Merge pull request #122771 from der3318/minor-fixes-for-face-api-docs

Minor Fixes for Azure Face API Docs

Author: Jak-MS

articles/ai-services/computer-vision/concept-face-recognition-data-structures.md

@@ -19,10 +19,6 @@ ms.author: pafarley
 
 This article explains the data structures used in the Face service for face recognition operations. These data structures hold data on faces and persons.
 
-You can try out the capabilities of face recognition quickly and easily using Vision Studio.
-> [!div class="nextstepaction"]
-> [Try Vision Studio](https://portal.vision.cognitive.azure.com/)
-
 [!INCLUDE [Gate notice](./includes/identity-gate-notice.md)]
 
 ## Data structures used with Identify 

articles/ai-services/computer-vision/concept-face-recognition.md

@@ -19,10 +19,6 @@ ms.author: pafarley
 
 This article explains the concept of Face recognition, its related operations, and the underlying data structures. Broadly, face recognition is the process of verifying or identifying individuals by their faces. Face recognition is important in implementing the identification scenario, which enterprises and apps can use to verify that a (remote) user is who they claim to be.
 
-You can try out the capabilities of face recognition quickly and easily using Vision Studio.
-> [!div class="nextstepaction"]
-> [Try Vision Studio](https://portal.vision.cognitive.azure.com/)
-
 
 ## Face recognition operations
 

articles/ai-services/computer-vision/how-to/identity-access-token.md

@@ -33,9 +33,9 @@ If the ISV learns that a client is using the LimitedAccessToken for non-approved
 
 ## Prerequisites
 
-* [cURL](https://curl.haxx.se/) installed (or another tool that can make HTTP requests).
-* The ISV needs to have either an [Azure AI Face](https://ms.portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/Face) resource or an [Azure AI services multi-service](https://ms.portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/AllInOne) resource.
-* The client needs to have an [Azure AI Face](https://ms.portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/Face) resource.
+* [cURL](https://curl.se/) installed (or another tool that can make HTTP requests).
+* The ISV needs to have either an [Azure AI Face](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/Face) resource or an [Azure AI services multi-service](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/AllInOne) resource.
+* The client needs to have an [Azure AI Face](https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/Face) resource.
 
 ## Step 1: ISV obtains client's Face resource ID
 

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

@@ -42,7 +42,7 @@ The different face detection models are optimized for different tasks. See the f
 |---------|------------|-------------------|-------------|--|
 |**detection_01** | Default choice for all face detection operations. | Not optimized for small, side-view, or blurry faces.                                                     | Returns main face attributes (head pose, age, emotion, and so on) if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
 |**detection_02** | Released in May 2019 and available optionally in all face detection operations.   | Improved accuracy on small, side-view, and blurry faces.  | Does not return face attributes. | Does not return face landmarks.     |
-|**detection_03** | Released in February 2021 and available optionally in all face detection operations.                   | Further improved accuracy, including on smaller faces (64x64 pixels) and rotated face orientations.       | Returns mask and head pose attributes if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
+|**detection_03** | Released in February 2021 and available optionally in all face detection operations.                   | Further improved accuracy, including on smaller faces (64x64 pixels) and rotated face orientations.       | Returns mask, blur, and head pose attributes if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
 
 
 The best way to compare the performances of the detection models is to use them on a sample dataset. We recommend calling the [Detect] API on a variety of images, especially images of many faces or of faces that are difficult to see, using each detection model. Pay attention to the number of faces that each model returns.
@@ -64,7 +64,7 @@ A request URL for the [Detect] REST API will look like this:
 If you are using the client library, you can assign the value for `detectionModel` by passing in an appropriate string. If you leave it unassigned, the API will use the default model version (`detection_01`). See the following code example for the .NET client library.
 
 ```csharp
-string imageUrl = "https://news.microsoft.com/ceo/assets/photos/06_web.jpg";
+string imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/detection1.jpg";
 var faces = await faceClient.Face.DetectWithUrlAsync(url: imageUrl, returnFaceId: false, returnFaceLandmarks: false, recognitionModel: "recognition_04", detectionModel: "detection_03");
 ```
 
@@ -81,7 +81,7 @@ await faceClient.PersonGroup.CreateAsync(personGroupId, "My Person Group Name",
 
 string personId = (await faceClient.PersonGroupPerson.CreateAsync(personGroupId, "My Person Name")).PersonId;
 
-string imageUrl = "https://news.microsoft.com/ceo/assets/photos/06_web.jpg";
+string imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/detection1.jpg";
 await client.PersonGroupPerson.AddFaceFromUrlAsync(personGroupId, personId, imageUrl, detectionModel: "detection_03");
 ```
 
@@ -97,7 +97,7 @@ You can also specify a detection model when you add a face to an existing **Face
 ```csharp
 await faceClient.FaceList.CreateAsync(faceListId, "My face collection", recognitionModel: "recognition_04");
 
-string imageUrl = "https://news.microsoft.com/ceo/assets/photos/06_web.jpg";
+string imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/detection1.jpg";
 await client.FaceList.AddFaceFromUrlAsync(faceListId, imageUrl, detectionModel: "detection_03");
 ```
 

articles/ai-services/computer-vision/how-to/use-large-scale.md

@@ -92,13 +92,13 @@ private static async Task TrainLargeFaceList(
     int timeIntervalInMilliseconds = 1000)
 {
     // Trigger a train call.
-    await FaceClient.LargeTrainLargeFaceListAsync(largeFaceListId);
+    await FaceClient.LargeFaceList.TrainAsync(largeFaceListId);
 
     // Wait for training finish.
     while (true)
     {
-        Task.Delay(timeIntervalInMilliseconds).Wait();
-        var status = await faceClient.LargeFaceList.TrainAsync(largeFaceListId);
+        await Task.Delay(timeIntervalInMilliseconds);
+        var status = await faceClient.LargeFaceList.GetTrainingStatusAsyn(largeFaceListId);
 
         if (status.Status == Status.Running)
         {
@@ -123,7 +123,7 @@ Previously, a typical use of **FaceList** with added faces and **FindSimilar** l
 const string FaceListId = "myfacelistid_001";
 const string FaceListName = "MyFaceListDisplayName";
 const string ImageDir = @"/path/to/FaceList/images";
-faceClient.FaceList.CreateAsync(FaceListId, FaceListName).Wait();
+await faceClient.FaceList.CreateAsync(FaceListId, FaceListName);
 
 // Add Faces to the FaceList.
 Parallel.ForEach(
@@ -141,7 +141,7 @@ const string QueryImagePath = @"/path/to/query/image";
 var results = new List<SimilarPersistedFace[]>();
 using (Stream stream = File.OpenRead(QueryImagePath))
 {
-    var faces = faceClient.Face.DetectWithStreamAsync(stream).Result;
+    var faces = await faceClient.Face.DetectWithStreamAsync(stream);
     foreach (var face in faces)
     {
         results.Add(await faceClient.Face.FindSimilarAsync(face.FaceId, FaceListId, 20));
@@ -156,7 +156,7 @@ When migrating it to **LargeFaceList**, it becomes the following:
 const string LargeFaceListId = "mylargefacelistid_001";
 const string LargeFaceListName = "MyLargeFaceListDisplayName";
 const string ImageDir = @"/path/to/FaceList/images";
-faceClient.LargeFaceList.CreateAsync(LargeFaceListId, LargeFaceListName).Wait();
+await faceClient.LargeFaceList.CreateAsync(LargeFaceListId, LargeFaceListName);
 
 // Add Faces to the LargeFaceList.
 Parallel.ForEach(
@@ -178,7 +178,7 @@ const string QueryImagePath = @"/path/to/query/image";
 var results = new List<SimilarPersistedFace[]>();
 using (Stream stream = File.OpenRead(QueryImagePath))
 {
-    var faces = faceClient.Face.DetectWithStreamAsync(stream).Result;
+    var faces = await faceClient.Face.DetectWithStreamAsync(stream);
     foreach (var face in faces)
     {
         results.Add(await faceClient.Face.FindSimilarAsync(face.FaceId, largeFaceListId: LargeFaceListId));

articles/ai-services/computer-vision/how-to/use-persondirectory.md

@@ -56,7 +56,7 @@ var client = new HttpClient();
 // Request headers
 client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");
 
-var addPersonUri = "https:// {endpoint}/face/v1.0-preview/persons";
+var addPersonUri = "https://{endpoint}/face/v1.0-preview/persons";
 
 HttpResponseMessage response;
 
@@ -113,10 +113,7 @@ Stopwatch s = Stopwatch.StartNew();
 string status = "notstarted";
 do
 {
-    if (status == "succeeded")
-    {
-        await Task.Delay(500);
-    }
+    await Task.Delay(500);
 
     var operationResponseMessage = await client.GetAsync(operationLocation);