Samples showing how to use Azure and AI services in Mixed Reality projects
Перейти к файлу
Jared Bienz 45867e4151 Added license headers. 2018-08-08 16:18:44 -05:00
Reference-Architecture/Client/MixedReality-Azure-Unity Corrected a bug in LuisExtensions for FirstOrDefaultResolution. Updated build script now that some plugin DLLs are not required. Generated new Unity Packages. 2018-06-11 15:11:11 -05:00
Solutions/LUIS-CachingService Switched LUIS cachine service repo source to master in ARM template. 2018-06-18 15:11:51 -04:00
Standalone-Samples Added license headers. 2018-08-08 16:18:44 -05:00
.gitignore Added gitignore by file and folder naming convention 2018-07-20 13:16:27 -05:00
LICENSE Initial commit 2018-01-31 09:06:42 -08:00
LICENSE.licenseheader Initial commit. Have the ability to store secret values like keys in environment now so that they don't accidentally get pushed to source control. Project is running, but getting http 400 errors. 2018-02-09 18:12:36 -06:00
README.md Update README.md 2018-06-21 11:47:04 -04:00

README.md

MixedReality Azure Samples

MixedReality Azure Samples is a collection of samples and reference implementations for using Azure services in simulations. Though "Mixed Reality" is mentioned throughout the project, the vast majority of resources here are not exclusive to Windows Mixed Reality devices. Each sample or reference includes a System Requirements section that clearly explains where the code can run.

Organization

This project is organized into 3 key areas:

Standalone Samples

Concise projects that demonstrate a capability quickly and don't have external dependencies. These samples can be downloaded independently and tested quickly with little or no server setup.

Samples:

Solutions

Also demonstrate a capability but require additional setup. Solutions, for example, may require deploying an Azure workload like a bot, a function, or a database.

Solutions:

  • LUIS Caching Service: Reusable solution that showcases how to cache results from LUIS in Cognitive Services.

Reference Architectures

Are a set of capabilities that have all been designed to work together. For example, Speech Recognition may be used on its own but it is also designed to work with Language Understanding.

Modules

  • LUIS for XR: A powerful Natural Language replacement for voice commands.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.