Description:
The Image Categorization step enables a FlowWright workflow to categorize an image by subject matter.
The step belongs to the Azure Cognitive Services category and is exposed in FlowWright with the display name Image Categorization. Its XML definition describes the capability as “Categorize images by subject matter.”
The step accepts an image file path and stores the categorization result in a workflow variable or global variable. This allows image classification to become part of an automated business process and enables subsequent workflow steps to use the returned information for routing, classification, reporting, or other processing.
Typical uses include:
- Categorizing uploaded images
- Classifying images by subject matter
- Routing images based on their category
- Enriching image-related business records
- Organizing image collections
- Supporting image-processing workflows
- Automating image classification
- Applying business rules based on image categories
This step allows FlowWright workflows to automatically incorporate image categorization without requiring users to manually classify every image.
Inputs
- Image file path – Specifies the path to the image file that should be categorized. This property is required.
- Variable/Global to store the result – Specifies the workflow variable or global variable where the image-categorization result will be stored. This property is required.
Returns
- True – Indicates that the image-categorization operation completed successfully. Workflow execution continues through the True path.
- False – Indicates that the image-categorization operation did not complete successfully. Workflow execution continues through the False path.
Usage:
The Image Categorization step is typically used after a workflow receives or generates an image that needs to be classified.
During execution:
- Provide the image file path.
- Execute the Image Categorization step.
- The image is analyzed according to its subject matter.
- The resulting categorization information is stored in the configured workflow variable or global variable.
- Continue workflow processing through the True or False execution path.
A typical workflow might look like this:
Typical workflow scenarios include:
- Image classification
- Product-image processing
- Automated media organization
- Image-based routing
- Document or photograph classification
- Image metadata enrichment
- Content-processing workflows
- Automated image review
To use this step, you need to set up an Azure ML service in the FlowWright application. Go to the Status > Settings > Configuration page. Select the Azure ML category from the drop-down menu. Click here to learn more about the Azure ML and Cognitive Service subscription.
A sample Azure ML configuration is provided here for reference.
Example:
Let’s build and execute the “clsAzureMLGetCategoriesDef” example.
- Create a new process definition named “clsAzureMLGetCategoriesDef” and open it in designer mode.
- Drag a "clsAzureMLgetCategories" step to the canvas.
- Connect the dots between the “Start” and “clsAzureMLgetCategories” steps, as shown above.
- Define a variable or a global to store the result.
- Click the "clsAzureMLgetCategories" step to configure its "Required" properties. Provide a name for the step, the image file path, and a variable or global reference to store the result. Then click the Save button. Note: Click the "AI Predict" button for the Copilot to add new process steps that match your process description.
- 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 in the images below. Configure the “Logging” using the following properties.
- Save the process definition, create a new instance, and run it. Render the process instance. Click the process step to view its properties. The step should retrieve an image's category name and score details, and store the result in “variable.Result” as configured.
Tips:
- Ensure that the configured Image file path points to an accessible image before executing the step.
- Store the categorization result in a workflow variable when it is required by subsequent workflow steps.
- Use a global variable when the result needs to be referenced more broadly within the workflow.
- Validate the returned categorization information before using it for business-critical routing decisions.
- Use the False path to handle image-processing failures or unexpected input conditions.
- Test representative images before deploying automated image-classification workflows.
- Combine this step with Decision, Business Rule, Send Email, database, file-management, or reporting steps to build complete image-processing workflows.
Notes:
- The step belongs to the Azure Cognitive Services category.
- Its display name is Image Categorization.
- An image file path is required.
- Variable/Global to store the result is required.
- Both configured properties use the string data type.
- The step provides True and False execution paths.
- The XML does not define the detailed structure, format, number of categories, or confidence information contained in the stored result. Those details should be verified from the runtime implementation rather than assumed.
- The XML defines two input connections and two output connections.
Image Categorization vs. Detect Adult Content:
Both Image Categorization (clsAzureMLGetCategories) and Detect Adult Content (clsAzureMLGetAdult) analyze images using Azure Cognitive Services. However, they serve different business purposes.
| Image Categorization | Detect Adult Content |
|---|---|
| Categorizes images by subject matter. | Detects adult material in images. |
| Display name: Image Categorization. | Display name: Detect Adult Content. |
| Requires an Image file path. | Requires an Image file path. |
| Stores the categorization result in a workflow variable/global. | Stores the adult-content detection result in a workflow variable/global. |
| Focuses on general subject-matter classification. | Focuses specifically on adult-content detection. |
| Useful for organization, classification, metadata enrichment, and routing. | Useful for content moderation, screening, and image approval workflows. |
| Has two required properties. | Has two required properties. |
| Provides True/False execution paths. | Provides True/False execution paths. |
When to use each step:
Use Image Categorization when the workflow needs to determine:
“What subject matter or category does this image represent?”
For example, an image-processing workflow could categorize incoming images and route them to different departments or processing paths.
Use Detect Adult Content when the workflow needs to determine:
“Does this image contain adult material?”
For example, an image-submission workflow could screen uploaded content before allowing it to proceed to publication or approval.
Key distinction:
The simplest way to distinguish the two is:
Image Categorization: “What subject matter does this image belong to?”
Detect Adult Content: “Does this image contain adult material?”
The XML definitions establish these purposes directly through their labels: “Categorize images by subject matter” and “Detect adult material in images.”
In short: use Image Categorization for general image classification, and Detect Adult Content for content-safety screening.
Definition Sample:
You may download the sample definition from the link provided and import it into your FlowWright environment.
Note: Verify and complete any missing configuration after importing the sample, including:
- Image file path
- Variable/Global to store the result
- Image availability and accessibility
- Success and failure workflow branches
- Any downstream processing that consumes the categorization result
After verifying the configuration, save the Process Definition before execution.
Click here to download the sample file.