Fix syntax to reduce warnings

Author: dargilco

articles/ai-services/computer-vision/includes/how-to-guides/analyze-image-40-cpp.md

@@ -53,7 +53,7 @@ Create a new **VisionSource** object from the local image file you want to analy
 
 Create a new **VisionSource** object from a memory buffer containing the image data, by using the static constructor [VisionSource::FromImageSourceBuffer](/cpp/cognitive-services/vision/input-visionsource#fromimagesourcebuffer).
 
-This is done by first creating a new [ImageSourceBuffer](/cpp/cognitive-services/vision/input-imagesourcebuffer), getting access to its [ImageWriter](/cpp/cognitive-services/input-imagewriter) object and writing the image data into it. In the following code example, `imageBuffer` is a variable of type `std::vector<uint8_t>` containing the image data.
+Start by creating a new [ImageSourceBuffer](/cpp/cognitive-services/vision/input-imagesourcebuffer), then get access to its [ImageWriter](/cpp/cognitive-services/input-imagewriter) object and write the image data into it. In the following code example, `imageBuffer` is a variable of type `std::vector<uint8_t>` containing the image data.
 
 ```cpp
   auto imageSourceBuffer = std::make_shared<ImageSourceBuffer>();
@@ -80,7 +80,7 @@ Create a new [ImageAnalysisOptions](/cpp/cognitive-services/vision/imageanalysis
 
 ### Set model name when using a custom model
 
-You can also do image analysis with a custom trained model. To create and train a model, see [Create a custom Image Analysis model](/azure/ai-services/computer-vision/how-to/model-customization). Once your model is trained, all you need is the model's name. You do not need to specify visual features if you use a custom model.
+You can also do image analysis with a custom trained model. To create and train a model, see [Create a custom Image Analysis model](/azure/ai-services/computer-vision/how-to/model-customization). Once your model is trained, all you need is the model's name. You don't need to specify visual features if you use a custom model.
 
 
 To use a custom model, create the [ImageAnalysisOptions](/cpp/cognitive-services/vision/imageanalysis-imageanalysisoptions) object and call the [SetModelName](/cpp/cognitive-services/vision/imageanalysis-imageanalysisoptions#setmodelname) method.  You don't need to call any other methods on **ImageAnalysisOptions**. There's no need to call [SetFeatures](/cpp/cognitive-services/vision/imageanalysis-imageanalysisoptions#setfeatures) as you do with standard model, since your custom model already implies the visual features the service extracts.
@@ -132,7 +132,7 @@ This section shows you how to make an analysis call to the service using the sta
 
 1. Using the **VisionServiceOptions**, **VisionSource** and **ImageAnalysisOptions** objects, construct a new [ImageAnalyzer](/cpp/cognitive-services/vision/imageanalysis-imageanalyzer) object.
 
-1. Call the **Analyze** method on the **ImageAnalyzer** object, as shown here. This is a blocking (synchronous) call until the service returns the results or an error occurred. Alternatively, you can call the nonblocking **AnalyzeAsync** method.
+1. Call the **Analyze** method on the **ImageAnalyzer** object, as shown here. This call is synchronous, and will block until the service returns the results or an error occurred. Alternatively, you can call the nonblocking **AnalyzeAsync** method.
 
 1. Call **GetReason** method on the [ImageAnalysisResult](/cpp/cognitive-services/vision/imageanalysis-imageanalysisresult) object, to determine if analysis succeeded or failed.
 

articles/ai-services/computer-vision/includes/how-to-guides/analyze-image-40-csharp.md

@@ -50,7 +50,7 @@ Create a new **VisionSource** object from the local image file you want to analy
 
 Create a new **VisionSource** object from a memory buffer containing the image data, by using the static constructor [VisionSource.FromImageSourceBuffer](/dotnet/api/azure.ai.vision.common.visionsource.fromimagesourcebuffer).
 
-This is done by first creating a new [ImageSourceBuffer](/dotnet/api/azure.ai.vision.common.imagesourcebuffer), getting access to its [ImageWriter](/dotnet/api/azure.ai.vision.common.imagewriter) object and writing the image data into it. In the following code example, `imageBuffer` is a variable of type `Memory<byte>` containing the image data.
+Start by creating a new [ImageSourceBuffer](/dotnet/api/azure.ai.vision.common.imagesourcebuffer), then get access to its [ImageWriter](/dotnet/api/azure.ai.vision.common.imagewriter) object and write the image data into it. In the following code example, `imageBuffer` is a variable of type `Memory<byte>` containing the image data.
 
 ```csharp
 using var imageSourceBuffer = new ImageSourceBuffer();
@@ -79,7 +79,7 @@ Create a new [ImageAnalysisOptions](/dotnet/api/azure.ai.vision.imageanalysis.im
 
 ### Set model name when using a custom model
 
-You can also do image analysis with a custom trained model. To create and train a model, see [Create a custom Image Analysis model](/azure/ai-services/computer-vision/how-to/model-customization). Once your model is trained, all you need is the model's name. You do not need to specify visual features if you use a custom model.
+You can also do image analysis with a custom trained model. To create and train a model, see [Create a custom Image Analysis model](/azure/ai-services/computer-vision/how-to/model-customization). Once your model is trained, all you need is the model's name. You don't need to specify visual features if you use a custom model.
 
 
 To use a custom model, create the [ImageAnalysisOptions](/dotnet/api/azure.ai.vision.imageanalysis.imageanalysisoptions) object and set the [ModelName](/dotnet/api/azure.ai.vision.imageanalysis.imageanalysisoptions.modelname#azure-ai-vision-imageanalysis-imageanalysisoptions-modelname) property. You don't need to set any other properties on **ImageAnalysisOptions**. There's no need to set the [Features](/dotnet/api/azure.ai.vision.imageanalysis.imageanalysisoptions.features#azure-ai-vision-imageanalysis-imageanalysisoptions-features) property, as you do with the standard model, since your custom model already implies the visual features the service extracts.
@@ -132,7 +132,7 @@ This section shows you how to make an analysis call to the service using the sta
 
 1. Using the **VisionServiceOptions**, **VisionSource** and **ImageAnalysisOptions** objects, construct a new [ImageAnalyzer](/dotnet/api/azure.ai.vision.imageanalysis.imageanalyzer) object. **ImageAnalyzer** implements **IDisposable**, therefore create the object with a **using** statement, or explicitly call **Dispose** method after analysis completes.
 
-1. Call the **Analyze** method on the **ImageAnalyzer** object, as shown here. This is a blocking (synchronous) call until the service returns the results or an error occurred. Alternatively, you can call the nonblocking **AnalyzeAsync** method.
+1. Call the **Analyze** method on the **ImageAnalyzer** object, as shown here. The call is synchronous, and will block until the service returns the results or an error occurred. Alternatively, you can call the nonblocking **AnalyzeAsync** method.
 
 1. Check the **Reason** property on the [ImageAnalysisResult](/dotnet/api/azure.ai.vision.imageanalysis.imageanalysisresult) object, to determine if analysis succeeded or failed.
 

articles/ai-services/computer-vision/includes/how-to-guides/analyze-image-40-python.md

@@ -74,7 +74,7 @@ Create a new [ImageAnalysisOptions](/python/api/azure-ai-vision/azure.ai.vision.
 
 ### Set model name when using a custom model
 
-You can also do image analysis with a custom trained model. To create and train a model, see [Create a custom Image Analysis model](/azure/ai-services/computer-vision/how-to/model-customization). Once your model is trained, all you need is the model's name. You do not need to specify visual features if you use a custom model.
+You can also do image analysis with a custom trained model. To create and train a model, see [Create a custom Image Analysis model](/azure/ai-services/computer-vision/how-to/model-customization). Once your model is trained, all you need is the model's name. You don't need to specify visual features if you use a custom model.
 
 To use a custom model, create the [ImageAnalysisOptions](/python/api/azure-ai-vision/azure.ai.vision.imageanalysisoptions) object and set the [model_name](/python/api/azure-ai-vision/azure.ai.vision.imageanalysisoptions#azure-ai-vision-imageanalysisoptions-model-name) property. You don't need to set any other properties on **ImageAnalysisOptions**. There's no need to set the [features](/python/api/azure-ai-vision/azure.ai.vision.imageanalysisoptions#azure-ai-vision-imageanalysisoptions-features) property, as you do with the standard model, since your custom model already implies the visual features the service extracts.
 
@@ -125,7 +125,7 @@ This section shows you how to make an analysis call to the service using the sta
 
 1. Using the **VisionServiceOptions**, **VisionSource** and **ImageAnalysisOptions** objects, construct a new [ImageAnalyzer](/python/api/azure-ai-vision/azure.ai.vision.imageanalyzer) object.
 
-1. Call the **analyze** method on the **ImageAnalyzer** object, as shown here. This is a blocking (synchronous) call until the service returns the results or an error occurred. Alternatively, you can call the nonblocking **analyze_async** method.
+1. Call the **analyze** method on the **ImageAnalyzer** object, as shown here. This call is synchronous, and will block until the service returns the results or an error occurred. Alternatively, you can call the nonblocking **analyze_async** method.
 
 1. Check the **reason** property on the [ImageAnalysisResult](/python/api/azure-ai-vision/azure.ai.vision.imageanalysisresult) object, to determine if analysis succeeded or failed.
 

articles/ai-services/computer-vision/includes/quickstarts-sdk/image-analysis-cpp-sdk-40.md

@@ -26,7 +26,7 @@ Use the Image Analysis client SDK for C++ to analyze an image to read text and g
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/)
 * For Windows development, the [Visual Studio IDE](https://visualstudio.microsoft.com/vs/) with workload **Desktop development with C++** enabled.
 * Once you have your Azure subscription, <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision"  title="create a Vision resource"  target="_blank">create a Vision resource</a> in the Azure portal. In order to use the captioning feature in this quickstart, you must create your resource in one of the following Azure regions: East US, France Central, Korea Central, North Europe, Southeast Asia, West Europe, West US, East Asia, East Asia. After it deploys, select **Go to resource**.
-    * You'll need the key and endpoint from the resource you create to connect your application to the Azure AI Vision service. 
+    * You need the key and endpoint from the resource you create to connect your application to the Azure AI Vision service. 
     * You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
 
 
@@ -56,7 +56,7 @@ Follow the [SDK installation guide](../../sdk/install-sdk.md?pivots=programming-
 From the project directory, open the _ImageAnalysisQuickstart.cpp_ file that was created previously with [your new project](#set-up-application). Clear its contents and paste in the following code:
 
 > [!TIP]
-> The code shows analyzing an image URL. You can also analyze a local image file, or an image from a memory buffer. See the [Analyze Image how-to guide](../../how-to/call-analyze-image-40.md) for more details.
+> The code shows analyzing an image URL. You can also analyze a local image file, or an image from a memory buffer. For more information, see the [Analyze Image how-to guide](../../how-to/call-analyze-image-40.md).
 
 [!code-cpp[](~/azure-ai-vision-sdk/docs/learn.microsoft.com/cpp/image-analysis/quick-start/quick-start.cpp?name=snippet_single)]
 

articles/ai-services/computer-vision/includes/quickstarts-sdk/image-analysis-csharp-sdk-40.md

@@ -24,7 +24,7 @@ Use the Image Analysis client SDK for C# to analyze an image to read text and ge
 ## Prerequisites
 
 * An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/)
-* The [Visual Studio IDE](https://visualstudio.microsoft.com/vs/) with workload **.NET desktop development** enabled. Or if you don't plan on using Visual Studio IDE, you need [.NET 6.0](https://dotnet.microsoft.com/download/dotnet-core) SDK or above installed.
+* The [Visual Studio IDE](https://visualstudio.microsoft.com/vs/) with workload **.NET desktop development** enabled. Or if you don't plan on using Visual Studio IDE, you need [.NET 6.0](https://dotnet.microsoft.com/download/dotnet-core) SDK or higher installed.
 * [.NET Runtime](https://dotnet.microsoft.com/download/dotnet/) installed.
 * Once you have your Azure subscription, <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision"  title="create a Vision resource"  target="_blank">create a Vision resource</a> in the Azure portal. In order to use the captioning feature in this quickstart, you must create your resource in one of the following Azure regions: East US, France Central, Korea Central, North Europe, Southeast Asia, West Europe, West US. After it deploys, select **Go to resource**.
     * You need the key and endpoint from the resource you create to connect your application to the Azure AI Vision service.
@@ -86,7 +86,7 @@ For more information, see the [SDK installation guide](../../sdk/install-sdk.md?
 From the project directory, open the *Program.cs* file that was created previously with [your new project](#set-up-application). Paste in the following code:
 
 > [!TIP]
-> The code shows analyzing an image URL. You can also analyze a local image file, or an image from a memory buffer. See the [Analyze Image how-to guide](../../how-to/call-analyze-image-40.md) for more details.
+> The code shows analyzing an image URL. You can also analyze a local image file, or an image from a memory buffer. For more information, see the [Analyze Image how-to guide](../../how-to/call-analyze-image-40.md).
 
 [!code-csharp[](~/azure-ai-vision-sdk/docs/learn.microsoft.com/csharp/image-analysis/quick-start/program.cs?name=snippet_single)]
 

articles/ai-services/computer-vision/includes/quickstarts-sdk/image-analysis-python-sdk-40.md

@@ -49,7 +49,7 @@ Use the Image Analysis client SDK for Python to analyze a remote image to read t
 1. Copy the following code into *quickstart.py*:
 
 > [!TIP]
-> The code shows analyzing an image URL. You can also analyze a local image file, or an image from a memory buffer. See the [Analyze Image how-to guide](../../how-to/call-analyze-image-40.md) for more details.
+> The code shows analyzing an image URL. You can also analyze a local image file, or an image from a memory buffer. For more information, see the [Analyze Image how-to guide](../../how-to/call-analyze-image-40.md).
 
 [!code-python[](~/azure-ai-vision-sdk/docs/learn.microsoft.com/python/image-analysis/quick-start/main.py?name=snippet_single)]
 

articles/ai-services/computer-vision/sdk/overview-sdk.md

@@ -48,8 +48,8 @@ Before you create a new issue:
 ## Release notes
 
 * **Vision SDK 0.15.1-beta.1** released September 2023.
-  * Add support for Java JRE on Windows x64 and Linux x64.
-  * Input image can now be provided from a memory buffer (in addition to from file or URL).
+  * Image Analysis Java JRE APIs for Windows x64 and Linux x64 were added.
+  * Image Analysis can now be done from a memory buffer (C#, C++, Python, Java).
 * **Vision SDK 0.13.0-beta.1** released July 2023. Image Analysis support was added for Universal Windows Platform (UWP) applications (C++, C#). Run-time package size reduction: Only the two native binaries
 `Azure-AI-Vision-Native.dll` and `Azure-AI-Vision-Extension-Image.dll` are now needed.
 * **Vision SDK 0.11.1-beta.1** released May 2023. Image Analysis APIs were updated to support [Background Removal](../how-to/background-removal.md).