Merge branch 'main' of https://github.com/microsoftdocs/azure-ai-docs-pr into mflow-artifacts

Author: v-thepet

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

@@ -330,6 +330,26 @@
       "redirect_url": "/azure/ai-services/computer-vision/how-to/model-customization",
       "redirect_document_id": false
     },
+    {
+      "source_path_from_root": "/articles/ai-services/computer-vision/deploy-computer-vision-on-premises.md",
+      "redirect_url": "/azure/ai-services/computer-vision/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/computer-vision/spatial-analysis-web-app.md",
+      "redirect_url": "/azure/ai-services/computer-vision/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/computer-vision/tutorials/storage-lab-tutorial.md",
+      "redirect_url": "/azure/ai-services/computer-vision/",
+      "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/custom-vision-service/iot-visual-alerts-tutorial.md",
+      "redirect_url": "/azure/ai-services/computer-vision/",
+      "redirect_document_id": false
+    },
     {
       "source_path_from_root": "/articles/ai-services/document-intelligence/concept-document-intelligence-studio.md",
       "redirect_url": "/azure/ai-services/document-intelligence/studio-overview",

articles/ai-services/cognitive-services-container-support.md

@@ -15,7 +15,7 @@ keywords: on-premises, Docker, container, Kubernetes
 
 # What are Azure AI containers?
 
-Azure AI services provides several [Docker containers](https://www.docker.com/what-container) that let you use the same APIs that are available in Azure, on-premises. Using these containers gives you the flexibility to bring Azure AI services closer to your data for compliance, security or other operational reasons. Container support is currently available for a subset of Azure AI services.
+Azure AI services provide several [Docker containers](https://www.docker.com/what-container) that let you use the same APIs that are available in Azure, on-premises. Using these containers gives you the flexibility to bring Azure AI services closer to your data for compliance, security or other operational reasons. Container support is currently available for a subset of Azure AI services.
 
 > [!VIDEO https://www.youtube.com/embed/hdfbn4Q8jbo]
 
@@ -48,7 +48,7 @@ Azure AI containers provide the following set of Docker containers, each of whic
 | Service |  Container | Description | Availability |
 |--|--|--|--|
 | [LUIS][lu-containers] |  **LUIS** ([image](https://mcr.microsoft.com/product/azure-cognitive-services/language/luis/about)) | Loads a trained or published Language Understanding model, also known as a LUIS app, into a docker container and provides access to the query predictions from the container's API endpoints. You can collect query logs from the container and upload these back to the [LUIS portal](https://www.luis.ai) to improve the app's prediction accuracy. | Generally available. <br> This container can also [run in disconnected environments](containers/disconnected-containers.md). |
-| [Language service][ta-containers-keyphrase] | **Key Phrase Extraction** ([image](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/keyphrase/about)) | Extracts key phrases to identify the main points. For example, for the input text "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". | Generally available. <br> This container can also [run in disconnected environments](containers/disconnected-containers.md). |
+| [Language service][ta-containers-keyphrase] | **Key Phrase Extraction** ([image](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/keyphrase/about)) | Extracts key phrases to identify the main points. For example, for the input text "The food was delicious and there were wonderful staff," the API returns the main talking points: "food" and "wonderful staff". | Generally available. <br> This container can also [run in disconnected environments](containers/disconnected-containers.md). |
 | [Language service][ta-containers-language] |  **Text Language Detection** ([image](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/language/about)) | For up to 120 languages, detects which language the input text is written in and report a single language code for every document submitted on the request. The language code is paired with a score indicating the strength of the score. | Generally available. <br> This container can also [run in disconnected environments](containers/disconnected-containers.md). |
 | [Language service][ta-containers-sentiment] | **Sentiment Analysis** ([image](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/sentiment/about)) | Analyzes raw text for clues about positive or negative sentiment. This version of sentiment analysis returns sentiment labels (for example *positive* or *negative*) for each document and sentence within it. |  Generally available. <br> This container can also [run in disconnected environments](containers/disconnected-containers.md). |
 | [Language service][ta-containers-health] |  **Text Analytics for health** ([image](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/healthcare/about))| Extract and label medical information from unstructured clinical text. | Generally available |

articles/ai-services/computer-vision/computer-vision-how-to-install-containers.md

@@ -134,7 +134,7 @@ More [examples](./computer-vision-resource-container-config.md#example-docker-ru
 > [!IMPORTANT]
 > The `Eula`, `Billing`, and `ApiKey` options must be specified to run the container; otherwise, the container won't start.  For more information, see [Billing](#billing).
 
-If you need higher throughput (for example, when processing multi-page files), consider deploying multiple containers [on a Kubernetes cluster](deploy-computer-vision-on-premises.md), using [Azure Storage](/azure/storage/common/storage-account-create) and [Azure Queue](/azure/storage/queues/storage-queues-introduction).
+<!--If you need higher throughput (for example, when processing multi-page files), consider deploying multiple containers [on a Kubernetes cluster](deploy-computer-vision-on-premises.md), using [Azure Storage](/azure/storage/common/storage-account-create) and [Azure Queue](/azure/storage/queues/storage-queues-introduction).-->
 
 If you're using Azure Storage to store images for processing, you can create a [connection string](/azure/storage/common/storage-configure-connection-string) to use when calling the container.