04-nlp-comprehend.py

import boto3

# Document
documentName = "simple-document-image.jpg"

# Amazon Textract client
textract = boto3.client('textract')

# Call Amazon Textract
with open(documentName, "rb") as document:
    response = textract.detect_document_text(
        Document={
            'Bytes': document.read(),
        }
    )

#print(response)

# Print text
print("\nText\n========")
text = ""
for item in response["Blocks"]:
    if item["BlockType"] == "LINE":
        print ('\033[94m' +  item["Text"] + '\033[0m')
        text = text + " " + item["Text"]

# Amazon Comprehend client
comprehend = boto3.client('comprehend')

# Detect sentiment
sentiment =  comprehend.detect_sentiment(LanguageCode="en", Text=text)
print ("\nSentiment\n========\n{}".format(sentiment.get('Sentiment')))

# Detect entities
entities =  comprehend.detect_entities(LanguageCode="en", Text=text)
print("\nEntities\n========")
for entity in entities["Entities"]:
    print ("{}\t=>\t{}".format(entity["Type"], entity["Text"]))