private int recongnize(FaceTemplate template)
{
bool match = false;
int i;
for (i = 0; i < UserTemplates.Count; i++)
{
foreach (FaceTemplate t in UserTemplates[i])
{
float Siminarity = 0.0f;
FaceTemplate t1 = t;
FSDK.MatchFaces(ref template.templateData, ref t1.templateData, ref Siminarity);
float threashold = 0.0f;
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
FSDK.GetMatchingThresholdAtFAR(0.25f, ref threashold);
//0.1表示程序误认为不同的人为检测对象的几率是0.1 该取值范围0~1
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
if (Siminarity > threashold)
{
match = true;
break;
}
}
if (match)
{
return(i);
}
}
return(-1);
}
//bool _toContinue = true;
public bool check_reg(byte[] ttp)
{
try
{
bool val = false;
foreach (byte[] t in faceTemplates)
{
float similarity = 0.0f;
byte[] t1 = t;
FSDK.MatchFaces(ref ttp, ref t1, ref similarity);
float threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(0.001f, ref threshold); // set FAR to 1%--0.1%
if (similarity > threshold)
{
val = true;
setV(t1);
break;
}
Application.DoEvents();
}
return(val);
}
catch (InvalidOperationException inov)
{
return(false);
}
}
public void GetPerson(TFaceRecord faceIn, out string FaceFullName)
{
bool ok = false;
string fName = "Unknown Face";
if (Global.Persons == null)
{
FaceFullName = fName; return;
}
try
{
float Threshold = 0.034455f;
//float Threshold = 0.001155f;
SimilarFaces[] Faces = null;
SimilarFaces[] faces = new SimilarFaces[Global.Persons.Length];
List <SimilarFaces> Fa = new List <SimilarFaces>();
int i = -1;
foreach (TFaceRecord fac in Global.Persons)
{
TFaceRecord F = new TFaceRecord();
F = fac;
float Similarity = 0.0f;
FSDK.MatchFaces(ref faceIn.Template, ref F.Template, ref Similarity);
if (Similarity >= Threshold)
{
i++;
faces[i].FullName = fac.Fullname;
faces[i].Similarity = Similarity;
}
}
if (faces != null)
{
Faces = faces.Where(v => v.FullName != null).ToArray();
fName = GetMostAcurateFace(Faces);
//fName = SortSimilarFaces(Faces)[0].FullName;
}
}
catch (Exception n)
{
}
FaceFullName = fName;
//return ok;
}
/// <summary>
/// Xử Lý
/// </summary>
/// <param name="SearchFace"></param>
public void xuLy(TFaceRecord SearchFace, int index)
{
float Threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(Form1.FARValue / 100, ref Threshold);
int MatchedCount = 0;
int FaceCount = Form2.FaceList.Count;
float[] Similarities = new float[FaceCount];
int[] Numbers = new int[FaceCount];
for (int j = 0; j < SearchFace.Template.Count; j++)
{
for (int i = 0; i < Form2.FaceList.Count; i++)
{
float Similarity = 0.0f;
TFaceRecord CurrentFace = Form2.FaceList[i];
byte[] anh1 = new byte[FSDK.TemplateSize];
byte[] anh2 = new byte[FSDK.TemplateSize];
anh1 = SearchFace.Template[j];
anh2 = Form2.FaceList[i].Template[0];
FSDK.MatchFaces(ref anh1, ref anh2, ref Similarity);
if (Similarity >= Threshold)
{
SearchFace.Template[0] = SearchFace.Template[j];
Form2.FaceList.Add(SearchFace);
imageList2.Images.Add(SearchFace.image.ToCLRImage());
items = new ListViewItem();
items.ImageIndex = demlv2++;
items.Text = SearchFace.ImageFileName;
items.ToolTipText = SearchFace.ImageFileName;
items.Tag = SearchFace;
listView2.Items.Add(items);
// MessageBox.Show(index.ToString()+" "+AnhList.Count+" "+FaceListID.Count);
AnhList[index].TrangThai = true;///sfsdfds
return;
////Similarities[MatchedCount] = Similarity;
////Numbers[MatchedCount] = i;
////++MatchedCount;
}
}
}
}
public bool check_reg(byte[] ttp)
{
bool val = false;
foreach (byte[] t in faceTemplates)
{
float similarity = 0.0f;
byte[] t1 = t;
FSDK.MatchFaces(ref ttp, ref t1, ref similarity);
float threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(0.01f, ref threshold);
if (similarity > threshold)
{
val = true;
setV(t1);
break;
}
}
return(val);
}
void Go(ref TFaceRecords SearchFace)
{
System.Drawing.Image img = SearchFace.faceImage.ToCLRImage();
float Threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(70 / 100, ref Threshold);
int MatchedCount = 0;
int FaceCount = FaceList.Count();
Double[] Similarities = new Double[FaceCount];
int[] Numbers = new int[FaceCount];
MessageBox.Show("Facelist = " + FaceList.Count);
for (int i = 0; i <= FaceList.Count - 1; i++)
{
float Similarity = 0.0F;
TFaceRecords CurrentFace = FaceList[i];
FSDK.MatchFaces(ref SearchFace.Template, ref CurrentFace.Template, ref Similarity);
MessageBox.Show("Similarity = " + Similarity + "Threshold = " + Threshold);
if (Similarity >= Threshold)
{
Similarities[MatchedCount] = Similarity;
Numbers[MatchedCount] = i;
MatchedCount += 1;
}
}
if (MatchedCount == 0)
{
MessageBox.Show("No matches found.\nTry Again !!!" + MatchedCount, "No matches");
}
else
{
MessageBox.Show("Staff Record found in database...");
}
/*
*/
t.Abort();
// button1.Enabled = true;
}
public void Go(TFaceRecord SearchFace)
{
Image img = SearchFace.image.ToCLRImage();
pictureBox1.Image = img;
pictureBox1.Height = img.Height;
pictureBox1.Width = img.Width;
imageList1 = new ImageList();
Size size100x100 = new Size();
size100x100.Height = 100;
size100x100.Width = 100;
imageList1.ImageSize = size100x100;
imageList1.ColorDepth = ColorDepth.Depth24Bit;
listView1.OwnerDraw = false;
listView1.View = View.LargeIcon;
listView1.Dock = DockStyle.Bottom;
listView1.LargeImageList = imageList1;
label1.Dock = DockStyle.Bottom;
float Threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(Form1.FARValue / 100, ref Threshold);
int MatchedCount = 0;
int FaceCount = Form1.FaceList.Count;
float[] Similarities = new float[FaceCount];
int[] Numbers = new int[FaceCount];
for (int i = 0; i < Form1.FaceList.Count; i++)
{
float Similarity = 0.0f;
TFaceRecord CurrentFace = Form1.FaceList[i];
FSDK.MatchFaces(ref SearchFace.Template, ref CurrentFace.Template, ref Similarity);
if (Similarity >= Threshold)
{
Similarities[MatchedCount] = Similarity;
Numbers[MatchedCount] = i;
++MatchedCount;
}
}
if (MatchedCount == 0)
{
MessageBox.Show("No matches found. You can try to increase the FAR parameter in the Options dialog box.", "No matches");
}
else
{
floatReverseComparer cmp = new floatReverseComparer();
Array.Sort(Similarities, Numbers, 0, MatchedCount, (IComparer <float>)cmp);
label1.Text = "Faces Matched: " + MatchedCount.ToString();
for (int i = 0; i < MatchedCount; i++)
{
imageList1.Images.Add(Form1.FaceList[Numbers[i]].faceImage.ToCLRImage());
listView1.Items.Add((Similarities[i] * 100.0f).ToString(System.Globalization.CultureInfo.InvariantCulture.NumberFormat),
Form1.FaceList[Numbers[i]].ImageFileName.Split('\\')[Form1.FaceList[Numbers[i]].ImageFileName.Split('\\').Length - 1] +
"\r\nSimilarity = " + (Similarities[i] * 100).ToString(),
imageList1.Images.Count - 1);
}
}
this.Show();
}
//处理三个摄像头图像
private void Bg1_DoWork(object sender, DoWorkEventArgs e)
{
string ConnString = Tool.connstr;//连接字符串
SqlConnection conn = new SqlConnection(ConnString);
int[] countID1 = new int[CountingSize];
byte[][] templates1 = new byte[CountingSize][];
int[] countID2 = new int[CountingSize];
byte[][] templates2 = new byte[CountingSize][];
//存储所有已经出现的id
List <long> allIDs1 = new List <long>();
//新建1个Tracker
int tracker1 = 0;
FSDK.CreateTracker(ref tracker1);
int tracker2 = 0;
FSDK.CreateTracker(ref tracker2);
//设置Tracker参数
int err1 = 0;
FSDK.SetTrackerMultipleParameters(tracker1,
"RecognizeFaces=" + RecognizeFaces.ToString().ToLower() +
"; HandleArbitraryRotations=" + HandleArbitraryRotations.ToString().ToLower() +
"; DetermineFaceRotationAngle=" + HandleArbitraryRotations.ToString().ToLower() +
"; InternalResizeWidth=" + InternalResizeWidth.ToString().ToLower() +
"; FaceDetectionThreshold=" + FaceDetectionThreshold.ToString().ToLower() + ";",
ref err1);
int err2 = 0;
FSDK.SetTrackerMultipleParameters(tracker2,
"RecognizeFaces=" + RecognizeFaces.ToString().ToLower() +
"; HandleArbitraryRotations=" + HandleArbitraryRotations.ToString().ToLower() +
"; DetermineFaceRotationAngle=" + HandleArbitraryRotations.ToString().ToLower() +
"; InternalResizeWidth=" + InternalResizeWidth.ToString().ToLower() +
"; FaceDetectionThreshold=" + FaceDetectionThreshold.ToString().ToLower() + ";",
ref err2);
DateTime t1 = DateTime.Now;
DateTime t2 = DateTime.Now;
//记录总帧数
int loops = 0;
while (!needClose)
{
//声明定义三个图片句柄，来源于三个摄像头句柄
Int32 imageHandle1 = 0;
Int32 imageHandle2 = 0;
if (FSDK.FSDKE_OK != FSDKCam.GrabFrame(cameraHandle1, ref imageHandle1))
{
continue;
}
if (FSDK.FSDKE_OK != FSDKCam.GrabFrame(cameraHandle2, ref imageHandle2))
{
continue;
}
FSDK.CImage image1 = new FSDK.CImage(imageHandle1);
Image frameImage1 = image1.ToCLRImage();
FSDK.CImage image2 = new FSDK.CImage(imageHandle2);
Image frameImage2 = image2.ToCLRImage();
long[] IDs1;
long[] IDs2;
long faceCount1 = 0;
long faceCount2 = 0;
FSDK.FeedFrame(tracker1, 0, image1.ImageHandle, ref faceCount1, out IDs1, sizeof(long) * 256); // maximum 256 faces detected
FSDK.FeedFrame(tracker2, 0, image2.ImageHandle, ref faceCount2, out IDs2, sizeof(long) * 256); // maximum 256 faces detected
Array.Resize(ref IDs1, (int)faceCount1);
Array.Resize(ref IDs2, (int)faceCount2);
Graphics g1 = Graphics.FromImage(frameImage1);
Graphics g2 = Graphics.FromImage(frameImage2);
conn.Open();
Application.DoEvents(); //使控件可用
//处理1号相机当前帧
for (int i = 0; i < IDs1.Length; ++i)
{
try
{
//计算人脸特征模板
FSDK.TFacePosition facePosition1 = new FSDK.TFacePosition();
FSDK.GetTrackerFacePosition(tracker1, 0, IDs1[i], ref facePosition1);
//绘制人脸矩形框
int left = facePosition1.xc - (int)(facePosition1.w * 0.5);
int top = facePosition1.yc - (int)(facePosition1.w * 0.5);
g1.DrawRectangle(Pens.LightGreen, left, top, (int)(facePosition1.w * 1.0), (int)(facePosition1.w * 1.0));
//计算当前ID对应人脸特征串
byte[] temp1 = image1.GetFaceTemplateInRegion(ref facePosition1);
//记录当前ID
if (allIDs1.Count == 0)//如果是第一个ID则直接加入
{
//记录当前ID出现次数
countID1[IDs1[i]] = countID1[IDs1[i]] >= 100 ? 100 : countID1[IDs1[i]] + 1;
//更新当前ID的特征串
templates1[IDs1[i]] = temp1;
//无重复添加新的ID
AddIDIntoAllIDList(allIDs1, IDs1[i]);
}
else if (allIDs1.Exists(x => x == IDs1[i]))//如果已存在当前ID，则只更新特征串数据
{
//更新当前ID的特征串
templates1[IDs1[i]] = temp1;
//记录当前ID出现次数
countID1[IDs1[i]] = countID1[IDs1[i]] >= 100 ? 100 : countID1[IDs1[i]] + 1;
}
else//如果是新的ID，则与原来的每个ID对应的模板进行比对，看相似度
{
float simlarity = 0;
//foreach (long id in allIDs1)
//{
// int r = FSDK.MatchFaces(ref templates1[id], ref temp1, ref simlarity);
// if (simlarity > 0.8f)//发现相似
// {
// //FSDK.PurgeID(tracker1, IDs[i]);
// countID1[id] = countID1[id] >= 100 ? 100 : countID1[id] + 1;
// break;
// }
// else//没有相似
// {
// //记录当前ID出现次数
// countID1[IDs1[i]] = countID1[IDs1[i]] >= 100 ? 100 : countID1[IDs1[i]] + 1;
// //更新当前ID的特征串
// templates1[IDs1[i]] = temp1;
// //无重复添加新的ID
// AddIDIntoAllIDList(allIDs1, IDs1[i]);
// }
//}
int sim1_count = 0;
foreach (long id in allIDs1)
{
int r = FSDK.MatchFaces(ref templates1[id], ref temp1, ref simlarity);
if (simlarity > 0.8f)//发现相似
{
countID1[id] = countID1[id] >= 100 ? 100 : countID1[id] + 1;
sim1_count = sim1_count + 1;
break;
}
}
if (sim1_count == 0)
{
//记录当前ID出现次数
countID1[IDs1[i]] = countID1[IDs1[i]] >= 100 ? 100 : countID1[IDs1[i]] + 1;
//更新当前ID的特征串
templates1[IDs1[i]] = temp1;
//无重复添加新的ID
AddIDIntoAllIDList(allIDs1, IDs1[i]);
}
}
}
catch { }
}
//处理2号相机当前帧
for (int i = 0; i < IDs2.Length; ++i)
{
try
{
//计算人脸特征模板
FSDK.TFacePosition facePosition2 = new FSDK.TFacePosition();
FSDK.GetTrackerFacePosition(tracker2, 0, IDs2[i], ref facePosition2);
//绘制人脸矩形框
int left = facePosition2.xc - (int)(facePosition2.w * 0.5);
int top = facePosition2.yc - (int)(facePosition2.w * 0.5);
g2.DrawRectangle(Pens.LightGreen, left, top, (int)(facePosition2.w * 1.0), (int)(facePosition2.w * 1.0));
//计算当前ID对应人脸特征串
byte[] temp2 = image2.GetFaceTemplateInRegion(ref facePosition2);
//如果是新的ID，则与原来的每个ID对应的模板进行比对，看相似度
float simlarity = 0;
foreach (long id in allIDs1)
{
int r = FSDK.MatchFaces(ref templates1[id], ref temp2, ref simlarity);
if (simlarity > 0.8f)//发现相似
{
countID1[id] = 0;
int a = Convert.ToInt32(id);
DateTime XiaCheShiJian = DateTime.Now.ToLocalTime();
SqlCommand sqlCmd = new SqlCommand("UPDATE [SafeSystem].[dbo].[FaceRecognition] SET [XiaCheShiJian] = @XiaCheShiJian WHERE Template = " + a + "and XiaCheShiJian is null", conn);
sqlCmd.Parameters.Add("@XiaCheShiJian", System.Data.SqlDbType.DateTime);
sqlCmd.Parameters["@XiaCheShiJian"].Value = XiaCheShiJian;
sqlCmd.ExecuteNonQuery();
RemoveIDFromAllIDList(allIDs1, IDs1[i]);
break;
}
}
}
catch { }
}
//组织当前全部ID列表字符串
string strAll1 = "";
int index1 = 0;
foreach (int id in allIDs1)
{
if (index1 == 0)
{
strAll1 += "(" + id + ":" + countID1[id] + ")";
}
else
{
strAll1 += ",(" + id + ":" + countID1[id] + ")";
}
index1++;
}
//显示当前实时数据到当前帧
t2 = DateTime.Now;
TimeSpan ts = t2 - t1;
t1 = t2;
g1.DrawString("Frames Count：" + loops, new Font("微软雅黑", 20f), Brushes.Red, 10, 0);
g1.DrawString("All Person：" + allIDs1.Count + "[" + strAll1 + "]", new Font("微软雅黑", 20f), Brushes.Red, 10, 50);
g1.DrawString("Frame Time：" + ts.TotalMilliseconds.ToString("####.#") + "ms", new Font("微软雅黑", 20f), Brushes.Red, 10, 100);
g1.DrawString("Frame Rate：" + (1000.0 / ts.TotalMilliseconds).ToString("####.#") + "fps", new Font("微软雅黑", 20f), Brushes.Red, 10, 150);
g1.Dispose();
g1 = null;
Helper.SetImage(box1, frameImage1);
Thread.Sleep(SleepTime);
g2.Dispose();
g2 = null;
Helper.SetImage(box2, frameImage2);
Thread.Sleep(SleepTime);
//每处理100帧图像就清理一次出现次数很少的ID，减少计数错误
if (loops == 100)
{
List <long> bak1 = new List <long>();
foreach (long id in allIDs1)
{
if (countID1[id] > MiniAppear)
{
bak1.Add(id);
int a = Convert.ToInt32(id);
DateTime ShangCheShiJian = DateTime.Now.ToLocalTime();
SqlCommand sqlCmd = new SqlCommand("if not exists (SELECT [Template] FROM [SafeSystem].[dbo].[FaceRecognition] Where Template = '" + a + "' and XiaCheShiJian is null) INSERT INTO [SafeSystem].[dbo].[FaceRecognition] ([Template],[ShangCheShiJian]) " + " values(@Template, @ShangCheShiJian)", conn);
sqlCmd.Parameters.Add("@Template", System.Data.SqlDbType.Int);
sqlCmd.Parameters.Add("@ShangCheShiJian", System.Data.SqlDbType.DateTime);
sqlCmd.Parameters["@Template"].Value = a;
sqlCmd.Parameters["@ShangCheShiJian"].Value = ShangCheShiJian;
sqlCmd.ExecuteNonQuery();
}
else
{
countID1[id] = 0;
}
}
allIDs1 = bak1;
loops = 0;
}
loops++;
GC.Collect(); // collect the garbage after the deletion
conn.Close();
}
FSDK.SaveTrackerMemoryToFile(tracker1, TrackerMemoryFile);
FSDK.FreeTracker(tracker1);
FSDK.FreeTracker(tracker2);
FSDKCam.CloseVideoCamera(cameraHandle1);
FSDKCam.CloseVideoCamera(cameraHandle2);
FSDKCam.FinalizeCapturing();
}
public bool GetPerson(TFaceRecord faceIn, out TFaceRecord faceOut)
{
bool ok = false;
TFaceRecord f = new TFaceRecord();
if (Global.Persons == null)
{
faceOut = f; return(ok);
}
try
{
float Threshold = 0.001155f;
//FSDK.GetMatchingThresholdAtFAR(0.0009f, ref Threshold);
List <float> sFaces = new List <float>();
SimilarFaces[] Faces = null;
SimilarFaces[] faces = new SimilarFaces[Global.Persons.Length];
int i = -1;
foreach (TFaceRecord fac in Global.Persons.AsParallel())
{
TFaceRecord F = new TFaceRecord();
F = fac;
float Similarity = 0.0f; //0.000026273356E == 0.00228634826
FSDK.MatchFaces(ref faceIn.Template, ref F.Template, ref Similarity);
if (Similarity >= Threshold)
{
i++;
faces[i].FullName = fac.Fullname;
faces[i].Similarity = Similarity;
ok = true;
f = fac;
break;
}
}
//Faces.OrderByDescending<SimilarFaces,>
//Parallel.ForEach(Global.Persons.AsParallel(), fac =>
// {
// float Similarity = 0.0f;
// FSDK.MatchFaces(ref faceIn.Template, ref fac.Template, ref Similarity);
// if (Similarity >= Threshold)
// {
// ok = true;
// f = fac;
// }
// });
}
catch (Exception n)
{
}
faceOut = f;
return(ok);
}
private void button1_Click(object sender, EventArgs e)
{
this.button1.Enabled = false;
int cameraHandle = 0;
int r = FSDKCam.OpenVideoCamera(ref cameraName, ref cameraHandle);
if (r != FSDK.FSDKE_OK)
{
MessageBox.Show("Error opening the first camera", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
Application.Exit();
}
// set realtime face detection parameters
FSDK.SetFaceDetectionParameters(false, false, 100);
FSDK.SetFaceDetectionThreshold(3);
// list where we store face templates
// faceTemplates = new List();
faceTemplates = new List <FaceTemplate>();
while (!needClose)
{
// faceTemplates.Clear();
Int32 imageHandle = 0;
if (FSDK.FSDKE_OK != FSDKCam.GrabFrame(cameraHandle, ref imageHandle)) // grab the current frame from the camera
{
Application.DoEvents();
continue;
}
FSDK.CImage image = new FSDK.CImage(imageHandle);
Image frameImage = image.ToCLRImage();
Graphics gr = Graphics.FromImage(frameImage);
FSDK.TFacePosition facePosition = image.DetectFace();
// if a face is detected, we can recognize it
if (facePosition.w != 0)
{
gr.DrawRectangle(Pens.LightGreen, facePosition.xc - facePosition.w / 2, facePosition.yc - facePosition.w / 2,
facePosition.w, facePosition.w);
// create a new face template
FaceTemplate template = new FaceTemplate();
template.templateData = new byte[FSDK.TemplateSize];
FaceTemplate template1 = new FaceTemplate();
if (programState == ProgramState.psRemember || programState == ProgramState.psRecognize)
{
template.templateData = image.GetFaceTemplateInRegion(ref facePosition);
}
switch (programState)
{
case ProgramState.psNormal: // normal state - do nothing
break;
case ProgramState.psRemember: // Remember Me state - store facial templates
label1.Text = "Templates stored: " + faceTemplates.Count.ToString();
faceTemplates.Add(template);
if (faceTemplates.Count > 9)
{
// get the user name
InputName inputName = new InputName();
inputName.ShowDialog();
userName = inputName.userName;
cmd = new SqlCommand("insert into facetb values(@Name,@face)", con);
cmd.Parameters.AddWithValue("@Name", userName);
cmd.Parameters.AddWithValue("@face", template.templateData);
con.Open();
cmd.ExecuteNonQuery();
con.Close();
MessageBox.Show("Record Save!");
programState = ProgramState.psRecognize;
}
break;
case ProgramState.psRecognize: // recognize the user
bool match = false;
con.Open();
cmd = new SqlCommand("select * from facetb ORDER BY id ASC ", con);
SqlDataReader dr = cmd.ExecuteReader();
while (dr.Read())
{
template1.templateData = (byte[])dr["face"];
faceTemplates.Add(template1);
strList.Add(dr["Name"].ToString());
}
con.Close();
int ii = 0;
foreach (FaceTemplate t in faceTemplates)
{
float similarity = 0.0f;
FaceTemplate t1 = t;
FSDK.MatchFaces(ref template.templateData, ref t1.templateData, ref similarity);
float threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(0.01f, ref threshold); // set FAR to 1%
if (similarity > threshold)
{
userName = strList[ii].ToString();
label3.Text = strList[ii].ToString();
match = true;
break;
}
ii++;
}
con.Close();
if (match)
{
StringFormat format = new StringFormat();
format.Alignment = StringAlignment.Center;
gr.DrawString(userName, new System.Drawing.Font("Arial", 16),
new System.Drawing.SolidBrush(System.Drawing.Color.LightGreen),
facePosition.xc, facePosition.yc + facePosition.w * 0.55f, format);
// abc = 0;
send();
}
else
{
abc = 0;
label3.Text = "UnKnow FACE";
}
break;
}
}
// display current frame
pictureBox1.Image = frameImage;
GC.Collect(); // collect the garbage after the deletion
// make UI controls accessible
Application.DoEvents();
}
FSDKCam.CloseVideoCamera(cameraHandle);
FSDKCam.FinalizeCapturing();
}
public FaceRecognitionResult MatchFace(Image <Bgr, byte> a_face)
{
try
{
if (a_face == null)
{
throw new ArgumentNullException();
}
//CREATE A FACE OBJECT
Face unknown_face = new Face();
unknown_face.face_position = new FacePosition();
unknown_face.facial_features = new FSDK.TPoint[FSDK.FSDK_FACIAL_FEATURE_COUNT];
unknown_face.face_template = new byte[FSDK.TemplateSize];
unknown_face.image = new FSDK.CImage(a_face.ToBitmap());
//GET THE POSITION OF THE FACE IN THE IAGE
unknown_face.face_position = FacePosition.FromFSDK(unknown_face.image.DetectFace());
unknown_face.face_image = unknown_face.Clone().image;
FSDK.TFacePosition face_pos = unknown_face.face_position.Clone();
//CHECK IF A FACE HAS BEEN DETECTED
if (0 == face_pos.w)
{
face_pos = null;
Debug.WriteLine("No Face Found");
return(face_recog_results);
}
try
{
FSDK.TFacePosition face_pos_1 = unknown_face.face_position.Clone();
//GET THE FACIAL FEATURES OF THE FACE LIKE EYES NOSE ETC
unknown_face.facial_features = unknown_face.Clone().image.DetectEyesInRegion(ref face_pos_1);
face_pos_1 = null;
}
catch (Exception) { }
try
{
FSDK.TFacePosition face_pos_2 = unknown_face.face_position.Clone();
//GET A TEMPLATE OF THE FACE TO BE USED FOR COMPARISON
unknown_face.face_template = unknown_face.Clone().image.GetFaceTemplateInRegion(ref face_pos_2);
face_pos_2 = null;
}
catch (Exception) { }
//THRESHOLD INDICATING HOW SIMILAR THE TWO FACS MUST BE TO BE CONSIDERED SAME
float similarity_threshold = 0.0f;
//TO DETERMINE IF THE MATCHED TEMPLATES BELONG TO THE SAME PERSON (WITH A SPECIFIED ERROR POSSIBILITY),
//YOU CAN COMPARE THE FACIAL SIMILARITY VALUE WITH A THRESHOLD CALCULATED BY
FSDK.GetMatchingThresholdAtFAR(FARValue / 100, ref similarity_threshold);
//NUMBER OF MATCHES FOUND
int matches_count = 0;
//COUNT OF ALL FACES ENROLLED
int faces_count = known_faces_list.Count;
//HOLDS A FLOAT INDICATING HOW SIMILAR GIVEN FACE IS TO THAT IN THE SAME INDEX IN THE FACE_LIST
float[] similarities = new float[faces_count];
int[] numbers = new int[faces_count];
List <KeyValuePair <Face, float> > face_to_similarity_map = new List <KeyValuePair <Face, float> >();
//LOOP THRU THE KNOWN FACES COMPARING EACH FACE WITH THE UNKNOWN FACE
for (int i = 0; i < known_faces_list.Count; i++)
{
//VALUE INDICATING HOW SIMILAR THE 2 FACES ARE
float similarity = 0.0f;
//GET THE NEXT FACE IN THE FACE_LIST
Face next_face = known_faces_list[i];
//GET TEMPLATES FOR BOTH THE UNKNOWN FACE AND NEXT FACE
Byte[] unknown_face_template = unknown_face.face_template;
Byte[] known_face_template = next_face.face_template;
//COMPARE THE 2 FACES FOR SIMILARITY BETWEEN THEM
FSDK.MatchFaces(ref unknown_face_template, ref known_face_template, ref similarity);
unknown_face_template = null;
known_face_template = null;
if (similarity >= similarity_threshold)
{
similarities[matches_count] = similarity;
numbers[matches_count] = i;
face_to_similarity_map.Add(new KeyValuePair <Face, float>(next_face, similarity));
++matches_count;
}
}
//Dispose of Face
//SORT THE SIMILARITIES IN DESCENDING ORDER INORDERTO FIND THE MOST SIMILAR FACE
FloatsDescendingOrder floats_descending_order = new FloatsDescendingOrder();
Array.Sort(similarities, numbers, 0, matches_count, (IComparer <float>)floats_descending_order);
//GET THE PERPETRATOR ASSOCIATED WITH THE FACE
face_recog_results = new FaceRecognitionResult();
face_recog_results = GetOfMostSimilarFace(similarities, face_to_similarity_map);
face_recog_results.original_detected_face = a_face;
face_to_similarity_map = null;
//RETURN RESULTS OF FACE RECOGNITION OPERATION
return(face_recog_results);
}
catch (Exception e)
{
Debug.WriteLine(e.Message);
}
return(face_recog_results);
}
private void matchesFace()
{
if (dataGridView1.Rows.Count > 0)
{
this.dataGridView1.Invoke(new MethodInvoker(() =>
this.dataGridView1.Rows.Clear()));
this.dataGridView1.Invoke(new MethodInvoker(() =>
this.dataGridView1.Refresh()));
}
for (int i = 0; i < SubjectList.Count; i++)
{
if (SubjectList.Count >= 1)
{
FSDK.GetMatchingThresholdAtFAR(FARValue / 100, ref FaceDetectionThreshold);
TFaceRecord DbSubject = SubjectList[i];
int MatchedCount = 0;
int FaceCount = FaceSearchList.Count;
float[] Similarities = new float[FaceCount];
float[] Smile = new float[FaceCount];
float[] EyesOpen = new float[FaceCount];
float[] Male = new float[FaceCount];
float[] Female = new float[FaceCount];
int[] Numbers = new int[FaceCount];
for (int k = 0; k < FaceSearchList.Count; k++)
{
float Similarity = 0.0f;
float ConfidenceSmile = 0.0f;
float ConfidenceEyesOpen = 0.0f;
float ConfidenceMale = 0.0f;
float ConfidenceFemale = 0.0f;
TFaceRecord SearchFace = FaceSearchList[k];
FSDK.MatchFaces(ref DbSubject.Template, ref SearchFace.Template, ref Similarity);
long MaxSizeInBytes = 100000;
string ExpressionValues = "";
string GenderValues = "";
FSDK.CImage CurrentImage = SearchFace.image;
FSDK.TPoint[] Facefeatures = null;
FSDK.DetectFacialFeatures(SearchFace.faceImage.ImageHandle, out Facefeatures);
if (Facefeatures != null)
{
FSDK.DetectFacialAttributeUsingFeatures(SearchFace.faceImage.ImageHandle, ref Facefeatures, "Expression", out ExpressionValues, MaxSizeInBytes);
FSDK.GetValueConfidence(ExpressionValues, "Smile", ref ConfidenceSmile);
FSDK.GetValueConfidence(ExpressionValues, "EyesOpen", ref ConfidenceEyesOpen);
FSDK.DetectFacialAttributeUsingFeatures(SearchFace.faceImage.ImageHandle, ref Facefeatures, "Gender", out GenderValues, MaxSizeInBytes);
FSDK.GetValueConfidence(GenderValues, "Male", ref ConfidenceMale);
FSDK.GetValueConfidence(GenderValues, "Female", ref ConfidenceFemale);
if (Similarity >= FaceDetectionThreshold)
{
Similarities[MatchedCount] = Similarity;
Smile[MatchedCount] = ConfidenceSmile;
EyesOpen[MatchedCount] = ConfidenceEyesOpen;
Male[MatchedCount] = ConfidenceMale;
Female[MatchedCount] = ConfidenceFemale;
Numbers[MatchedCount] = k;
++MatchedCount;
}
}
else
{
if (Similarity >= FaceDetectionThreshold)
{
Similarities[MatchedCount] = Similarity;
Smile[MatchedCount] = 0;
EyesOpen[MatchedCount] = 0;
Male[MatchedCount] = 0;
Female[MatchedCount] = 0;
Numbers[MatchedCount] = k;
++MatchedCount;
}
}
}
if (MatchedCount == 0)
{
MessageBox.Show("No matches found. You can try to increase the FAR parameter in the Options dialog box.", "No matches");
}
else
{
for (int j = 0; j < MatchedCount; j++)
{
if ((Similarities[j] * 100.0f) >= 30.0f)
{
resultImagelist.Images.Add(FaceSearchList[j].faceImage.ToCLRImage());
Image img1 = FaceSearchList[Numbers[j]].faceImage.ToCLRImage();
img1 = (Image)(new Bitmap(img1, new Size(100, 100)));
Image img2 = Image.FromFile(SubjectList[i].ImageFileName);
img2 = (Image)(new Bitmap(img2, new Size(100, 100)));
string feature = DbSubject.suspectName + " \r\n\nSimilarity = " + (Similarities[j] * 100).ToString() + " Smile:" + Smile[j] * 100 + " Eyes Open: " + EyesOpen[j] * 100
+ " Male:" + Male[j] * 100 + " Female: " + Female[j] * 100;
Object[] row = new Object[] { img1, img2, feature };
this.dataGridView1.Invoke(new MethodInvoker(() =>
this.dataGridView1.Rows.Add(row)));
}
}
}
}
}
}
private void handleClients(object threadId)
{
int clientId = (int)threadId;
TcpClient tcpClient = tcpClients[clientId];
string remoteEndPoint = tcpClient.Client.RemoteEndPoint.ToString();
string clientIp = remoteEndPoint.Substring(0, remoteEndPoint.IndexOf(":"));
string clientPort = remoteEndPoint.Substring(remoteEndPoint.IndexOf(":") + 1);
add("Client " + remoteEndPoint + " connected");
//Client client = new Client("Client " + clientIp + " @ " + clientPort);
//client = new Client("Client " + clientIp + " @ " + clientPort);
// this.BeginInvoke((Action)(() => client.Show()));
NetworkStream stream = tcpClient.GetStream();
string clientData = string.Empty;
Byte[] bytes = new Byte[256];
int i;
bool init = false;
try
{
while ((i = stream.Read(bytes, 0, bytes.Length)) != 0)
{
if (!init)
{
clientData += Encoding.ASCII.GetString(bytes, 0, i);
}
if (clientData.Contains("<EOF>") && !init)
{
init = true;
string result = clientData.Substring(0, clientData.IndexOf("<EOF>"));
clientData = string.Empty;
byte[] imageBytes = Convert.FromBase64String(result);
MemoryStream ms = new MemoryStream(imageBytes, 0, imageBytes.Length);
ms.Position = 0;
Image img = Image.FromStream(ms);
//if (client == null || client.IsDisposed)
//{
// client = new Client("Client " + clientIp + " @ " + clientPort);
// this.BeginInvoke((Action)(() => client.Show()));
//}
//this.BeginInvoke((Action)(() => client.label1.Visible = false));
//this.BeginInvoke((Action)(() => client.pictureBox1.Image = img));
if (FaceList.Count == 0)
{
add("Please enroll faces first");
init = false;
}
else
{
TFaceRecord fr = new TFaceRecord();
fr.FacePosition = new FSDK.TFacePosition();
fr.FacialFeatures = new FSDK.TPoint[FSDK.FSDK_FACIAL_FEATURE_COUNT];
fr.Template = new byte[FSDK.TemplateSize];
fr.image = new FSDK.CImage(img);
//img.Dispose();
fr.FacePosition = fr.image.DetectFace();
if (0 == fr.FacePosition.w)
{
add("No faces found. Try to lower the Minimal Face Quality parameter in the Options dialog box.");
init = false;
}
else
{
fr.faceImage = fr.image.CopyRect((int)(fr.FacePosition.xc - Math.Round(fr.FacePosition.w * 0.5)), (int)(fr.FacePosition.yc - Math.Round(fr.FacePosition.w * 0.5)), (int)(fr.FacePosition.xc + Math.Round(fr.FacePosition.w * 0.5)), (int)(fr.FacePosition.yc + Math.Round(fr.FacePosition.w * 0.5)));
bool eyesDetected = false;
try
{
fr.FacialFeatures = fr.image.DetectEyesInRegion(ref fr.FacePosition);
eyesDetected = true;
}
catch
{
add("Detecting eyes failed.");
init = false;
}
if (eyesDetected)
{
fr.Template = fr.image.GetFaceTemplateInRegion(ref fr.FacePosition); // get template with higher precision
float Threshold = 0.0f;
FSDK.GetMatchingThresholdAtFAR(FARValue / 100, ref Threshold);
int MatchedCount = 0;
int FaceCount = FaceList.Count;
float[] Similarities = new float[FaceCount];
for (int x = 0; x < FaceList.Count; x++)
{
float Similarity = 0.0f;
TFaceRecord CurrentFace = FaceList[x];
FSDK.MatchFaces(ref fr.Template, ref CurrentFace.Template, ref Similarity);
if (Similarity >= Threshold)
{
Similarities[MatchedCount] = Similarity;
++MatchedCount;
}
}
if (MatchedCount != 0)
{
float finalResult = Similarities.Max();
if (finalResult * 100 < 95.0)
{
SendBackToClient(tcpClient, "R=NONE;");
add("No morethan 95.0% matches found in database faces");
//init = false;
}
else
{
int index = 0;
for (int x = 0; x < MatchedCount; x++)
{
if (Similarities[x] == finalResult)
{
index = x;
}
}
SendBackToClient(tcpClient, "R=" + FaceName[index]);
//init = false;
}
}
else
{
SendBackToClient(tcpClient, "R=NONE;");
add("No matches found. You can try to increase the FAR parameter in the Options dialog box.");
//init = false;
}
}
else
{
add("No eyes detected in photos.");
init = false;
}
}
}
}
else
{
if (clientData.Contains(";"))
{
string result = clientData.Substring(0, clientData.IndexOf(";"));
if (result == "OK")
{
init = false;
}
}
}
}
tcpClients.Remove(clientId);
tcpClient.Client.Shutdown(SocketShutdown.Both);
tcpClient.Client.Close();
tcpClient.Client.Dispose();
int idx = 0;
for (int x = 0; x < threadClients.Count(); x++)
{
if (threadClients[x].ManagedThreadId == clientId)
{
idx = x;
}
}
threadClients.RemoveAt(idx);
add("Client " + remoteEndPoint + " disconnected");
//if (client.Visible)
//{
// this.BeginInvoke((Action)(() => client.Close()));
//}
}
catch
{
add("Client " + remoteEndPoint + " error");
}
}
