Description:

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

Usage:

Example:

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

• Create a new process definition called “clsAzureMLDescribeImageDef” and open the definition 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. Provide a step name. Click the Save button. Note: Click the "AI Predict" button for the Copilot to 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 is displayed for configuration. Click the Add Row (+) button to insert an empty row. Provide a variable or global reference to store the image file path on the application server. Click the Save button. You may insert multiple variables by using the Add Row button. 

• Click the “clsAzureMLDescribeImage” step to configure its “Required” properties. Provide a step name. Provide the variable or global reference with the image file path. Provide the 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 included here for reference. 

• The “Logging” setting configuration is necessary for documentation and also measures the workflow progress and the 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 then 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. According to the image 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 here and later import them (drag-and-drop) to 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 import. Then, save the definition to confirm the changes.

Click here to download the sample file.