Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. Potential applications include classifying images for a fashion website, analyzing text and images for insurance claims, or understanding telemetry data from game screenshots. Traditionally, companies would need to develop expertise in machine learning models, train the models, and finally run the images through their custom process to get the data out of the images. By using Azure services such as the Computer Vision API and Azure Functions, companies can eliminate the need to manage individual servers, while reducing costs and leveraging the expertise that Microsoft has already developed around processing images with Cognitive Services.
This example scenario specifically addresses an image-processing use case. If you have different AI needs, consider the full suite of Cognitive Services. This scenario covers the back-end components of a web or mobile application.
Data flows through the scenario as follows:. The majority of the components used in this example scenario are managed services that will automatically scale. A couple of notable exceptions: Azure Functions has a limit of a maximum of instances. If you need to scale beyond this limit, consider multiple regions or app plans. If you plan to use other APIs see guidance on estimating your requirements, see request units in our documentation.
NoSQL databases frequently trade consistency in the sense of the CAP theorem for availability, scalability, and partitioning. In this example scenario, a key-value data model is used and transaction consistency is rarely needed as most operations are by definition atomic. Additional guidance to Choose the right data store is available in the Azure Architecture Center.
If your implementation requires high consistency, you can choose your consistency level in Cosmos DB. For general guidance on designing scalable solutions, see the performance efficiency checklist in the Azure Architecture Center. Managed identities for Azure resources are used to provide access to other resources internal to your account and then assigned to your Azure Functions.
Only allow access to the requisite resources in those identities to ensure that nothing extra is exposed to your functions and potentially to your customers. For general guidance on designing secure solutions, see the Azure Security Documentation. All of the components in this scenario are managed, so at a regional level they are all resilient automatically.
For general guidance on designing resilient solutions, see Designing resilient applications for Azure. You can also enable search suggestions for the search widget. Note: If you want to handle all user input yourself, you can do so with some callback methods and event listeners. For more information, see the reference documentation for SearchView and its nested interfaces for the appropriate event listeners. The SearchView widget allows for a few additional features you might want:.
However, most of them are used only when you handle all user input yourself, instead of using the Android system to deliver search queries and display search suggestions. For example, when your application runs on a smaller screen, there might not be enough room in the Action Bar to display the search widget along with other action items or navigation elements, so the menu item will instead appear in the overflow menu. When placed in the overflow menu, the item works like an ordinary menu item and does not display the action view the search widget.
To handle this situation, the menu item to which you've attached the search widget should activate the search dialog when the user selects it from the overflow menu. In order for it to do so, you must implement onOptionsItemSelected to handle the "Search" menu item and open the search dialog by calling onSearchRequested.
For more information about how items in the Action Bar work and how to handle this situation, see the Action Bar developer guide. You can add voice search functionality to your search dialog or widget by adding the android:voiceSearchMode attribute to your searchable configuration.
This adds a voice search button that launches a voice prompt. When the user has finished speaking, the transcribed search query is sent to your searchable activity. The value showVoiceSearchButton is required to enable voice search, while the second value, launchRecognizer , specifies that the voice search button should launch a recognizer that returns the transcribed text to the searchable activity.
You can provide additional attributes to specify the voice search behavior, such as the language to be expected and the maximum number of results to return. See the Searchable Configuration reference for more information about the available attributes. Note: Carefully consider whether voice search is appropriate for your application. All searches performed with the voice search button are immediately sent to your searchable activity without a chance for the user to review the transcribed query.
Sufficiently test the voice recognition and ensure that it understands the types of queries that the user might submit inside your application. Figure 3. Screenshot of a search dialog with custom search suggestions. Both the search dialog and the search widget can provide search suggestions as the user types, with assistance from the Android system.
The system manages the list of suggestions and handles the event when the user selects a suggestion. See Adding Recent Query Suggestions. Content and code samples on this page are subject to the licenses described in the Content License.
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