Merge pull request #3756 from MicrosoftDocs/main

3/26/2025 PM Publish

Author: Albertyang0

articles/ai-foundry/model-inference/concepts/models.md

@@ -178,11 +178,11 @@ See [this model collection in Azure AI Foundry portal](https://ai.azure.com/expl
 
 ### NTT Data
 
-**Tsuzumi** is an autoregressive language optimized transformer. The tuned versions use supervised fine-tuning (SFT). Tsuzumi is handles both Japanese and English language with high efficiency.
+**tsuzumi** is an autoregressive language optimized transformer. The tuned versions use supervised fine-tuning (SFT). tsuzumi handles both Japanese and English language with high efficiency.
 
 | Model  | Type | Tier | Capabilities |
 | ------ | ---- | --- | ------------ |
-| [Tsuzumi-7b](https://ai.azure.com/explore/models/Tsuzumi-7b/version/1/registry/azureml-nttdata) | chat-completion | Global standard | - **Input:** text (8,192 tokens) <br /> - **Output:** text (8,192 tokens) <br /> - **Languages:** `en` and `jp` <br />  - **Tool calling:** No <br /> - **Response formats:** Text |
+| [tsuzumi-7b](https://ai.azure.com/explore/models/Tsuzumi-7b/version/1/registry/azureml-nttdata) | chat-completion | Global standard | - **Input:** text (8,192 tokens) <br /> - **Output:** text (8,192 tokens) <br /> - **Languages:** `en` and `jp` <br />  - **Tool calling:** No <br /> - **Response formats:** Text |
 
 
 ## Next steps

articles/ai-services/.openpublishing.redirection.ai-services.json

@@ -360,6 +360,11 @@
       "redirect_url": "/azure/ai-services/computer-vision/",
       "redirect_document_id": false
     },
+    {
+     "source_path_from_root": "/articles/ai-services/computer-vision/spatial-analysis-logging.md",
+      "redirect_url": "/azure/ai-services/computer-vision/spatial-analysis-container",
+      "redirect_document_id": false
+    },
     {
       "source_path_from_root": "/articles/ai-services/document-intelligence/concept-document-intelligence-studio.md",
       "redirect_url": "/azure/ai-services/document-intelligence/studio-overview",

articles/ai-services/cognitive-services-limited-access.md

@@ -6,7 +6,7 @@ author: PatrickFarley
 manager: nitinme
 ms.service: azure-ai-services
 ms.topic: conceptual
-ms.date: 09/18/2024
+ms.date: 03/26/2025
 ms.author: pafarley
 ---
 
@@ -27,7 +27,7 @@ The following services are Limited Access:
 - [Custom Neural Voice](/legal/cognitive-services/speech-service/text-to-speech/limited-access?context=/azure/ai-services/speech-service/context/context): Pro features
 - [Custom text to speech avatar](/legal/cognitive-services/speech-service/text-to-speech/limited-access?context=/azure/ai-services/speech-service/context/context): All features
 - [Speaker Recognition](/legal/cognitive-services/speech-service/speaker-recognition/limited-access-speaker-recognition?context=/azure/ai-services/speech-service/context/context): All features 
-- [Face API](/legal/cognitive-services/computer-vision/limited-access-identity?context=/azure/ai-services/computer-vision/context/context): Identify and Verify features, face ID property
+- [Azure AI Face](/legal/cognitive-services/computer-vision/limited-access-identity?context=/azure/ai-services/computer-vision/context/context): Identify and Verify features, face ID property
 - [Azure AI Vision](/legal/cognitive-services/computer-vision/limited-access?context=/azure/ai-services/computer-vision/context/context): Celebrity Recognition feature
 - [Azure AI Video Indexer](/azure/azure-video-indexer/limited-access-features): Celebrity Recognition and Face Identify features
 - [Azure OpenAI](/legal/cognitive-services/openai/limited-access): Azure OpenAI Service, modified abuse monitoring, and modified content filters
@@ -43,7 +43,7 @@ Submit a registration form for each Limited Access service you would like to use
 - [Custom Neural Voice](https://aka.ms/customneural): Pro features 
 - [Custom text to speech avatar](https://aka.ms/customneural): All features 
 - [Speaker Recognition](https://aka.ms/azure-speaker-recognition): All features 
-- [Face API](https://aka.ms/facerecognition): Identify and Verify features
+- [Azure AI Face](https://aka.ms/facerecognition): Identify and Verify features
 - [Azure AI Vision](https://aka.ms/facerecognition): Celebrity Recognition feature 
 - [Azure AI Video Indexer](https://aka.ms/facerecognition): Celebrity Recognition and Face Identify features 
 - [Azure OpenAI](/legal/cognitive-services/openai/limited-access): Azure OpenAI Service, modified abuse monitoring, and modified content filters 

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

@@ -10,7 +10,7 @@ ms.subservice: azure-ai-face
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 09/18/2024
+ms.date: 03/26/2025
 ms.author: pafarley
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 ---
@@ -20,11 +20,11 @@ feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 [!INCLUDE [Gate notice](./includes/identity-gate-notice.md)]
 
 > [!IMPORTANT]
-> Face attributes are predicted through the use of statistical algorithms. They might not always be accurate. Use caution when you make decisions based on attribute data. Please refrain from using these attributes for anti-spoofing. Instead, we recommend using Face Liveness detection. For more information, please refer to [Tutorial: Detect liveness in faces](/azure/ai-services/computer-vision/tutorials/liveness). 
+> Face attributes are predicted by statistical algorithms. They might not always be accurate. Use caution when you make decisions based on attribute data. Refrain from using these attributes for anti-spoofing. Instead, we recommend using Face Liveness detection. For more information, please refer to [Tutorial: Detect liveness in faces](/azure/ai-services/computer-vision/tutorials/liveness). 
 
 This article explains the concepts of face detection and face attribute data. Face detection is the process of locating human faces in an image and optionally returning different kinds of face-related data.
 
-You use the [Detect] API to detect faces in an image. To get started using the REST API or a client SDK, follow a [Face service quickstart](./quickstarts-sdk/identity-client-library.md). Or, for a more in-depth guide, see [Call the detect API](./how-to/identity-detect-faces.md).
+You use the [Detect] API to detect faces in an image. To get started using the REST API or a client SDK, follow a [Face service quickstart](./quickstarts-sdk/identity-client-library.md). Or, for a more in-depth guide, see [Call the Detect API](./how-to/identity-detect-faces.md).
 
 ## Face rectangle
 

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

@@ -7,15 +7,17 @@ manager: nitinme
 
 ms.service: azure-ai-vision
 ms.topic: conceptual
-ms.date: 09/19/2024
+ms.date: 03/26/2025
 ms.author: pafarley
 ---
 
 # Object detection
 
-This article explains the concept of object detection. Object detection is similar to [tagging](concept-tag-images-40.md), but the API returns the bounding box coordinates (in pixels) for each object found in the image. For example, if an image contains a dog, cat, and person, the object detection operation lists those objects with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same object in an image.
+This article explains the object detection feature. Object detection is similar to [tagging](concept-tag-images-40.md), but the API returns the bounding box coordinates (in pixels) for each object found in the image. For example, if an image contains a dog, cat, and person, the object detection operation lists those objects with their coordinates in the image. 
 
-The object detection function applies tags based on the objects or living things identified in the image. There's no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the object detection function only finds objects and living things, while the tag function can also include contextual terms like *indoor*, which can't be localized with bounding boxes.
+You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same object in an image.
+
+There's no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the object detection function only finds objects and living things, while the tag function can also include contextual terms like *indoor*, which can't be localized with bounding boxes.
 
 Try out the capabilities of object detection quickly and easily in your browser by using Azure AI Vision Studio.
 

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

@@ -2,14 +2,14 @@
 title: API Reference - Face
 titleSuffix: Azure AI services
 description: API reference provides information about the Person, LargePersonGroup/PersonGroup, LargeFaceList/FaceList, and Face Algorithms APIs.
-author: nitinme
+author: PatrickFarley
 manager: nitinme
 
 ms.service: azure-ai-vision
 ms.subservice: azure-ai-face
 ms.topic: conceptual
-ms.date: 02/17/2021
-ms.author: nitinme
+ms.date: 03/26/2025
+ms.author: pafarley
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 ---
 

articles/ai-services/computer-vision/index.yml

@@ -136,9 +136,6 @@ conceptualContent:
         - itemType: concept
           text: Camera placement
           url: spatial-analysis-camera-placement.md
-        - itemType: concept
-          text: Logging and troubleshooting
-          url: spatial-analysis-logging.md
       footerLink:
         text: More
         url: intro-to-spatial-analysis-public-preview.md

articles/ai-services/computer-vision/spatial-analysis-camera-placement.md

@@ -156,5 +156,4 @@ Organic queues are lines that form organically. This style of queue is acceptabl
 
 <!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
 * [Configure Spatial Analysis operations](./spatial-analysis-operations.md)
-* [Logging and troubleshooting](spatial-analysis-logging.md)
 * [Zone and line placement guide](spatial-analysis-zone-line-placement.md)

articles/ai-services/computer-vision/spatial-analysis-container.md

@@ -100,7 +100,7 @@ Select **Create**. The IoT Hub resource creation may take a couple of minutes. A
 When the Edge compute role is set up on the Edge device, it creates two devices: an IoT device and an IoT Edge device. Both devices can be viewed in the IoT Hub resource. The Azure IoT Edge Runtime will already be running on the IoT Edge device.
 
 > [!NOTE]
-> * Currently only the Linux platform is supported for IoT Edge devices. For help troubleshooting the Azure Stack Edge device, see the [logging and troubleshooting](spatial-analysis-logging.md) article.
+> * Currently only the Linux platform is supported for IoT Edge devices.
 > * To learn more about how to configure an IoT Edge device to communicate through a proxy server, see [Configure an IoT Edge device to communicate through a proxy server](/azure/iot-edge/how-to-configure-proxy-support#azure-portal)
 
 ###  Enable MPS on Azure Stack Edge 
@@ -208,7 +208,7 @@ sudo systemctl restart docker
 ## Enable NVIDIA MPS on the host computer
 
 > [!TIP]
-> * Don't install MPS if your GPU compute capability is less than 7.x (pre Volta). See [CUDA Compatability](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#support-title) for reference. 
+> * Don't install MPS if your GPU compute capability is less than 7.x (pre Volta). See [CUDA Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#support-title) for reference. 
 > * Run the MPS instructions from a terminal window on the host computer. Not inside your Docker container instance.
 
 For best performance and utilization, configure the host computer's GPU(s) for [NVIDIA Multiprocess Service (MPS)](https://docs.nvidia.com/deploy/pdf/CUDA_Multi_Process_Service_Overview.pdf). Run the MPS instructions from a terminal window on the host computer.
@@ -547,8 +547,6 @@ If you want to start consuming the output generated by the container, see the fo
 
 ## Troubleshooting
 
-If you encounter issues when starting or running the container, see [Telemetry and troubleshooting](spatial-analysis-logging.md) for steps for common issues. This article also contains information on generating and collecting logs and collecting system health.
-
 [!INCLUDE [Diagnostic container](../containers/includes/diagnostics-container.md)]
 
 ## Billing
@@ -571,6 +569,5 @@ In this article, you learned concepts and workflow for downloading, installing,
 
 <!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
 * [Configure Spatial Analysis operations](spatial-analysis-operations.md)
-* [Logging and troubleshooting](spatial-analysis-logging.md)
 * [Camera placement guide](spatial-analysis-camera-placement.md)
 * [Zone and line placement guide](spatial-analysis-zone-line-placement.md)

articles/ai-services/computer-vision/spatial-analysis-local.md

@@ -59,6 +59,5 @@ The Spatial Analysis module will start consuming video file and will continuousl
 
 <!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
 * [Configure Spatial Analysis operations](spatial-analysis-operations.md)
-* [Logging and troubleshooting](spatial-analysis-logging.md)
 * [Camera placement guide](spatial-analysis-camera-placement.md)
 * [Zone and line placement guide](spatial-analysis-zone-line-placement.md)