How To Use Amazon Textract

Amazon Textract is a machine learning service by AWS that automatically extracts text, handwriting, and data from scanned documents. It not only identifies printed text but also understands the structure of documents, extracting tables, forms, and key-value pairs. This makes it an excellent choice for processing documents such as invoices, receipts, forms, and other data-heavy formats.

This guide walks you through using Amazon Textract to analyze and extract data from documents effectively.

Benefits of Using Amazon Textract

Using Amazon Textract provides a range of advantages:

• Automated Document Processing: Extracts data from documents, saving time and reducing manual entry errors.
• High Accuracy: Recognizes tables, forms, and structured data to accurately extract valuable information.
• Integrates with AWS Services: Works well with other AWS services like Amazon S3, Amazon Comprehend, and Amazon SageMaker for advanced document workflows.
• Scalable Solution: Processes large volumes of documents, making it suitable for businesses with significant data entry needs.

Step-by-Step Guide to Using Amazon Textract

Step 1: Set Up AWS and Textract Permissions

To use Amazon Textract, you’ll need an AWS account and an IAM role with appropriate permissions.

1. Sign in to AWS: Go to the AWS Management Console and log in to your AWS account.
2. Set Up IAM Permissions: Go to IAM in the console to create a user or role for Textract with necessary permissions.
   • Assign the AmazonTextractFullAccess policy to your user or role, along with permissions for Amazon S3 if using it to store documents.
3. Enable Amazon Textract: Navigate to the Amazon Textract service to get started.

Step 2: Prepare Documents for Analysis

Amazon Textract supports multiple file formats, such as PNG, JPEG, PDF, and TIFF. Ensure that documents are clear and high quality for the best results.

1. Optimize Document Quality: Make sure documents are high-resolution and clear, with legible text and minimal background noise.
2. Store Documents in Amazon S3 (Optional): For bulk processing, upload documents to an Amazon S3 bucket. Textract can directly analyze files stored in S3.
3. Access Document Paths: If using S3, note the S3 path (e.g., s3://your-bucket-name/document.pdf) to access your document in Textract.

Step 3: Use Textract in the AWS Console

The AWS Management Console provides a quick way to try out Textract for document analysis.

1. Open Textract in AWS Console: Go to the Amazon Textract service page.
2. Select Document Type: Choose whether you want to analyze a Document or Table/Form.
   • For simple text extraction, choose Document.
   • For structured data extraction (tables, forms), choose Forms and Tables.
3. Upload or Choose Document: Upload your document or specify the S3 bucket path.
4. Analyze Document: Click Analyze to start processing. Once complete, Textract displays extracted text, tables, and key-value pairs for you to review.

Step 4: Analyze Documents Using AWS SDK or CLI

To automate Textract processing, use the AWS SDK or CLI to interact with Textract programmatically.

Using AWS CLI

1. Run Text Detection: To extract plain text, use the detect-document-text command:
   
   aws textract detect-document-text –document ‘{“S3Object”:{“Bucket”:”your-bucket-name”,”Name”:”your-document-name”}}’
   
2. Run Form/Table Analysis: To extract structured data like forms or tables, use analyze-document with Forms and Tables options:
   
   aws textract analyze-document –document ‘{“S3Object”:{“Bucket”:”your-bucket-name”,”Name”:”your-document-name”}}’ –feature-types ‘[“FORMS”, “TABLES”]’

Step 5: Process and Structure Extracted Data

Textract outputs data as JSON. Depending on your use case, you may need to process this data further to extract and format the required information.

1. Extract Key-Value Pairs: In form documents, Textract identifies key-value pairs, allowing you to structure data effectively.
2. Parse Tables: Textract organizes tables into cells and rows in JSON. Iterate through these to reconstruct tables in your desired format, such as CSV or Excel.
3. Format Data for Storage or Analysis: Save extracted data to a database, send it to a data analysis pipeline, or store it in a file format (e.g., CSV or JSON) for further use.

Step 6: Automate Document Processing with AWS Lambda

To process documents automatically, you can integrate Textract with AWS Lambda.

1. Create an S3 Trigger for Lambda:
   • In the S3 bucket, create an event trigger to invoke Lambda whenever a document is uploaded.
2. Write Lambda Function:
   • Write a Lambda function that processes the document using Textract and stores the results in an S3 bucket or database.
3. Deploy the Lambda Function: Set the function to execute whenever a new file is uploaded to the specified S3 bucket.

This setup allows you to process documents in real time, making it ideal for applications that handle frequent document uploads.

Step 7: Visualize Data with Amazon QuickSight

Amazon QuickSight can be used to create visualizations and reports based on the data extracted by Textract.

1. Store Extracted Data in a Database: Store structured data (like tables) extracted from Textract in Amazon RDS or Amazon Redshift.
2. Connect QuickSight to Data Source: Link QuickSight to your database or storage to import the Textract data.
3. Create Visualizations: Use QuickSight’s dashboard and visualization features to build reports or visualizations from your document data.

Best Practices for Using Amazon Textract

1. Use High-Resolution Documents: Textract performs better with high-quality, high-resolution documents where text and tables are clearly visible.
2. Leverage Batch Processing: For large numbers of documents, consider batch processing through the S3 integration, Lambda, or S3 Batch Operations to handle processing automatically.
3. Optimize for Security: Ensure that S3 buckets storing sensitive documents and Textract results are encrypted and access-controlled.
4. Handle JSON Output: Textract’s output format is JSON, so have a JSON parser or handler ready to structure and process extracted data as required.
5. Monitor Usage and Costs: Regularly check your Textract usage and costs in the AWS Billing Console to avoid unexpected charges, especially if processing large volumes of documents.

Frequently Asked Questions Related to Using Amazon Textract