Description:
This step describes an image as text using Azure 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 definition called “clsAzureMLDescribeImageDef”
- Select the definition and click the “design” button
- Drag the above steps to the canvas
- Connect the dots between the start and other steps as above
- Define a variable/global to store the image file path and the description text
- Click the “updateVariable” step to configure its “Settings” properties. Provide a step name.
- Click the “updateVariable” step to configure its “Advanced” properties. Click on the button to update multiple variables. A popup window is displayed for configuration. Provide a variable reference and the image file path on the application server as below. Click on the Save button to confirm.
- Click on the “clsAzureMLDescribeImage” step to configure its “Settings” properties. Provide a step name. Provide the variable/global reference with the image file path. Provide the variable/global reference to store the image description as text.
- 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 in the images below. Configure the “Logging” using the following properties.
- Save the process definition, create a new process instance, and execute. Render the process instance. Click on the process step to view its properties. The step describes an image as text using Azure ML services. As per the image in this example, the description generated is “a street with cars and buildings.”
