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Merge pull request #48828 from pamistel/main
Removing references to deprecated service Azure Spatial Anchors
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.openpublishing.redirection.json

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learn-pr/azure/azure-cloud-services-tutorials/includes/13-summary.md

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Throughout the module series, you have learned about the features you will implement and how Azure Cloud services tie in to making your HoloLens 2 application. You added the required components into the project and prepared the scene for this module series.
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You can now store data and images in the cloud with Azure Storage, use Azure AI Custom Vision to associate images and train a model, and bring objects to a local context with Azure Spatial Anchors.
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You can now store data and images in the cloud with Azure Storage, use Azure AI Custom Vision to associate images and train a model.
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## Next steps
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learn-pr/azure/azure-cloud-services-tutorials/includes/2-azure-cloud-services-for-hololens-2.md

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With Azure AI Custom Vision (part of the Azure AI services) you can associate a set of images to Tracked Objects, train a machine-learning model on the set you created, and detect the Tracked Object.
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## Azure Spatial Anchors
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Azure Spatial Anchors is a managed cloud service and platform that enables multiuser, spatially aware mixed-reality and augmented-reality (MR/AR) apps for HoloLens, iOS devices with ARKit, and Android devices with ARCore.
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## InternetClient
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Apps can receive incoming data from the Internet. InternetClient can't act as a server and has no local network access.

learn-pr/azure/azure-cloud-services-tutorials/includes/3-exercise-azure-cloud-services-for-hololens-2.md

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With [Azure AI Custom Vision](https://azure.microsoft.com/services/cognitive-services/custom-vision-service/) (part of the [Azure AI services](https://azure.microsoft.com/services/cognitive-services/)) you can associate a set of images to Tracked Objects, train a machine learning model on the set you created, and detect the Tracked Objects.
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### Azure Spatial Anchors
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To store a Tracked Object location and give guided directions to find it, you'll use [Azure Spatial Anchors](https://azure.microsoft.com/services/spatial-anchors/).
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In this section, you'll create a new Unity project and get it ready for MRTK development.
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## Import the tutorial assets
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1. Add the `AzurespatialAnchors` SDK to your project. To add the package, [follow this tutorial](/azure/spatial-anchors/how-tos/setup-unity-project?tabs=UPMPackage).
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1. Download and import the following Unity custom packages *in the order they're listed*:
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* [AzureStorageForUnity.unitypackage](https://github.com/microsoft/MixedRealityLearning/releases/download/azure-cloud-services-v3.0.0/AzureStorageForUnity.unitypackage)

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### Azure Table storage
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This service allows us to store data in a NoSQL fashion. In our project, we'll use it to store information about the Tracked Object, such as name, description, spatial anchor ID, and more.
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This service allows us to store data in a NoSQL fashion. In our project, we'll use it to store information about the Tracked Object, such as name, description, and more.
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In context of the demo application, you'll need two tables; one to store information about the project with information about the state of trained models (more about that in the *Integrate Azure Custom Vision* exercise later in this module), and a second table to store information about Tracked Objects.
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