Analyze and Extract Information from Images with a Vision Action

You can use AI to perform deep-learning–based image analysis with a vision action. Oracle Cloud Infrastructure Vision enables you to automatically extract textual or visual information from images.

Capabilities

OCI Vision is an AI service that enables you to detect objects and text in images, classify images using labels, and detect faces in images. You can use OCI Vision to detect visual anomalies (for example, anomalies in manufacturing), identify objects in images to automate counting of common items (such as packages, products, shipments, vehicles, and so on), identify items that need attention (such as overgrowth of vegetation near an electric power line), classify items (for example, digital media assets) to organize them, identify textual/visual data in images to power analytic applications, and much more. Oracle Integration supports using OCI Vision in an integration with the vision action.

See AI Vision.

Prerequisites

See Prerequisites for information on the prerequisites you must satisfy in the Oracle Cloud Infrastructure Console.

Invoke Oracle Cloud Infrastructure Vision from an Integration

  1. Add a Vision action to an integration in either of the following ways:
    • On the side of the canvas, click Actions Integration actions icon and drag the OCI Vision action to the appropriate location.
    • Click Add icon at the location where you want to add the OCI Vision action, then select OCI Vision.
  2. Enter a name and optional description, then click Continue.
  3. Select the following information, then click Continue.
    Element Description
    Compartment

    Select the Oracle Cloud Infrastructure compartment in which your Oracle Integration is installed.

    Task
    Select the task to perform.
    • Label the image: Classifies objects in an image using labels. For example, if an image is a surveillance image of a street that has a vehicle, an electric power line, and a tree, OCI Vision can identify these objects, classify them using labels, and return this information. This might be helpful to identify items that need attention such as overgrowth of vegetation near an electric power line.
    • Identify objects in the image: Identifies objects in an image. For example, if an image includes vehicles such as a car, a bus, or a truck, OCI Vision can identify these objects and return this information.
    • Recognize text at the word and line level: Identifies words and lines of text in an image. For example, if an image is a visa application form and it contains text such as name, city, citizenship, country and other text content, OCI Vision can recognize the text and return this information.
    • Identify faces in the image: Identifies faces and facial features of people in an image. For example, if an image is a photograph of a group of people, OCI Vision can identify the faces and facial features of the people in the image and return this information.
    Maximum no. of results to be returned Select the maximum number of results to be returned after the images have been analyzed using the selected task.
  4. On the Summary page, click Finish.
  5. Open the mapper and define the mappings between the source and target elements as needed. You must send the data in base-64 format.

  6. Drag Stream Reference from the Sources section into Data in the Target section.

  7. Click Functions Mapper functions icon.
  8. Click Design View Switch view icon in the Expression Builder.
  9. In the Functions section, expand Advanced, and drag encodeReferenceToBase64 into the Expression Builder for the Data target element.
    oraext:encodeReferenceToBase64 (/nssrcmpr:execute/ns23:streamReference)

    Note:

    You can optionally specify Compartment Id in the mapper to override the value you selected initially for Compartment.
  10. Exit the mapper.

    The vision action is now configured.