Documentation update.

Emgu.CV.Contrib/XImgproc/EdgeDrawing.cs

@@ -13,7 +13,9 @@ using Emgu.CV.Util;
 
 namespace Emgu.CV.XImgproc
 {
-    
+    /// <summary>
+    /// Class implementing the ED (EdgeDrawing)
+    /// </summary>
     public class EdgeDrawing : SharedPtrObject, IAlgorithm
     {
         private IntPtr _algorithm;
@@ -27,6 +29,9 @@ namespace Emgu.CV.XImgproc
         }
 
         
+        /// <summary>
+        /// Create a new Edge Drawing object using default parameters.
+        /// </summary>
         public EdgeDrawing()
 		{
             _ptr = XImgprocInvoke.cveEdgeDrawingCreate(ref _algorithm, ref _sharedPtr);
@@ -43,34 +48,54 @@ namespace Emgu.CV.XImgproc
             }
         }
 
+        /// <summary>
+        /// Detects edges and prepares them to detect lines and ellipses.
+        /// </summary>
+        /// <param name="src">Input image</param>
         public void DetectEdges(IInputArray src)
         {
             using (InputArray iaSrc = src.GetInputArray())
                 XImgprocInvoke.cveEdgeDrawingDetectEdges(_ptr, iaSrc);
         }
 
+        /// <summary>
+        /// Get the edge image
+        /// </summary>
+        /// <param name="dst">The output edge image</param>
         public void GetEdgeImage(IOutputArray dst)
         {
             using (OutputArray oaDst = dst.GetOutputArray())
                 XImgprocInvoke.cveEdgeDrawingGetEdgeImage(_ptr, oaDst);
         }
 
+        /// <summary>
+        /// Get the gradient image
+        /// </summary>
+        /// <param name="dst">The output gradient image</param>
         public void GetGradientImage(IOutputArray dst)
         {
             using (OutputArray oaDst = dst.GetOutputArray())
                 XImgprocInvoke.cveEdgeDrawingGetGradientImage(_ptr, oaDst);
         }
 
+        /// <summary>
+        /// Detects lines.
+        /// </summary>
+        /// <param name="dst">Output Vec&lt;4f&gt; contains start point and end point of detected lines.</param>
         public void DetectLines(IOutputArray dst)
         {
             using (OutputArray oaDst = dst.GetOutputArray())
-                XImgprocInvoke.cveEdgeDrawingGetGradientImage(_ptr, oaDst);
+                XImgprocInvoke.cveEdgeDrawingDetectLines(_ptr, oaDst);
         }
 
-        public void DetectDetectEllipses(IOutputArray dst)
+        /// <summary>
+        /// Detects circles and ellipses.
+        /// </summary>
+        /// <param name="dst">Output Vec&lt;6d&gt; contains center point and perimeter for circles.</param>
+        public void DetectEllipses(IOutputArray dst)
         {
             using (OutputArray oaDst = dst.GetOutputArray())
-                XImgprocInvoke.cveEdgeDrawingGetGradientImage(_ptr, oaDst);
+                XImgprocInvoke.cveEdgeDrawingDetectEllipses(_ptr, oaDst);
         }
     }
 

Emgu.CV.Cuda/CudaDeviceInfo.cs

@@ -263,7 +263,6 @@ namespace Emgu.CV.Cuda
         /// <summary>
         /// Print short cuda device info
         /// </summary>
-        /// <param name="device"></param>
         /// <param name="device">cuda device id</param>
         [DllImport(CvInvoke.ExternCudaLibrary, CallingConvention = CvInvoke.CvCallingConvention, EntryPoint = "cudaPrintShortCudaDeviceInfo")]
         public static extern void PrintShortCudaDeviceInfo(int device);

Emgu.CV.Cuda/Optflow/NvidiaOpticalFlow_1_0.cs

@@ -82,6 +82,13 @@ namespace Emgu.CV.Cuda
                 ref _sharedPtr);
         }
 
+        /// <summary>
+        /// The NVIDIA optical flow hardware generates flow vectors at granularity gridSize, which can be queried via function getGridSize(). Upsampler() helper function converts the hardware-generated flow vectors to dense representation (1 flow vector for each pixel) using nearest neighbour upsampling method.
+        /// </summary>
+        /// <param name="flow">Buffer of type CV_16FC2 containing flow vectors generated by calc().</param>
+        /// <param name="imageSize">Size of the input image in pixels for which these flow vectors were generated.</param>
+        /// <param name="gridSize">Granularity of the optical flow vectors returned by calc() function.</param>
+        /// <param name="upsampledFlow">Buffer of type CV_32FC2, containing upsampled flow vectors, each flow vector for 1 pixel, in the pitch-linear layout.</param>
         public void UpSampler(
             IInputArray flow,
             Size imageSize,

Emgu.CV.Models/CascadeFaceAndEyeDetector.cs

@@ -16,14 +16,24 @@ using Emgu.Util;
 
 namespace Emgu.CV.Models
 {
+    /// <summary>
+    /// Face and eye detector using HaarCascade.
+    /// </summary>
     public class CascadeFaceAndEyeDetector : DisposableObject, IProcessAndRenderModel
     {
         private CascadeClassifier _faceCascadeClassifier = null;
         private CascadeClassifier _eyeCascadeClassifier = null;
 
-        public static void Detect(
-           IInputArray image, CascadeClassifier face, CascadeClassifier eye,
-           List<Rectangle> faces, List<Rectangle> eyes)
+        /// <summary>
+        /// Detect faces and eyes region from the input image
+        /// </summary>
+        /// <param name="image">The input image.</param>
+        /// <param name="faces">The region of the faces.</param>
+        /// <param name="eyes">The region of the eyes.</param>
+        public void Detect(
+           IInputArray image,
+           List<Rectangle> faces, 
+           List<Rectangle> eyes)
         {
             using (Mat gray = new Mat())
             {
@@ -35,7 +45,7 @@ namespace Emgu.CV.Models
                 //Detect the faces from the gray scale image and store the locations as rectangle
                 //The first dimensional is the channel
                 //The second dimension is the index of the rectangle in the specific channel                     
-                Rectangle[] facesDetected = face.DetectMultiScale(
+                Rectangle[] facesDetected = _faceCascadeClassifier.DetectMultiScale(
                    gray,
                    1.1,
                    10,
@@ -48,7 +58,7 @@ namespace Emgu.CV.Models
                     //Get the region of interest on the faces
                     using (Mat faceRegion = new Mat(gray, f))
                     {
-                        Rectangle[] eyesDetected = eye.DetectMultiScale(
+                        Rectangle[] eyesDetected = _eyeCascadeClassifier.DetectMultiScale(
                            faceRegion,
                            1.1,
                            10,
@@ -63,7 +73,6 @@ namespace Emgu.CV.Models
                     }
                 }
             }
-
         }
 
 
@@ -71,6 +80,7 @@ namespace Emgu.CV.Models
         /// Download and initialize the face and eye cascade classifier detection model
         /// </summary>
         /// <param name="onDownloadProgressChanged">Call back method during download</param>
+        /// <param name="initOptions">Initialization options. None supported at the moment, any value passed will be ignored.</param>
         /// <returns>Asyn task</returns>
         public async Task Init(DownloadProgressChangedEventHandler onDownloadProgressChanged = null, Object initOptions = null)
         {
@@ -91,13 +101,19 @@ namespace Emgu.CV.Models
             }
         }
 
+        /// <summary>
+        /// Process the input image and render into the output image
+        /// </summary>
+        /// <param name="imageIn">The input image</param>
+        /// <param name="imageOut">The output image, can be the same as imageIn, in which case we will render directly into the input image</param>
+        /// <returns>The messages that we want to display.</returns>
         public string ProcessAndRender(IInputArray imageIn, IInputOutputArray imageOut)
         {
             List<Rectangle> faces = new List<Rectangle>();
             List<Rectangle> eyes = new List<Rectangle>();
 
             Stopwatch watch = Stopwatch.StartNew();
-            Detect(imageIn, _faceCascadeClassifier, _eyeCascadeClassifier, faces, eyes);
+            Detect(imageIn, faces, eyes);
             watch.Stop();
 
             if (imageOut != imageIn)
@@ -120,12 +136,10 @@ namespace Emgu.CV.Models
 
         }
 
+        /// <summary>
+        /// Clear and reset the model. Required Init function to be called again before calling ProcessAndRender.
+        /// </summary>
         public void Clear()
-        {
-            DisposeObject();
-        }
-
-        protected override void DisposeObject()
         {
             if (_faceCascadeClassifier != null)
             {
@@ -139,5 +153,13 @@ namespace Emgu.CV.Models
                 _eyeCascadeClassifier = null;
             }
         }
+
+        /// <summary>
+        /// Release the memory associated with this face and eye detector
+        /// </summary>
+        protected override void DisposeObject()
+        {
+            Clear();
+        }
     }
 }

Emgu.CV.Models/Dnn/FaceAndLandmarkDetector.cs

@@ -77,6 +77,7 @@ namespace Emgu.CV.Models
         /// Download and initialize the DNN face and facemark detector
         /// </summary>
         /// <param name="onDownloadProgressChanged">Callback when download progress has been changed</param>
+        /// <param name="initOptions">Initialization options. None supported at the moment, any value passed will be ignored.</param>
         /// <returns>Async task</returns>
         public async Task Init(
             DownloadProgressChangedEventHandler onDownloadProgressChanged = null, 

Emgu.CV.Models/Dnn/SceneTextDetector.cs

@@ -45,6 +45,7 @@ namespace Emgu.CV.Models
         /// Download and initialize the vehicle detector, the license plate detector and OCR.
         /// </summary>
         /// <param name="onDownloadProgressChanged">Callback when download progress has been changed</param>
+        /// <param name="initOptions">Initialization options. None supported at the moment, any value passed will be ignored.</param>
         /// <returns>Async task</returns>
         public async Task Init(
             System.Net.DownloadProgressChangedEventHandler onDownloadProgressChanged = null,
@@ -100,7 +101,6 @@ namespace Emgu.CV.Models
             }
         }
 
-
         private async Task InitTextRecognizer(System.Net.DownloadProgressChangedEventHandler onDownloadProgressChanged = null)
         {
             if (_ocr == null)

Emgu.CV.Models/Dnn/VehicleLicensePlateDetector.cs

@@ -224,6 +224,7 @@ namespace Emgu.CV.Models
         /// Download and initialize the vehicle detector, the license plate detector and OCR.
         /// </summary>
         /// <param name="onDownloadProgressChanged">Callback when download progress has been changed</param>
+        /// <param name="initOptions">Initialization options. A string in the format of "backend;target" that represent the DNN backend and target.</param>
         /// <returns>Async task</returns>
         public async Task Init(
             System.Net.DownloadProgressChangedEventHandler onDownloadProgressChanged = null, 

Emgu.CV.Models/PedestrianDetector.cs

@@ -17,6 +17,9 @@ using Emgu.Util;
 
 namespace Emgu.CV.Models
 {
+    /// <summary>
+    /// Pedestrian detector
+    /// </summary>
     public class PedestrianDetector : DisposableObject, IProcessAndRenderModel
     {
         private CudaHOG _hogCuda;
@@ -26,11 +29,6 @@ namespace Emgu.CV.Models
         /// Clear and reset the model. Required Init function to be called again before calling ProcessAndRender.
         /// </summary>
         public void Clear()
-        {
-            DisposeObject();
-        }
-
-        protected override void DisposeObject()
         {
             if (_hog != null)
             {
@@ -45,12 +43,20 @@ namespace Emgu.CV.Models
             }
         }
 
+        /// <summary>
+        /// Release the memory associated with this pedestrian detector
+        /// </summary>
+        protected override void DisposeObject()
+        {
+            Clear();
+        }
+
         /// <summary>
         /// Find the pedestrian in the image
         /// </summary>
         /// <param name="image">The image</param>
         /// <returns>The region where pedestrians are detected</returns>
-        public static Rectangle[] Find(IInputArray image, HOGDescriptor hog, CudaHOG hogCuda = null)
+        public Rectangle[] Find(IInputArray image)
         {
             Rectangle[] regions;
 
@@ -58,21 +64,21 @@ namespace Emgu.CV.Models
             {
                 //if the input array is a GpuMat
                 //check if there is a compatible Cuda device to run pedestrian detection
-                if (iaImage.Kind == InputArray.Type.CudaGpuMat && hogCuda != null)
+                if (iaImage.Kind == InputArray.Type.CudaGpuMat && _hogCuda != null)
                 {
                     //this is the Cuda version
                     using (GpuMat cudaBgra = new GpuMat())
                     using (VectorOfRect vr = new VectorOfRect())
                     {
                         CudaInvoke.CvtColor(image, cudaBgra, ColorConversion.Bgr2Bgra);
-                        hogCuda.DetectMultiScale(cudaBgra, vr);
+                        _hogCuda.DetectMultiScale(cudaBgra, vr);
                         regions = vr.ToArray();
                     }
                 }
                 else
                 {
                     //this is the CPU/OpenCL version
-                    MCvObjectDetection[] results = hog.DetectMultiScale(image);
+                    MCvObjectDetection[] results = _hog.DetectMultiScale(image);
                     regions = new Rectangle[results.Length];
                     for (int i = 0; i < results.Length; i++)
                         regions[i] = results[i].Rect;
@@ -82,6 +88,12 @@ namespace Emgu.CV.Models
             }
         }
 
+        /// <summary>
+        /// Initialize the pedestrian detection model
+        /// </summary>
+        /// <param name="onDownloadProgressChanged">Call back method during download</param>
+        /// <param name="initOptions">Initialization options. None supported at the moment, any value passed will be ignored.</param>
+        /// <returns>Asyn task</returns>
         public async Task Init(DownloadProgressChangedEventHandler onDownloadProgressChanged = null, Object initOptions = null)
         {
             _hog = new HOGDescriptor();
@@ -99,10 +111,16 @@ namespace Emgu.CV.Models
 
         }
 
+        /// <summary>
+        /// Process the input image and render into the output image
+        /// </summary>
+        /// <param name="imageIn">The input image</param>
+        /// <param name="imageOut">The output image, can be the same as imageIn, in which case we will render directly into the input image</param>
+        /// <returns>The messages that we want to display.</returns>
         public string ProcessAndRender(IInputArray imageIn, IInputOutputArray imageOut)
         {
             Stopwatch watch = Stopwatch.StartNew();
-            Rectangle[] pedestrians = Find(imageIn, _hog, _hogCuda);
+            Rectangle[] pedestrians = Find(imageIn);
             watch.Stop();
 
             if (imageOut != imageIn)

Emgu.CV.Models/TesseractModel.cs

@@ -20,6 +20,9 @@ using System.Diagnostics;
 
 namespace Emgu.CV.Models
 {
+    /// <summary>
+    /// Tesseract Ocr model.
+    /// </summary>
     public class TesseractModel : DisposableObject, IProcessAndRenderModel
     {
         private String _modelFolderName = "tessdata";
@@ -59,11 +62,21 @@ namespace Emgu.CV.Models
                 _ocr = null;
             }
         }
+
+        /// <summary>
+        /// Release all the unmanaged memory associated to this tesseract OCR model.
+        /// </summary>
         protected override void DisposeObject()
         {
             Clear();
         }
 
+        /// <summary>
+        /// Process the input image and render into the output image
+        /// </summary>
+        /// <param name="imageIn">The input image</param>
+        /// <param name="imageOut">The output image, can be the same as imageIn, in which case we will render directly into the input image</param>
+        /// <returns>The messages that we want to display.</returns>
         public string ProcessAndRender(IInputArray imageIn, IInputOutputArray imageOut)
         {
             Stopwatch watch = Stopwatch.StartNew();
@@ -90,11 +103,16 @@ namespace Emgu.CV.Models
 
         }
 
+        /// <summary>
+        /// Initialize the tesseract ocr model
+        /// </summary>
+        /// <param name="onDownloadProgressChanged">Call back method during download</param>
+        /// <param name="initOptions">Initialization options. None supported at the moment, any value passed will be ignored.</param>
+        /// <returns>Asyn task</returns>
         public async Task Init(System.Net.DownloadProgressChangedEventHandler onDownloadProgressChanged = null, Object initOptions = null)
         {
             await InitTesseract("eng", OcrEngineMode.TesseractOnly, onDownloadProgressChanged);
         }
 
-
     }
 }

Emgu.CV/PInvoke/CvInvokeCore.cs

@@ -3052,6 +3052,13 @@ namespace Emgu.CV
         private static extern int cveGetNumberOfCPUs();
 #endif
 
+        /// <summary>
+        /// Replace OpenCV parallel_for backend.
+        /// </summary>
+        /// <param name="backendName">The name of the backend.</param>
+        /// <param name="propagateNumThreads">It true, the number of threads of the current enviroment will be passed to the new backend.</param>
+        /// <returns>True if backend is set</returns>
+        /// <remarks>This call is not thread-safe. Consider calling this function from the main() before any other OpenCV processing functions (and without any other created threads).</remarks>
         public static bool SetParallelForBackend(String backendName, bool propagateNumThreads = true)
         {
             using (CvString csBackendName = new CvString(backendName))
@@ -3062,6 +3069,9 @@ namespace Emgu.CV
         [return: MarshalAs(CvInvoke.BoolMarshalType)]
         private static extern bool cveSetParallelForBackend(IntPtr backendName, bool propagateNumThreads);
 
+        /// <summary>
+        /// Get a list of the available parallel backends.
+        /// </summary>
         public static String[] AvailableParallelBackends
         {
             get