Merge pull request #276350 from MicrosoftDocs/main

05/24 OOB Publishing: https://dev.azure.com/msft-skilling/Content/_workitems/edit/257466

Author: v-alje

.openpublishing.publish.config.json

@@ -135,9 +135,9 @@
       "branch_mapping": {}
     },
     {
-      "path_to_root": "ms-identity-dotnetcore-b2c-account-management",
+      "path_to_root": "ms-identity-dotnetcore-b2c-account-management-archive",
       "url": "https://github.com/Azure-Samples/ms-identity-dotnetcore-b2c-account-management",
-      "branch": "master",
+      "branch": "archive",
       "branch_mapping": {}
     },
     {

articles/ai-services/computer-vision/concept-brand-detection.md

@@ -69,6 +69,6 @@ In some cases, the brand detector picks up both the logo image and the stylized
 
 ## Use the API
 
-The brand detection feature is part of the [Analyze Image](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) API. You can call this API through a native SDK or through REST calls. Include `Brands` in the **visualFeatures** query parameter. Then, when you get the full JSON response, parse the string for the contents of the `"brands"` section.
+The brand detection feature is part of the [Analyze Image](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) API. You can call this API through a native SDK or through REST calls. Include `Brands` in the **visualFeatures** query parameter. Then, when you get the full JSON response, parse the string for the contents of the `"brands"` section.
 
 * [Quickstart: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

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

@@ -56,7 +56,7 @@ The following table illustrates a typical image set and the category returned by
 
 ## Use the API
 
-The categorization feature is part of the [Analyze Image 3.2](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) 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.
+The categorization feature is part of the [Analyze Image 3.2](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) 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.
 
 * [Quickstart: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)
 

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

@@ -56,7 +56,7 @@ The following JSON response illustrates what the Analyze API returns when descri
 
 ## Use the API
 
-The image description feature is part of the [Analyze Image](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) API. You can call this API through a native SDK or through REST calls. Include `Description` in the **visualFeatures** query parameter. Then, when you get the full JSON response, parse the string for the contents of the `"description"` section.
+The image description feature is part of the [Analyze Image](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) API. You can call this API through a native SDK or through REST calls. Include `Description` in the **visualFeatures** query parameter. Then, when you get the full JSON response, parse the string for the contents of the `"description"` section.
 
 * [Quickstart: Image Analysis REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)
 

articles/ai-services/computer-vision/concept-detecting-adult-content.md

@@ -34,6 +34,6 @@ The "adult" classification contains several different categories:
 
 ## Use the API
 
-You can detect adult content with the [Analyze Image 3.2](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) 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.
+You can detect adult content with the [Analyze Image 3.2](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) 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: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/ai-services/computer-vision/concept-detecting-color-schemes.md

@@ -77,6 +77,6 @@ The following table shows Azure AI Vision's black and white evaluation in the sa
 
 ## Use the API
 
-The color scheme detection feature is part of the [Analyze Image 3.2](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) API. You can call this API through a native SDK or through REST calls. Include `Color` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"color"` section.
+The color scheme detection feature is part of the [Analyze Image 3.2](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) API. You can call this API through a native SDK or through REST calls. Include `Color` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"color"` section.
 
 * [Quickstart: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/ai-services/computer-vision/concept-detecting-domain-content.md

@@ -20,7 +20,7 @@ There are two ways to use the domain-specific models: by themselves (scoped anal
 
 ### Scoped analysis
 
-You can analyze an image using only the chosen domain-specific model by calling the [Models/\<model\>/Analyze](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) API.
+You can analyze an image using only the chosen domain-specific model by calling the [Models/\<model\>/Analyze](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) API.
 
 The following is a sample JSON response returned by the `models/celebrities/analyze` API for the given image:
 
@@ -51,7 +51,7 @@ The following is a sample JSON response returned by the `models/celebrities/anal
 
 ### Enhanced categorization analysis
 
-You can also use domain-specific models to supplement general image analysis. You do this as part of [high-level categorization](concept-categorizing-images.md) by specifying domain-specific models in the *details* parameter of the [Analyze Image](/rest/api/computervision/analyze-image?view=rest-computervision-v3.1) API call.
+You can also use domain-specific models to supplement general image analysis. You do this as part of [high-level categorization](concept-categorizing-images.md) by specifying domain-specific models in the *details* parameter of the [Analyze Image](/rest/api/computervision/analyze-image?view=rest-computervision-v3.2) API call.
 
 In this case, the 86-category taxonomy classifier is called first. If any of the detected categories have a matching domain-specific model, the image is passed through that model as well and the results are added.
 
@@ -99,7 +99,7 @@ Currently, Azure AI Vision supports the following domain-specific models:
 | celebrities | Celebrity recognition, supported for images classified in the `people_` category |
 | landmarks | Landmark recognition, supported for images classified in the `outdoor_` or `building_` categories |
 
-Calling the [Models](/rest/api/computervision/list-models/list-models?view=rest-computervision-v3.1&tabs=HTTP) API returns this information along with the categories to which each model can apply:
+Calling the [Models](/rest/api/computervision/list-models/list-models?view=rest-computervision-v3.2&tabs=HTTP) API returns this information along with the categories to which each model can apply:
 
 ```json
 {
@@ -133,6 +133,6 @@ Calling the [Models](/rest/api/computervision/list-models/list-models?view=rest-
 
 ## Use the API
 
-This feature is available through the [Analyze Image 3.2 API](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.1&tabs=HTTP). You can call this API through a native SDK or through REST calls. Include `Celebrities` or `Landmarks` in the **details** query parameter. Then, when you get the full JSON response, parse the string for the contents of the `"details"` section.
+This feature is available through the [Analyze Image 3.2 API](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.2&tabs=HTTP). You can call this API through a native SDK or through REST calls. Include `Celebrities` or `Landmarks` in the **details** query parameter. Then, when you get the full JSON response, parse the string for the contents of the `"details"` section.
 
 * [Quickstart: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/ai-services/computer-vision/concept-detecting-faces.md

@@ -110,6 +110,6 @@ 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 3.2](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.1&tabs=HTTP) 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](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.2&tabs=HTTP) 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: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/ai-services/computer-vision/concept-detecting-image-types.md

@@ -14,7 +14,7 @@ ms.author: pafarley
 
 # Image type detection
 
-With the [Analyze Image 3.2 API](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.1&tabs=HTTP), Azure AI Vision can analyze the content type of images and indicate whether an image is clip art or a line drawing.
+With the [Analyze Image 3.2 API](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.2&tabs=HTTP), Azure AI Vision can analyze the content type of images and indicate whether an image is clip art or a line drawing.
 
 ## Clip art detection
 
@@ -109,6 +109,6 @@ The following JSON responses illustrates what Azure AI Vision returns when indic
 
 ## Use the API
 
-The image type detection feature is part of the [Analyze Image 3.2 API](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.1&tabs=HTTP). You can call this API through a native SDK or through REST calls. Include `ImageType` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"imageType"` section.
+The image type detection feature is part of the [Analyze Image 3.2 API](/rest/api/computervision/analyze-image/analyze-image?view=rest-computervision-v3.2&tabs=HTTP). You can call this API through a native SDK or through REST calls. Include `ImageType` in the **visualFeatures** query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the `"imageType"` section.
 
 * [Quickstart: Vision REST API or client libraries](./quickstarts-sdk/image-analysis-client-library.md?pivots=programming-language-csharp)

articles/ai-services/computer-vision/concept-generating-thumbnails.md

@@ -46,7 +46,7 @@ The following table illustrates thumbnails defined by smart-cropping for the exa
 ## Use the API
 
 
-The generate thumbnail feature is available through the [Get Thumbnail](/rest/api/computervision/generate-thumbnail/generate-thumbnail?view=rest-computervision-v3.1&tabs=HTTP) and [Get Area of Interest](/rest/api/computervision/get-area-of-interest/get-area-of-interest?view=rest-computervision-v3.1&tabs=HTTP) API. You can call this API through a native SDK or through REST calls. 
+The generate thumbnail feature is available through the [Get Thumbnail](/rest/api/computervision/generate-thumbnail/generate-thumbnail?view=rest-computervision-v3.2&tabs=HTTP) and [Get Area of Interest](/rest/api/computervision/get-area-of-interest/get-area-of-interest?view=rest-computervision-v3.2&tabs=HTTP) API. You can call this API through a native SDK or through REST calls. 
 
 
 * [Generate a thumbnail (how-to)](./how-to/generate-thumbnail.md)