Before you use Vision, your tenancy administrator must
set up the appropriate policies.
Setting Up the Policies 🔗
Follow these steps to set up the policies needed to use Vision.
In the Console navigation menu, select
Identity & Security.
Under Identity, select
Policies.
Select Create Policy.
The Create Policy panel is displayed.
Enter a Name. You can use alphanumeric characters,
hyphens, periods, and underscores only. Spaces aren't allowed. For example,
enter, vision-access-policy.
Enter a Description to help other users know the purpose
of this set of policies. For example, enter, Policy to access Vision
service..
Select the Compartment.
In Policy Builder, select Show manual
editor.
Add the following statement:
Copy
allow any-user to use ai-service-vision-family in tenancy
(Optional)
To limit access to your user group only, add the following policy
instead:
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allow group <your-group-name> to use ai-service-vision-family in tenancy
Select Create.
1. Understand Data Requirements 🔗
Vision works with many formats of image data to detect
objects, assign labels to images, extract text, and more. It accepts data through Object Storage. If Vision is run
in the Console, you can also provide locally stored
images.
Vision offers synchronous and asynchronous APIs to analyze
images. The data requirements for each are explained in the following table:
API Data Requirements
API
Description
Supported Input Format
Synchronous API
analyzeImage
analyzeDocument
Analyzes individual images.
JPG, PNG. PDF and TIFF are also supported with analyzeDocument
Up to 5 MB
Single image input
Asynchronous API
Analyze several images or multi-page PDFs.
JPG, PNG. PDF and TIFF are also supported with analyzeDocument
Supports multi-page PDF
Up to 2,000 images input
2. Load Data to Object Storage 🔗
In this step, you load to Object Storage the images and
documents you want to analyze.
The results categorizing objects in the image, are displayed in the
Results section. There are labels to classify the detected objects,
and a confidence score for each object.
Use Object Detection 🔗
Under Vision, select Object Detection.
The Object Detection page is displayed.
The results are displayed in the Results section. The objects
detected, a confidence score for each object, and highlighted bounding box around each
object are displayed in the Results pane. If you click a label, where on the image that
object is detected is shown.
What's Next 🔗
Now you know how to use Vision with pretrained models, try
using it with custom models.