How to use Document AI
Science & Technology
Introduction
In this article, we will explore how to use Document AI with the Google Cloud Console and API along with the Python client library. Document AI allows for the extraction of structured data from unstructured documents, making it easier to analyze and process information efficiently. We will cover the process of creating Document AI processors, utilizing the API for both online and batch processing, and understanding the Document Object structure. By following the steps outlined here, you will be able to leverage Document AI for automated document processing tasks.
Before we start processing documents, it is essential to understand Document AI processors, which act as interfaces between document files and machine learning models. Processors can be general, specialized, or custom, designed for tasks such as optical character recognition, form parsing, classification, and parsing specialized document types. We will also walk through creating a processor in the Cloud Console and testing it with a sample document.
Using the Document AI API, you can create automated scripts to handle document processing tasks. The API supports both online and batch processing, similar to Vertex AI for online and batch prediction. By defining variables, configuring the processor client, and constructing requests, you can interact with the API to extract valuable information from documents efficiently. The Document Object structure contains extracted data, metadata, and annotations, providing a comprehensive view of the processed document.
Keywords
document AI, processors, API, online processing, batch processing, Document Object structure, Google Cloud Console
FAQ
What are Document AI processors? Document AI processors serve as interfaces between document files and machine learning models, enabling tasks such as classification, parsing, and analysis of documents.
How can I create a Document AI processor? To create a Document AI processor, navigate to the Google Cloud Console, select Document AI, and create a processor instance specifying the type and region.
What is the Document Object structure? The Document Object structure contains extracted data, metadata, and annotations from processed documents, providing comprehensive information for analysis and further processing.