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textract_python_analyze_document_text.py

textract_python_analyze_document_text.py demonstrates how to analyze text in a document.

#Analyzes text in a document stored in an S3 bucket. Display polygon box around text and angled text import boto3 import io from io import BytesIO import sys import math from PIL import Image, ImageDraw, ImageFont def ShowBoundingBox(draw,box,width,height,boxColor): left = width * box['Left'] top = height * box['Top'] draw.rectangle([left,top, left + (width * box['Width']), top +(height * box['Height'])],outline=boxColor) def ShowSelectedElement(draw,box,width,height,boxColor): left = width * box['Left'] top = height * box['Top'] draw.rectangle([left,top, left + (width * box['Width']), top +(height * box['Height'])],fill=boxColor) # Displays information about a block returned by text detection and text analysis def DisplayBlockInformation(block): print('Id: {}'.format(block['Id'])) if 'Text' in block: print(' Detected: ' + block['Text']) print(' Type: ' + block['BlockType']) if 'Confidence' in block: print(' Confidence: ' + "{:.2f}".format(block['Confidence']) + "%") if block['BlockType'] == 'CELL': print(" Cell information") print(" Column:" + str(block['ColumnIndex'])) print(" Row:" + str(block['RowIndex'])) print(" Column Span:" + str(block['ColumnSpan'])) print(" RowSpan:" + str(block['ColumnSpan'])) if 'Relationships' in block: print(' Relationships: {}'.format(block['Relationships'])) print(' Geometry: ') print(' Bounding Box: {}'.format(block['Geometry']['BoundingBox'])) print(' Polygon: {}'.format(block['Geometry']['Polygon'])) if block['BlockType'] == "KEY_VALUE_SET": print (' Entity Type: ' + block['EntityTypes'][0]) if block['BlockType'] == 'SELECTION_ELEMENT': print(' Selection element detected: ', end='') if block['SelectionStatus'] =='SELECTED': print('Selected') else: print('Not selected') if 'Page' in block: print('Page: ' + block['Page']) print() def process_text_analysis(bucket, document): #Get the document from S3 s3_connection = boto3.resource('s3') s3_object = s3_connection.Object(bucket,document) s3_response = s3_object.get() stream = io.BytesIO(s3_response['Body'].read()) image=Image.open(stream) # Analyze the document client = boto3.client('textract') image_binary = stream.getvalue() response = client.analyze_document(Document={'Bytes': image_binary}, FeatureTypes=["TABLES", "FORMS"]) # Alternatively, process using S3 object #response = client.analyze_document( # Document={'S3Object': {'Bucket': bucket, 'Name': document}}, # FeatureTypes=["TABLES", "FORMS"]) #Get the text blocks blocks=response['Blocks'] width, height =image.size draw = ImageDraw.Draw(image) print ('Detected Document Text') # Create image showing bounding box/polygon the detected lines/text for block in blocks: DisplayBlockInformation(block) draw=ImageDraw.Draw(image) if block['BlockType'] == "KEY_VALUE_SET": if block['EntityTypes'][0] == "KEY": ShowBoundingBox(draw, block['Geometry']['BoundingBox'],width,height,'red') else: ShowBoundingBox(draw, block['Geometry']['BoundingBox'],width,height,'green') if block['BlockType'] == 'TABLE': ShowBoundingBox(draw, block['Geometry']['BoundingBox'],width,height, 'blue') if block['BlockType'] == 'CELL': ShowBoundingBox(draw, block['Geometry']['BoundingBox'],width,height, 'yellow') if block['BlockType'] == 'SELECTION_ELEMENT': if block['SelectionStatus'] =='SELECTED': ShowSelectedElement(draw, block['Geometry']['BoundingBox'],width,height, 'blue') #uncomment to draw polygon for all Blocks #points=[] #for polygon in block['Geometry']['Polygon']: # points.append((width * polygon['X'], height * polygon['Y'])) #draw.polygon((points), outline='blue') # Display the image image.show() return len(blocks) def main(): bucket = '' document = '' block_count=process_text_analysis(bucket,document) print("Blocks detected: " + str(block_count)) if __name__ == "__main__": main()

Sample Details

Service: textract

Last tested: 2019-8-26

Author: reesch (AWS)

Type: full-example

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