Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The source and
+ * This operation applies only to Amazon Rekognition Custom Labels.
Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The source and * destination projects can be in different AWS accounts but must be in the same AWS Region. * You can't copy a model to another AWS service. * @@ -51,7 +54,9 @@ export interface CopyProjectVersionCommandOutput extends CopyProjectVersionRespo *
*If you are copying a model version to a project in the same AWS account, you don't need to create a project policy.
*To copy a model, the destination project, source project, and source model version must already exist.
+ *Copying project versions is supported only for Custom Labels models.
+ *To copy a model, the destination project, source project, and source model version + * must already exist.
*Copying a model version takes a while to complete. To get the current status, call DescribeProjectVersions and check the value of Status in the
* ProjectVersionDescription object. The copy operation has finished when
@@ -102,9 +107,11 @@ export interface CopyProjectVersionCommandOutput extends CopyProjectVersionRespo
* operation again.
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/CreateDatasetCommand.ts b/clients/client-rekognition/src/commands/CreateDatasetCommand.ts index c899b84a23300..c1809d2aa1917 100644 --- a/clients/client-rekognition/src/commands/CreateDatasetCommand.ts +++ b/clients/client-rekognition/src/commands/CreateDatasetCommand.ts @@ -37,7 +37,10 @@ export interface CreateDatasetCommandOutput extends CreateDatasetResponse, __Met /** * @public - *
Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using
+ * This operation applies only to Amazon Rekognition Custom Labels.
Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using * an Amazon Sagemaker format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset.
*To create a training dataset for a project, specify TRAIN for the value of
* DatasetType. To create the test dataset for a project,
@@ -104,9 +107,11 @@ export interface CreateDatasetCommandOutput extends CreateDatasetResponse, __Met
*
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/CreateProjectCommand.ts b/clients/client-rekognition/src/commands/CreateProjectCommand.ts index 678ba15c6898f..4cd353d3763e7 100644 --- a/clients/client-rekognition/src/commands/CreateProjectCommand.ts +++ b/clients/client-rekognition/src/commands/CreateProjectCommand.ts @@ -37,9 +37,12 @@ export interface CreateProjectCommandOutput extends CreateProjectResponse, __Met /** * @public - *
Creates a new Amazon Rekognition Custom Labels project. A project is a group of resources (datasets, model versions) - * that you use to create and manage Amazon Rekognition Custom Labels models.
- *This operation requires permissions to perform the rekognition:CreateProject action.
Creates a new Amazon Rekognition project. A project is a group of resources (datasets, model
+ * versions) that you use to create and manage a Amazon Rekognition Custom Labels Model or custom adapter. You can
+ * specify a feature to create the project with, if no feature is specified then Custom Labels
+ * is used by default. For adapters, you can also choose whether or not to have the project
+ * auto update by using the AutoUpdate argument. This operation requires permissions to
+ * perform the rekognition:CreateProject action.
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/CreateProjectVersionCommand.ts b/clients/client-rekognition/src/commands/CreateProjectVersionCommand.ts index 8efda08a411c2..c5fd3166d5d7d 100644 --- a/clients/client-rekognition/src/commands/CreateProjectVersionCommand.ts +++ b/clients/client-rekognition/src/commands/CreateProjectVersionCommand.ts @@ -37,14 +37,24 @@ export interface CreateProjectVersionCommandOutput extends CreateProjectVersionR /** * @public - *
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. - *
+ *Creates a new version of Amazon Rekognition project (like a Custom Labels model or a custom adapter)
+ * and begins training. Models and adapters are managed as part of a Rekognition project. The
+ * response from CreateProjectVersion is an Amazon Resource Name (ARN) for the
+ * project version.
The FeatureConfig operation argument allows you to configure specific model or adapter
+ * settings. You can provide a description to the project version by using the
+ * VersionDescription argment. Training can take 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. Once training has successfully completed, call DescribeProjectVersions to get the training results and evaluate the
+ * model.
This operation requires permissions to perform the
+ * rekognition:CreateProjectVersion action.
+ * The following applies only to projects with Amazon Rekognition Custom Labels as the chosen + * feature: + *
*You can train a model in a project that doesn't have associated datasets by specifying manifest files in the
* TrainingData and TestingData fields.
*
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.
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/CreateStreamProcessorCommand.ts b/clients/client-rekognition/src/commands/CreateStreamProcessorCommand.ts index db54a740249dc..13719dfdbd07b 100644 --- a/clients/client-rekognition/src/commands/CreateStreamProcessorCommand.ts +++ b/clients/client-rekognition/src/commands/CreateStreamProcessorCommand.ts @@ -155,9 +155,11 @@ export interface CreateStreamProcessorCommandOutput extends CreateStreamProcesso * operation again.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/DeleteDatasetCommand.ts b/clients/client-rekognition/src/commands/DeleteDatasetCommand.ts index b4ba40679b350..a40d8a4a52a87 100644 --- a/clients/client-rekognition/src/commands/DeleteDatasetCommand.ts +++ b/clients/client-rekognition/src/commands/DeleteDatasetCommand.ts @@ -37,7 +37,10 @@ export interface DeleteDatasetCommandOutput extends DeleteDatasetResponse, __Met /** * @public - *
Deletes an existing Amazon Rekognition Custom Labels dataset.
+ * This operation applies only to Amazon Rekognition Custom Labels.
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
@@ -79,9 +82,11 @@ export interface DeleteDatasetCommandOutput extends DeleteDatasetResponse, __Met
* operation again.
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/DeleteProjectCommand.ts b/clients/client-rekognition/src/commands/DeleteProjectCommand.ts index b998bb40735ce..0d31ec98fbaa0 100644 --- a/clients/client-rekognition/src/commands/DeleteProjectCommand.ts +++ b/clients/client-rekognition/src/commands/DeleteProjectCommand.ts @@ -37,8 +37,8 @@ export interface DeleteProjectCommandOutput extends DeleteProjectResponse, __Met /** * @public - *
Deletes an Amazon Rekognition Custom Labels project. To delete a project you must first delete all models associated - * with the project. To delete a model, see DeleteProjectVersion.
+ *Deletes a Amazon Rekognition project. To delete a project you must first delete all models or + * adapters associated with the project. To delete a model or adapter, see DeleteProjectVersion.
*
* DeleteProject is an asynchronous operation. To check if the project is
* deleted, call DescribeProjects. The project is deleted when the project
diff --git a/clients/client-rekognition/src/commands/DeleteProjectPolicyCommand.ts b/clients/client-rekognition/src/commands/DeleteProjectPolicyCommand.ts
index 41d179f758d54..5b21a8b64cd81 100644
--- a/clients/client-rekognition/src/commands/DeleteProjectPolicyCommand.ts
+++ b/clients/client-rekognition/src/commands/DeleteProjectPolicyCommand.ts
@@ -37,7 +37,10 @@ export interface DeleteProjectPolicyCommandOutput extends DeleteProjectPolicyRes
/**
* @public
- *
Deletes an existing project policy.
+ *This operation applies only to Amazon Rekognition Custom Labels.
+ *Deletes an existing project policy.
*To get a list of project policies attached to a project, call ListProjectPolicies. To attach a project policy to a project, call PutProjectPolicy.
*This operation requires permissions to perform the rekognition:DeleteProjectPolicy action.
Deletes an Amazon Rekognition Custom Labels model.
- *You can't delete a model if it is running or if it is training.
- * To check the status of a model, use the Status field returned
- * from DescribeProjectVersions.
- * To stop a running model call StopProjectVersion. If the model
- * is training, wait until it finishes.
Deletes a Rekognition project model or project version, like a Amazon Rekognition Custom Labels model or a custom + * adapter.
+ *You can't delete a project version if it is running or if it is training. To check + * the status of a project version, use the Status field returned from DescribeProjectVersions. To stop a project version call StopProjectVersion. If the project version is training, wait until it + * finishes.
*This operation requires permissions to perform the
* rekognition:DeleteProjectVersion action.
+ * This operation applies only to Amazon Rekognition Custom Labels.
* Describes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a dataset and * statistics about the images and labels in a dataset. *
diff --git a/clients/client-rekognition/src/commands/DescribeProjectVersionsCommand.ts b/clients/client-rekognition/src/commands/DescribeProjectVersionsCommand.ts index fd5ce246142fd..a46201090d2d9 100644 --- a/clients/client-rekognition/src/commands/DescribeProjectVersionsCommand.ts +++ b/clients/client-rekognition/src/commands/DescribeProjectVersionsCommand.ts @@ -37,9 +37,9 @@ export interface DescribeProjectVersionsCommandOutput extends DescribeProjectVer /** * @public - *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.
Lists and describes the versions of an Amazon Rekognition project. You can specify up to 10 model or
+ * adapter versions in ProjectVersionArns. If you don't specify a value,
+ * descriptions for all model/adapter versions in the project are returned.
This operation requires permissions to perform the rekognition:DescribeProjectVersions
* action.
Gets information about your Amazon Rekognition Custom Labels projects.
+ *Gets information about your Rekognition projects.
*This operation requires permissions to perform the rekognition:DescribeProjects action.
Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model.
+ *This operation applies only to Amazon Rekognition Custom Labels.
+ *Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model.
*You specify which version of a model version to use by using the ProjectVersionArn input
* parameter.
You pass the input image as base64-encoded image bytes or as a reference to an image in @@ -144,9 +147,11 @@ export interface DetectCustomLabelsCommandOutput extends DetectCustomLabelsRespo *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/DetectModerationLabelsCommand.ts b/clients/client-rekognition/src/commands/DetectModerationLabelsCommand.ts index c4e8b33c333a0..21eb9a7a2ec52 100644 --- a/clients/client-rekognition/src/commands/DetectModerationLabelsCommand.ts +++ b/clients/client-rekognition/src/commands/DetectModerationLabelsCommand.ts @@ -50,6 +50,8 @@ export interface DetectModerationLabelsCommandOutput extends DetectModerationLab * AWS * CLI to call Amazon Rekognition operations, passing image bytes is not * supported. The image must be either a PNG or JPEG formatted file.
+ *You can specify an adapter to use when retrieving label predictions by providing a
+ * ProjectVersionArn to the ProjectVersion argument.
The number of requests exceeded your throughput limit. If you want to increase this * limit, contact Amazon Rekognition.
* + * @throws {@link ResourceNotFoundException} (client fault) + *The resource specified in the request cannot be found.
+ * + * @throws {@link ResourceNotReadyException} (client fault) + *The requested resource isn't ready. For example,
+ * this exception occurs when you call DetectCustomLabels with a
+ * model version that isn't deployed.
Amazon Rekognition is temporarily unable to process the request. Try your call again.
* diff --git a/clients/client-rekognition/src/commands/DistributeDatasetEntriesCommand.ts b/clients/client-rekognition/src/commands/DistributeDatasetEntriesCommand.ts index 58496cb066955..889dabcfc3aa0 100644 --- a/clients/client-rekognition/src/commands/DistributeDatasetEntriesCommand.ts +++ b/clients/client-rekognition/src/commands/DistributeDatasetEntriesCommand.ts @@ -37,7 +37,10 @@ export interface DistributeDatasetEntriesCommandOutput extends DistributeDataset /** * @public - *Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a project.
+ * This operation applies only to Amazon Rekognition Custom Labels.
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.
*
+ * This operation applies only to Amazon Rekognition Custom Labels.
* Lists the entries (images) within a dataset. An entry is a * JSON Line that contains the information for a single image, including * the image location, assigned labels, and object location bounding boxes. For diff --git a/clients/client-rekognition/src/commands/ListDatasetLabelsCommand.ts b/clients/client-rekognition/src/commands/ListDatasetLabelsCommand.ts index 681c4ad7bbce4..864b124de24a1 100644 --- a/clients/client-rekognition/src/commands/ListDatasetLabelsCommand.ts +++ b/clients/client-rekognition/src/commands/ListDatasetLabelsCommand.ts @@ -37,7 +37,10 @@ export interface ListDatasetLabelsCommandOutput extends ListDatasetLabelsRespons /** * @public - *
Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see
+ * This operation applies only to Amazon Rekognition Custom Labels.
Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see * Labeling images. *
*diff --git a/clients/client-rekognition/src/commands/ListProjectPoliciesCommand.ts b/clients/client-rekognition/src/commands/ListProjectPoliciesCommand.ts index 6edb5a590afb8..eacee753420ec 100644 --- a/clients/client-rekognition/src/commands/ListProjectPoliciesCommand.ts +++ b/clients/client-rekognition/src/commands/ListProjectPoliciesCommand.ts @@ -37,7 +37,10 @@ export interface ListProjectPoliciesCommandOutput extends ListProjectPoliciesRes /** * @public - *
Gets a list of the project policies attached to a project.
+ *This operation applies only to Amazon Rekognition Custom Labels.
+ *Gets a list of the project policies attached to a project.
*To attach a project policy to a project, call PutProjectPolicy. To remove a project policy from a project, call DeleteProjectPolicy.
*This operation requires permissions to perform the rekognition:ListProjectPolicies action.
Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A
+ * This operation applies only to Amazon Rekognition Custom Labels.
Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A * project policy specifies that a trusted AWS account can copy a model version from a - * trusting AWS account to a project in the trusted AWS account. To copy a model version you use - * the CopyProjectVersion operation.
+ * trusting AWS account to a project in the trusted AWS account. To copy a model version + * you use the CopyProjectVersion operation. Only applies to Custom Labels + * projects. *For more information about the format of a project policy document, see Attaching a project policy (SDK) * in the Amazon Rekognition Custom Labels Developer Guide. *
@@ -91,9 +95,11 @@ export interface PutProjectPolicyCommandOutput extends PutProjectPolicyResponse, *The supplied revision id for the project policy is invalid.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The format of the project policy document that you supplied to diff --git a/clients/client-rekognition/src/commands/SearchUsersByImageCommand.ts b/clients/client-rekognition/src/commands/SearchUsersByImageCommand.ts index 2edb3d0ab1c61..b230fb03f19ba 100644 --- a/clients/client-rekognition/src/commands/SearchUsersByImageCommand.ts +++ b/clients/client-rekognition/src/commands/SearchUsersByImageCommand.ts @@ -14,7 +14,8 @@ import { SMITHY_CONTEXT_KEY, } from "@smithy/types"; -import { SearchUsersByImageRequest, SearchUsersByImageResponse } from "../models/models_0"; +import { SearchUsersByImageRequest } from "../models/models_0"; +import { SearchUsersByImageResponse } from "../models/models_1"; import { de_SearchUsersByImageCommand, se_SearchUsersByImageCommand } from "../protocols/Aws_json1_1"; import { RekognitionClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../RekognitionClient"; diff --git a/clients/client-rekognition/src/commands/StartCelebrityRecognitionCommand.ts b/clients/client-rekognition/src/commands/StartCelebrityRecognitionCommand.ts index e6f8b87f91a85..1bdc9d461656a 100644 --- a/clients/client-rekognition/src/commands/StartCelebrityRecognitionCommand.ts +++ b/clients/client-rekognition/src/commands/StartCelebrityRecognitionCommand.ts @@ -14,8 +14,7 @@ import { SMITHY_CONTEXT_KEY, } from "@smithy/types"; -import { StartCelebrityRecognitionRequest } from "../models/models_0"; -import { StartCelebrityRecognitionResponse } from "../models/models_1"; +import { StartCelebrityRecognitionRequest, StartCelebrityRecognitionResponse } from "../models/models_1"; import { de_StartCelebrityRecognitionCommand, se_StartCelebrityRecognitionCommand } from "../protocols/Aws_json1_1"; import { RekognitionClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../RekognitionClient"; @@ -102,9 +101,11 @@ export interface StartCelebrityRecognitionCommandOutput extends StartCelebrityRe *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartContentModerationCommand.ts b/clients/client-rekognition/src/commands/StartContentModerationCommand.ts index e56a4974a2d4e..3fda28ebbadcf 100644 --- a/clients/client-rekognition/src/commands/StartContentModerationCommand.ts +++ b/clients/client-rekognition/src/commands/StartContentModerationCommand.ts @@ -102,9 +102,11 @@ export interface StartContentModerationCommandOutput extends StartContentModerat *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartFaceDetectionCommand.ts b/clients/client-rekognition/src/commands/StartFaceDetectionCommand.ts index d4dcbed90fc7d..6650eee14bfed 100644 --- a/clients/client-rekognition/src/commands/StartFaceDetectionCommand.ts +++ b/clients/client-rekognition/src/commands/StartFaceDetectionCommand.ts @@ -103,9 +103,11 @@ export interface StartFaceDetectionCommandOutput extends StartFaceDetectionRespo *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartFaceSearchCommand.ts b/clients/client-rekognition/src/commands/StartFaceSearchCommand.ts index c64a0f4d4fd38..8e506b6f8071c 100644 --- a/clients/client-rekognition/src/commands/StartFaceSearchCommand.ts +++ b/clients/client-rekognition/src/commands/StartFaceSearchCommand.ts @@ -103,9 +103,11 @@ export interface StartFaceSearchCommandOutput extends StartFaceSearchResponse, _ *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartLabelDetectionCommand.ts b/clients/client-rekognition/src/commands/StartLabelDetectionCommand.ts index dce00e71f6085..a46da47243e4a 100644 --- a/clients/client-rekognition/src/commands/StartLabelDetectionCommand.ts +++ b/clients/client-rekognition/src/commands/StartLabelDetectionCommand.ts @@ -135,9 +135,11 @@ export interface StartLabelDetectionCommandOutput extends StartLabelDetectionRes *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartPersonTrackingCommand.ts b/clients/client-rekognition/src/commands/StartPersonTrackingCommand.ts index 77a839da933b4..2598736987d90 100644 --- a/clients/client-rekognition/src/commands/StartPersonTrackingCommand.ts +++ b/clients/client-rekognition/src/commands/StartPersonTrackingCommand.ts @@ -99,9 +99,11 @@ export interface StartPersonTrackingCommandOutput extends StartPersonTrackingRes *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartProjectVersionCommand.ts b/clients/client-rekognition/src/commands/StartProjectVersionCommand.ts index d59307a8484f9..638e88b8281c5 100644 --- a/clients/client-rekognition/src/commands/StartProjectVersionCommand.ts +++ b/clients/client-rekognition/src/commands/StartProjectVersionCommand.ts @@ -37,15 +37,17 @@ export interface StartProjectVersionCommandOutput extends StartProjectVersionRes /** * @public - *
Starts the running of the version of a model. Starting a model takes a while - * to complete. To check the current state of the model, use DescribeProjectVersions.
+ *This operation applies only to Amazon Rekognition Custom Labels.
+ *Starts the running of the version of a model. Starting a model takes a while to + * complete. To check the current state of the model, use DescribeProjectVersions.
*Once the model is running, you can detect custom labels in new images by calling * DetectCustomLabels.
*You are charged for the amount of time that the model is running. To stop a running * model, call StopProjectVersion.
*For more information, see Running a trained Amazon Rekognition Custom Labels model in the Amazon Rekognition Custom Labels Guide.
*This operation requires permissions to perform the
* rekognition:StartProjectVersion action.
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartSegmentDetectionCommand.ts b/clients/client-rekognition/src/commands/StartSegmentDetectionCommand.ts index 07bfb5ace9ffc..95bcd17d41337 100644 --- a/clients/client-rekognition/src/commands/StartSegmentDetectionCommand.ts +++ b/clients/client-rekognition/src/commands/StartSegmentDetectionCommand.ts @@ -119,9 +119,11 @@ export interface StartSegmentDetectionCommandOutput extends StartSegmentDetectio *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StartTextDetectionCommand.ts b/clients/client-rekognition/src/commands/StartTextDetectionCommand.ts index f2ec7e6b65ecd..796fd83deac0f 100644 --- a/clients/client-rekognition/src/commands/StartTextDetectionCommand.ts +++ b/clients/client-rekognition/src/commands/StartTextDetectionCommand.ts @@ -121,9 +121,11 @@ export interface StartTextDetectionCommandOutput extends StartTextDetectionRespo *
Amazon Rekognition is unable to access the S3 object specified in the request.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/commands/StopProjectVersionCommand.ts b/clients/client-rekognition/src/commands/StopProjectVersionCommand.ts index 3b2a817237f83..e30fe67c50dda 100644 --- a/clients/client-rekognition/src/commands/StopProjectVersionCommand.ts +++ b/clients/client-rekognition/src/commands/StopProjectVersionCommand.ts @@ -37,8 +37,12 @@ export interface StopProjectVersionCommandOutput extends StopProjectVersionRespo /** * @public - *
Stops a running model. The operation might take a while to complete. To - * check the current status, call DescribeProjectVersions.
+ *This operation applies only to Amazon Rekognition Custom Labels.
+ *Stops a running model. The operation might take a while to complete. To check the + * current status, call DescribeProjectVersions. Only applies to Custom + * Labels projects.
*This operation requires permissions to perform the rekognition:StopProjectVersion action.
Adds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the
+ * This operation applies only to Amazon Rekognition Custom Labels.
Adds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the * information for a single image, including * the image location, assigned labels, and object location bounding boxes. For more information, * see Image-Level labels in manifest files and Object localization in manifest files in the Amazon Rekognition Custom Labels Developer Guide. @@ -94,9 +97,11 @@ export interface UpdateDatasetEntriesCommandOutput extends UpdateDatasetEntriesR * operation again.
* * @throws {@link LimitExceededException} (client fault) - *An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The number of requests exceeded your throughput limit. If you want to increase this diff --git a/clients/client-rekognition/src/models/models_0.ts b/clients/client-rekognition/src/models/models_0.ts index 2c9af4d857781..bc5f7ff83ee82 100644 --- a/clients/client-rekognition/src/models/models_0.ts +++ b/clients/client-rekognition/src/models/models_0.ts @@ -2130,9 +2130,11 @@ export interface CopyProjectVersionResponse { /** * @public - *
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations
- * (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until
- * the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
+ * concurrently, subsequent calls to start operations (ex:
+ * StartLabelDetection) will raise a LimitExceededException
+ * exception (HTTP status code: 400) until the number of concurrently running jobs is below
+ * the Amazon Rekognition service limit.
The name of the project to create.
*/ ProjectName: string | undefined; + + /** + * @public + *Specifies feature that is being customized. If no value is provided CUSTOM_LABELS is used as a default.
+ */ + Feature?: CustomizationFeature | string; + + /** + * @public + *Specifies whether automatic retraining should be attempted for the versions of the + * project. Automatic retraining is done as a best effort. Required argument for Content + * Moderation. Applicable only to adapters.
+ */ + AutoUpdate?: ProjectAutoUpdate | string; } /** @@ -2463,7 +2507,33 @@ export interface CreateProjectResponse { /** * @public - *The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition Custom Labels uses the
+ *
Configuration options for Content Moderation training.
+ */ +export interface CustomizationFeatureContentModerationConfig { + /** + * @public + *The confidence level you plan to use to identify if unsafe content is present during inference.
+ */ + ConfidenceThreshold?: number; +} + +/** + * @public + *Feature specific configuration for the training job. Configuration provided for the job must match + * the feature type parameter associated with project. If configuration + * and feature type do not match an InvalidParameterException is returned.
+ */ +export interface CustomizationFeatureConfig { + /** + * @public + *Configuration options for Custom Moderation training.
+ */ + ContentModeration?: CustomizationFeatureContentModerationConfig; +} + +/** + * @public + *The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition uses the
* training dataset to create a test dataset with a temporary split of the training dataset.
If specified, Amazon Rekognition Custom Labels temporarily splits the training dataset (80%) to create a test dataset (20%) for the training job. - * After training completes, the test dataset is not stored and the training dataset reverts to its previous size.
+ *If specified, Rekognition splits training dataset to create a test dataset for + * the training job.
*/ AutoCreate?: boolean; } @@ -2488,7 +2558,8 @@ export interface TestingData { export interface TrainingData { /** * @public - *A Sagemaker GroundTruth manifest file that contains the training images (assets).
+ *A manifest file that contains references to the training images and ground-truth + * annotations.
*/ Assets?: Asset[]; } @@ -2499,56 +2570,55 @@ export interface TrainingData { export interface CreateProjectVersionRequest { /** * @public - *The ARN of the Amazon Rekognition Custom Labels project that - * manages the model that you want to train.
+ *The ARN of the Amazon Rekognition project that will manage the project version you want to + * train.
*/ ProjectArn: string | undefined; /** * @public - *A name for the version of the model. This value must be unique.
+ *A name for the version of the project version. This value must be unique.
*/ VersionName: string | undefined; /** * @public - *The Amazon S3 bucket location to store the results of training.
- * The S3 bucket can be in any AWS account as long as the caller has
- * s3:PutObject permissions on the S3 bucket.
The Amazon S3 bucket location to store the results of training. The bucket can be any S3
+ * bucket in your AWS account. You need s3:PutObject permission on the bucket.
+ *
Specifies an external manifest that the services uses to train the model. + *
Specifies an external manifest that the services uses to train the project version.
* If you specify TrainingData you must also specify TestingData.
- * The project must not have any associated datasets.
- *
Specifies an external manifest that the service uses to test the model.
- * If you specify TestingData you must also specify TrainingData.
- * The project must not have any associated datasets.
Specifies an external manifest that the service uses to test the project version. If
+ * you specify TestingData you must also specify TrainingData. The
+ * project must not have any associated datasets.
A set of tags (key-value pairs) that you want to attach to the model.
+ *A set of tags (key-value pairs) that you want to attach to the project version.
*/ Tags?: RecordThe identifier for your AWS Key Management Service key (AWS KMS key).
- * You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key,
- * an alias for your KMS key, or an alias ARN.
- * The key is used to encrypt training and test images copied into the service for model training.
- * Your source images are unaffected. The key is also used to encrypt training results
- * and manifest files written to the output Amazon S3 bucket (OutputConfig).
The identifier for your AWS Key Management Service key (AWS KMS key). You can supply
+ * the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for
+ * your KMS key, or an alias ARN. The key is used to encrypt training images, test images, and manifest files copied
+ * into the service for the project version. Your source images are unaffected. The
+ * key is also used to encrypt training results and manifest files written to the output Amazon S3
+ * bucket (OutputConfig).
If you choose to use your own KMS key, you need the following permissions on the KMS key.
*A description applied to the project version being created.
+ */ + VersionDescription?: string; + + /** + * @public + *Feature-specific configuration of the training job. If the job configuration does not match the feature type associated with the project, an InvalidParameterException is returned.
+ */ + FeatureConfig?: CustomizationFeatureConfig; } /** @@ -2576,8 +2658,9 @@ export interface CreateProjectVersionRequest { export interface CreateProjectVersionResponse { /** * @public - *The ARN of the model version that was created. Use DescribeProjectVersion
- * to get the current status of the training operation.
The ARN of the model or the project version that was created. Use
+ * DescribeProjectVersion to get the current status of the training
+ * operation.
The Amazon Resource Name (ARN) of the model version that you want to delete.
+ *The Amazon Resource Name (ARN) of the project version that you want to + * delete.
*/ ProjectVersionArn: string | undefined; } @@ -3467,6 +3551,8 @@ export const ProjectVersionStatus = { COPYING_FAILED: "COPYING_FAILED", COPYING_IN_PROGRESS: "COPYING_IN_PROGRESS", DELETING: "DELETING", + DEPRECATED: "DEPRECATED", + EXPIRED: "EXPIRED", FAILED: "FAILED", RUNNING: "RUNNING", STARTING: "STARTING", @@ -3622,7 +3708,7 @@ export interface DescribeProjectsRequest { /** * @public *If the previous response was incomplete (because there is more - * results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. You can use this pagination + * results to retrieve), Rekognition returns a pagination token in the response. You can use this pagination * token to retrieve the next set of results.
*/ NextToken?: string; @@ -3637,10 +3723,17 @@ export interface DescribeProjectsRequest { /** * @public - *A list of the projects that you want Amazon Rekognition Custom Labels to describe. If you don't specify a value, + *
A list of the projects that you want Rekognition to describe. If you don't specify a value, * the response includes descriptions for all the projects in your AWS account.
*/ ProjectNames?: string[]; + + /** + * @public + *Specifies the type of customization to filter projects by. If no value is specified, + * CUSTOM_LABELS is used as a default.
+ */ + Features?: (CustomizationFeature | string)[]; } /** @@ -3673,6 +3766,18 @@ export interface ProjectDescription { * */ Datasets?: DatasetMetadata[]; + + /** + * @public + *Specifies the project that is being customized.
+ */ + Feature?: CustomizationFeature | string; + + /** + * @public + *Indicates whether automatic retraining will be attempted for the versions of the project. Applies only to adapters.
+ */ + AutoUpdate?: ProjectAutoUpdate | string; } /** @@ -3688,7 +3793,7 @@ export interface DescribeProjectsResponse { /** * @public *If the previous response was incomplete (because there is more - * results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. + * results to retrieve), Amazon Rekognition returns a pagination token in the response. * You can use this pagination token to retrieve the next set of results.
*/ NextToken?: string; @@ -3730,15 +3835,17 @@ export class InvalidPaginationTokenException extends __BaseException { export interface DescribeProjectVersionsRequest { /** * @public - *The Amazon Resource Name (ARN) of the project that contains the models you want to describe.
+ *The Amazon Resource Name (ARN) of the project that contains the model/adapter you want + * to describe.
*/ ProjectArn: string | undefined; /** * @public - *A list of model version names that you want to describe. You can add up to 10 model version names
- * to the list. If you don't specify a value, all model descriptions are returned. A version name is part of a
- * model (ProjectVersion) ARN. For example, my-model.2020-01-21T09.10.15 is the version name in the following ARN.
+ *
A list of model or project version names that you want to describe. You can add
+ * up to 10 model or project version names to the list. If you don't specify a value, all
+ * project version descriptions are returned. A version name is part of a project version ARN. For example, my-model.2020-01-21T09.10.15 is
+ * the version name in the following ARN.
* arn:aws:rekognition:us-east-1:123456789012:project/getting-started/version/my-model.2020-01-21T09.10.15/1234567890123.
If the previous response was incomplete (because there is more - * results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. + * results to retrieve), Amazon Rekognition returns a pagination token in the response. * You can use this pagination token to retrieve the next set of results.
*/ NextToken?: string; @@ -3826,7 +3933,8 @@ export interface ValidationData { /** * @public - *Sagemaker Groundtruth format manifest files for the input, output and validation datasets that are used and created during testing.
+ *Sagemaker Groundtruth format manifest files for the input, output and validation + * datasets that are used and created during testing.
*/ export interface TestingDataResult { /** @@ -3851,36 +3959,39 @@ export interface TestingDataResult { /** * @public - *Sagemaker Groundtruth format manifest files for the input, output and validation datasets that are used and created during testing.
+ *The data + * validation manifest created for the training dataset during model training.
*/ export interface TrainingDataResult { /** * @public - *The training assets that you supplied for training.
+ *The training data that you supplied.
*/ Input?: TrainingData; /** * @public - *The images (assets) that were actually trained by Amazon Rekognition Custom Labels.
+ *Reference to images (assets) that were actually used during training with trained model + * predictions.
*/ Output?: TrainingData; /** * @public - *The location of the data validation manifest. The data validation manifest is created for the training dataset during model training.
+ *A manifest that you supplied for training, with validation results for each + * line.
*/ Validation?: ValidationData; } /** * @public - *A description of a version of an Amazon Rekognition Custom Labels model.
+ *A description of a version of a Amazon Rekognition project version.
*/ export interface ProjectVersionDescription { /** * @public - *The Amazon Resource Name (ARN) of the model version.
+ *The Amazon Resource Name (ARN) of the project version.
*/ ProjectVersionArn?: string; @@ -3892,8 +4003,8 @@ export interface ProjectVersionDescription { /** * @public - *The minimum number of inference units used by the model. For more information, - * see StartProjectVersion.
+ *The minimum number of inference units used by the model. Applies only to Custom Labels + * projects. For more information, see StartProjectVersion.
*/ MinInferenceUnits?: number; @@ -3961,8 +4072,8 @@ export interface ProjectVersionDescription { /** * @public - *The maximum number of inference units Amazon Rekognition Custom Labels uses to auto-scale the model. - * For more information, see StartProjectVersion.
+ *The maximum number of inference units Amazon Rekognition uses to auto-scale the model. Applies + * only to Custom Labels projects. For more information, see StartProjectVersion.
*/ MaxInferenceUnits?: number; @@ -3971,6 +4082,30 @@ export interface ProjectVersionDescription { *If the model version was copied from a different project, SourceProjectVersionArn contains the ARN of the source model version.
A user-provided description of the project version.
+ */ + VersionDescription?: string; + + /** + * @public + *The feature that was customized.
+ */ + Feature?: CustomizationFeature | string; + + /** + * @public + *The base detection model version used to create the project version.
+ */ + BaseModelVersion?: string; + + /** + * @public + *Feature specific configuration that was applied during training.
+ */ + FeatureConfig?: CustomizationFeatureConfig; } /** @@ -3979,15 +4114,15 @@ export interface ProjectVersionDescription { export interface DescribeProjectVersionsResponse { /** * @public - *A list of model descriptions. The list is sorted by the creation date and time of - * the model versions, latest to earliest.
+ *A list of project version descriptions. The list is sorted by the creation date and + * time of the project versions, latest to earliest.
*/ ProjectVersionDescriptions?: ProjectVersionDescription[]; /** * @public *If the previous response was incomplete (because there is more - * results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. + * results to retrieve), Amazon Rekognition returns a pagination token in the response. * You can use this pagination token to retrieve the next set of results.
*/ NextToken?: string; @@ -4130,7 +4265,10 @@ export interface DescribeStreamProcessorResponse { export interface DetectCustomLabelsRequest { /** * @public - *The ARN of the model version that you want to use.
+ *The ARN of the model version that you want to use. Only models associated with Custom + * Labels projects accepted by the operation. If a provided ARN refers to a model version + * associated with a project for a different feature type, then an InvalidParameterException + * is returned.
*/ ProjectVersionArn: string | undefined; @@ -4802,6 +4940,13 @@ export interface DetectModerationLabelsRequest { * will be sent to. */ HumanLoopConfig?: HumanLoopConfig; + + /** + * @public + *Identifier for the custom adapter. Expects the ProjectVersionArn as a value. + * Use the CreateProject or CreateProjectVersion APIs to create a custom adapter.
+ */ + ProjectVersion?: string; } /** @@ -4843,7 +4988,7 @@ export interface DetectModerationLabelsResponse { /** * @public - *Version number of the moderation detection model that was used to detect unsafe + *
Version number of the base moderation detection model that was used to detect unsafe * content.
*/ ModerationModelVersion?: string; @@ -4853,6 +4998,14 @@ export interface DetectModerationLabelsResponse { *Shows the results of the human in the loop evaluation.
*/ HumanLoopActivationOutput?: HumanLoopActivationOutput; + + /** + * @public + *Identifier of the custom adapter that was used during inference. If + * during inference the adapter was EXPIRED, then the parameter will not be returned, + * indicating that a base moderation detection project version was used.
+ */ + ProjectVersion?: string; } /** @@ -8125,140 +8278,6 @@ export interface SearchedFaceDetails { FaceDetail?: FaceDetail; } -/** - * @public - * @enum - */ -export const UnsearchedFaceReason = { - EXCEEDS_MAX_FACES: "EXCEEDS_MAX_FACES", - EXTREME_POSE: "EXTREME_POSE", - FACE_NOT_LARGEST: "FACE_NOT_LARGEST", - LOW_BRIGHTNESS: "LOW_BRIGHTNESS", - LOW_CONFIDENCE: "LOW_CONFIDENCE", - LOW_FACE_QUALITY: "LOW_FACE_QUALITY", - LOW_SHARPNESS: "LOW_SHARPNESS", - SMALL_BOUNDING_BOX: "SMALL_BOUNDING_BOX", -} as const; - -/** - * @public - */ -export type UnsearchedFaceReason = (typeof UnsearchedFaceReason)[keyof typeof UnsearchedFaceReason]; - -/** - * @public - *Face details inferred from the image but not used for search. The response attribute - * contains reasons for why a face wasn't used for Search.
- */ -export interface UnsearchedFace { - /** - * @public - *Structure containing attributes of the face that the algorithm detected.
- *A FaceDetail object contains either the default facial attributes or all
- * facial attributes. The default attributes are BoundingBox,
- * Confidence, Landmarks, Pose, and
- * Quality.
- * GetFaceDetection is the only Amazon Rekognition Video stored video operation that can
- * return a FaceDetail object with all attributes. To specify which attributes to
- * return, use the FaceAttributes input parameter for StartFaceDetection. The following Amazon Rekognition Video operations return only the default
- * attributes. The corresponding Start operations don't have a FaceAttributes input
- * parameter:
GetCelebrityRecognition
- *GetPersonTracking
- *GetFaceSearch
- *The Amazon Rekognition Image DetectFaces and IndexFaces operations
- * can return all facial attributes. To specify which attributes to return, use the
- * Attributes input parameter for DetectFaces. For
- * IndexFaces, use the DetectAttributes input parameter.
Reasons why a face wasn't used for Search.
- */ - Reasons?: (UnsearchedFaceReason | string)[]; -} - -/** - * @public - */ -export interface SearchUsersByImageResponse { - /** - * @public - *An array of UserID objects that matched the input face, along with the confidence in the - * match. The returned structure will be empty if there are no matches. Returned if the - * SearchUsersByImageResponse action is successful.
- */ - UserMatches?: UserMatch[]; - - /** - * @public - *Version number of the face detection model associated with the input collection - * CollectionId.
- */ - FaceModelVersion?: string; - - /** - * @public - *A list of FaceDetail objects containing the BoundingBox for the largest face in image, as - * well as the confidence in the bounding box, that was searched for matches. If no valid face is - * detected in the image the response will contain no SearchedFace object.
- */ - SearchedFace?: SearchedFaceDetails; - - /** - * @public - *List of UnsearchedFace objects. Contains the face details infered from the specified image - * but not used for search. Contains reasons that describe why a face wasn't used for Search. - *
- */ - UnsearchedFaces?: UnsearchedFace[]; -} - -/** - * @public - */ -export interface StartCelebrityRecognitionRequest { - /** - * @public - *The video in which you want to recognize celebrities. The video must be stored - * in an Amazon S3 bucket.
- */ - Video: Video | undefined; - - /** - * @public - *Idempotent token used to identify the start request. If you use the same token with multiple
- * StartCelebrityRecognition requests, the same JobId is returned. Use
- * ClientRequestToken to prevent the same job from being accidently started more than once.
The Amazon SNS topic ARN that you want Amazon Rekognition Video to publish the completion status of the - * celebrity recognition analysis to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.
- */ - NotificationChannel?: NotificationChannel; - - /** - * @public - *An identifier you specify that's returned in the completion notification that's published to your Amazon Simple Notification Service topic.
- * For example, you can use JobTag to group related jobs and identify them in the completion notification.
Face details inferred from the image but not used for search. The response attribute + * contains reasons for why a face wasn't used for Search.
+ */ +export interface UnsearchedFace { + /** + * @public + *Structure containing attributes of the face that the algorithm detected.
+ *A FaceDetail object contains either the default facial attributes or all
+ * facial attributes. The default attributes are BoundingBox,
+ * Confidence, Landmarks, Pose, and
+ * Quality.
+ * GetFaceDetection is the only Amazon Rekognition Video stored video operation that can
+ * return a FaceDetail object with all attributes. To specify which attributes to
+ * return, use the FaceAttributes input parameter for StartFaceDetection. The following Amazon Rekognition Video operations return only the default
+ * attributes. The corresponding Start operations don't have a FaceAttributes input
+ * parameter:
GetCelebrityRecognition
+ *GetPersonTracking
+ *GetFaceSearch
+ *The Amazon Rekognition Image DetectFaces and IndexFaces operations
+ * can return all facial attributes. To specify which attributes to return, use the
+ * Attributes input parameter for DetectFaces. For
+ * IndexFaces, use the DetectAttributes input parameter.
Reasons why a face wasn't used for Search.
+ */ + Reasons?: (UnsearchedFaceReason | string)[]; +} + +/** + * @public + */ +export interface SearchUsersByImageResponse { + /** + * @public + *An array of UserID objects that matched the input face, along with the confidence in the + * match. The returned structure will be empty if there are no matches. Returned if the + * SearchUsersByImageResponse action is successful.
+ */ + UserMatches?: UserMatch[]; + + /** + * @public + *Version number of the face detection model associated with the input collection + * CollectionId.
+ */ + FaceModelVersion?: string; + + /** + * @public + *A list of FaceDetail objects containing the BoundingBox for the largest face in image, as + * well as the confidence in the bounding box, that was searched for matches. If no valid face is + * detected in the image the response will contain no SearchedFace object.
+ */ + SearchedFace?: SearchedFaceDetails; + + /** + * @public + *List of UnsearchedFace objects. Contains the face details infered from the specified image + * but not used for search. Contains reasons that describe why a face wasn't used for Search. + *
+ */ + UnsearchedFaces?: UnsearchedFace[]; +} + +/** + * @public + */ +export interface StartCelebrityRecognitionRequest { + /** + * @public + *The video in which you want to recognize celebrities. The video must be stored + * in an Amazon S3 bucket.
+ */ + Video: Video | undefined; + + /** + * @public + *Idempotent token used to identify the start request. If you use the same token with multiple
+ * StartCelebrityRecognition requests, the same JobId is returned. Use
+ * ClientRequestToken to prevent the same job from being accidently started more than once.
The Amazon SNS topic ARN that you want Amazon Rekognition Video to publish the completion status of the + * celebrity recognition analysis to. The Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy.
+ */ + NotificationChannel?: NotificationChannel; + + /** + * @public + *An identifier you specify that's returned in the completion notification that's published to your Amazon Simple Notification Service topic.
+ * For example, you can use JobTag to group related jobs and identify them in the completion notification.
The minimum number of inference units to use. A single * inference unit represents 1 hour of processing.
- *For information about the number - * of transactions per second (TPS) that an inference unit can support, see - * Running a trained Amazon Rekognition Custom Labels model in the - * Amazon Rekognition Custom Labels Guide. - *
*Use a higher number to increase the TPS throughput of your model. You are charged for the number * of inference units that you use. *
@@ -670,7 +802,7 @@ export interface StartTextDetectionResponse { export interface StopProjectVersionRequest { /** * @public - *The Amazon Resource Name (ARN) of the model version that you want to delete.
+ *The Amazon Resource Name (ARN) of the model version that you want to stop.
*This operation requires permissions to perform the rekognition:StopProjectVersion action.
Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The source and\n destination projects can be in different AWS accounts but must be in the same AWS Region.\n You can't copy a model to another AWS service.\n \n
\nTo copy a model version to a different AWS account, you need to create a resource-based policy known as a\n project policy. You attach the project policy to the\n source project by calling PutProjectPolicy. The project policy\n gives permission to copy the model version from a trusting AWS account to a trusted account.
\nFor more information creating and attaching a project policy, see Attaching a project policy (SDK)\n in the Amazon Rekognition Custom Labels Developer Guide.\n
\nIf you are copying a model version to a project in the same AWS account, you don't need to create a project policy.
\nTo copy a model, the destination project, source project, and source model version must already exist.
\nCopying a model version takes a while to complete. To get the current status, call DescribeProjectVersions and check the value of Status in the\n ProjectVersionDescription object. The copy operation has finished when\n the value of Status is COPYING_COMPLETED.
This operation requires permissions to perform the rekognition:CopyProjectVersion action.
This operation applies only to Amazon Rekognition Custom Labels.
\nCopies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The source and\n destination projects can be in different AWS accounts but must be in the same AWS Region.\n You can't copy a model to another AWS service.\n \n
\nTo copy a model version to a different AWS account, you need to create a resource-based policy known as a\n project policy. You attach the project policy to the\n source project by calling PutProjectPolicy. The project policy\n gives permission to copy the model version from a trusting AWS account to a trusted account.
\nFor more information creating and attaching a project policy, see Attaching a project policy (SDK)\n in the Amazon Rekognition Custom Labels Developer Guide.\n
\nIf you are copying a model version to a project in the same AWS account, you don't need to create a project policy.
\nCopying project versions is supported only for Custom Labels models.
\nTo copy a model, the destination project, source project, and source model version\n must already exist.
\nCopying a model version takes a while to complete. To get the current status, call DescribeProjectVersions and check the value of Status in the\n ProjectVersionDescription object. The copy operation has finished when\n the value of Status is COPYING_COMPLETED.
This operation requires permissions to perform the rekognition:CopyProjectVersion action.
Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using\n an Amazon Sagemaker format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset.
\nTo create a training dataset for a project, specify TRAIN for the value of \n DatasetType. To create the test dataset for a project,\n specify TEST for the value of DatasetType.\n
The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset.\n Creating a dataset takes a while to complete. Use DescribeDataset to check the \n current status. The dataset created successfully if the value of Status is\n CREATE_COMPLETE.
To check if any non-terminal errors occurred, call ListDatasetEntries\nand check for the presence of errors lists in the JSON Lines.
Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). \n Currently, you can't access the terminal error information.\n \n
For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide.
\nThis operation requires permissions to perform the rekognition:CreateDataset action.\n If you want to copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries action.
This operation applies only to Amazon Rekognition Custom Labels.
\nCreates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using\n an Amazon Sagemaker format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset.
\nTo create a training dataset for a project, specify TRAIN for the value of \n DatasetType. To create the test dataset for a project,\n specify TEST for the value of DatasetType.\n
The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset.\n Creating a dataset takes a while to complete. Use DescribeDataset to check the \n current status. The dataset created successfully if the value of Status is\n CREATE_COMPLETE.
To check if any non-terminal errors occurred, call ListDatasetEntries\nand check for the presence of errors lists in the JSON Lines.
Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). \n Currently, you can't access the terminal error information.\n \n
For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide.
\nThis operation requires permissions to perform the rekognition:CreateDataset action.\n If you want to copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries action.
Creates a new Amazon Rekognition Custom Labels project. A project is a group of resources (datasets, model versions) \n that you use to create and manage Amazon Rekognition Custom Labels models.
\nThis operation requires permissions to perform the rekognition:CreateProject action.
Creates a new Amazon Rekognition project. A project is a group of resources (datasets, model\n versions) that you use to create and manage a Amazon Rekognition Custom Labels Model or custom adapter. You can\n specify a feature to create the project with, if no feature is specified then Custom Labels\n is used by default. For adapters, you can also choose whether or not to have the project\n auto update by using the AutoUpdate argument. This operation requires permissions to\n perform the rekognition:CreateProject action.
The name of the project to create.
", "smithy.api#required": {} } + }, + "Feature": { + "target": "com.amazonaws.rekognition#CustomizationFeature", + "traits": { + "smithy.api#documentation": "Specifies feature that is being customized. If no value is provided CUSTOM_LABELS is used as a default.
" + } + }, + "AutoUpdate": { + "target": "com.amazonaws.rekognition#ProjectAutoUpdate", + "traits": { + "smithy.api#documentation": "Specifies whether automatic retraining should be attempted for the versions of the\n project. Automatic retraining is done as a best effort. Required argument for Content\n Moderation. Applicable only to adapters.
" + } } }, "traits": { @@ -1737,7 +1745,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a new version of a model and begins training. \n Models are managed as part of an Amazon Rekognition Custom Labels project. \n The response from CreateProjectVersion\n is an Amazon Resource Name (ARN) for the version of the model.
Training uses the training and test datasets associated with the project. \n For more information, see Creating training and test dataset in the Amazon Rekognition Custom Labels Developer Guide.\n
\nYou can train a model in a project that doesn't have associated datasets by specifying manifest files in the\n TrainingData and TestingData fields.\n
If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates\n the datasets for you using the most recent manifest files. You can no longer train\n a model version for the project by specifying manifest files.
\nInstead of training with a project without associated datasets,\n we recommend that you use the manifest\n files to create training and test datasets for the project.
\nTraining takes a while to complete. You can get the current status by calling\n DescribeProjectVersions. Training completed successfully if\n the value of the Status field is TRAINING_COMPLETED.
If training \n fails, see Debugging a failed model training in the Amazon Rekognition Custom Labels developer guide.
\nOnce training has successfully completed, call DescribeProjectVersions to\n get the training results and evaluate the model. For more information, see Improving a trained Amazon Rekognition Custom Labels model\n in the Amazon Rekognition Custom Labels developers guide.\n
\nAfter evaluating the model, you start the model\n by calling StartProjectVersion.
\nThis operation requires permissions to perform the rekognition:CreateProjectVersion action.
Creates a new version of Amazon Rekognition project (like a Custom Labels model or a custom adapter)\n and begins training. Models and adapters are managed as part of a Rekognition project. The\n response from CreateProjectVersion is an Amazon Resource Name (ARN) for the\n project version.
The FeatureConfig operation argument allows you to configure specific model or adapter\n settings. You can provide a description to the project version by using the\n VersionDescription argment. Training can take a while to complete. You can get the current\n status by calling DescribeProjectVersions. Training completed\n successfully if the value of the Status field is\n TRAINING_COMPLETED. Once training has successfully completed, call DescribeProjectVersions to get the training results and evaluate the\n model.
This operation requires permissions to perform the\n rekognition:CreateProjectVersion action.
\n The following applies only to projects with Amazon Rekognition Custom Labels as the chosen\n feature:\n
\nYou can train a model in a project that doesn't have associated datasets by specifying manifest files in the\n TrainingData and TestingData fields.\n
If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates\n the datasets for you using the most recent manifest files. You can no longer train\n a model version for the project by specifying manifest files.
\nInstead of training with a project without associated datasets,\n we recommend that you use the manifest\n files to create training and test datasets for the project.
\nThe ARN of the Amazon Rekognition Custom Labels project that \n manages the model that you want to train.
", + "smithy.api#documentation": "The ARN of the Amazon Rekognition project that will manage the project version you want to\n train.
", "smithy.api#required": {} } }, "VersionName": { "target": "com.amazonaws.rekognition#VersionName", "traits": { - "smithy.api#documentation": "A name for the version of the model. This value must be unique.
", + "smithy.api#documentation": "A name for the version of the project version. This value must be unique.
", "smithy.api#required": {} } }, "OutputConfig": { "target": "com.amazonaws.rekognition#OutputConfig", "traits": { - "smithy.api#documentation": "The Amazon S3 bucket location to store the results of training.\n The S3 bucket can be in any AWS account as long as the caller has\n s3:PutObject permissions on the S3 bucket.
The Amazon S3 bucket location to store the results of training. The bucket can be any S3\n bucket in your AWS account. You need s3:PutObject permission on the bucket.\n
Specifies an external manifest that the services uses to train the model.\n If you specify TrainingData you must also specify TestingData.\n The project must not have any associated datasets.\n
Specifies an external manifest that the services uses to train the project version.\n If you specify TrainingData you must also specify TestingData.\n The project must not have any associated datasets.
Specifies an external manifest that the service uses to test the model.\n If you specify TestingData you must also specify TrainingData.\n The project must not have any associated datasets.
Specifies an external manifest that the service uses to test the project version. If\n you specify TestingData you must also specify TrainingData. The\n project must not have any associated datasets.
A set of tags (key-value pairs) that you want to attach to the model.
" + "smithy.api#documentation": "A set of tags (key-value pairs) that you want to attach to the project version.
" } }, "KmsKeyId": { "target": "com.amazonaws.rekognition#KmsKeyId", "traits": { - "smithy.api#documentation": "The identifier for your AWS Key Management Service key (AWS KMS key).\n You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key,\n an alias for your KMS key, or an alias ARN.\n The key is used to encrypt training and test images copied into the service for model training.\n Your source images are unaffected. The key is also used to encrypt training results\n and manifest files written to the output Amazon S3 bucket (OutputConfig).
If you choose to use your own KMS key, you need the following permissions on the KMS key.
\nkms:CreateGrant
\nkms:DescribeKey
\nkms:GenerateDataKey
\nkms:Decrypt
\nIf you don't specify a value for KmsKeyId, images copied into the service are encrypted\n using a key that AWS owns and manages.
The identifier for your AWS Key Management Service key (AWS KMS key). You can supply\n the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for\n your KMS key, or an alias ARN. The key is used to encrypt training images, test images, and manifest files copied\n into the service for the project version. Your source images are unaffected. The\n key is also used to encrypt training results and manifest files written to the output Amazon S3\n bucket (OutputConfig).
If you choose to use your own KMS key, you need the following permissions on the KMS key.
\nkms:CreateGrant
\nkms:DescribeKey
\nkms:GenerateDataKey
\nkms:Decrypt
\nIf you don't specify a value for KmsKeyId, images copied into the service are encrypted\n using a key that AWS owns and manages.
A description applied to the project version being created.
" + } + }, + "FeatureConfig": { + "target": "com.amazonaws.rekognition#CustomizationFeatureConfig", + "traits": { + "smithy.api#documentation": "Feature-specific configuration of the training job. If the job configuration does not match the feature type associated with the project, an InvalidParameterException is returned.
" } } }, @@ -1816,7 +1836,7 @@ "ProjectVersionArn": { "target": "com.amazonaws.rekognition#ProjectVersionArn", "traits": { - "smithy.api#documentation": "The ARN of the model version that was created. Use DescribeProjectVersion\n to get the current status of the training operation.
The ARN of the model or the project version that was created. Use\n DescribeProjectVersion to get the current status of the training\n operation.
Configuration options for Custom Moderation training.
" + } + } + }, + "traits": { + "smithy.api#documentation": "Feature specific configuration for the training job. Configuration provided for the job must match \n the feature type parameter associated with project. If configuration \n and feature type do not match an InvalidParameterException is returned.
" + } + }, + "com.amazonaws.rekognition#CustomizationFeatureContentModerationConfig": { + "type": "structure", + "members": { + "ConfidenceThreshold": { + "target": "com.amazonaws.rekognition#Percent", + "traits": { + "smithy.api#documentation": "The confidence level you plan to use to identify if unsafe content is present during inference.
" + } + } + }, + "traits": { + "smithy.api#documentation": "Configuration options for Content Moderation training.
" + } + }, + "com.amazonaws.rekognition#CustomizationFeatures": { + "type": "list", + "member": { + "target": "com.amazonaws.rekognition#CustomizationFeature" + }, + "traits": { + "smithy.api#length": { + "min": 1, + "max": 2 + } + } + }, "com.amazonaws.rekognition#DatasetArn": { "type": "string", "traits": { @@ -2524,7 +2601,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes an existing Amazon Rekognition Custom Labels dataset.\n Deleting a dataset might take while. Use DescribeDataset to check the \n current status. The dataset is still deleting if the value of Status is\n DELETE_IN_PROGRESS. If you try to access the dataset after it is deleted, you get\n a ResourceNotFoundException exception.\n\n
You can't delete a dataset while it is creating (Status = CREATE_IN_PROGRESS)\n or if the dataset is updating (Status = UPDATE_IN_PROGRESS).
This operation requires permissions to perform the rekognition:DeleteDataset action.
This operation applies only to Amazon Rekognition Custom Labels.
\nDeletes an existing Amazon Rekognition Custom Labels dataset.\n Deleting a dataset might take while. Use DescribeDataset to check the \n current status. The dataset is still deleting if the value of Status is\n DELETE_IN_PROGRESS. If you try to access the dataset after it is deleted, you get\n a ResourceNotFoundException exception.\n\n
You can't delete a dataset while it is creating (Status = CREATE_IN_PROGRESS)\n or if the dataset is updating (Status = UPDATE_IN_PROGRESS).
This operation requires permissions to perform the rekognition:DeleteDataset action.
Deletes an Amazon Rekognition Custom Labels project. To delete a project you must first delete all models associated \n with the project. To delete a model, see DeleteProjectVersion.
\n\n DeleteProject is an asynchronous operation. To check if the project is\n deleted, call DescribeProjects. The project is deleted when the project\n no longer appears in the response. Be aware that deleting a given project will also delete\n any ProjectPolicies associated with that project.
This operation requires permissions to perform the\n rekognition:DeleteProject action.
Deletes a Amazon Rekognition project. To delete a project you must first delete all models or\n adapters associated with the project. To delete a model or adapter, see DeleteProjectVersion.
\n\n DeleteProject is an asynchronous operation. To check if the project is\n deleted, call DescribeProjects. The project is deleted when the project\n no longer appears in the response. Be aware that deleting a given project will also delete\n any ProjectPolicies associated with that project.
This operation requires permissions to perform the\n rekognition:DeleteProject action.
Deletes an existing project policy.
\nTo get a list of project policies attached to a project, call ListProjectPolicies. To attach a project policy to a project, call PutProjectPolicy.
\nThis operation requires permissions to perform the rekognition:DeleteProjectPolicy action.
This operation applies only to Amazon Rekognition Custom Labels.
\nDeletes an existing project policy.
\nTo get a list of project policies attached to a project, call ListProjectPolicies. To attach a project policy to a project, call PutProjectPolicy.
\nThis operation requires permissions to perform the rekognition:DeleteProjectPolicy action.
Deletes an Amazon Rekognition Custom Labels model.
\nYou can't delete a model if it is running or if it is training. \n To check the status of a model, use the Status field returned\n from DescribeProjectVersions.\n To stop a running model call StopProjectVersion. If the model\n is training, wait until it finishes.
This operation requires permissions to perform the\n rekognition:DeleteProjectVersion action.
Deletes a Rekognition project model or project version, like a Amazon Rekognition Custom Labels model or a custom\n adapter.
\nYou can't delete a project version if it is running or if it is training. To check\n the status of a project version, use the Status field returned from DescribeProjectVersions. To stop a project version call StopProjectVersion. If the project version is training, wait until it\n finishes.
\nThis operation requires permissions to perform the\n rekognition:DeleteProjectVersion action.
The Amazon Resource Name (ARN) of the model version that you want to delete.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the project version that you want to\n delete.
", "smithy.api#required": {} } } @@ -3140,7 +3213,7 @@ } ], "traits": { - "smithy.api#documentation": "\nDescribes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a dataset and\nstatistics about the images and labels in a dataset. \n
\nThis operation requires permissions to perform the rekognition:DescribeDataset action.
This operation applies only to Amazon Rekognition Custom Labels.
\n\nDescribes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a dataset and\nstatistics about the images and labels in a dataset. \n
\nThis operation requires permissions to perform the rekognition:DescribeDataset action.
Lists and describes the versions of a model in an Amazon Rekognition Custom Labels project. You \n can specify up to 10 model versions in ProjectVersionArns. If\n 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\n action.
Lists and describes the versions of an Amazon Rekognition project. You can specify up to 10 model or\n adapter versions in ProjectVersionArns. If you don't specify a value,\n descriptions for all model/adapter versions in the project are returned.
This operation requires permissions to perform the rekognition:DescribeProjectVersions\n action.
The Amazon Resource Name (ARN) of the project that contains the models you want to describe.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the project that contains the model/adapter you want\n to describe.
", "smithy.api#required": {} } }, "VersionNames": { "target": "com.amazonaws.rekognition#VersionNames", "traits": { - "smithy.api#documentation": "A list of model version names that you want to describe. You can add up to 10 model version names\n to the list. If you don't specify a value, all model descriptions are returned. A version name is part of a\n model (ProjectVersion) ARN. For example, my-model.2020-01-21T09.10.15 is the version name in the following ARN.\n arn:aws:rekognition:us-east-1:123456789012:project/getting-started/version/my-model.2020-01-21T09.10.15/1234567890123.
A list of model or project version names that you want to describe. You can add\n up to 10 model or project version names to the list. If you don't specify a value, all\n project version descriptions are returned. A version name is part of a project version ARN. For example, my-model.2020-01-21T09.10.15 is\n the version name in the following ARN.\n arn:aws:rekognition:us-east-1:123456789012:project/getting-started/version/my-model.2020-01-21T09.10.15/1234567890123.
If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. \n You can use this pagination token to retrieve the next set of results.
" + "smithy.api#documentation": "If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition returns a pagination token in the response. \n You can use this pagination token to retrieve the next set of results.
" } }, "MaxResults": { @@ -3306,13 +3379,13 @@ "ProjectVersionDescriptions": { "target": "com.amazonaws.rekognition#ProjectVersionDescriptions", "traits": { - "smithy.api#documentation": "A list of model descriptions. The list is sorted by the creation date and time of\n the model versions, latest to earliest.
" + "smithy.api#documentation": "A list of project version descriptions. The list is sorted by the creation date and\n time of the project versions, latest to earliest.
" } }, "NextToken": { "target": "com.amazonaws.rekognition#ExtendedPaginationToken", "traits": { - "smithy.api#documentation": "If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. \n You can use this pagination token to retrieve the next set of results.
" + "smithy.api#documentation": "If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition returns a pagination token in the response. \n You can use this pagination token to retrieve the next set of results.
" } } }, @@ -3349,7 +3422,7 @@ } ], "traits": { - "smithy.api#documentation": "Gets information about your Amazon Rekognition Custom Labels projects.
\nThis operation requires permissions to perform the rekognition:DescribeProjects action.
Gets information about your Rekognition projects.
\nThis operation requires permissions to perform the rekognition:DescribeProjects action.
If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. You can use this pagination \n token to retrieve the next set of results.
" + "smithy.api#documentation": "If the previous response was incomplete (because there is more\n results to retrieve), Rekognition returns a pagination token in the response. You can use this pagination \n token to retrieve the next set of results.
" } }, "MaxResults": { @@ -3376,7 +3449,13 @@ "ProjectNames": { "target": "com.amazonaws.rekognition#ProjectNames", "traits": { - "smithy.api#documentation": "A list of the projects that you want Amazon Rekognition Custom Labels to describe. If you don't specify a value, \n the response includes descriptions for all the projects in your AWS account.
" + "smithy.api#documentation": "A list of the projects that you want Rekognition to describe. If you don't specify a value, \n the response includes descriptions for all the projects in your AWS account.
" + } + }, + "Features": { + "target": "com.amazonaws.rekognition#CustomizationFeatures", + "traits": { + "smithy.api#documentation": "Specifies the type of customization to filter projects by. If no value is specified, \n CUSTOM_LABELS is used as a default.
" } } }, @@ -3396,7 +3475,7 @@ "NextToken": { "target": "com.amazonaws.rekognition#ExtendedPaginationToken", "traits": { - "smithy.api#documentation": "If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition Custom Labels returns a pagination token in the response. \n You can use this pagination token to retrieve the next set of results.
" + "smithy.api#documentation": "If the previous response was incomplete (because there is more\n results to retrieve), Amazon Rekognition returns a pagination token in the response. \n You can use this pagination token to retrieve the next set of results.
" } } }, @@ -3584,7 +3663,7 @@ } ], "traits": { - "smithy.api#documentation": "Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model.
\nYou specify which version of a model version to use by using the ProjectVersionArn input\n parameter.
You pass the input image as base64-encoded image bytes or as a reference to an image in\n an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing\n image bytes is not supported. The image must be either a PNG or JPEG formatted file.
\n For each object that the model version detects on an image, the API returns a \n (CustomLabel) object in an array (CustomLabels).\n Each CustomLabel object provides the label name (Name), the level\n of confidence that the image contains the object (Confidence), and \n object location information, if it exists, for the label on the image (Geometry).
To filter labels that are returned, specify a value for MinConfidence.\n DetectCustomLabelsLabels only returns labels with a confidence that's higher than\n the specified value.\n\n The value of MinConfidence maps to the assumed threshold values\n created during training. For more information, see Assumed threshold\n in the Amazon Rekognition Custom Labels Developer Guide. \n Amazon Rekognition Custom Labels metrics expresses an assumed threshold as a floating point value between 0-1. The range of\n MinConfidence normalizes the threshold value to a percentage value (0-100). Confidence\n responses from DetectCustomLabels are also returned as a percentage. \n You can use MinConfidence to change the precision and recall or your model. \n For more information, see \n Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.
If you don't specify a value for MinConfidence, DetectCustomLabels\n returns labels based on the assumed threshold of each label.
This is a stateless API operation. That is, the operation does not persist any\n data.
\nThis operation requires permissions to perform the\n rekognition:DetectCustomLabels action.
For more information, see \n Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.
", + "smithy.api#documentation": "This operation applies only to Amazon Rekognition Custom Labels.
\nDetects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model.
\nYou specify which version of a model version to use by using the ProjectVersionArn input\n parameter.
You pass the input image as base64-encoded image bytes or as a reference to an image in\n an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing\n image bytes is not supported. The image must be either a PNG or JPEG formatted file.
\n For each object that the model version detects on an image, the API returns a \n (CustomLabel) object in an array (CustomLabels).\n Each CustomLabel object provides the label name (Name), the level\n of confidence that the image contains the object (Confidence), and \n object location information, if it exists, for the label on the image (Geometry).
To filter labels that are returned, specify a value for MinConfidence.\n DetectCustomLabelsLabels only returns labels with a confidence that's higher than\n the specified value.\n\n The value of MinConfidence maps to the assumed threshold values\n created during training. For more information, see Assumed threshold\n in the Amazon Rekognition Custom Labels Developer Guide. \n Amazon Rekognition Custom Labels metrics expresses an assumed threshold as a floating point value between 0-1. The range of\n MinConfidence normalizes the threshold value to a percentage value (0-100). Confidence\n responses from DetectCustomLabels are also returned as a percentage. \n You can use MinConfidence to change the precision and recall or your model. \n For more information, see \n Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.
If you don't specify a value for MinConfidence, DetectCustomLabels\n returns labels based on the assumed threshold of each label.
This is a stateless API operation. That is, the operation does not persist any\n data.
\nThis operation requires permissions to perform the\n rekognition:DetectCustomLabels action.
For more information, see \n Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.
", "smithy.api#examples": [ { "title": "To detect custom labels in an image with an Amazon Rekognition Custom Labels model", @@ -3622,7 +3701,7 @@ "ProjectVersionArn": { "target": "com.amazonaws.rekognition#ProjectVersionArn", "traits": { - "smithy.api#documentation": "The ARN of the model version that you want to use.
", + "smithy.api#documentation": "The ARN of the model version that you want to use. Only models associated with Custom\n Labels projects accepted by the operation. If a provided ARN refers to a model version\n associated with a project for a different feature type, then an InvalidParameterException\n is returned.
", "smithy.api#required": {} } }, @@ -4148,12 +4227,18 @@ { "target": "com.amazonaws.rekognition#ProvisionedThroughputExceededException" }, + { + "target": "com.amazonaws.rekognition#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.rekognition#ResourceNotReadyException" + }, { "target": "com.amazonaws.rekognition#ThrottlingException" } ], "traits": { - "smithy.api#documentation": "Detects unsafe content in a specified JPEG or PNG format image. Use\n DetectModerationLabels to moderate images depending on your requirements. For\n example, you might want to filter images that contain nudity, but not images containing\n suggestive content.
To filter images, use the labels returned by DetectModerationLabels to\n determine which types of content are appropriate.
For information about moderation labels, see Detecting Unsafe Content in the\n Amazon Rekognition Developer Guide.
\nYou pass the input image either as base64-encoded image bytes or as a reference to an\n image in an Amazon S3 bucket. If you use the\n AWS\n CLI to call Amazon Rekognition operations, passing image bytes is not\n supported. The image must be either a PNG or JPEG formatted file.
" + "smithy.api#documentation": "Detects unsafe content in a specified JPEG or PNG format image. Use\n DetectModerationLabels to moderate images depending on your requirements. For\n example, you might want to filter images that contain nudity, but not images containing\n suggestive content.
To filter images, use the labels returned by DetectModerationLabels to\n determine which types of content are appropriate.
For information about moderation labels, see Detecting Unsafe Content in the\n Amazon Rekognition Developer Guide.
\nYou pass the input image either as base64-encoded image bytes or as a reference to an\n image in an Amazon S3 bucket. If you use the\n AWS\n CLI to call Amazon Rekognition operations, passing image bytes is not\n supported. The image must be either a PNG or JPEG formatted file.
\nYou can specify an adapter to use when retrieving label predictions by providing a\n ProjectVersionArn to the ProjectVersion argument.
Sets up the configuration for human evaluation, including the FlowDefinition the image\n will be sent to.
" } + }, + "ProjectVersion": { + "target": "com.amazonaws.rekognition#ProjectVersionId", + "traits": { + "smithy.api#documentation": "Identifier for the custom adapter. Expects the ProjectVersionArn as a value. \n Use the CreateProject or CreateProjectVersion APIs to create a custom adapter.
" + } } }, "traits": { @@ -4195,7 +4286,7 @@ "ModerationModelVersion": { "target": "com.amazonaws.rekognition#String", "traits": { - "smithy.api#documentation": "Version number of the moderation detection model that was used to detect unsafe\n content.
" + "smithy.api#documentation": "Version number of the base moderation detection model that was used to detect unsafe\n content.
" } }, "HumanLoopActivationOutput": { @@ -4203,6 +4294,12 @@ "traits": { "smithy.api#documentation": "Shows the results of the human in the loop evaluation.
" } + }, + "ProjectVersion": { + "target": "com.amazonaws.rekognition#ProjectVersionId", + "traits": { + "smithy.api#documentation": "Identifier of the custom adapter that was used during inference. If\n during inference the adapter was EXPIRED, then the parameter will not be returned,\n indicating that a base moderation detection project version was used.
" + } } }, "traits": { @@ -4459,10 +4556,7 @@ "input": { "CollectionId": "MyCollection", "UserId": "DemoUser", - "FaceIds": [ - "f5817d37-94f6-4335-bfee-6cf79a3d806e", - "c92265d4-5f9c-43af-a58e-12be0ce02bc3" - ], + "FaceIds": ["f5817d37-94f6-4335-bfee-6cf79a3d806e", "c92265d4-5f9c-43af-a58e-12be0ce02bc3"], "ClientRequestToken": "550e8400-e29b-41d4-a716-446655440003" }, "output": { @@ -4474,9 +4568,7 @@ ], "UnsuccessfulFaceDisassociations": [ { - "Reasons": [ - "ASSOCIATED_TO_A_DIFFERENT_USER" - ], + "Reasons": ["ASSOCIATED_TO_A_DIFFERENT_USER"], "FaceId": "f5817d37-94f6-4335-bfee-6cf79a3d806e", "UserId": "demoUser1" } @@ -4621,7 +4713,7 @@ } ], "traits": { - "smithy.api#documentation": "Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a project.\n DistributeDatasetEntries moves 20% of the training dataset images to the test dataset.\n An entry is a JSON Line that describes an image.\n
You supply the Amazon Resource Names (ARN) of a project's training dataset and test dataset. \n The training dataset must contain the images that you want to split. The test dataset \n must be empty. The datasets must belong to the same project. To create training and test datasets for a project, call CreateDataset.
\nDistributing a dataset takes a while to complete. To check the status call DescribeDataset. The operation\n is complete when the Status field for the training dataset and the test dataset is UPDATE_COMPLETE. \n If the dataset split fails, the value of Status is UPDATE_FAILED.
This operation requires permissions to perform the rekognition:DistributeDatasetEntries action.
This operation applies only to Amazon Rekognition Custom Labels.
\nDistributes the entries (images) in a training dataset across the training dataset and the test dataset for a project.\n DistributeDatasetEntries moves 20% of the training dataset images to the test dataset.\n An entry is a JSON Line that describes an image.\n
You supply the Amazon Resource Names (ARN) of a project's training dataset and test dataset. \n The training dataset must contain the images that you want to split. The test dataset \n must be empty. The datasets must belong to the same project. To create training and test datasets for a project, call CreateDataset.
\nDistributing a dataset takes a while to complete. To check the status call DescribeDataset. The operation\n is complete when the Status field for the training dataset and the test dataset is UPDATE_COMPLETE. \n If the dataset split fails, the value of Status is UPDATE_FAILED.
This operation requires permissions to perform the rekognition:DistributeDatasetEntries action.
An Amazon Rekognition service limit was exceeded. For example, if you start too many Amazon Rekognition Video jobs concurrently, calls to start operations \n (StartLabelDetection, for example) will raise a LimitExceededException exception (HTTP status code: 400) until\n the number of concurrently running jobs is below the Amazon Rekognition service limit.
An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs\n concurrently, subsequent calls to start operations (ex:\n StartLabelDetection) will raise a LimitExceededException\n exception (HTTP status code: 400) until the number of concurrently running jobs is below\n the Amazon Rekognition service limit.
\nLists the entries (images) within a dataset. An entry is a\nJSON Line that contains the information for a single image, including\nthe image location, assigned labels, and object location bounding boxes. For \nmore information, see Creating a manifest file.
\nJSON Lines in the response include information about non-terminal\n errors found in the dataset. \n Non terminal errors are reported in errors lists within each JSON Line. The\n same information is reported in the training and testing validation result manifests that\n Amazon Rekognition Custom Labels creates during model training.\n
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.\n
\nThis operation requires permissions to perform the rekognition:ListDatasetEntries action.
This operation applies only to Amazon Rekognition Custom Labels.
\n\nLists the entries (images) within a dataset. An entry is a\nJSON Line that contains the information for a single image, including\nthe image location, assigned labels, and object location bounding boxes. For \nmore information, see Creating a manifest file.
\nJSON Lines in the response include information about non-terminal\n errors found in the dataset. \n Non terminal errors are reported in errors lists within each JSON Line. The\n same information is reported in the training and testing validation result manifests that\n Amazon Rekognition Custom Labels creates during model training.\n
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.\n
\nThis operation requires permissions to perform the rekognition:ListDatasetEntries action.
Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see \n Labeling images.\n
\n\n Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see Labeling images\n in the Amazon Rekognition Custom Labels Developer Guide.
", + "smithy.api#documentation": "This operation applies only to Amazon Rekognition Custom Labels.
\nLists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see \n Labeling images.\n
\n\n Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more information, see Labeling images\n in the Amazon Rekognition Custom Labels Developer Guide.
", "smithy.api#examples": [ { "title": "To list the entries in an Amazon Rekognition Custom Labels dataset", @@ -8532,7 +8620,7 @@ } ], "traits": { - "smithy.api#documentation": "Gets a list of the project policies attached to a project.
\nTo attach a project policy to a project, call PutProjectPolicy. To remove a project policy from a project, call DeleteProjectPolicy.
\nThis operation requires permissions to perform the rekognition:ListProjectPolicies action.
This operation applies only to Amazon Rekognition Custom Labels.
\nGets a list of the project policies attached to a project.
\nTo attach a project policy to a project, call PutProjectPolicy. To remove a project policy from a project, call DeleteProjectPolicy.
\nThis operation requires permissions to perform the rekognition:ListProjectPolicies action.
\n Information about the training and test datasets in the project.\n
" } + }, + "Feature": { + "target": "com.amazonaws.rekognition#CustomizationFeature", + "traits": { + "smithy.api#documentation": "Specifies the project that is being customized.
" + } + }, + "AutoUpdate": { + "target": "com.amazonaws.rekognition#ProjectAutoUpdate", + "traits": { + "smithy.api#documentation": "Indicates whether automatic retraining will be attempted for the versions of the project. Applies only to adapters.
" + } } }, "traits": { @@ -9576,7 +9693,7 @@ "ProjectVersionArn": { "target": "com.amazonaws.rekognition#ProjectVersionArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the model version.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the project version.
" } }, "CreationTimestamp": { @@ -9588,7 +9705,7 @@ "MinInferenceUnits": { "target": "com.amazonaws.rekognition#InferenceUnits", "traits": { - "smithy.api#documentation": "The minimum number of inference units used by the model. For more information,\n see StartProjectVersion.
" + "smithy.api#documentation": "The minimum number of inference units used by the model. Applies only to Custom Labels\n projects. For more information, see StartProjectVersion.
" } }, "Status": { @@ -9654,7 +9771,7 @@ "MaxInferenceUnits": { "target": "com.amazonaws.rekognition#InferenceUnits", "traits": { - "smithy.api#documentation": "The maximum number of inference units Amazon Rekognition Custom Labels uses to auto-scale the model.\n For more information, see StartProjectVersion.
" + "smithy.api#documentation": "The maximum number of inference units Amazon Rekognition uses to auto-scale the model. Applies\n only to Custom Labels projects. For more information, see StartProjectVersion.
" } }, "SourceProjectVersionArn": { @@ -9662,10 +9779,34 @@ "traits": { "smithy.api#documentation": "If the model version was copied from a different project, SourceProjectVersionArn contains the ARN of the source model version.
A user-provided description of the project version.
" + } + }, + "Feature": { + "target": "com.amazonaws.rekognition#CustomizationFeature", + "traits": { + "smithy.api#documentation": "The feature that was customized.
" + } + }, + "BaseModelVersion": { + "target": "com.amazonaws.rekognition#String", + "traits": { + "smithy.api#documentation": "The base detection model version used to create the project version.
" + } + }, + "FeatureConfig": { + "target": "com.amazonaws.rekognition#CustomizationFeatureConfig", + "traits": { + "smithy.api#documentation": "Feature specific configuration that was applied during training.
" + } } }, "traits": { - "smithy.api#documentation": "A description of a version of an Amazon Rekognition Custom Labels model.
" + "smithy.api#documentation": "A description of a version of a Amazon Rekognition project version.
" } }, "com.amazonaws.rekognition#ProjectVersionDescriptions": { @@ -9674,6 +9815,16 @@ "target": "com.amazonaws.rekognition#ProjectVersionDescription" } }, + "com.amazonaws.rekognition#ProjectVersionId": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 20, + "max": 2048 + }, + "smithy.api#pattern": "^(^arn:[a-z\\d-]+:rekognition:[a-z\\d-]+:\\d{12}:project\\/[a-zA-Z0-9_.\\-]{1,255}\\/version\\/[a-zA-Z0-9_.\\-]{1,255}\\/[0-9]+$)$" + } + }, "com.amazonaws.rekognition#ProjectVersionStatus": { "type": "enum", "members": { @@ -9748,6 +9899,18 @@ "traits": { "smithy.api#enumValue": "COPYING_FAILED" } + }, + "DEPRECATED": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "DEPRECATED" + } + }, + "EXPIRED": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "EXPIRED" + } } } }, @@ -9981,7 +10144,7 @@ } ], "traits": { - "smithy.api#documentation": "Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A\n project policy specifies that a trusted AWS account can copy a model version from a\n trusting AWS account to a project in the trusted AWS account. To copy a model version you use\n the CopyProjectVersion operation.
\nFor more information about the format of a project policy document, see Attaching a project policy (SDK)\n in the Amazon Rekognition Custom Labels Developer Guide.\n
\nThe response from PutProjectPolicy is a revision ID for the project policy.\n You can attach multiple project policies to a project. You can also update an existing\n project policy by specifying the policy revision ID of the existing policy.
To remove a project policy from a project, call DeleteProjectPolicy.\n To get a list of project policies attached to a project, call ListProjectPolicies.
\nYou copy a model version by calling CopyProjectVersion.
\nThis operation requires permissions to perform the rekognition:PutProjectPolicy action.
This operation applies only to Amazon Rekognition Custom Labels.
\nAttaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A\n project policy specifies that a trusted AWS account can copy a model version from a\n trusting AWS account to a project in the trusted AWS account. To copy a model version\n you use the CopyProjectVersion operation. Only applies to Custom Labels\n projects.
\nFor more information about the format of a project policy document, see Attaching a project policy (SDK)\n in the Amazon Rekognition Custom Labels Developer Guide.\n
\nThe response from PutProjectPolicy is a revision ID for the project policy.\n You can attach multiple project policies to a project. You can also update an existing\n project policy by specifying the policy revision ID of the existing policy.
To remove a project policy from a project, call DeleteProjectPolicy.\n To get a list of project policies attached to a project, call ListProjectPolicies.
\nYou copy a model version by calling CopyProjectVersion.
\nThis operation requires permissions to perform the rekognition:PutProjectPolicy action.
Starts the running of the version of a model. Starting a model takes a while\n to complete. To check the current state of the model, use DescribeProjectVersions.
\nOnce the model is running, you can detect custom labels in new images by calling \n DetectCustomLabels.
\nYou are charged for the amount of time that the model is running. To stop a running\n model, call StopProjectVersion.
\nFor more information, see Running a trained Amazon Rekognition Custom Labels model in the Amazon Rekognition Custom Labels Guide.
\nThis operation requires permissions to perform the \n rekognition:StartProjectVersion action.
This operation applies only to Amazon Rekognition Custom Labels.
\nStarts the running of the version of a model. Starting a model takes a while to\n complete. To check the current state of the model, use DescribeProjectVersions.
\nOnce the model is running, you can detect custom labels in new images by calling \n DetectCustomLabels.
\nYou are charged for the amount of time that the model is running. To stop a running\n model, call StopProjectVersion.
\nThis operation requires permissions to perform the \n rekognition:StartProjectVersion action.
The minimum number of inference units to use. A single\n inference unit represents 1 hour of processing.
\nFor information about the number \n of transactions per second (TPS) that an inference unit can support, see \n Running a trained Amazon Rekognition Custom Labels model in the \n Amazon Rekognition Custom Labels Guide.\n
\nUse a higher number to increase the TPS throughput of your model. You are charged for the number\n of inference units that you use.\n
", + "smithy.api#documentation": "The minimum number of inference units to use. A single\n inference unit represents 1 hour of processing.
\nUse a higher number to increase the TPS throughput of your model. You are charged for the number\n of inference units that you use.\n
", "smithy.api#required": {} } }, @@ -13493,7 +13652,7 @@ } ], "traits": { - "smithy.api#documentation": "Stops a running model. The operation might take a while to complete. To\n check the current status, call DescribeProjectVersions.
\nThis operation requires permissions to perform the rekognition:StopProjectVersion action.
This operation applies only to Amazon Rekognition Custom Labels.
\nStops a running model. The operation might take a while to complete. To check the\n current status, call DescribeProjectVersions. Only applies to Custom\n Labels projects.
\nThis operation requires permissions to perform the rekognition:StopProjectVersion action.
The Amazon Resource Name (ARN) of the model version that you want to delete.
\nThis operation requires permissions to perform the rekognition:StopProjectVersion action.
The Amazon Resource Name (ARN) of the model version that you want to stop.
\nThis operation requires permissions to perform the rekognition:StopProjectVersion action.
If specified, Amazon Rekognition Custom Labels temporarily splits the training dataset (80%) to create a test dataset (20%) for the training job.\n After training completes, the test dataset is not stored and the training dataset reverts to its previous size.
" + "smithy.api#documentation": "If specified, Rekognition splits training dataset to create a test dataset for\n the training job.
" } } }, "traits": { - "smithy.api#documentation": "The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition Custom Labels uses the\n training dataset to create a test dataset with a temporary split of the training dataset.
The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition uses the\n training dataset to create a test dataset with a temporary split of the training dataset.
Sagemaker Groundtruth format manifest files for the input, output and validation datasets that are used and created during testing.
" + "smithy.api#documentation": "Sagemaker Groundtruth format manifest files for the input, output and validation\n datasets that are used and created during testing.
" } }, "com.amazonaws.rekognition#TextDetection": { @@ -14224,7 +14383,7 @@ "Assets": { "target": "com.amazonaws.rekognition#Assets", "traits": { - "smithy.api#documentation": "A Sagemaker GroundTruth manifest file that contains the training images (assets).
" + "smithy.api#documentation": "A manifest file that contains references to the training images and ground-truth\n annotations.
" } } }, @@ -14238,24 +14397,24 @@ "Input": { "target": "com.amazonaws.rekognition#TrainingData", "traits": { - "smithy.api#documentation": "The training assets that you supplied for training.
" + "smithy.api#documentation": "The training data that you supplied.
" } }, "Output": { "target": "com.amazonaws.rekognition#TrainingData", "traits": { - "smithy.api#documentation": "The images (assets) that were actually trained by Amazon Rekognition Custom Labels.
" + "smithy.api#documentation": "Reference to images (assets) that were actually used during training with trained model\n predictions.
" } }, "Validation": { "target": "com.amazonaws.rekognition#ValidationData", "traits": { - "smithy.api#documentation": "The location of the data validation manifest. The data validation manifest is created for the training dataset during model training.
" + "smithy.api#documentation": "A manifest that you supplied for training, with validation results for each\n line.
" } } }, "traits": { - "smithy.api#documentation": "Sagemaker Groundtruth format manifest files for the input, output and validation datasets that are used and created during testing.
" + "smithy.api#documentation": "The data \n validation manifest created for the training dataset during model training.
" } }, "com.amazonaws.rekognition#UInteger": { @@ -14673,7 +14832,7 @@ } ], "traits": { - "smithy.api#documentation": "Adds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the\n information for a single image, including\n the image location, assigned labels, and object location bounding boxes. For more information, \n see Image-Level labels in manifest files and Object localization in manifest files in the Amazon Rekognition Custom Labels Developer Guide.\n
\nIf the source-ref field in the JSON line references an existing image, the existing image in the dataset\n is updated. \n 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. \n There isn't a limit to the number JSON Lines that you can change, but the size of Changes must be less\nthan 5MB.
\n UpdateDatasetEntries returns immediatly, but the dataset update might take a while to complete.\n Use DescribeDataset to check the \n current status. The dataset updated successfully if the value of Status is\n UPDATE_COMPLETE.
To check if any non-terminal errors occured, call ListDatasetEntries\n and check for the presence of errors lists in the JSON Lines.
Dataset update fails if a terminal error occurs (Status = UPDATE_FAILED). \n Currently, you can't access the terminal error information from the Amazon Rekognition Custom Labels SDK.\n
This operation requires permissions to perform the rekognition:UpdateDatasetEntries action.
This operation applies only to Amazon Rekognition Custom Labels.
\nAdds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the\n information for a single image, including\n the image location, assigned labels, and object location bounding boxes. For more information, \n see Image-Level labels in manifest files and Object localization in manifest files in the Amazon Rekognition Custom Labels Developer Guide.\n
\nIf the source-ref field in the JSON line references an existing image, the existing image in the dataset\n is updated. \n 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. \n There isn't a limit to the number JSON Lines that you can change, but the size of Changes must be less\nthan 5MB.
\n UpdateDatasetEntries returns immediatly, but the dataset update might take a while to complete.\n Use DescribeDataset to check the \n current status. The dataset updated successfully if the value of Status is\n UPDATE_COMPLETE.
To check if any non-terminal errors occured, call ListDatasetEntries\n and check for the presence of errors lists in the JSON Lines.
Dataset update fails if a terminal error occurs (Status = UPDATE_FAILED). \n Currently, you can't access the terminal error information from the Amazon Rekognition Custom Labels SDK.\n
This operation requires permissions to perform the rekognition:UpdateDatasetEntries action.
Contains the Amazon S3 bucket location of the validation data for a model training job.
\nThe validation data includes error information for individual JSON Lines in the dataset.\n For more information, see Debugging a Failed Model Training in the\n Amazon Rekognition Custom Labels Developer Guide.
\nYou get the ValidationData object for the training dataset (TrainingDataResult)\n and the test dataset (TestingDataResult) by calling DescribeProjectVersions.
The assets array contains a single Asset object. \n The GroundTruthManifest field of the Asset object contains the S3 bucket location of\n the validation data. \n
" } }, + "com.amazonaws.rekognition#VersionDescription": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 255 + }, + "smithy.api#pattern": "^[a-zA-Z0-9-_. ()':,;?]+$" + } + }, "com.amazonaws.rekognition#VersionName": { "type": "string", "traits": { @@ -15097,4 +15266,4 @@ } } } -} \ No newline at end of file +}