Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API.
It quickly classifies images into thousands of categories (e.g., "sailboat", "lion", "Eiffel Tower"), detects individual objects and faces within images, and finds and reads printed words contained within images.
The Google Vision package can perform metadata analysis on images. There are multiple use cases depending on the industry and application.
The possible use cases are:
- Label Detection - Detect broad sets of categories within an image, ranging from modes of transportation to animals.
- Explicit Content Detection - Detect explicit content like adult themes or violence within an image.
- Logo Detection - Detect popular product logos within an image.
- Optical Character Recognition - Detect and extract text within an image, with support for a broad range of languages, along with support for automatic language identification.
- Face Detection - Detect multiple faces within an image.
- Web Detection - Search the Internet for similar images.
Before using the the Google Vision Activities Package, you need to configure your applications using the Google Cloud Platform .
There are two configuration steps:
- Enable APIs - this step enables automation by granting API access to your Google applications.
- Create credentials - this specifies the authentication type used to interact with your enabled APIs.
Follow the steps listed below to enable your APIs.
The steps listed below are sourced from Enable and disable APIs in the Google API Console Help documentation.
- Sign in to the Google Cloud Platform using your personal, work, or school Google G Suite account.
- In the top menu bar, after Google Cloud Platform, select the project you want to use for your automation project.
- If you don't have a project, create one by following the Creating and Managing Projects instructions in the Google Cloud documentation.
- Open the Navigation menu in the top navigation bar.
- Hover over APIs & Services (showing a menu of options) and select Library (opening the API Library).
- From the API Library, go to the Machine Learning section.
- Click Cloud Vision API.
- In the Google Vision API page, click Enable.
You're done! Now, let's create your credentials to access the enabled APIs.
Follow the steps listed below to create credentials for your project.
- From your project APIs & Services page (Google Cloud Platform> Project > APIs & Services), click Credentials in the left-hand navigation panel.
- After the Credentials page opens, click Create credentials and select the type of credentials used for your application.
You should consult your IT department to determine the type of credentials you should use for your project. For more information about the differences between the credential types, see Authentication Overview .
For information about each credential type, see the details below.
An API key is the simplest authentication mechanism.
For more information about API Keys, see Using API Keys in the Google Cloud Documentation.
OAuth client ID
The OAuth Client ID method is recommended for attended automation because user consent is required before the robot can access to your Google account (for more information, see User consent in the Google Help documentation).
For more information about OAuth client ID, see Using OAuth 2.0 to Access Google APIs in the Google Cloud Documentation. For step-by-step instructions, see Setting up OAuth 2.0 in the Google Help documentation.
Service account key
A service account key is a special type of Google account that belongs to your application instead of to an individual end user. Your application calls Google APIs on behalf of the service account, so users aren't directly involved.
For more information about Service account keys, see Understanding service accounts in the Google Cloud Documentation.
- Follow the applicable instructions (listed below) to add your selected credentials.
Now that you have enabled APIs and added credentials, you can build automation projects that include Google Vision activities.
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