clsAzureMLDescribeImage step

Use this step to provide a description of an image as text using Azure ML services.

Last published at: January 22nd, 2026

Description:

This step describes an image in text using Azure Machine Learning (ML) services.

 

Inputs

  • imageFilePath – Image File Path
  • varGlobalToStoreValue – Variable / Global to store the description
 

 

Returns

  • true  – true condition
  • false – false condition
 

 

 

Usage:

 

 

Example:

Let’s build and execute the “clsAzureMLDescribeImageDef” example.

  • Create a new process definition named “clsAzureMLDescribeImageDef” and open it in designer mode. 
  • Drag a "clsAzureMLDescribeImage" step to the canvas.
  • Connect the dots between the “Start” and “clsAzureMLDescribeImage” steps, as shown above.
  • Define a variable or a global to store the image file path and the description text.
  • Click the “updateVariable” step to configure its “Required” properties. Enter a step name. Then click the Save button. Note: Click the "AI Predict" button to have the Copilot add new process steps that match your process description. 
     

 

  • Click the “updateVariable” step to configure its “Optional” properties. Click the button to update multiple variables. A pop-up window appears for configuration. Click the Add Row (+) button to insert an empty row. Enter a variable or global reference to store the image file path on the application server. Click the Save button. You may insert multiple variables using the Add Row button. 

 

  • Click the “clsAzureMLDescribeImage” step to configure its “Required” properties. Provide a step name. Provide a variable or global reference for the image file path. Provide a variable or global reference to store the image description as text. Click the Save button. Note: Click the "AI Predict" button for the Copilot to add new process steps that match your process description. 
     

 

  • An image used in this example is provided here for reference. 

 

  • The “Logging” configuration is necessary for documentation and also measures workflow progress and percent complete. This is achieved by configuring the step state and percent fields individually, as shown below. Configure the “Logging” using the following properties.

 

  • Save the process definition, create a new instance, and execute it. Render the process instance. Click the process step to view its properties. The step describes an image as text using Azure Machine Learning (ML) services. In this example, the generated description is “a street with cars and buildings.”

 

 

Definition Sample:

You may download the sample definition(s) from the link provided and later import them (drag-and-drop) into your FlowWright Process Definition (XML file) or Form Definition (HTML file) page.

Note: Please verify and complete the process steps for any missing configurations, such as file path references and database connections, after the import. Then, save the definition to confirm the changes.

Click here to download the sample file.