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==Namespace==
== Wrapping OpenCV ==


===Emgu===
===Function Mapping - Emgu.CV.CvInvoke ===
All libraries implemented by Emgu® will be put under the namespace of Emgu.
The CvInvoke class provides a way to directly invoke [[OpenCV]] function within .NET languages. Each method in this class corresponds to a function in [[OpenCV]] of the same name. For example, a call to
<source lang="csharp">
IntPtr image = CvInvoke.cvCreateImage(new System.Drawing.Size(400, 300), CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);  
</source> is equivalent to the following function call in C 
<source lang="c">
IplImage* image = cvCreateImage(cvSize(400, 300), IPL_DEPTH_8U, 1);
</source>
Both of which create a 400x300 of 8-bit unsigned grayscale image.


===Emgu.CV===
===Structure Mapping - Emgu.CV.Structure.M''xxx'' ===
The Emgu.CV namespace implement wrapper functions for OpenCV. To use this namespace in your code, it is recommended to include
This type of structure is a direct mapping to [[OpenCV]] structures.
<source lang="csharp">
{| style="text-align:center" border="1px" cellspacing="0" cellpadding="5"
using Emgu.CV;
![[Emgu CV]] Structure || [[OpenCV]] structure
</source>
|-
in the begining of your C# code.
| Emgu.CV.Structure.MIplImage || IplImage
|-
| Emgu.CV.Structure.MCvMat || CvMat
|-
| ... || ...
|-
| Emgu.CV.Structure.M''xxxx'' || ''xxxx''
|}
 
The prefix ''M'' here stands for Managed structure.
 
[[Emgu CV]] also borrows some existing structures in .Net to represent structures in [[OpenCV]]:


====Function Mapping - Emgu.CV.CvInvoke ====
{| style="text-align:center" border="1px" cellspacing="0" cellpadding="5"
The CvInvoke class provides a way to directly invoke opencv function within .NET languages. Each method in this class corresponds to the same function in opencv. For example, a call to
!.Net Structure || [[OpenCV]] structure
<source lang="csharp">
|-
CvInvoke.cvCreateImage(new MCvSize(400, 300), CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
| System.Drawing.Point || CvPoint
</source> is equivalent to calling the function in opencv
|-
<source lang="c">
| System.Drawing.PointF || CvPoint2D32f
cvCreateImage(cvSize(400, 300), IPL_DEPTH_8U, 1);
|-
</source>Both of which create a 400x300 single-channel image of 8-bit depth.
| System.Drawing.Size || CvSize
|-
| System.Drawing.Rectangle || CvRect
|}


====Enumeration Mapping - Emgu.CV.CvEnum ====
===Enumeration Mapping - Emgu.CV.CvEnum ===
The CvEnum namespace provides direct mapping to opencv enumerations. For example, <code> CvEnum.IPL_DEPTH.IPL_DEPTH_8U </code> is equivalent to the value in opencv <code> IPL_DEPTH_8U </code>. Both of which has the value of <code>8</code>.
The CvEnum namespace provides direct mapping to [[OpenCV]] enumerations. For example, <code> CvEnum.IPL_DEPTH.IPL_DEPTH_8U </code> has the same value as <code> IPL_DEPTH_8U </code> in [[OpenCV]]; both of which equals <code>8</code>.


====Structure Mapping - Emgu.CV.M''xxx'' ====
==Managed classes==
This type of structure is a direct mapping to opencv structures. For example
===[[Working with Images]]===
*<code> MIplImage </code> is equivalent to <code> IplImage </code> structure in OpenCV
===[[Working with Matrices]]===
*<code> MCvSize</code> is equivalent to <code>CvSize</code> structure
*<code> M''xxxx'' </code> is equivalent to <code>''xxxx''</code> structure


==Working with images==
==Error Handling==
===Creating Image===
[[Emgu CV]] register a custom error handler in [[OpenCV]]. When error is encountered from [[OpenCV]], a <code>CvException</code> will be thrown.
Although it is possible to create image by calling <code>CvInvoke.cvCreateImage</code>, we suggest using the generic class Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> for image creation. There are serveral advantage of using the Managed Image<Color, Depth> class, among those are
* Memory is automatically released when the garbage collector dispose the Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> Object
* Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> class contains advanced method that is not available on OpenCV, for example, generic operation


To create an 480x320 image with Bgr color and 8-bit unsigned value, in C# you can call
==Code Documentation==
<source lang="csharp">
===Xml Documentation===
Image<Bgr, Byte> img1 = new Image<Bgr, Byte>(480, 320);
Documentation is embedded in the code using xml format, which can then be compiled as HTML documentation using [http://www.codeplex.com/Sandcastle Sandcastle]. You can browse our [[Documentation | Online Documentation]] for the latest stable and development code.
</source>
 
Note that the image initialized this way contains random pixel values, if you wants to specify the background value of the image, let's say in Blue, in C# you write
===Method Documentation===
<source lang="csharp">
A library of coding examples according to the methods is being formed here: [http://www.emgu.com/wiki/index.php/Code_Reference Online Code Reference].
Image<Bgr, Byte> img1 = new Image<Bgr, Byte>(480, 320, new Bgr(255, 0, 0));
</source>
Creating image from file is also simple, in C# just call
<source lang="csharp">
Image<Bgr, Byte> img1 = new Image<Bgr, Byte>("MyImage.jpg");
</source>
assuming the image file is call "MyImage.jpg"


====Image Color====
===Intellisense in Visual Studio===
The first generic parameter of the Image class specific the color of the image type, for example <code>Image<Gray, ...> img1; </code> tells that <code>img1</code> is a single channel gray color image.
If you are using Visual Studio as your development tools, you will have intellisense support when developing [[Emgu CV]] applications. For example, if you want to create an image directly using cvCreateImage function, which is wrapped by the CvInvoke Class, just type <code>CvInvoke.</code>
Color Types supported in Emgu CV includes:
* Gray
* Bgr (Blue Green Red)
* Hsv (Hue Satuation Value)
* Hls (Hue Lightness Satuation)
* Lab (CIE L*a*b*)
* Luv (CIE L*u*v*)
* Xyz (CIE XYZ.Rec 709 with D65 white point)
* Ycc (YCrCb JPEG)


====Image Depth====
[[image:EmguCvIntellisenseCreateImage1.GIF]]
Image Depth is specified using the second generic parameter <code>Depth</code>
Available Color Depths are:
* Byte
* Single (float)


===Methods===
and a list of functions belonging to <code>CvInvoke</code> class is displayed along with a description for each of the functions. Since you are creating an image, select the <code> cvCreateImage </code> function
====Naming Convention====
* Method <code>XYZ</code> in Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> class corresponse to the OpenCV function <code>cvXYZ</code>. For example, Image< [[#Image Color |Color]], [[#Image Depth |Depth]]>.Not() function corresponse to <code> cvNot </code> function with the resulting image being returned.
* Method <code>_XYZ</code> is usually the same as Method <code>XYZ</code> except that the operation is performed inplace rather than returning a value. For example, Image< [[#Image Color |Color]], [[#Image Depth |Depth]]>._Not() function performs the bitwise inversion inplace.


===Generic Operation===
[[image:EmguCvIntellisenseCreateImage2.GIF]]
One of the advantage of using Emgu CV is the ability to perform generic operations.


It's best if I demostrate this using with example. Suppose we have an gray scale image of bytes
The list of parameters for this function will be displayed as well as a description for each of the parameters.
<source lang="csharp">
Image<Gray, Byte> img1 = new Image<Gray, Byte>(400, 300, new Gray(30));
</source>
To invert all the pixels in this image we can call the function using plain old CvInvoke
<source lang="csharp">
Image<Gray, Byte> img2 = img1.Not();
</source>
As an alternative, we can also use the generic method <code> Convert </code> available from the Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> class
<source lang="csharp">
Image<Gray, Byte> img3 = img1.Convert<Byte>( delegate(Byte b) { return (Byte) (255-b); } );
</source>
The resulting image <code>img2</code> and <code>img3</code> contains the same value for each pixel.  


At first glance it wouldn't seems to be a big gain when using generic operations. In fact, since opencv already has an implementation of the Not function and performance-wise it is better than the generic version of the equailent <code>Convert</code> function call. However, there comes to cases when generic functions provides the flexibility with minor performance cost. 
==Examples==
<b>[http://www.emgu.com/wiki/index.php/Code_Reference Online Code Reference]</b>


Let's say you have an <code>Image<Gray, Byte> img1</code> with pixels set. and you wants to create a single channel float point image of the same size, when each pixel of the new image, corresponse to the old image, can be describe in the following delegate
===C#===
<source lang="csharp">
====Image Processing Examples ====
delegate(Byte b) { return (Single) Math.cos( b * b / 255.0); }
<b>Introductions</b>
</source>
* [[Hello World in CSharp|Hello World for Windows]]
This operation can be completed as follows in Emgu CV
* [[Hello World for Ubuntu|Hello World for Ubuntu]]
<source lang="csharp">
* [[Setting_up_EMGU_C_Sharp| User Guide to EMGU and Accessing Image Data]]
Image<Gray, Single> img4 = img1.Convert<Single>( delegate(Byte b) { return (Single) Math.cos( b * b / 255.0); }  );
* [[Camera Capture in a few lines of code]]
</source>
<b>Intermediate</b>
Which is simple and meaningfull. This operation in OpenCV is hard to perform since equivalent function such as <code>Math.cos</code> is not available.
* [[Shape (Triangle, Rectangle, Circle, Line) Detection in CSharp | Shape (Triangle, Rectangle, Circle, Line) Detection]]
* [[SURF feature detector in CSharp|SURF Feature Detector]]
* [[FAST feature detector in CSharp|FAST Feature Detector]]
* [[WPF in CSharp|Windows Presentation Foundation (WPF)]]
* [[Face detection| Face detection in Csharp]]
* [[Pedestrian Detection in CSharp | Pedestrian Detection, Histogram of oriented gradients (HOG)]]
* [[Traffic Sign Detection in CSharp|Traffic Sign Detection]]
* [[License Plate Recognition in CSharp|License Plate Recognition (LPR), Optical Character Recognition (OCR)]]
* [[Image Stitching in CSharp| Image Stitching]]
* [[Kalman_Filter| Using the Kalman Filter]]
* [[Asp.Net Core on Ubuntu| Asp.Net Core project on Ubuntu]]


===Drawing Objects on Image===
====Computational Geometry Examples ====
The <code> Draw( )</code> method in Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> can be used to draw different types of objects, including fonts, lines, circles, rectangles, boxes, ellipses as well as contours. Use the documentation and intellisense as a guideline to discover the many functionality of the <code> Draw </code> function.
* [[Planar Subdivision in CSharp|Delaunay's Triangulation and Voronoi Diagram]]
* [[Convex Hull in CSharp| Convex Hull]]
* [[Ellipse Fitting in CSharp | Ellipse Fitting]]
* [[Minimum Area Rectangle in CSharp | Minimum Area Rectangle]]
* [[Minimum Enclosing Circle in CSharp | Minimum Enclosing Circle]]


===Color and Depth Conversion===
====Machine Learning Examples ====
Converting an Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> between different colors and depths are simple. For example, if you have <code> Image<Bgr, Byte> img1 </code> and you wants to convert it to a Grayscale image of Single, all you need to do is
* [[Normal Bayes Classifier in CSharp | Normal Bayes Classifier ]]
<source lang="csharp">
* [[K Nearest Neighbors in CSharp | K Nearest Neighbors ]]
Image<Gray, Single> img2 = img1.Convert<Gray, Single>();
* [[SVM (Support Vector Machine) in CSharp | Support Vector Machine (SVM) - thanks to Albert G.]]
</source>
* [[Expectation-Maximization in CSharp | Expectation-Maximization (EM)]]
There is no need to worry about the color convertion code as it is handled by the Emgu CV library.
* [[ANN MLP (Neural Network) in CSharp | Neural Network (ANN MLP) ]]
* [[Mushroom Poisonous Prediction (Decision Tree) in CSharp | Mushroom Poisonous Prediction (Decision Tree) ]]


===XML serialization===
==== Video Codec ====
One of the future of Emgu CV is that Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> can be XML serializated. You might ask why we need to serialization an Image. The answer is simple, we wants to use it in a web service!
* [[H264 Codec | VideoWriter with H264 codec]]


Since the Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> class implements ISerializable, when you work in WCF (Windows Communication Fundation), you are free to use Image< [[#Image Color |Color]], [[#Image Depth |Depth]]> type as parameters or return value of a web service.  
===C++===
* [[Hello World in C++|Hello World]]
===IronPython===
* [[Setting up Emgu CV and IronPython]]
* [[Face Detection from IronPython]]
===VB.NET===
* [[Face Detection in VB.NET]]
* [[Hello World in VB.NET]]


This will be ideal, for example, if you are building a cluster of computers to recongnize different groups of object and have a center computer to coordinate the tasks. I will also be useful if your wants to implement remote monitoring software that constainly query image from a remote server, which use the <code>Capture</code> class in Emgu CV to capture images from camera.
===Unity===
* [[Working with Vuforia]]


==Code Documentation==
== Upgrading from Emgu CV 2.x to 3.x ==
===Xml Documentation===
Documentation is emmbedded in the code using xml format, which can then be compiled as HTML documentation using Sandcastle.
===Intellisense in Visual Studio===
If you are using Visual Studio as your development tools, you will have intellisense support when developping Emgu CV applications. For example, if you wants to create an image directly using cvCreateImage function, which is wrapped by the CvInvoke Class, just type <code>CvInvoke.</code>


[[image:EmguCvIntellisenseCreateImage1.GIF]]
===Function Mapping - Emgu.CV.CvInvoke ===


and a list of functions belongs to <code>CvInvoke</code> class is displayed along with a description for each of the function. Since you are creating an image, select the <code> cvCreateImage </code> function
In Emgu CV v2.x, CvInvoke function calls use the C interface. In v3.x, we have migrate away from the opencv c interface to opencv C++ interface, so does the function names.


[[image:EmguCvIntellisenseCreateImage2.GIF]]
For example, in v2.x, the function <pre>CvInvoke.cvAnd(IntPtr src1, IntPtr src2, IntPtr dst, Intptr mask)</pre> has been replaced by <pre>CvInvoke.BitwiseAnd(IInputArray src1, IInputArray src2, IOutputArray dst, IInputArray mask)</pre>


The list of parameters for this function will be displayed as well as a description for each of the parameters.
The best way to find out the new function names if you are migrating from version 2.x is through the Open CV documentation:


==Examples==
http://docs.opencv.org/trunk/
===Hello, World===
We will start by the Hello World sample, written in C#


<source lang="csharp">String win1 = "Test Window"; //The name of the window
You can search for the C function name and the search result should have the C++ function name right next to the C interface.


//Create the window using the specific name
=== IInputArray, IOutputArray ===
CvInvoke.cvNamedWindow(win1);


//Create an image of 400x200 of Blue color
<code>IInputArray</code> has been introduced in version 3.0. You can find that many of our new interfaces accepts <code>IInputArray</code> and <code>IOutputArray</code>. They can be any one of the following:
using (Image<Bgr, Byte> img = new Image<Bgr, byte>(400, 200, new Bgr(255, 0, 0)))
*A CvArray, which is the base class of Matrix and Image<,>
using (Font f = new Font(CvEnum.FONT.CV_FONT_HERSHEY_COMPLEX, 1.0, 1.0)) //Create the font
*A Mat, which is the Open CV equivalent of cv::Mat
{
*A UMat, which is the Open CV equivalent of cv::UMat
  //Draw "Hello, world." on the image using the specific font
*A ScalarArray, which can be used to convert a scalar to an IInputArray
  img.Draw("Hello, world", f, new Point2D<int>(10, 80), new Bgr(0, 255, 0));
*VectorOf{XXX}, this is the interface for the C++ standard vector


  CvInvoke.cvShowImage(win1, img.Ptr); //Show the image
=== T-API ===
'''T-API is THE MOST AWESOME FUTURE in 3.0 release !!!'''


  CvInvoke.cvWaitKey(0);  //Wait for the key pressing event
Let me explain why:


  CvInvoke.cvDestroyWindow(win1); //Destory the window
For a simple image operation, suppose we have an image in memory and we wants to perform an invert operation. In Emgu CV 2.x, we can write the code as follows:
}
<pre>
</source>
Image<Gray, Byte> image = ... //load the image from some where
Image<Gray, Byte> imageInvert = new Image<Gray, Byte>(image.Width, image.Height);
CvInvoke.cvNot(image, imageInvert);
</pre>
In Emgu CV 3.x, we can still use the Image<Gray, Byte> class to perform the same operation, with a slight change in the CvInvoke function name
<pre>
Image<Gray, Byte> image = ... //load the image from some where
Image<Gray, Byte> imageInvert = new Image<Gray, Byte>(image.Width, image.Height);
CvInvoke.BitwiseNot(image, imageInvert);
</pre>
To realize the true potential with T-API, let's try to use UMat to perform the same operation
<pre>
UMat image = ... //load the image from some where
UMat imageInvert = new UMat();
CvInvoke.BitwiseNot(image, imageInvert);
</pre>
It all seems to be not much different from the code that use the Image<,> class in 3.0. However, the above code can automatically use OpenCL engine to perform the operation if a suitable OpenCL device is found. That means it will run many times faster on a system with a discrete GPU (Nvidia, AMD, Intel Iris Pro etc). On systems that do not have a OpenCL devices, the code will be run on CPU and have the same performance as if we are passing the Image<,> or Mat objects to the CvInvoke function.


The above code will create an image of 400x200 with blue background color and the String "Hello, world" in green on the forground. The image will be displayed a window named "Test Window".
In short, T-API enable developer to automatically use the OpenCL devices (GPU) for computing and automatically fall back to CPU in the absent of OpenCL devices. You can also turn the OpenCL engine off by simply setting
<pre>
CvInvoke.UseOpenCL = false
</pre>
In which case all the code will be run on CPU instead.


[[image:HelloWorldExample.GIF]]
The T-API is the motivation for us to rewrite all our code using the OpenCV C++ interface to take advantage of this future. We believe it is well worth the effort once we see the results.

Latest revision as of 21:12, 10 January 2023

Wrapping OpenCV

Function Mapping - Emgu.CV.CvInvoke

The CvInvoke class provides a way to directly invoke OpenCV function within .NET languages. Each method in this class corresponds to a function in OpenCV of the same name. For example, a call to

 
 IntPtr image = CvInvoke.cvCreateImage(new System.Drawing.Size(400, 300), CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);

is equivalent to the following function call in C

 
 IplImage* image = cvCreateImage(cvSize(400, 300), IPL_DEPTH_8U, 1);

Both of which create a 400x300 of 8-bit unsigned grayscale image.

Structure Mapping - Emgu.CV.Structure.Mxxx

This type of structure is a direct mapping to OpenCV structures.

Emgu CV Structure OpenCV structure
Emgu.CV.Structure.MIplImage IplImage
Emgu.CV.Structure.MCvMat CvMat
... ...
Emgu.CV.Structure.Mxxxx xxxx

The prefix M here stands for Managed structure.

Emgu CV also borrows some existing structures in .Net to represent structures in OpenCV:

.Net Structure OpenCV structure
System.Drawing.Point CvPoint
System.Drawing.PointF CvPoint2D32f
System.Drawing.Size CvSize
System.Drawing.Rectangle CvRect

Enumeration Mapping - Emgu.CV.CvEnum

The CvEnum namespace provides direct mapping to OpenCV enumerations. For example, CvEnum.IPL_DEPTH.IPL_DEPTH_8U has the same value as IPL_DEPTH_8U in OpenCV; both of which equals 8.

Managed classes

Working with Images

Working with Matrices

Error Handling

Emgu CV register a custom error handler in OpenCV. When error is encountered from OpenCV, a CvException will be thrown.

Code Documentation

Xml Documentation

Documentation is embedded in the code using xml format, which can then be compiled as HTML documentation using Sandcastle. You can browse our Online Documentation for the latest stable and development code.

Method Documentation

A library of coding examples according to the methods is being formed here: Online Code Reference.

Intellisense in Visual Studio

If you are using Visual Studio as your development tools, you will have intellisense support when developing Emgu CV applications. For example, if you want to create an image directly using cvCreateImage function, which is wrapped by the CvInvoke Class, just type CvInvoke.

and a list of functions belonging to CvInvoke class is displayed along with a description for each of the functions. Since you are creating an image, select the cvCreateImage function

The list of parameters for this function will be displayed as well as a description for each of the parameters.

Examples

Online Code Reference

C#

Image Processing Examples

Introductions

Intermediate

Computational Geometry Examples

Machine Learning Examples

Video Codec

C++

IronPython

VB.NET

Unity

Upgrading from Emgu CV 2.x to 3.x

Function Mapping - Emgu.CV.CvInvoke

In Emgu CV v2.x, CvInvoke function calls use the C interface. In v3.x, we have migrate away from the opencv c interface to opencv C++ interface, so does the function names.

For example, in v2.x, the function

CvInvoke.cvAnd(IntPtr src1, IntPtr src2, IntPtr dst, Intptr mask)

has been replaced by

CvInvoke.BitwiseAnd(IInputArray src1, IInputArray src2, IOutputArray dst, IInputArray mask)

The best way to find out the new function names if you are migrating from version 2.x is through the Open CV documentation:

http://docs.opencv.org/trunk/

You can search for the C function name and the search result should have the C++ function name right next to the C interface.

IInputArray, IOutputArray

IInputArray has been introduced in version 3.0. You can find that many of our new interfaces accepts IInputArray and IOutputArray. They can be any one of the following:

  • A CvArray, which is the base class of Matrix and Image<,>
  • A Mat, which is the Open CV equivalent of cv::Mat
  • A UMat, which is the Open CV equivalent of cv::UMat
  • A ScalarArray, which can be used to convert a scalar to an IInputArray
  • VectorOf{XXX}, this is the interface for the C++ standard vector

T-API

T-API is THE MOST AWESOME FUTURE in 3.0 release !!!

Let me explain why:

For a simple image operation, suppose we have an image in memory and we wants to perform an invert operation. In Emgu CV 2.x, we can write the code as follows:

Image<Gray, Byte> image = ... //load the image from some where
Image<Gray, Byte> imageInvert = new Image<Gray, Byte>(image.Width, image.Height);
CvInvoke.cvNot(image, imageInvert);

In Emgu CV 3.x, we can still use the Image<Gray, Byte> class to perform the same operation, with a slight change in the CvInvoke function name

Image<Gray, Byte> image = ... //load the image from some where
Image<Gray, Byte> imageInvert = new Image<Gray, Byte>(image.Width, image.Height);
CvInvoke.BitwiseNot(image, imageInvert);

To realize the true potential with T-API, let's try to use UMat to perform the same operation

UMat image = ... //load the image from some where
UMat imageInvert = new UMat();
CvInvoke.BitwiseNot(image, imageInvert);

It all seems to be not much different from the code that use the Image<,> class in 3.0. However, the above code can automatically use OpenCL engine to perform the operation if a suitable OpenCL device is found. That means it will run many times faster on a system with a discrete GPU (Nvidia, AMD, Intel Iris Pro etc). On systems that do not have a OpenCL devices, the code will be run on CPU and have the same performance as if we are passing the Image<,> or Mat objects to the CvInvoke function.

In short, T-API enable developer to automatically use the OpenCL devices (GPU) for computing and automatically fall back to CPU in the absent of OpenCL devices. You can also turn the OpenCL engine off by simply setting

CvInvoke.UseOpenCL = false

In which case all the code will be run on CPU instead.

The T-API is the motivation for us to rewrite all our code using the OpenCV C++ interface to take advantage of this future. We believe it is well worth the effort once we see the results.