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Amazon Textract explorer example

Purpose

Shows how to use the AWS SDK for Python (Boto3) with Amazon Textract to detect text, form, and table elements in a document image. The input image and Textract output are shown in a Tkinter application that lets you explore the detected elements.

  • Submit a document image to Textract and explore the output of detected elements.
  • Submit images directly to Textract or through an Amazon Simple Storage Service (Amazon S3) bucket.
  • Use asynchronous APIs to start a job that publishes a notification to an Amazon Simple Notification Service (Amazon SNS) topic when the job completes.
  • Poll an Amazon Simple Queue Service (Amazon SQS) queue for a job completion message and display the results.

Prerequisites

Cautions

  • As an AWS best practice, grant this code least privilege, or only the permissions required to perform a task. For more information, see Grant Least Privilege in the AWS Identity and Access Management User Guide.
  • This code has not been tested in all AWS Regions. Some AWS services are available only in specific Regions. For more information, see the AWS Region Table on the AWS website.
  • Running this code might result in charges to your AWS account.

Running the code

The asynchronous APIs used in this example require an Amazon S3 bucket to contain input images, an Amazon SNS topic to publish notifications, and an Amazon SQS queue that the application can poll for notification messages. These resources are managed by an AWS CloudFormation stack that is defined in the accompanying setup.yaml file.

Deploy resources

Deploy prerequisite resources by running the example script with the deploy flag at a command prompt.

python textract_demo_launcher.py deploy

Run the usage demonstration

Run the usage example with the demo flag at a command prompt.

python textract_demo_launcher.py demo

Destroy resources

Destroy example resources by running the script with the destroy flag at a command prompt.

python textract_demo_launcher.py destroy

Example structure

The example contains the following files.

textract_app.py

A Tkinter application that displays document images, starts Textract synchronous and asynchronous detection processes, and shows the hierarchy of detected elements. Elements can be clicked to explore the hierarchy and draw bounding polygons on the input image.

textract_demo_launcher.py

Launches the Textract demo.

  • Run with the deploy option to deploy prerequisite resources defined in the setup.yaml CloudFormation stack.
  • Run with the demo option to show the Tkinter application.
  • Run with the destroy option to destroy prerequisite resources.

textract_wrapper.py

Wraps Textract, Amazon S3, Amazon SNS, and Amazon SQS functions that are used by the application.

setup.yaml

Contains a CloudFormation script that is used to create the resources needed for the demo.

  • An Amazon S3 bucket that contains input document images.
  • An Amazon SNS topic that receives notification of job completion.
  • An IAM role that grants permission to publish to the topic.
  • An Amazon SQS queue that is subscribed to receive messages from the topic.

The setup.yaml file was built from the AWS Cloud Development Kit (AWS CDK) source script here: /resources/cdk/textract_example_s3_sns_sqs/setup.ts.

Running the tests

The unit tests in this module use the botocore Stubber. The Stubber captures requests before they are sent to AWS, and returns a mocked response. To run all of the tests, run the following command in your [GitHub root]/python/cross_service/textract_explorer folder.

python -m pytest

Additional information

Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

SPDX-License-Identifier: Apache-2.0