Starts the asynchronous detection of text in a document. Amazon Textract can detect lines of text and the words that make up a line of text.
StartDocumentTextDetection
can analyze text in documents that are in JPEG, PNG, TIFF, and PDF format. The documents are stored in an Amazon S3 bucket. Use DocumentLocation to specify the bucket name and file name of the document.
StartTextDetection
returns a job identifier (JobId
) that you use to get the results of the operation. When text detection is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you specify inNotificationChannel
. To get the results of the text detection operation, first check that the status value published to the Amazon SNS topic isSUCCEEDED
. If so, call GetDocumentTextDetection , and pass the job identifier (JobId
) from the initial call toStartDocumentTextDetection
.
For more information, see Document Text Detection .
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
start-document-text-detection
--document-location <value>
[--client-request-token <value>]
[--job-tag <value>]
[--notification-channel <value>]
[--output-config <value>]
[--kms-key-id <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
--document-location
(structure)
The location of the document to be processed.
S3Object -> (structure)
The Amazon S3 bucket that contains the input document.
Bucket -> (string)
The name of the S3 bucket. Note that the # character is not valid in the file name.
Name -> (string)
The file name of the input document. Synchronous operations can use image files that are in JPEG or PNG format. Asynchronous operations also support PDF and TIFF format files.
Version -> (string)
If the bucket has versioning enabled, you can specify the object version.
Shorthand Syntax:
S3Object={Bucket=string,Name=string,Version=string}
JSON Syntax:
{
"S3Object": {
"Bucket": "string",
"Name": "string",
"Version": "string"
}
}
--client-request-token
(string)
The idempotent token that’s used to identify the start request. If you use the same token with multiple
StartDocumentTextDetection
requests, the sameJobId
is returned. UseClientRequestToken
to prevent the same job from being accidentally started more than once. For more information, see Calling Amazon Textract Asynchronous Operations .
--job-tag
(string)
An identifier that you specify that’s included in the completion notification published to the Amazon SNS topic. For example, you can use
JobTag
to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).
--notification-channel
(structure)
The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.
SNSTopicArn -> (string)
The Amazon SNS topic that Amazon Textract posts the completion status to.
RoleArn -> (string)
The Amazon Resource Name (ARN) of an IAM role that gives Amazon Textract publishing permissions to the Amazon SNS topic.
Shorthand Syntax:
SNSTopicArn=string,RoleArn=string
JSON Syntax:
{
"SNSTopicArn": "string",
"RoleArn": "string"
}
--output-config
(structure)
Sets if the output will go to a customer defined bucket. By default Amazon Textract will save the results internally to be accessed with the GetDocumentTextDetection operation.
S3Bucket -> (string)
The name of the bucket your output will go to.
S3Prefix -> (string)
The prefix of the object key that the output will be saved to. When not enabled, the prefix will be “textract_output”.
Shorthand Syntax:
S3Bucket=string,S3Prefix=string
JSON Syntax:
{
"S3Bucket": "string",
"S3Prefix": "string"
}
--kms-key-id
(string)
The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.
--cli-input-json
| --cli-input-yaml
(string)
Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton
. If other arguments are provided on the command line, those 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. This may not be specified along with --cli-input-yaml
.
--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
. Similarly, if provided yaml-input
it will print a sample input YAML that can be used with --cli-input-yaml
. If provided with the value output
, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.
See ‘aws help’ for descriptions of global parameters.
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 start detecting text in a multi-page document
The following start-document-text-detection
example shows how to start asynchronous detection of text in a multi-page document.
Linux/macOS:
aws textract start-document-text-detection \
--document-location '{"S3Object":{"Bucket":"bucket","Name":"document"}}' \
--notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleARN"
Windows:
aws textract start-document-text-detection \
--document-location "{\"S3Object\":{\"Bucket\":\"bucket\",\"Name\":\"document\"}}" \
--region region-name \
--notification-channel "SNSTopicArn=arn:snsTopic,RoleArn=roleArn"
Output:
{
"JobId": "57849a3dc627d4df74123dca269d69f7b89329c870c65bb16c9fd63409d200b9"
}
For more information, see Detecting and Analyzing Text in Multi-Page Documents in the Amazon Textract Developers Guide
JobId -> (string)
The identifier of the text detection job for the document. Use
JobId
to identify the job in a subsequent call toGetDocumentTextDetection
. AJobId
value is only valid for 7 days.