@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AbstractAmazonRekognitionAsync extends AbstractAmazonRekognition implements AmazonRekognitionAsync
AmazonRekognitionAsync. Convenient method forms pass through to the corresponding
overload that takes a request object and an AsyncHandler, which throws an
UnsupportedOperationException.ENDPOINT_PREFIX| Modifier | Constructor and Description |
|---|---|
protected |
AbstractAmazonRekognitionAsync() |
compareFaces, createCollection, createDataset, createProject, createProjectVersion, createStreamProcessor, deleteCollection, deleteDataset, deleteFaces, deleteProject, deleteProjectVersion, deleteStreamProcessor, describeCollection, describeDataset, describeProjects, describeProjectVersions, describeStreamProcessor, detectCustomLabels, detectFaces, detectLabels, detectModerationLabels, detectProtectiveEquipment, detectText, distributeDatasetEntries, getCachedResponseMetadata, getCelebrityInfo, getCelebrityRecognition, getContentModeration, getFaceDetection, getFaceSearch, getLabelDetection, getPersonTracking, getSegmentDetection, getTextDetection, indexFaces, listCollections, listDatasetEntries, listDatasetLabels, listFaces, listStreamProcessors, listTagsForResource, recognizeCelebrities, searchFaces, searchFacesByImage, setEndpoint, setRegion, shutdown, startCelebrityRecognition, startContentModeration, startFaceDetection, startFaceSearch, startLabelDetection, startPersonTracking, startProjectVersion, startSegmentDetection, startStreamProcessor, startTextDetection, stopProjectVersion, stopStreamProcessor, tagResource, untagResource, updateDatasetEntries, waitersclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcompareFaces, createCollection, createDataset, createProject, createProjectVersion, createStreamProcessor, deleteCollection, deleteDataset, deleteFaces, deleteProject, deleteProjectVersion, deleteStreamProcessor, describeCollection, describeDataset, describeProjects, describeProjectVersions, describeStreamProcessor, detectCustomLabels, detectFaces, detectLabels, detectModerationLabels, detectProtectiveEquipment, detectText, distributeDatasetEntries, getCachedResponseMetadata, getCelebrityInfo, getCelebrityRecognition, getContentModeration, getFaceDetection, getFaceSearch, getLabelDetection, getPersonTracking, getSegmentDetection, getTextDetection, indexFaces, listCollections, listDatasetEntries, listDatasetLabels, listFaces, listStreamProcessors, listTagsForResource, recognizeCelebrities, searchFaces, searchFacesByImage, setEndpoint, setRegion, shutdown, startCelebrityRecognition, startContentModeration, startFaceDetection, startFaceSearch, startLabelDetection, startPersonTracking, startProjectVersion, startSegmentDetection, startStreamProcessor, startTextDetection, stopProjectVersion, stopStreamProcessor, tagResource, untagResource, updateDatasetEntries, waiterspublic Future<CompareFacesResult> compareFacesAsync(CompareFacesRequest request)
AmazonRekognitionAsyncCompares 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.
compareFacesAsync in interface AmazonRekognitionAsyncpublic Future<CompareFacesResult> compareFacesAsync(CompareFacesRequest request, AsyncHandler<CompareFacesRequest,CompareFacesResult> asyncHandler)
AmazonRekognitionAsyncCompares 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.
compareFacesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateCollectionResult> createCollectionAsync(CreateCollectionRequest request)
AmazonRekognitionAsyncCreates 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.
createCollectionAsync in interface AmazonRekognitionAsyncpublic Future<CreateCollectionResult> createCollectionAsync(CreateCollectionRequest request, AsyncHandler<CreateCollectionRequest,CreateCollectionResult> asyncHandler)
AmazonRekognitionAsyncCreates 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.
createCollectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest request)
AmazonRekognitionAsyncCreates 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.
createDatasetAsync in interface AmazonRekognitionAsyncpublic Future<CreateDatasetResult> createDatasetAsync(CreateDatasetRequest request, AsyncHandler<CreateDatasetRequest,CreateDatasetResult> asyncHandler)
AmazonRekognitionAsyncCreates 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.
createDatasetAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateProjectResult> createProjectAsync(CreateProjectRequest request)
AmazonRekognitionAsyncCreates 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.
createProjectAsync in interface AmazonRekognitionAsyncpublic Future<CreateProjectResult> createProjectAsync(CreateProjectRequest request, AsyncHandler<CreateProjectRequest,CreateProjectResult> asyncHandler)
AmazonRekognitionAsyncCreates 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.
createProjectAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateProjectVersionResult> createProjectVersionAsync(CreateProjectVersionRequest request)
AmazonRekognitionAsync
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 modelin 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.
createProjectVersionAsync in interface AmazonRekognitionAsyncpublic Future<CreateProjectVersionResult> createProjectVersionAsync(CreateProjectVersionRequest request, AsyncHandler<CreateProjectVersionRequest,CreateProjectVersionResult> asyncHandler)
AmazonRekognitionAsync
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 modelin 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.
createProjectVersionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateStreamProcessorResult> createStreamProcessorAsync(CreateStreamProcessorRequest request)
AmazonRekognitionAsyncCreates 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.
createStreamProcessorAsync in interface AmazonRekognitionAsyncpublic Future<CreateStreamProcessorResult> createStreamProcessorAsync(CreateStreamProcessorRequest request, AsyncHandler<CreateStreamProcessorRequest,CreateStreamProcessorResult> asyncHandler)
AmazonRekognitionAsyncCreates 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.
createStreamProcessorAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteCollectionResult> deleteCollectionAsync(DeleteCollectionRequest request)
AmazonRekognitionAsyncDeletes 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.
deleteCollectionAsync in interface AmazonRekognitionAsyncpublic Future<DeleteCollectionResult> deleteCollectionAsync(DeleteCollectionRequest request, AsyncHandler<DeleteCollectionRequest,DeleteCollectionResult> asyncHandler)
AmazonRekognitionAsyncDeletes 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.
deleteCollectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest request)
AmazonRekognitionAsync
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.
deleteDatasetAsync in interface AmazonRekognitionAsyncpublic Future<DeleteDatasetResult> deleteDatasetAsync(DeleteDatasetRequest request, AsyncHandler<DeleteDatasetRequest,DeleteDatasetResult> asyncHandler)
AmazonRekognitionAsync
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.
deleteDatasetAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteFacesResult> deleteFacesAsync(DeleteFacesRequest request)
AmazonRekognitionAsyncDeletes 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.
deleteFacesAsync in interface AmazonRekognitionAsyncpublic Future<DeleteFacesResult> deleteFacesAsync(DeleteFacesRequest request, AsyncHandler<DeleteFacesRequest,DeleteFacesResult> asyncHandler)
AmazonRekognitionAsyncDeletes 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.
deleteFacesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteProjectResult> deleteProjectAsync(DeleteProjectRequest request)
AmazonRekognitionAsyncDeletes 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.
deleteProjectAsync in interface AmazonRekognitionAsyncpublic Future<DeleteProjectResult> deleteProjectAsync(DeleteProjectRequest request, AsyncHandler<DeleteProjectRequest,DeleteProjectResult> asyncHandler)
AmazonRekognitionAsyncDeletes 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.
deleteProjectAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteProjectVersionResult> deleteProjectVersionAsync(DeleteProjectVersionRequest request)
AmazonRekognitionAsyncDeletes 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.
deleteProjectVersionAsync in interface AmazonRekognitionAsyncpublic Future<DeleteProjectVersionResult> deleteProjectVersionAsync(DeleteProjectVersionRequest request, AsyncHandler<DeleteProjectVersionRequest,DeleteProjectVersionResult> asyncHandler)
AmazonRekognitionAsyncDeletes 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.
deleteProjectVersionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteStreamProcessorResult> deleteStreamProcessorAsync(DeleteStreamProcessorRequest request)
AmazonRekognitionAsync
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.
deleteStreamProcessorAsync in interface AmazonRekognitionAsyncpublic Future<DeleteStreamProcessorResult> deleteStreamProcessorAsync(DeleteStreamProcessorRequest request, AsyncHandler<DeleteStreamProcessorRequest,DeleteStreamProcessorResult> asyncHandler)
AmazonRekognitionAsync
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.
deleteStreamProcessorAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeCollectionResult> describeCollectionAsync(DescribeCollectionRequest request)
AmazonRekognitionAsync
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.
describeCollectionAsync in interface AmazonRekognitionAsyncpublic Future<DescribeCollectionResult> describeCollectionAsync(DescribeCollectionRequest request, AsyncHandler<DescribeCollectionRequest,DescribeCollectionResult> asyncHandler)
AmazonRekognitionAsync
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.
describeCollectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest request)
AmazonRekognitionAsyncDescribes 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.
describeDatasetAsync in interface AmazonRekognitionAsyncpublic Future<DescribeDatasetResult> describeDatasetAsync(DescribeDatasetRequest request, AsyncHandler<DescribeDatasetRequest,DescribeDatasetResult> asyncHandler)
AmazonRekognitionAsyncDescribes 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.
describeDatasetAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeProjectVersionsResult> describeProjectVersionsAsync(DescribeProjectVersionsRequest request)
AmazonRekognitionAsync
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.
describeProjectVersionsAsync in interface AmazonRekognitionAsyncpublic Future<DescribeProjectVersionsResult> describeProjectVersionsAsync(DescribeProjectVersionsRequest request, AsyncHandler<DescribeProjectVersionsRequest,DescribeProjectVersionsResult> asyncHandler)
AmazonRekognitionAsync
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.
describeProjectVersionsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeProjectsResult> describeProjectsAsync(DescribeProjectsRequest request)
AmazonRekognitionAsyncGets information about your Amazon Rekognition Custom Labels projects.
This operation requires permissions to perform the rekognition:DescribeProjects action.
describeProjectsAsync in interface AmazonRekognitionAsyncpublic Future<DescribeProjectsResult> describeProjectsAsync(DescribeProjectsRequest request, AsyncHandler<DescribeProjectsRequest,DescribeProjectsResult> asyncHandler)
AmazonRekognitionAsyncGets information about your Amazon Rekognition Custom Labels projects.
This operation requires permissions to perform the rekognition:DescribeProjects action.
describeProjectsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeStreamProcessorResult> describeStreamProcessorAsync(DescribeStreamProcessorRequest request)
AmazonRekognitionAsyncProvides 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.
describeStreamProcessorAsync in interface AmazonRekognitionAsyncpublic Future<DescribeStreamProcessorResult> describeStreamProcessorAsync(DescribeStreamProcessorRequest request, AsyncHandler<DescribeStreamProcessorRequest,DescribeStreamProcessorResult> asyncHandler)
AmazonRekognitionAsyncProvides 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.
describeStreamProcessorAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DetectCustomLabelsResult> detectCustomLabelsAsync(DetectCustomLabelsRequest request)
AmazonRekognitionAsyncDetects 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.
detectCustomLabelsAsync in interface AmazonRekognitionAsyncpublic Future<DetectCustomLabelsResult> detectCustomLabelsAsync(DetectCustomLabelsRequest request, AsyncHandler<DetectCustomLabelsRequest,DetectCustomLabelsResult> asyncHandler)
AmazonRekognitionAsyncDetects 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.
detectCustomLabelsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DetectFacesResult> detectFacesAsync(DetectFacesRequest request)
AmazonRekognitionAsyncDetects 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.
detectFacesAsync in interface AmazonRekognitionAsyncpublic Future<DetectFacesResult> detectFacesAsync(DetectFacesRequest request, AsyncHandler<DetectFacesRequest,DetectFacesResult> asyncHandler)
AmazonRekognitionAsyncDetects 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.
detectFacesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DetectLabelsResult> detectLabelsAsync(DetectLabelsRequest request)
AmazonRekognitionAsyncDetects 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.
detectLabelsAsync in interface AmazonRekognitionAsyncpublic Future<DetectLabelsResult> detectLabelsAsync(DetectLabelsRequest request, AsyncHandler<DetectLabelsRequest,DetectLabelsResult> asyncHandler)
AmazonRekognitionAsyncDetects 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.
detectLabelsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DetectModerationLabelsResult> detectModerationLabelsAsync(DetectModerationLabelsRequest request)
AmazonRekognitionAsync
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.
detectModerationLabelsAsync in interface AmazonRekognitionAsyncpublic Future<DetectModerationLabelsResult> detectModerationLabelsAsync(DetectModerationLabelsRequest request, AsyncHandler<DetectModerationLabelsRequest,DetectModerationLabelsResult> asyncHandler)
AmazonRekognitionAsync
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.
detectModerationLabelsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DetectProtectiveEquipmentResult> detectProtectiveEquipmentAsync(DetectProtectiveEquipmentRequest request)
AmazonRekognitionAsyncDetects 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.
detectProtectiveEquipmentAsync in interface AmazonRekognitionAsyncpublic Future<DetectProtectiveEquipmentResult> detectProtectiveEquipmentAsync(DetectProtectiveEquipmentRequest request, AsyncHandler<DetectProtectiveEquipmentRequest,DetectProtectiveEquipmentResult> asyncHandler)
AmazonRekognitionAsyncDetects 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.
detectProtectiveEquipmentAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DetectTextResult> detectTextAsync(DetectTextRequest request)
AmazonRekognitionAsyncDetects 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 DetectText in the Amazon Rekognition Developer Guide.
detectTextAsync in interface AmazonRekognitionAsyncpublic Future<DetectTextResult> detectTextAsync(DetectTextRequest request, AsyncHandler<DetectTextRequest,DetectTextResult> asyncHandler)
AmazonRekognitionAsyncDetects 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 DetectText in the Amazon Rekognition Developer Guide.
detectTextAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DistributeDatasetEntriesResult> distributeDatasetEntriesAsync(DistributeDatasetEntriesRequest request)
AmazonRekognitionAsync
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.
distributeDatasetEntriesAsync in interface AmazonRekognitionAsyncpublic Future<DistributeDatasetEntriesResult> distributeDatasetEntriesAsync(DistributeDatasetEntriesRequest request, AsyncHandler<DistributeDatasetEntriesRequest,DistributeDatasetEntriesResult> asyncHandler)
AmazonRekognitionAsync
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.
distributeDatasetEntriesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetCelebrityInfoResult> getCelebrityInfoAsync(GetCelebrityInfoRequest request)
AmazonRekognitionAsyncGets 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 Recognizing Celebrities in an Image in the Amazon Rekognition Developer Guide.
This operation requires permissions to perform the rekognition:GetCelebrityInfo action.
getCelebrityInfoAsync in interface AmazonRekognitionAsyncpublic Future<GetCelebrityInfoResult> getCelebrityInfoAsync(GetCelebrityInfoRequest request, AsyncHandler<GetCelebrityInfoRequest,GetCelebrityInfoResult> asyncHandler)
AmazonRekognitionAsyncGets 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 Recognizing Celebrities in an Image in the Amazon Rekognition Developer Guide.
This operation requires permissions to perform the rekognition:GetCelebrityInfo action.
getCelebrityInfoAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetCelebrityRecognitionResult> getCelebrityRecognitionAsync(GetCelebrityRecognitionRequest request)
AmazonRekognitionAsyncGets 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.
getCelebrityRecognitionAsync in interface AmazonRekognitionAsyncpublic Future<GetCelebrityRecognitionResult> getCelebrityRecognitionAsync(GetCelebrityRecognitionRequest request, AsyncHandler<GetCelebrityRecognitionRequest,GetCelebrityRecognitionResult> asyncHandler)
AmazonRekognitionAsyncGets 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.
getCelebrityRecognitionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetContentModerationResult> getContentModerationAsync(GetContentModerationRequest request)
AmazonRekognitionAsyncGets 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 Content moderation in the Amazon Rekognition Developer Guide.
getContentModerationAsync in interface AmazonRekognitionAsyncpublic Future<GetContentModerationResult> getContentModerationAsync(GetContentModerationRequest request, AsyncHandler<GetContentModerationRequest,GetContentModerationResult> asyncHandler)
AmazonRekognitionAsyncGets 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 Content moderation in the Amazon Rekognition Developer Guide.
getContentModerationAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetFaceDetectionResult> getFaceDetectionAsync(GetFaceDetectionRequest request)
AmazonRekognitionAsyncGets 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.
getFaceDetectionAsync in interface AmazonRekognitionAsyncpublic Future<GetFaceDetectionResult> getFaceDetectionAsync(GetFaceDetectionRequest request, AsyncHandler<GetFaceDetectionRequest,GetFaceDetectionResult> asyncHandler)
AmazonRekognitionAsyncGets 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.
getFaceDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetFaceSearchResult> getFaceSearchAsync(GetFaceSearchRequest request)
AmazonRekognitionAsyncGets 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. Each
PersonMatch 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.
getFaceSearchAsync in interface AmazonRekognitionAsyncpublic Future<GetFaceSearchResult> getFaceSearchAsync(GetFaceSearchRequest request, AsyncHandler<GetFaceSearchRequest,GetFaceSearchResult> asyncHandler)
AmazonRekognitionAsyncGets 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. Each
PersonMatch 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.
getFaceSearchAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetLabelDetectionResult> getLabelDetectionAsync(GetLabelDetectionRequest request)
AmazonRekognitionAsyncGets 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.
getLabelDetectionAsync in interface AmazonRekognitionAsyncpublic Future<GetLabelDetectionResult> getLabelDetectionAsync(GetLabelDetectionRequest request, AsyncHandler<GetLabelDetectionRequest,GetLabelDetectionResult> asyncHandler)
AmazonRekognitionAsyncGets 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.
getLabelDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetPersonTrackingResult> getPersonTrackingAsync(GetPersonTrackingRequest request)
AmazonRekognitionAsyncGets 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.
getPersonTrackingAsync in interface AmazonRekognitionAsyncpublic Future<GetPersonTrackingResult> getPersonTrackingAsync(GetPersonTrackingRequest request, AsyncHandler<GetPersonTrackingRequest,GetPersonTrackingResult> asyncHandler)
AmazonRekognitionAsyncGets 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.
getPersonTrackingAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetSegmentDetectionResult> getSegmentDetectionAsync(GetSegmentDetectionRequest request)
AmazonRekognitionAsyncGets 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.
getSegmentDetectionAsync in interface AmazonRekognitionAsyncpublic Future<GetSegmentDetectionResult> getSegmentDetectionAsync(GetSegmentDetectionRequest request, AsyncHandler<GetSegmentDetectionRequest,GetSegmentDetectionResult> asyncHandler)
AmazonRekognitionAsyncGets 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.
getSegmentDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetTextDetectionResult> getTextDetectionAsync(GetTextDetectionRequest request)
AmazonRekognitionAsyncGets 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.
getTextDetectionAsync in interface AmazonRekognitionAsyncpublic Future<GetTextDetectionResult> getTextDetectionAsync(GetTextDetectionRequest request, AsyncHandler<GetTextDetectionRequest,GetTextDetectionResult> asyncHandler)
AmazonRekognitionAsyncGets 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.
getTextDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<IndexFacesResult> indexFacesAsync(IndexFacesRequest request)
AmazonRekognitionAsyncDetects 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, use the same external
ID, and use the same model version 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.
indexFacesAsync in interface AmazonRekognitionAsyncpublic Future<IndexFacesResult> indexFacesAsync(IndexFacesRequest request, AsyncHandler<IndexFacesRequest,IndexFacesResult> asyncHandler)
AmazonRekognitionAsyncDetects 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, use the same external
ID, and use the same model version 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.
indexFacesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListCollectionsResult> listCollectionsAsync(ListCollectionsRequest request)
AmazonRekognitionAsync
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.
listCollectionsAsync in interface AmazonRekognitionAsyncpublic Future<ListCollectionsResult> listCollectionsAsync(ListCollectionsRequest request, AsyncHandler<ListCollectionsRequest,ListCollectionsResult> asyncHandler)
AmazonRekognitionAsync
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.
listCollectionsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDatasetEntriesResult> listDatasetEntriesAsync(ListDatasetEntriesRequest request)
AmazonRekognitionAsyncLists 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.
listDatasetEntriesAsync in interface AmazonRekognitionAsyncpublic Future<ListDatasetEntriesResult> listDatasetEntriesAsync(ListDatasetEntriesRequest request, AsyncHandler<ListDatasetEntriesRequest,ListDatasetEntriesResult> asyncHandler)
AmazonRekognitionAsyncLists 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.
listDatasetEntriesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDatasetLabelsResult> listDatasetLabelsAsync(ListDatasetLabelsRequest request)
AmazonRekognitionAsyncLists 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.
listDatasetLabelsAsync in interface AmazonRekognitionAsyncpublic Future<ListDatasetLabelsResult> listDatasetLabelsAsync(ListDatasetLabelsRequest request, AsyncHandler<ListDatasetLabelsRequest,ListDatasetLabelsResult> asyncHandler)
AmazonRekognitionAsyncLists 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.
listDatasetLabelsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListFacesResult> listFacesAsync(ListFacesRequest request)
AmazonRekognitionAsyncReturns 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.
listFacesAsync in interface AmazonRekognitionAsyncpublic Future<ListFacesResult> listFacesAsync(ListFacesRequest request, AsyncHandler<ListFacesRequest,ListFacesResult> asyncHandler)
AmazonRekognitionAsyncReturns 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.
listFacesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListStreamProcessorsResult> listStreamProcessorsAsync(ListStreamProcessorsRequest request)
AmazonRekognitionAsyncGets a list of stream processors that you have created with CreateStreamProcessor.
listStreamProcessorsAsync in interface AmazonRekognitionAsyncpublic Future<ListStreamProcessorsResult> listStreamProcessorsAsync(ListStreamProcessorsRequest request, AsyncHandler<ListStreamProcessorsRequest,ListStreamProcessorsResult> asyncHandler)
AmazonRekognitionAsyncGets a list of stream processors that you have created with CreateStreamProcessor.
listStreamProcessorsAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest request)
AmazonRekognitionAsyncReturns 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.
listTagsForResourceAsync in interface AmazonRekognitionAsyncpublic Future<ListTagsForResourceResult> listTagsForResourceAsync(ListTagsForResourceRequest request, AsyncHandler<ListTagsForResourceRequest,ListTagsForResourceResult> asyncHandler)
AmazonRekognitionAsyncReturns 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.
listTagsForResourceAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<RecognizeCelebritiesResult> recognizeCelebritiesAsync(RecognizeCelebritiesRequest request)
AmazonRekognitionAsyncReturns 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.
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.
recognizeCelebritiesAsync in interface AmazonRekognitionAsyncpublic Future<RecognizeCelebritiesResult> recognizeCelebritiesAsync(RecognizeCelebritiesRequest request, AsyncHandler<RecognizeCelebritiesRequest,RecognizeCelebritiesResult> asyncHandler)
AmazonRekognitionAsyncReturns 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.
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.
recognizeCelebritiesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<SearchFacesResult> searchFacesAsync(SearchFacesRequest request)
AmazonRekognitionAsyncFor 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.
searchFacesAsync in interface AmazonRekognitionAsyncpublic Future<SearchFacesResult> searchFacesAsync(SearchFacesRequest request, AsyncHandler<SearchFacesRequest,SearchFacesResult> asyncHandler)
AmazonRekognitionAsyncFor 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.
searchFacesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<SearchFacesByImageResult> searchFacesByImageAsync(SearchFacesByImageRequest request)
AmazonRekognitionAsyncFor 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.
searchFacesByImageAsync in interface AmazonRekognitionAsyncpublic Future<SearchFacesByImageResult> searchFacesByImageAsync(SearchFacesByImageRequest request, AsyncHandler<SearchFacesByImageRequest,SearchFacesByImageResult> asyncHandler)
AmazonRekognitionAsyncFor 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.
searchFacesByImageAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartCelebrityRecognitionResult> startCelebrityRecognitionAsync(StartCelebrityRecognitionRequest request)
AmazonRekognitionAsyncStarts 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.
startCelebrityRecognitionAsync in interface AmazonRekognitionAsyncpublic Future<StartCelebrityRecognitionResult> startCelebrityRecognitionAsync(StartCelebrityRecognitionRequest request, AsyncHandler<StartCelebrityRecognitionRequest,StartCelebrityRecognitionResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startCelebrityRecognitionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartContentModerationResult> startContentModerationAsync(StartContentModerationRequest request)
AmazonRekognitionAsyncStarts 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 Content moderation in the Amazon Rekognition Developer Guide.
startContentModerationAsync in interface AmazonRekognitionAsyncpublic Future<StartContentModerationResult> startContentModerationAsync(StartContentModerationRequest request, AsyncHandler<StartContentModerationRequest,StartContentModerationResult> asyncHandler)
AmazonRekognitionAsyncStarts 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 Content moderation in the Amazon Rekognition Developer Guide.
startContentModerationAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartFaceDetectionResult> startFaceDetectionAsync(StartFaceDetectionRequest request)
AmazonRekognitionAsyncStarts 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.
startFaceDetectionAsync in interface AmazonRekognitionAsyncpublic Future<StartFaceDetectionResult> startFaceDetectionAsync(StartFaceDetectionRequest request, AsyncHandler<StartFaceDetectionRequest,StartFaceDetectionResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startFaceDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartFaceSearchResult> startFaceSearchAsync(StartFaceSearchRequest request)
AmazonRekognitionAsyncStarts 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.
startFaceSearchAsync in interface AmazonRekognitionAsyncpublic Future<StartFaceSearchResult> startFaceSearchAsync(StartFaceSearchRequest request, AsyncHandler<StartFaceSearchRequest,StartFaceSearchResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startFaceSearchAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartLabelDetectionResult> startLabelDetectionAsync(StartLabelDetectionRequest request)
AmazonRekognitionAsyncStarts 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.
startLabelDetectionAsync in interface AmazonRekognitionAsyncpublic Future<StartLabelDetectionResult> startLabelDetectionAsync(StartLabelDetectionRequest request, AsyncHandler<StartLabelDetectionRequest,StartLabelDetectionResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startLabelDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartPersonTrackingResult> startPersonTrackingAsync(StartPersonTrackingRequest request)
AmazonRekognitionAsyncStarts 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.
startPersonTrackingAsync in interface AmazonRekognitionAsyncpublic Future<StartPersonTrackingResult> startPersonTrackingAsync(StartPersonTrackingRequest request, AsyncHandler<StartPersonTrackingRequest,StartPersonTrackingResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startPersonTrackingAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartProjectVersionResult> startProjectVersionAsync(StartProjectVersionRequest request)
AmazonRekognitionAsyncStarts 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.
startProjectVersionAsync in interface AmazonRekognitionAsyncpublic Future<StartProjectVersionResult> startProjectVersionAsync(StartProjectVersionRequest request, AsyncHandler<StartProjectVersionRequest,StartProjectVersionResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startProjectVersionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartSegmentDetectionResult> startSegmentDetectionAsync(StartSegmentDetectionRequest request)
AmazonRekognitionAsyncStarts 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.
startSegmentDetectionAsync in interface AmazonRekognitionAsyncpublic Future<StartSegmentDetectionResult> startSegmentDetectionAsync(StartSegmentDetectionRequest request, AsyncHandler<StartSegmentDetectionRequest,StartSegmentDetectionResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startSegmentDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartStreamProcessorResult> startStreamProcessorAsync(StartStreamProcessorRequest request)
AmazonRekognitionAsync
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.
startStreamProcessorAsync in interface AmazonRekognitionAsyncpublic Future<StartStreamProcessorResult> startStreamProcessorAsync(StartStreamProcessorRequest request, AsyncHandler<StartStreamProcessorRequest,StartStreamProcessorResult> asyncHandler)
AmazonRekognitionAsync
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.
startStreamProcessorAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartTextDetectionResult> startTextDetectionAsync(StartTextDetectionRequest request)
AmazonRekognitionAsyncStarts 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.
startTextDetectionAsync in interface AmazonRekognitionAsyncpublic Future<StartTextDetectionResult> startTextDetectionAsync(StartTextDetectionRequest request, AsyncHandler<StartTextDetectionRequest,StartTextDetectionResult> asyncHandler)
AmazonRekognitionAsyncStarts 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.
startTextDetectionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopProjectVersionResult> stopProjectVersionAsync(StopProjectVersionRequest request)
AmazonRekognitionAsyncStops a running model. The operation might take a while to complete. To check the current status, call DescribeProjectVersions.
stopProjectVersionAsync in interface AmazonRekognitionAsyncpublic Future<StopProjectVersionResult> stopProjectVersionAsync(StopProjectVersionRequest request, AsyncHandler<StopProjectVersionRequest,StopProjectVersionResult> asyncHandler)
AmazonRekognitionAsyncStops a running model. The operation might take a while to complete. To check the current status, call DescribeProjectVersions.
stopProjectVersionAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopStreamProcessorResult> stopStreamProcessorAsync(StopStreamProcessorRequest request)
AmazonRekognitionAsyncStops a running stream processor that was created by CreateStreamProcessor.
stopStreamProcessorAsync in interface AmazonRekognitionAsyncpublic Future<StopStreamProcessorResult> stopStreamProcessorAsync(StopStreamProcessorRequest request, AsyncHandler<StopStreamProcessorRequest,StopStreamProcessorResult> asyncHandler)
AmazonRekognitionAsyncStops a running stream processor that was created by CreateStreamProcessor.
stopStreamProcessorAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<TagResourceResult> tagResourceAsync(TagResourceRequest request)
AmazonRekognitionAsyncAdds 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.
tagResourceAsync in interface AmazonRekognitionAsyncpublic Future<TagResourceResult> tagResourceAsync(TagResourceRequest request, AsyncHandler<TagResourceRequest,TagResourceResult> asyncHandler)
AmazonRekognitionAsyncAdds 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.
tagResourceAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest request)
AmazonRekognitionAsyncRemoves 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.
untagResourceAsync in interface AmazonRekognitionAsyncpublic Future<UntagResourceResult> untagResourceAsync(UntagResourceRequest request, AsyncHandler<UntagResourceRequest,UntagResourceResult> asyncHandler)
AmazonRekognitionAsyncRemoves 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.
untagResourceAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateDatasetEntriesResult> updateDatasetEntriesAsync(UpdateDatasetEntriesRequest request)
AmazonRekognitionAsyncAdds 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.
updateDatasetEntriesAsync in interface AmazonRekognitionAsyncpublic Future<UpdateDatasetEntriesResult> updateDatasetEntriesAsync(UpdateDatasetEntriesRequest request, AsyncHandler<UpdateDatasetEntriesRequest,UpdateDatasetEntriesResult> asyncHandler)
AmazonRekognitionAsyncAdds 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.
updateDatasetEntriesAsync in interface AmazonRekognitionAsyncasyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Copyright © 2022. All rights reserved.