Merge pull request #1438 from madeline-underwood/OpenCV_WoA

pareenaverma · web-flow · commit bb52d18de67a · 2024-12-20T15:27:42.000-05:00
OpenCV_WoA_AP to review
diff --git a/content/learning-paths/laptops-and-desktops/win-opencv/1-opencv-compilers.md b/content/learning-paths/laptops-and-desktops/win-opencv/1-opencv-compilers.md
@@ -8,73 +8,33 @@ layout: learningpathall
 
 ## What is OpenCV?
 
-OpenCV (Open Source Computer Vision Library) is a popular, open-source library that developers use to build computer vision applications. It provides a set of tools and functions that help you handle tasks related to images and videos without needing to write everything from scratch. 
+Open Source Computer Vision Library (OpenCV) is a popular, Open Source library that developers can use to build computer vision applications. It provides a set of tools and functions that can help you with tasks handling images and videos. 
 
-Here’s what developers should know:
+Here are some of the benefits of using OpenCV:
 
-* __Ease of Use__: OpenCV comes with pre-built functions for common tasks like reading, displaying, and processing images and videos. This saves time compared to writing algorithms from the ground up.
+* __Ease of Use__: OpenCV comes with pre-built functions for common tasks such as reading, displaying, and processing images and videos. This saves time compared to needing to cover absolutely every detail when writing an algorithm.
 
-* __Image Processing__: You can perform operations like changing colors, applying filters, resizing, rotating, and other transformations to images with minimal code.
+* __Image Processing__: You can perform operations such as changing colors, applying filters, resizing, rotating, and make other transformations to images with minimal coding effort.
 
-* __Video Handling__: Developers can use OpenCV to capture, modify, and analyze video frames, making it ideal for creating applications like video surveillance or video editing tools.
+* __Video Handling__: Developers can use OpenCV to capture, modify, and analyze video frames, making it ideal for creating applications such as video surveillance or video editing tools.
 
-* __Computer Vision Algorithms__: OpenCV includes built-in algorithms for complex tasks like object detection (e.g., face and eye recognition), edge detection, and image segmentation.
+* __Computer Vision Algorithms__: OpenCV includes built-in algorithms for complex tasks such as:
 
-* __Machine Learning__: It includes modules for training models using basic machine learning algorithms, which can be applied for pattern recognition and data analysis in visual data.
+    * Object detection; for example, face and eye recognition.
+    * Edge detection.
+    * Image segmentation.
 
-* __Community and Resources__: Being open-source and widely adopted, there is a large community of developers contributing to and supporting OpenCV. This makes it easier to find tutorials, documentation, and answers to questions.
+* __Machine Learning__: OpenCV includes modules for training models using basic machine learning algorithms, which can be applied for pattern recognition and data analysis in visual data.
 
+* __Community and Resources__: As OpenCV is Open Source and widely adopted, there is a large community of developers both contributing to, and supporting, OpenCV. This makes it easier to find tutorials, documentation, and answers to questions, as there are many resources available.
 
-## Which compilers are available for Windows on Arm Development?
-
-MSVC (Microsoft Visual C++) and Clang are options for developers building Windows on Arm applications.
-
-* __MSVC__: A compiler developed by Microsoft that’s part of the Visual Studio IDE. It’s designed specifically for Windows and integrates well with the Windows development ecosystem.
-
-* __Clang__: An open-source compiler that is part of the LLVM project. It’s known for its modern design and cross-platform capabilities. 
-
-MSVC is ideal for Windows-focused projects needing seamless integration with Visual Studio. Clang is ideal for cross-platform projects or when using modern C++ features.
-
-## Before you begin
-
-Any Windows on Arm machine which has the required tools installed can be used for this Learning Path. You will learn how to build OpenCV using both MSVC and Clang. 
-
-Please install the following tools required for both methods.
-
-* [CMake](/install-guides/cmake)
 
-{{% notice Note %}}
-The instructions were tested with the version 3.28.1
-{{% /notice %}}
-
-* [Git](https://git-scm.com/downloads/win)
-
-{{% notice Note %}}
-There is currently no Arm version of Git. Install the 64-bit x86 version.
-{{% /notice %}}
-
-Follow the link to install the required tools for a method using MSVC.
-
-* [Visual Studio 2022 or higher](/install-guides/vs-woa). 
-
-{{% notice Note %}}
-The instructions were tested with Visual Studio 2022.
-{{% /notice %}}
-
-To build using Clang, please install the following.
-
-* [LLVM](/install-guides/llvm-woa/)
+## Which compilers are available for Windows on Arm Development?
 
-{{% notice Note %}}
-The instructions were tested with the version 18.1.8.
-{{% /notice %}}
+MSVC (Microsoft Visual C++) and Clang are both compilers that are available for developers building Windows on Arm applications.
 
-* [Ninja]( https://github.com/ninja-build/ninja/releases)
+* __MSVC__: Developed by Microsoft, MSVC is a compiler that is part of the Visual Studio IDE. It is designed specifically for Windows, and integrates well with the Windows development ecosystem. MSVC is ideal for Windows-focused projects requiring seamless integration with Visual Studio.
 
-{{% notice Note %}}
-The instructions were tested with version 1.11.1
-{{% /notice %}}
+* __Clang__: Part of the LLVM project, Clang is an Open Source compiler that is known for its modern design and cross-platform capabilities. Clang is better suited to cross-platform projects, or when using modern C++ features.
 
-Make sure LLVM Clang and Ninja are in your search path. If they are not, you can use Windows Control Panel to set the PATH environment variable.
 
-You now have the required development tools installed. Please proceed to the page for the compiler you want to build with.
diff --git a/content/learning-paths/laptops-and-desktops/win-opencv/1.5-opencv-setup.md b/content/learning-paths/laptops-and-desktops/win-opencv/1.5-opencv-setup.md
@@ -0,0 +1,54 @@
+---
+title: Setup
+weight: 3
+
+### FIXED, DO NOT MODIFY
+layout: learningpathall
+---
+## Before you begin
+
+You can use any Windows on Arm machine that has the required tools for this Learning Path. 
+
+The Learning Path shows you how to build OpenCV using MSVC or Clang. 
+
+Click on the links below for the tools download instructions.
+
+### For both compilers
+
+* [CMake](/install-guides/cmake).
+
+{{% notice Note %}}
+This Learning Path was tested with CMake version 3.28.1.
+{{% /notice %}}
+
+* [Git for Windows on Arm](/install-guides/git-woa).
+
+### For MSVC
+
+Follow the link to install the required tools for a method using MSVC.
+
+* [Visual Studio 2022 or higher](/install-guides/vs-woa). 
+
+{{% notice Note %}}
+The instructions were tested with Visual Studio 2022.
+{{% /notice %}}
+
+### For Clang
+
+To build using Clang, install the following tools:
+
+* [LLVM](/install-guides/llvm-woa/).
+
+{{% notice Note %}}
+This Learning Path was tested with LLVM version 18.1.8.
+{{% /notice %}}
+
+* [Ninja]( https://github.com/ninja-build/ninja/releases).
+
+{{% notice Note %}}
+This Learning Path was tested with Ninja version 1.11.1.
+{{% /notice %}}
+
+Make sure LLVM Clang and Ninja are in your search path. If they are not, you can use Windows Control Panel to set the `path` environment variable.
+
+You now have the required development tools installed. You can move on to the page for the compiler that you want to build with.
diff --git a/content/learning-paths/laptops-and-desktops/win-opencv/2-1-build-msvc.md b/content/learning-paths/laptops-and-desktops/win-opencv/2-1-build-msvc.md
@@ -1,14 +1,14 @@
 ---
 title: Build OpenCV Applications with MSVC
-weight: 3
+weight: 5
 
 ### FIXED, DO NOT MODIFY
 layout: learningpathall
 ---
 
 ## How do I build OpenCV with MSVC?
 
-Follow the steps below to build OpenCV and a test application using the library with the MSVC compiler.
+Follow these steps to build OpenCV and a test application using the library with the MSVC compiler.
 
 ### Clone the OpenCV repository
 
@@ -21,14 +21,14 @@ git checkout tags/4.10.0
 ```
 
 {{% notice Note %}}
-You might be able to use a later version, but these steps have been tested with the version 4.10.0.
+You might be able to use a later version, but these steps have been tested with version 4.10.0.
 {{% /notice %}}
 
 ### Pre-build configuration
 
 You can use CMake from the command line. 
 
-First, run the following command to run the pre-build configuration. 
+First, run the following command to run the pre-build configuration: 
 
 ```bash
 mkdir build_msvc
@@ -51,7 +51,7 @@ cmake `
 -DWITH_CAROTENE=OFF
 ```
 
-The given options specify the following:
+The given options in the code above specify the following:
 - The source code is located one level above the current directory.
 - The build will be performed in the current directory.
 - The Visual Studio 2022 MSVC compiler will be used as the compiler.
@@ -108,12 +108,12 @@ cmake --build . --target INSTALL --config Release
 ```
 
 {{% notice Note %}}
-The build takes approximately 25 mins on a Lenovo X13s
+The build takes approximately 25 mins on a Lenovo X13s.
 {{% /notice %}}
 
 &nbsp;
 
-When the build and the install steps are complete, confirm the shared library has been created by inspecting the results in the `install/bin` directory:
+When you have completed the build and installation steps, confirm the shared library has been created by inspecting the results in the `install/bin` directory:
 
 ```bash { output_lines = "2-12" }
 ls ./install/x64/vc17/bin
@@ -148,15 +148,15 @@ Mode                 LastWriteTime         Length Name
 
 The library used in your application is `opencv_world<version>.lib/dll`. 
 
-Once the library files are correctly generated, run the following command to ensure there are no errors.
+Once the library files are correctly generated, run the following command to ensure that there are no errors.
 
 ```bash { output_lines = "2" }
 ./install/x64/vc17/bin/opencv_version.exe
 4.10.0
 ```
 
 {{% notice Note %}}
-The genereated directory name contains "x64," but there is no need to worry as the libraries and executable files will definitely run as ARM64.
+The generated directory name contains "x64," but there is no need to worry as the libraries and executable files will definitely run as AArch64.
 {{% /notice %}}
 
 &nbsp;
@@ -169,23 +169,23 @@ Once the OpenCV library has been successfully created, the next step is to link
 
 First, create a new project in Visual Studio. 
 
-Launch Visual Studio, click `Create a new project` on the initial screen, then select `Empty Project` and click `Next`. 
+Launch Visual Studio, click **Create a new project** on the initial screen, then select **Empty Project**, and click **Next**. 
 
-On the next screen, set the `Project name` and `Location`. You can choose any name and location, but for this example, name the project `TestOpenCV`, as shown below. 
+On the next screen, set the **Project name** and **Location**. You can choose any name and location, but for this example, name the project `TestOpenCV`, as shown below. 
 
-Click `Create` to generate the new project.
+Click **Create** to generate the new project.
 
 ![MSVC project #center](msvc_project.png "Create a new project")
 
 ### Add source code
 
- In `Solution Explorer`, right-click the `Source Files` folder, select `Add`, and then `New Item...`. Create a file named `test_opencv.cpp`.
+ In **Solution Explorer**, right-click the **Source Files** folder, select **Add**, and then **New Item...**. Create a file named `test_opencv.cpp`.
 
 ![MSVC add file #center](msvc_add_file.png "Add a source file")
 
 &nbsp;
 
-Once the file is created, it will open in the editor. 
+Once the file is created, it opens in the editor. 
 
 Copy and paste the following program into it and save the file.
 
@@ -205,17 +205,25 @@ int main() {
 }
 ```
 
-This program is a simple example that uses OpenCV to create a 100x100 black image, draw a blue circle on it, and save it as a file.
+This program is a simple example that uses OpenCV to do the following:
+
+* Create a 100x100 black image.
+* Draw a blue circle on it.
+* Save it as a file.
 
 ### Configure build settings
 
-Next, select the `Configuration` dropdown menu in the center of the screen and change it from `Debug` to `Release`. At this stage, your screen should look like the example shown below.
+Next, select the **Configuration** drop-down menu in the center of the screen, and change it from **Debug** to **Release**. At this stage, your screen should look like the example shown below.
 
 ![MSVC screenshot #center](msvc_screen.png "MSVC screenshot")
 
 &nbsp;
 
-Now, set up the compile and link settings. Select `Project` from the top menu and click on `TestOpenCV properties`. Edit `Include directories`, `Library directories`, and `Additional dependencies` as shown in the images below, and then click OK.
+Now, set up the compile and link settings. 
+
+Select **Project** from the top menu and click on **TestOpenCV properties**. 
+
+Edit **Include directories**, **Library directories**, and **Additional dependencies** as shown in the images below, and then click **OK**.
 
 ![MSVC include dir #center](msvc_include_dir.png "Include directories: Specify the directory containing the OpenCV header files.")
 
@@ -237,7 +245,7 @@ Finally, ensure that the directory containing the dynamic libraries (DLLs) is ad
 
 You are now ready to build the application. 
 
-From the top menu, select `Debug` and click `Start Without Debugging` or press `Ctrl` + `F5`.
+From the top menu, select **Debug** and click **Start Without Debugging** or press Ctrl+F5.
 
 If a console window appears showing that the program exited with code 0 and `test_image.png` is generated in the top-level directory of your Visual Studio project, you have succeeded. 
 
diff --git a/content/learning-paths/laptops-and-desktops/win-opencv/2-2-build-clang.md b/content/learning-paths/laptops-and-desktops/win-opencv/2-2-build-clang.md
@@ -162,7 +162,7 @@ Once the library files are correctly generated, run the following command to ens
 
 Once the OpenCV library has been successfully created, you can create a simple application and try using it.
 
-### Prepare a application program
+### Prepare an application program
 
 First, use a text editor to save the following C++ program as `test_opencv.cpp` in the `build_clang` directory.
 
@@ -216,7 +216,7 @@ Run the test program:
 .\test_opencv.exe
 ```
 
-When you execute the command, it will finish quickly, and `test_image.png` is generated. If you don't have the DLL directory in your search path, the program appears to run, but no `test_image.png` is generated. 
+When you execute the command, it will finish quickly, and `test_image.png` is generated. If you do not have the DLL directory in your search path, the program appears to run, but no `test_image.png` is generated. 
 
 Open the image file, it should look like the example shown below.
 
diff --git a/content/learning-paths/laptops-and-desktops/win-opencv/_index.md b/content/learning-paths/laptops-and-desktops/win-opencv/_index.md
@@ -1,18 +1,16 @@
 ---
-title: Build OpenCV applications on Windows on Arm
-draft: true
-cascade:
-    draft: true
+title: Create OpenCV applications on Windows on Arm
+
 minutes_to_complete: 90
 
-who_is_this_for: This is an advanced topic for software developers who want to use OpenCV with Windows on Arm devices.
+who_is_this_for: This is an advanced topic for software developers who want to build and develop applications on Windows on Arm devices using OpenCV.
 
 learning_objectives: 
     - Build the OpenCV library for Windows on Arm devices.
     - Develop applications using OpenCV.
 
 prerequisites:
-    - A Windows on Arm computer such as Lenovo Thinkpad X13s or an [Azure virtual machine](/learning-paths/cross-platform/woa_azure/).
+    - A Windows on Arm machine such as the Lenovo Thinkpad X13s, or an [Azure virtual machine](/learning-paths/cross-platform/woa_azure/).
 
 author_primary: Koki Mitsunami
 
