Merge branch 'MicrosoftDocs:main' into CPMPythonDocs

Author: Shamkh

.openpublishing.publish.config.json

@@ -1330,6 +1330,7 @@
   "articles/spatial-anchors/.openpublishing.redirection.spatial-anchors.json",
   "articles/spring-apps/.openpublishing.redirection.spring-apps.json",
   "articles/static-web-apps/.openpublishing.redirection.static-web-apps.json",
+  "articles/storage/.openpublishing.redirection.storage.json",
   "articles/storsimple/.openpublishing.redirection.storsimple.json",
   "articles/stream-analytics/.openpublishing.redirection.stream-analytics.json",
   "articles/synapse-analytics/.openpublishing.redirection.synapse-analytics.json",

articles/ai-services/computer-vision/how-to/background-removal.md

@@ -70,7 +70,7 @@ Where we used this helper function to read the value of an environment variable:
 #### [REST API](#tab/rest)
 -->
 
-Authentication is done by adding the HTTP request header **Ocp-Apim-Subscription-Key** and setting it to your vision key. The call is made to the URL `https://<endpoint>/computervision/imageanalysis:segment?api-version=2023-02-01-preview`, where `<endpoint>` is your unique Computer Vision endpoint URL. See [Select a mode ](./background-removal.md#select-a-mode) section for another query string you add to this URL.
+Authentication is done by adding the HTTP request header **Ocp-Apim-Subscription-Key** and setting it to your vision key. The call is made to the URL `<endpoint>/computervision/imageanalysis:segment?api-version=2023-02-01-preview`, where `<endpoint>` is your unique Computer Vision endpoint URL. See [Select a mode ](./background-removal.md#select-a-mode) section for another query string you add to this URL.
 
 
 ## Select the image to analyze
@@ -164,7 +164,7 @@ Set the query string *mode* to one of these two values. This query string is man
 | `mode`       | `backgroundRemoval` | Outputs an image of the detected foreground object with a transparent background. |
 | `mode`       | `foregroundMatting` | Outputs a gray-scale alpha matte image showing the opacity of the detected foreground object. |
 
-A populated URL for backgroundRemoval would look like this: `https://<endpoint>/computervision/imageanalysis:segment?api-version=2023-02-01-preview&mode=backgroundRemoval`
+A populated URL for backgroundRemoval would look like this: `<endpoint>/computervision/imageanalysis:segment?api-version=2023-02-01-preview&mode=backgroundRemoval`
 
 
 ## Get results from the service

articles/ai-services/computer-vision/how-to/call-analyze-image.md

@@ -86,7 +86,7 @@ You can specify which features you want to use by setting the URL query paramete
 
 A populated URL might look like this:
 
-`https://<endpoint>/vision/v3.2/analyze?visualFeatures=Tags`
+`<endpoint>/vision/v3.2/analyze?visualFeatures=Tags`
 
 #### [C#](#tab/csharp)
 
@@ -135,7 +135,7 @@ The following URL query parameter specifies the language. The default value is `
 
 A populated URL might look like this:
 
-`https://<endpoint>/vision/v3.2/analyze?visualFeatures=Tags&language=en`
+`<endpoint>/vision/v3.2/analyze?visualFeatures=Tags&language=en`
 
 #### [C#](#tab/csharp)
 
@@ -183,7 +183,7 @@ This section shows you how to parse the results of the API call. It includes the
 > [!NOTE]
 > **Scoped API calls**
 >
-> Some of the features in Image Analysis can be called directly as well as through the Analyze API call. For example, you can do a scoped analysis of only image tags by making a request to `https://<endpoint>/vision/v3.2/tag` (or to the corresponding method in the SDK). See the [reference documentation](https://westus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b) for other features that can be called separately.
+> Some of the features in Image Analysis can be called directly as well as through the Analyze API call. For example, you can do a scoped analysis of only image tags by making a request to `<endpoint>/vision/v3.2/tag` (or to the corresponding method in the SDK). See the [reference documentation](https://westus.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/56f91f2e778daf14a499f21b) for other features that can be called separately.
 
 #### [REST](#tab/rest)
 

articles/ai-services/computer-vision/how-to/image-retrieval.md

@@ -17,6 +17,8 @@ ms.custom: references_regions
 
 The Multimodal embeddings APIs enable the _vectorization_ of images and text queries. They convert images to coordinates in a multi-dimensional vector space. Then, incoming text queries can also be converted to vectors, and images can be matched to the text based on semantic closeness. This allows the user to search a set of images using text, without the need to use image tags or other metadata. Semantic closeness often produces better results in search.
 
+The `2024-02-01` API includes a multi-lingual model that supports text search in 102 languages. The original English-only model is still available, but it cannot be combined with the new model in the same search index. If you vectorized text and images using the English-only model, these vectors won’t be compatible with multi-lingual text and image vectors.
+
 > [!IMPORTANT]
 > These APIs are only available in the following geographic regions: East US, France Central, Korea Central, North Europe, Southeast Asia, West Europe, West US.
 
@@ -46,7 +48,7 @@ The `retrieval:vectorizeImage` API lets you convert an image's data to a vector.
 1. Optionally, change the `model-version` parameter to an older version. `2022-04-11` is the legacy model that supports only English text. Images and text that are vectorized with a certain model aren't compatible with other models, so be sure to use the same model for both. 
 
 ```bash
-curl.exe -v -X POST "https://<endpoint>/computervision/retrieval:vectorizeImage?api-version=2023-02-01-preview&model-version=2023-04-15" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
+curl.exe -v -X POST "<endpoint>/computervision/retrieval:vectorizeImage?api-version=2024-02-01&model-version=2023-04-15" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
 {
 'url':'https://learn.microsoft.com/azure/ai-services/computer-vision/media/quickstarts/presentation.png'
 }"
@@ -73,7 +75,7 @@ The `retrieval:vectorizeText` API lets you convert a text string to a vector. To
 1. Optionally, change the `model-version` parameter to an older version. `2022-04-11` is the legacy model that supports only English text. Images and text that are vectorized with a certain model aren't compatible with other models, so be sure to use the same model for both. 
 
 ```bash
-curl.exe -v -X POST "https://<endpoint>/computervision/retrieval:vectorizeText?api-version=2023-02-01-preview&model-version=2023-04-15" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
+curl.exe -v -X POST "<endpoint>/computervision/retrieval:vectorizeText?api-version=2024-02-01&model-version=2023-04-15" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
 {
 'text':'cat jumping'
 }"

articles/ai-services/computer-vision/how-to/model-customization.md

@@ -235,7 +235,6 @@ prediction = prediction_client.predict(model_name, img, content_type='image/png'
 logging.info(f'Prediction: {prediction}')
 ```
 
-<!-- nbend -->
 -->
 
 #### [Vision Studio](#tab/studio)
@@ -369,7 +368,7 @@ The `datasets/<dataset-name>` API lets you create a new dataset object that refe
 1. In the request body, set the `"annotationFileUris"` array to an array of string(s) that show the URI location(s) of your COCO file(s) in blob storage.
 
 ```bash
-curl.exe -v -X PUT "https://<endpoint>/computervision/datasets/<dataset-name>?api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
+curl.exe -v -X PUT "<endpoint>/computervision/datasets/<dataset-name>?api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
 {
 'annotationKind':'imageClassification',
 'annotationFileUris':['<URI>']
@@ -387,7 +386,7 @@ The `models/<model-name>` API lets you create a new custom model and associate i
 1. In the request body, set `"modelKind"` to either `"Generic-Classifier"` or `"Generic-Detector"`, depending on your project.
 
 ```bash
-curl.exe -v -X PUT "https://<endpoint>/computervision/models/<model-name>?api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
+curl.exe -v -X PUT "<endpoint>/computervision/models/<model-name>?api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
 {
 'trainingParameters': {
     'trainingDatasetName':'<dataset-name>',
@@ -408,7 +407,7 @@ The `models/<model-name>/evaluations/<eval-name>` API evaluates the performance
 1. In the request body, set `"testDatasetName"` to the name of the dataset you want to use for evaluation. If you don't have a dedicated dataset, you can use the same dataset you used for training.
 
 ```bash
-curl.exe -v -X PUT "https://<endpoint>/computervision/models/<model-name>/evaluations/<eval-name>?api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
+curl.exe -v -X PUT "<endpoint>/computervision/models/<model-name>/evaluations/<eval-name>?api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
 {
 'evaluationParameters':{
     'testDatasetName':'<dataset-name>'
@@ -431,7 +430,7 @@ The `imageanalysis:analyze` API does ordinary Image Analysis operations. By spec
 1. In the request body, set `"url"` to the URL of a remote image you want to test your model on.
 
 ```bash
-curl.exe -v -X POST "https://<endpoint>/computervision/imageanalysis:analyze?model-name=<model-name>&api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
+curl.exe -v -X POST "<endpoint>/computervision/imageanalysis:analyze?model-name=<model-name>&api-version=2023-02-01-preview" -H "Content-Type: application/json" -H "Ocp-Apim-Subscription-Key: <subscription-key>" --data-ascii "
 {'url':'https://learn.microsoft.com/azure/ai-services/computer-vision/media/quickstarts/presentation.png'
 }"
 ```

articles/ai-services/computer-vision/how-to/shelf-analyze.md

@@ -36,7 +36,7 @@ To analyze a shelf image, do the following steps:
 1. Copy the following `curl` command into a text editor.
 
     ```bash
-    curl -X PUT -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/productrecognition/ms-pretrained-product-detection/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
+    curl -X PUT -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "<endpoint>/computervision/productrecognition/ms-pretrained-product-detection/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
         'url':'<your_url_string>'
     }"
     ```

articles/ai-services/computer-vision/how-to/shelf-model-customization.md

@@ -46,7 +46,7 @@ When your custom model is trained and ready (you've completed the steps in the [
 The API call will look like this:
 
 ```bash
-curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/productrecognition/<your_model_name>/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
+curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "<endpoint>/computervision/productrecognition/<your_model_name>/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
     'url':'<your_url_string>'
 }"
 ```

articles/ai-services/computer-vision/how-to/shelf-modify-images.md

@@ -43,7 +43,7 @@ To run the image stitching operation on a set of images, follow these steps:
 1. Copy the following `curl` command into a text editor.
 
     ```bash
-    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/imagecomposition:stitch?api-version=2023-04-01-preview" --output <your_filename> -d "{
+    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "<endpoint>/computervision/imagecomposition:stitch?api-version=2023-04-01-preview" --output <your_filename> -d "{
         'images': [
             '<your_url_string_>',
             '<your_url_string_2>',
@@ -78,7 +78,7 @@ To correct the perspective distortion in the composite image, follow these steps
 1. Copy the following `curl` command into a text editor.
 
     ```bash
-    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/imagecomposition:rectify?api-version=2023-04-01-preview" --output <your_filename> -d "{
+    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "<endpoint>/computervision/imagecomposition:rectify?api-version=2023-04-01-preview" --output <your_filename> -d "{
       'url': '<your_url_string>',
       'controlPoints': {
         'topLeft': {

articles/ai-services/computer-vision/how-to/shelf-planogram.md

@@ -250,7 +250,7 @@ This is the text you'll use in your API request body.
 1. Copy the following `curl` command into a text editor.
 
     ```bash
-    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/planogramcompliance:match?api-version=2023-04-01-preview" -d "<body>"
+    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "<endpoint>/computervision/planogramcompliance:match?api-version=2023-04-01-preview" -d "<body>"
     ```
 1. Make the following changes in the command where needed:
     1. Replace the value of `<subscriptionKey>` with your Vision resource key.

articles/ai-services/computer-vision/identity-api-reference.md

@@ -18,13 +18,13 @@ ms.author: nitinme
 Azure AI Face is a cloud-based service that provides algorithms for face detection and recognition. The Face APIs comprise the following categories:
 
 - Face Algorithm APIs: Cover core functions such as [Detection](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236), [Find Similar](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237), [Verification](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523a), [Identification](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239), and [Group](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395238).
+- [DetectLiveness session APIs](https://westus.dev.cognitive.microsoft.com/docs/services/609a5e53f0971cb3/operations/session-create-detectliveness-singlemodal): Used to create and manage a Liveness Detection session. See the [Liveness Detection](/azure/ai-services/computer-vision/tutorials/liveness) tutorial.
 - [FaceList APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039524b): Used to manage a FaceList for [Find Similar](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237).
 - [LargePersonGroup Person APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/599adcba3a7b9412a4d53f40): Used to manage LargePersonGroup Person Faces for [Identification](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239).
 - [LargePersonGroup APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/599acdee6ac60f11b48b5a9d): Used to manage a LargePersonGroup dataset for [Identification](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239).
 - [LargeFaceList APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/5a157b68d2de3616c086f2cc): Used to manage a LargeFaceList for [Find Similar](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237).
 - [PersonGroup Person APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523c): Used to manage PersonGroup Person Faces for [Identification](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239).
 - [PersonGroup APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395244): Used to manage a PersonGroup dataset for [Identification](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239).
-- [PersonDirectory Person APIs](https://westus.dev.cognitive.microsoft.com/docs/services/face-v1-0-preview/operations/5f06637aad1c4fba7238de25)
+- [PersonDirectory Person APIs](https://westus.dev.cognitive.microsoft.com/docs/services/face-v1-0-preview/operations/5f063c5279ef2ecd2da02bbc)
 - [PersonDirectory DynamicPersonGroup APIs](https://westus.dev.cognitive.microsoft.com/docs/services/face-v1-0-preview/operations/5f066b475d2e298611e11115)
-- [Snapshot APIs](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/snapshot-take): Used to manage a Snapshot for data migration across subscriptions.
 - [Liveness Session APIs](https://westus.dev.cognitive.microsoft.com/docs/services/609a5e53f0971cb3/operations/session-create-detectliveness-singlemodal) and [Liveness-With-Verify Session APIs](https://westus.dev.cognitive.microsoft.com/docs/services/609a5e53f0971cb3/operations/session-create-detectlivenesswithverify-singlemodal): Used to manage liveness sessions from App Server to orchestrate the liveness solution.