OCR and text read with Azure Computer Vision

Step 1. clone the repository
https://github.com/MicrosoftLearning/AI-102-AIEngineer/20-ocr

Step 2. edit read-text.py as below:

import os
import time
from PIL import Image, ImageDraw
from matplotlib import pyplot as plt

# import namespaces
from azure.cognitiveservices.vision.computervision import ComputerVisionClient
from azure.cognitiveservices.vision.computervision.models import OperationStatusCodes
from msrest.authentication import CognitiveServicesCredentials

def main():
    global cv_client
    try:
        # Get Configuration Settings
        KEY='c36f33fd15784c3984c5a88dcde4c31c'
        ENDPOINT='https://ai102cg.cognitiveservices.azure.com/'

        # Authenticate Computer Vision client
        credential = CognitiveServicesCredentials(KEY) 
        cv_client = ComputerVisionClient(ENDPOINT, credential)
     
        # Menu for text reading functions
        print('1: Use OCR API\n2: Use Read API\n3: Read handwriting\nAny other key to quit')
        command = input('Enter a number:')
        if command == '1':
            image_file = os.path.join('images','Lincoln.jpg')
            GetTextOcr(image_file)
        elif command =='2':
            image_file = os.path.join('images','Rome.pdf')
            GetTextRead(image_file)
        elif command =='3':
            image_file = os.path.join('images','Note.jpg')
            GetTextRead(image_file)
                
    except Exception as ex:
        print(ex)

def GetTextOcr(image_file):
    print('Reading text in {}\n'.format(image_file))
    # Use OCR API to read text in image
    with open(image_file, mode="rb") as image_data:
        ocr_results = cv_client.recognize_printed_text_in_stream(image_data)

    # Prepare image for drawing
    fig = plt.figure(figsize=(7, 7))
    img = Image.open(image_file)
    draw = ImageDraw.Draw(img)

    # Process the text line by line
    for region in ocr_results.regions:
        for line in region.lines:

            # Show the position of the line of text
            l,t,w,h = list(map(int, line.bounding_box.split(',')))
            draw.rectangle(((l,t), (l+w, t+h)), outline='magenta', width=5)

            # Read the words in the line of text
            line_text = ''
            for word in line.words:
                line_text += word.text + ' '
            print(line_text.rstrip())

    # Save the image with the text locations highlighted
    plt.axis('off')
    plt.imshow(img)
    outputfile = 'ocr_results.jpg'
    fig.savefig(outputfile)
    print('Results saved in', outputfile)

def GetTextRead(image_file):
    print('Reading text in {}\n'.format(image_file))
    # Use Read API to read text in image
    with open(image_file, mode="rb") as image_data:
        read_op = cv_client.read_in_stream(image_data, raw=True)

        # Get the async operation ID so we can check for the results
        operation_location = read_op.headers["Operation-Location"]
        operation_id = operation_location.split("/")[-1]

        # Wait for the asynchronous operation to complete
        while True:
            read_results = cv_client.get_read_result(operation_id)
            if read_results.status not in [OperationStatusCodes.running, OperationStatusCodes.not_started]:
                break
            time.sleep(1)

        # If the operation was successfuly, process the text line by line
        if read_results.status == OperationStatusCodes.succeeded:
            for page in read_results.analyze_result.read_results:
                for line in page.lines:
                    print(line.text)

if __name__ == "__main__":
    main()

Step 3. verify the app

C:\Hans\AI-102-AIEngineer\20-ocr\Python\read-text> python .\read-text.py
1: Use OCR API
2: Use Read API
3: Read handwriting
Any other key to quit
Enter a number:3
Reading text in images\Note.jpg

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