face freshness

Author: PatrickFarley

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

@@ -1,7 +1,7 @@
 ---
 title: "Face recognition data structures - Face"
 titleSuffix: Azure AI services
-description: Learn about the Face recognition data structures, which hold data on faces and persons.
+description: Learn about the Face recognition data structures, which store data on faces and persons.
 #services: cognitive-services
 author: PatrickFarley
 manager: nitinme
@@ -11,7 +11,7 @@ ms.subservice: azure-ai-face
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 11/04/2023
+ms.date: 01/22/2025
 ms.author: pafarley
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 ---
@@ -73,14 +73,15 @@ Unlike the Identify API, the Find Similar API is designed to be used in applicat
 
 ### FaceList 
 
-**FaceList** represent a flat list of persisted faces. It can hold up 1,000 faces.
+**FaceList** represents a flat list of persisted faces. It can hold up 1,000 faces.
 
 ### LargeFaceList 
 
 **LargeFaceList** is a later version which can hold up to 1,000,000 faces.
 
-## Next steps
+## Next step
 
 Now that you're familiar with the face data structures, write a script that uses them in the Identify operation.
 
-* [Face quickstart](./quickstarts-sdk/identity-client-library.md)
+> [!div class="nextstepaction"]
+> [Face quickstart](./quickstarts-sdk/identity-client-library.md)

articles/ai-services/computer-vision/how-to/add-faces.md

@@ -8,11 +8,13 @@ manager: nitinme
 ms.service: azure-ai-vision
 ms.subservice: azure-ai-face
 ms.topic: how-to
-ms.date: 02/14/2024
+ms.date: 01/22/2025
 ms.author: pafarley
 ms.devlang: csharp
 ms.custom: devx-track-csharp
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
+#customer intent: As a developer, I want to add a large number of persons and faces to a PersonGroup object so that I can manage and recognize faces efficiently.
+
 ---
 
 # Add faces to a PersonGroup
@@ -21,7 +23,7 @@ feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 
 This guide demonstrates how to add a large number of persons and faces to a **PersonGroup** object. The same strategy also applies to **LargePersonGroup**, **FaceList**, and **LargeFaceList** objects. This sample is written in C#.
 
-## Initialization
+## Setup
 
 The following code declares several variables and implements a helper function to schedule the **face add** requests:
 
@@ -124,15 +126,16 @@ Parallel.For(0, PersonCount, async i =>
 
 ## Summary
 
-In this guide, you learned the process of creating a PersonGroup with a massive number of persons and faces. Several reminders:
+In this guide, you learned the process of creating a PersonGroup with a massive number of persons and faces. Key points:
 
 - This strategy also applies to **FaceLists** and **LargePersonGroups**.
-- Adding or deleting faces to different **FaceLists** or persons in **LargePersonGroups** are processed concurrently.
-- Adding or deleting faces to one specific **FaceList** or persons in a **LargePersonGroup** is done sequentially.
+- Adding or deleting faces in different **FaceLists** or persons in **LargePersonGroups** are processed concurrently.
+- Adding or deleting faces in one specific **FaceList** or persons in a **LargePersonGroup** is done sequentially.
 
 
-## Next steps
+## Next step
 
 Next, learn how to use the enhanced data structure **PersonDirectory** to do more with your face data.
 
-- [Use the PersonDirectory structure (preview)](use-persondirectory.md)
+> [!div class="nextstepaction"]
+> [Use the PersonDirectory structure (preview)](use-persondirectory.md)

articles/ai-services/computer-vision/how-to/find-similar-faces.md

@@ -1,15 +1,16 @@
 ---
-title: "Find similar faces"
+title: "Find similar faces using Azure AI services"
 titleSuffix: Azure AI services
-description: Use the Face service to find similar faces (face search by image).
+description: Learn how to use the Azure Face service to find similar faces in a set of images, performing face search by image for various applications.
 #services: cognitive-services
+#customer intent: As a developer, I want to find similar faces in images so that I can perform face recognition tasks.
 author: PatrickFarley
 manager: nitinme
 
 ms.service: azure-ai-vision
 ms.subservice: azure-ai-face
 ms.topic: how-to
-ms.date: 02/14/2024
+ms.date: 01/22/2025
 ms.author: pafarley
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 ---
@@ -22,13 +23,6 @@ The [Find Similar](/rest/api/face/face-recognition-operations/find-similar) oper
 
 This guide demonstrates how to use the Find Similar feature in the different language SDKs. The following sample code assumes you have already authenticated a Face client object. For details on how to do this, follow a [quickstart](../quickstarts-sdk/identity-client-library.md).
 
-## Set up sample URL
-
-This guide uses remote images that are accessed by URL. Save a reference to the following URL string. All of the images accessed in this guide are located at this URL path.
-
-```
-https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/
-```
 
 ## Detect faces for comparison
 
@@ -38,6 +32,12 @@ You need to detect faces in images before you can compare them. In this guide, t
 
 #### [C#](#tab/csharp)
 
+This guide uses remote images that are accessed by URL. Save a reference to the base URL string. All of the images accessed in this guide are located at that URL path.
+
+```csharp
+string baseUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/";
+```
+
 The following face detection method is optimized for comparison operations. It doesn't extract detailed face attributes, and it uses an optimized recognition model.
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FindSimilar.cs?name=snippet_face_detect_recognize)]
@@ -96,8 +96,9 @@ Run the command, and the returned JSON should show the correct face ID as a simi
 
 ---
 
-## Next steps
+## Next step
 
 In this guide, you learned how to call the Find Similar API to do a face search by similarity in a larger group of faces. Next, learn more about the different recognition models available for face comparison operations.
 
-* [Specify a face recognition model](specify-recognition-model.md)
+> [!div class="nextstepaction"]
+> [Specify a face recognition model](specify-recognition-model.md)

articles/ai-services/computer-vision/how-to/identity-detect-faces.md

@@ -2,18 +2,20 @@
 title: "Call the Detect API - Face"
 titleSuffix: Azure AI services
 description: This guide demonstrates how to use face detection to extract attributes like age, emotion, or head pose from a given image.
+#customer intent: As a developer, I want to use face detection to extract attributes from images so that I can analyze and process facial data.
 #services: cognitive-services
 author: PatrickFarley
 manager: nitinme
 
 ms.service: azure-ai-vision
 ms.subservice: azure-ai-face
 ms.topic: how-to
-ms.date: 02/14/2024
+ms.date: 01/22/2025
 ms.author: pafarley
 ms.devlang: csharp
 ms.custom: devx-track-csharp
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
+
 ---
 
 # Call the Detect API
@@ -27,9 +29,9 @@ This guide demonstrates how to use the face detection API to extract attributes
 The code snippets in this guide are written in C# by using the Azure AI Face client library. The same functionality is available through the [REST API](/rest/api/face/face-detection-operations/detect).
 
 
-## Setup
+## Prerequisites
 
-This guide assumes that you already constructed a [FaceClient](/dotnet/api/azure.ai.vision.face.faceclient) object, named `faceClient`, using a Face key and endpoint URL. For instructions on how to set up this feature, follow one of the quickstarts.
+- This guide assumes that you already constructed a [FaceClient](/dotnet/api/azure.ai.vision.face.faceclient) object, named `faceClient`, using a Face key and endpoint URL. For instructions on how to set up this feature, follow one of the quickstarts.
 
 ## Submit data to the service
 
@@ -43,7 +45,7 @@ For information on how to parse the location and dimensions of the face, see [Fa
 
 ## Determine how to process the data
 
-This guide focuses on the specifics of the Detect call, such as what arguments you can pass and what you can do with the returned data. We recommend that you query for only the features you need. Each operation takes more time to complete.
+This guide focuses on the specifics of the Detect call, such as what arguments you can pass and what you can do with the returned data. We recommend that you query for only the features you need. Each operation takes additional time to complete.
 
 ### Get face ID
 
@@ -91,13 +93,13 @@ The following code shows how you might retrieve the face attribute data that you
 
 To learn more about each of the attributes, see the [Face detection and attributes](../concept-face-detection.md) conceptual guide.
 
-## Next steps
+## Next step
 
 In this guide, you learned how to use the various functionalities of face detection and analysis. Next, integrate these features into an app to add face data from users.
 
 - [Tutorial: Add users to a Face service](../enrollment-overview.md)
 
-## Related articles
+## Related content
 
 - [Reference documentation (REST)](/rest/api/face/operation-groups)
 - [Reference documentation (.NET SDK)](https://aka.ms/azsdk-csharp-face-ref)

articles/ai-services/computer-vision/how-to/mitigate-latency.md

@@ -1,25 +1,26 @@
 ---
-title: How to mitigate latency and improve performance when using the Face service
+title: Mitigate latency and improve Face service performance
 titleSuffix: Azure AI services
-description: Learn how to mitigate network latency and improve service performance when using the Face service.
+description: Learn how to mitigate network latency and improve service performance when using the Azure AI Face service to enhance user experience.
 #services: cognitive-services
 author: PatrickFarley
 manager: nitinme
 ms.service: azure-ai-vision
 ms.subservice: azure-ai-face
 ms.topic: how-to
-ms.date: 11/06/2023
+ms.date: 01/22/2025
 ms.author: pafarley
 ms.devlang: csharp
 ms.custom:
   - cogserv-non-critical-vision
   - ignite-2023
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
+#customer intent: As a developer, I want to mitigate latency and improve performance when using the Face service so that my application provides a better user experience.
 ---
 
 # Mitigate latency and improve performance
 
-This guide describes how to mitigate network latency and improve service performance when using the Face service. The speed and performance of your application will affect the experience of your end-users, such as people who enroll in and use a face identification system.
+This guide describes how to mitigate network latency and improve service performance when using Azure Face service. The speed and performance of your application will affect the experience of your end-users, such as people who enroll in and use the face identification system.
 
 ## Mitigate latency
 
@@ -59,6 +60,11 @@ If the image files you use are large, it affects the response time of the Face s
 - It takes more time to upload the file.
 - It takes the service more time to process the file, in proportion to the file size.
 
+Note the following additional tips:
+- For face detection, when using detection model `FaceDetectionModel.Detection01`, reducing the image file size increases processing speed. When you use detection model `FaceDetectionModel.Detection02`, reducing the image file size will only increase processing speed if the image file is smaller than 1920x1080 pixels.
+- For face recognition, reducing the face size will only increase the speed if the image is smaller than 200x200 pixels.
+- The performance of the face detection methods also depends on how many faces are in an image. The Face service can return up to 100 faces for an image. Faces are ranked by face rectangle size from large to small.
+
 
 #### The tradeoff between accuracy and network speed
 
@@ -68,13 +74,6 @@ To achieve the optimal balance between accuracy and speed, follow these tips to
 - For face detection and recognition operations, see [input data for face detection](../concept-face-detection.md#input-requirements) and [input data for face recognition](../concept-face-recognition.md#input-requirements).
 - For liveness detection, see the [tutorial](../Tutorials/liveness.md#select-a-reference-image). 
 
-#### Other file size tips
-
-Note the following additional tips:
-- For face detection, when using detection model `FaceDetectionModel.Detection01`, reducing the image file size increases processing speed. When you use detection model `FaceDetectionModel.Detection02`, reducing the image file size will only increase processing speed if the image file is smaller than 1920x1080 pixels.
-- For face recognition, reducing the face size will only increase the speed if the image is smaller than 200x200 pixels.
-- The performance of the face detection methods also depends on how many faces are in an image. The Face service can return up to 100 faces for an image. Faces are ranked by face rectangle size from large to small.
-
 
 ## Call APIs in parallel when possible
 
@@ -111,7 +110,7 @@ The following are other tips to ensure the reliability and high support of your
     - Always record the `client-request-id` and the response you received when you encounter an unexpected response. If you need any assistance, provide this information to Microsoft Support, along with the Azure resource ID and the time period when the problem occurred.
 - Conduct a pilot test before you release your application into production. Ensure that your application can handle errors properly and effectively. 
 
-## Next steps
+## Next step
 
 In this guide, you learned how to improve performance when using the Face service. Next, follow the tutorial to set up a working software solution that combines server-side and client-side logic to do face liveness detection on users.
 

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

@@ -9,20 +9,19 @@ manager: nitinme
 ms.service: azure-ai-vision
 ms.subservice: azure-ai-face
 ms.topic: how-to
-ms.date: 06/10/2024
+ms.date: 01/22/2025
 ms.author: pafarley
 ms.devlang: csharp
 ms.custom: devx-track-csharp
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
+#customer intent: As a developer, I want to specify the face detection model so that I can choose the best model for my use case.
 ---
 
 # Specify a face detection model
 
 This guide shows you how to specify a face detection model for the Azure AI Face service.
 
-The Face service uses machine learning models to perform operations on human faces in images. We continue to improve the accuracy of our models based on customer feedback and advances in research, and we deliver these improvements as model updates. Developers can specify which version of the face detection model they'd like to use; they can choose the model that best fits their use case.
-
-Read on to learn how to specify the face detection model in certain face operations. The Face service uses face detection whenever it converts an image of a face into some other form of data.
+The Face service uses machine learning models to perform operations on human faces in images. We continue to improve the accuracy of our models based on customer feedback and advances in research, and we deliver these improvements as model updates. Developers can specify which version of the face detection model they'd like to use; they can choose the model that best fits their use case. Read on to learn how to specify the face detection model in certain face operations. The Face service uses face detection whenever it converts an image of a face into some other form of data.
 
 If you aren't sure whether you should use the latest model, skip to the [Evaluate different models](#evaluate-different-models) section to evaluate the new model and compare results using your current data set.
 
@@ -48,9 +47,9 @@ Attributes are a set of features that can optionally be detected if they're spec
 
 | Model | accessories | blur | exposure | glasses | headPose | mask | noise | occlusion | qualityForRecognition |
 |-------|:-----------:|:----:|:--------:|:-------:|:--------:|:----:|:-----:|:---------:|:---------------------:|
-|**detection_01** | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | | ✔️ | ✔️ | ✔️ (for recognition_03 or 04) |
+|**detection_01** | ✅ | ✅ | ✅ | ✅ | ✅ | | ✅ | ✅ | ✅ (for recognition_03 or 04) |
 |**detection_02** | | | | | | | | | |
-|**detection_03** | | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | | ✔️ | ✔️ (for recognition_03 or 04) |
+|**detection_03** | | ✅ | ✅ | ✅ | ✅ | ✅ | | ✅ | ✅ (for recognition_03 or 04) |
 
 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.
 
@@ -139,15 +138,12 @@ This code creates a **FaceList** called `My face collection` and adds a Face to
 > [!NOTE]
 > You don't need to use the same detection model for all faces in a **FaceList** object, and you don't need to use the same detection model when detecting new faces to compare with a **FaceList** object.
 
-
-## Next steps
+## Next step
 
 In this article, you learned how to specify the detection model to use with different Face APIs. Next, follow a quickstart to get started with face detection and analysis.
 
-* [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp)
-* [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python)
-* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java)
-* [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript)
+> [!div class="nextstepaction"]
+> [Face quickstart](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp)
 
 [Detect]: /rest/api/face/face-detection-operations/detect
 [Identify From Person Group]: /rest/api/face/face-recognition-operations/identify-from-person-group