AWS SDK for PHP 3.x

Client: Aws\Rekognition\RekognitionClient

Service ID: rekognition

Version: 2016-06-27

This page describes the parameters and results for the operations of the Amazon Rekognition (2016-06-27), and shows how to use the Aws\Rekognition\RekognitionClient object to call the described operations. This documentation is specific to the 2016-06-27 API version of the service.

Operation Summary

Each of the following operations can be created from a client using $client->getCommand('CommandName'), where "CommandName" is the name of one of the following operations. Note: a command is a value that encapsulates an operation and the parameters used to create an HTTP request.

You can also create and send a command immediately using the magic methods available on a client object: $client->commandName(/* parameters */). You can send the command asynchronously (returning a promise) by appending the word "Async" to the operation name: $client->commandNameAsync(/* parameters */).

AssociateFaces ( array $params = [] )
Associates one or more faces with an existing UserID.
CompareFaces ( array $params = [] )
Compares a face in the source input image with each of the 100 largest faces detected in the target input image.
CopyProjectVersion ( array $params = [] )
Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project.
CreateCollection ( array $params = [] )
Creates a collection in an AWS Region.
CreateDataset ( array $params = [] )
Creates a new Amazon Rekognition Custom Labels dataset.
CreateFaceLivenessSession ( array $params = [] )
This API operation initiates a Face Liveness session.
CreateProject ( array $params = [] )
Creates a new Amazon Rekognition Custom Labels project.
CreateProjectVersion ( array $params = [] )
Creates a new version of a model and begins training.
CreateStreamProcessor ( array $params = [] )
Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces or to detect labels in a streaming video.
CreateUser ( array $params = [] )
Creates a new User within a collection specified by CollectionId.
DeleteCollection ( array $params = [] )
Deletes the specified collection.
DeleteDataset ( array $params = [] )
Deletes an existing Amazon Rekognition Custom Labels dataset.
DeleteFaces ( array $params = [] )
Deletes faces from a collection.
DeleteProject ( array $params = [] )
Deletes an Amazon Rekognition Custom Labels project.
DeleteProjectPolicy ( array $params = [] )
Deletes an existing project policy.
DeleteProjectVersion ( array $params = [] )
Deletes an Amazon Rekognition Custom Labels model.
DeleteStreamProcessor ( array $params = [] )
Deletes the stream processor identified by Name.
DeleteUser ( array $params = [] )
Deletes the specified UserID within the collection.
DescribeCollection ( array $params = [] )
Describes the specified collection.
DescribeDataset ( array $params = [] )
Describes an Amazon Rekognition Custom Labels dataset.
DescribeProjectVersions ( array $params = [] )
Lists and describes the versions of a model in an Amazon Rekognition Custom Labels project.
DescribeProjects ( array $params = [] )
Gets information about your Amazon Rekognition Custom Labels projects.
DescribeStreamProcessor ( array $params = [] )
Provides information about a stream processor created by CreateStreamProcessor.
DetectCustomLabels ( array $params = [] )
Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model.
DetectFaces ( array $params = [] )
Detects faces within an image that is provided as input.
DetectLabels ( array $params = [] )
Detects instances of real-world entities within an image (JPEG or PNG) provided as input.
DetectModerationLabels ( array $params = [] )
Detects unsafe content in a specified JPEG or PNG format image.
DetectProtectiveEquipment ( array $params = [] )
Detects Personal Protective Equipment (PPE) worn by people detected in an image.
DetectText ( array $params = [] )
Detects text in the input image and converts it into machine-readable text.
DisassociateFaces ( array $params = [] )
Removes the association between a Face supplied in an array of FaceIds and the User.
DistributeDatasetEntries ( array $params = [] )
Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a project.
GetCelebrityInfo ( array $params = [] )
Gets the name and additional information about a celebrity based on their Amazon Rekognition ID.
GetCelebrityRecognition ( array $params = [] )
Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by StartCelebrityRecognition.
GetContentModeration ( array $params = [] )
Gets the inappropriate, unwanted, or offensive content analysis results for a Amazon Rekognition Video analysis started by StartContentModeration.
GetFaceDetection ( array $params = [] )
Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection.
GetFaceLivenessSessionResults ( array $params = [] )
Retrieves the results of a specific Face Liveness session.
GetFaceSearch ( array $params = [] )
Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch.
GetLabelDetection ( array $params = [] )
Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection.
GetPersonTracking ( array $params = [] )
Gets the path tracking results of a Amazon Rekognition Video analysis started by StartPersonTracking.
GetSegmentDetection ( array $params = [] )
Gets the segment detection results of a Amazon Rekognition Video analysis started by StartSegmentDetection.
GetTextDetection ( array $params = [] )
Gets the text detection results of a Amazon Rekognition Video analysis started by StartTextDetection.
IndexFaces ( array $params = [] )
Detects faces in the input image and adds them to the specified collection.
ListCollections ( array $params = [] )
Returns list of collection IDs in your account.
ListDatasetEntries ( array $params = [] )
Lists the entries (images) within a dataset.
ListDatasetLabels ( array $params = [] )
Lists the labels in a dataset.
ListFaces ( array $params = [] )
Returns metadata for faces in the specified collection.
ListProjectPolicies ( array $params = [] )
Gets a list of the project policies attached to a project.
ListStreamProcessors ( array $params = [] )
Gets a list of stream processors that you have created with CreateStreamProcessor.
ListTagsForResource ( array $params = [] )
Returns a list of tags in an Amazon Rekognition collection, stream processor, or Custom Labels model.
ListUsers ( array $params = [] )
Returns metadata of the User such as UserID in the specified collection.
PutProjectPolicy ( array $params = [] )
Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account.
RecognizeCelebrities ( array $params = [] )
Returns an array of celebrities recognized in the input image.
SearchFaces ( array $params = [] )
For a given input face ID, searches for matching faces in the collection the face belongs to.
SearchFacesByImage ( array $params = [] )
For a given input image, first detects the largest face in the image, and then searches the specified collection for matching faces.
SearchUsers ( array $params = [] )
Searches for UserIDs within a collection based on a FaceId or UserId.
SearchUsersByImage ( array $params = [] )
Searches for UserIDs using a supplied image.
StartCelebrityRecognition ( array $params = [] )
Starts asynchronous recognition of celebrities in a stored video.
StartContentModeration ( array $params = [] )
Starts asynchronous detection of inappropriate, unwanted, or offensive content in a stored video.
StartFaceDetection ( array $params = [] )
Starts asynchronous detection of faces in a stored video.
StartFaceSearch ( array $params = [] )
Starts the asynchronous search for faces in a collection that match the faces of persons detected in a stored video.
StartLabelDetection ( array $params = [] )
Starts asynchronous detection of labels in a stored video.
StartPersonTracking ( array $params = [] )
Starts the asynchronous tracking of a person's path in a stored video.
StartProjectVersion ( array $params = [] )
Starts the running of the version of a model.
StartSegmentDetection ( array $params = [] )
Starts asynchronous detection of segment detection in a stored video.
StartStreamProcessor ( array $params = [] )
Starts processing a stream processor.
StartTextDetection ( array $params = [] )
Starts asynchronous detection of text in a stored video.
StopProjectVersion ( array $params = [] )
Stops a running model.
StopStreamProcessor ( array $params = [] )
Stops a running stream processor that was created by CreateStreamProcessor.
TagResource ( array $params = [] )
Adds one or more key-value tags to an Amazon Rekognition collection, stream processor, or Custom Labels model.
UntagResource ( array $params = [] )
Removes one or more tags from an Amazon Rekognition collection, stream processor, or Custom Labels model.
UpdateDatasetEntries ( array $params = [] )
Adds or updates one or more entries (images) in a dataset.
UpdateStreamProcessor ( array $params = [] )
Allows you to update a stream processor.

Paginators

Paginators handle automatically iterating over paginated API results. Paginators are associated with specific API operations, and they accept the parameters that the corresponding API operation accepts. You can get a paginator from a client class using getPaginator($paginatorName, $operationParameters). This client supports the following paginators:

DescribeProjectVersions
DescribeProjects
GetCelebrityRecognition
GetContentModeration
GetFaceDetection
GetFaceSearch
GetLabelDetection
GetPersonTracking
GetSegmentDetection
GetTextDetection
ListCollections
ListDatasetEntries
ListDatasetLabels
ListFaces
ListProjectPolicies
ListStreamProcessors
ListUsers

Waiters

Waiters allow you to poll a resource until it enters into a desired state. A waiter has a name used to describe what it does, and is associated with an API operation. When creating a waiter, you can provide the API operation parameters associated with the corresponding operation. Waiters can be accessed using the getWaiter($waiterName, $operationParameters) method of a client object. This client supports the following waiters:

Waiter name	API Operation	Delay	Max Attempts
ProjectVersionTrainingCompleted	DescribeProjectVersions	120	360
ProjectVersionRunning	DescribeProjectVersions	30	40

Operations

AssociateFaces

$result = $client->associateFaces([/* ... */]);
$promise = $client->associateFacesAsync([/* ... */]);

Associates one or more faces with an existing UserID. Takes an array of FaceIds. Each FaceId that are present in the FaceIds list is associated with the provided UserID. The maximum number of total FaceIds per UserID is 100.

The UserMatchThreshold parameter specifies the minimum user match confidence required for the face to be associated with a UserID that has at least one FaceID already associated. This ensures that the FaceIds are associated with the right UserID. The value ranges from 0-100 and default value is 75.

If successful, an array of AssociatedFace objects containing the associated FaceIds is returned. If a given face is already associated with the given UserID, it will be ignored and will not be returned in the response. If a given face is already associated to a different UserID, isn't found in the collection, doesn’t meet the UserMatchThreshold, or there are already 100 faces associated with the UserID, it will be returned as part of an array of UnsuccessfulFaceAssociations.

The UserStatus reflects the status of an operation which updates a UserID representation with a list of given faces. The UserStatus can be:

ACTIVE - All associations or disassociations of FaceID(s) for a UserID are complete.
CREATED - A UserID has been created, but has no FaceID(s) associated with it.
UPDATING - A UserID is being updated and there are current associations or disassociations of FaceID(s) taking place.

Parameter Syntax

$result = $client->associateFaces([
    'ClientRequestToken' => '<string>',
    'CollectionId' => '<string>', // REQUIRED
    'FaceIds' => ['<string>', ...], // REQUIRED
    'UserId' => '<string>', // REQUIRED
    'UserMatchThreshold' => <float>,
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the request to AssociateFaces. If you use the same token with multiple AssociateFaces requests, the same response is returned. Use ClientRequestToken to prevent the same request from being processed more than once.

CollectionId

Required: Yes
Type: string

The ID of an existing collection containing the UserID.

FaceIds

Required: Yes
Type: Array of strings

An array of FaceIDs to associate with the UserID.

UserId

Required: Yes
Type: string

The ID for the existing UserID.

UserMatchThreshold

Type: float

An optional value specifying the minimum confidence in the UserID match to return. The default value is 75.

Result Syntax

[
    'AssociatedFaces' => [
        [
            'FaceId' => '<string>',
        ],
        // ...
    ],
    'UnsuccessfulFaceAssociations' => [
        [
            'Confidence' => <float>,
            'FaceId' => '<string>',
            'Reasons' => ['<string>', ...],
            'UserId' => '<string>',
        ],
        // ...
    ],
    'UserStatus' => 'ACTIVE|UPDATING|CREATING|CREATED',
]

Result Details

Members

AssociatedFaces

Type: Array of AssociatedFace structures

An array of AssociatedFace objects containing FaceIDs that are successfully associated with the UserID is returned. Returned if the AssociateFaces action is successful.

UnsuccessfulFaceAssociations

Type: Array of UnsuccessfulFaceAssociation structures

An array of UnsuccessfulAssociation objects containing FaceIDs that are not successfully associated along with the reasons. Returned if the AssociateFaces action is successful.

UserStatus

Type: string

The status of an update made to a UserID. Reflects if the UserID has been updated for every requested change.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
IdempotentParameterMismatchException:
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:
The resource specified in the request cannot be found.
ConflictException:
A User with the same Id already exists within the collection, or the update or deletion of the User caused an inconsistent state. **
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.

Examples

Example 1: AssociateFaces

This operation associates one or more faces with an existing UserID.

$result = $client->associateFaces([
    'ClientRequestToken' => '550e8400-e29b-41d4-a716-446655440002',
    'CollectionId' => 'MyCollection',
    'FaceIds' => [
        'f5817d37-94f6-4335-bfee-6cf79a3d806e',
        '851cb847-dccc-4fea-9309-9f4805967855',
        '35ebbb41-7f67-4263-908d-dd0ecba05ab9',
    ],
    'UserId' => 'DemoUser',
    'UserMatchThreshold' => 70,
]);

Result syntax:

[
    'AssociatedFaces' => [
        [
            'FaceId' => '35ebbb41-7f67-4263-908d-dd0ecba05ab9',
        ],
    ],
    'UnsuccessfulFaceAssociations' => [
        [
            'Confidence' => 0.93753749132156,
            'FaceId' => 'f5817d37-94f6-4335-bfee-6cf79a3d806e',
            'Reasons' => [
                'LOW_MATCH_CONFIDENCE',
            ],
        ],
        [
            'FaceId' => '851cb847-dccc-4fea-9309-9f4805967855',
            'Reasons' => [
                'ASSOCIATED_TO_A_DIFFERENT_USER',
            ],
            'UserId' => 'demoUser2',
        ],
    ],
    'UserStatus' => 'UPDATING',
]

CompareFaces

$result = $client->compareFaces([/* ... */]);
$promise = $client->compareFacesAsync([/* ... */]);

Compares a face in the source input image with each of the 100 largest faces detected in the target input image.

If the source image contains multiple faces, the service detects the largest face and compares it with each face detected in the target image.

CompareFaces uses machine learning algorithms, which are probabilistic. A false negative is an incorrect prediction that a face in the target image has a low similarity confidence score when compared to the face in the source image. To reduce the probability of false negatives, we recommend that you compare the target image against multiple source images. If you plan to use CompareFaces to make a decision that impacts an individual's rights, privacy, or access to services, we recommend that you pass the result to a human for review and further validation before taking action.

You pass the input and target images either as base64-encoded image bytes or as references to images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't supported. The image must be formatted as a PNG or JPEG file.

In response, the operation returns an array of face matches ordered by similarity score in descending order. For each face match, the response provides a bounding box of the face, facial landmarks, pose details (pitch, roll, and yaw), quality (brightness and sharpness), and confidence value (indicating the level of confidence that the bounding box contains a face). The response also provides a similarity score, which indicates how closely the faces match.

By default, only faces with a similarity score of greater than or equal to 80% are returned in the response. You can change this value by specifying the SimilarityThreshold parameter.

CompareFaces also returns an array of faces that don't match the source image. For each face, it returns a bounding box, confidence value, landmarks, pose details, and quality. The response also returns information about the face in the source image, including the bounding box of the face and confidence value.

The QualityFilter input parameter allows you to filter out detected faces that don’t meet a required quality bar. The quality bar is based on a variety of common use cases. Use QualityFilter to set the quality bar by specifying LOW, MEDIUM, or HIGH. If you do not want to filter detected faces, specify NONE. The default value is NONE.

If the image doesn't contain Exif metadata, CompareFaces returns orientation information for the source and target images. Use these values to display the images with the correct image orientation.

If no faces are detected in the source or target images, CompareFaces returns an InvalidParameterException error.

This is a stateless API operation. That is, data returned by this operation doesn't persist.

For an example, see Comparing Faces in Images in the Amazon Rekognition Developer Guide.

This operation requires permissions to perform the rekognition:CompareFaces action.

Parameter Syntax

$result = $client->compareFaces([
    'QualityFilter' => 'NONE|AUTO|LOW|MEDIUM|HIGH',
    'SimilarityThreshold' => <float>,
    'SourceImage' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'TargetImage' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

QualityFilter

Type: string

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't compared. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE, no filtering is performed. The default value is NONE.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

SimilarityThreshold

Type: float

The minimum level of confidence in the face matches that a match must meet to be included in the FaceMatches array.

SourceImage

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported.

If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the Bytes field. For more information, see Images in the Amazon Rekognition developer guide.

TargetImage

Required: Yes
Type: Image structure

The target image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported.

Result Syntax

[
    'FaceMatches' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Emotions' => [
                    [
                        'Confidence' => <float>,
                        'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                    ],
                    // ...
                ],
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
                'Pose' => [
                    'Pitch' => <float>,
                    'Roll' => <float>,
                    'Yaw' => <float>,
                ],
                'Quality' => [
                    'Brightness' => <float>,
                    'Sharpness' => <float>,
                ],
                'Smile' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
            ],
            'Similarity' => <float>,
        ],
        // ...
    ],
    'SourceImageFace' => [
        'BoundingBox' => [
            'Height' => <float>,
            'Left' => <float>,
            'Top' => <float>,
            'Width' => <float>,
        ],
        'Confidence' => <float>,
    ],
    'SourceImageOrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
    'TargetImageOrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
    'UnmatchedFaces' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Confidence' => <float>,
            'Emotions' => [
                [
                    'Confidence' => <float>,
                    'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                ],
                // ...
            ],
            'Landmarks' => [
                [
                    'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
            'Pose' => [
                'Pitch' => <float>,
                'Roll' => <float>,
                'Yaw' => <float>,
            ],
            'Quality' => [
                'Brightness' => <float>,
                'Sharpness' => <float>,
            ],
            'Smile' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
        ],
        // ...
    ],
]

Result Details

Members

FaceMatches

Type: Array of CompareFacesMatch structures

An array of faces in the target image that match the source image face. Each CompareFacesMatch object provides the bounding box, the confidence level that the bounding box contains a face, and the similarity score for the face in the bounding box and the face in the source image.

SourceImageFace

Type: ComparedSourceImageFace structure

The face in the source image that was used for comparison.

SourceImageOrientationCorrection

Type: string

The value of SourceImageOrientationCorrection is always null.

If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.

Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

TargetImageOrientationCorrection

Type: string

The value of TargetImageOrientationCorrection is always null.

UnmatchedFaces

Type: Array of ComparedFace structures

An array of faces in the target image that did not match the source image face.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

Examples

Example 1: To compare two images

This operation compares the largest face detected in the source image with each face detected in the target image.

$result = $client->compareFaces([
    'SimilarityThreshold' => 90,
    'SourceImage' => [
        'S3Object' => [
            'Bucket' => 'mybucket',
            'Name' => 'mysourceimage',
        ],
    ],
    'TargetImage' => [
        'S3Object' => [
            'Bucket' => 'mybucket',
            'Name' => 'mytargetimage',
        ],
    ],
]);

Result syntax:

[
    'FaceMatches' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.33481481671333,
                    'Left' => 0.31888890266418,
                    'Top' => 0.49333333969116,
                    'Width' => 0.25,
                ],
                'Confidence' => 99.999122619629,
            ],
            'Similarity' => 100,
        ],
    ],
    'SourceImageFace' => [
        'BoundingBox' => [
            'Height' => 0.33481481671333,
            'Left' => 0.31888890266418,
            'Top' => 0.49333333969116,
            'Width' => 0.25,
        ],
        'Confidence' => 99.999122619629,
    ],
]

CopyProjectVersion

$result = $client->copyProjectVersion([/* ... */]);
$promise = $client->copyProjectVersionAsync([/* ... */]);

Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The source and destination projects can be in different AWS accounts but must be in the same AWS Region. You can't copy a model to another AWS service.

To copy a model version to a different AWS account, you need to create a resource-based policy known as a project policy. You attach the project policy to the source project by calling PutProjectPolicy. The project policy gives permission to copy the model version from a trusting AWS account to a trusted account.

For more information creating and attaching a project policy, see Attaching a project policy (SDK) in the Amazon Rekognition Custom Labels Developer Guide.

If you are copying a model version to a project in the same AWS account, you don't need to create a project policy.

To copy a model, the destination project, source project, and source model version must already exist.

Copying a model version takes a while to complete. To get the current status, call DescribeProjectVersions and check the value of Status in the ProjectVersionDescription object. The copy operation has finished when the value of Status is COPYING_COMPLETED.

This operation requires permissions to perform the rekognition:CopyProjectVersion action.

Parameter Syntax

$result = $client->copyProjectVersion([
    'DestinationProjectArn' => '<string>', // REQUIRED
    'KmsKeyId' => '<string>',
    'OutputConfig' => [ // REQUIRED
        'S3Bucket' => '<string>',
        'S3KeyPrefix' => '<string>',
    ],
    'SourceProjectArn' => '<string>', // REQUIRED
    'SourceProjectVersionArn' => '<string>', // REQUIRED
    'Tags' => ['<string>', ...],
    'VersionName' => '<string>', // REQUIRED
]);

Parameter Details

Members

DestinationProjectArn

Required: Yes
Type: string

The ARN of the project in the trusted AWS account that you want to copy the model version to.

KmsKeyId

Type: string

The identifier for your AWS Key Management Service key (AWS KMS key). You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt training results and manifest files written to the output Amazon S3 bucket (OutputConfig).

If you choose to use your own KMS key, you need the following permissions on the KMS key.

kms:CreateGrant
kms:DescribeKey
kms:GenerateDataKey
kms:Decrypt

If you don't specify a value for KmsKeyId, images copied into the service are encrypted using a key that AWS owns and manages.

OutputConfig

Required: Yes
Type: OutputConfig structure

The S3 bucket and folder location where the training output for the source model version is placed.

SourceProjectArn

Required: Yes
Type: string

The ARN of the source project in the trusting AWS account.

SourceProjectVersionArn

Required: Yes
Type: string

The ARN of the model version in the source project that you want to copy to a destination project.

Tags

Type: Associative array of custom strings keys (TagKey) to strings

The key-value tags to assign to the model version.

VersionName

Required: Yes
Type: string

A name for the version of the model that's copied to the destination project.

Result Syntax

[
    'ProjectVersionArn' => '<string>',
]

Result Details

Members

ProjectVersionArn

Type: string

The ARN of the copied model version in the destination project.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceInUseException:
The specified resource is already being used.

Examples

Example 1: CopyProjectVersion

Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project.

$result = $client->copyProjectVersion([
    'DestinationProjectArn' => 'arn:aws:rekognition:us-east-1:555555555555:project/DestinationProject/1656705098765',
    'KmsKeyId' => 'arn:1234abcd-12ab-34cd-56ef-1234567890ab',
    'OutputConfig' => [
        'S3Bucket' => 'bucket-name',
        'S3KeyPrefix' => 'path_to_folder',
    ],
    'SourceProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/SourceProject/16565123456',
    'SourceProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/SourceProject/version/model_1/1656611123456',
    'Tags' => [
        'key1' => 'val1',
    ],
    'VersionName' => 'DestinationVersionName_cross_account',
]);

Result syntax:

[
    'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:555555555555:project/DestinationProject/version/DestinationVersionName_cross_account/16567050987651',
]

CreateCollection

$result = $client->createCollection([/* ... */]);
$promise = $client->createCollectionAsync([/* ... */]);

Creates a collection in an AWS Region. You can add faces to the collection using the IndexFaces operation.

For example, you might create collections, one for each of your application users. A user can then index faces using the IndexFaces operation and persist results in a specific collection. Then, a user can search the collection for faces in the user-specific container.

When you create a collection, it is associated with the latest version of the face model version.

Collection names are case-sensitive.

This operation requires permissions to perform the rekognition:CreateCollection action. If you want to tag your collection, you also require permission to perform the rekognition:TagResource operation.

Parameter Syntax

$result = $client->createCollection([
    'CollectionId' => '<string>', // REQUIRED
    'Tags' => ['<string>', ...],
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

ID for the collection that you are creating.

Tags

Type: Associative array of custom strings keys (TagKey) to strings

A set of tags (key-value pairs) that you want to attach to the collection.

Result Syntax

[
    'CollectionArn' => '<string>',
    'FaceModelVersion' => '<string>',
    'StatusCode' => <integer>,
]

Result Details

Members

CollectionArn

Type: string

Amazon Resource Name (ARN) of the collection. You can use this to manage permissions on your resources.

FaceModelVersion

Type: string

Version number of the face detection model associated with the collection you are creating.

StatusCode

Type: int

HTTP status code indicating the result of the operation.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceAlreadyExistsException:
A resource with the specified ID already exists.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.

Examples

Example 1: To create a collection

This operation creates a Rekognition collection for storing image data.

$result = $client->createCollection([
    'CollectionId' => 'myphotos',
]);

Result syntax:

[
    'CollectionArn' => 'aws:rekognition:us-west-2:123456789012:collection/myphotos',
    'StatusCode' => 200,
]

CreateDataset

$result = $client->createDataset([/* ... */]);
$promise = $client->createDatasetAsync([/* ... */]);

Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using an Amazon Sagemaker format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset.

To create a training dataset for a project, specify TRAIN for the value of DatasetType. To create the test dataset for a project, specify TEST for the value of DatasetType.

The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset. Creating a dataset takes a while to complete. Use DescribeDataset to check the current status. The dataset created successfully if the value of Status is CREATE_COMPLETE.

To check if any non-terminal errors occurred, call ListDatasetEntries and check for the presence of errors lists in the JSON Lines.

Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). Currently, you can't access the terminal error information.

For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide.

This operation requires permissions to perform the rekognition:CreateDataset action. If you want to copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries action.

Parameter Syntax

$result = $client->createDataset([
    'DatasetSource' => [
        'DatasetArn' => '<string>',
        'GroundTruthManifest' => [
            'S3Object' => [
                'Bucket' => '<string>',
                'Name' => '<string>',
                'Version' => '<string>',
            ],
        ],
    ],
    'DatasetType' => 'TRAIN|TEST', // REQUIRED
    'ProjectArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

DatasetSource

Type: DatasetSource structure

The source files for the dataset. You can specify the ARN of an existing dataset or specify the Amazon S3 bucket location of an Amazon Sagemaker format manifest file. If you don't specify datasetSource, an empty dataset is created. To add labeled images to the dataset, You can use the console or call UpdateDatasetEntries.

DatasetType

Required: Yes
Type: string

The type of the dataset. Specify TRAIN to create a training dataset. Specify TEST to create a test dataset.

ProjectArn

Required: Yes
Type: string

The ARN of the Amazon Rekognition Custom Labels project to which you want to asssign the dataset.

Result Syntax

[
    'DatasetArn' => '<string>',
]

Result Details

Members

DatasetArn

Type: string

The ARN of the created Amazon Rekognition Custom Labels dataset.

Errors

InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
ResourceAlreadyExistsException:
A resource with the specified ID already exists.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To create an Amazon Rekognition Custom Labels dataset

Creates an Amazon Rekognition Custom Labels dataset with a manifest file stored in an Amazon S3 bucket.

$result = $client->createDataset([
    'DatasetSource' => [
        'GroundTruthManifest' => [
            'S3Object' => [
                'Bucket' => 'my-bucket',
                'Name' => 'datasets/flowers_training/manifests/output/output.manifest',
            ],
        ],
    ],
    'DatasetType' => 'TRAIN',
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690474772815',
]);

Result syntax:

[
    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/dataset/train/1690476084535',
]

CreateFaceLivenessSession

$result = $client->createFaceLivenessSession([/* ... */]);
$promise = $client->createFaceLivenessSessionAsync([/* ... */]);

This API operation initiates a Face Liveness session. It returns a SessionId, which you can use to start streaming Face Liveness video and get the results for a Face Liveness session.

You can use the OutputConfig option in the Settings parameter to provide an Amazon S3 bucket location. The Amazon S3 bucket stores reference images and audit images. If no Amazon S3 bucket is defined, raw bytes are sent instead.

You can use AuditImagesLimit to limit the number of audit images returned when GetFaceLivenessSessionResults is called. This number is between 0 and 4. By default, it is set to 0. The limit is best effort and based on the duration of the selfie-video.

Parameter Syntax

$result = $client->createFaceLivenessSession([
    'ClientRequestToken' => '<string>',
    'KmsKeyId' => '<string>',
    'Settings' => [
        'AuditImagesLimit' => <integer>,
        'OutputConfig' => [
            'S3Bucket' => '<string>', // REQUIRED
            'S3KeyPrefix' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token is used to recognize the Face Liveness request. If the same token is used with multiple CreateFaceLivenessSession requests, the same session is returned. This token is employed to avoid unintentionally creating the same session multiple times.

KmsKeyId

Type: string

The identifier for your AWS Key Management Service key (AWS KMS key). Used to encrypt audit images and reference images.

Settings

Type: CreateFaceLivenessSessionRequestSettings structure

A session settings object. It contains settings for the operation to be performed. For Face Liveness, it accepts OutputConfig and AuditImagesLimit.

Result Syntax

[
    'SessionId' => '<string>',
]

Result Details

Members

SessionId

Required: Yes
Type: string

A unique 128-bit UUID identifying a Face Liveness session.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

CreateProject

$result = $client->createProject([/* ... */]);
$promise = $client->createProjectAsync([/* ... */]);

Creates a new Amazon Rekognition Custom Labels project. A project is a group of resources (datasets, model versions) that you use to create and manage Amazon Rekognition Custom Labels models.

This operation requires permissions to perform the rekognition:CreateProject action.

Parameter Syntax

$result = $client->createProject([
    'ProjectName' => '<string>', // REQUIRED
]);

Parameter Details

Members

ProjectName

Required: Yes
Type: string

The name of the project to create.

Result Syntax

[
    'ProjectArn' => '<string>',
]

Result Details

Members

ProjectArn

Type: string

The Amazon Resource Name (ARN) of the new project. You can use the ARN to configure IAM access to the project.

Errors

ResourceInUseException:
The specified resource is already being used.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To create an Amazon Rekognition Custom Labels project

Creates an Amazon Rekognition Custom Labels project.

$result = $client->createProject([
    'ProjectName' => 'my-project',
]);

Result syntax:

[
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690405809285',
]

CreateProjectVersion

$result = $client->createProjectVersion([/* ... */]);
$promise = $client->createProjectVersionAsync([/* ... */]);

Creates a new version of a model and begins training. Models are managed as part of an Amazon Rekognition Custom Labels project. The response from CreateProjectVersion is an Amazon Resource Name (ARN) for the version of the model.

Training uses the training and test datasets associated with the project. For more information, see Creating training and test dataset in the Amazon Rekognition Custom Labels Developer Guide.

You can train a model in a project that doesn't have associated datasets by specifying manifest files in the TrainingData and TestingData fields.

If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates the datasets for you using the most recent manifest files. You can no longer train a model version for the project by specifying manifest files.

Instead of training with a project without associated datasets, we recommend that you use the manifest files to create training and test datasets for the project.

Training takes a while to complete. You can get the current status by calling DescribeProjectVersions. Training completed successfully if the value of the Status field is TRAINING_COMPLETED.

If training fails, see Debugging a failed model training in the Amazon Rekognition Custom Labels developer guide.

Once training has successfully completed, call DescribeProjectVersions to get the training results and evaluate the model. For more information, see Improving a trained Amazon Rekognition Custom Labels model in the Amazon Rekognition Custom Labels developers guide.

After evaluating the model, you start the model by calling StartProjectVersion.

This operation requires permissions to perform the rekognition:CreateProjectVersion action.

Parameter Syntax

$result = $client->createProjectVersion([
    'KmsKeyId' => '<string>',
    'OutputConfig' => [ // REQUIRED
        'S3Bucket' => '<string>',
        'S3KeyPrefix' => '<string>',
    ],
    'ProjectArn' => '<string>', // REQUIRED
    'Tags' => ['<string>', ...],
    'TestingData' => [
        'Assets' => [
            [
                'GroundTruthManifest' => [
                    'S3Object' => [
                        'Bucket' => '<string>',
                        'Name' => '<string>',
                        'Version' => '<string>',
                    ],
                ],
            ],
            // ...
        ],
        'AutoCreate' => true || false,
    ],
    'TrainingData' => [
        'Assets' => [
            [
                'GroundTruthManifest' => [
                    'S3Object' => [
                        'Bucket' => '<string>',
                        'Name' => '<string>',
                        'Version' => '<string>',
                    ],
                ],
            ],
            // ...
        ],
    ],
    'VersionName' => '<string>', // REQUIRED
]);

Parameter Details

Members

KmsKeyId

Type: string

The identifier for your AWS Key Management Service key (AWS KMS key). You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt training and test images copied into the service for model training. Your source images are unaffected. The key is also used to encrypt training results and manifest files written to the output Amazon S3 bucket (OutputConfig).

If you choose to use your own KMS key, you need the following permissions on the KMS key.

kms:CreateGrant
kms:DescribeKey
kms:GenerateDataKey
kms:Decrypt

If you don't specify a value for KmsKeyId, images copied into the service are encrypted using a key that AWS owns and manages.

OutputConfig

Required: Yes
Type: OutputConfig structure

The Amazon S3 bucket location to store the results of training. The S3 bucket can be in any AWS account as long as the caller has s3:PutObject permissions on the S3 bucket.

ProjectArn

Required: Yes
Type: string

The ARN of the Amazon Rekognition Custom Labels project that manages the model that you want to train.

Tags

Type: Associative array of custom strings keys (TagKey) to strings

A set of tags (key-value pairs) that you want to attach to the model.

TestingData

Type: TestingData structure

Specifies an external manifest that the service uses to test the model. If you specify TestingData you must also specify TrainingData. The project must not have any associated datasets.

TrainingData

Type: TrainingData structure

Specifies an external manifest that the services uses to train the model. If you specify TrainingData you must also specify TestingData. The project must not have any associated datasets.

VersionName

Required: Yes
Type: string

A name for the version of the model. This value must be unique.

Result Syntax

[
    'ProjectVersionArn' => '<string>',
]

Result Details

Members

ProjectVersionArn

Type: string

The ARN of the model version that was created. Use DescribeProjectVersion to get the current status of the training operation.

Errors

ResourceInUseException:
The specified resource is already being used.
ResourceNotFoundException:
The resource specified in the request cannot be found.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.

Examples

Example 1: To train an Amazon Rekognition Custom Labels model

Trains a version of an Amazon Rekognition Custom Labels model.

$result = $client->createProjectVersion([
    'OutputConfig' => [
        'S3Bucket' => 'output_bucket',
        'S3KeyPrefix' => 'output_folder',
    ],
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690474772815',
    'VersionName' => '1',
]);

Result syntax:

[
    'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/version/1/1690556751958',
]

CreateStreamProcessor

$result = $client->createStreamProcessor([/* ... */]);
$promise = $client->createStreamProcessorAsync([/* ... */]);

Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces or to detect labels in a streaming video.

Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. There are two different settings for stream processors in Amazon Rekognition: detecting faces and detecting labels.

If you are creating a stream processor for detecting faces, you provide as input a Kinesis video stream (Input) and a Kinesis data stream (Output) stream for receiving the output. You must use the FaceSearch option in Settings, specifying the collection that contains the faces you want to recognize. After you have finished analyzing a streaming video, use StopStreamProcessor to stop processing.
If you are creating a stream processor to detect labels, you provide as input a Kinesis video stream (Input), Amazon S3 bucket information (Output), and an Amazon SNS topic ARN (NotificationChannel). You can also provide a KMS key ID to encrypt the data sent to your Amazon S3 bucket. You specify what you want to detect by using the ConnectedHome option in settings, and selecting one of the following: PERSON, PET, PACKAGE, ALL You can also specify where in the frame you want Amazon Rekognition to monitor with RegionsOfInterest. When you run the StartStreamProcessor operation on a label detection stream processor, you input start and stop information to determine the length of the processing time.

Use Name to assign an identifier for the stream processor. You use Name to manage the stream processor. For example, you can start processing the source video by calling StartStreamProcessor with the Name field.

This operation requires permissions to perform the rekognition:CreateStreamProcessor action. If you want to tag your stream processor, you also require permission to perform the rekognition:TagResource operation.

Parameter Syntax

$result = $client->createStreamProcessor([
    'DataSharingPreference' => [
        'OptIn' => true || false, // REQUIRED
    ],
    'Input' => [ // REQUIRED
        'KinesisVideoStream' => [
            'Arn' => '<string>',
        ],
    ],
    'KmsKeyId' => '<string>',
    'Name' => '<string>', // REQUIRED
    'NotificationChannel' => [
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Output' => [ // REQUIRED
        'KinesisDataStream' => [
            'Arn' => '<string>',
        ],
        'S3Destination' => [
            'Bucket' => '<string>',
            'KeyPrefix' => '<string>',
        ],
    ],
    'RegionsOfInterest' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Polygon' => [
                [
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
        ],
        // ...
    ],
    'RoleArn' => '<string>', // REQUIRED
    'Settings' => [ // REQUIRED
        'ConnectedHome' => [
            'Labels' => ['<string>', ...], // REQUIRED
            'MinConfidence' => <float>,
        ],
        'FaceSearch' => [
            'CollectionId' => '<string>',
            'FaceMatchThreshold' => <float>,
        ],
    ],
    'Tags' => ['<string>', ...],
]);

Parameter Details

Members

DataSharingPreference

Type: StreamProcessorDataSharingPreference structure

Shows whether you are sharing data with Rekognition to improve model performance. You can choose this option at the account level or on a per-stream basis. Note that if you opt out at the account level this setting is ignored on individual streams.

Input

Required: Yes
Type: StreamProcessorInput structure

Kinesis video stream stream that provides the source streaming video. If you are using the AWS CLI, the parameter name is StreamProcessorInput. This is required for both face search and label detection stream processors.

KmsKeyId

Type: string

The identifier for your AWS Key Management Service key (AWS KMS key). This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor. You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt results and data published to your Amazon S3 bucket, which includes image frames and hero images. Your source images are unaffected.

Name

Required: Yes
Type: string

An identifier you assign to the stream processor. You can use Name to manage the stream processor. For example, you can get the current status of the stream processor by calling DescribeStreamProcessor. Name is idempotent. This is required for both face search and label detection stream processors.

NotificationChannel

Type: StreamProcessorNotificationChannel structure

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the object detection results and completion status of a video analysis operation.

Amazon Rekognition publishes a notification the first time an object of interest or a person is detected in the video stream. For example, if Amazon Rekognition detects a person at second 2, a pet at second 4, and a person again at second 5, Amazon Rekognition sends 2 object class detected notifications, one for a person at second 2 and one for a pet at second 4.

Amazon Rekognition also publishes an an end-of-session notification with a summary when the stream processing session is complete.

Output

Required: Yes
Type: StreamProcessorOutput structure

Kinesis data stream stream or Amazon S3 bucket location to which Amazon Rekognition Video puts the analysis results. If you are using the AWS CLI, the parameter name is StreamProcessorOutput. This must be a S3Destination of an Amazon S3 bucket that you own for a label detection stream processor or a Kinesis data stream ARN for a face search stream processor.

RegionsOfInterest

Type: Array of RegionOfInterest structures

Specifies locations in the frames where Amazon Rekognition checks for objects or people. You can specify up to 10 regions of interest, and each region has either a polygon or a bounding box. This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor.

RoleArn

Required: Yes
Type: string

The Amazon Resource Number (ARN) of the IAM role that allows access to the stream processor. The IAM role provides Rekognition read permissions for a Kinesis stream. It also provides write permissions to an Amazon S3 bucket and Amazon Simple Notification Service topic for a label detection stream processor. This is required for both face search and label detection stream processors.

Settings

Required: Yes
Type: StreamProcessorSettings structure

Input parameters used in a streaming video analyzed by a stream processor. You can use FaceSearch to recognize faces in a streaming video, or you can use ConnectedHome to detect labels.

Tags

Type: Associative array of custom strings keys (TagKey) to strings

A set of tags (key-value pairs) that you want to attach to the stream processor.

Result Syntax

[
    'StreamProcessorArn' => '<string>',
]

Result Details

Members

StreamProcessorArn

Type: string

Amazon Resource Number for the newly created stream processor.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ResourceInUseException:
The specified resource is already being used.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.

CreateUser

$result = $client->createUser([/* ... */]);
$promise = $client->createUserAsync([/* ... */]);

Creates a new User within a collection specified by CollectionId. Takes UserId as a parameter, which is a user provided ID which should be unique within the collection. The provided UserId will alias the system generated UUID to make the UserId more user friendly.

Uses a ClientToken, an idempotency token that ensures a call to CreateUser completes only once. If the value is not supplied, the AWS SDK generates an idempotency token for the requests. This prevents retries after a network error results from making multiple CreateUser calls.

Parameter Syntax

$result = $client->createUser([
    'ClientRequestToken' => '<string>',
    'CollectionId' => '<string>', // REQUIRED
    'UserId' => '<string>', // REQUIRED
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the request to CreateUser. If you use the same token with multiple CreateUser requests, the same response is returned. Use ClientRequestToken to prevent the same request from being processed more than once.

CollectionId

Required: Yes
Type: string

The ID of an existing collection to which the new UserID needs to be created.

UserId

Required: Yes
Type: string

ID for the UserID to be created. This ID needs to be unique within the collection.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ConflictException:
A User with the same Id already exists within the collection, or the update or deletion of the User caused an inconsistent state. **
ResourceNotFoundException:
The resource specified in the request cannot be found.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
IdempotentParameterMismatchException:
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.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

Examples

Example 1: CreateUser

Creates a new User within a collection specified by CollectionId.

$result = $client->createUser([
    'CollectionId' => 'MyCollection',
    'UserId' => 'DemoUser',
]);

DeleteCollection

$result = $client->deleteCollection([/* ... */]);
$promise = $client->deleteCollectionAsync([/* ... */]);

Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, see Deleting a collection.

This operation requires permissions to perform the rekognition:DeleteCollection action.

Parameter Syntax

$result = $client->deleteCollection([
    'CollectionId' => '<string>', // REQUIRED
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

ID of the collection to delete.

Result Syntax

[
    'StatusCode' => <integer>,
]

Result Details

Members

StatusCode

Type: int

HTTP status code that indicates the result of the operation.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To delete a collection

This operation deletes a Rekognition collection.

$result = $client->deleteCollection([
    'CollectionId' => 'myphotos',
]);

Result syntax:

[
    'StatusCode' => 200,
]

DeleteDataset

$result = $client->deleteDataset([/* ... */]);
$promise = $client->deleteDatasetAsync([/* ... */]);

Deletes an existing Amazon Rekognition Custom Labels dataset. Deleting a dataset might take while. Use DescribeDataset to check the current status. The dataset is still deleting if the value of Status is DELETE_IN_PROGRESS. If you try to access the dataset after it is deleted, you get a ResourceNotFoundException exception.

You can't delete a dataset while it is creating (Status = CREATE_IN_PROGRESS) or if the dataset is updating (Status = UPDATE_IN_PROGRESS).

This operation requires permissions to perform the rekognition:DeleteDataset action.

Parameter Syntax

$result = $client->deleteDataset([
    'DatasetArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

DatasetArn

Required: Yes
Type: string

The ARN of the Amazon Rekognition Custom Labels dataset that you want to delete.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ResourceInUseException:
The specified resource is already being used.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To delete an Amazon Rekognition Custom Labels dataset

Deletes an Amazon Rekognition Custom Labels dataset.

$result = $client->deleteDataset([
    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/dataset/test/1690556733321',
]);

Result syntax:

[
]

DeleteFaces

$result = $client->deleteFaces([/* ... */]);
$promise = $client->deleteFacesAsync([/* ... */]);

Deletes faces from a collection. You specify a collection ID and an array of face IDs to remove from the collection.

This operation requires permissions to perform the rekognition:DeleteFaces action.

Parameter Syntax

$result = $client->deleteFaces([
    'CollectionId' => '<string>', // REQUIRED
    'FaceIds' => ['<string>', ...], // REQUIRED
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

Collection from which to remove the specific faces.

FaceIds

Required: Yes
Type: Array of strings

An array of face IDs to delete.

Result Syntax

[
    'DeletedFaces' => ['<string>', ...],
    'UnsuccessfulFaceDeletions' => [
        [
            'FaceId' => '<string>',
            'Reasons' => ['<string>', ...],
            'UserId' => '<string>',
        ],
        // ...
    ],
]

Result Details

Members

DeletedFaces

Type: Array of strings

An array of strings (face IDs) of the faces that were deleted.

UnsuccessfulFaceDeletions

Type: Array of UnsuccessfulFaceDeletion structures

An array of any faces that weren't deleted.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To delete a face

This operation deletes one or more faces from a Rekognition collection.

$result = $client->deleteFaces([
    'CollectionId' => 'myphotos',
    'FaceIds' => [
        'ff43d742-0c13-5d16-a3e8-03d3f58e980b',
    ],
]);

Result syntax:

[
    'DeletedFaces' => [
        'ff43d742-0c13-5d16-a3e8-03d3f58e980b',
    ],
]

DeleteProject

$result = $client->deleteProject([/* ... */]);
$promise = $client->deleteProjectAsync([/* ... */]);

Deletes an Amazon Rekognition Custom Labels project. To delete a project you must first delete all models associated with the project. To delete a model, see DeleteProjectVersion.

DeleteProject is an asynchronous operation. To check if the project is deleted, call DescribeProjects. The project is deleted when the project no longer appears in the response. Be aware that deleting a given project will also delete any ProjectPolicies associated with that project.

This operation requires permissions to perform the rekognition:DeleteProject action.

Parameter Syntax

$result = $client->deleteProject([
    'ProjectArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

ProjectArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the project that you want to delete.

Result Syntax

[
    'Status' => 'CREATING|CREATED|DELETING',
]

Result Details

Members

Status

Type: string

The current status of the delete project operation.

Errors

ResourceInUseException:
The specified resource is already being used.
ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To delete an Amazon Rekognition Custom Labels project

Deletes an Amazon Rekognition Custom Labels projects.

$result = $client->deleteProject([
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690405809285',
]);

Result syntax:

[
    'Status' => 'DELETING',
]

DeleteProjectPolicy

$result = $client->deleteProjectPolicy([/* ... */]);
$promise = $client->deleteProjectPolicyAsync([/* ... */]);

Deletes an existing project policy.

To get a list of project policies attached to a project, call ListProjectPolicies. To attach a project policy to a project, call PutProjectPolicy.

This operation requires permissions to perform the rekognition:DeleteProjectPolicy action.

Parameter Syntax

$result = $client->deleteProjectPolicy([
    'PolicyName' => '<string>', // REQUIRED
    'PolicyRevisionId' => '<string>',
    'ProjectArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

PolicyName

Required: Yes
Type: string

The name of the policy that you want to delete.

PolicyRevisionId

Type: string

The ID of the project policy revision that you want to delete.

ProjectArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the project that the project policy you want to delete is attached to.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidPolicyRevisionIdException:
The supplied revision id for the project policy is invalid.

Examples

Example 1: DeleteProjectPolicy

This operation deletes a revision of an existing project policy from an Amazon Rekognition Custom Labels project.

$result = $client->deleteProjectPolicy([
    'PolicyName' => 'testPolicy1',
    'PolicyRevisionId' => '3b274c25e9203a56a99e00e3ff205fbc',
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/SourceProject/1656557123456',
]);

Result syntax:

[
]

DeleteProjectVersion

$result = $client->deleteProjectVersion([/* ... */]);
$promise = $client->deleteProjectVersionAsync([/* ... */]);

Deletes an Amazon Rekognition Custom Labels model.

You can't delete a model if it is running or if it is training. To check the status of a model, use the Status field returned from DescribeProjectVersions. To stop a running model call StopProjectVersion. If the model is training, wait until it finishes.

This operation requires permissions to perform the rekognition:DeleteProjectVersion action.

Parameter Syntax

$result = $client->deleteProjectVersion([
    'ProjectVersionArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

ProjectVersionArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the model version that you want to delete.

Result Syntax

[
    'Status' => 'TRAINING_IN_PROGRESS|TRAINING_COMPLETED|TRAINING_FAILED|STARTING|RUNNING|FAILED|STOPPING|STOPPED|DELETING|COPYING_IN_PROGRESS|COPYING_COMPLETED|COPYING_FAILED',
]

Result Details

Members

Status

Type: string

The status of the deletion operation.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceInUseException:
The specified resource is already being used.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To delete an Amazon Rekognition Custom Labels model

Deletes a version of an Amazon Rekognition Custom Labels model.

$result = $client->deleteProjectVersion([
    'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/version/1/1690556751958',
]);

Result syntax:

[
    'Status' => 'DELETING',
]

DeleteStreamProcessor

$result = $client->deleteStreamProcessor([/* ... */]);
$promise = $client->deleteStreamProcessorAsync([/* ... */]);

Deletes the stream processor identified by Name. You assign the value for Name when you create the stream processor with CreateStreamProcessor. You might not be able to use the same name for a stream processor for a few seconds after calling DeleteStreamProcessor.

Parameter Syntax

$result = $client->deleteStreamProcessor([
    'Name' => '<string>', // REQUIRED
]);

Parameter Details

Members

Name

Required: Yes
Type: string

The name of the stream processor you want to delete.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceInUseException:
The specified resource is already being used.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

DeleteUser

$result = $client->deleteUser([/* ... */]);
$promise = $client->deleteUserAsync([/* ... */]);

Deletes the specified UserID within the collection. Faces that are associated with the UserID are disassociated from the UserID before deleting the specified UserID. If the specified Collection or UserID is already deleted or not found, a ResourceNotFoundException will be thrown. If the action is successful with a 200 response, an empty HTTP body is returned.

Parameter Syntax

$result = $client->deleteUser([
    'ClientRequestToken' => '<string>',
    'CollectionId' => '<string>', // REQUIRED
    'UserId' => '<string>', // REQUIRED
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the request to DeleteUser. If you use the same token with multiple DeleteUser requests, the same response is returned. Use ClientRequestToken to prevent the same request from being processed more than once.

CollectionId

Required: Yes
Type: string

The ID of an existing collection from which the UserID needs to be deleted.

UserId

Required: Yes
Type: string

ID for the UserID to be deleted.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ConflictException:
A User with the same Id already exists within the collection, or the update or deletion of the User caused an inconsistent state. **
ResourceNotFoundException:
The resource specified in the request cannot be found.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
IdempotentParameterMismatchException:
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.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

Examples

Example 1: DeleteUser

Deletes the specified UserID within the collection.

$result = $client->deleteUser([
    'ClientRequestToken' => '550e8400-e29b-41d4-a716-446655440001',
    'CollectionId' => 'MyCollection',
    'UserId' => 'DemoUser',
]);

DescribeCollection

$result = $client->describeCollection([/* ... */]);
$promise = $client->describeCollectionAsync([/* ... */]);

Describes the specified collection. You can use DescribeCollection to get information, such as the number of faces indexed into a collection and the version of the model used by the collection for face detection.

For more information, see Describing a Collection in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->describeCollection([
    'CollectionId' => '<string>', // REQUIRED
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

The ID of the collection to describe.

Result Syntax

[
    'CollectionARN' => '<string>',
    'CreationTimestamp' => <DateTime>,
    'FaceCount' => <integer>,
    'FaceModelVersion' => '<string>',
    'UserCount' => <integer>,
]

Result Details

Members

CollectionARN

Type: string

The Amazon Resource Name (ARN) of the collection.

CreationTimestamp

Type: timestamp (string|DateTime or anything parsable by strtotime)

The number of milliseconds since the Unix epoch time until the creation of the collection. The Unix epoch time is 00:00:00 Coordinated Universal Time (UTC), Thursday, 1 January 1970.

FaceCount

Type: long (int|float)

The number of faces that are indexed into the collection. To index faces into a collection, use IndexFaces.

FaceModelVersion

Type: string

The version of the face model that's used by the collection for face detection.

For more information, see Model versioning in the Amazon Rekognition Developer Guide.

UserCount

Type: long (int|float)

The number of UserIDs assigned to the specified colleciton.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.

DescribeDataset

$result = $client->describeDataset([/* ... */]);
$promise = $client->describeDatasetAsync([/* ... */]);

Describes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a dataset and statistics about the images and labels in a dataset.

This operation requires permissions to perform the rekognition:DescribeDataset action.

Parameter Syntax

$result = $client->describeDataset([
    'DatasetArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

DatasetArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the dataset that you want to describe.

Result Syntax

[
    'DatasetDescription' => [
        'CreationTimestamp' => <DateTime>,
        'DatasetStats' => [
            'ErrorEntries' => <integer>,
            'LabeledEntries' => <integer>,
            'TotalEntries' => <integer>,
            'TotalLabels' => <integer>,
        ],
        'LastUpdatedTimestamp' => <DateTime>,
        'Status' => 'CREATE_IN_PROGRESS|CREATE_COMPLETE|CREATE_FAILED|UPDATE_IN_PROGRESS|UPDATE_COMPLETE|UPDATE_FAILED|DELETE_IN_PROGRESS',
        'StatusMessage' => '<string>',
        'StatusMessageCode' => 'SUCCESS|SERVICE_ERROR|CLIENT_ERROR',
    ],
]

Result Details

Members

DatasetDescription

Type: DatasetDescription structure

The description for the dataset.

Errors

InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To describe an Amazon Rekognition Custom Labels dataset

Describes an Amazon Rekognition Custom Labels dataset.

$result = $client->describeDataset([
    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/dataset/train/1690476084535',
]);

Result syntax:

[
    'DatasetDescription' => [
        'CreationTimestamp' => ,
        'DatasetStats' => [
            'ErrorEntries' => 0,
            'LabeledEntries' => 15,
            'TotalEntries' => 15,
            'TotalLabels' => 9,
        ],
        'LastUpdatedTimestamp' => ,
        'Status' => 'UPDATE_FAILED',
        'StatusMessage' => 'The manifest file contains images from multiple S3 buckets.',
        'StatusMessageCode' => 'CLIENT_ERROR',
    ],
]

DescribeProjectVersions

$result = $client->describeProjectVersions([/* ... */]);
$promise = $client->describeProjectVersionsAsync([/* ... */]);

Lists and describes the versions of a model in an Amazon Rekognition Custom Labels project. You can specify up to 10 model versions in ProjectVersionArns. If you don't specify a value, descriptions for all model versions in the project are returned.

This operation requires permissions to perform the rekognition:DescribeProjectVersions action.

Parameter Syntax

$result = $client->describeProjectVersions([
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'ProjectArn' => '<string>', // REQUIRED
    'VersionNames' => ['<string>', ...],
]);

Parameter Details

Members

MaxResults

Type: int

The maximum number of results to return per paginated call. The largest value you can specify is 100. If you specify a value greater than 100, a ValidationException error occurs. The default value is 100.

NextToken

Type: string

If the previous response was incomplete (because there is more results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. You can use this pagination token to retrieve the next set of results.

ProjectArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the project that contains the models you want to describe.

VersionNames

Type: Array of strings

A list of model version names that you want to describe. You can add up to 10 model version names to the list. If you don't specify a value, all model descriptions are returned. A version name is part of a model (ProjectVersion) ARN. For example, my-model.2020-01-21T09.10.15 is the version name in the following ARN. arn:aws:rekognition:us-east-1:123456789012:project/getting-started/version/my-model.2020-01-21T09.10.15/1234567890123.

Result Syntax

[
    'NextToken' => '<string>',
    'ProjectVersionDescriptions' => [
        [
            'BillableTrainingTimeInSeconds' => <integer>,
            'CreationTimestamp' => <DateTime>,
            'EvaluationResult' => [
                'F1Score' => <float>,
                'Summary' => [
                    'S3Object' => [
                        'Bucket' => '<string>',
                        'Name' => '<string>',
                        'Version' => '<string>',
                    ],
                ],
            ],
            'KmsKeyId' => '<string>',
            'ManifestSummary' => [
                'S3Object' => [
                    'Bucket' => '<string>',
                    'Name' => '<string>',
                    'Version' => '<string>',
                ],
            ],
            'MaxInferenceUnits' => <integer>,
            'MinInferenceUnits' => <integer>,
            'OutputConfig' => [
                'S3Bucket' => '<string>',
                'S3KeyPrefix' => '<string>',
            ],
            'ProjectVersionArn' => '<string>',
            'SourceProjectVersionArn' => '<string>',
            'Status' => 'TRAINING_IN_PROGRESS|TRAINING_COMPLETED|TRAINING_FAILED|STARTING|RUNNING|FAILED|STOPPING|STOPPED|DELETING|COPYING_IN_PROGRESS|COPYING_COMPLETED|COPYING_FAILED',
            'StatusMessage' => '<string>',
            'TestingDataResult' => [
                'Input' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => '<string>',
                                    'Name' => '<string>',
                                    'Version' => '<string>',
                                ],
                            ],
                        ],
                        // ...
                    ],
                    'AutoCreate' => true || false,
                ],
                'Output' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => '<string>',
                                    'Name' => '<string>',
                                    'Version' => '<string>',
                                ],
                            ],
                        ],
                        // ...
                    ],
                    'AutoCreate' => true || false,
                ],
                'Validation' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => '<string>',
                                    'Name' => '<string>',
                                    'Version' => '<string>',
                                ],
                            ],
                        ],
                        // ...
                    ],
                ],
            ],
            'TrainingDataResult' => [
                'Input' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => '<string>',
                                    'Name' => '<string>',
                                    'Version' => '<string>',
                                ],
                            ],
                        ],
                        // ...
                    ],
                ],
                'Output' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => '<string>',
                                    'Name' => '<string>',
                                    'Version' => '<string>',
                                ],
                            ],
                        ],
                        // ...
                    ],
                ],
                'Validation' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => '<string>',
                                    'Name' => '<string>',
                                    'Version' => '<string>',
                                ],
                            ],
                        ],
                        // ...
                    ],
                ],
            ],
            'TrainingEndTimestamp' => <DateTime>,
        ],
        // ...
    ],
]

Result Details

Members

NextToken

Type: string

ProjectVersionDescriptions

Type: Array of ProjectVersionDescription structures

A list of model descriptions. The list is sorted by the creation date and time of the model versions, latest to earliest.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To describe an Amazon Rekognition Custom Labels model

Describes a version of an Amazon Rekognition Custom Labels model.

$result = $client->describeProjectVersions([
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/1690474772815',
    'VersionNames' => [
        '1',
    ],
]);

Result syntax:

[
    'NextToken' => '',
    'ProjectVersionDescriptions' => [
        [
            'BillableTrainingTimeInSeconds' => 1899,
            'CreationTimestamp' => ,
            'EvaluationResult' => [
                'F1Score' => 1,
                'Summary' => [
                    'S3Object' => [
                        'Bucket' => 'custom-labels-console-us-east-1-111111111',
                        'Name' => 'my-model-output/EvaluationResultSummary-my-project-1.json',
                    ],
                ],
            ],
            'ManifestSummary' => [
                'S3Object' => [
                    'Bucket' => 'custom-labels-console-us-east-1-111111111',
                    'Name' => 'my-model-output/ManifestSummary-my-project-1.json',
                ],
            ],
            'OutputConfig' => [
                'S3Bucket' => 'custom-labels-console-us-east-1-111111111',
                'S3KeyPrefix' => 'my-model-output',
            ],
            'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/version/1/1690556751958',
            'Status' => 'TRAINING_COMPLETED',
            'StatusMessage' => 'The model is ready to run.',
            'TestingDataResult' => [
                'Input' => [
                    'AutoCreate' => ,
                ],
                'Output' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => 'custom-labels-console-us-east-1-111111111',
                                    'Name' => 'my-model-output/TestingGroundTruth-my-project-1.json',
                                ],
                            ],
                        ],
                    ],
                    'AutoCreate' => ,
                ],
                'Validation' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => 'custom-labels-console-us-east-1-111111111',
                                    'Name' => 'my-model-output/TestingManifestWithValidation-my-project-1.json',
                                ],
                            ],
                        ],
                    ],
                ],
            ],
            'TrainingDataResult' => [
                'Input' => [
                ],
                'Output' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => 'custom-labels-console-us-east-1-111111111',
                                    'Name' => 'my-model-output/TrainingGroundTruth-my-project-1.json',
                                ],
                            ],
                        ],
                    ],
                ],
                'Validation' => [
                    'Assets' => [
                        [
                            'GroundTruthManifest' => [
                                'S3Object' => [
                                    'Bucket' => 'custom-labels-console-us-east-1-111111111',
                                    'Name' => 'my-model-output/TrainingManifestWithValidation-my-project-1.json',
                                ],
                            ],
                        ],
                    ],
                ],
            ],
            'TrainingEndTimestamp' => ,
        ],
    ],
]

DescribeProjects

$result = $client->describeProjects([/* ... */]);
$promise = $client->describeProjectsAsync([/* ... */]);

Gets information about your Amazon Rekognition Custom Labels projects.

This operation requires permissions to perform the rekognition:DescribeProjects action.

Parameter Syntax

$result = $client->describeProjects([
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'ProjectNames' => ['<string>', ...],
]);

Parameter Details

Members

MaxResults

Type: int

NextToken

Type: string

ProjectNames

Type: Array of strings

A list of the projects that you want Amazon Rekognition Custom Labels to describe. If you don't specify a value, the response includes descriptions for all the projects in your AWS account.

Result Syntax

[
    'NextToken' => '<string>',
    'ProjectDescriptions' => [
        [
            'CreationTimestamp' => <DateTime>,
            'Datasets' => [
                [
                    'CreationTimestamp' => <DateTime>,
                    'DatasetArn' => '<string>',
                    'DatasetType' => 'TRAIN|TEST',
                    'Status' => 'CREATE_IN_PROGRESS|CREATE_COMPLETE|CREATE_FAILED|UPDATE_IN_PROGRESS|UPDATE_COMPLETE|UPDATE_FAILED|DELETE_IN_PROGRESS',
                    'StatusMessage' => '<string>',
                    'StatusMessageCode' => 'SUCCESS|SERVICE_ERROR|CLIENT_ERROR',
                ],
                // ...
            ],
            'ProjectArn' => '<string>',
            'Status' => 'CREATING|CREATED|DELETING',
        ],
        // ...
    ],
]

Result Details

Members

NextToken

Type: string

ProjectDescriptions

Type: Array of ProjectDescription structures

A list of project descriptions. The list is sorted by the date and time the projects are created.

Errors

InvalidPaginationTokenException:
Pagination token in the request is not valid.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To describe an Amazon Rekognition Custom Labels project.

Describes an Amazon Rekognition Custom Labels projects.

$result = $client->describeProjects([
    'ProjectNames' => [
        'my-project',
    ],
]);

Result syntax:

[
    'ProjectDescriptions' => [
        [
            'CreationTimestamp' => ,
            'Datasets' => [
                [
                    'CreationTimestamp' => ,
                    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/dataset/test/1655158654491',
                    'DatasetType' => 'TEST',
                    'Status' => 'CREATE_COMPLETE',
                    'StatusMessage' => 'The dataset was successfully created from the manifest file.',
                    'StatusMessageCode' => 'SUCCESS',
                ],
                [
                    'CreationTimestamp' => ,
                    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/dataset/train/1655158669954',
                    'DatasetType' => 'TRAIN',
                    'Status' => 'CREATE_COMPLETE',
                    'StatusMessage' => 'The dataset was successfully created from the manifest file.',
                    'StatusMessageCode' => 'SUCCESS',
                ],
            ],
            'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/1655158560634',
            'Status' => 'CREATED',
        ],
    ],
]

DescribeStreamProcessor

$result = $client->describeStreamProcessor([/* ... */]);
$promise = $client->describeStreamProcessorAsync([/* ... */]);

Provides information about a stream processor created by CreateStreamProcessor. You can get information about the input and output streams, the input parameters for the face recognition being performed, and the current status of the stream processor.

Parameter Syntax

$result = $client->describeStreamProcessor([
    'Name' => '<string>', // REQUIRED
]);

Parameter Details

Members

Name

Required: Yes
Type: string

Name of the stream processor for which you want information.

Result Syntax

[
    'CreationTimestamp' => <DateTime>,
    'DataSharingPreference' => [
        'OptIn' => true || false,
    ],
    'Input' => [
        'KinesisVideoStream' => [
            'Arn' => '<string>',
        ],
    ],
    'KmsKeyId' => '<string>',
    'LastUpdateTimestamp' => <DateTime>,
    'Name' => '<string>',
    'NotificationChannel' => [
        'SNSTopicArn' => '<string>',
    ],
    'Output' => [
        'KinesisDataStream' => [
            'Arn' => '<string>',
        ],
        'S3Destination' => [
            'Bucket' => '<string>',
            'KeyPrefix' => '<string>',
        ],
    ],
    'RegionsOfInterest' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Polygon' => [
                [
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
        ],
        // ...
    ],
    'RoleArn' => '<string>',
    'Settings' => [
        'ConnectedHome' => [
            'Labels' => ['<string>', ...],
            'MinConfidence' => <float>,
        ],
        'FaceSearch' => [
            'CollectionId' => '<string>',
            'FaceMatchThreshold' => <float>,
        ],
    ],
    'Status' => 'STOPPED|STARTING|RUNNING|FAILED|STOPPING|UPDATING',
    'StatusMessage' => '<string>',
    'StreamProcessorArn' => '<string>',
]

Result Details

Members

CreationTimestamp

Type: timestamp (string|DateTime or anything parsable by strtotime)

Date and time the stream processor was created

DataSharingPreference

Type: StreamProcessorDataSharingPreference structure

Input

Type: StreamProcessorInput structure

Kinesis video stream that provides the source streaming video.

KmsKeyId

Type: string

The identifier for your AWS Key Management Service key (AWS KMS key). This is an optional parameter for label detection stream processors.

LastUpdateTimestamp

Type: timestamp (string|DateTime or anything parsable by strtotime)

The time, in Unix format, the stream processor was last updated. For example, when the stream processor moves from a running state to a failed state, or when the user starts or stops the stream processor.

Name

Type: string

Name of the stream processor.

NotificationChannel

Type: StreamProcessorNotificationChannel structure

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the object detection results and completion status of a video analysis operation.

Amazon Rekognition also publishes an an end-of-session notification with a summary when the stream processing session is complete.

Output

Type: StreamProcessorOutput structure

Kinesis data stream to which Amazon Rekognition Video puts the analysis results.

RegionsOfInterest

Type: Array of RegionOfInterest structures

Specifies locations in the frames where Amazon Rekognition checks for objects or people. This is an optional parameter for label detection stream processors.

RoleArn

Type: string

ARN of the IAM role that allows access to the stream processor.

Settings

Type: StreamProcessorSettings structure

Input parameters used in a streaming video analyzed by a stream processor. You can use FaceSearch to recognize faces in a streaming video, or you can use ConnectedHome to detect labels.

Status

Type: string

Current status of the stream processor.

StatusMessage

Type: string

Detailed status message about the stream processor.

StreamProcessorArn

Type: string

ARN of the stream processor.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

DetectCustomLabels

$result = $client->detectCustomLabels([/* ... */]);
$promise = $client->detectCustomLabelsAsync([/* ... */]);

Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model.

You specify which version of a model version to use by using the ProjectVersionArn input parameter.

You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.

For each object that the model version detects on an image, the API returns a (CustomLabel) object in an array (CustomLabels). Each CustomLabel object provides the label name (Name), the level of confidence that the image contains the object (Confidence), and object location information, if it exists, for the label on the image (Geometry).

To filter labels that are returned, specify a value for MinConfidence. DetectCustomLabelsLabels only returns labels with a confidence that's higher than the specified value. The value of MinConfidence maps to the assumed threshold values created during training. For more information, see Assumed threshold in the Amazon Rekognition Custom Labels Developer Guide. Amazon Rekognition Custom Labels metrics expresses an assumed threshold as a floating point value between 0-1. The range of MinConfidence normalizes the threshold value to a percentage value (0-100). Confidence responses from DetectCustomLabels are also returned as a percentage. You can use MinConfidence to change the precision and recall or your model. For more information, see Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.

If you don't specify a value for MinConfidence, DetectCustomLabels returns labels based on the assumed threshold of each label.

This is a stateless API operation. That is, the operation does not persist any data.

This operation requires permissions to perform the rekognition:DetectCustomLabels action.

For more information, see Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.

Parameter Syntax

$result = $client->detectCustomLabels([
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'MaxResults' => <integer>,
    'MinConfidence' => <float>,
    'ProjectVersionArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

Image

Required: Yes
Type: Image structure

Provides the input image either as bytes or an S3 object.

You pass image bytes to an Amazon Rekognition API operation by using the Bytes property. For example, you would use the Bytes property to pass an image loaded from a local file system. Image bytes passed by using the Bytes property must be base64-encoded. Your code may not need to encode image bytes if you are using an AWS SDK to call Amazon Rekognition API operations.

For more information, see Analyzing an Image Loaded from a Local File System in the Amazon Rekognition Developer Guide.

You pass images stored in an S3 bucket to an Amazon Rekognition API operation by using the S3Object property. Images stored in an S3 bucket do not need to be base64-encoded.

The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes using the Bytes property is not supported. You must first upload the image to an Amazon S3 bucket and then call the operation using the S3Object property.

For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide.

MaxResults

Type: int

Maximum number of results you want the service to return in the response. The service returns the specified number of highest confidence labels ranked from highest confidence to lowest.

MinConfidence

Type: float

Specifies the minimum confidence level for the labels to return. DetectCustomLabels doesn't return any labels with a confidence value that's lower than this specified value. If you specify a value of 0, DetectCustomLabels returns all labels, regardless of the assumed threshold applied to each label. If you don't specify a value for MinConfidence, DetectCustomLabels returns labels based on the assumed threshold of each label.

ProjectVersionArn

Required: Yes
Type: string

The ARN of the model version that you want to use.

Result Syntax

[
    'CustomLabels' => [
        [
            'Confidence' => <float>,
            'Geometry' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Polygon' => [
                    [
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
            ],
            'Name' => '<string>',
        ],
        // ...
    ],
]

Result Details

Members

CustomLabels

Type: Array of CustomLabel structures

An array of custom labels detected in the input image.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceNotReadyException:
The requested resource isn't ready. For example, this exception occurs when you call DetectCustomLabels with a model version that isn't deployed.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

Examples

Example 1: To detect custom labels in an image with an Amazon Rekognition Custom Labels model

Detects custom labels in an image with an Amazon Rekognition Custom Labels model

$result = $client->detectCustomLabels([
    'Image' => [
        'S3Object' => [
            'Bucket' => 'custom-labels-console-us-east-1-1111111111',
            'Name' => 'assets/flowers_1_test_dataset/camellia4.jpg',
        ],
    ],
    'MaxResults' => 100,
    'MinConfidence' => 50,
    'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/version/my-project.2023-07-31T11.49.37/1690829378219',
]);

Result syntax:

[
    'CustomLabels' => [
        [
            'Confidence' => 67.563995361328,
            'Name' => 'with_leaves',
        ],
        [
            'Confidence' => 50.656997680664,
            'Name' => 'without_leaves',
        ],
    ],
]

DetectFaces

$result = $client->detectFaces([/* ... */]);
$promise = $client->detectFacesAsync([/* ... */]);

Detects faces within an image that is provided as input.

DetectFaces detects the 100 largest faces in the image. For each face detected, the operation returns face details. These details include a bounding box of the face, a confidence value (that the bounding box contains a face), and a fixed set of attributes such as facial landmarks (for example, coordinates of eye and mouth), pose, presence of facial occlusion, and so on.

The face-detection algorithm is most effective on frontal faces. For non-frontal or obscured faces, the algorithm might not detect the faces or might detect faces with lower confidence.

You pass the input image either as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.

This is a stateless API operation. That is, the operation does not persist any data.

This operation requires permissions to perform the rekognition:DetectFaces action.

Parameter Syntax

$result = $client->detectFaces([
    'Attributes' => ['<string>', ...],
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

Attributes

Type: Array of strings

An array of facial attributes you want to be returned. A DEFAULT subset of facial attributes - BoundingBox, Confidence, Pose, Quality, and Landmarks - will always be returned. You can request for specific facial attributes (in addition to the default list) - by using ["DEFAULT", "FACE_OCCLUDED"] or just ["FACE_OCCLUDED"]. You can request for all facial attributes by using ["ALL"]. Requesting more attributes may increase response time.

If you provide both, ["ALL", "DEFAULT"], the service uses a logical "AND" operator to determine which attributes to return (in this case, all attributes).

Note that while the FaceOccluded and EyeDirection attributes are supported when using DetectFaces, they aren't supported when analyzing videos with StartFaceDetection and GetFaceDetection.

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported.

Result Syntax

[
    'FaceDetails' => [
        [
            'AgeRange' => [
                'High' => <integer>,
                'Low' => <integer>,
            ],
            'Beard' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Confidence' => <float>,
            'Emotions' => [
                [
                    'Confidence' => <float>,
                    'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                ],
                // ...
            ],
            'EyeDirection' => [
                'Confidence' => <float>,
                'Pitch' => <float>,
                'Yaw' => <float>,
            ],
            'Eyeglasses' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'EyesOpen' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'FaceOccluded' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Gender' => [
                'Confidence' => <float>,
                'Value' => 'Male|Female',
            ],
            'Landmarks' => [
                [
                    'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
            'MouthOpen' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Mustache' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Pose' => [
                'Pitch' => <float>,
                'Roll' => <float>,
                'Yaw' => <float>,
            ],
            'Quality' => [
                'Brightness' => <float>,
                'Sharpness' => <float>,
            ],
            'Smile' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Sunglasses' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
        ],
        // ...
    ],
    'OrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
]

Result Details

Members

FaceDetails

Type: Array of FaceDetail structures

Details of each face found in the image.

OrientationCorrection

Type: string

The value of OrientationCorrection is always null.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

Examples

Example 1: To detect faces in an image

This operation detects faces in an image stored in an AWS S3 bucket.

$result = $client->detectFaces([
    'Image' => [
        'S3Object' => [
            'Bucket' => 'mybucket',
            'Name' => 'myphoto',
        ],
    ],
]);

Result syntax:

[
    'FaceDetails' => [
        [
            'BoundingBox' => [
                'Height' => 0.18000000715256,
                'Left' => 0.55555558204651,
                'Top' => 0.33666667342186,
                'Width' => 0.23999999463558,
            ],
            'Confidence' => 100,
            'Landmarks' => [
                [
                    'Type' => 'eyeLeft',
                    'X' => 0.63947373628616,
                    'Y' => 0.40819624066353,
                ],
                [
                    'Type' => 'eyeRight',
                    'X' => 0.72666609287262,
                    'Y' => 0.41039225459099,
                ],
                [
                    'Type' => 'eyeRight',
                    'X' => 0.69124621152878,
                    'Y' => 0.44240960478783,
                ],
                [
                    'Type' => 'mouthDown',
                    'X' => 0.63061982393265,
                    'Y' => 0.46700039505959,
                ],
                [
                    'Type' => 'mouthUp',
                    'X' => 0.72156089544296,
                    'Y' => 0.47114261984825,
                ],
            ],
            'Pose' => [
                'Pitch' => 4.0508065223694,
                'Roll' => 0.99507474899292,
                'Yaw' => 13.693790435791,
            ],
            'Quality' => [
                'Brightness' => 37.601699829102,
                'Sharpness' => 80,
            ],
        ],
    ],
    'OrientationCorrection' => 'ROTATE_0',
]

DetectLabels

$result = $client->detectLabels([/* ... */]);
$promise = $client->detectLabelsAsync([/* ... */]);

Detects instances of real-world entities within an image (JPEG or PNG) provided as input. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; and concepts like landscape, evening, and nature.

For an example, see Analyzing images stored in an Amazon S3 bucket in the Amazon Rekognition Developer Guide.

Optional Parameters

You can specify one or both of the GENERAL_LABELS and IMAGE_PROPERTIES feature types when calling the DetectLabels API. Including GENERAL_LABELS will ensure the response includes the labels detected in the input image, while including IMAGE_PROPERTIES will ensure the response includes information about the image quality and color.

When using GENERAL_LABELS and/or IMAGE_PROPERTIES you can provide filtering criteria to the Settings parameter. You can filter with sets of individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information on filtering see Detecting Labels in an Image.

When getting labels, you can specify MinConfidence to control the confidence threshold for the labels returned. The default is 55%. You can also add the MaxLabels parameter to limit the number of labels returned. The default and upper limit is 1000 labels. These arguments are only valid when supplying GENERAL_LABELS as a feature type.

Response Elements

For each object, scene, and concept the API returns one or more labels. The API returns the following types of information about labels:

Name - The name of the detected label.
Confidence - The level of confidence in the label assigned to a detected object.
Parents - The ancestor labels for a detected label. DetectLabels returns a hierarchical taxonomy of detected labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.
Aliases - Possible Aliases for the label.
Categories - The label categories that the detected label belongs to.
BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label on the input image. It also includes the confidence for the accuracy of the detected bounding box.

The API returns the following information regarding the image, as part of the ImageProperties structure:

Quality - Information about the Sharpness, Brightness, and Contrast of the input image, scored between 0 to 100. Image quality is returned for the entire image, as well as the background and the foreground.
Dominant Color - An array of the dominant colors in the image.
Foreground - Information about the sharpness, brightness, and dominant colors of the input image’s foreground.
Background - Information about the sharpness, brightness, and dominant colors of the input image’s background.

The list of returned labels will include at least one label for every detected object, along with information about that label. In the following example, suppose the input image has a lighthouse, the sea, and a rock. The response includes all three labels, one for each object, as well as the confidence in the label:

{Name: lighthouse, Confidence: 98.4629}

{Name: rock,Confidence: 79.2097}

{Name: sea,Confidence: 75.061}

The list of labels can include multiple labels for the same object. For example, if the input image shows a flower (for example, a tulip), the operation might return the following three labels.

{Name: flower,Confidence: 99.0562}

{Name: plant,Confidence: 99.0562}

{Name: tulip,Confidence: 99.0562}

In this example, the detection algorithm more precisely identifies the flower as a tulip.

If the object detected is a person, the operation doesn't provide the same facial details that the DetectFaces operation provides.

This is a stateless API operation that doesn't return any data.

This operation requires permissions to perform the rekognition:DetectLabels action.

Parameter Syntax

$result = $client->detectLabels([
    'Features' => ['<string>', ...],
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'MaxLabels' => <integer>,
    'MinConfidence' => <float>,
    'Settings' => [
        'GeneralLabels' => [
            'LabelCategoryExclusionFilters' => ['<string>', ...],
            'LabelCategoryInclusionFilters' => ['<string>', ...],
            'LabelExclusionFilters' => ['<string>', ...],
            'LabelInclusionFilters' => ['<string>', ...],
        ],
        'ImageProperties' => [
            'MaxDominantColors' => <integer>,
        ],
    ],
]);

Parameter Details

Members

Features

Type: Array of strings

A list of the types of analysis to perform. Specifying GENERAL_LABELS uses the label detection feature, while specifying IMAGE_PROPERTIES returns information regarding image color and quality. If no option is specified GENERAL_LABELS is used by default.

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. Images stored in an S3 Bucket do not need to be base64-encoded.

MaxLabels

Type: int

Maximum number of labels you want the service to return in the response. The service returns the specified number of highest confidence labels. Only valid when GENERAL_LABELS is specified as a feature type in the Feature input parameter.

MinConfidence

Type: float

Specifies the minimum confidence level for the labels to return. Amazon Rekognition doesn't return any labels with confidence lower than this specified value.

If MinConfidence is not specified, the operation returns labels with a confidence values greater than or equal to 55 percent. Only valid when GENERAL_LABELS is specified as a feature type in the Feature input parameter.

Settings

Type: DetectLabelsSettings structure

A list of the filters to be applied to returned detected labels and image properties. Specified filters can be inclusive, exclusive, or a combination of both. Filters can be used for individual labels or label categories. The exact label names or label categories must be supplied. For a full list of labels and label categories, see Detecting labels.

Result Syntax

[
    'ImageProperties' => [
        'Background' => [
            'DominantColors' => [
                [
                    'Blue' => <integer>,
                    'CSSColor' => '<string>',
                    'Green' => <integer>,
                    'HexCode' => '<string>',
                    'PixelPercent' => <float>,
                    'Red' => <integer>,
                    'SimplifiedColor' => '<string>',
                ],
                // ...
            ],
            'Quality' => [
                'Brightness' => <float>,
                'Contrast' => <float>,
                'Sharpness' => <float>,
            ],
        ],
        'DominantColors' => [
            [
                'Blue' => <integer>,
                'CSSColor' => '<string>',
                'Green' => <integer>,
                'HexCode' => '<string>',
                'PixelPercent' => <float>,
                'Red' => <integer>,
                'SimplifiedColor' => '<string>',
            ],
            // ...
        ],
        'Foreground' => [
            'DominantColors' => [
                [
                    'Blue' => <integer>,
                    'CSSColor' => '<string>',
                    'Green' => <integer>,
                    'HexCode' => '<string>',
                    'PixelPercent' => <float>,
                    'Red' => <integer>,
                    'SimplifiedColor' => '<string>',
                ],
                // ...
            ],
            'Quality' => [
                'Brightness' => <float>,
                'Contrast' => <float>,
                'Sharpness' => <float>,
            ],
        ],
        'Quality' => [
            'Brightness' => <float>,
            'Contrast' => <float>,
            'Sharpness' => <float>,
        ],
    ],
    'LabelModelVersion' => '<string>',
    'Labels' => [
        [
            'Aliases' => [
                [
                    'Name' => '<string>',
                ],
                // ...
            ],
            'Categories' => [
                [
                    'Name' => '<string>',
                ],
                // ...
            ],
            'Confidence' => <float>,
            'Instances' => [
                [
                    'BoundingBox' => [
                        'Height' => <float>,
                        'Left' => <float>,
                        'Top' => <float>,
                        'Width' => <float>,
                    ],
                    'Confidence' => <float>,
                    'DominantColors' => [
                        [
                            'Blue' => <integer>,
                            'CSSColor' => '<string>',
                            'Green' => <integer>,
                            'HexCode' => '<string>',
                            'PixelPercent' => <float>,
                            'Red' => <integer>,
                            'SimplifiedColor' => '<string>',
                        ],
                        // ...
                    ],
                ],
                // ...
            ],
            'Name' => '<string>',
            'Parents' => [
                [
                    'Name' => '<string>',
                ],
                // ...
            ],
        ],
        // ...
    ],
    'OrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
]

Result Details

Members

ImageProperties

Type: DetectLabelsImageProperties structure

Information about the properties of the input image, such as brightness, sharpness, contrast, and dominant colors.

LabelModelVersion

Type: string

Version number of the label detection model that was used to detect labels.

Labels

Type: Array of Label structures

An array of labels for the real-world objects detected.

OrientationCorrection

Type: string

The value of OrientationCorrection is always null.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

Examples

Example 1: To detect labels

This operation detects labels in the supplied image

$result = $client->detectLabels([
    'Image' => [
        'S3Object' => [
            'Bucket' => 'mybucket',
            'Name' => 'myphoto',
        ],
    ],
    'MaxLabels' => 123,
    'MinConfidence' => 70,
]);

Result syntax:

[
    'Labels' => [
        [
            'Confidence' => 99.25072479248,
            'Name' => 'People',
        ],
        [
            'Confidence' => 99.25074005127,
            'Name' => 'Person',
        ],
    ],
]

DetectModerationLabels

$result = $client->detectModerationLabels([/* ... */]);
$promise = $client->detectModerationLabelsAsync([/* ... */]);

Detects unsafe content in a specified JPEG or PNG format image. Use DetectModerationLabels to moderate images depending on your requirements. For example, you might want to filter images that contain nudity, but not images containing suggestive content.

To filter images, use the labels returned by DetectModerationLabels to determine which types of content are appropriate.

For information about moderation labels, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->detectModerationLabels([
    'HumanLoopConfig' => [
        'DataAttributes' => [
            'ContentClassifiers' => ['<string>', ...],
        ],
        'FlowDefinitionArn' => '<string>', // REQUIRED
        'HumanLoopName' => '<string>', // REQUIRED
    ],
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'MinConfidence' => <float>,
]);

Parameter Details

Members

HumanLoopConfig

Type: HumanLoopConfig structure

Sets up the configuration for human evaluation, including the FlowDefinition the image will be sent to.

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported.

MinConfidence

Type: float

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

If you don't specify MinConfidence, the operation returns labels with confidence values greater than or equal to 50 percent.

Result Syntax

[
    'HumanLoopActivationOutput' => [
        'HumanLoopActivationConditionsEvaluationResults' => '<string>',
        'HumanLoopActivationReasons' => ['<string>', ...],
        'HumanLoopArn' => '<string>',
    ],
    'ModerationLabels' => [
        [
            'Confidence' => <float>,
            'Name' => '<string>',
            'ParentName' => '<string>',
        ],
        // ...
    ],
    'ModerationModelVersion' => '<string>',
]

Result Details

Members

HumanLoopActivationOutput

Type: HumanLoopActivationOutput structure

Shows the results of the human in the loop evaluation.

ModerationLabels

Type: Array of ModerationLabel structures

Array of detected Moderation labels and the time, in milliseconds from the start of the video, they were detected.

ModerationModelVersion

Type: string

Version number of the moderation detection model that was used to detect unsafe content.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.
HumanLoopQuotaExceededException:
The number of in-progress human reviews you have has exceeded the number allowed.

DetectProtectiveEquipment

$result = $client->detectProtectiveEquipment([/* ... */]);
$promise = $client->detectProtectiveEquipmentAsync([/* ... */]);

Detects Personal Protective Equipment (PPE) worn by people detected in an image. Amazon Rekognition can detect the following types of PPE.

Face cover
Hand cover
Head cover

You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. The image must be either a PNG or JPG formatted file.

DetectProtectiveEquipment detects PPE worn by up to 15 persons detected in an image.

For each person detected in the image the API returns an array of body parts (face, head, left-hand, right-hand). For each body part, an array of detected items of PPE is returned, including an indicator of whether or not the PPE covers the body part. The API returns the confidence it has in each detection (person, PPE, body part and body part coverage). It also returns a bounding box (BoundingBox) for each detected person and each detected item of PPE.

You can optionally request a summary of detected PPE items with the SummarizationAttributes input parameter. The summary provides the following information.

The persons detected as wearing all of the types of PPE that you specify.
The persons detected as not wearing all of the types PPE that you specify.
The persons detected where PPE adornment could not be determined.

This is a stateless API operation. That is, the operation does not persist any data.

This operation requires permissions to perform the rekognition:DetectProtectiveEquipment action.

Parameter Syntax

$result = $client->detectProtectiveEquipment([
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'SummarizationAttributes' => [
        'MinConfidence' => <float>, // REQUIRED
        'RequiredEquipmentTypes' => ['<string>', ...], // REQUIRED
    ],
]);

Parameter Details

Members

Image

Required: Yes
Type: Image structure

The image in which you want to detect PPE on detected persons. The image can be passed as image bytes or you can reference an image stored in an Amazon S3 bucket.

SummarizationAttributes

Type: ProtectiveEquipmentSummarizationAttributes structure

An array of PPE types that you want to summarize.

Result Syntax

[
    'Persons' => [
        [
            'BodyParts' => [
                [
                    'Confidence' => <float>,
                    'EquipmentDetections' => [
                        [
                            'BoundingBox' => [
                                'Height' => <float>,
                                'Left' => <float>,
                                'Top' => <float>,
                                'Width' => <float>,
                            ],
                            'Confidence' => <float>,
                            'CoversBodyPart' => [
                                'Confidence' => <float>,
                                'Value' => true || false,
                            ],
                            'Type' => 'FACE_COVER|HAND_COVER|HEAD_COVER',
                        ],
                        // ...
                    ],
                    'Name' => 'FACE|HEAD|LEFT_HAND|RIGHT_HAND',
                ],
                // ...
            ],
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Confidence' => <float>,
            'Id' => <integer>,
        ],
        // ...
    ],
    'ProtectiveEquipmentModelVersion' => '<string>',
    'Summary' => [
        'PersonsIndeterminate' => [<integer>, ...],
        'PersonsWithRequiredEquipment' => [<integer>, ...],
        'PersonsWithoutRequiredEquipment' => [<integer>, ...],
    ],
]

Result Details

Members

Persons

Type: Array of ProtectiveEquipmentPerson structures

An array of persons detected in the image (including persons not wearing PPE).

ProtectiveEquipmentModelVersion

Type: string

The version number of the PPE detection model used to detect PPE in the image.

Summary

Type: ProtectiveEquipmentSummary structure

Summary information for the types of PPE specified in the SummarizationAttributes input parameter.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

DetectText

$result = $client->detectText([/* ... */]);
$promise = $client->detectTextAsync([/* ... */]);

Detects text in the input image and converts it into machine-readable text.

Pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, you must pass it as a reference to an image in an Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The image must be either a .png or .jpeg formatted file.

The DetectText operation returns text in an array of TextDetection elements, TextDetections. Each TextDetection element provides information about a single word or line of text that was detected in the image.

A word is one or more script characters that are not separated by spaces. DetectText can detect up to 100 words in an image.

A line is a string of equally spaced words. A line isn't necessarily a complete sentence. For example, a driver's license number is detected as a line. A line ends when there is no aligned text after it. Also, a line ends when there is a large gap between words, relative to the length of the words. This means, depending on the gap between words, Amazon Rekognition may detect multiple lines in text aligned in the same direction. Periods don't represent the end of a line. If a sentence spans multiple lines, the DetectText operation returns multiple lines.

To determine whether a TextDetection element is a line of text or a word, use the TextDetection object Type field.

To be detected, text must be within +/- 90 degrees orientation of the horizontal axis.

For more information, see Detecting text in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->detectText([
    'Filters' => [
        'RegionsOfInterest' => [
            [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Polygon' => [
                    [
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
            ],
            // ...
        ],
        'WordFilter' => [
            'MinBoundingBoxHeight' => <float>,
            'MinBoundingBoxWidth' => <float>,
            'MinConfidence' => <float>,
        ],
    ],
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

Filters

Type: DetectTextFilters structure

Optional parameters that let you set the criteria that the text must meet to be included in your response.

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an Amazon S3 object. If you use the AWS CLI to call Amazon Rekognition operations, you can't pass image bytes.

Result Syntax

[
    'TextDetections' => [
        [
            'Confidence' => <float>,
            'DetectedText' => '<string>',
            'Geometry' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Polygon' => [
                    [
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
            ],
            'Id' => <integer>,
            'ParentId' => <integer>,
            'Type' => 'LINE|WORD',
        ],
        // ...
    ],
    'TextModelVersion' => '<string>',
]

Result Details

Members

TextDetections

Type: Array of TextDetection structures

An array of text that was detected in the input image.

TextModelVersion

Type: string

The model version used to detect text.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

DisassociateFaces

$result = $client->disassociateFaces([/* ... */]);
$promise = $client->disassociateFacesAsync([/* ... */]);

Removes the association between a Face supplied in an array of FaceIds and the User. If the User is not present already, then a ResourceNotFound exception is thrown. If successful, an array of faces that are disassociated from the User is returned. If a given face is already disassociated from the given UserID, it will be ignored and not be returned in the response. If a given face is already associated with a different User or not found in the collection it will be returned as part of UnsuccessfulDisassociations. You can remove 1 - 100 face IDs from a user at one time.

Parameter Syntax

$result = $client->disassociateFaces([
    'ClientRequestToken' => '<string>',
    'CollectionId' => '<string>', // REQUIRED
    'FaceIds' => ['<string>', ...], // REQUIRED
    'UserId' => '<string>', // REQUIRED
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the request to DisassociateFaces. If you use the same token with multiple DisassociateFaces requests, the same response is returned. Use ClientRequestToken to prevent the same request from being processed more than once.

CollectionId

Required: Yes
Type: string

The ID of an existing collection containing the UserID.

FaceIds

Required: Yes
Type: Array of strings

An array of face IDs to disassociate from the UserID.

UserId

Required: Yes
Type: string

ID for the existing UserID.

Result Syntax

[
    'DisassociatedFaces' => [
        [
            'FaceId' => '<string>',
        ],
        // ...
    ],
    'UnsuccessfulFaceDisassociations' => [
        [
            'FaceId' => '<string>',
            'Reasons' => ['<string>', ...],
            'UserId' => '<string>',
        ],
        // ...
    ],
    'UserStatus' => 'ACTIVE|UPDATING|CREATING|CREATED',
]

Result Details

Members

DisassociatedFaces

Type: Array of DisassociatedFace structures

An array of DissociatedFace objects containing FaceIds that are successfully disassociated with the UserID is returned. Returned if the DisassociatedFaces action is successful.

UnsuccessfulFaceDisassociations

Type: Array of UnsuccessfulFaceDisassociation structures

An array of UnsuccessfulDisassociation objects containing FaceIds that are not successfully associated, along with the reasons for the failure to associate. Returned if the DisassociateFaces action is successful.

UserStatus

Type: string

The status of an update made to a User. Reflects if the User has been updated for every requested change.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
IdempotentParameterMismatchException:
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:
The resource specified in the request cannot be found.
ConflictException:
A User with the same Id already exists within the collection, or the update or deletion of the User caused an inconsistent state. **

Examples

Example 1: DisassociateFaces

Removes the association between a Face supplied in an array of FaceIds and the User.

$result = $client->disassociateFaces([
    'ClientRequestToken' => '550e8400-e29b-41d4-a716-446655440003',
    'CollectionId' => 'MyCollection',
    'FaceIds' => [
        'f5817d37-94f6-4335-bfee-6cf79a3d806e',
        'c92265d4-5f9c-43af-a58e-12be0ce02bc3',
    ],
    'UserId' => 'DemoUser',
]);

Result syntax:

[
    'DisassociatedFaces' => [
        [
            'FaceId' => 'c92265d4-5f9c-43af-a58e-12be0ce02bc3',
        ],
    ],
    'UnsuccessfulFaceDisassociations' => [
        [
            'FaceId' => 'f5817d37-94f6-4335-bfee-6cf79a3d806e',
            'Reasons' => [
                'ASSOCIATED_TO_A_DIFFERENT_USER',
            ],
            'UserId' => 'demoUser1',
        ],
    ],
    'UserStatus' => 'UPDATING',
]

DistributeDatasetEntries

$result = $client->distributeDatasetEntries([/* ... */]);
$promise = $client->distributeDatasetEntriesAsync([/* ... */]);

Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a project. DistributeDatasetEntries moves 20% of the training dataset images to the test dataset. An entry is a JSON Line that describes an image.

You supply the Amazon Resource Names (ARN) of a project's training dataset and test dataset. The training dataset must contain the images that you want to split. The test dataset must be empty. The datasets must belong to the same project. To create training and test datasets for a project, call CreateDataset.

Distributing a dataset takes a while to complete. To check the status call DescribeDataset. The operation is complete when the Status field for the training dataset and the test dataset is UPDATE_COMPLETE. If the dataset split fails, the value of Status is UPDATE_FAILED.

This operation requires permissions to perform the rekognition:DistributeDatasetEntries action.

Parameter Syntax

$result = $client->distributeDatasetEntries([
    'Datasets' => [ // REQUIRED
        [
            'Arn' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members

Datasets

Required: Yes
Type: Array of DistributeDataset structures

The ARNS for the training dataset and test dataset that you want to use. The datasets must belong to the same project. The test dataset must be empty.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotReadyException:
The requested resource isn't ready. For example, this exception occurs when you call DetectCustomLabels with a model version that isn't deployed.

Examples

Example 1: To distribute an Amazon Rekognition Custom Labels dataset

Distributes an Amazon Rekognition Custom Labels training dataset to a test dataset.

$result = $client->distributeDatasetEntries([
    'Datasets' => [
        [
            'Arn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/train/1690564858106',
        ],
        [
            'Arn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/test/1690564858106',
        ],
    ],
]);

Result syntax:

[
]

GetCelebrityInfo

$result = $client->getCelebrityInfo([/* ... */]);
$promise = $client->getCelebrityInfoAsync([/* ... */]);

Gets the name and additional information about a celebrity based on their Amazon Rekognition ID. The additional information is returned as an array of URLs. If there is no additional information about the celebrity, this list is empty.

For more information, see Getting information about a celebrity in the Amazon Rekognition Developer Guide.

This operation requires permissions to perform the rekognition:GetCelebrityInfo action.

Parameter Syntax

$result = $client->getCelebrityInfo([
    'Id' => '<string>', // REQUIRED
]);

Parameter Details

Members

Id

Required: Yes
Type: string

The ID for the celebrity. You get the celebrity ID from a call to the RecognizeCelebrities operation, which recognizes celebrities in an image.

Result Syntax

[
    'KnownGender' => [
        'Type' => 'Male|Female|Nonbinary|Unlisted',
    ],
    'Name' => '<string>',
    'Urls' => ['<string>', ...],
]

Result Details

Members

KnownGender

Type: KnownGender structure

Retrieves the known gender for the celebrity.

Name

Type: string

The name of the celebrity.

Urls

Type: Array of strings

An array of URLs pointing to additional celebrity information.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.

GetCelebrityRecognition

$result = $client->getCelebrityRecognition([/* ... */]);
$promise = $client->getCelebrityRecognitionAsync([/* ... */]);

Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by StartCelebrityRecognition.

Celebrity recognition in a video is an asynchronous operation. Analysis is started by a call to StartCelebrityRecognition which returns a job identifier (JobId).

When the celebrity recognition operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartCelebrityRecognition. To get the results of the celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetCelebrityDetection and pass the job identifier (JobId) from the initial call to StartCelebrityDetection.

For more information, see Working With Stored Videos in the Amazon Rekognition Developer Guide.

GetCelebrityRecognition returns detected celebrities and the time(s) they are detected in an array (Celebrities) of CelebrityRecognition objects. Each CelebrityRecognition contains information about the celebrity in a CelebrityDetail object and the time, Timestamp, the celebrity was detected. This CelebrityDetail object stores information about the detected celebrity's face attributes, a face bounding box, known gender, the celebrity's name, and a confidence estimate.

GetCelebrityRecognition only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The BoundingBox field only applies to the detected face instance. The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.

By default, the Celebrities array is sorted by time (milliseconds from the start of the video). You can also sort the array by celebrity by specifying the value ID in the SortBy input parameter.

The CelebrityDetail object includes the celebrity identifer and additional information urls. If you don't store the additional information urls, you can get them later by calling GetCelebrityInfo with the celebrity identifer.

No information is returned for faces not recognized as celebrities.

Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetCelebrityDetection and populate the NextToken request parameter with the token value returned from the previous call to GetCelebrityRecognition.

Parameter Syntax

$result = $client->getCelebrityRecognition([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'ID|TIMESTAMP',
]);

Parameter Details

Members

JobId

Required: Yes
Type: string

Job identifier for the required celebrity recognition analysis. You can get the job identifer from a call to StartCelebrityRecognition.

MaxResults

Type: int

Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.

NextToken

Type: string

If the previous response was incomplete (because there is more recognized celebrities to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of celebrities.

SortBy

Type: string

Sort to use for celebrities returned in Celebrities field. Specify ID to sort by the celebrity identifier, specify TIMESTAMP to sort by the time the celebrity was recognized.

Result Syntax

[
    'Celebrities' => [
        [
            'Celebrity' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Face' => [
                    'AgeRange' => [
                        'High' => <integer>,
                        'Low' => <integer>,
                    ],
                    'Beard' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'BoundingBox' => [
                        'Height' => <float>,
                        'Left' => <float>,
                        'Top' => <float>,
                        'Width' => <float>,
                    ],
                    'Confidence' => <float>,
                    'Emotions' => [
                        [
                            'Confidence' => <float>,
                            'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                        ],
                        // ...
                    ],
                    'EyeDirection' => [
                        'Confidence' => <float>,
                        'Pitch' => <float>,
                        'Yaw' => <float>,
                    ],
                    'Eyeglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'EyesOpen' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'FaceOccluded' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Gender' => [
                        'Confidence' => <float>,
                        'Value' => 'Male|Female',
                    ],
                    'Landmarks' => [
                        [
                            'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                            'X' => <float>,
                            'Y' => <float>,
                        ],
                        // ...
                    ],
                    'MouthOpen' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Mustache' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Pose' => [
                        'Pitch' => <float>,
                        'Roll' => <float>,
                        'Yaw' => <float>,
                    ],
                    'Quality' => [
                        'Brightness' => <float>,
                        'Sharpness' => <float>,
                    ],
                    'Smile' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Sunglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                ],
                'Id' => '<string>',
                'KnownGender' => [
                    'Type' => 'Male|Female|Nonbinary|Unlisted',
                ],
                'Name' => '<string>',
                'Urls' => ['<string>', ...],
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

Celebrities

Type: Array of CelebrityRecognition structures

Array of celebrities recognized in the video.

JobId

Type: string

Job identifier for the celebrity recognition operation for which you want to obtain results. The job identifer is returned by an initial call to StartCelebrityRecognition.

JobStatus

Type: string

The current status of the celebrity recognition job.

JobTag

Type: string

A job identifier specified in the call to StartCelebrityRecognition and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of celebrities.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

Video file stored in an Amazon S3 bucket. Amazon Rekognition video start operations such as StartLabelDetection use Video to specify a video for analysis. The supported file formats are .mp4, .mov and .avi.

VideoMetadata

Type: VideoMetadata structure

Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition Video operation.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetContentModeration

$result = $client->getContentModeration([/* ... */]);
$promise = $client->getContentModerationAsync([/* ... */]);

Gets the inappropriate, unwanted, or offensive content analysis results for a Amazon Rekognition Video analysis started by StartContentModeration. For a list of moderation labels in Amazon Rekognition, see Using the image and video moderation APIs.

Amazon Rekognition Video inappropriate or offensive content detection in a stored video is an asynchronous operation. You start analysis by calling StartContentModeration which returns a job identifier (JobId). When analysis finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartContentModeration. To get the results of the content analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetContentModeration and pass the job identifier (JobId) from the initial call to StartContentModeration.

For more information, see Working with Stored Videos in the Amazon Rekognition Devlopers Guide.

GetContentModeration returns detected inappropriate, unwanted, or offensive content moderation labels, and the time they are detected, in an array, ModerationLabels, of ContentModerationDetection objects.

By default, the moderated labels are returned sorted by time, in milliseconds from the start of the video. You can also sort them by moderated label by specifying NAME for the SortBy input parameter.

Since video analysis can return a large number of results, use the MaxResults parameter to limit the number of labels returned in a single call to GetContentModeration. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetContentModeration and populate the NextToken request parameter with the value of NextToken returned from the previous call to GetContentModeration.

For more information, see moderating content in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->getContentModeration([
    'AggregateBy' => 'TIMESTAMPS|SEGMENTS',
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'NAME|TIMESTAMP',
]);

Parameter Details

Members

AggregateBy

Type: string

Defines how to aggregate results of the StartContentModeration request. Default aggregation option is TIMESTAMPS. SEGMENTS mode aggregates moderation labels over time.

JobId

Required: Yes
Type: string

The identifier for the inappropriate, unwanted, or offensive content moderation job. Use JobId to identify the job in a subsequent call to GetContentModeration.

MaxResults

Type: int

NextToken

Type: string

If the previous response was incomplete (because there is more data to retrieve), Amazon Rekognition returns a pagination token in the response. You can use this pagination token to retrieve the next set of content moderation labels.

SortBy

Type: string

Sort to use for elements in the ModerationLabelDetections array. Use TIMESTAMP to sort array elements by the time labels are detected. Use NAME to alphabetically group elements for a label together. Within each label group, the array element are sorted by detection confidence. The default sort is by TIMESTAMP.

Result Syntax

[
    'GetRequestMetadata' => [
        'AggregateBy' => 'TIMESTAMPS|SEGMENTS',
        'SortBy' => 'NAME|TIMESTAMP',
    ],
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'ModerationLabels' => [
        [
            'DurationMillis' => <integer>,
            'EndTimestampMillis' => <integer>,
            'ModerationLabel' => [
                'Confidence' => <float>,
                'Name' => '<string>',
                'ParentName' => '<string>',
            ],
            'StartTimestampMillis' => <integer>,
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'ModerationModelVersion' => '<string>',
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

GetRequestMetadata

Type: GetContentModerationRequestMetadata structure

Information about the paramters used when getting a response. Includes information on aggregation and sorting methods.

JobId

Type: string

Job identifier for the content moderation operation for which you want to obtain results. The job identifer is returned by an initial call to StartContentModeration.

JobStatus

Type: string

The current status of the content moderation analysis job.

JobTag

Type: string

A job identifier specified in the call to StartContentModeration and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

ModerationLabels

Type: Array of ContentModerationDetection structures

The detected inappropriate, unwanted, or offensive content moderation labels and the time(s) they were detected.

ModerationModelVersion

Type: string

Version number of the moderation detection model that was used to detect inappropriate, unwanted, or offensive content.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of content moderation labels.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

VideoMetadata

Type: VideoMetadata structure

Information about a video that Amazon Rekognition analyzed. Videometadata is returned in every page of paginated responses from GetContentModeration.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetFaceDetection

$result = $client->getFaceDetection([/* ... */]);
$promise = $client->getFaceDetectionAsync([/* ... */]);

Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection.

Face detection with Amazon Rekognition Video is an asynchronous operation. You start face detection by calling StartFaceDetection which returns a job identifier (JobId). When the face detection operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceDetection. To get the results of the face detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceDetection and pass the job identifier (JobId) from the initial call to StartFaceDetection.

GetFaceDetection returns an array of detected faces (Faces) sorted by the time the faces were detected.

Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetFaceDetection and populate the NextToken request parameter with the token value returned from the previous call to GetFaceDetection.

Note that for the GetFaceDetection operation, the returned values for FaceOccluded and EyeDirection will always be "null".

Parameter Syntax

$result = $client->getFaceDetection([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

JobId

Required: Yes
Type: string

Unique identifier for the face detection job. The JobId is returned from StartFaceDetection.

MaxResults

Type: int

NextToken

Type: string

If the previous response was incomplete (because there are more faces to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of faces.

Result Syntax

[
    'Faces' => [
        [
            'Face' => [
                'AgeRange' => [
                    'High' => <integer>,
                    'Low' => <integer>,
                ],
                'Beard' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Emotions' => [
                    [
                        'Confidence' => <float>,
                        'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                    ],
                    // ...
                ],
                'EyeDirection' => [
                    'Confidence' => <float>,
                    'Pitch' => <float>,
                    'Yaw' => <float>,
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'FaceOccluded' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Gender' => [
                    'Confidence' => <float>,
                    'Value' => 'Male|Female',
                ],
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
                'MouthOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Mustache' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Pose' => [
                    'Pitch' => <float>,
                    'Roll' => <float>,
                    'Yaw' => <float>,
                ],
                'Quality' => [
                    'Brightness' => <float>,
                    'Sharpness' => <float>,
                ],
                'Smile' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Sunglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

Faces

Type: Array of FaceDetection structures

An array of faces detected in the video. Each element contains a detected face's details and the time, in milliseconds from the start of the video, the face was detected.

JobId

Type: string

Job identifier for the face detection operation for which you want to obtain results. The job identifer is returned by an initial call to StartFaceDetection.

JobStatus

Type: string

The current status of the face detection job.

JobTag

Type: string

A job identifier specified in the call to StartFaceDetection and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

NextToken

Type: string

If the response is truncated, Amazon Rekognition returns this token that you can use in the subsequent request to retrieve the next set of faces.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

VideoMetadata

Type: VideoMetadata structure

Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition video operation.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetFaceLivenessSessionResults

$result = $client->getFaceLivenessSessionResults([/* ... */]);
$promise = $client->getFaceLivenessSessionResultsAsync([/* ... */]);

Retrieves the results of a specific Face Liveness session. It requires the sessionId as input, which was created using CreateFaceLivenessSession. Returns the corresponding Face Liveness confidence score, a reference image that includes a face bounding box, and audit images that also contain face bounding boxes. The Face Liveness confidence score ranges from 0 to 100.

The number of audit images returned by GetFaceLivenessSessionResults is defined by the AuditImagesLimit paramater when calling CreateFaceLivenessSession. Reference images are always returned when possible.

Parameter Syntax

$result = $client->getFaceLivenessSessionResults([
    'SessionId' => '<string>', // REQUIRED
]);

Parameter Details

Members

SessionId

Required: Yes
Type: string

A unique 128-bit UUID. This is used to uniquely identify the session and also acts as an idempotency token for all operations associated with the session.

Result Syntax

[
    'AuditImages' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
            'S3Object' => [
                'Bucket' => '<string>',
                'Name' => '<string>',
                'Version' => '<string>',
            ],
        ],
        // ...
    ],
    'Confidence' => <float>,
    'ReferenceImage' => [
        'BoundingBox' => [
            'Height' => <float>,
            'Left' => <float>,
            'Top' => <float>,
            'Width' => <float>,
        ],
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'SessionId' => '<string>',
    'Status' => 'CREATED|IN_PROGRESS|SUCCEEDED|FAILED|EXPIRED',
]

Result Details

Members

AuditImages

Type: Array of AuditImage structures

A set of images from the Face Liveness video that can be used for audit purposes. It includes a bounding box of the face and the Base64-encoded bytes that return an image. If the CreateFaceLivenessSession request included an OutputConfig argument, the image will be uploaded to an S3Object specified in the output configuration. If no Amazon S3 bucket is defined, raw bytes are sent instead.

Confidence

Type: float

Probabalistic confidence score for if the person in the given video was live, represented as a float value between 0 to 100.

ReferenceImage

Type: AuditImage structure

A high-quality image from the Face Liveness video that can be used for face comparison or search. It includes a bounding box of the face and the Base64-encoded bytes that return an image. If the CreateFaceLivenessSession request included an OutputConfig argument, the image will be uploaded to an S3Object specified in the output configuration. In case the reference image is not returned, it's recommended to retry the Liveness check.

SessionId

Required: Yes
Type: string

The sessionId for which this request was called.

Status

Required: Yes
Type: string

Represents a status corresponding to the state of the session. Possible statuses are: CREATED, IN_PROGRESS, SUCCEEDED, FAILED, EXPIRED.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
SessionNotFoundException:
Occurs when a given sessionId is not found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

GetFaceSearch

$result = $client->getFaceSearch([/* ... */]);
$promise = $client->getFaceSearchAsync([/* ... */]);

Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch. The search returns faces in a collection that match the faces of persons detected in a video. It also includes the time(s) that faces are matched in the video.

Face search in a video is an asynchronous operation. You start face search by calling to StartFaceSearch which returns a job identifier (JobId). When the search operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceSearch. To get the search results, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (JobId) from the initial call to StartFaceSearch.

For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.

The search results are retured in an array, Persons, of PersonMatch objects. EachPersonMatch element contains details about the matching faces in the input collection, person information (facial attributes, bounding boxes, and person identifer) for the matched person, and the time the person was matched in the video.

GetFaceSearch only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.

By default, the Persons array is sorted by the time, in milliseconds from the start of the video, persons are matched. You can also sort by persons by specifying INDEX for the SORTBY input parameter.

Parameter Syntax

$result = $client->getFaceSearch([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'INDEX|TIMESTAMP',
]);

Parameter Details

Members

JobId

Required: Yes
Type: string

The job identifer for the search request. You get the job identifier from an initial call to StartFaceSearch.

MaxResults

Type: int

NextToken

Type: string

If the previous response was incomplete (because there is more search results to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of search results.

SortBy

Type: string

Sort to use for grouping faces in the response. Use TIMESTAMP to group faces by the time that they are recognized. Use INDEX to sort by recognized faces.

Result Syntax

[
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'NextToken' => '<string>',
    'Persons' => [
        [
            'FaceMatches' => [
                [
                    'Face' => [
                        'BoundingBox' => [
                            'Height' => <float>,
                            'Left' => <float>,
                            'Top' => <float>,
                            'Width' => <float>,
                        ],
                        'Confidence' => <float>,
                        'ExternalImageId' => '<string>',
                        'FaceId' => '<string>',
                        'ImageId' => '<string>',
                        'IndexFacesModelVersion' => '<string>',
                        'UserId' => '<string>',
                    ],
                    'Similarity' => <float>,
                ],
                // ...
            ],
            'Person' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Face' => [
                    'AgeRange' => [
                        'High' => <integer>,
                        'Low' => <integer>,
                    ],
                    'Beard' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'BoundingBox' => [
                        'Height' => <float>,
                        'Left' => <float>,
                        'Top' => <float>,
                        'Width' => <float>,
                    ],
                    'Confidence' => <float>,
                    'Emotions' => [
                        [
                            'Confidence' => <float>,
                            'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                        ],
                        // ...
                    ],
                    'EyeDirection' => [
                        'Confidence' => <float>,
                        'Pitch' => <float>,
                        'Yaw' => <float>,
                    ],
                    'Eyeglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'EyesOpen' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'FaceOccluded' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Gender' => [
                        'Confidence' => <float>,
                        'Value' => 'Male|Female',
                    ],
                    'Landmarks' => [
                        [
                            'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                            'X' => <float>,
                            'Y' => <float>,
                        ],
                        // ...
                    ],
                    'MouthOpen' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Mustache' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Pose' => [
                        'Pitch' => <float>,
                        'Roll' => <float>,
                        'Yaw' => <float>,
                    ],
                    'Quality' => [
                        'Brightness' => <float>,
                        'Sharpness' => <float>,
                    ],
                    'Smile' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Sunglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                ],
                'Index' => <integer>,
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobId

Type: string

Job identifier for the face search operation for which you want to obtain results. The job identifer is returned by an initial call to StartFaceSearch.

JobStatus

Type: string

The current status of the face search job.

JobTag

Type: string

A job identifier specified in the call to StartFaceSearch and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of search results.

Persons

Type: Array of PersonMatch structures

An array of persons, PersonMatch, in the video whose face(s) match the face(s) in an Amazon Rekognition collection. It also includes time information for when persons are matched in the video. You specify the input collection in an initial call to StartFaceSearch. Each Persons element includes a time the person was matched, face match details (FaceMatches) for matching faces in the collection, and person information (Person) for the matched person.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

VideoMetadata

Type: VideoMetadata structure

Information about a video that Amazon Rekognition analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition Video operation.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetLabelDetection

$result = $client->getLabelDetection([/* ... */]);
$promise = $client->getLabelDetectionAsync([/* ... */]);

Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection.

The label detection operation is started by a call to StartLabelDetection which returns a job identifier (JobId). When the label detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartlabelDetection.

To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (JobId) from the initial call to StartLabelDetection.

GetLabelDetection returns an array of detected labels (Labels) sorted by the time the labels were detected. You can also sort by the label name by specifying NAME for the SortBy input parameter. If there is no NAME specified, the default sort is by timestamp.

You can select how results are aggregated by using the AggregateBy input parameter. The default aggregation method is TIMESTAMPS. You can also aggregate by SEGMENTS, which aggregates all instances of labels detected in a given segment.

The returned Labels array may include the following attributes:

Name - The name of the detected label.
Confidence - The level of confidence in the label assigned to a detected object.
Parents - The ancestor labels for a detected label. GetLabelDetection returns a hierarchical taxonomy of detected labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.
Aliases - Possible Aliases for the label.
Categories - The label categories that the detected label belongs to.
BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label on the input image. It also includes the confidence for the accuracy of the detected bounding box.
Timestamp - Time, in milliseconds from the start of the video, that the label was detected. For aggregation by SEGMENTS, the StartTimestampMillis, EndTimestampMillis, and DurationMillis structures are what define a segment. Although the “Timestamp” structure is still returned with each label, its value is set to be the same as StartTimestampMillis.

Timestamp and Bounding box information are returned for detected Instances, only if aggregation is done by TIMESTAMPS. If aggregating by SEGMENTS, information about detected instances isn’t returned.

The version of the label model used for the detection is also returned.

Note DominantColors isn't returned for Instances, although it is shown as part of the response in the sample seen below.

Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetlabelDetection and populate the NextToken request parameter with the token value returned from the previous call to GetLabelDetection.

Parameter Syntax

$result = $client->getLabelDetection([
    'AggregateBy' => 'TIMESTAMPS|SEGMENTS',
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'NAME|TIMESTAMP',
]);

Parameter Details

Members

AggregateBy

Type: string

Defines how to aggregate the returned results. Results can be aggregated by timestamps or segments.

JobId

Required: Yes
Type: string

Job identifier for the label detection operation for which you want results returned. You get the job identifer from an initial call to StartlabelDetection.

MaxResults

Type: int

NextToken

Type: string

If the previous response was incomplete (because there are more labels to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of labels.

SortBy

Type: string

Sort to use for elements in the Labels array. Use TIMESTAMP to sort array elements by the time labels are detected. Use NAME to alphabetically group elements for a label together. Within each label group, the array element are sorted by detection confidence. The default sort is by TIMESTAMP.

Result Syntax

[
    'GetRequestMetadata' => [
        'AggregateBy' => 'TIMESTAMPS|SEGMENTS',
        'SortBy' => 'NAME|TIMESTAMP',
    ],
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'LabelModelVersion' => '<string>',
    'Labels' => [
        [
            'DurationMillis' => <integer>,
            'EndTimestampMillis' => <integer>,
            'Label' => [
                'Aliases' => [
                    [
                        'Name' => '<string>',
                    ],
                    // ...
                ],
                'Categories' => [
                    [
                        'Name' => '<string>',
                    ],
                    // ...
                ],
                'Confidence' => <float>,
                'Instances' => [
                    [
                        'BoundingBox' => [
                            'Height' => <float>,
                            'Left' => <float>,
                            'Top' => <float>,
                            'Width' => <float>,
                        ],
                        'Confidence' => <float>,
                        'DominantColors' => [
                            [
                                'Blue' => <integer>,
                                'CSSColor' => '<string>',
                                'Green' => <integer>,
                                'HexCode' => '<string>',
                                'PixelPercent' => <float>,
                                'Red' => <integer>,
                                'SimplifiedColor' => '<string>',
                            ],
                            // ...
                        ],
                    ],
                    // ...
                ],
                'Name' => '<string>',
                'Parents' => [
                    [
                        'Name' => '<string>',
                    ],
                    // ...
                ],
            ],
            'StartTimestampMillis' => <integer>,
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

GetRequestMetadata

Type: GetLabelDetectionRequestMetadata structure

Information about the paramters used when getting a response. Includes information on aggregation and sorting methods.

JobId

Type: string

Job identifier for the label detection operation for which you want to obtain results. The job identifer is returned by an initial call to StartLabelDetection.

JobStatus

Type: string

The current status of the label detection job.

JobTag

Type: string

A job identifier specified in the call to StartLabelDetection and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

LabelModelVersion

Type: string

Version number of the label detection model that was used to detect labels.

Labels

Type: Array of LabelDetection structures

An array of labels detected in the video. Each element contains the detected label and the time, in milliseconds from the start of the video, that the label was detected.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of labels.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

VideoMetadata

Type: VideoMetadata structure

Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition video operation.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetPersonTracking

$result = $client->getPersonTracking([/* ... */]);
$promise = $client->getPersonTrackingAsync([/* ... */]);

Gets the path tracking results of a Amazon Rekognition Video analysis started by StartPersonTracking.

The person path tracking operation is started by a call to StartPersonTracking which returns a job identifier (JobId). When the operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartPersonTracking.

To get the results of the person path tracking operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (JobId) from the initial call to StartPersonTracking.

GetPersonTracking returns an array, Persons, of tracked persons and the time(s) their paths were tracked in the video.

GetPersonTracking only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The other facial attributes listed in the Face object of the following response syntax are not returned.

For more information, see FaceDetail in the Amazon Rekognition Developer Guide.

By default, the array is sorted by the time(s) a person's path is tracked in the video. You can sort by tracked persons by specifying INDEX for the SortBy input parameter.

Use the MaxResults parameter to limit the number of items returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetPersonTracking and populate the NextToken request parameter with the token value returned from the previous call to GetPersonTracking.

Parameter Syntax

$result = $client->getPersonTracking([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'INDEX|TIMESTAMP',
]);

Parameter Details

Members

JobId

Required: Yes
Type: string

The identifier for a job that tracks persons in a video. You get the JobId from a call to StartPersonTracking.

MaxResults

Type: int

NextToken

Type: string

If the previous response was incomplete (because there are more persons to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of persons.

SortBy

Type: string

Sort to use for elements in the Persons array. Use TIMESTAMP to sort array elements by the time persons are detected. Use INDEX to sort by the tracked persons. If you sort by INDEX, the array elements for each person are sorted by detection confidence. The default sort is by TIMESTAMP.

Result Syntax

[
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'NextToken' => '<string>',
    'Persons' => [
        [
            'Person' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Face' => [
                    'AgeRange' => [
                        'High' => <integer>,
                        'Low' => <integer>,
                    ],
                    'Beard' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'BoundingBox' => [
                        'Height' => <float>,
                        'Left' => <float>,
                        'Top' => <float>,
                        'Width' => <float>,
                    ],
                    'Confidence' => <float>,
                    'Emotions' => [
                        [
                            'Confidence' => <float>,
                            'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                        ],
                        // ...
                    ],
                    'EyeDirection' => [
                        'Confidence' => <float>,
                        'Pitch' => <float>,
                        'Yaw' => <float>,
                    ],
                    'Eyeglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'EyesOpen' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'FaceOccluded' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Gender' => [
                        'Confidence' => <float>,
                        'Value' => 'Male|Female',
                    ],
                    'Landmarks' => [
                        [
                            'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                            'X' => <float>,
                            'Y' => <float>,
                        ],
                        // ...
                    ],
                    'MouthOpen' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Mustache' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Pose' => [
                        'Pitch' => <float>,
                        'Roll' => <float>,
                        'Yaw' => <float>,
                    ],
                    'Quality' => [
                        'Brightness' => <float>,
                        'Sharpness' => <float>,
                    ],
                    'Smile' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'Sunglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                ],
                'Index' => <integer>,
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobId

Type: string

Job identifier for the person tracking operation for which you want to obtain results. The job identifer is returned by an initial call to StartPersonTracking.

JobStatus

Type: string

The current status of the person tracking job.

JobTag

Type: string

A job identifier specified in the call to StartCelebrityRecognition and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of persons.

Persons

Type: Array of PersonDetection structures

An array of the persons detected in the video and the time(s) their path was tracked throughout the video. An array element will exist for each time a person's path is tracked.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

VideoMetadata

Type: VideoMetadata structure

Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition Video operation.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetSegmentDetection

$result = $client->getSegmentDetection([/* ... */]);
$promise = $client->getSegmentDetectionAsync([/* ... */]);

Gets the segment detection results of a Amazon Rekognition Video analysis started by StartSegmentDetection.

Segment detection with Amazon Rekognition Video is an asynchronous operation. You start segment detection by calling StartSegmentDetection which returns a job identifier (JobId). When the segment detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartSegmentDetection. To get the results of the segment detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so, call GetSegmentDetection and pass the job identifier (JobId) from the initial call of StartSegmentDetection.

GetSegmentDetection returns detected segments in an array (Segments) of SegmentDetection objects. Segments is sorted by the segment types specified in the SegmentTypes input parameter of StartSegmentDetection. Each element of the array includes the detected segment, the precentage confidence in the acuracy of the detected segment, the type of the segment, and the frame in which the segment was detected.

Use SelectedSegmentTypes to find out the type of segment detection requested in the call to StartSegmentDetection.

Use the MaxResults parameter to limit the number of segment detections returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetSegmentDetection and populate the NextToken request parameter with the token value returned from the previous call to GetSegmentDetection.

For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->getSegmentDetection([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

JobId

Required: Yes
Type: string

Job identifier for the text detection operation for which you want results returned. You get the job identifer from an initial call to StartSegmentDetection.

MaxResults

Type: int

Maximum number of results to return per paginated call. The largest value you can specify is 1000.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of text.

Result Syntax

[
    'AudioMetadata' => [
        [
            'Codec' => '<string>',
            'DurationMillis' => <integer>,
            'NumberOfChannels' => <integer>,
            'SampleRate' => <integer>,
        ],
        // ...
    ],
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'NextToken' => '<string>',
    'Segments' => [
        [
            'DurationFrames' => <integer>,
            'DurationMillis' => <integer>,
            'DurationSMPTE' => '<string>',
            'EndFrameNumber' => <integer>,
            'EndTimecodeSMPTE' => '<string>',
            'EndTimestampMillis' => <integer>,
            'ShotSegment' => [
                'Confidence' => <float>,
                'Index' => <integer>,
            ],
            'StartFrameNumber' => <integer>,
            'StartTimecodeSMPTE' => '<string>',
            'StartTimestampMillis' => <integer>,
            'TechnicalCueSegment' => [
                'Confidence' => <float>,
                'Type' => 'ColorBars|EndCredits|BlackFrames|OpeningCredits|StudioLogo|Slate|Content',
            ],
            'Type' => 'TECHNICAL_CUE|SHOT',
        ],
        // ...
    ],
    'SelectedSegmentTypes' => [
        [
            'ModelVersion' => '<string>',
            'Type' => 'TECHNICAL_CUE|SHOT',
        ],
        // ...
    ],
    'StatusMessage' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        [
            'Codec' => '<string>',
            'ColorRange' => 'FULL|LIMITED',
            'DurationMillis' => <integer>,
            'Format' => '<string>',
            'FrameHeight' => <integer>,
            'FrameRate' => <float>,
            'FrameWidth' => <integer>,
        ],
        // ...
    ],
]

Result Details

Members

AudioMetadata

Type: Array of AudioMetadata structures

An array of objects. There can be multiple audio streams. Each AudioMetadata object contains metadata for a single audio stream. Audio information in an AudioMetadata objects includes the audio codec, the number of audio channels, the duration of the audio stream, and the sample rate. Audio metadata is returned in each page of information returned by GetSegmentDetection.

JobId

Type: string

Job identifier for the segment detection operation for which you want to obtain results. The job identifer is returned by an initial call to StartSegmentDetection.

JobStatus

Type: string

Current status of the segment detection job.

JobTag

Type: string

A job identifier specified in the call to StartSegmentDetection and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

NextToken

Type: string

Segments

Type: Array of SegmentDetection structures

An array of segments detected in a video. The array is sorted by the segment types (TECHNICAL_CUE or SHOT) specified in the SegmentTypes input parameter of StartSegmentDetection. Within each segment type the array is sorted by timestamp values.

SelectedSegmentTypes

Type: Array of SegmentTypeInfo structures

An array containing the segment types requested in the call to StartSegmentDetection.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

Video

Type: Video structure

VideoMetadata

Type: Array of VideoMetadata structures

Currently, Amazon Rekognition Video returns a single object in the VideoMetadata array. The object contains information about the video stream in the input file that Amazon Rekognition Video chose to analyze. The VideoMetadata object includes the video codec, video format and other information. Video metadata is returned in each page of information returned by GetSegmentDetection.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

GetTextDetection

$result = $client->getTextDetection([/* ... */]);
$promise = $client->getTextDetectionAsync([/* ... */]);

Gets the text detection results of a Amazon Rekognition Video analysis started by StartTextDetection.

Text detection with Amazon Rekognition Video is an asynchronous operation. You start text detection by calling StartTextDetection which returns a job identifier (JobId) When the text detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartTextDetection. To get the results of the text detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so, call GetTextDetection and pass the job identifier (JobId) from the initial call of StartLabelDetection.

GetTextDetection returns an array of detected text (TextDetections) sorted by the time the text was detected, up to 100 words per frame of video.

Each element of the array includes the detected text, the precentage confidence in the acuracy of the detected text, the time the text was detected, bounding box information for where the text was located, and unique identifiers for words and their lines.

Use MaxResults parameter to limit the number of text detections returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetTextDetection and populate the NextToken request parameter with the token value returned from the previous call to GetTextDetection.

Parameter Syntax

$result = $client->getTextDetection([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

JobId

Required: Yes
Type: string

Job identifier for the text detection operation for which you want results returned. You get the job identifer from an initial call to StartTextDetection.

MaxResults

Type: int

Maximum number of results to return per paginated call. The largest value you can specify is 1000.

NextToken

Type: string

Result Syntax

[
    'JobId' => '<string>',
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'JobTag' => '<string>',
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'TextDetections' => [
        [
            'TextDetection' => [
                'Confidence' => <float>,
                'DetectedText' => '<string>',
                'Geometry' => [
                    'BoundingBox' => [
                        'Height' => <float>,
                        'Left' => <float>,
                        'Top' => <float>,
                        'Width' => <float>,
                    ],
                    'Polygon' => [
                        [
                            'X' => <float>,
                            'Y' => <float>,
                        ],
                        // ...
                    ],
                ],
                'Id' => <integer>,
                'ParentId' => <integer>,
                'Type' => 'LINE|WORD',
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'TextModelVersion' => '<string>',
    'Video' => [
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobId

Type: string

Job identifier for the text detection operation for which you want to obtain results. The job identifer is returned by an initial call to StartTextDetection.

JobStatus

Type: string

Current status of the text detection job.

JobTag

Type: string

A job identifier specified in the call to StartTextDetection and returned in the job completion notification sent to your Amazon Simple Notification Service topic.

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of text.

StatusMessage

Type: string

If the job fails, StatusMessage provides a descriptive error message.

TextDetections

Type: Array of TextDetectionResult structures

An array of text detected in the video. Each element contains the detected text, the time in milliseconds from the start of the video that the text was detected, and where it was detected on the screen.

TextModelVersion

Type: string

Version number of the text detection model that was used to detect text.

Video

Type: Video structure

VideoMetadata

Type: VideoMetadata structure

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

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

IndexFaces

$result = $client->indexFaces([/* ... */]);
$promise = $client->indexFacesAsync([/* ... */]);

Detects faces in the input image and adds them to the specified collection.

Amazon Rekognition doesn't save the actual faces that are detected. Instead, the underlying detection algorithm first detects the faces in the input image. For each face, the algorithm extracts facial features into a feature vector, and stores it in the backend database. Amazon Rekognition uses feature vectors when it performs face match and search operations using the SearchFaces and SearchFacesByImage operations.

For more information, see Adding faces to a collection in the Amazon Rekognition Developer Guide.

To get the number of faces in a collection, call DescribeCollection.

If you're using version 1.0 of the face detection model, IndexFaces indexes the 15 largest faces in the input image. Later versions of the face detection model index the 100 largest faces in the input image.

If you're using version 4 or later of the face model, image orientation information is not returned in the OrientationCorrection field.

To determine which version of the model you're using, call DescribeCollection and supply the collection ID. You can also get the model version from the value of FaceModelVersion in the response from IndexFaces

For more information, see Model Versioning in the Amazon Rekognition Developer Guide.

If you provide the optional ExternalImageId for the input image you provided, Amazon Rekognition associates this ID with all faces that it detects. When you call the ListFaces operation, the response returns the external ID. You can use this external image ID to create a client-side index to associate the faces with each image. You can then use the index to find all faces in an image.

You can specify the maximum number of faces to index with the MaxFaces input parameter. This is useful when you want to index the largest faces in an image and don't want to index smaller faces, such as those belonging to people standing in the background.

The QualityFilter input parameter allows you to filter out detected faces that don’t meet a required quality bar. The quality bar is based on a variety of common use cases. By default, IndexFaces chooses the quality bar that's used to filter faces. You can also explicitly choose the quality bar. Use QualityFilter, to set the quality bar by specifying LOW, MEDIUM, or HIGH. If you do not want to filter detected faces, specify NONE.

To use quality filtering, you need a collection associated with version 3 of the face model or higher. To get the version of the face model associated with a collection, call DescribeCollection.

Information about faces detected in an image, but not indexed, is returned in an array of UnindexedFace objects, UnindexedFaces. Faces aren't indexed for reasons such as:

The number of faces detected exceeds the value of the MaxFaces request parameter.
The face is too small compared to the image dimensions.
The face is too blurry.
The image is too dark.
The face has an extreme pose.
The face doesn’t have enough detail to be suitable for face search.

In response, the IndexFaces operation returns an array of metadata for all detected faces, FaceRecords. This includes:

The bounding box, BoundingBox, of the detected face.
A confidence value, Confidence, which indicates the confidence that the bounding box contains a face.
A face ID, FaceId, assigned by the service for each face that's detected and stored.
An image ID, ImageId, assigned by the service for the input image.

If you request ALL or specific facial attributes (e.g., FACE_OCCLUDED) by using the detectionAttributes parameter, Amazon Rekognition returns detailed facial attributes, such as facial landmarks (for example, location of eye and mouth), facial occlusion, and other facial attributes.

If you provide the same image, specify the same collection, and use the same external ID in the IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata.

The input image is passed either as base64-encoded image bytes, or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't supported. The image must be formatted as a PNG or JPEG file.

This operation requires permissions to perform the rekognition:IndexFaces action.

Parameter Syntax

$result = $client->indexFaces([
    'CollectionId' => '<string>', // REQUIRED
    'DetectionAttributes' => ['<string>', ...],
    'ExternalImageId' => '<string>',
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'MaxFaces' => <integer>,
    'QualityFilter' => 'NONE|AUTO|LOW|MEDIUM|HIGH',
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

The ID of an existing collection to which you want to add the faces that are detected in the input images.

DetectionAttributes

Type: Array of strings

An array of facial attributes you want to be returned. A DEFAULT subset of facial attributes - BoundingBox, Confidence, Pose, Quality, and Landmarks - will always be returned. You can request for specific facial attributes (in addition to the default list) - by using ["DEFAULT", "FACE_OCCLUDED"] or just ["FACE_OCCLUDED"]. You can request for all facial attributes by using ["ALL"]. Requesting more attributes may increase response time.

If you provide both, ["ALL", "DEFAULT"], the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).

ExternalImageId

Type: string

The ID you want to assign to all the faces detected in the image.

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes isn't supported.

MaxFaces

Type: int

The maximum number of faces to index. The value of MaxFaces must be greater than or equal to 1. IndexFaces returns no more than 100 detected faces in an image, even if you specify a larger value for MaxFaces.

If IndexFaces detects more faces than the value of MaxFaces, the faces with the lowest quality are filtered out first. If there are still more faces than the value of MaxFaces, the faces with the smallest bounding boxes are filtered out (up to the number that's needed to satisfy the value of MaxFaces). Information about the unindexed faces is available in the UnindexedFaces array.

The faces that are returned by IndexFaces are sorted by the largest face bounding box size to the smallest size, in descending order.

MaxFaces can be used with a collection associated with any version of the face model.

QualityFilter

Type: string

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't indexed. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The default value is AUTO. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE, no filtering is performed.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

Result Syntax

[
    'FaceModelVersion' => '<string>',
    'FaceRecords' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'ExternalImageId' => '<string>',
                'FaceId' => '<string>',
                'ImageId' => '<string>',
                'IndexFacesModelVersion' => '<string>',
                'UserId' => '<string>',
            ],
            'FaceDetail' => [
                'AgeRange' => [
                    'High' => <integer>,
                    'Low' => <integer>,
                ],
                'Beard' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Emotions' => [
                    [
                        'Confidence' => <float>,
                        'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                    ],
                    // ...
                ],
                'EyeDirection' => [
                    'Confidence' => <float>,
                    'Pitch' => <float>,
                    'Yaw' => <float>,
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'FaceOccluded' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Gender' => [
                    'Confidence' => <float>,
                    'Value' => 'Male|Female',
                ],
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
                'MouthOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Mustache' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Pose' => [
                    'Pitch' => <float>,
                    'Roll' => <float>,
                    'Yaw' => <float>,
                ],
                'Quality' => [
                    'Brightness' => <float>,
                    'Sharpness' => <float>,
                ],
                'Smile' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Sunglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
            ],
        ],
        // ...
    ],
    'OrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
    'UnindexedFaces' => [
        [
            'FaceDetail' => [
                'AgeRange' => [
                    'High' => <integer>,
                    'Low' => <integer>,
                ],
                'Beard' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Emotions' => [
                    [
                        'Confidence' => <float>,
                        'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                    ],
                    // ...
                ],
                'EyeDirection' => [
                    'Confidence' => <float>,
                    'Pitch' => <float>,
                    'Yaw' => <float>,
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'FaceOccluded' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Gender' => [
                    'Confidence' => <float>,
                    'Value' => 'Male|Female',
                ],
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
                'MouthOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Mustache' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Pose' => [
                    'Pitch' => <float>,
                    'Roll' => <float>,
                    'Yaw' => <float>,
                ],
                'Quality' => [
                    'Brightness' => <float>,
                    'Sharpness' => <float>,
                ],
                'Smile' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Sunglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
            ],
            'Reasons' => ['<string>', ...],
        ],
        // ...
    ],
]

Result Details

Members

FaceModelVersion

Type: string

The version number of the face detection model that's associated with the input collection (CollectionId).

FaceRecords

Type: Array of FaceRecord structures

An array of faces detected and added to the collection. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.

OrientationCorrection

Type: string

If your collection is associated with a face detection model that's later than version 3.0, the value of OrientationCorrection is always null and no orientation information is returned.

If your collection is associated with a face detection model that's version 3.0 or earlier, the following applies:

If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction - the bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata. The value of OrientationCorrection is null.
If the image doesn't contain orientation information in its Exif metadata, Amazon Rekognition returns an estimated orientation (ROTATE_0, ROTATE_90, ROTATE_180, ROTATE_270). Amazon Rekognition doesn’t perform image correction for images. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

Bounding box information is returned in the FaceRecords array. You can get the version of the face detection model by calling DescribeCollection.

UnindexedFaces

Type: Array of UnindexedFace structures

An array of faces that were detected in the image but weren't indexed. They weren't indexed because the quality filter identified them as low quality, or the MaxFaces request parameter filtered them out. To use the quality filter, you specify the QualityFilter request parameter.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidImageFormatException:
The provided image format is not supported.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.

Examples

Example 1: To add a face to a collection

This operation detects faces in an image and adds them to the specified Rekognition collection.

$result = $client->indexFaces([
    'CollectionId' => 'myphotos',
    'DetectionAttributes' => [
    ],
    'ExternalImageId' => 'myphotoid',
    'Image' => [
        'S3Object' => [
            'Bucket' => 'mybucket',
            'Name' => 'myphoto',
        ],
    ],
]);

Result syntax:

[
    'FaceRecords' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.33481481671333,
                    'Left' => 0.31888890266418,
                    'Top' => 0.49333333969116,
                    'Width' => 0.25,
                ],
                'Confidence' => 99.999122619629,
                'FaceId' => 'ff43d742-0c13-5d16-a3e8-03d3f58e980b',
                'ImageId' => '465f4e93-763e-51d0-b030-b9667a2d94b1',
            ],
            'FaceDetail' => [
                'BoundingBox' => [
                    'Height' => 0.33481481671333,
                    'Left' => 0.31888890266418,
                    'Top' => 0.49333333969116,
                    'Width' => 0.25,
                ],
                'Confidence' => 99.999122619629,
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft',
                        'X' => 0.39767646789551,
                        'Y' => 0.62483459711075,
                    ],
                    [
                        'Type' => 'eyeRight',
                        'X' => 0.48109364509583,
                        'Y' => 0.63171172142029,
                    ],
                    [
                        'Type' => 'noseLeft',
                        'X' => 0.41986238956451,
                        'Y' => 0.71119403839111,
                    ],
                    [
                        'Type' => 'mouthDown',
                        'X' => 0.40525302290916,
                        'Y' => 0.7497701048851,
                    ],
                    [
                        'Type' => 'mouthUp',
                        'X' => 0.47532489895821,
                        'Y' => 0.75585496425629,
                    ],
                ],
                'Pose' => [
                    'Pitch' => -9.7136459350586,
                    'Roll' => 4.7072811126709,
                    'Yaw' => -24.438663482666,
                ],
                'Quality' => [
                    'Brightness' => 29.233589172363,
                    'Sharpness' => 80,
                ],
            ],
        ],
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.32592591643333,
                    'Left' => 0.51444447040558,
                    'Top' => 0.15111111104488,
                    'Width' => 0.24444444477558,
                ],
                'Confidence' => 99.999504089355,
                'FaceId' => '8be04dba-4e58-520d-850e-9eae4af70eb2',
                'ImageId' => '465f4e93-763e-51d0-b030-b9667a2d94b1',
            ],
            'FaceDetail' => [
                'BoundingBox' => [
                    'Height' => 0.32592591643333,
                    'Left' => 0.51444447040558,
                    'Top' => 0.15111111104488,
                    'Width' => 0.24444444477558,
                ],
                'Confidence' => 99.999504089355,
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft',
                        'X' => 0.6006892323494,
                        'Y' => 0.29084220528603,
                    ],
                    [
                        'Type' => 'eyeRight',
                        'X' => 0.68081414699554,
                        'Y' => 0.29609042406082,
                    ],
                    [
                        'Type' => 'noseLeft',
                        'X' => 0.63953322172165,
                        'Y' => 0.35225957632065,
                    ],
                    [
                        'Type' => 'mouthDown',
                        'X' => 0.58920830488205,
                        'Y' => 0.38689887523651,
                    ],
                    [
                        'Type' => 'mouthUp',
                        'X' => 0.6745600104332,
                        'Y' => 0.39412575960159,
                    ],
                ],
                'Pose' => [
                    'Pitch' => -4.6831383705139,
                    'Roll' => 2.1029529571533,
                    'Yaw' => 6.716655254364,
                ],
                'Quality' => [
                    'Brightness' => 34.951698303223,
                    'Sharpness' => 160,
                ],
            ],
        ],
    ],
    'OrientationCorrection' => 'ROTATE_0',
]

ListCollections

$result = $client->listCollections([/* ... */]);
$promise = $client->listCollectionsAsync([/* ... */]);

Returns list of collection IDs in your account. If the result is truncated, the response also provides a NextToken that you can use in the subsequent request to fetch the next set of collection IDs.

For an example, see Listing collections in the Amazon Rekognition Developer Guide.

This operation requires permissions to perform the rekognition:ListCollections action.

Parameter Syntax

$result = $client->listCollections([
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

MaxResults

Type: int

Maximum number of collection IDs to return.

NextToken

Type: string

Pagination token from the previous response.

Result Syntax

[
    'CollectionIds' => ['<string>', ...],
    'FaceModelVersions' => ['<string>', ...],
    'NextToken' => '<string>',
]

Result Details

Members

CollectionIds

Type: Array of strings

An array of collection IDs.

FaceModelVersions

Type: Array of strings

Version numbers of the face detection models associated with the collections in the array CollectionIds. For example, the value of FaceModelVersions[2] is the version number for the face detection model used by the collection in CollectionId[2].

NextToken

Type: string

If the result is truncated, the response provides a NextToken that you can use in the subsequent request to fetch the next set of collection IDs.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To list the collections

This operation returns a list of Rekognition collections.

$result = $client->listCollections([
]);

Result syntax:

[
    'CollectionIds' => [
        'myphotos',
    ],
]

ListDatasetEntries

$result = $client->listDatasetEntries([/* ... */]);
$promise = $client->listDatasetEntriesAsync([/* ... */]);

Lists the entries (images) within a dataset. An entry is a JSON Line that contains the information for a single image, including the image location, assigned labels, and object location bounding boxes. For more information, see Creating a manifest file.

JSON Lines in the response include information about non-terminal errors found in the dataset. Non terminal errors are reported in errors lists within each JSON Line. The same information is reported in the training and testing validation result manifests that Amazon Rekognition Custom Labels creates during model training.

You can filter the response in variety of ways, such as choosing which labels to return and returning JSON Lines created after a specific date.

This operation requires permissions to perform the rekognition:ListDatasetEntries action.

Parameter Syntax

$result = $client->listDatasetEntries([
    'ContainsLabels' => ['<string>', ...],
    'DatasetArn' => '<string>', // REQUIRED
    'HasErrors' => true || false,
    'Labeled' => true || false,
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SourceRefContains' => '<string>',
]);

Parameter Details

Members

ContainsLabels

Type: Array of strings

Specifies a label filter for the response. The response includes an entry only if one or more of the labels in ContainsLabels exist in the entry.

DatasetArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) for the dataset that you want to use.

HasErrors

Type: boolean

Specifies an error filter for the response. Specify True to only include entries that have errors.

Labeled

Type: boolean

Specify true to get only the JSON Lines where the image is labeled. Specify false to get only the JSON Lines where the image isn't labeled. If you don't specify Labeled, ListDatasetEntries returns JSON Lines for labeled and unlabeled images.

MaxResults

Type: int

NextToken

Type: string

SourceRefContains

Type: string

If specified, ListDatasetEntries only returns JSON Lines where the value of SourceRefContains is part of the source-ref field. The source-ref field contains the Amazon S3 location of the image. You can use SouceRefContains for tasks such as getting the JSON Line for a single image, or gettting JSON Lines for all images within a specific folder.

Result Syntax

[
    'DatasetEntries' => ['<string>', ...],
    'NextToken' => '<string>',
]

Result Details

Members

DatasetEntries

Type: Array of strings

A list of entries (images) in the dataset.

NextToken

Type: string

Errors

InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
ResourceInUseException:
The specified resource is already being used.
ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ResourceNotReadyException:
The requested resource isn't ready. For example, this exception occurs when you call DetectCustomLabels with a model version that isn't deployed.

Examples

Example 1: To list the entries in an Amazon Rekognition Custom Labels dataset

Lists the JSON line entries in an Amazon Rekognition Custom Labels dataset.

$result = $client->listDatasetEntries([
    'ContainsLabels' => [
        'camellia',
    ],
    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/train/1690564858106',
    'HasErrors' => 1,
    'Labeled' => 1,
    'MaxResults' => 100,
    'NextToken' => '',
    'SourceRefContains' => 'camellia4.jpg',
]);

Result syntax:

[
    'DatasetEntries' => [
        '{"source-ref":"s3://custom-labels-console-us-east-1-1111111111/assets/flowers_1_train_dataset/camellia4.jpg","camellia":1,"camellia-metadata":{"confidence":1,"job-name":"labeling-job/camellia","class-name":"camellia","human-annotated":"yes","creation-date":"2021-07-11T03:32:13.456Z","type":"groundtruth/image-classification"},"with_leaves":1,"with_leaves-metadata":{"confidence":1,"job-name":"labeling-job/with_leaves","class-name":"with_leaves","human-annotated":"yes","creation-date":"2021-07-11T03:32:13.456Z","type":"groundtruth/image-classification"},"cl-metadata":{"is_labeled":true}}',
    ],
    'NextToken' => '',
]

ListDatasetLabels

$result = $client->listDatasetLabels([/* ... */]);
$promise = $client->listDatasetLabelsAsync([/* ... */]);

Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see Labeling images.

Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see Labeling images in the Amazon Rekognition Custom Labels Developer Guide.

Parameter Syntax

$result = $client->listDatasetLabels([
    'DatasetArn' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

DatasetArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the dataset that you want to use.

MaxResults

Type: int

NextToken

Type: string

Result Syntax

[
    'DatasetLabelDescriptions' => [
        [
            'LabelName' => '<string>',
            'LabelStats' => [
                'BoundingBoxCount' => <integer>,
                'EntryCount' => <integer>,
            ],
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members

DatasetLabelDescriptions

Type: Array of DatasetLabelDescription structures

A list of the labels in the dataset.

NextToken

Type: string

Errors

InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
ResourceInUseException:
The specified resource is already being used.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceNotReadyException:
The requested resource isn't ready. For example, this exception occurs when you call DetectCustomLabels with a model version that isn't deployed.

Examples

Example 1: To list the entries in an Amazon Rekognition Custom Labels dataset

Lists the JSON line entries in an Amazon Rekognition Custom Labels dataset.

$result = $client->listDatasetLabels([
    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/train/1690564858106',
    'MaxResults' => 100,
    'NextToken' => '',
]);

Result syntax:

[
    'DatasetLabelDescriptions' => [
        [
            'LabelName' => 'camellia',
            'LabelStats' => [
                'EntryCount' => 1,
            ],
        ],
        [
            'LabelName' => 'with_leaves',
            'LabelStats' => [
                'EntryCount' => 2,
            ],
        ],
        [
            'LabelName' => 'mediterranean_spurge',
            'LabelStats' => [
                'EntryCount' => 1,
            ],
        ],
    ],
]

ListFaces

$result = $client->listFaces([/* ... */]);
$promise = $client->listFacesAsync([/* ... */]);

Returns metadata for faces in the specified collection. This metadata includes information such as the bounding box coordinates, the confidence (that the bounding box contains a face), and face ID. For an example, see Listing Faces in a Collection in the Amazon Rekognition Developer Guide.

This operation requires permissions to perform the rekognition:ListFaces action.

Parameter Syntax

$result = $client->listFaces([
    'CollectionId' => '<string>', // REQUIRED
    'FaceIds' => ['<string>', ...],
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'UserId' => '<string>',
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

ID of the collection from which to list the faces.

FaceIds

Type: Array of strings

An array of face IDs to filter results with when listing faces in a collection.

MaxResults

Type: int

Maximum number of faces to return.

NextToken

Type: string

UserId

Type: string

An array of user IDs to filter results with when listing faces in a collection.

Result Syntax

[
    'FaceModelVersion' => '<string>',
    'Faces' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Confidence' => <float>,
            'ExternalImageId' => '<string>',
            'FaceId' => '<string>',
            'ImageId' => '<string>',
            'IndexFacesModelVersion' => '<string>',
            'UserId' => '<string>',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members

FaceModelVersion

Type: string

Version number of the face detection model associated with the input collection (CollectionId).

Faces

Type: Array of Face structures

An array of Face objects.

NextToken

Type: string

If the response is truncated, Amazon Rekognition returns this token that you can use in the subsequent request to retrieve the next set of faces.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To list the faces in a collection

This operation lists the faces in a Rekognition collection.

$result = $client->listFaces([
    'CollectionId' => 'myphotos',
    'MaxResults' => 20,
]);

Result syntax:

[
    'FaceModelVersion' => '6.0',
    'Faces' => [
        [
            'BoundingBox' => [
                'Height' => 0.056759100407362,
                'Left' => 0.34538298845291,
                'Top' => 0.3656849861145,
                'Width' => 0.031778100878,
            ],
            'Confidence' => 99.769401550293,
            'FaceId' => 'c92265d4-5f9c-43af-a58e-12be0ce02bc3',
            'ImageId' => '56a0ca74-1c83-39dd-b363-051a64168a65',
            'IndexFacesModelVersion' => '6.0',
            'UserId' => 'demoUser2',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.063479997217655,
                'Left' => 0.51606202125549,
                'Top' => 0.60803598165512,
                'Width' => 0.032544501125813,
            ],
            'Confidence' => 99.943695068359,
            'FaceId' => '851cb847-dccc-4fea-9309-9f4805967855',
            'ImageId' => 'a8aed589-ceec-35f7-9c04-82e0b546b024',
            'IndexFacesModelVersion' => '6.0',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.052662901580334,
                'Left' => 0.65138399600983,
                'Top' => 0.42184299230576,
                'Width' => 0.030946299433708,
            ],
            'Confidence' => 99.829696655273,
            'FaceId' => 'c0eb3b65-24a0-41e1-b23a-1908b1aaeac1',
            'ImageId' => '56a0ca74-1c83-39dd-b363-051a64168a65',
            'IndexFacesModelVersion' => '6.0',
        ],
    ],
]

ListProjectPolicies

$result = $client->listProjectPolicies([/* ... */]);
$promise = $client->listProjectPoliciesAsync([/* ... */]);

Gets a list of the project policies attached to a project.

To attach a project policy to a project, call PutProjectPolicy. To remove a project policy from a project, call DeleteProjectPolicy.

This operation requires permissions to perform the rekognition:ListProjectPolicies action.

Parameter Syntax

$result = $client->listProjectPolicies([
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'ProjectArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

MaxResults

Type: int

The maximum number of results to return per paginated call. The largest value you can specify is 5. If you specify a value greater than 5, a ValidationException error occurs. The default value is 5.

NextToken

Type: string

ProjectArn

Required: Yes
Type: string

The ARN of the project for which you want to list the project policies.

Result Syntax

[
    'NextToken' => '<string>',
    'ProjectPolicies' => [
        [
            'CreationTimestamp' => <DateTime>,
            'LastUpdatedTimestamp' => <DateTime>,
            'PolicyDocument' => '<string>',
            'PolicyName' => '<string>',
            'PolicyRevisionId' => '<string>',
            'ProjectArn' => '<string>',
        ],
        // ...
    ],
]

Result Details

Members

NextToken

Type: string

If the response is truncated, Amazon Rekognition returns this token that you can use in the subsequent request to retrieve the next set of project policies.

ProjectPolicies

Type: Array of ProjectPolicy structures

A list of project policies attached to the project.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidPaginationTokenException:
Pagination token in the request is not valid.

Examples

Example 1: ListProjectPolicies

This operation lists the project policies that are attached to an Amazon Rekognition Custom Labels project.

$result = $client->listProjectPolicies([
    'MaxResults' => 5,
    'NextToken' => '',
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-sdk-project/1656557051929',
]);

Result syntax:

[
    'NextToken' => '',
    'ProjectPolicies' => [
        [
            'CreationTimestamp' => ,
            'LastUpdatedTimestamp' => ,
            'PolicyDocument' => '{"Version":"2012-10-17","Statement":[{"Sid":"Statemented1","Effect":"Allow","Principal":{"AWS":"arn:aws:iam::111122223333:root"},"Action":"rekognition:CopyProjectVersion","Resource":"*"}]}',
            'PolicyName' => 'testPolicy',
            'PolicyRevisionId' => '3b274c25e9203a56a99e00e3ff205fbc',
            'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-sdk-project/1656557051929',
        ],
    ],
]

ListStreamProcessors

$result = $client->listStreamProcessors([/* ... */]);
$promise = $client->listStreamProcessorsAsync([/* ... */]);

Gets a list of stream processors that you have created with CreateStreamProcessor.

Parameter Syntax

$result = $client->listStreamProcessors([
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

MaxResults

Type: int

Maximum number of stream processors you want Amazon Rekognition Video to return in the response. The default is 1000.

NextToken

Type: string

If the previous response was incomplete (because there are more stream processors to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of stream processors.

Result Syntax

[
    'NextToken' => '<string>',
    'StreamProcessors' => [
        [
            'Name' => '<string>',
            'Status' => 'STOPPED|STARTING|RUNNING|FAILED|STOPPING|UPDATING',
        ],
        // ...
    ],
]

Result Details

Members

NextToken

Type: string

If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of stream processors.

StreamProcessors

Type: Array of StreamProcessor structures

List of stream processors that you have created.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

ListTagsForResource

$result = $client->listTagsForResource([/* ... */]);
$promise = $client->listTagsForResourceAsync([/* ... */]);

Returns a list of tags in an Amazon Rekognition collection, stream processor, or Custom Labels model.

This operation requires permissions to perform the rekognition:ListTagsForResource action.

Parameter Syntax

$result = $client->listTagsForResource([
    'ResourceArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

ResourceArn

Required: Yes
Type: string

Amazon Resource Name (ARN) of the model, collection, or stream processor that contains the tags that you want a list of.

Result Syntax

[
    'Tags' => ['<string>', ...],
]

Result Details

Members

Tags

Type: Associative array of custom strings keys (TagKey) to strings

A list of key-value tags assigned to the resource.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

ListUsers

$result = $client->listUsers([/* ... */]);
$promise = $client->listUsersAsync([/* ... */]);

Returns metadata of the User such as UserID in the specified collection. Anonymous User (to reserve faces without any identity) is not returned as part of this request. The results are sorted by system generated primary key ID. If the response is truncated, NextToken is returned in the response that can be used in the subsequent request to retrieve the next set of identities.

Parameter Syntax

$result = $client->listUsers([
    'CollectionId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

The ID of an existing collection.

MaxResults

Type: int

Maximum number of UsersID to return.

NextToken

Type: string

Pagingation token to receive the next set of UsersID.

Result Syntax

[
    'NextToken' => '<string>',
    'Users' => [
        [
            'UserId' => '<string>',
            'UserStatus' => 'ACTIVE|UPDATING|CREATING|CREATED',
        ],
        // ...
    ],
]

Result Details

Members

NextToken

Type: string

A pagination token to be used with the subsequent request if the response is truncated.

Users

Type: Array of User structures

List of UsersID associated with the specified collection.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidPaginationTokenException:
Pagination token in the request is not valid.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

Examples

Example 1: ListUsers

Returns metadata of the User such as UserID in the specified collection.

$result = $client->listUsers([
    'CollectionId' => 'MyCollection',
]);

Result syntax:

[
    'NextToken' => 'MGYZLAHX1T5a....',
    'Users' => [
        [
            'UserId' => 'demoUser4',
            'UserStatus' => 'CREATED',
        ],
        [
            'UserId' => 'demoUser2',
            'UserStatus' => 'CREATED',
        ],
    ],
]

PutProjectPolicy

$result = $client->putProjectPolicy([/* ... */]);
$promise = $client->putProjectPolicyAsync([/* ... */]);

Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A project policy specifies that a trusted AWS account can copy a model version from a trusting AWS account to a project in the trusted AWS account. To copy a model version you use the CopyProjectVersion operation.

For more information about the format of a project policy document, see Attaching a project policy (SDK) in the Amazon Rekognition Custom Labels Developer Guide.

The response from PutProjectPolicy is a revision ID for the project policy. You can attach multiple project policies to a project. You can also update an existing project policy by specifying the policy revision ID of the existing policy.

To remove a project policy from a project, call DeleteProjectPolicy. To get a list of project policies attached to a project, call ListProjectPolicies.

You copy a model version by calling CopyProjectVersion.

This operation requires permissions to perform the rekognition:PutProjectPolicy action.

Parameter Syntax

$result = $client->putProjectPolicy([
    'PolicyDocument' => '<string>', // REQUIRED
    'PolicyName' => '<string>', // REQUIRED
    'PolicyRevisionId' => '<string>',
    'ProjectArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

PolicyDocument

Required: Yes
Type: string

A resource policy to add to the model. The policy is a JSON structure that contains one or more statements that define the policy. The policy must follow the IAM syntax. For more information about the contents of a JSON policy document, see IAM JSON policy reference.

PolicyName

Required: Yes
Type: string

A name for the policy.

PolicyRevisionId

Type: string

The revision ID for the Project Policy. Each time you modify a policy, Amazon Rekognition Custom Labels generates and assigns a new PolicyRevisionId and then deletes the previous version of the policy.

ProjectArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the project that the project policy is attached to.

Result Syntax

[
    'PolicyRevisionId' => '<string>',
]

Result Details

Members

PolicyRevisionId

Type: string

The ID of the project policy.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidPolicyRevisionIdException:
The supplied revision id for the project policy is invalid.
MalformedPolicyDocumentException:
The format of the project policy document that you supplied to PutProjectPolicy is incorrect.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceAlreadyExistsException:
A resource with the specified ID already exists.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.

Examples

Example 1: PutProjectPolicy

This operation attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account.

$result = $client->putProjectPolicy([
    'PolicyDocument' => ''{"Version":"2012-10-17","Statement":[{"Effect":"ALLOW","Principal":{"AWS":"principal"},"Action":"rekognition:CopyProjectVersion","Resource":"arn:aws:rekognition:us-east-1:123456789012:project/my-sdk-project/version/DestinationVersionName/1627045542080"}]}'',
    'PolicyName' => 'SamplePolicy',
    'PolicyRevisionId' => '0123456789abcdef',
    'ProjectArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-sdk-project/1656557051929',
]);

Result syntax:

[
    'PolicyRevisionId' => '0123456789abcdef',
]

RecognizeCelebrities

$result = $client->recognizeCelebrities([/* ... */]);
$promise = $client->recognizeCelebritiesAsync([/* ... */]);

Returns an array of celebrities recognized in the input image. For more information, see Recognizing celebrities in the Amazon Rekognition Developer Guide.

RecognizeCelebrities returns the 64 largest faces in the image. It lists the recognized celebrities in the CelebrityFaces array and any unrecognized faces in the UnrecognizedFaces array. RecognizeCelebrities doesn't return celebrities whose faces aren't among the largest 64 faces in the image.

For each celebrity recognized, RecognizeCelebrities returns a Celebrity object. The Celebrity object contains the celebrity name, ID, URL links to additional information, match confidence, and a ComparedFace object that you can use to locate the celebrity's face on the image.

Amazon Rekognition doesn't retain information about which images a celebrity has been recognized in. Your application must store this information and use the Celebrity ID property as a unique identifier for the celebrity. If you don't store the celebrity name or additional information URLs returned by RecognizeCelebrities, you will need the ID to identify the celebrity in a call to the GetCelebrityInfo operation.

For an example, see Recognizing celebrities in an image in the Amazon Rekognition Developer Guide.

This operation requires permissions to perform the rekognition:RecognizeCelebrities operation.

Parameter Syntax

$result = $client->recognizeCelebrities([
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported.

Result Syntax

[
    'CelebrityFaces' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Emotions' => [
                    [
                        'Confidence' => <float>,
                        'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                    ],
                    // ...
                ],
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
                'Pose' => [
                    'Pitch' => <float>,
                    'Roll' => <float>,
                    'Yaw' => <float>,
                ],
                'Quality' => [
                    'Brightness' => <float>,
                    'Sharpness' => <float>,
                ],
                'Smile' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
            ],
            'Id' => '<string>',
            'KnownGender' => [
                'Type' => 'Male|Female|Nonbinary|Unlisted',
            ],
            'MatchConfidence' => <float>,
            'Name' => '<string>',
            'Urls' => ['<string>', ...],
        ],
        // ...
    ],
    'OrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
    'UnrecognizedFaces' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Confidence' => <float>,
            'Emotions' => [
                [
                    'Confidence' => <float>,
                    'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                ],
                // ...
            ],
            'Landmarks' => [
                [
                    'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
            'Pose' => [
                'Pitch' => <float>,
                'Roll' => <float>,
                'Yaw' => <float>,
            ],
            'Quality' => [
                'Brightness' => <float>,
                'Sharpness' => <float>,
            ],
            'Smile' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
        ],
        // ...
    ],
]

Result Details

Members

CelebrityFaces

Type: Array of Celebrity structures

Details about each celebrity found in the image. Amazon Rekognition can detect a maximum of 64 celebrities in an image. Each celebrity object includes the following attributes: Face, Confidence, Emotions, Landmarks, Pose, Quality, Smile, Id, KnownGender, MatchConfidence, Name, Urls.

OrientationCorrection

Type: string

Support for estimating image orientation using the the OrientationCorrection field has ceased as of August 2021. Any returned values for this field included in an API response will always be NULL.

The orientation of the input image (counterclockwise direction). If your application displays the image, you can use this value to correct the orientation. The bounding box coordinates returned in CelebrityFaces and UnrecognizedFaces represent face locations before the image orientation is corrected.

If the input image is in .jpeg format, it might contain exchangeable image (Exif) metadata that includes the image's orientation. If so, and the Exif metadata for the input image populates the orientation field, the value of OrientationCorrection is null. The CelebrityFaces and UnrecognizedFaces bounding box coordinates represent face locations after Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.

UnrecognizedFaces

Type: Array of ComparedFace structures

Details about each unrecognized face in the image.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidImageFormatException:
The provided image format is not supported.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidImageFormatException:
The provided image format is not supported.

SearchFaces

$result = $client->searchFaces([/* ... */]);
$promise = $client->searchFacesAsync([/* ... */]);

For a given input face ID, searches for matching faces in the collection the face belongs to. You get a face ID when you add a face to the collection using the IndexFaces operation. The operation compares the features of the input face with faces in the specified collection.

You can also search faces without indexing faces by using the SearchFacesByImage operation.

The operation response returns an array of faces that match, ordered by similarity score with the highest similarity first. More specifically, it is an array of metadata for each face match that is found. Along with the metadata, the response also includes a confidence value for each face match, indicating the confidence that the specific face matches the input face.

For an example, see Searching for a face using its face ID in the Amazon Rekognition Developer Guide.

This operation requires permissions to perform the rekognition:SearchFaces action.

Parameter Syntax

$result = $client->searchFaces([
    'CollectionId' => '<string>', // REQUIRED
    'FaceId' => '<string>', // REQUIRED
    'FaceMatchThreshold' => <float>,
    'MaxFaces' => <integer>,
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

ID of the collection the face belongs to.

FaceId

Required: Yes
Type: string

ID of a face to find matches for in the collection.

FaceMatchThreshold

Type: float

Optional value specifying the minimum confidence in the face match to return. For example, don't return any matches where confidence in matches is less than 70%. The default value is 80%.

MaxFaces

Type: int

Maximum number of faces to return. The operation returns the maximum number of faces with the highest confidence in the match.

Result Syntax

[
    'FaceMatches' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'ExternalImageId' => '<string>',
                'FaceId' => '<string>',
                'ImageId' => '<string>',
                'IndexFacesModelVersion' => '<string>',
                'UserId' => '<string>',
            ],
            'Similarity' => <float>,
        ],
        // ...
    ],
    'FaceModelVersion' => '<string>',
    'SearchedFaceId' => '<string>',
]

Result Details

Members

FaceMatches

Type: Array of FaceMatch structures

An array of faces that matched the input face, along with the confidence in the match.

FaceModelVersion

Type: string

Version number of the face detection model associated with the input collection (CollectionId).

SearchedFaceId

Type: string

ID of the face that was searched for matches in a collection.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To delete a face

This operation searches for matching faces in the collection the supplied face belongs to.

$result = $client->searchFaces([
    'CollectionId' => 'myphotos',
    'FaceId' => '70008e50-75e4-55d0-8e80-363fb73b3a14',
    'FaceMatchThreshold' => 90,
    'MaxFaces' => 10,
]);

Result syntax:

[
    'FaceMatches' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.3259260058403,
                    'Left' => 0.51444399356842,
                    'Top' => 0.15111100673676,
                    'Width' => 0.24444399774075,
                ],
                'Confidence' => 99.999496459961,
                'FaceId' => '8be04dba-4e58-520d-850e-9eae4af70eb2',
                'ImageId' => '465f4e93-763e-51d0-b030-b9667a2d94b1',
            ],
            'Similarity' => 99.972221374512,
        ],
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.16555599868298,
                    'Left' => 0.30963000655174,
                    'Top' => 0.70666700601578,
                    'Width' => 0.22074100375175,
                ],
                'Confidence' => 100,
                'FaceId' => '29a75abe-397b-5101-ba4f-706783b2246c',
                'ImageId' => '147fdf82-7a71-52cf-819b-e786c7b9746e',
            ],
            'Similarity' => 97.041549682617,
        ],
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.18888899683952,
                    'Left' => 0.37833800911903,
                    'Top' => 0.23555600643158,
                    'Width' => 0.25222599506378,
                ],
                'Confidence' => 99.999900817871,
                'FaceId' => '908544ad-edc3-59df-8faf-6a87cc256cf5',
                'ImageId' => '3c731605-d772-541a-a5e7-0375dbc68a07',
            ],
            'Similarity' => 95.945205688477,
        ],
    ],
    'SearchedFaceId' => '70008e50-75e4-55d0-8e80-363fb73b3a14',
]

SearchFacesByImage

$result = $client->searchFacesByImage([/* ... */]);
$promise = $client->searchFacesByImageAsync([/* ... */]);

For a given input image, first detects the largest face in the image, and then searches the specified collection for matching faces. The operation compares the features of the input face with faces in the specified collection.

To search for all faces in an input image, you might first call the IndexFaces operation, and then use the face IDs returned in subsequent calls to the SearchFaces operation.

You can also call the DetectFaces operation and use the bounding boxes in the response to make face crops, which then you can pass in to the SearchFacesByImage operation.

The response returns an array of faces that match, ordered by similarity score with the highest similarity first. More specifically, it is an array of metadata for each face match found. Along with the metadata, the response also includes a similarity indicating how similar the face is to the input face. In the response, the operation also returns the bounding box (and a confidence level that the bounding box contains a face) of the face that Amazon Rekognition used for the input image.

If no faces are detected in the input image, SearchFacesByImage returns an InvalidParameterException error.

For an example, Searching for a Face Using an Image in the Amazon Rekognition Developer Guide.

The QualityFilter input parameter allows you to filter out detected faces that don’t meet a required quality bar. The quality bar is based on a variety of common use cases. Use QualityFilter to set the quality bar for filtering by specifying LOW, MEDIUM, or HIGH. If you do not want to filter detected faces, specify NONE. The default value is NONE.

To use quality filtering, you need a collection associated with version 3 of the face model or higher. To get the version of the face model associated with a collection, call DescribeCollection.

This operation requires permissions to perform the rekognition:SearchFacesByImage action.

Parameter Syntax

$result = $client->searchFacesByImage([
    'CollectionId' => '<string>', // REQUIRED
    'FaceMatchThreshold' => <float>,
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'MaxFaces' => <integer>,
    'QualityFilter' => 'NONE|AUTO|LOW|MEDIUM|HIGH',
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

ID of the collection to search.

FaceMatchThreshold

Type: float

(Optional) Specifies the minimum confidence in the face match to return. For example, don't return any matches where confidence in matches is less than 70%. The default value is 80%.

Image

Required: Yes
Type: Image structure

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported.

MaxFaces

Type: int

Maximum number of faces to return. The operation returns the maximum number of faces with the highest confidence in the match.

QualityFilter

Type: string

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't searched for in the collection. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE, no filtering is performed. The default value is NONE.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

Result Syntax

[
    'FaceMatches' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'ExternalImageId' => '<string>',
                'FaceId' => '<string>',
                'ImageId' => '<string>',
                'IndexFacesModelVersion' => '<string>',
                'UserId' => '<string>',
            ],
            'Similarity' => <float>,
        ],
        // ...
    ],
    'FaceModelVersion' => '<string>',
    'SearchedFaceBoundingBox' => [
        'Height' => <float>,
        'Left' => <float>,
        'Top' => <float>,
        'Width' => <float>,
    ],
    'SearchedFaceConfidence' => <float>,
]

Result Details

Members

FaceMatches

Type: Array of FaceMatch structures

An array of faces that match the input face, along with the confidence in the match.

FaceModelVersion

Type: string

Version number of the face detection model associated with the input collection (CollectionId).

SearchedFaceBoundingBox

Type: BoundingBox structure

The bounding box around the face in the input image that Amazon Rekognition used for the search.

SearchedFaceConfidence

Type: float

The level of confidence that the searchedFaceBoundingBox, contains a face.

Errors

InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidImageFormatException:
The provided image format is not supported.

Examples

Example 1: To search for faces matching a supplied image

This operation searches for faces in a Rekognition collection that match the largest face in an S3 bucket stored image.

$result = $client->searchFacesByImage([
    'CollectionId' => 'myphotos',
    'FaceMatchThreshold' => 95,
    'Image' => [
        'S3Object' => [
            'Bucket' => 'mybucket',
            'Name' => 'myphoto',
        ],
    ],
    'MaxFaces' => 5,
]);

Result syntax:

[
    'FaceMatches' => [
        [
            'Face' => [
                'BoundingBox' => [
                    'Height' => 0.32344201207161,
                    'Left' => 0.32333299517632,
                    'Top' => 0.5,
                    'Width' => 0.24222199618816,
                ],
                'Confidence' => 99.99829864502,
                'FaceId' => '38271d79-7bc2-5efb-b752-398a8d575b85',
                'ImageId' => 'd5631190-d039-54e4-b267-abd22c8647c5',
            ],
            'Similarity' => 99.970367431641,
        ],
    ],
    'SearchedFaceBoundingBox' => [
        'Height' => 0.33481481671333,
        'Left' => 0.31888890266418,
        'Top' => 0.49333333969116,
        'Width' => 0.25,
    ],
    'SearchedFaceConfidence' => 99.999122619629,
]

SearchUsers

$result = $client->searchUsers([/* ... */]);
$promise = $client->searchUsersAsync([/* ... */]);

Searches for UserIDs within a collection based on a FaceId or UserId. This API can be used to find the closest UserID (with a highest similarity) to associate a face. The request must be provided with either FaceId or UserId. The operation returns an array of UserID that match the FaceId or UserId, ordered by similarity score with the highest similarity first.

Parameter Syntax

$result = $client->searchUsers([
    'CollectionId' => '<string>', // REQUIRED
    'FaceId' => '<string>',
    'MaxUsers' => <integer>,
    'UserId' => '<string>',
    'UserMatchThreshold' => <float>,
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

The ID of an existing collection containing the UserID, used with a UserId or FaceId. If a FaceId is provided, UserId isn’t required to be present in the Collection.

FaceId

Type: string

ID for the existing face.

MaxUsers

Type: int

Maximum number of identities to return.

UserId

Type: string

ID for the existing User.

UserMatchThreshold

Type: float

Optional value that specifies the minimum confidence in the matched UserID to return. Default value of 80.

Result Syntax

[
    'FaceModelVersion' => '<string>',
    'SearchedFace' => [
        'FaceId' => '<string>',
    ],
    'SearchedUser' => [
        'UserId' => '<string>',
    ],
    'UserMatches' => [
        [
            'Similarity' => <float>,
            'User' => [
                'UserId' => '<string>',
                'UserStatus' => 'ACTIVE|UPDATING|CREATING|CREATED',
            ],
        ],
        // ...
    ],
]

Result Details

Members

FaceModelVersion

Type: string

Version number of the face detection model associated with the input CollectionId.

SearchedFace

Type: SearchedFace structure

Contains the ID of a face that was used to search for matches in a collection.

SearchedUser

Type: SearchedUser structure

Contains the ID of the UserID that was used to search for matches in a collection.

UserMatches

Type: Array of UserMatch structures

An array of UserMatch objects that matched the input face along with the confidence in the match. Array will be empty if there are no matches.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

Examples

Example 1: SearchUsers

Searches for UserIDs within a collection based on a FaceId or UserId.

$result = $client->searchUsers([
    'CollectionId' => 'MyCollection',
    'MaxUsers' => 2,
    'UserId' => 'DemoUser',
    'UserMatchThreshold' => 70,
]);

Result syntax:

[
    'FaceModelVersion' => '6',
    'SearchedUser' => [
        'UserId' => 'DemoUser',
    ],
    'UserMatches' => [
        [
            'Similarity' => 99.881866455078,
            'User' => [
                'UserId' => 'demoUser1',
                'UserStatus' => 'ACTIVE',
            ],
        ],
    ],
]

SearchUsersByImage

$result = $client->searchUsersByImage([/* ... */]);
$promise = $client->searchUsersByImageAsync([/* ... */]);

Searches for UserIDs using a supplied image. It first detects the largest face in the image, and then searches a specified collection for matching UserIDs.

The operation returns an array of UserIDs that match the face in the supplied image, ordered by similarity score with the highest similarity first. It also returns a bounding box for the face found in the input image.

Information about faces detected in the supplied image, but not used for the search, is returned in an array of UnsearchedFace objects. If no valid face is detected in the image, the response will contain an empty UserMatches list and no SearchedFace object.

Parameter Syntax

$result = $client->searchUsersByImage([
    'CollectionId' => '<string>', // REQUIRED
    'Image' => [ // REQUIRED
        'Bytes' => <string || resource || Psr\Http\Message\StreamInterface>,
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
    'MaxUsers' => <integer>,
    'QualityFilter' => 'NONE|AUTO|LOW|MEDIUM|HIGH',
    'UserMatchThreshold' => <float>,
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

The ID of an existing collection containing the UserID.

Image

Required: Yes
Type: Image structure

Provides the input image either as bytes or an S3 object.

For more information, see Analyzing an Image Loaded from a Local File System in the Amazon Rekognition Developer Guide.

You pass images stored in an S3 bucket to an Amazon Rekognition API operation by using the S3Object property. Images stored in an S3 bucket do not need to be base64-encoded.

The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

MaxUsers

Type: int

Maximum number of UserIDs to return.

QualityFilter

Type: string

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't searched for in the collection. The default value is NONE.

UserMatchThreshold

Type: float

Specifies the minimum confidence in the UserID match to return. Default value is 80.

Result Syntax

[
    'FaceModelVersion' => '<string>',
    'SearchedFace' => [
        'FaceDetail' => [
            'AgeRange' => [
                'High' => <integer>,
                'Low' => <integer>,
            ],
            'Beard' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Confidence' => <float>,
            'Emotions' => [
                [
                    'Confidence' => <float>,
                    'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                ],
                // ...
            ],
            'EyeDirection' => [
                'Confidence' => <float>,
                'Pitch' => <float>,
                'Yaw' => <float>,
            ],
            'Eyeglasses' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'EyesOpen' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'FaceOccluded' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Gender' => [
                'Confidence' => <float>,
                'Value' => 'Male|Female',
            ],
            'Landmarks' => [
                [
                    'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
            'MouthOpen' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Mustache' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Pose' => [
                'Pitch' => <float>,
                'Roll' => <float>,
                'Yaw' => <float>,
            ],
            'Quality' => [
                'Brightness' => <float>,
                'Sharpness' => <float>,
            ],
            'Smile' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'Sunglasses' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
        ],
    ],
    'UnsearchedFaces' => [
        [
            'FaceDetails' => [
                'AgeRange' => [
                    'High' => <integer>,
                    'Low' => <integer>,
                ],
                'Beard' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Confidence' => <float>,
                'Emotions' => [
                    [
                        'Confidence' => <float>,
                        'Type' => 'HAPPY|SAD|ANGRY|CONFUSED|DISGUSTED|SURPRISED|CALM|UNKNOWN|FEAR',
                    ],
                    // ...
                ],
                'EyeDirection' => [
                    'Confidence' => <float>,
                    'Pitch' => <float>,
                    'Yaw' => <float>,
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'FaceOccluded' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Gender' => [
                    'Confidence' => <float>,
                    'Value' => 'Male|Female',
                ],
                'Landmarks' => [
                    [
                        'Type' => 'eyeLeft|eyeRight|nose|mouthLeft|mouthRight|leftEyeBrowLeft|leftEyeBrowRight|leftEyeBrowUp|rightEyeBrowLeft|rightEyeBrowRight|rightEyeBrowUp|leftEyeLeft|leftEyeRight|leftEyeUp|leftEyeDown|rightEyeLeft|rightEyeRight|rightEyeUp|rightEyeDown|noseLeft|noseRight|mouthUp|mouthDown|leftPupil|rightPupil|upperJawlineLeft|midJawlineLeft|chinBottom|midJawlineRight|upperJawlineRight',
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
                'MouthOpen' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Mustache' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Pose' => [
                    'Pitch' => <float>,
                    'Roll' => <float>,
                    'Yaw' => <float>,
                ],
                'Quality' => [
                    'Brightness' => <float>,
                    'Sharpness' => <float>,
                ],
                'Smile' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'Sunglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
            ],
            'Reasons' => ['<string>', ...],
        ],
        // ...
    ],
    'UserMatches' => [
        [
            'Similarity' => <float>,
            'User' => [
                'UserId' => '<string>',
                'UserStatus' => 'ACTIVE|UPDATING|CREATING|CREATED',
            ],
        ],
        // ...
    ],
]

Result Details

Members

FaceModelVersion

Type: string

Version number of the face detection model associated with the input collection CollectionId.

SearchedFace

Type: SearchedFaceDetails structure

A list of FaceDetail objects containing the BoundingBox for the largest face in image, as well as the confidence in the bounding box, that was searched for matches. If no valid face is detected in the image the response will contain no SearchedFace object.

UnsearchedFaces

Type: Array of UnsearchedFace structures

List of UnsearchedFace objects. Contains the face details infered from the specified image but not used for search. Contains reasons that describe why a face wasn't used for Search.

UserMatches

Type: Array of UserMatch structures

An array of UserID objects that matched the input face, along with the confidence in the match. The returned structure will be empty if there are no matches. Returned if the SearchUsersByImageResponse action is successful.

Errors

InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidImageFormatException:
The provided image format is not supported.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
ImageTooLargeException:
The input image size exceeds the allowed limit. If you are calling DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

Examples

Example 1: SearchUsersByImage

Searches for UserIDs using a supplied image.

$result = $client->searchUsersByImage([
    'CollectionId' => 'MyCollection',
    'Image' => [
        'S3Object' => [
            'Bucket' => 'bucket',
            'Name' => 'input.jpg',
        ],
    ],
    'MaxUsers' => 2,
    'QualityFilter' => 'MEDIUM',
    'UserMatchThreshold' => 70,
]);

Result syntax:

[
    'FaceModelVersion' => '6',
    'SearchedFace' => [
        'FaceDetail' => [
            'BoundingBox' => [
                'Height' => 0.075100161135197,
                'Left' => 0.35986787080765,
                'Top' => 0.53915268182755,
                'Width' => 0.036928374320269,
            ],
        ],
    ],
    'UnsearchedFaces' => [
        [
            'FaceDetails' => [
                'BoundingBox' => [
                    'Height' => 0.068217702209949,
                    'Left' => 0.610256254673,
                    'Top' => 0.5593535900116,
                    'Width' => 0.031677018851042,
                ],
            ],
            'Reasons' => [
                'FACE_NOT_LARGEST',
            ],
        ],
        [
            'FaceDetails' => [
                'BoundingBox' => [
                    'Height' => 0.063479974865913,
                    'Left' => 0.51606231927872,
                    'Top' => 0.60803580284119,
                    'Width' => 0.032544497400522,
                ],
            ],
            'Reasons' => [
                'FACE_NOT_LARGEST',
            ],
        ],
    ],
    'UserMatches' => [
        [
            'Similarity' => 99.881866455078,
            'User' => [
                'UserId' => 'demoUser1',
                'UserStatus' => 'ACTIVE',
            ],
        ],
    ],
]

StartCelebrityRecognition

$result = $client->startCelebrityRecognition([/* ... */]);
$promise = $client->startCelebrityRecognitionAsync([/* ... */]);

Starts asynchronous recognition of celebrities in a stored video.

Amazon Rekognition Video can detect celebrities in a video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartCelebrityRecognition returns a job identifier (JobId) which you use to get the results of the analysis. When celebrity recognition analysis is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel. To get the results of the celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetCelebrityRecognition and pass the job identifier (JobId) from the initial call to StartCelebrityRecognition.

For more information, see Recognizing celebrities in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->startCelebrityRecognition([
    'ClientRequestToken' => '<string>',
    'JobTag' => '<string>',
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartCelebrityRecognition requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

JobTag

Type: string

An identifier you specify that's returned in the completion notification that's published to your Amazon Simple Notification Service topic. For example, you can use JobTag to group related jobs and identify them in the completion notification.

NotificationChannel

Type: NotificationChannel structure

The Amazon SNS topic ARN that you want Amazon Rekognition Video to publish the completion status of the celebrity recognition analysis to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.

Video

Required: Yes
Type: Video structure

The video in which you want to recognize celebrities. The video must be stored in an Amazon S3 bucket.

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

The identifier for the celebrity recognition analysis job. Use JobId to identify the job in a subsequent call to GetCelebrityRecognition.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartContentModeration

$result = $client->startContentModeration([/* ... */]);
$promise = $client->startContentModerationAsync([/* ... */]);

Starts asynchronous detection of inappropriate, unwanted, or offensive content in a stored video. For a list of moderation labels in Amazon Rekognition, see Using the image and video moderation APIs.

Amazon Rekognition Video can moderate content in a video stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartContentModeration returns a job identifier (JobId) which you use to get the results of the analysis. When content analysis is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel.

To get the results of the content analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetContentModeration and pass the job identifier (JobId) from the initial call to StartContentModeration.

For more information, see Moderating content in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->startContentModeration([
    'ClientRequestToken' => '<string>',
    'JobTag' => '<string>',
    'MinConfidence' => <float>,
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartContentModeration requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

JobTag

Type: string

MinConfidence

Type: float

Specifies the minimum confidence that Amazon Rekognition must have in order to return a moderated content label. Confidence represents how certain Amazon Rekognition is that the moderated content is correctly identified. 0 is the lowest confidence. 100 is the highest confidence. Amazon Rekognition doesn't return any moderated content labels with a confidence level lower than this specified value. If you don't specify MinConfidence, GetContentModeration returns labels with confidence values greater than or equal to 50 percent.

NotificationChannel

Type: NotificationChannel structure

The Amazon SNS topic ARN that you want Amazon Rekognition Video to publish the completion status of the content analysis to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy to access the topic.

Video

Required: Yes
Type: Video structure

The video in which you want to detect inappropriate, unwanted, or offensive content. The video must be stored in an Amazon S3 bucket.

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

The identifier for the content analysis job. Use JobId to identify the job in a subsequent call to GetContentModeration.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartFaceDetection

$result = $client->startFaceDetection([/* ... */]);
$promise = $client->startFaceDetectionAsync([/* ... */]);

Starts asynchronous detection of faces in a stored video.

Amazon Rekognition Video can detect faces in a video stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartFaceDetection returns a job identifier (JobId) that you use to get the results of the operation. When face detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel. To get the results of the face detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceDetection and pass the job identifier (JobId) from the initial call to StartFaceDetection.

For more information, see Detecting faces in a stored video in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->startFaceDetection([
    'ClientRequestToken' => '<string>',
    'FaceAttributes' => 'DEFAULT|ALL',
    'JobTag' => '<string>',
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartFaceDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

FaceAttributes

Type: string

The face attributes you want returned.

DEFAULT - The following subset of facial attributes are returned: BoundingBox, Confidence, Pose, Quality and Landmarks.

ALL - All facial attributes are returned.

JobTag

Type: string

NotificationChannel

Type: NotificationChannel structure

The ARN of the Amazon SNS topic to which you want Amazon Rekognition Video to publish the completion status of the face detection operation. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.

Video

Required: Yes
Type: Video structure

The video in which you want to detect faces. The video must be stored in an Amazon S3 bucket.

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

The identifier for the face detection job. Use JobId to identify the job in a subsequent call to GetFaceDetection.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartFaceSearch

$result = $client->startFaceSearch([/* ... */]);
$promise = $client->startFaceSearchAsync([/* ... */]);

Starts the asynchronous search for faces in a collection that match the faces of persons detected in a stored video.

The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartFaceSearch returns a job identifier (JobId) which you use to get the search results once the search has completed. When searching is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel. To get the search results, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (JobId) from the initial call to StartFaceSearch. For more information, see Searching stored videos for faces.

Parameter Syntax

$result = $client->startFaceSearch([
    'ClientRequestToken' => '<string>',
    'CollectionId' => '<string>', // REQUIRED
    'FaceMatchThreshold' => <float>,
    'JobTag' => '<string>',
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartFaceSearch requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

CollectionId

Required: Yes
Type: string

ID of the collection that contains the faces you want to search for.

FaceMatchThreshold

Type: float

The minimum confidence in the person match to return. For example, don't return any matches where confidence in matches is less than 70%. The default value is 80%.

JobTag

Type: string

NotificationChannel

Type: NotificationChannel structure

The ARN of the Amazon SNS topic to which you want Amazon Rekognition Video to publish the completion status of the search. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy to access the topic.

Video

Required: Yes
Type: Video structure

The video you want to search. The video must be stored in an Amazon S3 bucket.

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

The identifier for the search job. Use JobId to identify the job in a subsequent call to GetFaceSearch.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartLabelDetection

$result = $client->startLabelDetection([/* ... */]);
$promise = $client->startLabelDetectionAsync([/* ... */]);

Starts asynchronous detection of labels in a stored video.

Amazon Rekognition Video can detect labels in a video. Labels are instances of real-world entities. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; concepts like landscape, evening, and nature; and activities like a person getting out of a car or a person skiing.

The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartLabelDetection returns a job identifier (JobId) which you use to get the results of the operation. When label detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel.

Optional Parameters

StartLabelDetection has the GENERAL_LABELS Feature applied by default. This feature allows you to provide filtering criteria to the Settings parameter. You can filter with sets of individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information on filtering, see Detecting labels in a video.

You can specify MinConfidence to control the confidence threshold for the labels returned. The default is 50.

Parameter Syntax

$result = $client->startLabelDetection([
    'ClientRequestToken' => '<string>',
    'Features' => ['<string>', ...],
    'JobTag' => '<string>',
    'MinConfidence' => <float>,
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Settings' => [
        'GeneralLabels' => [
            'LabelCategoryExclusionFilters' => ['<string>', ...],
            'LabelCategoryInclusionFilters' => ['<string>', ...],
            'LabelExclusionFilters' => ['<string>', ...],
            'LabelInclusionFilters' => ['<string>', ...],
        ],
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartLabelDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

Features

Type: Array of strings

The features to return after video analysis. You can specify that GENERAL_LABELS are returned.

JobTag

Type: string

MinConfidence

Type: float

Specifies the minimum confidence that Amazon Rekognition Video must have in order to return a detected label. Confidence represents how certain Amazon Rekognition is that a label is correctly identified.0 is the lowest confidence. 100 is the highest confidence. Amazon Rekognition Video doesn't return any labels with a confidence level lower than this specified value.

If you don't specify MinConfidence, the operation returns labels and bounding boxes (if detected) with confidence values greater than or equal to 50 percent.

NotificationChannel

Type: NotificationChannel structure

The Amazon SNS topic ARN you want Amazon Rekognition Video to publish the completion status of the label detection operation to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.

Settings

Type: LabelDetectionSettings structure

The settings for a StartLabelDetection request.Contains the specified parameters for the label detection request of an asynchronous label analysis operation. Settings can include filters for GENERAL_LABELS.

Video

Required: Yes
Type: Video structure

The video in which you want to detect labels. The video must be stored in an Amazon S3 bucket.

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

The identifier for the label detection job. Use JobId to identify the job in a subsequent call to GetLabelDetection.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartPersonTracking

$result = $client->startPersonTracking([/* ... */]);
$promise = $client->startPersonTrackingAsync([/* ... */]);

Starts the asynchronous tracking of a person's path in a stored video.

Amazon Rekognition Video can track the path of people in a video stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartPersonTracking returns a job identifier (JobId) which you use to get the results of the operation. When label detection is finished, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel.

To get the results of the person detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (JobId) from the initial call to StartPersonTracking.

Parameter Syntax

$result = $client->startPersonTracking([
    'ClientRequestToken' => '<string>',
    'JobTag' => '<string>',
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartPersonTracking requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

JobTag

Type: string

NotificationChannel

Type: NotificationChannel structure

The Amazon SNS topic ARN you want Amazon Rekognition Video to publish the completion status of the people detection operation to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.

Video

Required: Yes
Type: Video structure

The video in which you want to detect people. The video must be stored in an Amazon S3 bucket.

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

The identifier for the person detection job. Use JobId to identify the job in a subsequent call to GetPersonTracking.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartProjectVersion

$result = $client->startProjectVersion([/* ... */]);
$promise = $client->startProjectVersionAsync([/* ... */]);

Starts the running of the version of a model. Starting a model takes a while to complete. To check the current state of the model, use DescribeProjectVersions.

Once the model is running, you can detect custom labels in new images by calling DetectCustomLabels.

You are charged for the amount of time that the model is running. To stop a running model, call StopProjectVersion.

For more information, see Running a trained Amazon Rekognition Custom Labels model in the Amazon Rekognition Custom Labels Guide.

This operation requires permissions to perform the rekognition:StartProjectVersion action.

Parameter Syntax

$result = $client->startProjectVersion([
    'MaxInferenceUnits' => <integer>,
    'MinInferenceUnits' => <integer>, // REQUIRED
    'ProjectVersionArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

MaxInferenceUnits

Type: int

The maximum number of inference units to use for auto-scaling the model. If you don't specify a value, Amazon Rekognition Custom Labels doesn't auto-scale the model.

MinInferenceUnits

Required: Yes
Type: int

The minimum number of inference units to use. A single inference unit represents 1 hour of processing.

For information about the number of transactions per second (TPS) that an inference unit can support, see Running a trained Amazon Rekognition Custom Labels model in the Amazon Rekognition Custom Labels Guide.

Use a higher number to increase the TPS throughput of your model. You are charged for the number of inference units that you use.

ProjectVersionArn

Required: Yes
Type: string

The Amazon Resource Name(ARN) of the model version that you want to start.

Result Syntax

[
    'Status' => 'TRAINING_IN_PROGRESS|TRAINING_COMPLETED|TRAINING_FAILED|STARTING|RUNNING|FAILED|STOPPING|STOPPED|DELETING|COPYING_IN_PROGRESS|COPYING_COMPLETED|COPYING_FAILED',
]

Result Details

Members

Status

Type: string

The current running status of the model.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceInUseException:
The specified resource is already being used.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To start an Amazon Rekognition Custom Labels model

Starts a version of an Amazon Rekognition Custom Labels model.

$result = $client->startProjectVersion([
    'MaxInferenceUnits' => 1,
    'MinInferenceUnits' => 1,
    'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/version/1/1690556751958',
]);

Result syntax:

[
    'Status' => 'STARTING',
]

StartSegmentDetection

$result = $client->startSegmentDetection([/* ... */]);
$promise = $client->startSegmentDetectionAsync([/* ... */]);

Starts asynchronous detection of segment detection in a stored video.

Amazon Rekognition Video can detect segments in a video stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartSegmentDetection returns a job identifier (JobId) which you use to get the results of the operation. When segment detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel.

You can use the Filters (StartSegmentDetectionFilters) input parameter to specify the minimum detection confidence returned in the response. Within Filters, use ShotFilter (StartShotDetectionFilter) to filter detected shots. Use TechnicalCueFilter (StartTechnicalCueDetectionFilter) to filter technical cues.

To get the results of the segment detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so, call GetSegmentDetection and pass the job identifier (JobId) from the initial call to StartSegmentDetection.

For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide.

Parameter Syntax

$result = $client->startSegmentDetection([
    'ClientRequestToken' => '<string>',
    'Filters' => [
        'ShotFilter' => [
            'MinSegmentConfidence' => <float>,
        ],
        'TechnicalCueFilter' => [
            'BlackFrame' => [
                'MaxPixelThreshold' => <float>,
                'MinCoveragePercentage' => <float>,
            ],
            'MinSegmentConfidence' => <float>,
        ],
    ],
    'JobTag' => '<string>',
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'SegmentTypes' => ['<string>', ...], // REQUIRED
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartSegmentDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidently started more than once.

Filters

Type: StartSegmentDetectionFilters structure

Filters for technical cue or shot detection.

JobTag

Type: string

NotificationChannel

Type: NotificationChannel structure

The ARN of the Amazon SNS topic to which you want Amazon Rekognition Video to publish the completion status of the segment detection operation. Note that the Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy to access the topic.

SegmentTypes

Required: Yes
Type: Array of strings

An array of segment types to detect in the video. Valid values are TECHNICAL_CUE and SHOT.

Video

Required: Yes
Type: Video structure

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

Unique identifier for the segment detection job. The JobId is returned from StartSegmentDetection.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StartStreamProcessor

$result = $client->startStreamProcessor([/* ... */]);
$promise = $client->startStreamProcessorAsync([/* ... */]);

Starts processing a stream processor. You create a stream processor by calling CreateStreamProcessor. To tell StartStreamProcessor which stream processor to start, use the value of the Name field specified in the call to CreateStreamProcessor.

If you are using a label detection stream processor to detect labels, you need to provide a Start selector and a Stop selector to determine the length of the stream processing time.

Parameter Syntax

$result = $client->startStreamProcessor([
    'Name' => '<string>', // REQUIRED
    'StartSelector' => [
        'KVSStreamStartSelector' => [
            'FragmentNumber' => '<string>',
            'ProducerTimestamp' => <integer>,
        ],
    ],
    'StopSelector' => [
        'MaxDurationInSeconds' => <integer>,
    ],
]);

Parameter Details

Members

Name

Required: Yes
Type: string

The name of the stream processor to start processing.

StartSelector

Type: StreamProcessingStartSelector structure

Specifies the starting point in the Kinesis stream to start processing. You can use the producer timestamp or the fragment number. If you use the producer timestamp, you must put the time in milliseconds. For more information about fragment numbers, see Fragment.

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

StopSelector

Type: StreamProcessingStopSelector structure

Specifies when to stop processing the stream. You can specify a maximum amount of time to process the video.

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

Result Syntax

[
    'SessionId' => '<string>',
]

Result Details

Members

SessionId

Type: string

A unique identifier for the stream processing session.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceInUseException:
The specified resource is already being used.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

StartTextDetection

$result = $client->startTextDetection([/* ... */]);
$promise = $client->startTextDetectionAsync([/* ... */]);

Starts asynchronous detection of text in a stored video.

Amazon Rekognition Video can detect text in a video stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartTextDetection returns a job identifier (JobId) which you use to get the results of the operation. When text detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel.

To get the results of the text detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so, call GetTextDetection and pass the job identifier (JobId) from the initial call to StartTextDetection.

Parameter Syntax

$result = $client->startTextDetection([
    'ClientRequestToken' => '<string>',
    'Filters' => [
        'RegionsOfInterest' => [
            [
                'BoundingBox' => [
                    'Height' => <float>,
                    'Left' => <float>,
                    'Top' => <float>,
                    'Width' => <float>,
                ],
                'Polygon' => [
                    [
                        'X' => <float>,
                        'Y' => <float>,
                    ],
                    // ...
                ],
            ],
            // ...
        ],
        'WordFilter' => [
            'MinBoundingBoxHeight' => <float>,
            'MinBoundingBoxWidth' => <float>,
            'MinConfidence' => <float>,
        ],
    ],
    'JobTag' => '<string>',
    'NotificationChannel' => [
        'RoleArn' => '<string>', // REQUIRED
        'SNSTopicArn' => '<string>', // REQUIRED
    ],
    'Video' => [ // REQUIRED
        'S3Object' => [
            'Bucket' => '<string>',
            'Name' => '<string>',
            'Version' => '<string>',
        ],
    ],
]);

Parameter Details

Members

ClientRequestToken

Type: string

Idempotent token used to identify the start request. If you use the same token with multiple StartTextDetection requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentaly started more than once.

Filters

Type: StartTextDetectionFilters structure

Optional parameters that let you set criteria the text must meet to be included in your response.

JobTag

Type: string

An identifier returned in the completion status published by your Amazon Simple Notification Service topic. For example, you can use JobTag to group related jobs and identify them in the completion notification.

NotificationChannel

Type: NotificationChannel structure

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the completion status of a video analysis operation. For more information, see Calling Amazon Rekognition Video operations. Note that the Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy to access the topic. For more information, see Giving access to multiple Amazon SNS topics.

Video

Required: Yes
Type: Video structure

Result Syntax

[
    'JobId' => '<string>',
]

Result Details

Members

JobId

Type: string

Identifier for the text detection job. Use JobId to identify the job in a subsequent call to GetTextDetection.

Errors

AccessDeniedException:
You are not authorized to perform the action.
IdempotentParameterMismatchException:
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.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
InvalidS3ObjectException:
Amazon Rekognition is unable to access the S3 object specified in the request.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
VideoTooLargeException:
The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.

StopProjectVersion

$result = $client->stopProjectVersion([/* ... */]);
$promise = $client->stopProjectVersionAsync([/* ... */]);

Stops a running model. The operation might take a while to complete. To check the current status, call DescribeProjectVersions.

This operation requires permissions to perform the rekognition:StopProjectVersion action.

Parameter Syntax

$result = $client->stopProjectVersion([
    'ProjectVersionArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

ProjectVersionArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the model version that you want to delete.

This operation requires permissions to perform the rekognition:StopProjectVersion action.

Result Syntax

[
    'Status' => 'TRAINING_IN_PROGRESS|TRAINING_COMPLETED|TRAINING_FAILED|STARTING|RUNNING|FAILED|STOPPING|STOPPED|DELETING|COPYING_IN_PROGRESS|COPYING_COMPLETED|COPYING_FAILED',
]

Result Details

Members

Status

Type: string

The current status of the stop operation.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceInUseException:
The specified resource is already being used.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

Examples

Example 1: To stop an Amazon Rekognition Custom Labels model.

Stops a version of an Amazon Rekognition Custom Labels model.

$result = $client->stopProjectVersion([
    'ProjectVersionArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-project/version/1/1690556751958',
]);

Result syntax:

[
    'Status' => 'STOPPING',
]

StopStreamProcessor

$result = $client->stopStreamProcessor([/* ... */]);
$promise = $client->stopStreamProcessorAsync([/* ... */]);

Stops a running stream processor that was created by CreateStreamProcessor.

Parameter Syntax

$result = $client->stopStreamProcessor([
    'Name' => '<string>', // REQUIRED
]);

Parameter Details

Members

Name

Required: Yes
Type: string

The name of a stream processor created by CreateStreamProcessor.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ResourceInUseException:
The specified resource is already being used.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

TagResource

$result = $client->tagResource([/* ... */]);
$promise = $client->tagResourceAsync([/* ... */]);

Adds one or more key-value tags to an Amazon Rekognition collection, stream processor, or Custom Labels model. For more information, see Tagging AWS Resources.

This operation requires permissions to perform the rekognition:TagResource action.

Parameter Syntax

$result = $client->tagResource([
    'ResourceArn' => '<string>', // REQUIRED
    'Tags' => ['<string>', ...], // REQUIRED
]);

Parameter Details

Members

ResourceArn

Required: Yes
Type: string

Amazon Resource Name (ARN) of the model, collection, or stream processor that you want to assign the tags to.

Tags

Required: Yes
Type: Associative array of custom strings keys (TagKey) to strings

The key-value tags to assign to the resource.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ServiceQuotaExceededException:

The size of the collection exceeds the allowed limit. For more information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

UntagResource

$result = $client->untagResource([/* ... */]);
$promise = $client->untagResourceAsync([/* ... */]);

Removes one or more tags from an Amazon Rekognition collection, stream processor, or Custom Labels model.

This operation requires permissions to perform the rekognition:UntagResource action.

Parameter Syntax

$result = $client->untagResource([
    'ResourceArn' => '<string>', // REQUIRED
    'TagKeys' => ['<string>', ...], // REQUIRED
]);

Parameter Details

Members

ResourceArn

Required: Yes
Type: string

Amazon Resource Name (ARN) of the model, collection, or stream processor that you want to remove the tags from.

TagKeys

Required: Yes
Type: Array of strings

A list of the tags that you want to remove.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:
The resource specified in the request cannot be found.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

UpdateDatasetEntries

$result = $client->updateDatasetEntries([/* ... */]);
$promise = $client->updateDatasetEntriesAsync([/* ... */]);

Adds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the information for a single image, including the image location, assigned labels, and object location bounding boxes. For more information, see Image-Level labels in manifest files and Object localization in manifest files in the Amazon Rekognition Custom Labels Developer Guide.

If the source-ref field in the JSON line references an existing image, the existing image in the dataset is updated. If source-ref field doesn't reference an existing image, the image is added as a new image to the dataset.

You specify the changes that you want to make in the Changes input parameter. There isn't a limit to the number JSON Lines that you can change, but the size of Changes must be less than 5MB.

UpdateDatasetEntries returns immediatly, but the dataset update might take a while to complete. Use DescribeDataset to check the current status. The dataset updated successfully if the value of Status is UPDATE_COMPLETE.

To check if any non-terminal errors occured, call ListDatasetEntries and check for the presence of errors lists in the JSON Lines.

Dataset update fails if a terminal error occurs (Status = UPDATE_FAILED). Currently, you can't access the terminal error information from the Amazon Rekognition Custom Labels SDK.

This operation requires permissions to perform the rekognition:UpdateDatasetEntries action.

Parameter Syntax

$result = $client->updateDatasetEntries([
    'Changes' => [ // REQUIRED
        'GroundTruth' => <string || resource || Psr\Http\Message\StreamInterface>, // REQUIRED
    ],
    'DatasetArn' => '<string>', // REQUIRED
]);

Parameter Details

Members

Changes

Required: Yes
Type: DatasetChanges structure

The changes that you want to make to the dataset.

DatasetArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the dataset that you want to update.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
AccessDeniedException:
You are not authorized to perform the action.
LimitExceededException:
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until the number of concurrently running jobs is below the Amazon Rekognition service limit.
ResourceInUseException:
The specified resource is already being used.
ResourceNotFoundException:
The resource specified in the request cannot be found.

Examples

Example 1: To-add dataset entries to an Amazon Rekognition Custom Labels dataset

Adds dataset entries to an Amazon Rekognition Custom Labels dataset.

$result = $client->updateDatasetEntries([
    'Changes' => [
        'GroundTruth' => <BLOB>,
    ],
    'DatasetArn' => 'arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/train/1690564858106',
]);

Result syntax:

[
]

UpdateStreamProcessor

$result = $client->updateStreamProcessor([/* ... */]);
$promise = $client->updateStreamProcessorAsync([/* ... */]);

Allows you to update a stream processor. You can change some settings and regions of interest and delete certain parameters.

Parameter Syntax

$result = $client->updateStreamProcessor([
    'DataSharingPreferenceForUpdate' => [
        'OptIn' => true || false, // REQUIRED
    ],
    'Name' => '<string>', // REQUIRED
    'ParametersToDelete' => ['<string>', ...],
    'RegionsOfInterestForUpdate' => [
        [
            'BoundingBox' => [
                'Height' => <float>,
                'Left' => <float>,
                'Top' => <float>,
                'Width' => <float>,
            ],
            'Polygon' => [
                [
                    'X' => <float>,
                    'Y' => <float>,
                ],
                // ...
            ],
        ],
        // ...
    ],
    'SettingsForUpdate' => [
        'ConnectedHomeForUpdate' => [
            'Labels' => ['<string>', ...],
            'MinConfidence' => <float>,
        ],
    ],
]);

Parameter Details

Members

DataSharingPreferenceForUpdate

Type: StreamProcessorDataSharingPreference structure

Name

Required: Yes
Type: string

Name of the stream processor that you want to update.

ParametersToDelete

Type: Array of strings

A list of parameters you want to delete from the stream processor.

RegionsOfInterestForUpdate

Type: Array of RegionOfInterest structures

Specifies locations in the frames where Amazon Rekognition checks for objects or people. This is an optional parameter for label detection stream processors.

SettingsForUpdate

Type: StreamProcessorSettingsForUpdate structure

The stream processor settings that you want to update. Label detection settings can be updated to detect different labels with a different minimum confidence.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

AccessDeniedException:
You are not authorized to perform the action.
InternalServerError:
Amazon Rekognition experienced a service issue. Try your call again.
ThrottlingException:
Amazon Rekognition is temporarily unable to process the request. Try your call again.
InvalidParameterException:
Input parameter violated a constraint. Validate your parameter before calling the API operation again.
ResourceNotFoundException:
The resource specified in the request cannot be found.
ProvisionedThroughputExceededException:
The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.
ResourceInUseException:
The specified resource is already being used.

Shapes

AccessDeniedException

Description

You are not authorized to perform the action.

Members

AgeRange

Description

Structure containing the estimated age range, in years, for a face.

Amazon Rekognition estimates an age range for faces detected in the input image. Estimated age ranges can overlap. A face of a 5-year-old might have an estimated range of 4-6, while the face of a 6-year-old might have an estimated range of 4-8.

Members

High

Type: int

The highest estimated age.

Low

Type: int

The lowest estimated age.

Asset

Description

Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

Members

GroundTruthManifest

Type: GroundTruthManifest structure

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

AssociatedFace

Description

Provides face metadata for the faces that are associated to a specific UserID.

Members

FaceId

Type: string

Unique identifier assigned to the face.

AudioMetadata

Description

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

Members

Codec

Type: string

The audio codec used to encode or decode the audio stream.

DurationMillis

Type: long (int|float)

The duration of the audio stream in milliseconds.

NumberOfChannels

Type: long (int|float)

The number of audio channels in the segment.

SampleRate

Type: long (int|float)

The sample rate for the audio stream.

AuditImage

Description

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

Members

BoundingBox

Type: BoundingBox structure

Identifies the bounding box around the label, face, text, object of interest, or personal protective equipment. The left (x-coordinate) and top (y-coordinate) are coordinates representing the top and left sides of the bounding box. Note that the upper-left corner of the image is the origin (0,0).

The top and left values returned are ratios of the overall image size. For example, if the input image is 700x200 pixels, and the top-left coordinate of the bounding box is 350x50 pixels, the API returns a left value of 0.5 (350/700) and a top value of 0.25 (50/200).

The width and height values represent the dimensions of the bounding box as a ratio of the overall image dimension. For example, if the input image is 700x200 pixels, and the bounding box width is 70 pixels, the width returned is 0.1.

The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.

Bytes

Type: blob (string|resource|Psr\Http\Message\StreamInterface)

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

S3Object

Type: S3Object structure

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.

Beard

Description

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

Members

Confidence

Type: float

Level of confidence in the determination.

Value

Type: boolean

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

BlackFrame

Description

A filter that allows you to control the black frame detection by specifying the black levels and pixel coverage of black pixels in a frame. As videos can come from multiple sources, formats, and time periods, they may contain different standards and varying noise levels for black frames that need to be accounted for. For more information, see StartSegmentDetection.

Members

MaxPixelThreshold

Type: float

A threshold used to determine the maximum luminance value for a pixel to be considered black. In a full color range video, luminance values range from 0-255. A pixel value of 0 is pure black, and the most strict filter. The maximum black pixel value is computed as follows: max_black_pixel_value = minimum_luminance + MaxPixelThreshold *luminance_range.

For example, for a full range video with BlackPixelThreshold = 0.1, max_black_pixel_value is 0 + 0.1 * (255-0) = 25.5.

The default value of MaxPixelThreshold is 0.2, which maps to a max_black_pixel_value of 51 for a full range video. You can lower this threshold to be more strict on black levels.

MinCoveragePercentage

Type: float

The minimum percentage of pixels in a frame that need to have a luminance below the max_black_pixel_value for a frame to be considered a black frame. Luminance is calculated using the BT.709 matrix.

The default value is 99, which means at least 99% of all pixels in the frame are black pixels as per the MaxPixelThreshold set. You can reduce this value to allow more noise on the black frame.

BoundingBox

Description

Members

Height

Type: float

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

Left

Type: float

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

Top

Type: float

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

Width

Type: float

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

Celebrity

Description

Provides information about a celebrity recognized by the RecognizeCelebrities operation.

Members

Face

Type: ComparedFace structure

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

Id

Type: string

A unique identifier for the celebrity.

KnownGender

Type: KnownGender structure

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

MatchConfidence

Type: float

The confidence, in percentage, that Amazon Rekognition has that the recognized face is the celebrity.

Name

Type: string

The name of the celebrity.

Urls

Type: Array of strings

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

CelebrityDetail

Description

Information about a recognized celebrity.

Members

BoundingBox

Type: BoundingBox structure

Bounding box around the body of a celebrity.

Confidence

Type: float

The confidence, in percentage, that Amazon Rekognition has that the recognized face is the celebrity.

Face

Type: FaceDetail structure

Face details for the recognized celebrity.

Id

Type: string

The unique identifier for the celebrity.

KnownGender

Type: KnownGender structure

Retrieves the known gender for the celebrity.

Name

Type: string

The name of the celebrity.

Urls

Type: Array of strings

An array of URLs pointing to additional celebrity information.

CelebrityRecognition

Description

Information about a detected celebrity and the time the celebrity was detected in a stored video. For more information, see GetCelebrityRecognition in the Amazon Rekognition Developer Guide.

Members

Celebrity

Type: CelebrityDetail structure

Information about a recognized celebrity.

Timestamp

Type: long (int|float)

The time, in milliseconds from the start of the video, that the celebrity was recognized. Note that Timestamp is not guaranteed to be accurate to the individual frame where the celebrity first appears.

CompareFacesMatch

Description

Provides information about a face in a target image that matches the source image face analyzed by CompareFaces. The Face property contains the bounding box of the face in the target image. The Similarity property is the confidence that the source image face matches the face in the bounding box.

Members

Face

Type: ComparedFace structure

Provides face metadata (bounding box and confidence that the bounding box actually contains a face).

Similarity

Type: float

Level of confidence that the faces match.

ComparedFace

Description

Provides face metadata for target image faces that are analyzed by CompareFaces and RecognizeCelebrities.

Members

BoundingBox

Type: BoundingBox structure

Bounding box of the face.

Confidence

Type: float

Level of confidence that what the bounding box contains is a face.

Emotions

Type: Array of Emotion structures

The emotions that appear to be expressed on the face, and the confidence level in the determination. Valid values include "Happy", "Sad", "Angry", "Confused", "Disgusted", "Surprised", "Calm", "Unknown", and "Fear".

Landmarks

Type: Array of Landmark structures

An array of facial landmarks.

Pose

Type: Pose structure

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

Quality

Type: ImageQuality structure

Identifies face image brightness and sharpness.

Smile

Type: Smile structure

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

ComparedSourceImageFace

Description

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.

Members

BoundingBox

Type: BoundingBox structure

Bounding box of the face.

Confidence

Type: float

Confidence level that the selected bounding box contains a face.

ConflictException

Description

A User with the same Id already exists within the collection, or the update or deletion of the User caused an inconsistent state. **

Members

ConnectedHomeSettings

Description

Label detection settings to use on a streaming video. Defining the settings is required in the request parameter for CreateStreamProcessor. Including this setting in the CreateStreamProcessor request enables you to use the stream processor for label detection. You can then select what you want the stream processor to detect, such as people or pets. When the stream processor has started, one notification is sent for each object class specified. For example, if packages and pets are selected, one SNS notification is published the first time a package is detected and one SNS notification is published the first time a pet is detected, as well as an end-of-session summary.

Members

Labels

Required: Yes
Type: Array of strings

Specifies what you want to detect in the video, such as people, packages, or pets. The current valid labels you can include in this list are: "PERSON", "PET", "PACKAGE", and "ALL".

MinConfidence

Type: float

The minimum confidence required to label an object in the video.

ConnectedHomeSettingsForUpdate

Description

The label detection settings you want to use in your stream processor. This includes the labels you want the stream processor to detect and the minimum confidence level allowed to label objects.

Members

Labels

Type: Array of strings

Specifies what you want to detect in the video, such as people, packages, or pets. The current valid labels you can include in this list are: "PERSON", "PET", "PACKAGE", and "ALL".

MinConfidence

Type: float

The minimum confidence required to label an object in the video.

ContentModerationDetection

Description

Information about an inappropriate, unwanted, or offensive content label detection in a stored video.

Members

DurationMillis

Type: long (int|float)

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

EndTimestampMillis

Type: long (int|float)

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

ModerationLabel

Type: ModerationLabel structure

The content moderation label detected by in the stored video.

StartTimestampMillis

Type: long (int|float)

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

Timestamp

Type: long (int|float)

Time, in milliseconds from the beginning of the video, that the content moderation label was detected. Note that Timestamp is not guaranteed to be accurate to the individual frame where the moderated content first appears.

CoversBodyPart

Description

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

Members

Confidence

Type: float

The confidence that Amazon Rekognition has in the value of Value.

Value

Type: boolean

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

CreateFaceLivenessSessionRequestSettings

Description

A session settings object. It contains settings for the operation to be performed. It accepts arguments for OutputConfig and AuditImagesLimit.

Members

AuditImagesLimit

Type: int

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

OutputConfig

Type: LivenessOutputConfig structure

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

CustomLabel

Description

A custom label detected in an image by a call to DetectCustomLabels.

Members

Confidence

Type: float

The confidence that the model has in the detection of the custom label. The range is 0-100. A higher value indicates a higher confidence.

Geometry

Type: Geometry structure

The location of the detected object on the image that corresponds to the custom label. Includes an axis aligned coarse bounding box surrounding the object and a finer grain polygon for more accurate spatial information.

Name

Type: string

The name of the custom label.

DatasetChanges

Description

Describes updates or additions to a dataset. A Single update or addition is an entry (JSON Line) that provides information about a single image. To update an existing entry, you match the source-ref field of the update entry with the source-ref filed of the entry that you want to update. If the source-ref field doesn't match an existing entry, the entry is added to dataset as a new entry.

Members

GroundTruth

Required: Yes
Type: blob (string|resource|Psr\Http\Message\StreamInterface)

A Base64-encoded binary data object containing one or JSON lines that either update the dataset or are additions to the dataset. You change a dataset by calling UpdateDatasetEntries. If you are using an AWS SDK to call UpdateDatasetEntries, you don't need to encode Changes as the SDK encodes the data for you.

For example JSON lines, see Image-Level labels in manifest files and and Object localization in manifest files in the Amazon Rekognition Custom Labels Developer Guide.

DatasetDescription

Description

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

The status fields Status, StatusMessage, and StatusMessageCode reflect the last operation on the dataset.

Members

CreationTimestamp

Type: timestamp (string|DateTime or anything parsable by strtotime)

The Unix timestamp for the time and date that the dataset was created.

DatasetStats

Type: DatasetStats structure

The status message code for the dataset.

LastUpdatedTimestamp

Type: timestamp (string|DateTime or anything parsable by strtotime)

The Unix timestamp for the date and time that the dataset was last updated.

Status

Type: string

The status of the dataset.

StatusMessage

Type: string

The status message for the dataset.

StatusMessageCode

Type: string

The status message code for the dataset operation. If a service error occurs, try the API call again later. If a client error occurs, check the input parameters to the dataset API call that failed.

DatasetLabelDescription

Description

Describes a dataset label. For more information, see ListDatasetLabels.

Members

LabelName

Type: string

The name of the label.

LabelStats

Type: DatasetLabelStats structure

Statistics about the label.

DatasetLabelStats

Description

Statistics about a label used in a dataset. For more information, see DatasetLabelDescription.

Members

BoundingBoxCount

Type: int

The total number of images that have the label assigned to a bounding box.

EntryCount

Type: int

The total number of images that use the label.

DatasetMetadata

Description

Summary information for an Amazon Rekognition Custom Labels dataset. For more information, see ProjectDescription.

Members

CreationTimestamp

Type: timestamp (string|DateTime or anything parsable by strtotime)

The Unix timestamp for the date and time that the dataset was created.

DatasetArn

Type: string

The Amazon Resource Name (ARN) for the dataset.

DatasetType

Type: string

The type of the dataset.

Status

Type: string

The status for the dataset.

StatusMessage

Type: string

The status message for the dataset.

StatusMessageCode

Type: string

The status message code for the dataset operation. If a service error occurs, try the API call again later. If a client error occurs, check the input parameters to the dataset API call that failed.

DatasetSource

Description

The source that Amazon Rekognition Custom Labels uses to create a dataset. To use an Amazon Sagemaker format manifest file, specify the S3 bucket location in the GroundTruthManifest field. The S3 bucket must be in your AWS account. To create a copy of an existing dataset, specify the Amazon Resource Name (ARN) of an existing dataset in DatasetArn.

You need to specify a value for DatasetArn or GroundTruthManifest, but not both. if you supply both values, or if you don't specify any values, an InvalidParameterException exception occurs.

For more information, see CreateDataset.

Members

DatasetArn

Type: string

The ARN of an Amazon Rekognition Custom Labels dataset that you want to copy.

GroundTruthManifest

Type: GroundTruthManifest structure

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

DatasetStats

Description

Provides statistics about a dataset. For more information, see DescribeDataset.

Members

ErrorEntries

Type: int

The total number of entries that contain at least one error.

LabeledEntries

Type: int

The total number of images in the dataset that have labels.

TotalEntries

Type: int

The total number of images in the dataset.

TotalLabels

Type: int

The total number of labels declared in the dataset.

DetectLabelsImageBackground

Description

The background of the image with regard to image quality and dominant colors.

Members

DominantColors

Type: Array of DominantColor structures

The dominant colors found in the background of an image, defined with RGB values, CSS color name, simplified color name, and PixelPercentage (the percentage of image pixels that have a particular color).

Quality

Type: DetectLabelsImageQuality structure

The quality of the image background as defined by brightness and sharpness.

DetectLabelsImageForeground

Description

The foreground of the image with regard to image quality and dominant colors.

Members

DominantColors

Type: Array of DominantColor structures

The dominant colors found in the foreground of an image, defined with RGB values, CSS color name, simplified color name, and PixelPercentage (the percentage of image pixels that have a particular color).

Quality

Type: DetectLabelsImageQuality structure

The quality of the image foreground as defined by brightness and sharpness.

DetectLabelsImageProperties

Description

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

Members

Background

Type: DetectLabelsImageBackground structure

Information about the properties of an image’s background, including the background’s quality and dominant colors, including the quality and dominant colors of the image.

DominantColors

Type: Array of DominantColor structures

Information about the dominant colors found in an image, described with RGB values, CSS color name, simplified color name, and PixelPercentage (the percentage of image pixels that have a particular color).

Foreground

Type: DetectLabelsImageForeground structure

Information about the properties of an image’s foreground, including the foreground’s quality and dominant colors, including the quality and dominant colors of the image.

Quality

Type: DetectLabelsImageQuality structure

Information about the quality of the image foreground as defined by brightness, sharpness, and contrast. The higher the value the greater the brightness, sharpness, and contrast respectively.

DetectLabelsImagePropertiesSettings

Description

Settings for the IMAGE_PROPERTIES feature type.

Members

MaxDominantColors

Type: int

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

DetectLabelsImageQuality

Description

The quality of an image provided for label detection, with regard to brightness, sharpness, and contrast.

Members

Brightness

Type: float

The brightness of an image provided for label detection.

Contrast

Type: float

The contrast of an image provided for label detection.

Sharpness

Type: float

The sharpness of an image provided for label detection.

DetectLabelsSettings

Description

Settings for the DetectLabels request. Settings can include filters for both GENERAL_LABELS and IMAGE_PROPERTIES. GENERAL_LABELS filters can be inclusive or exclusive and applied to individual labels or label categories. IMAGE_PROPERTIES filters allow specification of a maximum number of dominant colors.

Members

GeneralLabels

Type: GeneralLabelsSettings structure

Contains the specified filters for GENERAL_LABELS.

ImageProperties

Type: DetectLabelsImagePropertiesSettings structure

Contains the chosen number of maximum dominant colors in an image.

DetectTextFilters

Description

A set of optional parameters that you can use to set the criteria that the text must meet to be included in your response. WordFilter looks at a word’s height, width, and minimum confidence. RegionOfInterest lets you set a specific region of the image to look for text in.

Members

RegionsOfInterest

Type: Array of RegionOfInterest structures

A Filter focusing on a certain area of the image. Uses a BoundingBox object to set the region of the image.

WordFilter

Type: DetectionFilter structure

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

DetectionFilter

Description

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

Members

MinBoundingBoxHeight

Type: float

Sets the minimum height of the word bounding box. Words with bounding box heights lesser than this value will be excluded from the result. Value is relative to the video frame height.

MinBoundingBoxWidth

Type: float

Sets the minimum width of the word bounding box. Words with bounding boxes widths lesser than this value will be excluded from the result. Value is relative to the video frame width.

MinConfidence

Type: float

Sets the confidence of word detection. Words with detection confidence below this will be excluded from the result. Values should be between 0 and 100. The default MinConfidence is 80.

DisassociatedFace

Description

Provides face metadata for the faces that are disassociated from a specific UserID.

Members

FaceId

Type: string

Unique identifier assigned to the face.

DistributeDataset

Description

A training dataset or a test dataset used in a dataset distribution operation. For more information, see DistributeDatasetEntries.

Members

Arn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the dataset that you want to use.

DominantColor

Description

A description of the dominant colors in an image.

Members

Blue

Type: int

The Blue RGB value for a dominant color.

CSSColor

Type: string

The CSS color name of a dominant color.

Green

Type: int

The Green RGB value for a dominant color.

HexCode

Type: string

The Hex code equivalent of the RGB values for a dominant color.

PixelPercent

Type: float

The percentage of image pixels that have a given dominant color.

Red

Type: int

The Red RGB value for a dominant color.

SimplifiedColor

Type: string

One of 12 simplified color names applied to a dominant color.

Emotion

Description

The emotions that appear to be expressed on the face, and the confidence level in the determination. The API is only making a determination of the physical appearance of a person's face. It is not a determination of the person’s internal emotional state and should not be used in such a way. For example, a person pretending to have a sad face might not be sad emotionally.

Members

Confidence

Type: float

Level of confidence in the determination.

Type

Type: string

Type of emotion detected.

EquipmentDetection

Description

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

Members

BoundingBox

Type: BoundingBox structure

A bounding box surrounding the item of detected PPE.

Confidence

Type: float

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

CoversBodyPart

Type: CoversBodyPart structure

Information about the body part covered by the detected PPE.

Type

Type: string

The type of detected PPE.

EvaluationResult

Description

The evaluation results for the training of a model.

Members

F1Score

Type: float

The F1 score for the evaluation of all labels. The F1 score metric evaluates the overall precision and recall performance of the model as a single value. A higher value indicates better precision and recall performance. A lower score indicates that precision, recall, or both are performing poorly.

Summary

Type: Summary structure

The S3 bucket that contains the training summary.

EyeDirection

Description

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

Members

Confidence

Type: float

The confidence that the service has in its predicted eye direction.

Pitch

Type: float

Value representing eye direction on the pitch axis.

Yaw

Type: float

Value representing eye direction on the yaw axis.

EyeOpen

Description

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

Members

Confidence

Type: float

Level of confidence in the determination.

Value

Type: boolean

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

Eyeglasses

Description

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

Members

Confidence

Type: float

Level of confidence in the determination.

Value

Type: boolean

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

Face

Description

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

Members

BoundingBox

Type: BoundingBox structure

Bounding box of the face.

Confidence

Type: float

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

ExternalImageId

Type: string

Identifier that you assign to all the faces in the input image.

FaceId

Type: string

Unique identifier that Amazon Rekognition assigns to the face.

ImageId

Type: string

Unique identifier that Amazon Rekognition assigns to the input image.

IndexFacesModelVersion

Type: string

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

UserId

Type: string

Unique identifier assigned to the user.

FaceDetail

Description

Structure containing attributes of the face that the algorithm detected.

A FaceDetail object contains either the default facial attributes or all facial attributes. The default attributes are BoundingBox, Confidence, Landmarks, Pose, and Quality.

GetFaceDetection is the only Amazon Rekognition Video stored video operation that can return a FaceDetail object with all attributes. To specify which attributes to return, use the FaceAttributes input parameter for StartFaceDetection. The following Amazon Rekognition Video operations return only the default attributes. The corresponding Start operations don't have a FaceAttributes input parameter:

GetCelebrityRecognition
GetPersonTracking
GetFaceSearch

The Amazon Rekognition Image DetectFaces and IndexFaces operations can return all facial attributes. To specify which attributes to return, use the Attributes input parameter for DetectFaces. For IndexFaces, use the DetectAttributes input parameter.

Members

AgeRange

Type: AgeRange structure

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

Beard

Type: Beard structure

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

BoundingBox

Type: BoundingBox structure

Bounding box of the face. Default attribute.

Confidence

Type: float

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

Emotions

Type: Array of Emotion structures

EyeDirection

Type: EyeDirection structure

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

Eyeglasses

Type: Eyeglasses structure

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

EyesOpen

Type: EyeOpen structure

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

FaceOccluded

Type: FaceOccluded structure

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

Gender

Type: Gender structure

The predicted gender of a detected face.

Landmarks

Type: Array of Landmark structures

Indicates the location of landmarks on the face. Default attribute.

MouthOpen

Type: MouthOpen structure

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

Mustache

Type: Mustache structure

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

Pose

Type: Pose structure

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

Quality

Type: ImageQuality structure

Identifies image brightness and sharpness. Default attribute.

Smile

Type: Smile structure

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

Sunglasses

Type: Sunglasses structure

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

FaceDetection

Description

Information about a face detected in a video analysis request and the time the face was detected in the video.

Members

Face

Type: FaceDetail structure

The face properties for the detected face.

Timestamp

Type: long (int|float)

Time, in milliseconds from the start of the video, that the face was detected. Note that Timestamp is not guaranteed to be accurate to the individual frame where the face first appears.

FaceMatch

Description

Provides face metadata. In addition, it also provides the confidence in the match of this face with the input face.

Members

Face

Type: Face structure

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

Similarity

Type: float

Confidence in the match of this face with the input face.

FaceOccluded

Description

You can use FaceOccluded to determine if an obstruction on a face negatively impacts using the image for face matching.

Members

Confidence

Type: float

The confidence that the service has detected the presence of a face occlusion.

Value

Type: boolean

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

FaceRecord

Description

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

Members

Face

Type: Face structure

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

FaceDetail

Type: FaceDetail structure

Structure containing attributes of the face that the algorithm detected.

FaceSearchSettings

Description

Input face recognition parameters for an Amazon Rekognition stream processor. Includes the collection to use for face recognition and the face attributes to detect. Defining the settings is required in the request parameter for CreateStreamProcessor.

Members

CollectionId

Type: string

The ID of a collection that contains faces that you want to search for.

FaceMatchThreshold

Type: float

Minimum face match confidence score that must be met to return a result for a recognized face. The default is 80. 0 is the lowest confidence. 100 is the highest confidence. Values between 0 and 100 are accepted, and values lower than 80 are set to 80.

Gender

Description

The predicted gender of a detected face.

Amazon Rekognition makes gender binary (male/female) predictions based on the physical appearance of a face in a particular image. This kind of prediction is not designed to categorize a person’s gender identity, and you shouldn't use Amazon Rekognition to make such a determination. For example, a male actor wearing a long-haired wig and earrings for a role might be predicted as female.

Using Amazon Rekognition to make gender binary predictions is best suited for use cases where aggregate gender distribution statistics need to be analyzed without identifying specific users. For example, the percentage of female users compared to male users on a social media platform.

We don't recommend using gender binary predictions to make decisions that impact an individual's rights, privacy, or access to services.

Members

Confidence

Type: float

Level of confidence in the prediction.

Value

Type: string

The predicted gender of the face.

GeneralLabelsSettings

Description

Contains filters for the object labels returned by DetectLabels. Filters can be inclusive, exclusive, or a combination of both and can be applied to individual labels or entire label categories. To see a list of label categories, see Detecting Labels.

Members

LabelCategoryExclusionFilters

Type: Array of strings

The label categories that should be excluded from the return from DetectLabels.

LabelCategoryInclusionFilters

Type: Array of strings

The label categories that should be included in the return from DetectLabels.

LabelExclusionFilters

Type: Array of strings

The labels that should be excluded from the return from DetectLabels.

LabelInclusionFilters

Type: Array of strings

The labels that should be included in the return from DetectLabels.

Geometry

Description

Information about where an object (DetectCustomLabels) or text (DetectText) is located on an image.

Members

BoundingBox

Type: BoundingBox structure

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

Polygon

Type: Array of Point structures

Within the bounding box, a fine-grained polygon around the detected item.

GetContentModerationRequestMetadata

Description

Contains metadata about a content moderation request, including the SortBy and AggregateBy options.

Members

AggregateBy

Type: string

The aggregation method chosen for a GetContentModeration request.

SortBy

Type: string

The sorting method chosen for a GetContentModeration request.

GetLabelDetectionRequestMetadata

Description

Contains metadata about a label detection request, including the SortBy and AggregateBy options.

Members

AggregateBy

Type: string

The aggregation method chosen for a GetLabelDetection request.

SortBy

Type: string

The sorting method chosen for a GetLabelDetection request.

GroundTruthManifest

Description

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

Members

S3Object

Type: S3Object structure

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.

HumanLoopActivationOutput

Description

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

Members

HumanLoopActivationConditionsEvaluationResults

Type: string (string|number|array|map or anything parsable by json_encode)

Shows the result of condition evaluations, including those conditions which activated a human review.

HumanLoopActivationReasons

Type: Array of strings

Shows if and why human review was needed.

HumanLoopArn

Type: string

The Amazon Resource Name (ARN) of the HumanLoop created.

HumanLoopConfig

Description

Sets up the flow definition the image will be sent to if one of the conditions is met. You can also set certain attributes of the image before review.

Members

DataAttributes

Type: HumanLoopDataAttributes structure

Sets attributes of the input data.

FlowDefinitionArn

Required: Yes
Type: string

The Amazon Resource Name (ARN) of the flow definition. You can create a flow definition by using the Amazon Sagemaker CreateFlowDefinition Operation.

HumanLoopName

Required: Yes
Type: string

The name of the human review used for this image. This should be kept unique within a region.

HumanLoopDataAttributes

Description

Allows you to set attributes of the image. Currently, you can declare an image as free of personally identifiable information.

Members

ContentClassifiers

Type: Array of strings

Sets whether the input image is free of personally identifiable information.

HumanLoopQuotaExceededException

Description

The number of in-progress human reviews you have has exceeded the number allowed.

Members

QuotaCode

Type: string

The quota code.

ResourceType

Type: string

The resource type.

ServiceCode

Type: string

The service code.

IdempotentParameterMismatchException

Description

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.

Members

Image

Description

Provides the input image either as bytes or an S3 object.

For more information, see Analyzing an Image Loaded from a Local File System in the Amazon Rekognition Developer Guide.

You pass images stored in an S3 bucket to an Amazon Rekognition API operation by using the S3Object property. Images stored in an S3 bucket do not need to be base64-encoded.

The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.

Members

Bytes

Type: blob (string|resource|Psr\Http\Message\StreamInterface)

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

Namespaces

Classes

Interfaces

Traits

Exceptions

Functions

Amazon Rekognition 2016-06-27

Operation Summary

Paginators

Waiters

Operations

AssociateFaces

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: AssociateFaces

CompareFaces

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: To compare two images

CopyProjectVersion

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: CopyProjectVersion

CreateCollection

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: To create a collection

CreateDataset

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: To create an Amazon Rekognition Custom Labels dataset

CreateFaceLivenessSession

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

CreateProject

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: To create an Amazon Rekognition Custom Labels project

CreateProjectVersion