fix more warnings

gewarren · Apr 5, 2024 · d7d1dad · d7d1dad
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diff --git a/docs/core/install/templates.md b/docs/core/install/templates.md
@@ -208,23 +208,23 @@ For example, the .NET 7 SDK includes templates for a console app targeting .NET
     dotnet new install Microsoft.DotNet.Common.ProjectTemplates.3.1
     ```
 
-01. Try creating the app a second time.
+1. Try creating the app a second time.
 
-    ```dotnetcli
-    dotnet new console --framework netcoreapp3.1
-    ```
+   ```dotnetcli
+   dotnet new console --framework netcoreapp3.1
+   ```
 
-    And you should see a message indicating the project was created.
+   And you should see a message indicating the project was created.
 
 <!-- markdownlint-disable MD027 -->
-    > The template "Console Application" was created successfully.
-    >
-    > Processing post-creation actions...
-    > Running 'dotnet restore' on path-to-project-file.csproj...
-    >   Determining projects to restore...
-    >   Restore completed in 1.05 sec for path-to-project-file.csproj.
-    >
-    > Restore succeeded.
+   > The template "Console Application" was created successfully.
+   >
+   > Processing post-creation actions...
+   > Running 'dotnet restore' on path-to-project-file.csproj...
+   >   Determining projects to restore...
+   >   Restore completed in 1.05 sec for path-to-project-file.csproj.
+   >
+   > Restore succeeded.
 <!-- markdownlint-enable MD027 -->
 
 ## See also

diff --git a/docs/machine-learning/tutorials/object-detection-model-builder.md b/docs/machine-learning/tutorials/object-detection-model-builder.md
@@ -261,33 +261,33 @@ When you add a web API to your solution, you're prompted to name the project.
 
 1. If successful, the output should look similar to the following text.
 
-    ```powershell
-    boxes                                      labels scores       boundingBoxes
-    -----                                      ------ ------       -------------
-    {339.97797, 154.43184, 472.6338, 245.0796} {1}    {0.99273646} {}
-    ```
+   ```powershell
+   boxes                                      labels scores       boundingBoxes
+   -----                                      ------ ------       -------------
+   {339.97797, 154.43184, 472.6338, 245.0796} {1}    {0.99273646} {}
+   ```
 
-    - The `boxes` column gives the bounding box coordinates of the object that was detected. The values here belong to the left, top, right, and bottom coordinates respectively.
-    - The `labels` are the index of the predicted labels. In this case, the value 1 is a stop sign.
-    - The `scores` defines how confident the model is that the bounding box belongs to that label.
+   - The `boxes` column gives the bounding box coordinates of the object that was detected. The values here belong to the left, top, right, and bottom coordinates respectively.
+   - The `labels` are the index of the predicted labels. In this case, the value 1 is a stop sign.
+   - The `scores` defines how confident the model is that the bounding box belongs to that label.
 
 <!-- markdownlint-disable MD027 -->
-    > [!NOTE]
-    > **(Optional)** The bounding box coordinates are normalized for a width of 800 pixels and a height of 600 pixels. To scale the bounding box coordinates for your image in further post-processing, you need to:
-    >
-    > 1. Multiply the top and bottom coordinates by the original image height, and multiply the left and right coordinates by the original image width.
-    > 1. Divide the top and bottom coordinates by 600, and divide the left and right coordinates by 800.
-    >
-    >    For example, given the original image dimensions,`actualImageHeight` and `actualImageWidth`, and a `ModelOutput` called `prediction`, the following code snippet shows how to scale the `BoundingBox` coordinates:
-    >
-    >    ```csharp
-    >    var top = originalImageHeight * prediction.Top / 600;
-    >    var bottom = originalImageHeight * prediction.Bottom / 600;
-    >    var left = originalImageWidth * prediction.Left / 800;
-    >    var right = originalImageWidth * prediction.Right / 800;
-    >    ```
-    >
-    > An image can have more than one bounding box, so the same process needs to be applied to each of the bounding boxes in the image.
+   > [!NOTE]
+   > **(Optional)** The bounding box coordinates are normalized for a width of 800 pixels and a height of 600 pixels. To scale the bounding box coordinates for your image in further post-processing, you need to:
+   >
+   > 1. Multiply the top and bottom coordinates by the original image height, and multiply the left and right coordinates by the original image width.
+   > 1. Divide the top and bottom coordinates by 600, and divide the left and right coordinates by 800.
+   >
+   >    For example, given the original image dimensions,`actualImageHeight` and `actualImageWidth`, and a `ModelOutput` called `prediction`, the following code snippet shows how to scale the `BoundingBox` coordinates:
+   >
+   >    ```csharp
+   >    var top = originalImageHeight * prediction.Top / 600;
+   >    var bottom = originalImageHeight * prediction.Bottom / 600;
+   >    var left = originalImageWidth * prediction.Left / 800;
+   >    var right = originalImageWidth * prediction.Right / 800;
+   >    ```
+   >
+   > An image can have more than one bounding box, so the same process needs to be applied to each of the bounding boxes in the image.
 <!-- markdownlint-enable MD027 -->
 
 Congratulations! You've successfully built a machine learning model to detect stop signs in images using Model Builder. You can find the source code for this tutorial at the [dotnet/machinelearning-samples](https://github.com/dotnet/machinelearning-samples/tree/main/samples/modelbuilder/ObjectDetection_StopSigns) GitHub repository.