pub struct CreateDatasetFluentBuilder { /* private fields */ }Expand description
Fluent builder constructing a request to CreateDataset.
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, specify TEST for the value of DatasetType.
The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset. Creating a dataset takes a while to complete. Use DescribeDataset to check the current status. The dataset created successfully if the value of Status is CREATE_COMPLETE.
To check if any non-terminal errors occurred, call ListDatasetEntries and check for the presence of errors lists in the JSON Lines.
Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). Currently, you can't access the terminal error information.
For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide.
This operation requires permissions to perform the rekognition:CreateDataset action. If you want to copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries action.
Implementations§
Source§impl CreateDatasetFluentBuilder
impl CreateDatasetFluentBuilder
Sourcepub fn as_input(&self) -> &CreateDatasetInputBuilder
pub fn as_input(&self) -> &CreateDatasetInputBuilder
Access the CreateDataset as a reference.
Sourcepub async fn send(
self,
) -> Result<CreateDatasetOutput, SdkError<CreateDatasetError, HttpResponse>>
pub async fn send( self, ) -> Result<CreateDatasetOutput, SdkError<CreateDatasetError, HttpResponse>>
Sends the request and returns the response.
If an error occurs, an SdkError will be returned with additional details that
can be matched against.
By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.
Sourcepub fn customize(
self,
) -> CustomizableOperation<CreateDatasetOutput, CreateDatasetError, Self>
pub fn customize( self, ) -> CustomizableOperation<CreateDatasetOutput, CreateDatasetError, Self>
Consumes this builder, creating a customizable operation that can be modified before being sent.
Sourcepub fn dataset_source(self, input: DatasetSource) -> Self
pub fn dataset_source(self, input: DatasetSource) -> Self
The source files for the dataset. You can specify the ARN of an existing dataset or specify the Amazon S3 bucket location of an Amazon Sagemaker format manifest file. If you don't specify datasetSource, an empty dataset is created. To add labeled images to the dataset, You can use the console or call UpdateDatasetEntries.
Sourcepub fn set_dataset_source(self, input: Option<DatasetSource>) -> Self
pub fn set_dataset_source(self, input: Option<DatasetSource>) -> Self
The source files for the dataset. You can specify the ARN of an existing dataset or specify the Amazon S3 bucket location of an Amazon Sagemaker format manifest file. If you don't specify datasetSource, an empty dataset is created. To add labeled images to the dataset, You can use the console or call UpdateDatasetEntries.
Sourcepub fn get_dataset_source(&self) -> &Option<DatasetSource>
pub fn get_dataset_source(&self) -> &Option<DatasetSource>
The source files for the dataset. You can specify the ARN of an existing dataset or specify the Amazon S3 bucket location of an Amazon Sagemaker format manifest file. If you don't specify datasetSource, an empty dataset is created. To add labeled images to the dataset, You can use the console or call UpdateDatasetEntries.
Sourcepub fn dataset_type(self, input: DatasetType) -> Self
pub fn dataset_type(self, input: DatasetType) -> Self
The type of the dataset. Specify TRAIN to create a training dataset. Specify TEST to create a test dataset.
Sourcepub fn set_dataset_type(self, input: Option<DatasetType>) -> Self
pub fn set_dataset_type(self, input: Option<DatasetType>) -> Self
The type of the dataset. Specify TRAIN to create a training dataset. Specify TEST to create a test dataset.
Sourcepub fn get_dataset_type(&self) -> &Option<DatasetType>
pub fn get_dataset_type(&self) -> &Option<DatasetType>
The type of the dataset. Specify TRAIN to create a training dataset. Specify TEST to create a test dataset.
Sourcepub fn project_arn(self, input: impl Into<String>) -> Self
pub fn project_arn(self, input: impl Into<String>) -> Self
The ARN of the Amazon Rekognition Custom Labels project to which you want to asssign the dataset.
Sourcepub fn set_project_arn(self, input: Option<String>) -> Self
pub fn set_project_arn(self, input: Option<String>) -> Self
The ARN of the Amazon Rekognition Custom Labels project to which you want to asssign the dataset.
Sourcepub fn get_project_arn(&self) -> &Option<String>
pub fn get_project_arn(&self) -> &Option<String>
The ARN of the Amazon Rekognition Custom Labels project to which you want to asssign the dataset.
Adds a key-value pair to Tags.
To override the contents of this collection use set_tags.
A set of tags (key-value pairs) that you want to attach to the dataset.
A set of tags (key-value pairs) that you want to attach to the dataset.
A set of tags (key-value pairs) that you want to attach to the dataset.
Trait Implementations§
Source§impl Clone for CreateDatasetFluentBuilder
impl Clone for CreateDatasetFluentBuilder
Source§fn clone(&self) -> CreateDatasetFluentBuilder
fn clone(&self) -> CreateDatasetFluentBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreAuto Trait Implementations§
impl Freeze for CreateDatasetFluentBuilder
impl !RefUnwindSafe for CreateDatasetFluentBuilder
impl Send for CreateDatasetFluentBuilder
impl Sync for CreateDatasetFluentBuilder
impl Unpin for CreateDatasetFluentBuilder
impl !UnwindSafe for CreateDatasetFluentBuilder
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