Programming Devices and Activities from the Microsoft Graph APIs

Project Rome has solved this user experience and seamless integration problem. Microsoft Graph and Windows 10 will deliver the ability to pick up activities between devices with no hassle. The key benefits for developers with Project Rome are driving adoption and installation of app across all these devices.

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Emgu Integration with .NET: Integrating Images

OpenCV is a very popular library written in the native C and C++ programming languages for processing images. Programmers familiar with the C# and Visual Basic.NET languages often face challenges in using OpenCV. Luckily for C# developers, a cross platform .NET wrapper to the OpenCV image processing library is available; it's named Emgu CV. This wrapper allows C# programs to communicate with native APIs of the underlying library that was written with unmanaged code. Emgu CV functions can be called from languages such as C#, VB, VC++, Python, and so forth. This wrapper can be compiled in Mono and run on Windows, Linux, Mac OS X, iPhone, iPad and Android devices.

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Working with the Microsoft Graph REST APIs

Microsoft Graph exposes Cloud services data, such as Outlook mail, calendar, One Drive, tasks, groups, SharePoint, and so forth. Cloud data could be accessed from a JavaScript client application. A developer needs to set up your Office 365 development environment before accessing Cloud services.

To extract data, follow these steps:

Register the application.
Get an access token for authentication.
Access the Microsoft services data over the Graph API.

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Reading Text from Images Using C#

By using Optical Character Recognition (OCR), you can detect and extract handwritten and printed text present in an image. The API works with different surfaces and backgrounds. To use OCR as a service, you have to get a subscription key from the Microsoft Cognitive Service portal. Steps of registration and obtaining the API keys are mentioned in my previous article, "Analyzing Image Content Programmatically: Using the Microsoft Cognitive Vision API."

In this post, I will demonstrate handwriting and text recognition by uploading a locally stored image consuming the Cognitive API.

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