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 */).

CompareFaces ( array $params = [] )
Compares a face in the source input image with each of the 100 largest faces detected in the target input image.
CreateCollection ( array $params = [] )
Creates a collection in an AWS Region.
CreateDataset ( array $params = [] )
Creates a new Amazon Rekognition Custom Labels dataset.
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.
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.
DeleteProjectVersion ( array $params = [] )
Deletes an Amazon Rekognition Custom Labels model.
DeleteStreamProcessor ( array $params = [] )
Deletes the stream processor identified by Name.
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.
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.
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.
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.
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.
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
ListStreamProcessors

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

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,
    ],
]

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.

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.

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.

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. You also specify the face recognition criteria in Settings. For example, the collection containing faces that 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 in ConnectedHomeSettings, such as people, packages and people, or pets, people, and packages. 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. 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.

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.

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>', ...],
]

Result Details

Members

DeletedFaces

Type: Array of strings

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

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.

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',
]

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.

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.

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>',
]

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.

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.

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>',
                ],
            ],
            'MinInferenceUnits' => <integer>,
            'OutputConfig' => [
                'S3Bucket' => '<string>',
                'S3KeyPrefix' => '<string>',
            ],
            'ProjectVersionArn' => '<string>',
            'Status' => 'TRAINING_IN_PROGRESS|TRAINING_COMPLETED|TRAINING_FAILED|STARTING|RUNNING|FAILED|STOPPING|STOPPED|DELETING',
            '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.

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.

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.

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), presence of beard, sunglasses, 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. This can be the default list of attributes or all attributes. If you don't specify a value for Attributes or if you specify ["DEFAULT"], the API returns the following subset of facial attributes: BoundingBox, Confidence, Pose, Quality, and Landmarks. If you provide ["ALL"], all facial attributes are returned, but the operation takes longer to complete.

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

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',
                ],
                // ...
            ],
            'Eyeglasses' => [
                'Confidence' => <float>,
                'Value' => true || false,
            ],
            'EyesOpen' => [
                '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.

DetectLabels does not support the detection of activities. However, activity detection is supported for label detection in videos. For more information, see StartLabelDetection in the Amazon Rekognition Developer Guide.

For each object, scene, and concept the API returns one or more labels. Each label provides the object name, and the level of confidence that the image contains the object. For example, suppose the input image has a lighthouse, the sea, and a rock. The response includes all three labels, one for each object.

{Name: lighthouse, Confidence: 98.4629}

{Name: rock,Confidence: 79.2097}

{Name: sea,Confidence: 75.061}

In the preceding example, the operation returns one label for each of the three objects. The operation can also return multiple labels for the same object in the image. 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.

In response, the API returns an array of labels. In addition, the response also includes the orientation correction. Optionally, 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.

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

DetectLabels returns bounding boxes for instances of common object labels in an array of Instance objects. An Instance object contains a BoundingBox object, for the location of the label on the image. It also includes the confidence by which the bounding box was detected.

DetectLabels also 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 returns the entire list of ancestors for a label. Each ancestor is a unique label in the response. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.

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

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

Parameter Syntax

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

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 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.

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.

Result Syntax

[
    'LabelModelVersion' => '<string>',
    'Labels' => [
        [
            'Confidence' => <float>,
            'Instances' => [
                [
                    'BoundingBox' => [
                        'Height' => <float>,
                        'Left' => <float>,
                        'Top' => <float>,
                        'Width' => <float>,
                    ],
                    'Confidence' => <float>,
                ],
                // ...
            ],
            'Name' => '<string>',
            'Parents' => [
                [
                    'Name' => '<string>',
                ],
                // ...
            ],
        ],
        // ...
    ],
    'OrientationCorrection' => 'ROTATE_0|ROTATE_90|ROTATE_180|ROTATE_270',
]

Result Details

Members

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.

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.

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',
                        ],
                        // ...
                    ],
                    'Eyeglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'EyesOpen' => [
                        '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>,
        ],
        // ...
    ],
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'NextToken' => '<string>',
    'StatusMessage' => '<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.

JobStatus

Type: string

The current status of the celebrity recognition job.

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.

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([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'NAME|TIMESTAMP',
]);

Parameter Details

Members

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

[
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'ModerationLabels' => [
        [
            'ModerationLabel' => [
                'Confidence' => <float>,
                'Name' => '<string>',
                'ParentName' => '<string>',
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'ModerationModelVersion' => '<string>',
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobStatus

Type: string

The current status of the content moderation analysis job.

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.

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.

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',
                    ],
                    // ...
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    '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>,
        ],
        // ...
    ],
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'NextToken' => '<string>',
    'StatusMessage' => '<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.

JobStatus

Type: string

The current status of the face detection job.

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.

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.

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

[
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'NextToken' => '<string>',
    'Persons' => [
        [
            'FaceMatches' => [
                [
                    'Face' => [
                        'BoundingBox' => [
                            'Height' => <float>,
                            'Left' => <float>,
                            'Top' => <float>,
                            'Width' => <float>,
                        ],
                        'Confidence' => <float>,
                        'ExternalImageId' => '<string>',
                        'FaceId' => '<string>',
                        'ImageId' => '<string>',
                        'IndexFacesModelVersion' => '<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',
                        ],
                        // ...
                    ],
                    'Eyeglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'EyesOpen' => [
                        '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>',
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobStatus

Type: string

The current status of the face search job.

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.

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.

The labels returned include the label name, the percentage confidence in the accuracy of the detected label, and the time the label was detected in the video.

The returned labels also include bounding box information for common objects, a hierarchical taxonomy of detected labels, and the version of the label model used for detection.

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([
    'JobId' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'SortBy' => 'NAME|TIMESTAMP',
]);

Parameter Details

Members

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

[
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    'LabelModelVersion' => '<string>',
    'Labels' => [
        [
            'Label' => [
                'Confidence' => <float>,
                'Instances' => [
                    [
                        'BoundingBox' => [
                            'Height' => <float>,
                            'Left' => <float>,
                            'Top' => <float>,
                            'Width' => <float>,
                        ],
                        'Confidence' => <float>,
                    ],
                    // ...
                ],
                'Name' => '<string>',
                'Parents' => [
                    [
                        'Name' => '<string>',
                    ],
                    // ...
                ],
            ],
            'Timestamp' => <integer>,
        ],
        // ...
    ],
    'NextToken' => '<string>',
    'StatusMessage' => '<string>',
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobStatus

Type: string

The current status of the label detection job.

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.

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

[
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    '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',
                        ],
                        // ...
                    ],
                    'Eyeglasses' => [
                        'Confidence' => <float>,
                        'Value' => true || false,
                    ],
                    'EyesOpen' => [
                        '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>',
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobStatus

Type: string

The current status of the person tracking job.

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.

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>,
        ],
        // ...
    ],
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    '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>',
    '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.

JobStatus

Type: string

Current status of the segment detection job.

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.

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 50 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

[
    'JobStatus' => 'IN_PROGRESS|SUCCEEDED|FAILED',
    '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>',
    'VideoMetadata' => [
        'Codec' => '<string>',
        'ColorRange' => 'FULL|LIMITED',
        'DurationMillis' => <integer>,
        'Format' => '<string>',
        'FrameHeight' => <integer>,
        'FrameRate' => <float>,
        'FrameWidth' => <integer>,
    ],
]

Result Details

Members

JobStatus

Type: string

Current status of the text detection job.

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.

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 facial attributes (by using the detectionAttributes parameter), Amazon Rekognition returns detailed facial attributes, such as facial landmarks (for example, location of eye and mouth) 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 that you want to be returned. This can be the default list of attributes or all attributes. If you don't specify a value for Attributes or if you specify ["DEFAULT"], the API returns the following subset of facial attributes: BoundingBox, Confidence, Pose, Quality, and Landmarks. If you provide ["ALL"], all facial attributes are returned, but the operation takes longer to complete.

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

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>',
            ],
            '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',
                    ],
                    // ...
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    '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',
                    ],
                    // ...
                ],
                'Eyeglasses' => [
                    'Confidence' => <float>,
                    'Value' => true || false,
                ],
                'EyesOpen' => [
                    '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.

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.

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
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members

CollectionId

Required: Yes
Type: string

ID of the collection from which to list the faces.

MaxResults

Type: int

Maximum number of faces to return.

NextToken

Type: string

Result Syntax

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

[
    'Faces' => [
        [
            'BoundingBox' => [
                'Height' => 0.18000000715256,
                'Left' => 0.55555599927902,
                'Top' => 0.33666700124741,
                'Width' => 0.23999999463558,
            ],
            'Confidence' => 100,
            'FaceId' => '1c62e8b5-69a7-5b7d-b3cd-db4338a8a7e7',
            'ImageId' => '147fdf82-7a71-52cf-819b-e786c7b9746e',
        ],
        [
            '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',
        ],
        [
            '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',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.035555601119995,
                'Left' => 0.37388700246811,
                'Top' => 0.24777799844742,
                'Width' => 0.047477699816227,
            ],
            'Confidence' => 99.99210357666,
            'FaceId' => '3b01bef0-c883-5654-ba42-d5ad28b720b3',
            'ImageId' => '812d9f04-86f9-54fc-9275-8d0dcbcb6784',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.053333301097155,
                'Left' => 0.29376900196075,
                'Top' => 0.35666701197624,
                'Width' => 0.071216598153114,
            ],
            'Confidence' => 99.999198913574,
            'FaceId' => '4839a608-49d0-566c-8301-509d71b534d1',
            'ImageId' => '812d9f04-86f9-54fc-9275-8d0dcbcb6784',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.32492598891258,
                'Left' => 0.51555597782135,
                'Top' => 0.15133500099182,
                'Width' => 0.24333299696445,
            ],
            'Confidence' => 99.999496459961,
            'FaceId' => '70008e50-75e4-55d0-8e80-363fb73b3a14',
            'ImageId' => 'd5631190-d039-54e4-b267-abd22c8647c5',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.037777800112963,
                'Left' => 0.70029699802399,
                'Top' => 0.18777799606323,
                'Width' => 0.050445098429918,
            ],
            'Confidence' => 99.926399230957,
            'FaceId' => '7f5f88ed-d684-5a88-b0df-01e4a521552b',
            'ImageId' => '812d9f04-86f9-54fc-9275-8d0dcbcb6784',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.05555560067296,
                'Left' => 0.1394660025835,
                'Top' => 0.46333301067352,
                'Width' => 0.072700299322605,
            ],
            'Confidence' => 99.994697570801,
            'FaceId' => '895b4e2c-81de-5902-a4bd-d1792bda00b2',
            'ImageId' => '812d9f04-86f9-54fc-9275-8d0dcbcb6784',
        ],
        [
            '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',
        ],
        [
            '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',
        ],
        [
            'BoundingBox' => [
                'Height' => 0.33481499552727,
                'Left' => 0.31888899207115,
                'Top' => 0.49333301186562,
                'Width' => 0.25,
            ],
            'Confidence' => 99.999099731445,
            'FaceId' => 'ff43d742-0c13-5d16-a3e8-03d3f58e980b',
            'ImageId' => '465f4e93-763e-51d0-b030-b9667a2d94b1',
        ],
    ],
]

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.

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>',
            ],
            '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>',
            ],
            '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,
]

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.

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.

Parameter Syntax

$result = $client->startLabelDetection([
    '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 StartLabelDetection 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 Video must have in order to return a detected label. Confidence represents how certain Amazon Rekognition is that a label is correctly identified.0 is the lowest confidence. 100 is the highest confidence. Amazon Rekognition Video doesn't return any labels with a confidence level lower than this specified value.

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

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.

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.

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

Parameter Syntax

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

Parameter Details

Members

MinInferenceUnits

Required: Yes
Type: int

The minimum number of inference units to use. A single inference unit represents 1 hour of processing and can support up to 5 Transaction Pers Second (TPS). 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',
]

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.

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

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.

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. For more information, 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.

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',
]

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.

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.

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.

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.

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.

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

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.

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.

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.

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

ModerationLabel

Type: ModerationLabel structure

The content moderation label detected by in the stored video.

Timestamp

Type: long (int|float)

Time, in milliseconds from the beginning of the video, that the content moderation label was detected.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

S3Object

Type: S3Object structure

Identifies an S3 object as the image source.

ImageQuality

Description

Identifies face image brightness and sharpness.

Members

Brightness

Type: float

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

Sharpness

Type: float

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

ImageTooLargeException

Description

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.

Members

Instance

Description

An instance of a label returned by Amazon Rekognition Image (DetectLabels) or by Amazon Rekognition Video (GetLabelDetection).

Members

BoundingBox

Type: BoundingBox structure

The position of the label instance on the image.

Confidence

Type: float

The confidence that Amazon Rekognition has in the accuracy of the bounding box.

InternalServerError

Description

Amazon Rekognition experienced a service issue. Try your call again.

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InvalidImageFormatException

Description

The provided image format is not supported.

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InvalidPaginationTokenException

Description

Pagination token in the request is not valid.

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InvalidParameterException

Description

Input parameter violated a constraint. Validate your parameter before calling the API operation again.

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InvalidS3ObjectException

Description

Amazon Rekognition is unable to access the S3 object specified in the request.

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KinesisDataStream

Description

The Kinesis data stream Amazon Rekognition to which the analysis results of a Amazon Rekognition stream processor are streamed. For more information, see CreateStreamProcessor in the Amazon Rekognition Developer Guide.

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Arn

Type: string

ARN of the output Amazon Kinesis Data Streams stream.

KinesisVideoStream

Description

Kinesis video stream stream that provides the source streaming video for a Amazon Rekognition Video stream processor. For more information, see CreateStreamProcessor in the Amazon Rekognition Developer Guide.

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Arn

Type: string

ARN of the Kinesis video stream stream that streams the source video.

KinesisVideoStreamStartSelector

Description

Specifies the starting point in a Kinesis stream to start processing. You can use the producer timestamp or the fragment number. For more information, see Fragment.

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FragmentNumber

Type: string

The unique identifier of the fragment. This value monotonically increases based on the ingestion order.

ProducerTimestamp

Type: long (int|float)

The timestamp from the producer corresponding to the fragment.

KnownGender

Description

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

Members

Type

Type: string

A string value of the KnownGender info about the Celebrity.

Label

Description

Structure containing details about the detected label, including the name, detected instances, parent labels, and level of confidence.

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Confidence

Type: float

Level of confidence.

Instances

Type: Array of Instance structures

If Label represents an object, Instances contains the bounding boxes for each instance of the detected object. Bounding boxes are returned for common object labels such as people, cars, furniture, apparel or pets.

Name

Type: string

The name (label) of the object or scene.

Parents

Type: Array of Parent structures

The parent labels for a label. The response includes all ancestor labels.

LabelDetection

Description

Information about a label detected in a video analysis request and the time the label was detected in the video.

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Label

Type: Label structure

Details about the detected label.

Timestamp

Type: long (int|float)

Time, in milliseconds from the start of the video, that the label was detected.

Landmark

Description

Indicates the location of the landmark on the face.

Members

Type

Type: string

Type of landmark.

X

Type: float

The x-coordinate of the landmark expressed as a ratio of the width of the image. The x-coordinate is measured from the left-side of the image. For example, if the image is 700 pixels wide and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.

Y

Type: float

The y-coordinate of the landmark expressed as a ratio of the height of the image. The y-coordinate is measured from the top of the image. For example, if the image height is 200 pixels and the y-coordinate of the landmark is at 50 pixels, this value is 0.25.

LimitExceededException

Description

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.

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ModerationLabel

Description

Provides information about a single type of inappropriate, unwanted, or offensive content found in an image or video. Each type of moderated content has a label within a hierarchical taxonomy. For more information, see Content moderation in the Amazon Rekognition Developer Guide.

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Confidence

Type: float

Specifies the confidence that Amazon Rekognition has that the label has been correctly identified.

If you don't specify the MinConfidence parameter in the call to DetectModerationLabels, the operation returns labels with a confidence value greater than or equal to 50 percent.

Name

Type: string

The label name for the type of unsafe content detected in the image.

ParentName

Type: string

The name for the parent label. Labels at the top level of the hierarchy have the parent label "".

MouthOpen

Description

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

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Confidence

Type: float

Level of confidence in the determination.

Value

Type: boolean

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

Mustache

Description

Indicates whether or not the face has a mustache, 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 mustache or not.

NotificationChannel

Description

Members

RoleArn

Required: Yes
Type: string

The ARN of an IAM role that gives Amazon Rekognition publishing permissions to the Amazon SNS topic.

SNSTopicArn

Required: Yes
Type: string

The Amazon SNS topic to which Amazon Rekognition posts the completion status.

OutputConfig

Description

The S3 bucket and folder location where training output is placed.

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S3Bucket

Type: string

The S3 bucket where training output is placed.

S3KeyPrefix

Type: string

The prefix applied to the training output files.

Parent

Description

A parent label for a label. A label can have 0, 1, or more parents.

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Name

Type: string

The name of the parent label.

PersonDetail

Description

Details about a person detected in a video analysis request.

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BoundingBox

Type: BoundingBox structure

Bounding box around the detected person.

Face

Type: FaceDetail structure

Face details for the detected person.

Index

Type: long (int|float)

Identifier for the person detected person within a video. Use to keep track of the person throughout the video. The identifier is not stored by Amazon Rekognition.

PersonDetection

Description

Details and path tracking information for a single time a person's path is tracked in a video. Amazon Rekognition operations that track people's paths return an array of PersonDetection objects with elements for each time a person's path is tracked in a video.

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

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Person

Type: PersonDetail structure

Details about a person whose path was tracked in a video.

Timestamp

Type: long (int|float)

The time, in milliseconds from the start of the video, that the person's path was tracked.

PersonMatch

Description

Information about a person whose face matches a face(s) in an Amazon Rekognition collection. Includes information about the faces in the Amazon Rekognition collection (FaceMatch), information about the person (PersonDetail), and the time stamp for when the person was detected in a video. An array of PersonMatch objects is returned by GetFaceSearch.

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FaceMatches

Type: Array of FaceMatch structures

Information about the faces in the input collection that match the face of a person in the video.

Person

Type: PersonDetail structure

Information about the matched person.

Timestamp

Type: long (int|float)

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

Point

Description

The X and Y coordinates of a point on an image or video frame. The X and Y values are ratios of the overall image size or video resolution. For example, if an input image is 700x200 and the values are X=0.5 and Y=0.25, then the point is at the (350,50) pixel coordinate on the image.

An array of Point objects makes up a Polygon. A Polygon is returned by DetectText and by DetectCustomLabels Polygon represents a fine-grained polygon around a detected item. For more information, see Geometry in the Amazon Rekognition Developer Guide.

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X

Type: float

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

Y

Type: float

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

Pose

Description

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

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Pitch

Type: float

Value representing the face rotation on the pitch axis.

Roll

Type: float

Value representing the face rotation on the roll axis.

Yaw

Type: float

Value representing the face rotation on the yaw axis.

ProjectDescription

Description

A description of an Amazon Rekognition Custom Labels project. For more information, see DescribeProjects.

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CreationTimestamp

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

The Unix timestamp for the date and time that the project was created.

Datasets

Type: Array of DatasetMetadata structures

Information about the training and test datasets in the project.

ProjectArn

Type: string

The Amazon Resource Name (ARN) of the project.

Status

Type: string

The current status of the project.

ProjectVersionDescription

Description

A description of a version of an Amazon Rekognition Custom Labels model.

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BillableTrainingTimeInSeconds

Type: long (int|float)

The duration, in seconds, that you were billed for a successful training of the model version. This value is only returned if the model version has been successfully trained.

CreationTimestamp

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

The Unix datetime for the date and time that training started.

EvaluationResult

Type: EvaluationResult structure

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

KmsKeyId

Type: string

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

ManifestSummary

Type: GroundTruthManifest structure

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

MinInferenceUnits

Type: int

The minimum number of inference units used by the model. For more information, see StartProjectVersion.

OutputConfig

Type: OutputConfig structure

The location where training results are saved.

ProjectVersionArn

Type: string

The Amazon Resource Name (ARN) of the model version.

Status

Type: string

The current status of the model version.

StatusMessage

Type: string

A descriptive message for an error or warning that occurred.

TestingDataResult

Type: TestingDataResult structure

Contains information about the testing results.

TrainingDataResult

Type: TrainingDataResult structure

Contains information about the training results.

TrainingEndTimestamp

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

The Unix date and time that training of the model ended.

ProtectiveEquipmentBodyPart

Description

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

Members

Confidence

Type: float

The confidence that Amazon Rekognition has in the detection accuracy of the detected body part.

EquipmentDetections

Type: Array of EquipmentDetection structures

An array of Personal Protective Equipment items detected around a body part.

Name

Type: string

The detected body part.

ProtectiveEquipmentPerson

Description

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

Members

BodyParts

Type: Array of ProtectiveEquipmentBodyPart structures

An array of body parts detected on a person's body (including body parts without PPE).

BoundingBox

Type: BoundingBox structure

A bounding box around the detected person.

Confidence

Type: float

The confidence that Amazon Rekognition has that the bounding box contains a person.

Id

Type: int

The identifier for the detected person. The identifier is only unique for a single call to DetectProtectiveEquipment.

ProtectiveEquipmentSummarizationAttributes

Description

Specifies summary attributes to return from a call to DetectProtectiveEquipment. You can specify which types of PPE to summarize. You can also specify a minimum confidence value for detections. Summary information is returned in the Summary (ProtectiveEquipmentSummary) field of the response from DetectProtectiveEquipment. The summary includes which persons in an image were detected wearing the requested types of person protective equipment (PPE), which persons were detected as not wearing PPE, and the persons in which a determination could not be made. For more information, see ProtectiveEquipmentSummary.

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MinConfidence

Required: Yes
Type: float

The minimum confidence level for which you want summary information. The confidence level applies to person detection, body part detection, equipment detection, and body part coverage. Amazon Rekognition doesn't return summary information with a confidence than this specified value. There isn't a default value.

Specify a MinConfidence value that is between 50-100% as DetectProtectiveEquipment returns predictions only where the detection confidence is between 50% - 100%. If you specify a value that is less than 50%, the results are the same specifying a value of 50%.

RequiredEquipmentTypes

Required: Yes
Type: Array of strings

An array of personal protective equipment types for which you want summary information. If a person is detected wearing a required requipment type, the person's ID is added to the PersonsWithRequiredEquipment array field returned in ProtectiveEquipmentSummary by DetectProtectiveEquipment.

ProtectiveEquipmentSummary

Description

Summary information for required items of personal protective equipment (PPE) detected on persons by a call to DetectProtectiveEquipment. You specify the required type of PPE in the SummarizationAttributes (ProtectiveEquipmentSummarizationAttributes) input parameter. The summary includes which persons were detected wearing the required personal protective equipment (PersonsWithRequiredEquipment), which persons were detected as not wearing the required PPE (PersonsWithoutRequiredEquipment), and the persons in which a determination could not be made (PersonsIndeterminate).

To get a total for each category, use the size of the field array. For example, to find out how many people were detected as wearing the specified PPE, use the size of the PersonsWithRequiredEquipment array. If you want to find out more about a person, such as the location (BoundingBox) of the person on the image, use the person ID in each array element. Each person ID matches the ID field of a ProtectiveEquipmentPerson object returned in the Persons array by DetectProtectiveEquipment.

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PersonsIndeterminate

Type: Array of ints

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

PersonsWithRequiredEquipment

Type: Array of ints

An array of IDs for persons who are wearing detected personal protective equipment.

PersonsWithoutRequiredEquipment

Type: Array of ints

An array of IDs for persons who are not wearing all of the types of PPE specified in the RequiredEquipmentTypes field of the detected personal protective equipment.

ProvisionedThroughputExceededException

Description

The number of requests exceeded your throughput limit. If you want to increase this limit, contact Amazon Rekognition.

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RegionOfInterest

Description

Specifies a location within the frame that Rekognition checks for objects of interest such as text, labels, or faces. It uses a BoundingBox or object or Polygon to set a region of the screen.

A word, face, or label is included in the region if it is more than half in that region. If there is more than one region, the word, face, or label is compared with all regions of the screen. Any object of interest that is more than half in a region is kept in the results.

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BoundingBox

Type: BoundingBox structure

The box representing a region of interest on screen.

Polygon

Type: Array of Point structures

Specifies a shape made up of up to 10 Point objects to define a region of interest.

ResourceAlreadyExistsException

Description

A resource with the specified ID already exists.

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ResourceInUseException

Description

The specified resource is already being used.

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ResourceNotFoundException

Description

The resource specified in the request cannot be found.

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ResourceNotReadyException

Description

The requested resource isn't ready. For example, this exception occurs when you call DetectCustomLabels with a model version that isn't deployed.

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S3Destination

Description

The Amazon S3 bucket location to which Amazon Rekognition publishes the detailed inference results of a video analysis operation. These results include the name of the stream processor resource, the session ID of the stream processing session, and labeled timestamps and bounding boxes for detected labels.

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Bucket

Type: string

The name of the Amazon S3 bucket you want to associate with the streaming video project. You must be the owner of the Amazon S3 bucket.

KeyPrefix

Type: string

The prefix value of the location within the bucket that you want the information to be published to. For more information, see Using prefixes.

S3Object

Description

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.

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Bucket

Type: string

Name of the S3 bucket.

Name

Type: string

S3 object key name.

Version

Type: string

If the bucket is versioning enabled, you can specify the object version.

SegmentDetection

Description

A technical cue or shot detection segment detected in a video. An array of SegmentDetection objects containing all segments detected in a stored video is returned by GetSegmentDetection.

Members

DurationFrames

Type: long (int|float)

The duration of a video segment, expressed in frames.

DurationMillis

Type: long (int|float)

The duration of the detected segment in milliseconds.

DurationSMPTE

Type: string

The duration of the timecode for the detected segment in SMPTE format.

EndFrameNumber

Type: long (int|float)

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

EndTimecodeSMPTE

Type: string

The frame-accurate SMPTE timecode, from the start of a video, for the end of a detected segment. EndTimecode is in HH:MM:SS:fr format (and ;fr for drop frame-rates).

EndTimestampMillis

Type: long (int|float)

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

ShotSegment

Type: ShotSegment structure

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

StartFrameNumber

Type: long (int|float)

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

StartTimecodeSMPTE

Type: string

The frame-accurate SMPTE timecode, from the start of a video, for the start of a detected segment. StartTimecode is in HH:MM:SS:fr format (and ;fr for drop frame-rates).

StartTimestampMillis

Type: long (int|float)

The start time of the detected segment in milliseconds from the start of the video. This value is rounded down. For example, if the actual timestamp is 100.6667 milliseconds, Amazon Rekognition Video returns a value of 100 millis.

TechnicalCueSegment

Type: TechnicalCueSegment structure

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

Type

Type: string

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

SegmentTypeInfo

Description

Information about the type of a segment requested in a call to StartSegmentDetection. An array of SegmentTypeInfo objects is returned by the response from GetSegmentDetection.

Members

ModelVersion

Type: string

The version of the model used to detect segments.

Type

Type: string

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

ServiceQuotaExceededException

Description

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.

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ShotSegment

Description

Information about a shot detection segment detected in a video. For more information, see SegmentDetection.

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Confidence

Type: float

The confidence that Amazon Rekognition Video has in the accuracy of the detected segment.

Index

Type: long (int|float)

An Identifier for a shot detection segment detected in a video.

Smile

Description

Indicates whether or not the face is smiling, 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 smiling or not.

StartSegmentDetectionFilters

Description

Filters applied to the technical cue or shot detection segments. For more information, see StartSegmentDetection.

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ShotFilter

Type: StartShotDetectionFilter structure

Filters that are specific to shot detections.

TechnicalCueFilter

Type: StartTechnicalCueDetectionFilter structure

Filters that are specific to technical cues.

StartShotDetectionFilter

Description

Filters for the shot detection segments returned by GetSegmentDetection. For more information, see StartSegmentDetectionFilters.

Members

MinSegmentConfidence

Type: float

Specifies the minimum confidence that Amazon Rekognition Video must have in order to return a detected segment. Confidence represents how certain Amazon Rekognition is that a segment is correctly identified. 0 is the lowest confidence. 100 is the highest confidence. Amazon Rekognition Video doesn't return any segments with a confidence level lower than this specified value.

If you don't specify MinSegmentConfidence, the GetSegmentDetection returns segments with confidence values greater than or equal to 50 percent.

StartTechnicalCueDetectionFilter

Description

Filters for the technical segments returned by GetSegmentDetection. For more information, see StartSegmentDetectionFilters.

Members

BlackFrame

Type: BlackFrame structure

A filter that allows you to control the black frame detection by specifying the black levels and pixel coverage of black pixels in a frame. Videos can come from multiple sources, formats, and time periods, with different standards and varying noise levels for black frames that need to be accounted for.

MinSegmentConfidence

Type: float

If you don't specify MinSegmentConfidence, GetSegmentDetection returns segments with confidence values greater than or equal to 50 percent.

StartTextDetectionFilters

Description

Set of optional parameters that let you set the criteria text must meet to be included in your response. WordFilter looks at a word's height, width and minimum confidence. RegionOfInterest lets you set a specific region of the screen to look for text in.

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RegionsOfInterest

Type: Array of RegionOfInterest structures

Filter focusing on a certain area of the frame. Uses a BoundingBox object to set the region of the screen.

WordFilter

Type: DetectionFilter structure

Filters focusing on qualities of the text, such as confidence or size.

StreamProcessingStartSelector

Description

Members

KVSStreamStartSelector

Type: KinesisVideoStreamStartSelector structure

Specifies the starting point in the stream to start processing. This can be done with a timestamp or a fragment number in a Kinesis stream.

StreamProcessingStopSelector

Description

Specifies when to stop processing the stream. You can specify a maximum amount of time to process the video.

Members

MaxDurationInSeconds

Type: long (int|float)

Specifies the maximum amount of time in seconds that you want the stream to be processed. The largest amount of time is 2 minutes. The default is 10 seconds.

StreamProcessor

Description

An object that recognizes faces or labels in a streaming video. An Amazon Rekognition stream processor is created by a call to CreateStreamProcessor. The request parameters for CreateStreamProcessor describe the Kinesis video stream source for the streaming video, face recognition parameters, and where to stream the analysis resullts.

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Name

Type: string

Name of the Amazon Rekognition stream processor.

Status

Type: string

Current status of the Amazon Rekognition stream processor.

StreamProcessorDataSharingPreference

Description

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

Members

OptIn

Required: Yes
Type: boolean

If this option is set to true, you choose to share data with Rekognition to improve model performance.

StreamProcessorInput

Description

Information about the source streaming video.

Members

KinesisVideoStream

Type: KinesisVideoStream structure

The Kinesis video stream input stream for the source streaming video.

StreamProcessorNotificationChannel

Description

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.

Members

SNSTopicArn

Required: Yes
Type: string

The Amazon Resource Number (ARN) of the Amazon Amazon Simple Notification Service topic to which Amazon Rekognition posts the completion status.

StreamProcessorOutput

Description

Information about the Amazon Kinesis Data Streams stream to which a Amazon Rekognition Video stream processor streams the results of a video analysis. For more information, see CreateStreamProcessor in the Amazon Rekognition Developer Guide.

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KinesisDataStream

Type: KinesisDataStream structure

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

S3Destination

Type: S3Destination structure

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

StreamProcessorSettings

Description

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

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ConnectedHome

Type: ConnectedHomeSettings structure

FaceSearch

Type: FaceSearchSettings structure

Face search settings to use on a streaming video.

StreamProcessorSettingsForUpdate

Description

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

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ConnectedHomeForUpdate

Type: ConnectedHomeSettingsForUpdate structure

The label detection settings you want to use for your stream processor.

Summary

Description

The S3 bucket that contains the training summary. The training summary includes aggregated evaluation metrics for the entire testing dataset and metrics for each individual label.

You get the training summary S3 bucket location by calling DescribeProjectVersions.

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.

Sunglasses

Description

Indicates whether or not the face is wearing sunglasses, 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 sunglasses or not.

TechnicalCueSegment

Description

Information about a technical cue segment. For more information, see SegmentDetection.

Members

Confidence

Type: float

The confidence that Amazon Rekognition Video has in the accuracy of the detected segment.

Type

Type: string

The type of the technical cue.

TestingData

Description

The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition Custom Labels uses the training dataset to create a test dataset with a temporary split of the training dataset.

Members

Assets

Type: Array of Asset structures

The assets used for testing.

AutoCreate

Type: boolean

If specified, Amazon Rekognition Custom Labels temporarily splits the training dataset (80%) to create a test dataset (20%) for the training job. After training completes, the test dataset is not stored and the training dataset reverts to its previous size.

TestingDataResult

Description

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

Members

Input

Type: TestingData structure

The testing dataset that was supplied for training.

Output

Type: TestingData structure

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

Validation

Type: ValidationData structure

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

TextDetection

Description

Information about a word or line of text detected by DetectText.

The DetectedText field contains the text that Amazon Rekognition detected in the image.

Every word and line has an identifier (Id). Each word belongs to a line and has a parent identifier (ParentId) that identifies the line of text in which the word appears. The word Id is also an index for the word within a line of words.

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

Members

Confidence

Type: float

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

DetectedText

Type: string

The word or line of text recognized by Amazon Rekognition.

Geometry

Type: Geometry structure

The location of the detected text on the image. Includes an axis aligned coarse bounding box surrounding the text and a finer grain polygon for more accurate spatial information.

Id

Type: int

The identifier for the detected text. The identifier is only unique for a single call to DetectText.

ParentId

Type: int

The Parent identifier for the detected text identified by the value of ID. If the type of detected text is LINE, the value of ParentId is Null.

Type

Type: string

The type of text that was detected.

TextDetectionResult

Description

Information about text detected in a video. Incudes the detected text, the time in milliseconds from the start of the video that the text was detected, and where it was detected on the screen.

Members

TextDetection

Type: TextDetection structure

Details about text detected in a video.

Timestamp

Type: long (int|float)

The time, in milliseconds from the start of the video, that the text was detected.

ThrottlingException

Description

Amazon Rekognition is temporarily unable to process the request. Try your call again.

Members

TrainingData

Description

The dataset used for training.

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Assets

Type: Array of Asset structures

A Sagemaker GroundTruth manifest file that contains the training images (assets).

TrainingDataResult

Description

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

Members

Input

Type: TrainingData structure

The training assets that you supplied for training.

Output

Type: TrainingData structure

The images (assets) that were actually trained by Amazon Rekognition Custom Labels.

Validation

Type: ValidationData structure

The location of the data validation manifest. The data validation manifest is created for the training dataset during model training.

UnindexedFace

Description

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

Members

FaceDetail

Type: FaceDetail structure

The structure that contains attributes of a face that IndexFacesdetected, but didn't index.

Reasons

Type: Array of strings

An array of reasons that specify why a face wasn't indexed.

EXTREME_POSE - The face is at a pose that can't be detected. For example, the head is turned too far away from the camera.
EXCEEDS_MAX_FACES - The number of faces detected is already higher than that specified by the MaxFaces input parameter for IndexFaces.
LOW_BRIGHTNESS - The image is too dark.
LOW_SHARPNESS - The image is too blurry.
LOW_CONFIDENCE - The face was detected with a low confidence.
SMALL_BOUNDING_BOX - The bounding box around the face is too small.

ValidationData

Description

Contains the Amazon S3 bucket location of the validation data for a model training job.

The validation data includes error information for individual JSON Lines in the dataset. For more information, see Debugging a Failed Model Training in the Amazon Rekognition Custom Labels Developer Guide.

You get the ValidationData object for the training dataset (TrainingDataResult) and the test dataset (TestingDataResult) by calling DescribeProjectVersions.

The assets array contains a single Asset object. The GroundTruthManifest field of the Asset object contains the S3 bucket location of the validation data.

Members

Assets

Type: Array of Asset structures

The assets that comprise the validation data.

Video

Description

Members

S3Object

Type: S3Object structure

The Amazon S3 bucket name and file name for the video.

VideoMetadata

Description

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

Members

Codec

Type: string

Type of compression used in the analyzed video.

ColorRange

Type: string

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

DurationMillis

Type: long (int|float)

Length of the video in milliseconds.

Format

Type: string

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

FrameHeight

Type: long (int|float)

Vertical pixel dimension of the video.

FrameRate

Type: float

Number of frames per second in the video.

FrameWidth

Type: long (int|float)

Horizontal pixel dimension of the video.

VideoTooLargeException

Description

The file size or duration of the supplied media is too large. The maximum file size is 10GB. The maximum duration is 6 hours.

Namespaces

Classes

Interfaces

Traits

Exceptions

Functions

Amazon Rekognition 2016-06-27

Operation Summary

Paginators

Waiters

Operations

CompareFaces

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

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Errors

Examples

Example 1: To compare two images

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

CreateProject

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

CreateProjectVersion

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

CreateStreamProcessor

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

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Errors

DeleteCollection

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Members

Errors

Examples

Example 1: To delete a collection

DeleteDataset

Parameter Syntax

Parameter Details

Members

Result Syntax

Result Details

Errors