universal-s3/clients/rekognition.d.ts

Universal S3 SDK for JavaScript, available for Node.js backends

import {Request} from '../lib/request';
import {Response} from '../lib/response';
import {AWSError} from '../lib/error';
import {Service} from '../lib/service';
import {ServiceConfigurationOptions} from '../lib/service';
import {ConfigBase as Config} from '../lib/config';
interface Blob {}
declare class Rekognition extends Service {
  /**
   * Constructs a service object. This object has one method for each API operation.
   */
  constructor(options?: Rekognition.Types.ClientConfiguration)
  config: Config & Rekognition.Types.ClientConfiguration;
  /**
   * Compares a face in the source input image with each of the 100 largest faces detected in the target input image.    If the source image contains multiple faces, the service detects the largest face and compares it with each face detected in the target image.   You pass the input and target images either as base64-encoded image bytes or as references to images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't supported. The image must be formatted as a PNG or JPEG file.  In response, the operation returns an array of face matches ordered by similarity score in descending order. For each face match, the response provides a bounding box of the face, facial landmarks, pose details (pitch, role, and yaw), quality (brightness and sharpness), and confidence value (indicating the level of confidence that the bounding box contains a face). The response also provides a similarity score, which indicates how closely the faces match.   By default, only faces with a similarity score of greater than or equal to 80% are returned in the response. You can change this value by specifying the SimilarityThreshold parameter.   CompareFaces also returns an array of faces that don't match the source image. For each face, it returns a bounding box, confidence value, landmarks, pose details, and quality. The response also returns information about the face in the source image, including the bounding box of the face and confidence value. If the image doesn't contain Exif metadata, CompareFaces returns orientation information for the source and target images. Use these values to display the images with the correct image orientation. If no faces are detected in the source or target images, CompareFaces returns an InvalidParameterException error.    This is a stateless API operation. That is, data returned by this operation doesn't persist.  For an example, see Comparing Faces in Images in the Amazon Rekognition Developer Guide. This operation requires permissions to perform the rekognition:CompareFaces action.
   */
  compareFaces(params: Rekognition.Types.CompareFacesRequest, callback?: (err: AWSError, data: Rekognition.Types.CompareFacesResponse) => void): Request<Rekognition.Types.CompareFacesResponse, AWSError>;
  /**
   * Compares a face in the source input image with each of the 100 largest faces detected in the target input image.    If the source image contains multiple faces, the service detects the largest face and compares it with each face detected in the target image.   You pass the input and target images either as base64-encoded image bytes or as references to images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't supported. The image must be formatted as a PNG or JPEG file.  In response, the operation returns an array of face matches ordered by similarity score in descending order. For each face match, the response provides a bounding box of the face, facial landmarks, pose details (pitch, role, and yaw), quality (brightness and sharpness), and confidence value (indicating the level of confidence that the bounding box contains a face). The response also provides a similarity score, which indicates how closely the faces match.   By default, only faces with a similarity score of greater than or equal to 80% are returned in the response. You can change this value by specifying the SimilarityThreshold parameter.   CompareFaces also returns an array of faces that don't match the source image. For each face, it returns a bounding box, confidence value, landmarks, pose details, and quality. The response also returns information about the face in the source image, including the bounding box of the face and confidence value. If the image doesn't contain Exif metadata, CompareFaces returns orientation information for the source and target images. Use these values to display the images with the correct image orientation. If no faces are detected in the source or target images, CompareFaces returns an InvalidParameterException error.    This is a stateless API operation. That is, data returned by this operation doesn't persist.  For an example, see Comparing Faces in Images in the Amazon Rekognition Developer Guide. This operation requires permissions to perform the rekognition:CompareFaces action.
   */
  compareFaces(callback?: (err: AWSError, data: Rekognition.Types.CompareFacesResponse) => void): Request<Rekognition.Types.CompareFacesResponse, AWSError>;
  /**
   * Creates a collection in an AWS Region. You can add faces to the collection using the IndexFaces operation.  For example, you might create collections, one for each of your application users. A user can then index faces using the IndexFaces operation and persist results in a specific collection. Then, a user can search the collection for faces in the user-specific container.  When you create a collection, it is associated with the latest version of the face model version.  Collection names are case-sensitive.  This operation requires permissions to perform the rekognition:CreateCollection action.
   */
  createCollection(params: Rekognition.Types.CreateCollectionRequest, callback?: (err: AWSError, data: Rekognition.Types.CreateCollectionResponse) => void): Request<Rekognition.Types.CreateCollectionResponse, AWSError>;
  /**
   * Creates a collection in an AWS Region. You can add faces to the collection using the IndexFaces operation.  For example, you might create collections, one for each of your application users. A user can then index faces using the IndexFaces operation and persist results in a specific collection. Then, a user can search the collection for faces in the user-specific container.  When you create a collection, it is associated with the latest version of the face model version.  Collection names are case-sensitive.  This operation requires permissions to perform the rekognition:CreateCollection action.
   */
  createCollection(callback?: (err: AWSError, data: Rekognition.Types.CreateCollectionResponse) => void): Request<Rekognition.Types.CreateCollectionResponse, AWSError>;
  /**
   * Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces in a streaming video. Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. Amazon Rekognition Video sends analysis results to Amazon Kinesis Data Streams. You provide as input a Kinesis video stream (Input) and a Kinesis data stream (Output) stream. You also specify the face recognition criteria in Settings. For example, the collection containing faces that you want to recognize. Use Name to assign an identifier for the stream processor. You use Name to manage the stream processor. For example, you can start processing the source video by calling StartStreamProcessor with the Name field.  After you have finished analyzing a streaming video, use StopStreamProcessor to stop processing. You can delete the stream processor by calling DeleteStreamProcessor.
   */
  createStreamProcessor(params: Rekognition.Types.CreateStreamProcessorRequest, callback?: (err: AWSError, data: Rekognition.Types.CreateStreamProcessorResponse) => void): Request<Rekognition.Types.CreateStreamProcessorResponse, AWSError>;
  /**
   * Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces in a streaming video. Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. Amazon Rekognition Video sends analysis results to Amazon Kinesis Data Streams. You provide as input a Kinesis video stream (Input) and a Kinesis data stream (Output) stream. You also specify the face recognition criteria in Settings. For example, the collection containing faces that you want to recognize. Use Name to assign an identifier for the stream processor. You use Name to manage the stream processor. For example, you can start processing the source video by calling StartStreamProcessor with the Name field.  After you have finished analyzing a streaming video, use StopStreamProcessor to stop processing. You can delete the stream processor by calling DeleteStreamProcessor.
   */
  createStreamProcessor(callback?: (err: AWSError, data: Rekognition.Types.CreateStreamProcessorResponse) => void): Request<Rekognition.Types.CreateStreamProcessorResponse, AWSError>;
  /**
   * Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, see delete-collection-procedure. This operation requires permissions to perform the rekognition:DeleteCollection action.
   */
  deleteCollection(params: Rekognition.Types.DeleteCollectionRequest, callback?: (err: AWSError, data: Rekognition.Types.DeleteCollectionResponse) => void): Request<Rekognition.Types.DeleteCollectionResponse, AWSError>;
  /**
   * Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, see delete-collection-procedure. This operation requires permissions to perform the rekognition:DeleteCollection action.
   */
  deleteCollection(callback?: (err: AWSError, data: Rekognition.Types.DeleteCollectionResponse) => void): Request<Rekognition.Types.DeleteCollectionResponse, AWSError>;
  /**
   * Deletes faces from a collection. You specify a collection ID and an array of face IDs to remove from the collection. This operation requires permissions to perform the rekognition:DeleteFaces action.
   */
  deleteFaces(params: Rekognition.Types.DeleteFacesRequest, callback?: (err: AWSError, data: Rekognition.Types.DeleteFacesResponse) => void): Request<Rekognition.Types.DeleteFacesResponse, AWSError>;
  /**
   * Deletes faces from a collection. You specify a collection ID and an array of face IDs to remove from the collection. This operation requires permissions to perform the rekognition:DeleteFaces action.
   */
  deleteFaces(callback?: (err: AWSError, data: Rekognition.Types.DeleteFacesResponse) => void): Request<Rekognition.Types.DeleteFacesResponse, AWSError>;
  /**
   * Deletes the stream processor identified by Name. You assign the value for Name when you create the stream processor with CreateStreamProcessor. You might not be able to use the same name for a stream processor for a few seconds after calling DeleteStreamProcessor.
   */
  deleteStreamProcessor(params: Rekognition.Types.DeleteStreamProcessorRequest, callback?: (err: AWSError, data: Rekognition.Types.DeleteStreamProcessorResponse) => void): Request<Rekognition.Types.DeleteStreamProcessorResponse, AWSError>;
  /**
   * Deletes the stream processor identified by Name. You assign the value for Name when you create the stream processor with CreateStreamProcessor. You might not be able to use the same name for a stream processor for a few seconds after calling DeleteStreamProcessor.
   */
  deleteStreamProcessor(callback?: (err: AWSError, data: Rekognition.Types.DeleteStreamProcessorResponse) => void): Request<Rekognition.Types.DeleteStreamProcessorResponse, AWSError>;
  /**
   * Describes the specified collection. You can use DescribeCollection to get information, such as the number of faces indexed into a collection and the version of the model used by the collection for face detection. For more information, see Describing a Collection in the Amazon Rekognition Developer Guide.
   */
  describeCollection(params: Rekognition.Types.DescribeCollectionRequest, callback?: (err: AWSError, data: Rekognition.Types.DescribeCollectionResponse) => void): Request<Rekognition.Types.DescribeCollectionResponse, AWSError>;
  /**
   * Describes the specified collection. You can use DescribeCollection to get information, such as the number of faces indexed into a collection and the version of the model used by the collection for face detection. For more information, see Describing a Collection in the Amazon Rekognition Developer Guide.
   */
  describeCollection(callback?: (err: AWSError, data: Rekognition.Types.DescribeCollectionResponse) => void): Request<Rekognition.Types.DescribeCollectionResponse, AWSError>;
  /**
   * Provides information about a stream processor created by CreateStreamProcessor. You can get information about the input and output streams, the input parameters for the face recognition being performed, and the current status of the stream processor.
   */
  describeStreamProcessor(params: Rekognition.Types.DescribeStreamProcessorRequest, callback?: (err: AWSError, data: Rekognition.Types.DescribeStreamProcessorResponse) => void): Request<Rekognition.Types.DescribeStreamProcessorResponse, AWSError>;
  /**
   * Provides information about a stream processor created by CreateStreamProcessor. You can get information about the input and output streams, the input parameters for the face recognition being performed, and the current status of the stream processor.
   */
  describeStreamProcessor(callback?: (err: AWSError, data: Rekognition.Types.DescribeStreamProcessorResponse) => void): Request<Rekognition.Types.DescribeStreamProcessorResponse, AWSError>;
  /**
   * Detects faces within an image that is provided as input.  DetectFaces detects the 100 largest faces in the image. For each face detected, the operation returns face details. These details include a bounding box of the face, a confidence value (that the bounding box contains a face), and a fixed set of attributes such as facial landmarks (for example, coordinates of eye and mouth), gender, presence of beard, sunglasses, and so on.  The face-detection algorithm is most effective on frontal faces. For non-frontal or obscured faces, the algorithm might not detect the faces or might detect faces with lower confidence.  You pass the input image either as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.   This is a stateless API operation. That is, the operation does not persist any data.  This operation requires permissions to perform the rekognition:DetectFaces action. 
   */
  detectFaces(params: Rekognition.Types.DetectFacesRequest, callback?: (err: AWSError, data: Rekognition.Types.DetectFacesResponse) => void): Request<Rekognition.Types.DetectFacesResponse, AWSError>;
  /**
   * Detects faces within an image that is provided as input.  DetectFaces detects the 100 largest faces in the image. For each face detected, the operation returns face details. These details include a bounding box of the face, a confidence value (that the bounding box contains a face), and a fixed set of attributes such as facial landmarks (for example, coordinates of eye and mouth), gender, presence of beard, sunglasses, and so on.  The face-detection algorithm is most effective on frontal faces. For non-frontal or obscured faces, the algorithm might not detect the faces or might detect faces with lower confidence.  You pass the input image either as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.   This is a stateless API operation. That is, the operation does not persist any data.  This operation requires permissions to perform the rekognition:DetectFaces action. 
   */
  detectFaces(callback?: (err: AWSError, data: Rekognition.Types.DetectFacesResponse) => void): Request<Rekognition.Types.DetectFacesResponse, AWSError>;
  /**
   * Detects instances of real-world entities within an image (JPEG or PNG) provided as input. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; and concepts like landscape, evening, and nature.  For an example, see Analyzing Images Stored in an Amazon S3 Bucket in the Amazon Rekognition Developer Guide.   DetectLabels does not support the detection of activities. However, activity detection is supported for label detection in videos. For more information, see StartLabelDetection in the Amazon Rekognition Developer Guide.  You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.   For each object, scene, and concept the API returns one or more labels. Each label provides the object name, and the level of confidence that the image contains the object. For example, suppose the input image has a lighthouse, the sea, and a rock. The response includes all three labels, one for each object.   {Name: lighthouse, Confidence: 98.4629}   {Name: rock,Confidence: 79.2097}    {Name: sea,Confidence: 75.061}  In the preceding example, the operation returns one label for each of the three objects. The operation can also return multiple labels for the same object in the image. For example, if the input image shows a flower (for example, a tulip), the operation might return the following three labels.   {Name: flower,Confidence: 99.0562}   {Name: plant,Confidence: 99.0562}   {Name: tulip,Confidence: 99.0562}  In this example, the detection algorithm more precisely identifies the flower as a tulip. In response, the API returns an array of labels. In addition, the response also includes the orientation correction. Optionally, you can specify MinConfidence to control the confidence threshold for the labels returned. The default is 55%. You can also add the MaxLabels parameter to limit the number of labels returned.   If the object detected is a person, the operation doesn't provide the same facial details that the DetectFaces operation provides.   DetectLabels returns bounding boxes for instances of common object labels in an array of Instance objects. An Instance object contains a BoundingBox object, for the location of the label on the image. It also includes the confidence by which the bounding box was detected.  DetectLabels also returns a hierarchical taxonomy of detected labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle (its parent) and Transportation (its grandparent). The response returns the entire list of ancestors for a label. Each ancestor is a unique label in the response. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.  This is a stateless API operation. That is, the operation does not persist any data. This operation requires permissions to perform the rekognition:DetectLabels action. 
   */
  detectLabels(params: Rekognition.Types.DetectLabelsRequest, callback?: (err: AWSError, data: Rekognition.Types.DetectLabelsResponse) => void): Request<Rekognition.Types.DetectLabelsResponse, AWSError>;
  /**
   * Detects instances of real-world entities within an image (JPEG or PNG) provided as input. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; and concepts like landscape, evening, and nature.  For an example, see Analyzing Images Stored in an Amazon S3 Bucket in the Amazon Rekognition Developer Guide.   DetectLabels does not support the detection of activities. However, activity detection is supported for label detection in videos. For more information, see StartLabelDetection in the Amazon Rekognition Developer Guide.  You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.   For each object, scene, and concept the API returns one or more labels. Each label provides the object name, and the level of confidence that the image contains the object. For example, suppose the input image has a lighthouse, the sea, and a rock. The response includes all three labels, one for each object.   {Name: lighthouse, Confidence: 98.4629}   {Name: rock,Confidence: 79.2097}    {Name: sea,Confidence: 75.061}  In the preceding example, the operation returns one label for each of the three objects. The operation can also return multiple labels for the same object in the image. For example, if the input image shows a flower (for example, a tulip), the operation might return the following three labels.   {Name: flower,Confidence: 99.0562}   {Name: plant,Confidence: 99.0562}   {Name: tulip,Confidence: 99.0562}  In this example, the detection algorithm more precisely identifies the flower as a tulip. In response, the API returns an array of labels. In addition, the response also includes the orientation correction. Optionally, you can specify MinConfidence to control the confidence threshold for the labels returned. The default is 55%. You can also add the MaxLabels parameter to limit the number of labels returned.   If the object detected is a person, the operation doesn't provide the same facial details that the DetectFaces operation provides.   DetectLabels returns bounding boxes for instances of common object labels in an array of Instance objects. An Instance object contains a BoundingBox object, for the location of the label on the image. It also includes the confidence by which the bounding box was detected.  DetectLabels also returns a hierarchical taxonomy of detected labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle (its parent) and Transportation (its grandparent). The response returns the entire list of ancestors for a label. Each ancestor is a unique label in the response. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.  This is a stateless API operation. That is, the operation does not persist any data. This operation requires permissions to perform the rekognition:DetectLabels action. 
   */
  detectLabels(callback?: (err: AWSError, data: Rekognition.Types.DetectLabelsResponse) => void): Request<Rekognition.Types.DetectLabelsResponse, AWSError>;
  /**
   * Detects unsafe content in a specified JPEG or PNG format image. Use DetectModerationLabels to moderate images depending on your requirements. For example, you might want to filter images that contain nudity, but not images containing suggestive content. To filter images, use the labels returned by DetectModerationLabels to determine which types of content are appropriate. For information about moderation labels, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide. You pass the input image either as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file. 
   */
  detectModerationLabels(params: Rekognition.Types.DetectModerationLabelsRequest, callback?: (err: AWSError, data: Rekognition.Types.DetectModerationLabelsResponse) => void): Request<Rekognition.Types.DetectModerationLabelsResponse, AWSError>;
  /**
   * Detects unsafe content in a specified JPEG or PNG format image. Use DetectModerationLabels to moderate images depending on your requirements. For example, you might want to filter images that contain nudity, but not images containing suggestive content. To filter images, use the labels returned by DetectModerationLabels to determine which types of content are appropriate. For information about moderation labels, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide. You pass the input image either as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file. 
   */
  detectModerationLabels(callback?: (err: AWSError, data: Rekognition.Types.DetectModerationLabelsResponse) => void): Request<Rekognition.Types.DetectModerationLabelsResponse, AWSError>;
  /**
   * Detects text in the input image and converts it into machine-readable text. Pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, you must pass it as a reference to an image in an Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The image must be either a .png or .jpeg formatted file.  The DetectText operation returns text in an array of TextDetection elements, TextDetections. Each TextDetection element provides information about a single word or line of text that was detected in the image.  A word is one or more ISO basic latin script characters that are not separated by spaces. DetectText can detect up to 50 words in an image. A line is a string of equally spaced words. A line isn't necessarily a complete sentence. For example, a driver's license number is detected as a line. A line ends when there is no aligned text after it. Also, a line ends when there is a large gap between words, relative to the length of the words. This means, depending on the gap between words, Amazon Rekognition may detect multiple lines in text aligned in the same direction. Periods don't represent the end of a line. If a sentence spans multiple lines, the DetectText operation returns multiple lines. To determine whether a TextDetection element is a line of text or a word, use the TextDetection object Type field.  To be detected, text must be within +/- 90 degrees orientation of the horizontal axis. For more information, see DetectText in the Amazon Rekognition Developer Guide.
   */
  detectText(params: Rekognition.Types.DetectTextRequest, callback?: (err: AWSError, data: Rekognition.Types.DetectTextResponse) => void): Request<Rekognition.Types.DetectTextResponse, AWSError>;
  /**
   * Detects text in the input image and converts it into machine-readable text. Pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, you must pass it as a reference to an image in an Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The image must be either a .png or .jpeg formatted file.  The DetectText operation returns text in an array of TextDetection elements, TextDetections. Each TextDetection element provides information about a single word or line of text that was detected in the image.  A word is one or more ISO basic latin script characters that are not separated by spaces. DetectText can detect up to 50 words in an image. A line is a string of equally spaced words. A line isn't necessarily a complete sentence. For example, a driver's license number is detected as a line. A line ends when there is no aligned text after it. Also, a line ends when there is a large gap between words, relative to the length of the words. This means, depending on the gap between words, Amazon Rekognition may detect multiple lines in text aligned in the same direction. Periods don't represent the end of a line. If a sentence spans multiple lines, the DetectText operation returns multiple lines. To determine whether a TextDetection element is a line of text or a word, use the TextDetection object Type field.  To be detected, text must be within +/- 90 degrees orientation of the horizontal axis. For more information, see DetectText in the Amazon Rekognition Developer Guide.
   */
  detectText(callback?: (err: AWSError, data: Rekognition.Types.DetectTextResponse) => void): Request<Rekognition.Types.DetectTextResponse, AWSError>;
  /**
   * Gets the name and additional information about a celebrity based on his or her Amazon Rekognition ID. The additional information is returned as an array of URLs. If there is no additional information about the celebrity, this list is empty. For more information, see Recognizing Celebrities in an Image in the Amazon Rekognition Developer Guide. This operation requires permissions to perform the rekognition:GetCelebrityInfo action. 
   */
  getCelebrityInfo(params: Rekognition.Types.GetCelebrityInfoRequest, callback?: (err: AWSError, data: Rekognition.Types.GetCelebrityInfoResponse) => void): Request<Rekognition.Types.GetCelebrityInfoResponse, AWSError>;
  /**
   * Gets the name and additional information about a celebrity based on his or her Amazon Rekognition ID. The additional information is returned as an array of URLs. If there is no additional information about the celebrity, this list is empty. For more information, see Recognizing Celebrities in an Image in the Amazon Rekognition Developer Guide. This operation requires permissions to perform the rekognition:GetCelebrityInfo action. 
   */
  getCelebrityInfo(callback?: (err: AWSError, data: Rekognition.Types.GetCelebrityInfoResponse) => void): Request<Rekognition.Types.GetCelebrityInfoResponse, AWSError>;
  /**
   * Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by StartCelebrityRecognition. Celebrity recognition in a video is an asynchronous operation. Analysis is started by a call to StartCelebrityRecognition which returns a job identifier (JobId). When the celebrity recognition operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartCelebrityRecognition. To get the results of the celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetCelebrityDetection and pass the job identifier (JobId) from the initial call to StartCelebrityDetection.  For more information, see Working With Stored Videos in the Amazon Rekognition Developer Guide.  GetCelebrityRecognition returns detected celebrities and the time(s) they are detected in an array (Celebrities) of CelebrityRecognition objects. Each CelebrityRecognition contains information about the celebrity in a CelebrityDetail object and the time, Timestamp, the celebrity was detected.    GetCelebrityRecognition only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.   By default, the Celebrities array is sorted by time (milliseconds from the start of the video). You can also sort the array by celebrity by specifying the value ID in the SortBy input parameter. The CelebrityDetail object includes the celebrity identifer and additional information urls. If you don't store the additional information urls, you can get them later by calling GetCelebrityInfo with the celebrity identifer. No information is returned for faces not recognized as celebrities. Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetCelebrityDetection and populate the NextToken request parameter with the token value returned from the previous call to GetCelebrityRecognition.
   */
  getCelebrityRecognition(params: Rekognition.Types.GetCelebrityRecognitionRequest, callback?: (err: AWSError, data: Rekognition.Types.GetCelebrityRecognitionResponse) => void): Request<Rekognition.Types.GetCelebrityRecognitionResponse, AWSError>;
  /**
   * Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by StartCelebrityRecognition. Celebrity recognition in a video is an asynchronous operation. Analysis is started by a call to StartCelebrityRecognition which returns a job identifier (JobId). When the celebrity recognition operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartCelebrityRecognition. To get the results of the celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetCelebrityDetection and pass the job identifier (JobId) from the initial call to StartCelebrityDetection.  For more information, see Working With Stored Videos in the Amazon Rekognition Developer Guide.  GetCelebrityRecognition returns detected celebrities and the time(s) they are detected in an array (Celebrities) of CelebrityRecognition objects. Each CelebrityRecognition contains information about the celebrity in a CelebrityDetail object and the time, Timestamp, the celebrity was detected.    GetCelebrityRecognition only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.   By default, the Celebrities array is sorted by time (milliseconds from the start of the video). You can also sort the array by celebrity by specifying the value ID in the SortBy input parameter. The CelebrityDetail object includes the celebrity identifer and additional information urls. If you don't store the additional information urls, you can get them later by calling GetCelebrityInfo with the celebrity identifer. No information is returned for faces not recognized as celebrities. Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetCelebrityDetection and populate the NextToken request parameter with the token value returned from the previous call to GetCelebrityRecognition.
   */
  getCelebrityRecognition(callback?: (err: AWSError, data: Rekognition.Types.GetCelebrityRecognitionResponse) => void): Request<Rekognition.Types.GetCelebrityRecognitionResponse, AWSError>;
  /**
   * Gets the unsafe content analysis results for a Amazon Rekognition Video analysis started by StartContentModeration. Unsafe content analysis of a video is an asynchronous operation. You start analysis by calling StartContentModeration which returns a job identifier (JobId). When analysis finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartContentModeration. To get the results of the unsafe content analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetContentModeration and pass the job identifier (JobId) from the initial call to StartContentModeration.  For more information, see Working with Stored Videos in the Amazon Rekognition Devlopers Guide.  GetContentModeration returns detected unsafe content labels, and the time they are detected, in an array, ModerationLabels, of ContentModerationDetection objects.  By default, the moderated labels are returned sorted by time, in milliseconds from the start of the video. You can also sort them by moderated label by specifying NAME for the SortBy input parameter.  Since video analysis can return a large number of results, use the MaxResults parameter to limit the number of labels returned in a single call to GetContentModeration. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetContentModeration and populate the NextToken request parameter with the value of NextToken returned from the previous call to GetContentModeration. For more information, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide.
   */
  getContentModeration(params: Rekognition.Types.GetContentModerationRequest, callback?: (err: AWSError, data: Rekognition.Types.GetContentModerationResponse) => void): Request<Rekognition.Types.GetContentModerationResponse, AWSError>;
  /**
   * Gets the unsafe content analysis results for a Amazon Rekognition Video analysis started by StartContentModeration. Unsafe content analysis of a video is an asynchronous operation. You start analysis by calling StartContentModeration which returns a job identifier (JobId). When analysis finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartContentModeration. To get the results of the unsafe content analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetContentModeration and pass the job identifier (JobId) from the initial call to StartContentModeration.  For more information, see Working with Stored Videos in the Amazon Rekognition Devlopers Guide.  GetContentModeration returns detected unsafe content labels, and the time they are detected, in an array, ModerationLabels, of ContentModerationDetection objects.  By default, the moderated labels are returned sorted by time, in milliseconds from the start of the video. You can also sort them by moderated label by specifying NAME for the SortBy input parameter.  Since video analysis can return a large number of results, use the MaxResults parameter to limit the number of labels returned in a single call to GetContentModeration. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetContentModeration and populate the NextToken request parameter with the value of NextToken returned from the previous call to GetContentModeration. For more information, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide.
   */
  getContentModeration(callback?: (err: AWSError, data: Rekognition.Types.GetContentModerationResponse) => void): Request<Rekognition.Types.GetContentModerationResponse, AWSError>;
  /**
   * Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection. Face detection with Amazon Rekognition Video is an asynchronous operation. You start face detection by calling StartFaceDetection which returns a job identifier (JobId). When the face detection operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceDetection. To get the results of the face detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceDetection and pass the job identifier (JobId) from the initial call to StartFaceDetection.  GetFaceDetection returns an array of detected faces (Faces) sorted by the time the faces were detected.  Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetFaceDetection and populate the NextToken request parameter with the token value returned from the previous call to GetFaceDetection.
   */
  getFaceDetection(params: Rekognition.Types.GetFaceDetectionRequest, callback?: (err: AWSError, data: Rekognition.Types.GetFaceDetectionResponse) => void): Request<Rekognition.Types.GetFaceDetectionResponse, AWSError>;
  /**
   * Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection. Face detection with Amazon Rekognition Video is an asynchronous operation. You start face detection by calling StartFaceDetection which returns a job identifier (JobId). When the face detection operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceDetection. To get the results of the face detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceDetection and pass the job identifier (JobId) from the initial call to StartFaceDetection.  GetFaceDetection returns an array of detected faces (Faces) sorted by the time the faces were detected.  Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetFaceDetection and populate the NextToken request parameter with the token value returned from the previous call to GetFaceDetection.
   */
  getFaceDetection(callback?: (err: AWSError, data: Rekognition.Types.GetFaceDetectionResponse) => void): Request<Rekognition.Types.GetFaceDetectionResponse, AWSError>;
  /**
   * Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch. The search returns faces in a collection that match the faces of persons detected in a video. It also includes the time(s) that faces are matched in the video. Face search in a video is an asynchronous operation. You start face search by calling to StartFaceSearch which returns a job identifier (JobId). When the search operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceSearch. To get the search results, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (JobId) from the initial call to StartFaceSearch. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide. The search results are retured in an array, Persons, of PersonMatch objects. EachPersonMatch element contains details about the matching faces in the input collection, person information (facial attributes, bounding boxes, and person identifer) for the matched person, and the time the person was matched in the video.   GetFaceSearch only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.   By default, the Persons array is sorted by the time, in milliseconds from the start of the video, persons are matched. You can also sort by persons by specifying INDEX for the SORTBY input parameter.
   */
  getFaceSearch(params: Rekognition.Types.GetFaceSearchRequest, callback?: (err: AWSError, data: Rekognition.Types.GetFaceSearchResponse) => void): Request<Rekognition.Types.GetFaceSearchResponse, AWSError>;
  /**
   * Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch. The search returns faces in a collection that match the faces of persons detected in a video. It also includes the time(s) that faces are matched in the video. Face search in a video is an asynchronous operation. You start face search by calling to StartFaceSearch which returns a job identifier (JobId). When the search operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceSearch. To get the search results, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (JobId) from the initial call to StartFaceSearch. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide. The search results are retured in an array, Persons, of PersonMatch objects. EachPersonMatch element contains details about the matching faces in the input collection, person information (facial attributes, bounding boxes, and person identifer) for the matched person, and the time the person was matched in the video.   GetFaceSearch only returns the default facial attributes (BoundingBox, Confidence, Landmarks, Pose, and Quality). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.   By default, the Persons array is sorted by the time, in milliseconds from the start of the video, persons are matched. You can also sort by persons by specifying INDEX for the SORTBY input parameter.
   */
  getFaceSearch(callback?: (err: AWSError, data: Rekognition.Types.GetFaceSearchResponse) => void): Request<Rekognition.Types.GetFaceSearchResponse, AWSError>;
  /**
   * Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection.  The label detection operation is started by a call to StartLabelDetection which returns a job identifier (JobId). When the label detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartlabelDetection. To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (JobId) from the initial call to StartLabelDetection.  GetLabelDetection returns an array of detected labels (Labels) sorted by the time the labels were detected. You can also sort by the label name by specifying NAME for the SortBy input parameter. The labels returned include the label name, the percentage confidence in the accuracy of the detected label, and the time the label was detected in the video. The returned labels also include bounding box information for common objects, a hierarchical taxonomy of detected labels, and the version of the label model used for detection. Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetlabelDetection and populate the NextToken request parameter with the token value returned from the previous call to GetLabelDetection.
   */
  getLabelDetection(params: Rekognition.Types.GetLabelDetectionRequest, callback?: (err: AWSError, data: Rekognition.Types.GetLabelDetectionResponse) => void): Request<Rekognition.Types.GetLabelDetectionResponse, AWSError>;
  /**
   * Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection.  The label detection operation is started by a call to StartLabelDetection which returns a job identifier (JobId). When the label detection operation finishes, Amazon Rekognition publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartlabelDetection. To get the results of the label detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (JobId) from the initial call to StartLabelDetection.  GetLabelDetection returns an array of detected labels (Labels) sorted by the time the labels were detected. You can also sort by the label name by specifying NAME for the SortBy input parameter. The labels returned include the label name, the percentage confidence in the accuracy of the detected label, and the time the label was detected in the video. The returned labels also include bounding box information for common objects, a hierarchical taxonomy of detected labels, and the version of the label model used for detection. Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults, the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetlabelDetection and populate the NextToken request parameter with the token value returned from the previous call to GetLabelDetection.
   */
  getLabelDetection(callback?: (err: AWSError, data: Rekognition.Types.GetLabelDetectionResponse) => void): Request<Rekognition.Types.GetLabelDetectionResponse, AWSError>;
  /**
   * Gets the path tracking results of a Amazon Rekognition Video analysis started by StartPersonTracking. The person path tracking operation is started by a call to StartPersonTracking which returns a job identifier (JobId). When the operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartPersonTracking. To get the results of the person path tracking operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (JobId) from the initial call to StartPersonTracking.  GetPersonTracking retur