aws_sdk_rekognition::operation::create_stream_processor::builders

Struct CreateStreamProcessorInputBuilder

#[non_exhaustive]
pub struct CreateStreamProcessorInputBuilder { /* private fields */ }

Expand description

A builder for CreateStreamProcessorInput.

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impl CreateStreamProcessorInputBuilder

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pub fn input(self, input: StreamProcessorInput) -> Self

Kinesis video stream stream that provides the source streaming video. If you are using the AWS CLI, the parameter name is StreamProcessorInput. This is required for both face search and label detection stream processors.

This field is required.

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pub fn set_input(self, input: Option<StreamProcessorInput>) -> Self

Kinesis video stream stream that provides the source streaming video. If you are using the AWS CLI, the parameter name is StreamProcessorInput. This is required for both face search and label detection stream processors.

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pub fn get_input(&self) -> &Option<StreamProcessorInput>

Kinesis video stream stream that provides the source streaming video. If you are using the AWS CLI, the parameter name is StreamProcessorInput. This is required for both face search and label detection stream processors.

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pub fn output(self, input: StreamProcessorOutput) -> Self

Kinesis data stream stream or Amazon S3 bucket location to which Amazon Rekognition Video puts the analysis results. If you are using the AWS CLI, the parameter name is StreamProcessorOutput. This must be a S3Destination of an Amazon S3 bucket that you own for a label detection stream processor or a Kinesis data stream ARN for a face search stream processor.

This field is required.

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pub fn set_output(self, input: Option<StreamProcessorOutput>) -> Self

Kinesis data stream stream or Amazon S3 bucket location to which Amazon Rekognition Video puts the analysis results. If you are using the AWS CLI, the parameter name is StreamProcessorOutput. This must be a S3Destination of an Amazon S3 bucket that you own for a label detection stream processor or a Kinesis data stream ARN for a face search stream processor.

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pub fn get_output(&self) -> &Option<StreamProcessorOutput>

Kinesis data stream stream or Amazon S3 bucket location to which Amazon Rekognition Video puts the analysis results. If you are using the AWS CLI, the parameter name is StreamProcessorOutput. This must be a S3Destination of an Amazon S3 bucket that you own for a label detection stream processor or a Kinesis data stream ARN for a face search stream processor.

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pub fn name(self, input: impl Into<String>) -> Self

An identifier you assign to the stream processor. You can use Name to manage the stream processor. For example, you can get the current status of the stream processor by calling DescribeStreamProcessor. Name is idempotent. This is required for both face search and label detection stream processors.

This field is required.

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pub fn set_name(self, input: Option<String>) -> Self

An identifier you assign to the stream processor. You can use Name to manage the stream processor. For example, you can get the current status of the stream processor by calling DescribeStreamProcessor. Name is idempotent. This is required for both face search and label detection stream processors.

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pub fn get_name(&self) -> &Option<String>

An identifier you assign to the stream processor. You can use Name to manage the stream processor. For example, you can get the current status of the stream processor by calling DescribeStreamProcessor. Name is idempotent. This is required for both face search and label detection stream processors.

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pub fn settings(self, input: StreamProcessorSettings) -> Self

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

This field is required.

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pub fn set_settings(self, input: Option<StreamProcessorSettings>) -> Self

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

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pub fn get_settings(&self) -> &Option<StreamProcessorSettings>

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

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pub fn role_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Number (ARN) of the IAM role that allows access to the stream processor. The IAM role provides Rekognition read permissions for a Kinesis stream. It also provides write permissions to an Amazon S3 bucket and Amazon Simple Notification Service topic for a label detection stream processor. This is required for both face search and label detection stream processors.

This field is required.

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pub fn set_role_arn(self, input: Option<String>) -> Self

The Amazon Resource Number (ARN) of the IAM role that allows access to the stream processor. The IAM role provides Rekognition read permissions for a Kinesis stream. It also provides write permissions to an Amazon S3 bucket and Amazon Simple Notification Service topic for a label detection stream processor. This is required for both face search and label detection stream processors.

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pub fn get_role_arn(&self) -> &Option<String>

The Amazon Resource Number (ARN) of the IAM role that allows access to the stream processor. The IAM role provides Rekognition read permissions for a Kinesis stream. It also provides write permissions to an Amazon S3 bucket and Amazon Simple Notification Service topic for a label detection stream processor. This is required for both face search and label detection stream processors.

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pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

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 stream processor.

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pub fn set_tags(self, input: Option<HashMap<String, String>>) -> Self

A set of tags (key-value pairs) that you want to attach to the stream processor.

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pub fn get_tags(&self) -> &Option<HashMap<String, String>>

A set of tags (key-value pairs) that you want to attach to the stream processor.

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pub fn notification_channel( self, input: StreamProcessorNotificationChannel, ) -> Self

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the object detection results and completion status of a video analysis operation.

Amazon Rekognition publishes a notification the first time an object of interest or a person is detected in the video stream. For example, if Amazon Rekognition detects a person at second 2, a pet at second 4, and a person again at second 5, Amazon Rekognition sends 2 object class detected notifications, one for a person at second 2 and one for a pet at second 4.

Amazon Rekognition also publishes an an end-of-session notification with a summary when the stream processing session is complete.

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pub fn set_notification_channel( self, input: Option<StreamProcessorNotificationChannel>, ) -> Self

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the object detection results and completion status of a video analysis operation.

Amazon Rekognition publishes a notification the first time an object of interest or a person is detected in the video stream. For example, if Amazon Rekognition detects a person at second 2, a pet at second 4, and a person again at second 5, Amazon Rekognition sends 2 object class detected notifications, one for a person at second 2 and one for a pet at second 4.

Amazon Rekognition also publishes an an end-of-session notification with a summary when the stream processing session is complete.

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pub fn get_notification_channel( &self, ) -> &Option<StreamProcessorNotificationChannel>

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the object detection results and completion status of a video analysis operation.

Amazon Rekognition publishes a notification the first time an object of interest or a person is detected in the video stream. For example, if Amazon Rekognition detects a person at second 2, a pet at second 4, and a person again at second 5, Amazon Rekognition sends 2 object class detected notifications, one for a person at second 2 and one for a pet at second 4.

Amazon Rekognition also publishes an an end-of-session notification with a summary when the stream processing session is complete.

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pub fn kms_key_id(self, input: impl Into<String>) -> Self

The identifier for your AWS Key Management Service key (AWS KMS key). This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor. You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt results and data published to your Amazon S3 bucket, which includes image frames and hero images. Your source images are unaffected.

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pub fn set_kms_key_id(self, input: Option<String>) -> Self

The identifier for your AWS Key Management Service key (AWS KMS key). This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor. You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt results and data published to your Amazon S3 bucket, which includes image frames and hero images. Your source images are unaffected.

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pub fn get_kms_key_id(&self) -> &Option<String>

The identifier for your AWS Key Management Service key (AWS KMS key). This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor. You can supply the Amazon Resource Name (ARN) of your KMS key, the ID of your KMS key, an alias for your KMS key, or an alias ARN. The key is used to encrypt results and data published to your Amazon S3 bucket, which includes image frames and hero images. Your source images are unaffected.

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pub fn regions_of_interest(self, input: RegionOfInterest) -> Self

Appends an item to regions_of_interest.

To override the contents of this collection use set_regions_of_interest.

Specifies locations in the frames where Amazon Rekognition checks for objects or people. You can specify up to 10 regions of interest, and each region has either a polygon or a bounding box. This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor.

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pub fn set_regions_of_interest( self, input: Option<Vec<RegionOfInterest>>, ) -> Self

Specifies locations in the frames where Amazon Rekognition checks for objects or people. You can specify up to 10 regions of interest, and each region has either a polygon or a bounding box. This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor.

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pub fn get_regions_of_interest(&self) -> &Option<Vec<RegionOfInterest>>

Specifies locations in the frames where Amazon Rekognition checks for objects or people. You can specify up to 10 regions of interest, and each region has either a polygon or a bounding box. This is an optional parameter for label detection stream processors and should not be used to create a face search stream processor.

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pub fn data_sharing_preference( self, input: StreamProcessorDataSharingPreference, ) -> Self

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

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pub fn set_data_sharing_preference( self, input: Option<StreamProcessorDataSharingPreference>, ) -> Self

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

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pub fn get_data_sharing_preference( &self, ) -> &Option<StreamProcessorDataSharingPreference>

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

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pub fn build(self) -> Result<CreateStreamProcessorInput, BuildError>

Consumes the builder and constructs a CreateStreamProcessorInput.

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impl CreateStreamProcessorInputBuilder

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pub async fn send_with( self, client: &Client, ) -> Result<CreateStreamProcessorOutput, SdkError<CreateStreamProcessorError, HttpResponse>>

Sends a request with this input using the given client.

Trait Implementations§

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impl Clone for CreateStreamProcessorInputBuilder

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fn clone(&self) -> CreateStreamProcessorInputBuilder

Returns a duplicate of the value. Read more

1.0.0 · Source§

const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more

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impl Debug for CreateStreamProcessorInputBuilder

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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impl Default for CreateStreamProcessorInputBuilder

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fn default() -> CreateStreamProcessorInputBuilder

Returns the “default value” for a type. Read more

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impl PartialEq for CreateStreamProcessorInputBuilder

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fn eq(&self, other: &CreateStreamProcessorInputBuilder) -> bool

Tests for self and other values to be equal, and is used by ==.

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const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

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impl StructuralPartialEq for CreateStreamProcessorInputBuilder

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impl UnwindSafe for CreateStreamProcessorInputBuilder

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Struct CreateStreamProcessorInputBuilderCopy item path

Implementations§

impl CreateStreamProcessorInputBuilder

pub fn input(self, input: StreamProcessorInput) -> Self

pub fn set_input(self, input: Option<StreamProcessorInput>) -> Self

pub fn get_input(&self) -> &Option<StreamProcessorInput>

pub fn output(self, input: StreamProcessorOutput) -> Self

pub fn set_output(self, input: Option<StreamProcessorOutput>) -> Self

pub fn get_output(&self) -> &Option<StreamProcessorOutput>

pub fn name(self, input: impl Into<String>) -> Self

pub fn set_name(self, input: Option<String>) -> Self

pub fn get_name(&self) -> &Option<String>

pub fn settings(self, input: StreamProcessorSettings) -> Self

pub fn set_settings(self, input: Option<StreamProcessorSettings>) -> Self

pub fn get_settings(&self) -> &Option<StreamProcessorSettings>

pub fn role_arn(self, input: impl Into<String>) -> Self

pub fn set_role_arn(self, input: Option<String>) -> Self

pub fn get_role_arn(&self) -> &Option<String>

pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

pub fn set_tags(self, input: Option<HashMap<String, String>>) -> Self

pub fn get_tags(&self) -> &Option<HashMap<String, String>>

pub fn notification_channel( self, input: StreamProcessorNotificationChannel, ) -> Self

pub fn set_notification_channel( self, input: Option<StreamProcessorNotificationChannel>, ) -> Self

pub fn get_notification_channel( &self, ) -> &Option<StreamProcessorNotificationChannel>

pub fn kms_key_id(self, input: impl Into<String>) -> Self

pub fn set_kms_key_id(self, input: Option<String>) -> Self

pub fn get_kms_key_id(&self) -> &Option<String>

pub fn regions_of_interest(self, input: RegionOfInterest) -> Self

pub fn set_regions_of_interest( self, input: Option<Vec<RegionOfInterest>>, ) -> Self

pub fn get_regions_of_interest(&self) -> &Option<Vec<RegionOfInterest>>

pub fn data_sharing_preference( self, input: StreamProcessorDataSharingPreference, ) -> Self

pub fn set_data_sharing_preference( self, input: Option<StreamProcessorDataSharingPreference>, ) -> Self

pub fn get_data_sharing_preference( &self, ) -> &Option<StreamProcessorDataSharingPreference>

pub fn build(self) -> Result<CreateStreamProcessorInput, BuildError>

impl CreateStreamProcessorInputBuilder

pub async fn send_with( self, client: &Client, ) -> Result<CreateStreamProcessorOutput, SdkError<CreateStreamProcessorError, HttpResponse>>

Trait Implementations§

impl Clone for CreateStreamProcessorInputBuilder

fn clone(&self) -> CreateStreamProcessorInputBuilder

const fn clone_from(&mut self, source: &Self)

impl Debug for CreateStreamProcessorInputBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

impl Default for CreateStreamProcessorInputBuilder

fn default() -> CreateStreamProcessorInputBuilder

impl PartialEq for CreateStreamProcessorInputBuilder

fn eq(&self, other: &CreateStreamProcessorInputBuilder) -> bool

const fn ne(&self, other: &Rhs) -> bool

impl StructuralPartialEq for CreateStreamProcessorInputBuilder

Auto Trait Implementations§

impl Freeze for CreateStreamProcessorInputBuilder

impl RefUnwindSafe for CreateStreamProcessorInputBuilder

impl Send for CreateStreamProcessorInputBuilder

impl Sync for CreateStreamProcessorInputBuilder

impl Unpin for CreateStreamProcessorInputBuilder

impl UnwindSafe for CreateStreamProcessorInputBuilder

Blanket Implementations§

impl<T> Any for Twhere T: 'static + ?Sized,

fn type_id(&self) -> TypeId

impl<T> Borrow<T> for Twhere T: ?Sized,

fn borrow(&self) -> &T

impl<T> BorrowMut<T> for Twhere T: ?Sized,

fn borrow_mut(&mut self) -> &mut T

impl<T> CloneToUninit for Twhere T: Clone,

unsafe fn clone_to_uninit(&self, dest: *mut u8)

impl<T> From<T> for T

fn from(t: T) -> T

impl<T> Instrument for T

fn instrument(self, span: Span) -> Instrumented<Self>

fn in_current_span(self) -> Instrumented<Self>

impl<T, U> Into<U> for Twhere U: From<T>,

fn into(self) -> U

impl<T> IntoEither for T

fn into_either(self, into_left: bool) -> Either<Self, Self>

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unsharedwhere Shared: FromUnshared<Unshared>,

fn into_shared(self) -> Shared

impl<T> Paint for Twhere T: ?Sized,

fn fg(&self, value: Color) -> Painted<&T>

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fn primary(&self) -> Painted<&T>

Struct CreateStreamProcessorInputBuilder

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unshared
where Shared: FromUnshared<Unshared>,

impl<T> Paint for T
where T: ?Sized,