/// <summary>
/// Initializes a new instance of SerializableFace object
/// </summary>
/// <param name="face">Base face</param>
public SerializableFace(Face face)
{
this.compressedFeatures = face.CompressedFeatures;
this.features = face.Features;
this.id = face.Id;
this.name = face.Name;
this.originalBitmap = face.OriginalBitmap;
this.vlFace = face.VlFace;
}
/// <summary>
/// Recognizes multiple faces from a single image frame
/// </summary>
/// <param name="image">Neurotec Image in which is based the face recognition</param>
/// <param name="vlFaces">Array of faces detected</param>
/// <param name="recognizedFaces">Array of Face objects used to realize each recognition</param>
/// <param name="MultipleRecognitionResults">An array containing all recognition results for each recognized face</param>
/// <returns>An array containing best match in all known faces.</returns>
private RecognitionResult[] RecognizeMultipleFaces(NImage image, VleFace[] vlFaces, out FaceCollection detectedFaces, out RecognitionResult[][] MultipleRecognitionResults)
{
#region Variables
// Stores the original image as bitmap
Bitmap bmp;
// Bitmap to draw in the detected face region
Bitmap croppedBitmap;
// Graphics used to copy the face detected region
Graphics g;
// Rectangle used to copy the scaled region of face detected
Rectangle rect;
// Nurotec Image required in the process of recognize the face detected region
NGrayscaleImage gray;
// Verilook Detetion Details as result of face recognition
VleDetectionDetails detectionDetails;
// The face template result of a face recognition
byte[][] templates = new byte[vlFaces.Length][];
// The face features result of a face recognition
byte[] features;
// Stores the current recognition face
Face currentFace;
// Stores the recognized faces
//FaceCollection recognizedFaces = new FaceCollection(vlFaces.Length);
detectedFaces = new FaceCollection(vlFaces.Length);
// Stores the best recognition result for current face
RecognitionResult currentResult;
// Stores the recognition results for current face
RecognitionResult[] currentRecognitionResults;
// Stores all Recognition results
List<RecognitionResult[]> recognitionResults = new List<RecognitionResult[]>();
// Stores the best recognition result matches
List<RecognitionResult> selectedResults = new List<RecognitionResult>();
#endregion
// Get the original image as bitmap
bmp = new Bitmap(image.ToBitmap());
// Extract each face, and get its template
foreach (VleFace vlFace in vlFaces)
{
// Get a rectangle a bit larger than the one the face has been recognized.
// Its because some times in the exact area of the face the face cannot be recognized again
//rect = new Rectangle(vlFace.Rectangle.X - 50, vlFace.Rectangle.Y - 50, vlFace.Rectangle.Width + 100, vlFace.Rectangle.Height + 100);
rect = new Rectangle(vlFace.Rectangle.X - vlFace.Rectangle.Width / 2, vlFace.Rectangle.Y - vlFace.Rectangle.Height / 2, vlFace.Rectangle.Width * 2, vlFace.Rectangle.Height * 2);
// Get the face bitmap
croppedBitmap = new Bitmap(rect.Width, rect.Height);
g = Graphics.FromImage(croppedBitmap);
g.DrawImage(bmp, 0, 0, rect, GraphicsUnit.Pixel);
// Get gray image for face detection
gray = (NGrayscaleImage)NImage.FromImage(NPixelFormat.Grayscale, 0, NImage.FromBitmap(croppedBitmap));
// Extract the face and extract its template
currentFace = new Face(vlFace);
features = vlExtractor.Extract(gray, out detectionDetails);
if (!detectionDetails.FaceAvailable) continue;
UseResources();
currentFace.SetRecognitionData(features, detectionDetails, croppedBitmap);
ReleaseResources();
currentFace.CalculateFovAndCoords((int)image.Width, (int)image.Height);
detectedFaces.Add(currentFace);
Console("Found face: location = (" + detectionDetails.Face.Rectangle.X + ", " + detectionDetails.Face.Rectangle.Y + "), width = " + detectionDetails.Face.Rectangle.Width + ", height = " + detectionDetails.Face.Rectangle.Height + ", confidence = " + detectionDetails.Face.Confidence);
try
{
croppedBitmap.Dispose();
g.Dispose();
gray.Dispose();
}
catch { }
}
if (detectedFaces.Count > 0) Console(detectedFaces.Count.ToString() + " faces found.");
if (knownFaces.Count > 0)
{
Console("Initializing recognition");
// Recognize each detected face
for (int i = 0; i < detectedFaces.Count; ++i)
{
if (detectedFaces[i].Features == null) continue;
currentFace = detectedFaces[i];
// Start recognition
currentResult = Recognize(currentFace, out currentRecognitionResults);
if (currentResult == null) continue;
selectedResults.Add(currentResult);
recognitionResults.Add(currentRecognitionResults);
}
}
MultipleRecognitionResults = recognitionResults.ToArray();
return selectedResults.ToArray();
}
/// <summary>
/// Recognizes multiple faces from a single image frame
/// </summary>
/// <param name="image">Neurotec Image in which is based the face recognition</param>
/// <param name="vlFaces">Array of faces detected</param>
/// <returns>An array containing best match in all known faces.</returns>
private RecognitionResult[] RecognizeMultipleFaces(NImage image, VleFace[] vlFaces)
{
RecognitionResult[][] MultipleRecognitionResults;
FaceCollection recognizedFaces;
return RecognizeMultipleFaces(image, vlFaces, out recognizedFaces, out MultipleRecognitionResults);
}
/// <summary>
/// Recognizes a single face from a single image frame
/// </summary>
/// <param name="image">Neurotec Image in which is based the face recognition</param>
/// <param name="vlFace">Face detected in which region is the face to recognize</param>
/// <param name="face">Face object used to realize a recognition</param>
/// <param name="recognitionResults">An array containing all recognition results for the recognized face</param>
/// <returns>The best match in all known faces. Null if not found</returns>
private RecognitionResult RecognizeFace(NImage image, VleFace vlFace, out Face face, out RecognitionResult[] recognitionResults)
{
// Bitmap to draw in the detected face region
Bitmap croppedBitmap;
// Graphics used to copy the face detected region
Graphics g;
// Rectangle used to copy the scaled region of face detected
Rectangle rect;
// The recognition result obtained
RecognitionResult result;
// Get a rectangle a bit larger than the one the face has been recognized.
// Its because some times in the exact area of the face the face cannot be recognized again
//rect = new Rectangle(vlFace.Rectangle.X - 50, vlFace.Rectangle.Y - 50, vlFace.Rectangle.Width + 100, vlFace.Rectangle.Height + 100);
rect = new Rectangle(vlFace.Rectangle.X - vlFace.Rectangle.Width / 2, vlFace.Rectangle.Y - vlFace.Rectangle.Height / 2, vlFace.Rectangle.Width * 2, vlFace.Rectangle.Height * 2);
croppedBitmap = new Bitmap(rect.Width, rect.Height);
g = Graphics.FromImage(croppedBitmap);
g.DrawImage(image.ToBitmap(), 0, 0, rect, GraphicsUnit.Pixel);
face = new Face(vlFace);
result = RecognizeFace(NImage.FromBitmap(croppedBitmap), ref face, out recognitionResults);
return result;
}
/// <summary>
/// Recognizes a single face from a single image frame
/// </summary>
/// <param name="image">Neurotec Image in which is based the face recognition</param>
/// <param name="vlFace">Face detected in which region is the face to recognize</param>
/// <returns>The best match in all known faces. Null if not found</returns>
private RecognitionResult RecognizeFace(NImage image, VleFace vlFace)
{
RecognitionResult[] recognitionResults;
Face face;
return RecognizeFace(image, vlFace, out face, out recognitionResults);
}
/// <summary>
/// Updates the output video control
/// </summary>
/// <param name="image">Base Image</param>
/// <param name="faces">List of faces detected</param>
private void RecognitionResultUpdate(Bitmap image, VleFace[] faces)
{
/*
if (this.InvokeRequired)
{
if (!this.IsHandleCreated || this.Disposing || this.IsDisposed)
return;
this.BeginInvoke(dlgRecognitionResultUpdate, image, faces);
return;
}
vcRecognitionResult.Image = image;
vcRecognitionResult.Faces = faces;
//vcRecognitionResult.DetectionDetails = details;
*/
}
/// <summary>
/// Updates the output video control
/// </summary>
/// <param name="image">Base Image</param>
/// <param name="faces">List of faces detected</param>
private void RecognitionResultUpdate(Bitmap image, Face[] faces)
{
if (this.InvokeRequired)
{
if (!this.IsHandleCreated || this.Disposing || this.IsDisposed)
return;
this.BeginInvoke(dlgRecognitionResultUpdate4, image, faces);
return;
}
VleFace[] vlFaces;
VleDetectionDetails[] vlDetails;
vlFaces = new VleFace[faces.Length];
vlDetails = new VleDetectionDetails[faces.Length];
for (int i = 0; i < faces.Length; ++i)
{
if (faces[i] != null)
{
vlFaces[i] = faces[i].VlFace;
vlDetails[i] = faces[i].DetectionDetails;
}
}
vcRecognitionResult.Image = image;
vcRecognitionResult.Faces = vlFaces;
vcRecognitionResult.DetectionDetails = vlDetails;
if (faces[0].HasFOV)
{
vcRecognitionResult.String = "(" + faces[0].HFoV.ToString("0.00") + "," + faces[0].VFoV.ToString("0.00") + ")";
}
}
/// <summary>
/// Updates the output video control
/// </summary>
/// <param name="image">Base Image</param>
/// <param name="faces">List of faces detected</param>
private void RecognitionResultUpdate(Bitmap image, Face face)
{
if (face == null)
return;
if (this.InvokeRequired)
{
if (!this.IsHandleCreated || this.Disposing || this.IsDisposed)
return;
this.BeginInvoke(dlgRecognitionResultUpdate3, image, face);
return;
}
VleFace[] vlFaces;
VleDetectionDetails[] vlDetails;
vlFaces = new VleFace[] { face.VlFace };
vlDetails = new VleDetectionDetails[] { face.DetectionDetails };
vcRecognitionResult.Image = image;
vcRecognitionResult.Faces = vlFaces;
vcRecognitionResult.DetectionDetails = vlDetails;
if (face.HasFOV)
{
vcRecognitionResult.String = "FOV: (" + face.HFoV.ToString("0.00") + "," + face.VFoV.ToString("0.00") + ")";
}
}
