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[ aws . rekognition ]

create-stream-processor

Description

Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces or to detect labels in a streaming video.

Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. There are two different settings for stream processors in Amazon Rekognition: detecting faces and detecting labels.

  • If you are creating a stream processor for detecting faces, 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. After you have finished analyzing a streaming video, use StopStreamProcessor to stop processing.
  • If you are creating a stream processor to detect labels, you provide as input a Kinesis video stream (Input ), Amazon S3 bucket information (Output ), and an Amazon SNS topic ARN (NotificationChannel ). You can also provide a KMS key ID to encrypt the data sent to your Amazon S3 bucket. You specify what you want to detect in ConnectedHomeSettings , such as people, packages and people, or pets, people, and packages. You can also specify where in the frame you want Amazon Rekognition to monitor with RegionsOfInterest . When you run the StartStreamProcessor operation on a label detection stream processor, you input start and stop information to determine the length of the processing time.

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.

This operation requires permissions to perform the rekognition:CreateStreamProcessor action. If you want to tag your stream processor, you also require permission to perform the rekognition:TagResource operation.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  create-stream-processor
--input <value>
--name <value>
--settings <value>
--role-arn <value>
[--tags <value>]
[--notification-channel <value>]
[--kms-key-id <value>]
[--regions-of-interest <value>]
[--data-sharing-preference <value>]
--stream-processor-output <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--input (structure)

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.

KinesisVideoStream -> (structure)

The Kinesis video stream input stream for the source streaming video.

Arn -> (string)

ARN of the Kinesis video stream stream that streams the source video.

Shorthand Syntax:

KinesisVideoStream={Arn=string}

JSON Syntax:

{
  "KinesisVideoStream": {
    "Arn": "string"
  }
}

--name (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.

--settings (structure)

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.

FaceSearch -> (structure)

Face search settings to use on a streaming video.

CollectionId -> (string)

The ID of a collection that contains faces that you want to search for.

FaceMatchThreshold -> (float)

Minimum face match confidence score that must be met to return a result for a recognized face. The default is 80. 0 is the lowest confidence. 100 is the highest confidence. Values between 0 and 100 are accepted, and values lower than 80 are set to 80.

ConnectedHome -> (structure)

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.

Labels -> (list)

Specifies what you want to detect in the video, such as people, packages, or pets. The current valid labels you can include in this list are: "PERSON", "PET", "PACKAGE", and "ALL".

(string)

MinConfidence -> (float)

The minimum confidence required to label an object in the video.

Shorthand Syntax:

FaceSearch={CollectionId=string,FaceMatchThreshold=float},ConnectedHome={Labels=[string,string],MinConfidence=float}

JSON Syntax:

{
  "FaceSearch": {
    "CollectionId": "string",
    "FaceMatchThreshold": float
  },
  "ConnectedHome": {
    "Labels": ["string", ...],
    "MinConfidence": float
  }
}

--role-arn (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.

--tags (map)

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

key -> (string)

value -> (string)

Shorthand Syntax:

KeyName1=string,KeyName2=string

JSON Syntax:

{"string": "string"
  ...}

--notification-channel (structure)

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.

SNSTopicArn -> (string)

The Amazon Resource Number (ARN) of the Amazon Amazon Simple Notification Service topic to which Amazon Rekognition posts the completion status.

Shorthand Syntax:

SNSTopicArn=string

JSON Syntax:

{
  "SNSTopicArn": "string"
}

--kms-key-id (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.

--regions-of-interest (list)

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.

(structure)

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.

A word, face, or label is included in the region if it is more than half in that region. If there is more than one region, the word, face, or label is compared with all regions of the screen. Any object of interest that is more than half in a region is kept in the results.

BoundingBox -> (structure)

The box representing a region of interest on screen.

Width -> (float)

Width of the bounding box as a ratio of the overall image width.

Height -> (float)

Height of the bounding box as a ratio of the overall image height.

Left -> (float)

Left coordinate of the bounding box as a ratio of overall image width.

Top -> (float)

Top coordinate of the bounding box as a ratio of overall image height.

Polygon -> (list)

Specifies a shape made up of up to 10 Point objects to define a region of interest.

(structure)

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.

An array of Point objects makes up a Polygon . A Polygon is returned by DetectText and by DetectCustomLabels Polygon represents a fine-grained polygon around a detected item. For more information, see Geometry in the Amazon Rekognition Developer Guide.

X -> (float)

The value of the X coordinate for a point on a Polygon .

Y -> (float)

The value of the Y coordinate for a point on a Polygon .

Shorthand Syntax:

BoundingBox={Width=float,Height=float,Left=float,Top=float},Polygon=[{X=float,Y=float},{X=float,Y=float}] ...

JSON Syntax:

[
  {
    "BoundingBox": {
      "Width": float,
      "Height": float,
      "Left": float,
      "Top": float
    },
    "Polygon": [
      {
        "X": float,
        "Y": float
      }
      ...
    ]
  }
  ...
]

--data-sharing-preference (structure)

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.

OptIn -> (boolean)

If this option is set to true, you choose to share data with Rekognition to improve model performance.

Shorthand Syntax:

OptIn=boolean

JSON Syntax:

{
  "OptIn": true|false
}

--stream-processor-output (structure)

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.

KinesisDataStream -> (structure)

The Amazon Kinesis Data Streams stream to which the Amazon Rekognition stream processor streams the analysis results.

Arn -> (string)

ARN of the output Amazon Kinesis Data Streams stream.

S3Destination -> (structure)

The Amazon S3 bucket location to which Amazon Rekognition publishes the detailed inference results of a video analysis operation.

Bucket -> (string)

The name of the Amazon S3 bucket you want to associate with the streaming video project. You must be the owner of the Amazon S3 bucket.

KeyPrefix -> (string)

The prefix value of the location within the bucket that you want the information to be published to. For more information, see Using prefixes .

Shorthand Syntax:

KinesisDataStream={Arn=string},S3Destination={Bucket=string,KeyPrefix=string}

JSON Syntax:

{
  "KinesisDataStream": {
    "Arn": "string"
  },
  "S3Destination": {
    "Bucket": "string",
    "KeyPrefix": "string"
  }
}

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Examples

Note

To use the following examples, you must have the AWS CLI installed and configured. See the Getting started guide in the AWS CLI User Guide for more information.

Unless otherwise stated, all examples have unix-like quotation rules. These examples will need to be adapted to your terminal's quoting rules. See Using quotation marks with strings in the AWS CLI User Guide .

To create a new stream processor

The following create-stream-processor example creates a new stream processor with the specified configuration.

aws rekognition create-stream-processor --name my-stream-processor\
    --input '{"KinesisVideoStream":{"Arn":"arn:aws:kinesisvideo:us-west-2:123456789012:stream/macwebcam/1530559711205"}}'\
    --stream-processor-output '{"KinesisDataStream":{"Arn":"arn:aws:kinesis:us-west-2:123456789012:stream/AmazonRekognitionRekStream"}}'\
    --role-arn arn:aws:iam::123456789012:role/AmazonRekognitionDetect\
    --settings '{"FaceSearch":{"CollectionId":"MyCollection","FaceMatchThreshold":85.5}}'

Output:

{
    "StreamProcessorArn": "arn:aws:rekognition:us-west-2:123456789012:streamprocessor/my-stream-processor"
}

For more information, see Working with Streaming Videos in the Amazon Rekognition Developer Guide.

Output

StreamProcessorArn -> (string)

Amazon Resource Number for the newly created stream processor.