Merge pull request #833 from PatrickFarley/comvis-updates

Jill Grant · web-flow · commit b58c4cce7db3 · 2024-10-16T21:02:22.000-06:00
add bg removal deprecation notice
diff --git a/articles/ai-services/computer-vision/concept-background-removal.md b/articles/ai-services/computer-vision/concept-background-removal.md
@@ -14,6 +14,8 @@ ms.author: pafarley
 
 # Background removal (version 4.0 preview)
 
+[!INCLUDE [segmentation-deprecation](includes/segmentation-deprecation.md)]
+
 The Background removal operation can divide images into multiple segments or regions to help the user identify different objects or parts of the image. Background removal creates an alpha matte that separates the foreground object from the background in an image. This service is currently in preview, and the API may change in the future.
 
 
diff --git a/articles/ai-services/computer-vision/how-to/background-removal.md b/articles/ai-services/computer-vision/how-to/background-removal.md
@@ -13,6 +13,8 @@ ms.date: 01/19/2024
 
 # Remove the background in images
 
+[!INCLUDE [segmentation-deprecation](../includes/segmentation-deprecation.md)]
+
 This article demonstrates how to call the Image Analysis 4.0 API to segment an image (separate the foreground from background). It also shows you how to parse the returned information.
 
 > [!IMPORTANT]
diff --git a/articles/ai-services/computer-vision/how-to/call-read-api.md b/articles/ai-services/computer-vision/how-to/call-read-api.md
@@ -20,17 +20,6 @@ The following steps assume that you've already created a [Computer Vision resour
 
 [!INCLUDE [read-editions](../includes/read-editions.md)]
 
-## Input requirements
-
-The **Read** API call takes images and documents as its input. The images and documents must meet the following requirements:
-
-* Supported file formats are JPEG, PNG, BMP, PDF, and TIFF.
-* For PDF and TIFF files, up to 2,000 pages (only the first two pages for the free tier) are processed.
-* The file size of images must be less than 500 MB (4 MB for the free tier) with dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels. PDF files don't have a size limit.
-* The minimum height of the text to be extracted is 12 pixels for a 1024 x 768 image, which corresponds to about 8-point font text at 150 DPI.
-
->[!NOTE]
-> You don't need to crop an image for text lines. Send the whole image to the Read API and it recognizes all texts.
 
 ## Determine how to process the data (optional)
 
diff --git a/articles/ai-services/computer-vision/includes/curl-quickstart.md b/articles/ai-services/computer-vision/includes/curl-quickstart.md
@@ -22,7 +22,6 @@ Use the optical character recognition (OCR) REST API to read printed and handwri
 - [cURL](https://curl.haxx.se/) installed.
 - <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision" title="create a Vision resource" target="_blank">An Azure AI Vision resource</a>. You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
 - The key and endpoint from the resource you create to connect your application to the Azure AI Vision service.
-
   1. After your Azure Vision resource deploys, select **Go to resource**.
   1. In the left navigation menu, select **Keys and Endpoint**.
   1. Copy one of the keys and the **Endpoint** for use later in the quickstart.
diff --git a/articles/ai-services/computer-vision/includes/model-customization-deprecation.md b/articles/ai-services/computer-vision/includes/model-customization-deprecation.md
@@ -11,6 +11,6 @@ ms.author: pafarley
 ---
 
 > [!IMPORTANT]
-> This feature is now deprecated. On January 10, 2025, the Azure AI Vision Product Recognition and model customization features will be retired: after this date, API calls to these services will fail.
+> This feature is now deprecated. On January 10, 2025, Azure AI Image Analysis 4.0 Custom Image Classification, Custom Object Detection, and Product Recognition preview API will be retired. After this date, API calls to these services will fail.
 >
 > To maintain a smooth operation of your models, transition to [Azure AI Custom Vision](/azure/ai-services/Custom-Vision-Service/overview), which is now generally available. Custom Vision offers similar functionality to these retiring features.
diff --git a/articles/ai-services/computer-vision/includes/ocr-studio-quickstart.md b/articles/ai-services/computer-vision/includes/ocr-studio-quickstart.md
@@ -17,7 +17,6 @@ ms.author: pafarley
 - An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/).
 - [An Azure AI Vision resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision). You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
 - Connect to [Vision Studio](https://portal.vision.cognitive.azure.com/).
-
   - You might need to sign in.
   - After you sign in, select **View all resources**. If necessary, select **Refresh**. Verify that your resource is available.
 
diff --git a/articles/ai-services/computer-vision/includes/quickstarts-sdk/csharp-sdk.md b/articles/ai-services/computer-vision/includes/quickstarts-sdk/csharp-sdk.md
@@ -26,7 +26,6 @@ Use the optical character recognition (OCR) client library to read printed and h
 - The [Visual Studio IDE](https://visualstudio.microsoft.com/vs/) or current version of [.NET Core](https://dotnet.microsoft.com/download/dotnet-core).
 - <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision" title="create a Vision resource" target="_blank">An Azure AI Vision resource</a>. You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
 - The key and endpoint from the resource you create to connect your application to the Azure AI Vision service.
-
   1. After your Azure Vision resource deploys, select **Go to resource**.
   1. In the left navigation menu, select **Keys and Endpoint**.
   1. Copy one of the keys and the **Endpoint** for use later in the quickstart.
diff --git a/articles/ai-services/computer-vision/includes/quickstarts-sdk/node-sdk.md b/articles/ai-services/computer-vision/includes/quickstarts-sdk/node-sdk.md
@@ -26,7 +26,6 @@ Use the optical character recognition (OCR) client library to read printed and h
 - The current version of [Node.js](https://nodejs.org/).
 - <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision" title="create a Vision resource" target="_blank">An Azure AI Vision resource</a>. You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
 - The key and endpoint from the resource you create to connect your application to the Azure AI Vision service.
-
   1. After your Azure Vision resource deploys, select **Go to resource**.
   1. In the left navigation menu, select **Keys and Endpoint**.
   1. Copy one of the keys and the **Endpoint** for use later in the quickstart.
diff --git a/articles/ai-services/computer-vision/includes/quickstarts-sdk/python-sdk.md b/articles/ai-services/computer-vision/includes/quickstarts-sdk/python-sdk.md
@@ -26,7 +26,6 @@ Use the optical character recognition (OCR) client library to read printed and h
 - Your Python installation should include [pip](https://pip.pypa.io/en/stable/). You can check whether you have pip installed, run `pip --version` on the command line. Get pip by installing the latest version of Python.
 - <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision" title="create a Vision resource" target="_blank">An Azure AI Vision resource</a>. You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
 - The key and endpoint from the resource you create to connect your application to the Azure AI Vision service.
-
   1. After your Azure Vision resource deploys, select **Go to resource**.
   1. In the left navigation menu, select **Keys and Endpoint**.
   1. Copy one of the keys and the **Endpoint** for use later in the quickstart.
diff --git a/articles/ai-services/computer-vision/includes/segmentation-deprecation.md b/articles/ai-services/computer-vision/includes/segmentation-deprecation.md
@@ -0,0 +1,16 @@
+---
+title: Background removal deprecation notice
+titleSuffix: Azure AI services
+#services: cognitive-services
+author: PatrickFarley
+manager: nitinme
+ms.service: azure-ai-vision
+ms.topic: include
+ms.date: 09/10/2024
+ms.author: pafarley
+---
+
+> [!IMPORTANT]
+> This feature is now deprecated. On January 10, 2025, the Azure AI Image Analysis 4.0 Segment API and background removal service will be retired. All requests to this service will fail after this date.
+>
+> To maintain a smooth operation of your models, install the open-source [Florence 2 model](https://huggingface.co/microsoft/Florence-2-large) and use its Region to segmentation feature, which allows for a similar background removal operation.
diff --git a/articles/ai-services/computer-vision/includes/spatial-analysis-deprecation.md b/articles/ai-services/computer-vision/includes/spatial-analysis-deprecation.md
@@ -0,0 +1,25 @@
+---
+title: Spatial Analysis deprecation notice
+titleSuffix: Azure AI services
+#services: cognitive-services
+author: PatrickFarley
+manager: nitinme
+ms.service: azure-ai-vision
+ms.topic: include
+ms.date: 09/10/2024
+ms.author: pafarley
+---
+
+> [!IMPORTANT]
+> On 30 March 2025, Azure AI Vision Spatial Analysis will be retired. Please transition to [Azure AI Video Indexer](https://azurearcjumpstart.com/azure_arc_jumpstart/azure_edge_iot_ops/aks_edge_essentials_single_vi) or another open-source solution before the specified date. We encourage you to make the switch sooner to gain the richer benefits of Azure AI Video Indexer. In addition to the familiar features you are using, here's a quick comparison between Azure AI Vision Spatial Analysis and Azure AI Video Indexer.
+>
+>|Feature |	Azure AI Vision Spatial Analysis |	Azure AI Video Indexer |
+>|---|---|---|
+>|Edge support |	Yes 	|Yes |
+>|Object Detection |	People & Vehicle detection only |	Detects 1000+ objects |
+>|Audio/Speech Processing |	Not supported |	Supported (includes speech transcription, translation and summarization)<br>Supported >(includes speech transcription and sentiment analysis) |
+>|Event Detection & Tracking |	Supported (tracking people & vehicles, event detection) |	Not supported at the Edge yet. Is partially supported at the Cloud. |
+>|Azure Arc Support|	Not supported |	Native support |
+>|Focus Area 	|Visual analysis with specialized tracking |	Comprehensive analysis of both audio and visual content |
+> 
+> From now until 30 March 2025, you can continue to use Azure AI Vision Spatial Analysis or transition to [Azure AI Video Indexer](https://azurearcjumpstart.com/azure_arc_jumpstart/azure_edge_iot_ops/aks_edge_essentials_single_vi) before the specified date. After 30 March 2025, the Spatial Analysis container will no longer be supported and will stop processing new streams.
diff --git a/articles/ai-services/computer-vision/intro-to-spatial-analysis-public-preview.md b/articles/ai-services/computer-vision/intro-to-spatial-analysis-public-preview.md
@@ -18,6 +18,8 @@ Video Analysis includes video-related features like Spatial Analysis and Video R
 
 ## Spatial Analysis
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 You can use Azure AI Vision Spatial Analysis to detect the presence and movements of people in video. Ingest video streams from cameras, extract insights, and generate events to be used by other systems. The service can do things like count the number of people entering a space or measure compliance with face mask and social distancing guidelines. By processing video streams from physical spaces, you can learn how people use them and maximize the space's value to your organization.
 
 Try out the capabilities of Spatial Analysis quickly and easily in your browser by using Azure AI Vision Studio.
diff --git a/articles/ai-services/computer-vision/overview-image-analysis.md b/articles/ai-services/computer-vision/overview-image-analysis.md
@@ -82,6 +82,8 @@ These APIs are only available in certain geographic regions. See [Region availab
 
 ## Background removal (v4.0 preview only)
 
+[!INCLUDE [segmentation-deprecation](includes/segmentation-deprecation.md)]
+
 Image Analysis 4.0 (preview) offers the ability to remove the background of an image. This feature can either output an image of the detected foreground object with a transparent background, or a grayscale alpha matte image showing the opacity of the detected foreground object. 
 
 [Background removal](./concept-background-removal.md)
diff --git a/articles/ai-services/computer-vision/overview-ocr.md b/articles/ai-services/computer-vision/overview-ocr.md
@@ -8,7 +8,7 @@ manager: nitinme
 
 ms.service: azure-ai-vision
 ms.topic: overview
-ms.date: 06/26/2024
+ms.date: 10/16/2024
 ms.author: pafarley
 ms.custom: devx-track-csharp
 ---
@@ -62,6 +62,19 @@ The cloud APIs are the preferred option for most customers because of their ease
 
 For on-premises deployment, the [Read Docker container](./computer-vision-how-to-install-containers.md) enables you to deploy the Azure AI Vision v3.2 generally available OCR capabilities in your own local environment. Containers are great for specific security and data governance requirements.
 
+
+## Input requirements
+
+The **Read** API takes images and documents as its input. The images and documents must meet the following requirements:
+
+* Supported file formats are JPEG, PNG, BMP, PDF, and TIFF.
+* For PDF and TIFF files, up to 2,000 pages (only the first two pages for the free tier) are processed.
+* The file size of images must be less than 500 MB (4 MB for the free tier) with dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels. PDF files don't have a size limit.
+* The minimum height of the text to be extracted is 12 pixels for a 1024 x 768 image, which corresponds to about 8-point font text at 150 DPI.
+
+>[!NOTE]
+> You don't need to crop an image for text lines. Send the whole image to the Read API and it recognizes all texts.
+
 ## OCR data privacy and security
 
 As with all of the Azure AI services, developers using the Azure AI Vision service should be aware of Microsoft's policies on customer data. See the [Azure AI services page](https://www.microsoft.com/trustcenter/cloudservices/cognitiveservices) on the Microsoft Trust Center to learn more.
diff --git a/articles/ai-services/computer-vision/quickstarts-sdk/client-library.md b/articles/ai-services/computer-vision/quickstarts-sdk/client-library.md
@@ -7,7 +7,7 @@ author: PatrickFarley
 manager: nitinme
 ms.service: azure-ai-vision
 ms.topic: quickstart
-ms.date: 06/26/2024
+ms.date: 10/16/2024
 ms.author: pafarley
 ms.devlang: csharp
 # ms.devlang: csharp, golang, java, javascript, python
diff --git a/articles/ai-services/computer-vision/spatial-analysis-camera-placement.md b/articles/ai-services/computer-vision/spatial-analysis-camera-placement.md
@@ -14,6 +14,8 @@ ms.author: pafarley
 
 # Spatial Analysis camera placement
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 This article provides camera placement recommendations for Spatial Analysis (public preview) scenarios. It includes general guidelines as well as specific recommendations for height, angle, and camera-to-focal-point-distance for all the included operations. 
 
 > [!NOTE]
@@ -134,7 +136,7 @@ The following illustration provides simulations for the left and right camera vi
 | ---------------------------------- | ----------------------------------- |  
 | ![Left angle for linear queue](./media/spatial-analysis/camera-angle-linear-left.png) | ![Right angle for linear queue](./media/spatial-analysis/camera-angle-linear-right.png) |  
 
-For zig-zag queues, it's best to avoid placing the camera directly facing the queue line direction, as shown in the following illustration. Note that each of the four example camera positions in the illustration provide the ideal view with an acceptable deviation of +/- 15 degrees in each direction.
+For zig-zag queues, it's best to avoid placing the camera directly facing the queue line direction, as shown in the following illustration. Note that each of the four example camera positions in the illustration provides the ideal view with an acceptable deviation of +/- 15 degrees in each direction.
 
 The following illustrations simulate the view from a camera placed in the ideal locations for a zig-zag queue.
 
diff --git a/articles/ai-services/computer-vision/spatial-analysis-container.md b/articles/ai-services/computer-vision/spatial-analysis-container.md
@@ -14,6 +14,8 @@ ms.custom: devx-track-azurecli
 
 # Install and run the Spatial Analysis container (preview)
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 The Spatial Analysis container enables you to analyze real-time streaming video to understand spatial relationships between people, their movement, and interactions with objects in physical environments. Containers help you meet specific security and data governance requirements.
 
 ## Prerequisites
diff --git a/articles/ai-services/computer-vision/spatial-analysis-local.md b/articles/ai-services/computer-vision/spatial-analysis-local.md
@@ -13,6 +13,8 @@ ms.author: pafarley
 
 # Run Spatial Analysis on a local video file
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 You can use Spatial Analysis with either recorded or live video. Use this guide to learn how to run Spatial Analysis on a recorded local video.
 
 ## Prerequisites
@@ -21,7 +23,7 @@ You can use Spatial Analysis with either recorded or live video. Use this guide
 
 ## Analyze a video file
 
-To use Spatial Analysis for recorded video, record a video file and save it as a .mp4 file. Then take the following steps:
+To use Spatial Analysis for recorded video, record a video file and save it as an .mp4 file. Then take the following steps:
 
 1. Create a blob storage account in Azure, or use an existing one. Then update the following blob storage settings in the Azure portal:
     1. Change **Secure transfer required** to **Disabled**
diff --git a/articles/ai-services/computer-vision/spatial-analysis-logging.md b/articles/ai-services/computer-vision/spatial-analysis-logging.md
@@ -14,6 +14,8 @@ ms.custom: cogserv-non-critical-vision
 
 # Telemetry and troubleshooting
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 Spatial Analysis includes a set of features to monitor the health of the system and help with diagnosing issues.
 
 ## Enable visualizations
diff --git a/articles/ai-services/computer-vision/spatial-analysis-operations.md b/articles/ai-services/computer-vision/spatial-analysis-operations.md
@@ -13,6 +13,8 @@ ms.author: pafarley
 
 # Spatial Analysis operations
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 Spatial Analysis lets you analyze video streams from camera devices in real time. For each camera device you configure, the Spatial Analysis operations will generate an output stream of JSON messages sent to your instance of Azure IoT Hub.
 
 The Spatial Analysis container implements the following operations. You can configure these operations in the deployment manifest of your container.
diff --git a/articles/ai-services/computer-vision/spatial-analysis-zone-line-placement.md b/articles/ai-services/computer-vision/spatial-analysis-zone-line-placement.md
@@ -11,9 +11,10 @@ ms.date: 01/20/2024
 ms.author: pafarley
 ---
 
-
 # Zone and line placement guide
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 This article provides guidelines for how to define zones and lines for Spatial Analysis operations to achieve accurate analysis of peoples movements in a space. This applies to all operations. 
 
 Zones and lines are defined using the JSON `SPACEANALYSIS_CONFIG` parameter. See the [Spatial Analysis operations](spatial-analysis-operations.md) article for more information.
diff --git a/articles/ai-services/computer-vision/use-case-dwell-time.md b/articles/ai-services/computer-vision/use-case-dwell-time.md
@@ -14,6 +14,8 @@ ms.author: pafarley
 
 # Monitor dwell time in front of displays with Spatial Analysis 
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 Spatial Analysis can provide real-time information about how long customers spend in front of a display in a retail store. The service monitors the length of time customers spend in a zone you specify. You can use this information to track customer engagement with promotions/displays within a store or understand customers' preference toward specific products. 
 
 :::image type="content" source="media/use-cases/dwell-time.jpg" alt-text="Photo of a person in a warehouse with stacks of boxes.":::
diff --git a/articles/ai-services/computer-vision/use-case-queue-time.md b/articles/ai-services/computer-vision/use-case-queue-time.md
@@ -14,6 +14,8 @@ ms.author: pafarley
 
 # Measure queue wait time with Spatial Analysis 
 
+[!INCLUDE [spatial-analysis-deprecation](includes/spatial-analysis-deprecation.md)]
+
 Spatial Analysis can generate real-time information about how long users are waiting in a queue in a retail store. The service monitors the length of time customers spend standing inside a checkout zone you specify. A store manager can use this information to manage open checkout stations and employee shifts.
 
 :::image type="content" source="media/use-cases/queue-wait-time.png" alt-text="Photo of people in line at a store.":::
diff --git a/articles/ai-services/computer-vision/vehicle-analysis.md b/articles/ai-services/computer-vision/vehicle-analysis.md
diff --git a/articles/ai-services/computer-vision/whats-new.md b/articles/ai-services/computer-vision/whats-new.md

Original file line number	Diff line number	Diff line change
`@@ -11,6 +11,6 @@ ms.author: pafarley`
`11`	`11`	`---`
`12`	`12`
`13`	`13`	`> [!IMPORTANT]`
`14`		`-> This feature is now deprecated. On January 10, 2025, the Azure AI Vision Product Recognition and model customization features will be retired: after this date, API calls to these services will fail.`
	`14`	`+> This feature is now deprecated. On January 10, 2025, Azure AI Image Analysis 4.0 Custom Image Classification, Custom Object Detection, and Product Recognition preview API will be retired. After this date, API calls to these services will fail.`
`15`	`15`	`>`
`16`	`16`	`> To maintain a smooth operation of your models, transition to [Azure AI Custom Vision](/azure/ai-services/Custom-Vision-Service/overview), which is now generally available. Custom Vision offers similar functionality to these retiring features.`