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textract_python_detect_document_text.py

textract_python_detect_document_text.py demonstrates how to detect text in a document.

#Detects 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 psutil import time import math from PIL import Image, ImageDraw, ImageFont # 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 'Page' in block: print('Page: ' + block['Page']) print() def process_text_detection(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) # Detect text in the document client = boto3.client('textract') #process using image bytes #image_binary = stream.getvalue() #response = client.detect_document_text(Document={'Bytes': image_binary}) #process using S3 object response = client.detect_document_text( Document={'S3Object': {'Bucket': bucket, 'Name': document}}) #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: print('Type: ' + block['BlockType']) if block['BlockType'] != 'PAGE': print('Detected: ' + block['Text']) print('Confidence: ' + "{:.2f}".format(block['Confidence']) + "%") print('Id: {}'.format(block['Id'])) if 'Relationships' in block: print('Relationships: {}'.format(block['Relationships'])) print('Bounding Box: {}'.format(block['Geometry']['BoundingBox'])) print('Polygon: {}'.format(block['Geometry']['Polygon'])) print() draw=ImageDraw.Draw(image) # Draw WORD - Green - start of word, red - end of word if block['BlockType'] == "WORD": draw.line([(width * block['Geometry']['Polygon'][0]['X'], height * block['Geometry']['Polygon'][0]['Y']), (width * block['Geometry']['Polygon'][3]['X'], height * block['Geometry']['Polygon'][3]['Y'])],fill='green', width=2) draw.line([(width * block['Geometry']['Polygon'][1]['X'], height * block['Geometry']['Polygon'][1]['Y']), (width * block['Geometry']['Polygon'][2]['X'], height * block['Geometry']['Polygon'][2]['Y'])], fill='red', width=2) # Draw box around entire LINE if block['BlockType'] == "LINE": points=[] for polygon in block['Geometry']['Polygon']: points.append((width * polygon['X'], height * polygon['Y'])) draw.polygon((points), outline='black') # Uncomment to draw bounding box #box=block['Geometry']['BoundingBox'] #left = width * box['Left'] #top = height * box['Top'] #draw.rectangle([left,top, left + (width * box['Width']), top +(height * box['Height'])],outline='black') # Display the image image.show() # display image for 10 seconds return len(blocks) def main(): bucket = '' document = '' block_count=process_text_detection(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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