fn start_label_detection(
        &self,
        input: StartLabelDetectionRequest,
    ) -> RusotoFuture<StartLabelDetectionResponse, StartLabelDetectionError> {
        let mut request = SignedRequest::new("POST", "rekognition", &self.region, "/");

        request.set_content_type("application/x-amz-json-1.1".to_owned());
        request.add_header("x-amz-target", "RekognitionService.StartLabelDetection");
        let encoded = serde_json::to_string(&input).unwrap();
        request.set_payload(Some(encoded.into_bytes()));

        self.client.sign_and_dispatch(request, |response| {
            if response.status.is_success() {
                Box::new(response.buffer().from_err().map(|response| {
                    let mut body = response.body;

                    if body.is_empty() || body == b"null" {
                        body = b"{}".to_vec();
                    }

                    serde_json::from_str::<StartLabelDetectionResponse>(
                        String::from_utf8_lossy(body.as_ref()).as_ref(),
                    )
                    .unwrap()
                }))
            } else {
                Box::new(
                    response.buffer().from_err().and_then(|response| {
                        Err(StartLabelDetectionError::from_response(response))
                    }),
                )
            }
        })
    }
/// <p><p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon Rekognition Video can detect labels in a video. Labels are instances of real-world entities. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; concepts like landscape, evening, and nature; and activities like a person getting out of a car or a person skiing.</p> <p>The video must be stored in an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the video. <code>StartLabelDetection</code> returns a job identifier (<code>JobId</code>) which you use to get the results of the operation. When label detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in <code>NotificationChannel</code>.</p> <p>To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call and pass the job identifier (<code>JobId</code>) from the initial call to <code>StartLabelDetection</code>.</p> <p/></p>
Starts asynchronous detection of labels in a stored video. Amazon Rekognition Video can detect labels in a video. Labels are instances of real-world entities. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; concepts like landscape, evening, and nature; and activities like a person getting out of a car or a person skiing. The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of the video. StartLabelDetection returns a job identifier (JobId) which you use to get the results of the operation. When label detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel. To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call and pass the job identifier (JobId) from the initial call to StartLabelDetection. 
Starts asynchronous detection of labels in a stored video . Amazon Rekognition Video can detect labels in a video . Labels are instances of real - world entities . This includes objects like flower tree and table ; events like wedding graduation and birthday party ; concepts like landscape evening and nature ; and activities like a person getting out of a car or a person skiing . The video must be stored in an Amazon S3 bucket . Use Video to specify the bucket name and the filename of the video . StartLabelDetection returns a job identifier ( JobId ) which you use to get the results of the operation . When label detection is finished Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic that you specify in NotificationChannel . To get the results of the label detection operation first check that the status value published to the Amazon SNS topic is SUCCEEDED . If so call and pass the job identifier ( JobId ) from the initial call to StartLabelDetection .
fn start_label_detection(
        &self,
        input: StartLabelDetectionRequest,
    ) -> RusotoFuture<StartLabelDetectionResponse, StartLabelDetectionError> {
        let mut request = SignedRequest::new("POST", "rekognition", &self.region, "/");
        request.set_content_type("application/x-amz-json-1.1".to_owned());
        request.add_header("x-amz-target", "RekognitionService.StartLabelDetection");
        let encoded = serde_json::to_string(&input).unwrap();
        request.set_payload(Some(encoded.into_bytes()));
        self.client.sign_and_dispatch(request, |response| {
            if response.status.is_success() {
                Box::new(response.buffer().from_err().map(|response| {
                    let mut body = response.body;
                    if body.is_empty() || body == b"null" {
                        body = b"{}".to_vec();
                    }
                    serde_json::from_str::<StartLabelDetectionResponse>(
                        String::from_utf8_lossy(body.as_ref()).as_ref(),
                    )
                    .unwrap()
                }))
            } else {
                Box::new(
                    response.buffer().from_err().and_then(|response| {
                        Err(StartLabelDetectionError::from_response(response))
                    }),
                )
            }
        })
    }
fn start_label_detection ( & self , input : StartLabelDetectionRequest , ) -> RusotoFuture < StartLabelDetectionResponse , StartLabelDetectionError > { let mut request = SignedRequest :: new ( " " , " " , & self . region , " " ) ; request . set_content_type ( " " . to_owned ( ) ) ; request . add_header ( " " , " " ) ; let encoded = serde_json :: to_string ( & input ) . unwrap ( ) ; request . set_payload ( Some ( encoded . into_bytes ( ) ) ) ; self . client . sign_and_dispatch ( request , | response | { if response . status . is_success ( ) { Box :: new ( response . buffer ( ) . from_err ( ) . map ( | response | { let mut body = response . body ; if body . is_empty ( ) || body == b" " { body = b" " . to_vec ( ) ; } serde_json :: from_str :: < StartLabelDetectionResponse > ( String :: from_utf8_lossy ( body . as_ref ( ) ) . as_ref ( ) , ) . unwrap ( ) } ) ) } else { Box :: new ( response . buffer ( ) . from_err ( ) . and_then ( | response | { Err ( StartLabelDetectionError :: from_response ( response ) ) } ) , ) } } ) }
<p><p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon Rekognition Video can detect labels in a video.
<p > <p > Starts asynchronous detection of labels in a stored video . < / p > <p > Amazon Rekognition Video can detect labels in a video .
&self
input
StartLabelDetectionRequest
&self
input
StartLabelDetectionRequest