Structure containing the estimated age range, in years, for a face.

Assets are the images that you use to train and evaluate a model version. Assets can also contain validation information that you use to debug a failed model training.

Metadata information about an audio stream. An array of AudioMetadata objects for the audio streams found in a stored video is returned by "GetSegmentDetection".

Indicates whether or not the face has a beard, and the confidence level in the determination.

A filter that allows you to control the black frame detection by specifying the black levels and pixel coverage of black pixels in a frame. As videos can come from multiple sources, formats, and time periods, they may contain different standards and varying noise levels for black frames that need to be accounted for. For more information, see "StartSegmentDetection".

Identifies the bounding box around the label, face, text, object of interest, or personal protective equipment. The left (x-coordinate) and top (y-coordinate) are coordinates representing the top and left sides of the bounding box. Note that the upper-left corner of the image is the origin (0,0).

Provides information about a celebrity recognized by the "RecognizeCelebrities" operation.

Information about a recognized celebrity.

Information about a detected celebrity and the time the celebrity was detected in a stored video. For more information, see GetCelebrityRecognition in the Amazon Rekognition Developer Guide.

Provides face metadata for target image faces that are analyzed by CompareFaces and RecognizeCelebrities.

Type that describes the face Amazon Rekognition chose to compare with the faces in the target. This contains a bounding box for the selected face and confidence level that the bounding box contains a face. Note that Amazon Rekognition selects the largest face in the source image for this comparison.

Provides information about a face in a target image that matches the source image face analyzed by CompareFaces. The Face property contains the bounding box of the face in the target image. The Similarity property is the confidence that the source image face matches the face in the bounding box.

Label detection settings to use on a streaming video. Defining the settings is required in the request parameter for "CreateStreamProcessor". Including this setting in the CreateStreamProcessor request enables you to use the stream processor for label detection. You can then select what you want the stream processor to detect, such as people or pets. When the stream processor has started, one notification is sent for each object class specified. For example, if packages and pets are selected, one SNS notification is published the first time a package is detected and one SNS notification is published the first time a pet is detected, as well as an end-of-session summary.

The label detection settings you want to use in your stream processor. This includes the labels you want the stream processor to detect and the minimum confidence level allowed to label objects.

Information about an inappropriate, unwanted, or offensive content label detection in a stored video.

Information about an item of Personal Protective Equipment covering a corresponding body part. For more information, see "DetectProtectiveEquipment".

A custom label detected in an image by a call to "DetectCustomLabels".

Describes updates or additions to a dataset. A Single update or addition is an entry (JSON Line) that provides information about a single image. To update an existing entry, you match the source-ref field of the update entry with the source-ref filed of the entry that you want to update. If the source-ref field doesn't match an existing entry, the entry is added to dataset as a new entry.

A description for a dataset. For more information, see "DescribeDataset".

Describes a dataset label. For more information, see "ListDatasetLabels".

Statistics about a label used in a dataset. For more information, see "DatasetLabelDescription".

Summary information for an Amazon Rekognition Custom Labels dataset. For more information, see "ProjectDescription".

The source that Amazon Rekognition Custom Labels uses to create a dataset. To use an Amazon Sagemaker format manifest file, specify the S3 bucket location in the GroundTruthManifest field. The S3 bucket must be in your AWS account. To create a copy of an existing dataset, specify the Amazon Resource Name (ARN) of an existing dataset in DatasetArn.

Provides statistics about a dataset. For more information, see "DescribeDataset".

A set of parameters that allow you to filter out certain results from your returned results.

The background of the image with regard to image quality and dominant colors.

The foreground of the image with regard to image quality and dominant colors.

Information about the quality and dominant colors of an input image. Quality and color information is returned for the entire image, foreground, and background.

Settings for the IMAGE_PROPERTIES feature type.

The quality of an image provided for label detection, with regard to brightness, sharpness, and contrast.

Settings for the DetectLabels request. Settings can include filters for both GENERAL_LABELS and IMAGE_PROPERTIES. GENERAL_LABELS filters can be inclusive or exclusive and applied to individual labels or label categories. IMAGE_PROPERTIES filters allow specification of a maximum number of dominant colors.

A set of optional parameters that you can use to set the criteria that the text must meet to be included in your response. WordFilter looks at a word’s height, width, and minimum confidence. RegionOfInterest lets you set a specific region of the image to look for text in.

A training dataset or a test dataset used in a dataset distribution operation. For more information, see "DistributeDatasetEntries".

A description of the dominant colors in an image.

The emotions that appear to be expressed on the face, and the confidence level in the determination. The API is only making a determination of the physical appearance of a person's face. It is not a determination of the person’s internal emotional state and should not be used in such a way. For example, a person pretending to have a sad face might not be sad emotionally.

Information about an item of Personal Protective Equipment (PPE) detected by "DetectProtectiveEquipment". For more information, see "DetectProtectiveEquipment".

The evaluation results for the training of a model.

Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.

Indicates whether or not the eyes on the face are open, and the confidence level in the determination.

Describes the face properties such as the bounding box, face ID, image ID of the input image, and external image ID that you assigned.

Structure containing attributes of the face that the algorithm detected.

Information about a face detected in a video analysis request and the time the face was detected in the video.

Provides face metadata. In addition, it also provides the confidence in the match of this face with the input face.

Object containing both the face metadata (stored in the backend database), and facial attributes that are detected but aren't stored in the database.

Input face recognition parameters for an Amazon Rekognition stream processor. Includes the collection to use for face recognition and the face attributes to detect. Defining the settings is required in the request parameter for "CreateStreamProcessor".

The predicted gender of a detected face.

Contains filters for the object labels returned by DetectLabels. Filters can be inclusive, exclusive, or a combination of both and can be applied to individual l abels or entire label categories.

Information about where an object ("DetectCustomLabels") or text ("DetectText") is located on an image.

The S3 bucket that contains an Amazon Sagemaker Ground Truth format manifest file.

Shows the results of the human in the loop evaluation. If there is no HumanLoopArn, the input did not trigger human review.

Sets up the flow definition the image will be sent to if one of the conditions is met. You can also set certain attributes of the image before review.

Allows you to set attributes of the image. Currently, you can declare an image as free of personally identifiable information.

Provides the input image either as bytes or an S3 object.

Identifies face image brightness and sharpness.

An instance of a label returned by Amazon Rekognition Image ("DetectLabels") or by Amazon Rekognition Video ("GetLabelDetection").

The Kinesis data stream Amazon Rekognition to which the analysis results of a Amazon Rekognition stream processor are streamed. For more information, see CreateStreamProcessor in the Amazon Rekognition Developer Guide.

Kinesis video stream stream that provides the source streaming video for a Amazon Rekognition Video stream processor. For more information, see CreateStreamProcessor in the Amazon Rekognition Developer Guide.

Specifies the starting point in a Kinesis stream to start processing. You can use the producer timestamp or the fragment number. One of either producer timestamp or fragment number is required. If you use the producer timestamp, you must put the time in milliseconds. For more information about fragment numbers, see Fragment.

The known gender identity for the celebrity that matches the provided ID. The known gender identity can be Male, Female, Nonbinary, or Unlisted.

Structure containing details about the detected label, including the name, detected instances, parent labels, and level of confidence.

A potential alias of for a given label.

The category that applies to a given label.

Information about a label detected in a video analysis request and the time the label was detected in the video.

Contains the specified filters that should be applied to a list of returned GENERAL_LABELS.

Indicates the location of the landmark on the face.

Provides information about a single type of inappropriate, unwanted, or offensive content found in an image or video. Each type of moderated content has a label within a hierarchical taxonomy. For more information, see Content moderation in the Amazon Rekognition Developer Guide.

Indicates whether or not the mouth on the face is open, and the confidence level in the determination.

Indicates whether or not the face has a mustache, and the confidence level in the determination.

The Amazon Simple Notification Service topic to which Amazon Rekognition publishes the completion status of a video analysis operation. For more information, see Calling Amazon Rekognition Video operations. Note that the Amazon SNS topic must have a topic name that begins with AmazonRekognition if you are using the AmazonRekognitionServiceRole permissions policy to access the topic. For more information, see Giving access to multiple Amazon SNS topics.

The S3 bucket and folder location where training output is placed.

A parent label for a label. A label can have 0, 1, or more parents.

Details about a person detected in a video analysis request.

Details and path tracking information for a single time a person's path is tracked in a video. Amazon Rekognition operations that track people's paths return an array of PersonDetection objects with elements for each time a person's path is tracked in a video.

Information about a person whose face matches a face(s) in an Amazon Rekognition collection. Includes information about the faces in the Amazon Rekognition collection ("FaceMatch"), information about the person ("PersonDetail"), and the time stamp for when the person was detected in a video. An array of PersonMatch objects is returned by "GetFaceSearch".

The X and Y coordinates of a point on an image or video frame. The X and Y values are ratios of the overall image size or video resolution. For example, if an input image is 700x200 and the values are X=0.5 and Y=0.25, then the point is at the (350,50) pixel coordinate on the image.

Indicates the pose of the face as determined by its pitch, roll, and yaw.

A description of an Amazon Rekognition Custom Labels project. For more information, see "DescribeProjects".

Describes a project policy in the response from "ListProjectPolicies".

A description of a version of an Amazon Rekognition Custom Labels model.

Information about a body part detected by "DetectProtectiveEquipment" that contains PPE. An array of ProtectiveEquipmentBodyPart objects is returned for each person detected by DetectProtectiveEquipment.

A person detected by a call to "DetectProtectiveEquipment". The API returns all persons detected in the input image in an array of ProtectiveEquipmentPerson objects.

Specifies summary attributes to return from a call to "DetectProtectiveEquipment". You can specify which types of PPE to summarize. You can also specify a minimum confidence value for detections. Summary information is returned in the Summary ("ProtectiveEquipmentSummary") field of the response from DetectProtectiveEquipment. The summary includes which persons in an image were detected wearing the requested types of person protective equipment (PPE), which persons were detected as not wearing PPE, and the persons in which a determination could not be made. For more information, see "ProtectiveEquipmentSummary".

Summary information for required items of personal protective equipment (PPE) detected on persons by a call to "DetectProtectiveEquipment". You specify the required type of PPE in the SummarizationAttributes ("ProtectiveEquipmentSummarizationAttributes") input parameter. The summary includes which persons were detected wearing the required personal protective equipment (PersonsWithRequiredEquipment), which persons were detected as not wearing the required PPE (PersonsWithoutRequiredEquipment), and the persons in which a determination could not be made (PersonsIndeterminate).

Specifies a location within the frame that Rekognition checks for objects of interest such as text, labels, or faces. It uses a BoundingBox or Polygon to set a region of the screen.

The Amazon S3 bucket location to which Amazon Rekognition publishes the detailed inference results of a video analysis operation. These results include the name of the stream processor resource, the session ID of the stream processing session, and labeled timestamps and bounding boxes for detected labels.

Provides the S3 bucket name and object name.

A technical cue or shot detection segment detected in a video. An array of SegmentDetection objects containing all segments detected in a stored video is returned by "GetSegmentDetection".

Information about the type of a segment requested in a call to "StartSegmentDetection". An array of SegmentTypeInfo objects is returned by the response from "GetSegmentDetection".

Information about a shot detection segment detected in a video. For more information, see "SegmentDetection".

Indicates whether or not the face is smiling, and the confidence level in the determination.

Filters applied to the technical cue or shot detection segments. For more information, see "StartSegmentDetection".

Filters for the shot detection segments returned by GetSegmentDetection. For more information, see "StartSegmentDetectionFilters".

Filters for the technical segments returned by "GetSegmentDetection". For more information, see "StartSegmentDetectionFilters".

Set of optional parameters that let you set the criteria text must meet to be included in your response. WordFilter looks at a word's height, width and minimum confidence. RegionOfInterest lets you set a specific region of the screen to look for text in.

This is a required parameter for label detection stream processors and should not be used to start a face search stream processor.

Specifies when to stop processing the stream. You can specify a maximum amount of time to process the video.

An object that recognizes faces or labels in a streaming video. An Amazon Rekognition stream processor is created by a call to "CreateStreamProcessor". The request parameters for CreateStreamProcessor describe the Kinesis video stream source for the streaming video, face recognition parameters, and where to stream the analysis resullts.

Allows you to opt in or opt out to share 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.

Information about the source streaming video.

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

Information about the Amazon Kinesis Data Streams stream to which a Amazon Rekognition Video stream processor streams the results of a video analysis. For more information, see CreateStreamProcessor in the Amazon Rekognition Developer Guide.

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

The stream processor settings that you want to update. ConnectedHome settings can be updated to detect different labels with a different minimum confidence.

The S3 bucket that contains the training summary. The training summary includes aggregated evaluation metrics for the entire testing dataset and metrics for each individual label.

Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.

Information about a technical cue segment. For more information, see "SegmentDetection".

The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition Custom Labels uses the 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.

Information about a word or line of text detected by "DetectText".

Information about text detected in a video. Incudes the detected text, the time in milliseconds from the start of the video that the text was detected, and where it was detected on the screen.

The dataset used for training.

Sagemaker Groundtruth format manifest files for the input, output and validation datasets that are used and created during testing.

A face that "IndexFaces" detected, but didn't index. Use the Reasons response attribute to determine why a face wasn't indexed.

Contains the Amazon S3 bucket location of the validation data for a model training job.

Video file stored in an Amazon S3 bucket. Amazon Rekognition video start operations such as "StartLabelDetection" use Video to specify a video for analysis. The supported file formats are .mp4, .mov and .avi.

Information about a video that Amazon Rekognition analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition video operation.

A list of enum string of possible gender values that Celebrity returns.