Review comments resolved

Author: sahehb

mevislab.github.io/content/tutorials/image_processing/cpp_1.md

@@ -1,5 +1,5 @@
 ---
-title: "Example 1: Creating a New ML Module for Adding Values"
+title: "Example 1: Creating a New ML Module for Adding a Value to Each Voxel"
 date: 2026-03-15T08:56:33+02:00
 status: "OK"
 draft: false
@@ -8,36 +8,36 @@ tags: ["Advanced", "Tutorial", "Image Processing", "C++"]
 menu: 
   main:
     identifier: "cpp1"
-    title: "Example 1: Creating a New ML Module for Adding Values"
+    title: "Example 1: Creating a New ML Module for Adding a Value to Each Voxel"
     weight: 602
     parent: "cpp"
 ---
 
-# Example 1: Creating a New ML Module for Adding Values
+# Example 1: Creating a New ML Module for Adding a Value to Each Voxel
 
 ## Precondition
 Make sure to have [cmake](https://cmake.org/download) installed. This example has been created using CMake Legacy Release (3.31.11).
 
 ## Introduction
-In this example, we develop our own C++ ML module which adds a constant value to each voxel of the given input image.
+In this example, we develop our own C++ ML module, which adds a constant value to each voxel of the given input image.
 
 ## Steps to Do
 ### Create a new ML Module
 Before creating the module, make sure to have your own user package available. See [Package creation](tutorials/basicmechanisms/macromodules/package/) for details about Packages.
 
-Use the *Project Wizard* via menu entry {{< menuitem "File" "Run Project Wizard ..." >}} to create a new ML module. Select *ML Module* and click *Run Wizard*.
+Use the *Project Wizard* via the menu entry {{< menuitem "File" "Run Project Wizard ..." >}} to create a new ML module. Select *ML Module* and click *Run Wizard*.
 
 ![ML Module Project Wizard](images/tutorials/image_processing/cpp/cpp1_1.png "ML Module Project Wizard")
 
 Enter properties of your new module and give your module the name `SimpleAdd`. Make sure to select your user package and name your project *SimpleAdd*.
 
 ![ML Module Properties](images/tutorials/image_processing/cpp/cpp1_2.png "ML Module Properties")
 
- Click *Next*. The next screen of the wizard allows you to define the inputs and outputs of your module. Select *Module Type* as *New style ML Module*, make sure to have one in- and one output and leave the rest of the settings unchanged. 
+ Click *Next*. The next screen of the Wizard allows you to define the inputs and outputs of your module. Select *Module Type* as *New style ML Module*, make sure to have one input and one output and leave the rest of the settings unchanged. 
 
 ![ML Module Properties](images/tutorials/image_processing/cpp/cpp1_3.png "ML Module Properties")
 
-Click *Next*. On the next screen, we can define some additional properties of our module. Select *Add activateAttachments()*, unselect *Acc configuration hints* and select *Add MDL window with fields*.
+Click *Next*. On the next screen, we can define some additional properties of our module. Select *Add activateAttachments()*, unselect *Add configuration hints* and select *Add MDL window with fields*.
 
 ![ML Module Additional Properties](images/tutorials/image_processing/cpp/cpp1_4.png "ML Module Additional Properties")
 
@@ -49,7 +49,7 @@ Click *Next*. The Module Field Interface allows you to define additional fields
 
 ![ML Module Field Interface](images/tutorials/image_processing/cpp/cpp1_5.png "ML Module Field Interface")
 
-Click *Create*. You see a screen showing the results of the module creation process. In case the Wizard finished succesfully, you can close the window. Additionally an explorer window opens showing the created folder containing your sources and the *CMakeLists.txt*.
+Click *Create*. You see a screen showing the results of the module creation process. In the case the Wizard finished succesfully, you can close the window. Additionally, an explorer window opens showing the created folder containing your sources and the *CMakeLists.txt*.
 
 The foundation of the module has been created with the Wizard. From here on, the programming starts.
 
@@ -62,13 +62,13 @@ Just make sure that the MLAB_ROOT environment variable is set on your system and
 
 Open a commandline and change to your current module directory (the directory containing your *CMakeLists.txt* file). Enter **cmake . -G "Visual Studio 17"**. After execution, a lot of files are generated by CMake. 
 
-For further documentation about our use of CMake see: [CMake for MeVisLab - Documentation](https://mevislabdownloads.mevis.de/docs/current/MeVisLab/Resources/Documentation/Publish/SDK/CMakeManual/#mainBook).
+For further documentation about our use of CMake, see: [CMake for MeVisLab - Documentation](https://mevislabdownloads.mevis.de/docs/current/MeVisLab/Resources/Documentation/Publish/SDK/CMakeManual/#mainBook).
 
 ### Programming the Functions of the ML Module
-Open the file *ALL_BUILD.vcxproj* in your preferred C++ development environment. Select the file  *mlSimpleAdd.cpp*.
+Open the file *ALL_BUILD.vcxproj* in your preferred C++ development environment. Select the file *mlSimpleAdd.cpp*.
 
 {{<alert class="info" caption="Note">}}
-In the following code examples, the comment lines already available in the created .cpp file are added for better overview.
+In the following code examples, the comment lines already available in the created *.cpp* file are added for better overview.
 {{</alert>}}
 
 #### Implementing *calculateOutputImageProperties*
@@ -92,14 +92,14 @@ void SimpleAdd::calculateOutputImageProperties(int /*outputIndex*/, PagedImage*
 
   // Change properties of output image outputImage here whose
   // defaults are inherited from the input image 0 (if there is one).
-  // get the constant add value
+  // Get the constant add value.
   const MLdouble constantValue = _constantValueFld->getDoubleValue();
 
-  // get input image's min and max values
+  // Get the input image's minimum and maximum values.
   const MLdouble inMinValue = getInputImage(0)->getMinVoxelValue();
   const MLdouble inMaxValue = getInputImage(0)->getMaxVoxelValue();
 
-  // set the output image's min and max values
+  // Set the output image's minimum and maximum values.
   outputImage->setMinVoxelValue(inMinValue + constantValue);
   outputImage->setMaxVoxelValue(inMaxValue + constantValue);
 
@@ -111,7 +111,7 @@ void SimpleAdd::calculateOutputImageProperties(int /*outputIndex*/, PagedImage*
 {{</highlight>}}
 
 {{<alert class="info" caption="Note">}}
-*outputIndex* is the index number of the output connector. It is commented out in this example, because we only defined one output. In case of more than one outputs, uncomment this parameter.
+*outputIndex* is the index number of the output connector. It is commented out in this example, because we only defined one output. In the case of more than one outputs, uncomment this parameter.
 {{</alert>}}
 
 #### Implementing *typedCalculateOutputSubImage*
@@ -124,7 +124,7 @@ Next, we are going to finally change the voxel values of the image. Open the fil
 ```
 {{</highlight>}}
 
-Then change the inner line of the loop, so that the constant value is added to the value of the input voxel:
+Then, change the inner line of the loop, so that the constant value is added to the value of the input voxel:
 
 {{< highlight filename="mlSimpleAddOutputImageHandler.cpp" >}}
 ```c++
@@ -136,20 +136,20 @@ Then change the inner line of the loop, so that the constant value is added to t
 ```
 {{</highlight>}}
 
-Compile the project (this includes all module files) in the development environment. Make sure to select a *Release* build.
+Compile the project in the development environment. Make sure to select a *Release* build.
 
-### Use your module in MeVisLab
-Your compiled *.dll is available in your project directory under *Sources/lib*. In order to use it in MeVisLab, it needs to be copied to the *lib* folder of your user package.
+### Use Your Module in MeVisLab
+Your compiled **.dll* is available in your project directory under *Sources/lib*. In order to use it in MeVisLab, it needs to be copied to the *lib* folder of your user package.
 
 You can either do this manually or via PostBuild step.
 
-In case MeVisLab was running during development, restart MeVisLab and use your new module.
+In the case MeVisLab was running during development, restart MeVisLab and use your new module.
 
 For testing purposes, you can use a `LocalImage` module and two `View2D` modules. Connect the `SimpleAdd` module to the second `View2D` and change the <field>Constant Value</field> field.
 
 ![Testing Network](images/tutorials/image_processing/cpp/cpp1_6.png "Testing Network")
 
-The output image of the module `SimpleAdd` is automatically re-calculated on changing the field <field>Constant Value</field>. This is already implemented in the generated code of the file below:
+The output image of the module `SimpleAdd` is automatically recalculated on changing the field <field>Constant Value</field>. This is already implemented in the generated code of the file below:
 
 {{< highlight filename="mlSimpleAdd.cpp" >}}
 ```c++
@@ -177,5 +177,5 @@ The output image of the module `SimpleAdd` is automatically re-calculated on cha
 
 ## Summary
 * MeVisLab allows to develop your own C++ modules.
-* The Project Wizard already generates all necessary *.cpp and *.h files and a loop through all voxels of the input image.
-* Changes of user defined fields automatically lead to a recalculation of the input image.
+* The Project Wizard already generates all necessary \**.cpp* and \**.h* files and a loop through all voxels of the input image.
+* Changes of user-defined fields automatically lead to a recalculation of the input image.

mevislab.github.io/content/tutorials/image_processing/cpp_development.md

@@ -1,5 +1,5 @@
 ---
-title: "Developing your own C++ Modules"
+title: "Developing Your Own C++ Modules"
 date: 2026-03-15T08:56:33+02:00
 status: "OK"
 draft: false
@@ -8,32 +8,32 @@ tags: ["Advanced", "Tutorial", "Image Processing", "C++"]
 menu: 
   main:
     identifier: "cpp"
-    title: "Developing your own C++ Modules"
+    title: "Developing Your Own C++ Modules"
     weight: 601
     parent: "imageprocessing"
 ---
 
-# C++ Module development
+# C++ Module Development
 ## Introduction
-The development of your own C++ modules can be done by ML modules and by Inventor modules.
+The development of your own C++ modules can be done by ML modules and by Open Inventor modules.
 
 {{<alert class="info" caption="Important Information">}}
 Make sure to use a compiler that is compatible to your currently installed MeVisLab version.
 {{</alert>}}
 
-### ML modules on the C++ level
+### ML Modules on the C++ Level
 * Image processing modules are objects derived from class Module defined in the ML library and therefore are also called ML modules.
 * Image inputs and outputs are connectors to objects of class PagedImage, which are defined in the ML library.
 * Inputs and outputs for abstract data structures are connectors to pointers of objects derived from class Base and are called Base objects.
 
-### Inventor modules on the C++-level:
-* Most Inventor modules are objects derived from class SoNode defined in the Open Inventor library.
-* Inventor inputs and outputs are connectors to objects derived from class SoNode defined in the Open Inventor library. Many Inventor modules will return themselves as outputs (“self”). On inputs, they may have connectors to child Inventor modules.
-* Some Inventor modules are objects derived from class SoEngine. They are used for calculations and return their output not via output connectors but via fields.
-* Inventor modules may also have input and output connectors to Base objects and Image objects.
-* All standard Inventor nodes defined in the Open Inventor library are available in MeVisLab as Inventor modules.
+### Open Inventor Modules on the C++ Level
+* Most Open Inventor modules are objects derived from class SoNode defined in the Open Inventor library.
+* Open Inventor inputs and outputs are connectors to objects derived from class SoNode defined in the Open Inventor library. Many Open Inventor modules will return themselves as outputs (“self”). On inputs, they may have connectors to child Open Inventor modules.
+* Some Open Inventor modules are objects derived from class SoEngine. They are used for calculations and return their output not via output connectors but via fields.
+* Open Inventor modules may also have input and output connectors to Base objects and Image objects.
+* All standard Open Inventor nodes defined in the Open Inventor library are available in MeVisLab as Open Inventor modules.
 
-This chapter describes some examples for developing your own ML and Inventor modules.
+This chapter describes some examples for developing your own ML and Open Inventor modules.
 
 ## Some Tips for Module Design
 ### Macro Modules or C++ Modules?
@@ -46,23 +46,20 @@ In [Example 2: Macro Modules](tutorials/basicmechanisms/macromodules/), we alrea
   * scripting possible on the module or network level
   * scripting supported by the Scripting Assistant View (basically a recorder for actions performed on the network)
 
-**Disadvantages:**
-* With macros, only existing functionalities and algorithms can be used.
-
 **Conclusion:**
 * For rapid prototyping based on existing image processing algorithms, use macros.
 * For implementing new image processing, write new ML or Open Inventor modules.
 
 ### Combining Functionalities
 It is possible to have ML and Open Inventor connectors in the same module. Two cases are possible:
 * Type 1: **ML -> visualization:** Image data or properties are displayed by a visualization module. Usually a <field>SoSFXVImage</field> field gets random access to an ML image by *getTile()*. Examples: `SoView2D`, `GlobalStatistics`.
-* Type 2: **visualization -> ML:** Modules generate an ML image from an Inventor scene. Examples: `VoxelizeInventorScene`, `SoExaminerViewer` (hidden functionality).
+* Type 2: **visualization -> ML:** Modules generate an ML image from an Open Inventor scene. Examples: `VoxelizeInventorScene`, `SoExaminerViewer` (hidden functionality).
 
 Generally, however, it is not always a good solution to combine that, as the processes of image processing and image visualization are usually separated.
 
 Therefore, rather separate the ML and Open Inventor functionalities into two modules. This way,
 * functionality is encapsulated and can be reused as module
 * modules for the single steps may already be available in MeVisLab and spare you a new development
 
-## Code examples
-In addition to the tutorials in this chapter, you can find additional code examples in your MeVisLab installation directory.
+## Code Examples
+In addition to the tutorials in this chapter, you can find additional code examples in your MeVisLab installation directory.