Merge pull request #222560 from PatrickFarley/minor-updates

[cog svcs] Minor updates

Author: v-regandowner

articles/applied-ai-services/form-recognizer/containers/form-recognizer-container-install-run.md

@@ -32,7 +32,7 @@ You'll also need the following to use Form Recognizer containers:
 | **Familiarity with Docker** | You should have a basic understanding of Docker concepts, like registries, repositories, containers, and container images, as well as knowledge of basic `docker`  [terminology and commands](/dotnet/architecture/microservices/container-docker-introduction/docker-terminology). |
 | **Docker Engine installed** | <ul><li>You need the Docker Engine installed on a [host computer](#host-computer-requirements). Docker provides packages that configure the Docker environment on [macOS](https://docs.docker.com/docker-for-mac/), [Windows](https://docs.docker.com/docker-for-windows/), and [Linux](https://docs.docker.com/engine/installation/#supported-platforms). For a primer on Docker and container basics, see the [Docker overview](https://docs.docker.com/engine/docker-overview/).</li><li> Docker must be configured to allow the containers to connect with and send billing data to Azure. </li><li> On **Windows**, Docker must also be configured to support **Linux** containers.</li></ul>  |
 |**Form Recognizer resource** | A [**single-service Azure Form Recognizer**](https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer) or [**multi-service Cognitive Services**](https://portal.azure.com/#create/Microsoft.CognitiveServicesAllInOne) resource in the Azure portal. To use the containers, you must have the associated key and endpoint URI. Both values are available on the Azure portal Form Recognizer **Keys and Endpoint** page: <ul><li>**{FORM_RECOGNIZER_KEY}**: one of the two available resource keys.<li>**{FORM_RECOGNIZER_ENDPOINT_URI}**: the endpoint for the resource used to track billing information.</li></li></ul>|
-| **Computer Vision API resource** | **To process business cards, ID documents, or Receipts, you'll need a Computer Vision resource.** <ul><li>You can access the Recognize Text feature as either an Azure resource (the REST API or SDK) or a **cognitive-services-recognize-text** [container](../../../cognitive-services/Computer-vision/computer-vision-how-to-install-containers.md#get-the-container-image-with-docker-pull). The usual [billing](#billing) fees apply.</li> <li>If you use the **cognitive-services-recognize-text** container, make sure that your Computer Vision key for the Form Recognizer container is the key specified in the Computer Vision `docker run`  or `docker compose` command for the **cognitive-services-recognize-text** container and  your billing endpoint is the container's endpoint (for example, `http://localhost:5000`). If you use both the Computer Vision container and Form Recognizer container together on the same host, they can't both be started with the default port of *5000*. </li></ul></br>Pass in both the key and endpoints for your Computer Vision Azure cloud or Cognitive Services container:<ul><li>**{COMPUTER_VISION_KEY}**: one of the two available resource keys.</li><li> **{COMPUTER_VISION_ENDPOINT_URI}**: the endpoint for the resource used to track billing information.</li></ul> |
+| **Computer Vision API resource** | **To process business cards, ID documents, or Receipts, you'll need a Computer Vision resource.** <ul><li>You can access the Recognize Text feature as either an Azure resource (the REST API or SDK) or a **cognitive-services-recognize-text** [container](../../../cognitive-services/Computer-vision/computer-vision-how-to-install-containers.md#get-the-container-image). The usual [billing](#billing) fees apply.</li> <li>If you use the **cognitive-services-recognize-text** container, make sure that your Computer Vision key for the Form Recognizer container is the key specified in the Computer Vision `docker run`  or `docker compose` command for the **cognitive-services-recognize-text** container and  your billing endpoint is the container's endpoint (for example, `http://localhost:5000`). If you use both the Computer Vision container and Form Recognizer container together on the same host, they can't both be started with the default port of *5000*. </li></ul></br>Pass in both the key and endpoints for your Computer Vision Azure cloud or Cognitive Services container:<ul><li>**{COMPUTER_VISION_KEY}**: one of the two available resource keys.</li><li> **{COMPUTER_VISION_ENDPOINT_URI}**: the endpoint for the resource used to track billing information.</li></ul> |
 
 |Optional|Purpose|
 |---------|----------|

articles/cognitive-services/Anomaly-Detector/whats-new.md

@@ -25,7 +25,7 @@ We've also added links to some user-generated content. Those items will be marke
     | [JAVA](https://search.maven.org/artifact/com.azure/azure-ai-anomalydetector/3.0.0-beta.5/jar) | [MultivariateSample.java](https://github.com/Azure/azure-sdk-for-java/blob/e845677d919d47a2c4837153306b37e5f4ecd795/sdk/anomalydetector/azure-ai-anomalydetector/src/samples/java/com/azure/ai/anomalydetector/MultivariateSample.java)|
     | [JS/TS](https://www.npmjs.com/package/@azure-rest/ai-anomaly-detector/v/1.0.0-beta.1) |[sample_multivariate_detection.ts](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples-dev/sample_multivariate_detection.ts)|
 
-* Check out this AI Show video to learn more about the GA version of Multivariate Anomaly Detection: [AI Show | Multivariate Anomaly Detection is Generally Available](https://learn.microsoft.com/shows/ai-show/ep-70-the-latest-from-azure-multivariate-anomaly-detection).
+* Check out this AI Show video to learn more about the GA version of Multivariate Anomaly Detection: [AI Show | Multivariate Anomaly Detection is Generally Available](/shows/ai-show/ep-70-the-latest-from-azure-multivariate-anomaly-detection).
 
 ### Nov 2022
 
@@ -100,7 +100,7 @@ We've also added links to some user-generated content. Those items will be marke
 
 ## Videos
 
-* Nov 12, 2022 AI Show: [Multivariate Anomaly Detection is GA](https://learn.microsoft.com/shows/ai-show/ep-70-the-latest-from-azure-multivariate-anomaly-detection) (Seth with Louise Han).
+* Nov 12, 2022 AI Show: [Multivariate Anomaly Detection is GA](/shows/ai-show/ep-70-the-latest-from-azure-multivariate-anomaly-detection) (Seth with Louise Han).
 * May 7, 2021 [New to Anomaly Detector: Multivariate Capabilities](/shows/AI-Show/New-to-Anomaly-Detector-Multivariate-Capabilities) - AI Show on the new multivariate anomaly detection APIs with Tony Xing and Seth Juarez
 * April 20, 2021 AI Show Live | Episode 11| New to Anomaly Detector: Multivariate Capabilities - AI Show live recording with Tony Xing and Seth Juarez
 * May 18, 2020 [Inside Anomaly Detector](/shows/AI-Show/Inside-Anomaly-Detector) - AI Show with Qun Ying and Seth Juarez

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

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: computer-vision
 ms.topic: how-to
-ms.date: 06/13/2022
+ms.date: 12/27/2022
 ms.author: pafarley
 ms.custom: seodec18, cog-serv-seo-aug-2020
 keywords: on-premises, OCR, Docker, container
@@ -23,9 +23,7 @@ Containers enable you to run the Computer Vision APIs in your own environment. C
 The Read container allows you to extract printed and handwritten text from images and documents with support for JPEG, PNG, BMP, PDF, and TIFF file formats. For more information, see the [Read API how-to guide](how-to/call-read-api.md).
 
 ## What's new
-The `3.2-model-2022-04-30` GA version of the Read container is available with support for [164 languages and other enhancements](./whats-new.md#may-2022). If you are an existing customer, please follow the [download instructions](#docker-pull-for-the-read-ocr-container) to get started.
-
-## Read 3.2 container
+The `3.2-model-2022-04-30` GA version of the Read container is available with support for [164 languages and other enhancements](./whats-new.md#may-2022). If you're an existing customer, follow the [download instructions](#get-the-container-image) to get started.
 
 The Read 3.2 OCR container is the latest GA model and provides:
 * New models for enhanced accuracy.
@@ -80,18 +78,16 @@ grep -q avx2 /proc/cpuinfo && echo AVX2 supported || echo No AVX2 support detect
 
 [!INCLUDE [Container requirements and recommendations](includes/container-requirements-and-recommendations.md)]
 
-## Get the container image with `docker pull`
+## Get the container image
 
-Container images for Read are available.
+The following container images for Read are available.
 
 | Container | Container Registry / Repository / Image Name | Tags |
 |-----------|------------|-----------------------------------------|
 | Read 3.2 GA | `mcr.microsoft.com/azure-cognitive-services/vision/read:3.2-model-2022-04-30` | 	latest, 3.2, 3.2-model-2022-04-30 |
 
 Use the [`docker pull`](https://docs.docker.com/engine/reference/commandline/pull/) command to download a container image.
 
-### Docker pull for the Read OCR container
-
 ```bash
 docker pull mcr.microsoft.com/azure-cognitive-services/vision/read:3.2-model-2022-04-30
 ```
@@ -104,10 +100,10 @@ docker pull mcr.microsoft.com/azure-cognitive-services/vision/read:3.2-model-202
 
 Once the container is on the [host computer](#host-computer-requirements), use the following process to work with the container.
 
-1. [Run the container](#run-the-container-with-docker-run), with the required billing settings. More [examples](computer-vision-resource-container-config.md) of the `docker run` command are available. 
+1. [Run the container](#run-the-container), with the required billing settings. More [examples](computer-vision-resource-container-config.md) of the `docker run` command are available. 
 1. [Query the container's prediction endpoint](#query-the-containers-prediction-endpoint). 
 
-## Run the container with `docker run`
+## Run the container
 
 Use the [docker run](https://docs.docker.com/engine/reference/commandline/run/) command to run the container. Refer to [gather required parameters](#gather-required-parameters) for details on how to get the `{ENDPOINT_URI}` and `{API_KEY}` values.
 
@@ -121,7 +117,7 @@ Billing={ENDPOINT_URI} \
 ApiKey={API_KEY}
 ```
 
-This command:
+The above command:
 
 * Runs the Read OCR latest GA container from the container image.
 * Allocates 8 CPU core and 16 gigabytes (GB) of memory.
@@ -151,7 +147,7 @@ If you're using Azure Storage to store images for processing, you can create a [
 To find your connection string:
 
 1. Navigate to **Storage accounts** on the Azure portal, and find your account.
-2. Click on **Access keys** in the left navigation list.
+2. Select on **Access keys** in the left navigation list.
 3. Your connection string will be located below **Connection string**
 
 [!INCLUDE [Running multiple containers on the same host](../../../includes/cognitive-services-containers-run-multiple-same-host.md)]
@@ -168,7 +164,7 @@ Use the host, `http://localhost:5000`, for container APIs. You can view the Swag
 
 ### Asynchronous Read
 
-You can use the `POST /vision/v3.2/read/analyze` and `GET /vision/v3.2/read/operations/{operationId}` operations in concert to asynchronously read an image, similar to how the Computer Vision service uses those corresponding REST operations. The asynchronous POST method will return an `operationId` that is used as the identifer to the HTTP GET request.
+You can use the `POST /vision/v3.2/read/analyze` and `GET /vision/v3.2/read/operations/{operationId}` operations in concert to asynchronously read an image, similar to how the Computer Vision service uses those corresponding REST operations. The asynchronous POST method will return an `operationId` that is used as the identifier to the HTTP GET request.
 
 From the swagger UI, select the `Analyze` to expand it in the browser. Then select **Try it out** > **Choose file**. In this example, we'll use the following image:
 
@@ -301,7 +297,7 @@ You can use the following operation to synchronously read an image.
 
 `POST /vision/v3.2/read/syncAnalyze` 
 
-When the image is read in its entirety, then and only then does the API return a JSON response. The only exception to this is if an error occurs. When an error occurs the following JSON is returned:
+When the image is read in its entirety, then and only then does the API return a JSON response. The only exception to this behavior is if an error occurs. If an error occurs, the following JSON is returned:
 
 ```json
 {

articles/cognitive-services/Computer-vision/concept-detecting-adult-content.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: computer-vision
 ms.topic: conceptual
-ms.date: 07/05/2022
+ms.date: 12/27/2022
 ms.author: pafarley
 ms.custom: seodec18, ignite-2022
 ---
@@ -33,14 +33,6 @@ The "adult" classification contains several different categories:
 
 ## Use the API
 
-#### [Version 3.2](#tab/3-2)
-
-You can detect adult content with the [Analyze Image](https://westcentralus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b) API. When you add the value of `Adult` to the **visualFeatures** query parameter, the API returns three boolean properties—`isAdultContent`, `isRacyContent`, and `isGoryContent`—in its JSON response. The method also returns corresponding properties—`adultScore`, `racyScore`, and `goreScore`—which represent confidence scores between zero and one for each respective category.
-
-#### [Version 4.0](#tab/4-0)
-
-You can detect adult content with the [Analyze Image](https://aka.ms/vision-4-0-ref) API. When you add the value of `Adult` to the **features** query parameter, the API returns three properties—`adult`, `racy`, and `gore`—in its JSON response. Each of these properties contains a boolean value and confidence scores between zero and one.
-
----
+You can detect adult content with the [Analyze Image 3.2](https://westcentralus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b) API. When you add the value of `Adult` to the **visualFeatures** query parameter, the API returns three boolean properties—`isAdultContent`, `isRacyContent`, and `isGoryContent`—in its JSON response. The method also returns corresponding properties—`adultScore`, `racyScore`, and `goreScore`—which represent confidence scores between zero and one for each respective category.
 
 - [Quickstart: Computer Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/cognitive-services/Computer-vision/concept-detecting-faces.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: computer-vision
 ms.topic: conceptual
-ms.date: 06/13/2022
+ms.date: 12/27/2022
 ms.author: pafarley
 ms.custom: seodec18
 ---
@@ -116,6 +116,6 @@ The next example demonstrates the JSON response returned for an image containing
 
 ## Use the API
 
-The face detection 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 `Faces` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"faces"` section.
+The face detection 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 `Faces` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"faces"` section.
 
 * [Quickstart: Computer Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/cognitive-services/Computer-vision/concept-face-detection.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: face-api
 ms.topic: conceptual
-ms.date: 07/20/2022
+ms.date: 12/27/2022
 ms.author: pafarley
 ---
 
@@ -31,7 +31,7 @@ Try out the capabilities of face detection quickly and easily using Vision Studi
 
 ## Face ID
 
-The face ID is a unique identifier string for each detected face in an image. Note that Face ID requires limited access approval by filling out the [intake form](https://aka.ms/facerecognition). For more information, see the Face [limited access page](/legal/cognitive-services/computer-vision/limited-access-identity?context=%2Fazure%2Fcognitive-services%2Fcomputer-vision%2Fcontext%2Fcontext). You can request a face ID in your [Face - Detect](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236) API call.
+The face ID is a unique identifier string for each detected face in an image. Note that Face ID requires limited access approval, which you can apply for by filling out the [intake form](https://aka.ms/facerecognition). For more information, see the Face [limited access page](/legal/cognitive-services/computer-vision/limited-access-identity?context=%2Fazure%2Fcognitive-services%2Fcomputer-vision%2Fcontext%2Fcontext). You can request a face ID in your [Face - Detect](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236) API call.
 
 ## Face landmarks
 

articles/cognitive-services/Computer-vision/concept-face-recognition.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: face-api
 ms.topic: conceptual
-ms.date: 07/20/2022
+ms.date: 12/27/2022
 ms.author: pafarley
 ---
 
@@ -22,7 +22,9 @@ You can try out the capabilities of face recognition quickly and easily using Vi
 > [Try Vision Studio](https://portal.vision.cognitive.azure.com/)
 
 
-## Recognition operations
+## Face recognition operations
+
+[!INCLUDE [Gate notice](./includes/identity-gate-notice.md)]
 
 This section details how the underlying operations use the above data structures to identify and verify a face.