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articles/ai-services/.openpublishing.redirection.applied-ai-services.json

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"source_path_from_root": "/articles/ai-services/computer-vision/how-to/migrate-face-data.md",
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"redirect_url": "/azure/ai-services/computer-vision/overview-identity",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/computer-vision/index-spatial-analysis.yml",
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"redirect_url": "/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/custom-vision-service/update-application-to-3.0-sdk.md",
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"redirect_url": "/azure/ai-services/custom-vision-service/overview",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/custom-vision-service/release-notes.md",
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"redirect_url": "/azure/ai-services/custom-vision-service/whats-new",
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"redirect_document_id": false
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articles/ai-services/autoscale.md

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---
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title: Auto-scale AI services limits
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title: Autoscale AI services limits
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description: Learn how to use the autoscale feature for Azure AI services to dynamically adjust the rate limit of your service.
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author: PatrickFarley
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ms.author: pafarley
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ms.service: azure-ai-services
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- ignite-2023
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ms.date: 06/27/2022
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ms.date: 01/20/2024
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---
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# Auto-scale AI services limits
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# Autoscale AI services limits
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This article provides guidance for how customers can access higher rate limits on their Azure AI services resources.
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## Overview
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Each Azure AI services resource has a preconfigured static call rate (transactions per second) which limits the number of concurrent calls that customers can make to the backend service in a given time frame. The autoscale feature will automatically increase/decrease a customer's resource's rate limits based on near-real-time resource usage metrics and backend service capacity metrics.
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Each Azure AI services resource has a pre-configured static call rate (transactions per second) which limits the number of concurrent calls that customers can make to the backend service in a given time frame. The autoscale feature will automatically increase/decrease a customer's resource's rate limits based on near-real-time resource usage metrics and backend service capacity metrics.
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## Get started with the autoscale feature
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articles/ai-services/cognitive-services-custom-subdomains.md

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ms.topic: conceptual
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ms.date: 12/04/2020
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ms.date: 01/20/2024
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ms.author: pafarley
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---
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# Custom subdomain names for Azure AI services
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Azure AI services use custom subdomain names for each resource created through the [Azure portal](https://portal.azure.com), [Azure Cloud Shell](https://azure.microsoft.com/features/cloud-shell/), or [Azure CLI](/cli/azure/install-azure-cli). Unlike regional endpoints, which were common for all customers in a specific Azure region, custom subdomain names are unique to the resource. Custom subdomain names are required to enable features like Microsoft Entra ID for authentication.
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Starting in July 2019, Azure AI services use custom subdomain names for each resource created through the [Azure portal](https://portal.azure.com), [Azure Cloud Shell](https://azure.microsoft.com/features/cloud-shell/), or [Azure CLI](/cli/azure/install-azure-cli). Unlike regional endpoints, which were common for all customers in a specific Azure region, custom subdomain names are unique to the resource. Custom subdomain names are required to enable features like Microsoft Entra ID for authentication.
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## How does this impact existing resources?
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Azure AI services resources created before July 1, 2019 will use the regional endpoints for the associated service. These endpoints will work with existing and new resources.
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Azure AI services resources created before July 1, 2019 use the regional endpoints for the associated service. These endpoints work with existing and new resources.
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If you'd like to migrate an existing resource to leverage custom subdomain names, so that you can enable features like Microsoft Entra ID, follow these instructions:
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If you'd like to migrate an existing resource to use custom subdomain names to enable features like Microsoft Entra ID, follow these instructions:
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1. Sign in to the Azure portal and locate the Azure AI services resource that you'd like to add a custom subdomain name to.
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2. In the **Overview** blade, locate and select **Generate Custom Domain Name**.
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## What if an SDK asks me for the region for a resource?
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> [!WARNING]
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> Speech Services use custom subdomains with [private endpoints](Speech-Service/speech-services-private-link.md) **only**. In all other cases use **regional endpoints** with Speech Services and associated SDKs.
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> Speech Services use custom subdomains with [private endpoints](Speech-Service/speech-services-private-link.md) **only**. In all other cases, use **regional endpoints** with Speech Services and associated SDKs.
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Regional endpoints and custom subdomain names are both supported and can be used interchangeably. However, the full endpoint is required.
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articles/ai-services/cognitive-services-data-loss-prevention.md

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ms.date: 01/20/2024
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## Prerequisites
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Before you make a request, you need an Azure account and an Azure AI services subscription. If you already have an account, go ahead and skip to the next section. If you don't have an account, we have a guide to get you set up in minutes: [Create a multi-service resource](multi-service-resource.md?pivots=azportal).
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You can get your subscription key from the [Azure portal](multi-service-resource.md?pivots=azportal#get-the-keys-for-your-resource) after [creating your account](https://azure.microsoft.com/free/cognitive-services/).
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- Before you make a request, you need an Azure account and an Azure AI services subscription. If you already have an account, go ahead and skip to the next section. If you don't have an account, we have a guide to get you set up in minutes: [Create a multi-service resource](multi-service-resource.md?pivots=azportal).
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- You can get your subscription key from the [Azure portal](multi-service-resource.md?pivots=azportal#get-the-keys-for-your-resource) after [creating your account](https://azure.microsoft.com/free/cognitive-services/).
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## Enabling data loss prevention
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There are two parts to enable data loss prevention. First the property restrictOutboundNetworkAccess must be set to true. When this is set to true, you also need to provide the list of approved URLs. The list of URLs is added to the allowedFqdnList property. The allowedFqdnList property contains an array of comma-separated URLs.
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There are two parts to enable data loss prevention. First, the resource property `restrictOutboundNetworkAccess` must be set to `true`. When this is set to true, you also need to provide the list of approved URLs. The list of URLs is added to the `allowedFqdnList` property. The `allowedFqdnList` property contains an array of comma-separated URLs.
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>[!NOTE]
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>

articles/ai-services/cognitive-services-environment-variables.md

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articles/ai-services/commitment-tier.md

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# Purchase commitment tier pricing
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Azure AI offers commitment tier pricing, each offering a discounted rate compared to the pay-as-you-go pricing model. With commitment tier pricing, you can commit to using the following Azure AI services features for a fixed fee, enabling you to have a predictable total cost based on the needs of your workload:
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Azure AI offers commitment tier pricing, allowing discounted rates compared to the pay-as-you-go pricing model. With commitment tier pricing, you can commit to using the following Azure AI services features for a fixed fee, enabling you to have a predictable total cost based on the needs of your workload:
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* Speech to text (Standard)
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articles/ai-services/computer-vision/computer-vision-resource-container-config.md

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# Configure Read OCR Docker containers
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You configure the Azure AI Vision Read OCR container's runtime environment by using the `docker run` command arguments. This container has several required settings, along with a few optional settings. Several [examples](#example-docker-run-commands) of the command are available. The container-specific settings are the billing settings.
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You can configure the Azure AI Vision Read OCR container's runtime environment by using the `docker run` command arguments. This container has several required settings, along with a few optional settings. Several [examples](#example-docker-run-commands) of the command are available. The container-specific settings are the billing settings.
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articles/ai-services/computer-vision/concept-background-removal.md

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The Image Analysis service can divide images into multiple segments or regions to help the user identify different objects or parts of the image. Background removal creates an alpha matte that separates the foreground object from the background in an image.
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The Background removal operation can divide images into multiple segments or regions to help the user identify different objects or parts of the image. Background removal creates an alpha matte that separates the foreground object from the background in an image. This service is currently in preview, and the API may change in the future.
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articles/ai-services/computer-vision/concept-brand-detection.md

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articles/ai-services/computer-vision/concept-categorizing-images.md

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In addition to tags and a description, Image Analysis can return the taxonomy-based categories detected in an image. Unlike tags, categories are organized in a parent/child hierarchy, and there are fewer of them (86, as opposed to thousands of tags). All category names are in English. Categorization can be done by itself or alongside the newer tags model.
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In addition to tags and a description, Image Analysis 3.2 can return the taxonomy-based categories detected in an image. Unlike tags, categories are organized in a parent/child hierarchy, and there are fewer of them (86, as opposed to thousands of tags). All category names are in English. Categorization can be done by itself or alongside the newer tags model.
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## The 86-category taxonomy
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Azure AI Vision can categorize an image broadly or specifically, using the list of 86 categories in the following diagram. For the full taxonomy in text format, see [Category Taxonomy](category-taxonomy.md).
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The categorization feature is part of the [Analyze Image](https://westcentralus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b) API. You can call this API through a native SDK or through REST calls. Include `Categories` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"categories"` section.
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The categorization feature is part of the [Analyze Image 3.2](https://westcentralus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b) API. You can call this API through a native SDK or through REST calls. Include `Categories` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"categories"` section.
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* [Quickstart: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)
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