Amazon Textract Code Samples

This repository contains example code snippets showing how Amazon Textract and other AWS services can be used to get insights from documents.

Usage

python3 01-detect-text-local.py

For examples that use S3 bucket, upload sample images to an S3 bucket and update variable "s3BucketName" in the example before running it.

Python Samples

Argument	Description
01-detect-text-local.py	Example showing processing a document on local machine.
02-detect-text-s3.py	Example showing processing a document in Amazon S3 bucket.
03-reading-order.py	Example showing printing document in reading order.
04-nlp-comprehend.py	Example showing detecting entities and sentiment.
05-nlp-medical.py	Example showing detecting medical entities.
06-translate.py	Example showing translation of documents.
07-search.py	Example showing document indexing in Elasticsearch.
08-forms.py	Example showing form (key/value) processing.
09-forms-redaction.py	Example showing redacting information in document.
10-tables.py	Example showing table processing.
11-tables-expense.py	Example showing validation of table data.
12-pdf-text.py	Example showing PDF document processing.

.NET Usage

Usage: dotnet run [--switch]
To run this console app, use the following valid switches one at a time:
--detect-text-local
--detect-text-s3
--pdf-text
--forms
--forms-redaction
--tables
--tables-expense
--reading-order
--nlp-comprehend
--nlp-medical
--translate
--search
e.g. dotnet run --detect-text-s3

.NET Samples

Go to src-csharp folder for .NET samples

Argument	Description
--detect-text-local	Example showing processing a document on local machine.
--detect-text-s3	Example showing processing a document in Amazon S3 bucket.
--pdf-text	Example showing PDF document processing.
--forms	Example showing form (key/value) processing.
--forms-redaction	Example showing redacting information in document.
--tables	Example showing table processing.
--tables-expense	Example showing validation of table data.
--reading-order	Example showing printing document in reading order.
--nlp-comprehend	Example showing detecting entities and sentiment.
--nlp-medical	Example showing detecting medical entities.
--translate	Example showing translation of documents.
--search	Example showing document indexing in Elasticsearch.

Other Resources

• Large scale document processing with Amazon Textract - Reference Architecture
• Batch processing tool
• JSON response parser

License Summary

This sample code is made available under the MIT-0 license. See the LICENSE file.