How to Invoke HTTP Web Service of Dynamsoft SDKs with Power Automate for Desktop

Microsoft Power Automate is a powerful service designed to automate workflows between various apps and services. Its Desktop version provides the added capability of automating desktop-centric operations, with or without user interface interactions. In this article, we will explore how to integrate Dynamsoft Barcode Reader, Dynamsoft Document Normalizer, and Dynamsoft Label Recognizer into a web service using Flask. By leveraging this web API, we can seamlessly invoke these Dynamsoft tools within Power Automate for Desktop. This enables you to transform the created flow into a convenient desktop application that significantly enhances your daily work efficiency.

Installing Python Packages

pip install dbr mrz-scanner-sdk document-scanner-sdk opencv-python flask

To use Dynamsoft SDKs, you need to apply for a trial license.

Does Power Automate Support External Python Libraries?

If you have tried to use Python script in Power Automate for Desktop, you may have noticed that it does not support external libraries installed via pip. This is because Power Automate Desktop uses IronPython, which is a .NET implementation of Python. IronPython is a subset of the Python language, and it does not support external libraries. To address this issue, we can create a web service using Flask, and then invoke the web API using Power Automate HTTP action.

Setting Up an HTTP Web Service Using Flask

  1. Import the dependent packages:
     from flask import Flask, request, jsonify
     import dbr
     import base64
     version = dbr.__version__
     import urllib.parse
     import mrzscanner
     import docscanner
     import numpy as np
     import cv2
     import time
     from dbr import *
  2. Set the Dynamsoft license key and initialize the three SDKs. You need to replace the license key with your own.
     license_key = "DLS2eyJoYW5kc2hha2VDb2RlIjoiMjAwMDAxLTE2NDk4Mjk3OTI2MzUiLCJvcmdhbml6YXRpb25JRCI6IjIwMDAwMSIsInNlc3Npb25QYXNzd29yZCI6IndTcGR6Vm05WDJrcEQ5YUoifQ=="
     reader = BarcodeReader()
     mrz_scanner = mrzscanner.createInstance()
     doc_scanner = docscanner.createInstance()
  3. Create a Flask app and define the web API endpoints:
     app = Flask(__name__)
     @app.route('/api/dbr/decode', methods=['POST'])
     def dbr_decode():
         return handle_request(request, 'dbr')
     @app.route('/api/mrz/scan', methods=['POST'])
     def mrz_scan():
         return handle_request(request, 'mrz')
     @app.route('/api/document/rectify', methods=['POST'])
     def document_rectify():
         return handle_request(request, 'document')
     if __name__ == '__main__':
  4. Handle the HTTP request to get the image data from request.files or request body. The image data from the request body is encoded in base64 format, so we need to decode it first.
     def handle_request(request, sdk):
         output = []
         request_body ='utf-8')
         if request_body != '':
                 base64_content = urllib.parse.unquote(request_body)
                 file_content = base64.b64decode(base64_content)
                 return 'Invalid base64 string', 400
             output = process_file(file_content, sdk)
             if 'file' not in request.files:
                 return 'No file uploaded', 400
             file = request.files['file']
             if file.filename == '':
                 return 'Empty file', 400
             file_content =
             output = process_file(file_content, sdk)
         return jsonify(results=output)
  5. Invoke the corresponding SDK methods to process the image data for barcode detection, document rectification and MRZ recognition respectively.
     def decode_file_stream(file_content):
         output = []
             results = reader.decode_file_stream(file_content)
             for result in results:
                 output.append({'format': result.barcode_format_string, 'text': result.barcode_text})
         except BarcodeReaderError as error:
             output = error
         return output
     def mrz_decode_file_stream(file_content):
         output = []
         results = mrz_scanner.decodeMat(file_content)
         for result in results:
         return output
     def document_rectify_file_stream(file_content):
         output = []
         results = doc_scanner.detectMat(file_content)
         for result in results:
             x1 = result.x1
             y1 = result.y1
             x2 = result.x2
             y2 = result.y2
             x3 = result.x3
             y3 = result.y3
             x4 = result.x4
             y4 = result.y4
             normalized_image = doc_scanner.normalizeBuffer(file_content, x1, y1, x2, y2, x3, y3, x4, y4)
             image_path = os.path.join(os.getcwd(), str(time.time()) + '.png')
         return output
     def process_file(file_content, sdk):
         output = []
         if sdk == 'dbr':
             output = decode_file_stream(file_content)
         elif sdk == 'mrz':
             output = mrz_decode_file_stream(cv2.imdecode(np.frombuffer(file_content, np.uint8), cv2.IMREAD_COLOR))
         elif sdk == 'document':
             output = document_rectify_file_stream(cv2.imdecode(np.frombuffer(file_content, np.uint8), cv2.IMREAD_COLOR))
         return output
  6. Start the Flask server and test the web API with curl commands:
     # barcode
     curl -X POST -F 'file=@./barcode.jpg'
     # mrz
     curl -X POST -F 'file=@./mrz.png'
     # document
     curl -X POST -F 'file=@./document.png'

Invoking Web Service in Power Automate for Desktop

In the following section, we will show you how to create a flow step by step.

  1. Launch Power Automate for Desktop and create a new flow.

    create flow

  2. Create a loop. Since we want to keep the flow running as a tool, we can set a big number for the loop count.


  3. In the loop, add a Display custom form action. Open Custom form designer to add Choice set input and Submit. The ID of the Choice set input is Options, which will be used in the next step.

    display custom form

    The custom form looks like this:

    custom form

  4. Create a Switch action to check the option value with %CustomFormData2['Options']%.


  5. Create four cases: Barcode, MRZ, Document, and Quit.


    • The Barcode case is used to decode 1D/2D barcodes from an image file or a screenshot.

      barcode case

    • The MRZ case is used to scan MRZ from an image file.

      mrz case

    • The Document case is used to rectify a document image.

      document case

    • The default case is used to quit the loop when the selected option is Quit.

Decode Barcodes from an Image File or a Screenshot


  1. Add a Display select file dialog action to let the user select an image file.

    select file

  2. Add a Convert file to Base64 action to convert the image file to base64 format.

    convert to base64

  3. Add a Invoke web service action. Set the URL to, the Method to POST, the Accept to application/json, the Content type to application/json and the Request body to %Base64Text%.

    invoke web service

  4. Add a Display message action to show the decoded results.

    display message


  1. Add a Take screenshot action to take a screenshot. Set the Capture to All screens, the Save screenshot to to File, the Image file to any path you want, and the Image format to PNG.

    take screenshot

  2. Take the same steps 2 through 4 in the image example we just mentioned.

Scan MRZ from an Image File

The MRZ case is similar to the barcode case. The only difference is that we change URL to instead of

Rectify a Document Image

Just like the MRZ scenario, we modify the URL to Once the web API is invoked, we acquire the path of the rectified image by using the Convert JSON to custom object action. Subsequently, we use the Write to CMD session action to display the rectified image.

rectify document

Source Code