NAME
Paws::Rekognition - Perl Interface to AWS Amazon Rekognition
SYNOPSIS
use Paws;
my $obj = Paws->service('Rekognition');
my $res = $obj->Method(
Arg1 => $val1,
Arg2 => [ 'V1', 'V2' ],
# if Arg3 is an object, the HashRef will be used as arguments to the constructor
# of the arguments type
Arg3 => { Att1 => 'Val1' },
# if Arg4 is an array of objects, the HashRefs will be passed as arguments to
# the constructor of the arguments type
Arg4 => [ { Att1 => 'Val1' }, { Att1 => 'Val2' } ],
);
DESCRIPTION
This is the Amazon Rekognition API reference.
For the AWS API documentation, see https://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27
METHODS
CompareFaces
- SourceImage => Paws::Rekognition::Image
- TargetImage => Paws::Rekognition::Image
- [QualityFilter => Str]
- [SimilarityThreshold => Num]
Each argument is described in detail in: Paws::Rekognition::CompareFaces
Returns: a Paws::Rekognition::CompareFacesResponse instance
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, role, 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.
CreateCollection
- CollectionId => Str
- [Tags => Paws::Rekognition::TagMap]
Each argument is described in detail in: Paws::Rekognition::CreateCollection
Returns: a Paws::Rekognition::CreateCollectionResponse instance
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.
CreateProject
Each argument is described in detail in: Paws::Rekognition::CreateProject
Returns: a Paws::Rekognition::CreateProjectResponse instance
Creates a new Amazon Rekognition Custom Labels project. A project is a logical grouping of resources (images, Labels, models) and operations (training, evaluation and detection).
This operation requires permissions to perform the rekognition:CreateProject
action.
CreateProjectVersion
- OutputConfig => Paws::Rekognition::OutputConfig
- ProjectArn => Str
- TestingData => Paws::Rekognition::TestingData
- TrainingData => Paws::Rekognition::TrainingData
- VersionName => Str
- [KmsKeyId => Str]
- [Tags => Paws::Rekognition::TagMap]
Each argument is described in detail in: Paws::Rekognition::CreateProjectVersion
Returns: a Paws::Rekognition::CreateProjectVersionResponse instance
Creates a new version of a model and begins training. Models are managed as part of an Amazon Rekognition Custom Labels project. You can specify one training dataset and one testing dataset. The response from CreateProjectVersion
is an Amazon Resource Name (ARN) for the version of the model.
Training takes a while to complete. You can get the current status by calling DescribeProjectVersions.
Once training has successfully completed, call DescribeProjectVersions to get the training results and evaluate the model.
After evaluating the model, you start the model by calling StartProjectVersion.
This operation requires permissions to perform the rekognition:CreateProjectVersion
action.
CreateStreamProcessor
- Input => Paws::Rekognition::StreamProcessorInput
- Name => Str
- Output => Paws::Rekognition::StreamProcessorOutput
- RoleArn => Str
- Settings => Paws::Rekognition::StreamProcessorSettings
- [Tags => Paws::Rekognition::TagMap]
Each argument is described in detail in: Paws::Rekognition::CreateStreamProcessor
Returns: a Paws::Rekognition::CreateStreamProcessorResponse instance
Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces in a streaming video.
Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. Amazon Rekognition Video sends analysis results to Amazon Kinesis Data Streams.
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. 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.
After you have finished analyzing a streaming video, use StopStreamProcessor to stop processing. You can delete the stream processor by calling DeleteStreamProcessor.
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.
DeleteCollection
Each argument is described in detail in: Paws::Rekognition::DeleteCollection
Returns: a Paws::Rekognition::DeleteCollectionResponse instance
Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, see delete-collection-procedure.
This operation requires permissions to perform the rekognition:DeleteCollection
action.
DeleteFaces
Each argument is described in detail in: Paws::Rekognition::DeleteFaces
Returns: a Paws::Rekognition::DeleteFacesResponse instance
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.
DeleteProject
Each argument is described in detail in: Paws::Rekognition::DeleteProject
Returns: a Paws::Rekognition::DeleteProjectResponse instance
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.
This operation requires permissions to perform the rekognition:DeleteProject
action.
DeleteProjectVersion
Each argument is described in detail in: Paws::Rekognition::DeleteProjectVersion
Returns: a Paws::Rekognition::DeleteProjectVersionResponse instance
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.
DeleteStreamProcessor
Each argument is described in detail in: Paws::Rekognition::DeleteStreamProcessor
Returns: a Paws::Rekognition::DeleteStreamProcessorResponse instance
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
.
DescribeCollection
Each argument is described in detail in: Paws::Rekognition::DescribeCollection
Returns: a Paws::Rekognition::DescribeCollectionResponse instance
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.
DescribeProjects
Each argument is described in detail in: Paws::Rekognition::DescribeProjects
Returns: a Paws::Rekognition::DescribeProjectsResponse instance
Lists and gets information about your Amazon Rekognition Custom Labels projects.
This operation requires permissions to perform the rekognition:DescribeProjects
action.
DescribeProjectVersions
Each argument is described in detail in: Paws::Rekognition::DescribeProjectVersions
Returns: a Paws::Rekognition::DescribeProjectVersionsResponse instance
Lists and describes the models 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 models are returned.
This operation requires permissions to perform the rekognition:DescribeProjectVersions
action.
DescribeStreamProcessor
Each argument is described in detail in: Paws::Rekognition::DescribeStreamProcessor
Returns: a Paws::Rekognition::DescribeStreamProcessorResponse instance
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.
DetectCustomLabels
- Image => Paws::Rekognition::Image
- ProjectVersionArn => Str
- [MaxResults => Int]
- [MinConfidence => Num]
Each argument is described in detail in: Paws::Rekognition::DetectCustomLabels
Returns: a Paws::Rekognition::DetectCustomLabelsResponse instance
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
).
During training model calculates a threshold value that determines if a prediction for a label is true. By default, DetectCustomLabels
doesn't return labels whose confidence value is below the model's calculated threshold value. To filter labels that are returned, specify a value for MinConfidence
that is higher than the model's calculated threshold. You can get the model's calculated threshold from the model's training results shown in the Amazon Rekognition Custom Labels console. To get all labels, regardless of confidence, specify a MinConfidence
value of 0.
You can also add the MaxResults
parameter to limit the number of labels returned.
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.
DetectFaces
- Image => Paws::Rekognition::Image
- [Attributes => ArrayRef[Str|Undef]]
Each argument is described in detail in: Paws::Rekognition::DetectFaces
Returns: a Paws::Rekognition::DetectFacesResponse instance
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.
DetectLabels
- Image => Paws::Rekognition::Image
- [MaxLabels => Int]
- [MinConfidence => Num]
Each argument is described in detail in: Paws::Rekognition::DetectLabels
Returns: a Paws::Rekognition::DetectLabelsResponse instance
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.
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, 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.
DetectModerationLabels
- Image => Paws::Rekognition::Image
- [HumanLoopConfig => Paws::Rekognition::HumanLoopConfig]
- [MinConfidence => Num]
Each argument is described in detail in: Paws::Rekognition::DetectModerationLabels
Returns: a Paws::Rekognition::DetectModerationLabelsResponse instance
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.
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.
DetectProtectiveEquipment
- Image => Paws::Rekognition::Image
- [SummarizationAttributes => Paws::Rekognition::ProtectiveEquipmentSummarizationAttributes]
Each argument is described in detail in: Paws::Rekognition::DetectProtectiveEquipment
Returns: a Paws::Rekognition::DetectProtectiveEquipmentResponse instance
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.
DetectText
- Image => Paws::Rekognition::Image
- [Filters => Paws::Rekognition::DetectTextFilters]
Each argument is described in detail in: Paws::Rekognition::DetectText
Returns: a Paws::Rekognition::DetectTextResponse instance
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 ISO basic latin script characters that are not separated by spaces. DetectText
can detect up to 50 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 DetectText in the Amazon Rekognition Developer Guide.
GetCelebrityInfo
Each argument is described in detail in: Paws::Rekognition::GetCelebrityInfo
Returns: a Paws::Rekognition::GetCelebrityInfoResponse instance
Gets the name and additional information about a celebrity based on his or her 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 Recognizing Celebrities in an Image in the Amazon Rekognition Developer Guide.
This operation requires permissions to perform the rekognition:GetCelebrityInfo
action.
GetCelebrityRecognition
Each argument is described in detail in: Paws::Rekognition::GetCelebrityRecognition
Returns: a Paws::Rekognition::GetCelebrityRecognitionResponse instance
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.
GetCelebrityRecognition
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 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
.
GetContentModeration
Each argument is described in detail in: Paws::Rekognition::GetContentModeration
Returns: a Paws::Rekognition::GetContentModerationResponse instance
Gets the unsafe content analysis results for a Amazon Rekognition Video analysis started by StartContentModeration.
Unsafe content analysis of a 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 unsafe 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 unsafe content 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 Detecting Unsafe Content in the Amazon Rekognition Developer Guide.
GetFaceDetection
Each argument is described in detail in: Paws::Rekognition::GetFaceDetection
Returns: a Paws::Rekognition::GetFaceDetectionResponse instance
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
.
GetFaceSearch
Each argument is described in detail in: Paws::Rekognition::GetFaceSearch
Returns: a Paws::Rekognition::GetFaceSearchResponse instance
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.
GetLabelDetection
Each argument is described in detail in: Paws::Rekognition::GetLabelDetection
Returns: a Paws::Rekognition::GetLabelDetectionResponse instance
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
.
GetPersonTracking
Each argument is described in detail in: Paws::Rekognition::GetPersonTracking
Returns: a Paws::Rekognition::GetPersonTrackingResponse instance
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
.
GetSegmentDetection
Each argument is described in detail in: Paws::Rekognition::GetSegmentDetection
Returns: a Paws::Rekognition::GetSegmentDetectionResponse instance
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.
GetTextDetection
Each argument is described in detail in: Paws::Rekognition::GetTextDetection
Returns: a Paws::Rekognition::GetTextDetectionResponse instance
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
.
IndexFaces
- CollectionId => Str
- Image => Paws::Rekognition::Image
- [DetectionAttributes => ArrayRef[Str|Undef]]
- [ExternalImageId => Str]
- [MaxFaces => Int]
- [QualityFilter => Str]
Each argument is described in detail in: Paws::Rekognition::IndexFaces
Returns: a Paws::Rekognition::IndexFacesResponse instance
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.
ListCollections
Each argument is described in detail in: Paws::Rekognition::ListCollections
Returns: a Paws::Rekognition::ListCollectionsResponse instance
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.
ListFaces
Each argument is described in detail in: Paws::Rekognition::ListFaces
Returns: a Paws::Rekognition::ListFacesResponse instance
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.
ListStreamProcessors
Each argument is described in detail in: Paws::Rekognition::ListStreamProcessors
Returns: a Paws::Rekognition::ListStreamProcessorsResponse instance
Gets a list of stream processors that you have created with CreateStreamProcessor.
ListTagsForResource
Each argument is described in detail in: Paws::Rekognition::ListTagsForResource
Returns: a Paws::Rekognition::ListTagsForResourceResponse instance
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.
RecognizeCelebrities
- Image => Paws::Rekognition::Image
Each argument is described in detail in: Paws::Rekognition::RecognizeCelebrities
Returns: a Paws::Rekognition::RecognizeCelebritiesResponse instance
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 recognized celebrities in the CelebrityFaces
array and 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.
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.
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.
SearchFaces
Each argument is described in detail in: Paws::Rekognition::SearchFaces
Returns: a Paws::Rekognition::SearchFacesResponse instance
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.
SearchFacesByImage
- CollectionId => Str
- Image => Paws::Rekognition::Image
- [FaceMatchThreshold => Num]
- [MaxFaces => Int]
- [QualityFilter => Str]
Each argument is described in detail in: Paws::Rekognition::SearchFacesByImage
Returns: a Paws::Rekognition::SearchFacesByImageResponse instance
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.
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.
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.
StartCelebrityRecognition
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [JobTag => Str]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartCelebrityRecognition
Returns: a Paws::Rekognition::StartCelebrityRecognitionResponse instance
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.
StartContentModeration
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [JobTag => Str]
- [MinConfidence => Num]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartContentModeration
Returns: a Paws::Rekognition::StartContentModerationResponse instance
Starts asynchronous detection of unsafe content in a stored video.
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 unsafe 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 unsafe 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 Detecting Unsafe Content in the Amazon Rekognition Developer Guide.
StartFaceDetection
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [FaceAttributes => Str]
- [JobTag => Str]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartFaceDetection
Returns: a Paws::Rekognition::StartFaceDetectionResponse instance
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.
StartFaceSearch
- CollectionId => Str
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [FaceMatchThreshold => Num]
- [JobTag => Str]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartFaceSearch
Returns: a Paws::Rekognition::StartFaceSearchResponse instance
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 procedure-person-search-videos.
StartLabelDetection
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [JobTag => Str]
- [MinConfidence => Num]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartLabelDetection
Returns: a Paws::Rekognition::StartLabelDetectionResponse instance
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
.
StartPersonTracking
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [JobTag => Str]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartPersonTracking
Returns: a Paws::Rekognition::StartPersonTrackingResponse instance
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
.
StartProjectVersion
Each argument is described in detail in: Paws::Rekognition::StartProjectVersion
Returns: a Paws::Rekognition::StartProjectVersionResponse instance
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.
StartSegmentDetection
- SegmentTypes => ArrayRef[Str|Undef]
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [Filters => Paws::Rekognition::StartSegmentDetectionFilters]
- [JobTag => Str]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartSegmentDetection
Returns: a Paws::Rekognition::StartSegmentDetectionResponse instance
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.
StartStreamProcessor
Each argument is described in detail in: Paws::Rekognition::StartStreamProcessor
Returns: a Paws::Rekognition::StartStreamProcessorResponse instance
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
.
StartTextDetection
- Video => Paws::Rekognition::Video
- [ClientRequestToken => Str]
- [Filters => Paws::Rekognition::StartTextDetectionFilters]
- [JobTag => Str]
- [NotificationChannel => Paws::Rekognition::NotificationChannel]
Each argument is described in detail in: Paws::Rekognition::StartTextDetection
Returns: a Paws::Rekognition::StartTextDetectionResponse instance
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
.
StopProjectVersion
Each argument is described in detail in: Paws::Rekognition::StopProjectVersion
Returns: a Paws::Rekognition::StopProjectVersionResponse instance
Stops a running model. The operation might take a while to complete. To check the current status, call DescribeProjectVersions.
StopStreamProcessor
Each argument is described in detail in: Paws::Rekognition::StopStreamProcessor
Returns: a Paws::Rekognition::StopStreamProcessorResponse instance
Stops a running stream processor that was created by CreateStreamProcessor.
TagResource
- ResourceArn => Str
- Tags => Paws::Rekognition::TagMap
Each argument is described in detail in: Paws::Rekognition::TagResource
Returns: a Paws::Rekognition::TagResourceResponse instance
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 (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).
This operation requires permissions to perform the rekognition:TagResource
action.
UntagResource
Each argument is described in detail in: Paws::Rekognition::UntagResource
Returns: a Paws::Rekognition::UntagResourceResponse instance
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.
PAGINATORS
Paginator methods are helpers that repetively call methods that return partial results
DescribeAllProjects(sub { },[MaxResults => Int, NextToken => Str])
DescribeAllProjects([MaxResults => Int, NextToken => Str])
If passed a sub as first parameter, it will call the sub for each element found in :
- ProjectDescriptions, passing the object as the first parameter, and the string 'ProjectDescriptions' as the second parameter
If not, it will return a a Paws::Rekognition::DescribeProjectsResponse instance with all the param
s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.
DescribeAllProjectVersions(sub { },ProjectArn => Str, [MaxResults => Int, NextToken => Str, VersionNames => ArrayRef[Str|Undef]])
DescribeAllProjectVersions(ProjectArn => Str, [MaxResults => Int, NextToken => Str, VersionNames => ArrayRef[Str|Undef]])
If passed a sub as first parameter, it will call the sub for each element found in :
- ProjectVersionDescriptions, passing the object as the first parameter, and the string 'ProjectVersionDescriptions' as the second parameter
If not, it will return a a Paws::Rekognition::DescribeProjectVersionsResponse instance with all the param
s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.
ListAllCollections(sub { },[MaxResults => Int, NextToken => Str])
ListAllCollections([MaxResults => Int, NextToken => Str])
If passed a sub as first parameter, it will call the sub for each element found in :
- CollectionIds, passing the object as the first parameter, and the string 'CollectionIds' as the second parameter
- FaceModelVersions, passing the object as the first parameter, and the string 'FaceModelVersions' as the second parameter
If not, it will return a a Paws::Rekognition::ListCollectionsResponse instance with all the param
s; andparam
s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.
ListAllFaces(sub { },CollectionId => Str, [MaxResults => Int, NextToken => Str])
ListAllFaces(CollectionId => Str, [MaxResults => Int, NextToken => Str])
If passed a sub as first parameter, it will call the sub for each element found in :
- Faces, passing the object as the first parameter, and the string 'Faces' as the second parameter
If not, it will return a a Paws::Rekognition::ListFacesResponse instance with all the param
s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.
ListAllStreamProcessors(sub { },[MaxResults => Int, NextToken => Str])
ListAllStreamProcessors([MaxResults => Int, NextToken => Str])
If passed a sub as first parameter, it will call the sub for each element found in :
- StreamProcessors, passing the object as the first parameter, and the string 'StreamProcessors' as the second parameter
If not, it will return a a Paws::Rekognition::ListStreamProcessorsResponse instance with all the param
s; from all the responses. Please take into account that this mode can potentially consume vasts ammounts of memory.
SEE ALSO
This service class forms part of Paws
BUGS and CONTRIBUTIONS
The source code is located here: https://github.com/pplu/aws-sdk-perl
Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues