation .
See: moderationLabel smart constructor.
Instances
moderationLabel :: ModerationLabel #
Creates a value of ModerationLabel with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
mlConfidence- Specifies the confidence that Amazon Rekognition has that the label has been correctly identified. If you don't specify theMinConfidenceparameter in the call toDetectModerationLabels, the operation returns labels with a confidence value greater than or equal to 50 percent.mlName- The label name for the type of content detected in the image.mlParentName- The name for the parent label. Labels at the top-level of the hierarchy have the parent label"".
mlConfidence :: Lens' ModerationLabel (Maybe Double) #
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.
mlName :: Lens' ModerationLabel (Maybe Text) #
The label name for the type of content detected in the image.
mlParentName :: Lens' ModerationLabel (Maybe Text) #
The name for the parent label. Labels at the top-level of the hierarchy have the parent label "" .
MouthOpen
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
See: mouthOpen smart constructor.
Instances
| Eq MouthOpen # | |
| Data MouthOpen # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> MouthOpen -> c MouthOpen # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c MouthOpen # toConstr :: MouthOpen -> Constr # dataTypeOf :: MouthOpen -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c MouthOpen) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c MouthOpen) # gmapT :: (forall b. Data b => b -> b) -> MouthOpen -> MouthOpen # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> MouthOpen -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> MouthOpen -> r # gmapQ :: (forall d. Data d => d -> u) -> MouthOpen -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> MouthOpen -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> MouthOpen -> m MouthOpen # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> MouthOpen -> m MouthOpen # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> MouthOpen -> m MouthOpen # | |
| Read MouthOpen # | |
| Show MouthOpen # | |
| Generic MouthOpen # | |
| Hashable MouthOpen # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON MouthOpen # | |
| NFData MouthOpen # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep MouthOpen # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep MouthOpen = D1 (MetaData "MouthOpen" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "MouthOpen'" PrefixI True) (S1 (MetaSel (Just "_moValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_moConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Creates a value of MouthOpen with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
moValue- Boolean value that indicates whether the mouth on the face is open or not.moConfidence- Level of confidence in the determination.
moValue :: Lens' MouthOpen (Maybe Bool) #
Boolean value that indicates whether the mouth on the face is open or not.
Mustache
Indicates whether or not the face has a mustache, and the confidence level in the determination.
See: mustache smart constructor.
Instances
| Eq Mustache # | |
| Data Mustache # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Mustache -> c Mustache # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Mustache # toConstr :: Mustache -> Constr # dataTypeOf :: Mustache -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Mustache) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Mustache) # gmapT :: (forall b. Data b => b -> b) -> Mustache -> Mustache # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Mustache -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Mustache -> r # gmapQ :: (forall d. Data d => d -> u) -> Mustache -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Mustache -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Mustache -> m Mustache # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Mustache -> m Mustache # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Mustache -> m Mustache # | |
| Read Mustache # | |
| Show Mustache # | |
| Generic Mustache # | |
| Hashable Mustache # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Mustache # | |
| NFData Mustache # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Mustache # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Mustache = D1 (MetaData "Mustache" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Mustache'" PrefixI True) (S1 (MetaSel (Just "_mValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_mConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Creates a value of Mustache with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
mValue- Boolean value that indicates whether the face has mustache or not.mConfidence- Level of confidence in the determination.
mValue :: Lens' Mustache (Maybe Bool) #
Boolean value that indicates whether the face has mustache or not.
NotificationChannel
data NotificationChannel #
The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the completion status of a video analysis operation. For more information, see 'api-video' .
See: notificationChannel smart constructor.
Instances
Arguments
| :: Text | |
| -> Text | |
| -> NotificationChannel |
Creates a value of NotificationChannel with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
ncSNSTopicARN- The Amazon SNS topic to which Amazon Rekognition to posts the completion status.ncRoleARN- The ARN of an IAM role that gives Amazon Rekognition publishing permissions to the Amazon SNS topic.
ncSNSTopicARN :: Lens' NotificationChannel Text #
The Amazon SNS topic to which Amazon Rekognition to posts the completion status.
ncRoleARN :: Lens' NotificationChannel Text #
The ARN of an IAM role that gives Amazon Rekognition publishing permissions to the Amazon SNS topic.
PersonDetail
data PersonDetail #
Details about a person detected in a video analysis request.
See: personDetail smart constructor.
Instances
personDetail :: PersonDetail #
Creates a value of PersonDetail with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
pdBoundingBox- Bounding box around the detected person.pdIndex- 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.pdFace- Face details for the detected person.
pdBoundingBox :: Lens' PersonDetail (Maybe BoundingBox) #
Bounding box around the detected person.
pdIndex :: Lens' PersonDetail (Maybe Integer) #
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.
pdFace :: Lens' PersonDetail (Maybe FaceDetail) #
Face details for the detected person.
PersonDetection
data PersonDetection #
Details and tracking information for a single time a person is tracked in a video. Amazon Rekognition operations that track persons return an array of PersonDetection objects with elements for each time a person is tracked in a video. For more information, see .
See: personDetection smart constructor.
Instances
personDetection :: PersonDetection #
Creates a value of PersonDetection with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
pdPerson- Details about a person tracked in a video.pdTimestamp- The time, in milliseconds from the start of the video, that the person was tracked.
pdPerson :: Lens' PersonDetection (Maybe PersonDetail) #
Details about a person tracked in a video.
pdTimestamp :: Lens' PersonDetection (Maybe Integer) #
The time, in milliseconds from the start of the video, that the person was tracked.
PersonMatch
data PersonMatch #
Information about a person whose face matches a face(s) in a Amazon Rekognition collection. Includes information about the faces in the Amazon Rekognition collection (, information about the person (PersonDetail ) and the timestamp for when the person was detected in a video. An array of PersonMatch objects is returned by .
See: personMatch smart constructor.
Instances
Creates a value of PersonMatch with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
pmFaceMatches- Information about the faces in the input collection that match the face of a person in the video.pmPerson- Information about the matched person.pmTimestamp- The time, in milliseconds from the beginning of the video, that the person was matched in the video.
pmFaceMatches :: Lens' PersonMatch [FaceMatch] #
Information about the faces in the input collection that match the face of a person in the video.
pmPerson :: Lens' PersonMatch (Maybe PersonDetail) #
Information about the matched person.
pmTimestamp :: Lens' PersonMatch (Maybe Integer) #
The time, in milliseconds from the beginning of the video, that the person was matched in the video.
Point
The X and Y coordinates of a point on an image. The X and Y values returned are ratios of the overall image size. For example, if the input image is 700x200 and the operation returns 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, Polygon , is returned by . Polygon represents a fine-grained polygon around detected text. For more information, see .
See: point smart constructor.
Instances
| Eq Point # | |
| Data Point # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Point -> c Point # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Point # dataTypeOf :: Point -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Point) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Point) # gmapT :: (forall b. Data b => b -> b) -> Point -> Point # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Point -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Point -> r # gmapQ :: (forall d. Data d => d -> u) -> Point -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Point -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Point -> m Point # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Point -> m Point # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Point -> m Point # | |
| Read Point # | |
| Show Point # | |
| Generic Point # | |
| Hashable Point # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Point # | |
| NFData Point # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Point # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Point = D1 (MetaData "Point" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Point'" PrefixI True) (S1 (MetaSel (Just "_pX") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_pY") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Pose
Indicates the pose of the face as determined by its pitch, roll, and yaw.
See: pose smart constructor.
Instances
| Eq Pose # | |
| Data Pose # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Pose -> c Pose # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Pose # dataTypeOf :: Pose -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Pose) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Pose) # gmapT :: (forall b. Data b => b -> b) -> Pose -> Pose # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Pose -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Pose -> r # gmapQ :: (forall d. Data d => d -> u) -> Pose -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Pose -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Pose -> m Pose # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Pose -> m Pose # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Pose -> m Pose # | |
| Read Pose # | |
| Show Pose # | |
| Generic Pose # | |
| Hashable Pose # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Pose # | |
| NFData Pose # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Pose # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Pose = D1 (MetaData "Pose" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Pose'" PrefixI True) (S1 (MetaSel (Just "_pYaw") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: (S1 (MetaSel (Just "_pRoll") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)) :*: S1 (MetaSel (Just "_pPitch") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double))))) | |
Creates a value of Pose with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
S3Object
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 'manage-access-resource-policies' .
See: s3Object smart constructor.
Instances
| Eq S3Object # | |
| Data S3Object # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> S3Object -> c S3Object # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c S3Object # toConstr :: S3Object -> Constr # dataTypeOf :: S3Object -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c S3Object) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c S3Object) # gmapT :: (forall b. Data b => b -> b) -> S3Object -> S3Object # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> S3Object -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> S3Object -> r # gmapQ :: (forall d. Data d => d -> u) -> S3Object -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> S3Object -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> S3Object -> m S3Object # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> S3Object -> m S3Object # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> S3Object -> m S3Object # | |
| Read S3Object # | |
| Show S3Object # | |
| Generic S3Object # | |
| Hashable S3Object # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| ToJSON S3Object # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| NFData S3Object # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep S3Object # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep S3Object = D1 (MetaData "S3Object" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "S3Object'" PrefixI True) (S1 (MetaSel (Just "_soBucket") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 (MetaSel (Just "_soName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)) :*: S1 (MetaSel (Just "_soVersion") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))))) | |
soVersion :: Lens' S3Object (Maybe Text) #
If the bucket is versioning enabled, you can specify the object version.
Smile
Indicates whether or not the face is smiling, and the confidence level in the determination.
See: smile smart constructor.
Instances
| Eq Smile # | |
| Data Smile # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Smile -> c Smile # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Smile # dataTypeOf :: Smile -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Smile) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Smile) # gmapT :: (forall b. Data b => b -> b) -> Smile -> Smile # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Smile -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Smile -> r # gmapQ :: (forall d. Data d => d -> u) -> Smile -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Smile -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Smile -> m Smile # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Smile -> m Smile # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Smile -> m Smile # | |
| Read Smile # | |
| Show Smile # | |
| Generic Smile # | |
| Hashable Smile # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| FromJSON Smile # | |
| NFData Smile # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Smile # | |
Defined in Network.AWS.Rekognition.Types.Product type Rep Smile = D1 (MetaData "Smile" "Network.AWS.Rekognition.Types.Product" "amazonka-rekognition-1.6.1-LJYoSuoGbtd78kiYOWkJFK" False) (C1 (MetaCons "Smile'" PrefixI True) (S1 (MetaSel (Just "_smiValue") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 (MetaSel (Just "_smiConfidence") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Double)))) | |
Creates a value of Smile with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
smiValue- Boolean value that indicates whether the face is smiling or not.smiConfidence- Level of confidence in the determination.
smiValue :: Lens' Smile (Maybe Bool) #
Boolean value that indicates whether the face is smiling or not.
StreamProcessor
data StreamProcessor #
An object that recognizes faces in a streaming video. An Amazon Rekognition stream processor is created by a call to . 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.
See: streamProcessor smart constructor.
Instances
streamProcessor :: StreamProcessor #
Creates a value of StreamProcessor with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
spStatus :: Lens' StreamProcessor (Maybe StreamProcessorStatus) #
Current status of the Amazon Rekognition stream processor.
StreamProcessorInput
data StreamProcessorInput #
Information about the source streaming video.
See: streamProcessorInput smart constructor.
Instances
streamProcessorInput :: StreamProcessorInput #
Creates a value of StreamProcessorInput with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
spiKinesisVideoStream- The Kinesis video stream input stream for the source streaming video.
spiKinesisVideoStream :: Lens' StreamProcessorInput (Maybe KinesisVideoStream) #
The Kinesis video stream input stream for the source streaming video.
StreamProcessorOutput
data StreamProcessorOutput #
Information about the Amazon Kinesis Data Streams stream to which a Rekognition Video stream processor streams the results of a video analysis. For more information, see .
See: streamProcessorOutput smart constructor.
Instances
streamProcessorOutput :: StreamProcessorOutput #
Creates a value of StreamProcessorOutput with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
spoKinesisDataStream- The Amazon Kinesis Data Streams stream to which the Amazon Rekognition stream processor streams the analysis results.
spoKinesisDataStream :: Lens' StreamProcessorOutput (Maybe KinesisDataStream) #
The Amazon Kinesis Data Streams stream to which the Amazon Rekognition stream processor streams the analysis results.
StreamProcessorSettings
data StreamProcessorSettings #
Input parameters used to recognize faces in a streaming video analyzed by a Amazon Rekognition stream processor.
See: streamProcessorSettings smart constructor.
Instances
streamProcessorSettings :: StreamProcessorSettings #
Creates a value of StreamProcessorSettings with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
spsFaceSearch- Face search settings to use on a streaming video.
spsFaceSearch :: Lens' StreamProcessorSettings (Maybe FaceSearchSettings) #
Face search settings to use on a streaming video.
Sunglasses
data Sunglasses #
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
See: sunglasses smart constructor.
Instances
Creates a value of Sunglasses with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
sValue- Boolean value that indicates whether the face is wearing sunglasses or not.sConfidence- Level of confidence in the determination.
sValue :: Lens' Sunglasses (Maybe Bool) #
Boolean value that indicates whether the face is wearing sunglasses or not.
sConfidence :: Lens' Sunglasses (Maybe Double) #
Level of confidence in the determination.
TextDetection
data TextDetection #
Information about a word or line of text detected by .
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 'text-detection' .
See: textDetection smart constructor.
Instances
textDetection :: TextDetection #
Creates a value of TextDetection with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
tdDetectedText- The word or line of text recognized by Amazon Rekognition.tdConfidence- The confidence that Amazon Rekognition has in the accuracy of the detected text and the accuracy of the geometry points around the detected text.tdGeometry- 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.tdId- The identifier for the detected text. The identifier is only unique for a single call toDetectText.tdType- The type of text that was detected.tdParentId- The Parent identifier for the detected text identified by the value ofID. If the type of detected text isLINE, the value ofParentIdisNull.
tdDetectedText :: Lens' TextDetection (Maybe Text) #
The word or line of text recognized by Amazon Rekognition.
tdConfidence :: Lens' TextDetection (Maybe Double) #
The confidence that Amazon Rekognition has in the accuracy of the detected text and the accuracy of the geometry points around the detected text.
tdGeometry :: Lens' TextDetection (Maybe Geometry) #
The location of the detected text on the image. Includes an axis aligned coarse bounding box surrounding the text and a finer grain polygon for more accurate spatial information.
tdId :: Lens' TextDetection (Maybe Natural) #
The identifier for the detected text. The identifier is only unique for a single call to DetectText .
tdParentId :: Lens' TextDetection (Maybe Natural) #
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 .
Video
Video file stored in an Amazon S3 bucket. Amazon Rekognition video start operations such as use Video to specify a video for analysis. The supported file formats are .mp4, .mov and .avi.
See: video smart constructor.
Instances
| Eq Video # | |
| Data Video # | |
Defined in Network.AWS.Rekognition.Types.Product Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Video -> c Video # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Video # dataTypeOf :: Video -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Video) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Video) # gmapT :: (forall b. Data b => b -> b) -> Video -> Video # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Video -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Video -> r # gmapQ :: (forall d. Data d => d -> u) -> Video -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> Video -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> Video -> m Video # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Video -> m Video # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Video -> m Video # | |
| Read Video # | |
| Show Video # | |
| Generic Video # | |
| Hashable Video # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| ToJSON Video # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| NFData Video # | |
Defined in Network.AWS.Rekognition.Types.Product | |
| type Rep Video # | |
Defined in Network.AWS.Rekognition.Types.Product | |
VideoMetadata
data VideoMetadata #
Information about a video that Amazon Rekognition analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition video operation.
See: videoMetadata smart constructor.
Instances
videoMetadata :: VideoMetadata #
Creates a value of VideoMetadata with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
vmFrameRate- Number of frames per second in the video.vmFormat- Format of the analyzed video. Possible values are MP4, MOV and AVI.vmCodec- Type of compression used in the analyzed video.vmFrameHeight- Vertical pixel dimension of the video.vmDurationMillis- Length of the video in milliseconds.vmFrameWidth- Horizontal pixel dimension of the video.
vmFrameRate :: Lens' VideoMetadata (Maybe Double) #
Number of frames per second in the video.
vmFormat :: Lens' VideoMetadata (Maybe Text) #
Format of the analyzed video. Possible values are MP4, MOV and AVI.
vmFrameHeight :: Lens' VideoMetadata (Maybe Natural) #
Vertical pixel dimension of the video.
vmDurationMillis :: Lens' VideoMetadata (Maybe Natural) #
Length of the video in milliseconds.
vmFrameWidth :: Lens' VideoMetadata (Maybe Natural) #
Horizontal pixel dimension of the video.