Which solution will meet these requirements with the LEAST operational effort?
Use a PaddleOCR model in Amazon SageMaker to detect and extract the required text and fields. Use a SageMaker text classification model to classify the document.
Use a PaddleOCR model in Amazon SageMaker to detect and extract the required text and fields. Use Amazon Comprehend to classify the document.
Use Amazon Textract to detect and extract the required text and fields. Use Amazon Rekognition to classify the document.
Use Amazon Textract to detect and extract the required text and fields. Use Amazon Comprehend to classify the document.
Explanations:
While PaddleOCR is capable of extracting text and fields, it requires more setup and maintenance than using fully managed services like Amazon Textract. Additionally, using a SageMaker text classification model requires custom model training and management, which increases operational effort.
Similar to Option A, this option involves using PaddleOCR for text extraction, which adds complexity and maintenance. While Amazon Comprehend can handle document classification effectively, the need to manage and deploy the PaddleOCR model makes this solution less suitable for low maintenance requirements.
Although Amazon Textract can effectively extract text and fields, Amazon Rekognition is not designed for document classification; it is primarily focused on image analysis and facial recognition. Thus, this combination does not adequately meet the requirements for document classification.
Amazon Textract is a fully managed service that automatically extracts text and fields from documents with minimal setup and maintenance. Coupled with Amazon Comprehend, which can classify documents with pre-trained models, this solution requires the least operational effort while effectively fulfilling both text extraction and classification needs.
I value that the answer is:
Use Amazon Textract to detect and extract the required text and fields. Use Amazon Comprehend to classify the document.