public FaceDetection ConfigureDetection(NameValueCollection s)
{
var f = new FaceDetection();
//Parse min/max faces
int[] count = NameValueCollectionExtensions.GetList<int>(s,"f.faces",null,1,2);
if (count == null) {
f.MinFaces = 1;
f.MaxFaces = 8;
}else if (count.Length > 0){
f.MinFaces = f.MaxFaces = count[0];
if (count.Length > 1) f.MaxFaces = count[1];
}
//Parse min/default thresholds
int[] threshold = NameValueCollectionExtensions.GetList<int>(s,"f.threshold",null,1,2);
if (threshold != null && threshold.Length > 0){
f.MinConfidenceLevel = f.ConfidenceLevelThreshold = threshold[0];
if (threshold.Length > 1) f.ConfidenceLevelThreshold = threshold[1];
}
//Parse min size percent
f.MinSizePercent = NameValueCollectionExtensions.Get<float>(s,"f.minsize",f.MinSizePercent);
//Parse expandsion rules
double[] expand = NameValueCollectionExtensions.GetList<double>(s, "f.expand", null, 1, 2);
//Exapnd bounding box by requested percentage
if (expand != null) {
f.ExpandX = expand[0];
f.ExpandY = expand.Length > 1 ? expand[1] : expand[0];
}
return f;
}
/// <summary>
/// Initializes and assigns values to this class' data members.
/// </summary>
void Start()
{
mapGenerator = gameObject.GetComponent(typeof(MapGenerator)) as MapGenerator;
webcamController = gameObject.GetComponent(typeof(WebcamTextureController)) as WebcamTextureController;
chunkWidth = mapGenerator.MapChunkWidth - 1;
chunkHeight = mapGenerator.MapChunkHeight - 1;
_face = gameObject.GetComponent(typeof(FaceDetection)) as FaceDetection;
numChunkWidth = mapGenerator.NumChunkWidth;
numChunkHeight = mapGenerator.NumChunkHeight;
terrainChunkArray = new TerrainChunk[numChunkWidth, numChunkHeight];
InitializeChunks();
}
private Image <Bgr, byte> Question(Image <Bgr, byte> imageFrame)
{
try
{
if (imageFrame == null)
{
return(null);
}
// copy frame, for detection objects
var imgCommit = imageFrame.Copy(); //.Resize(300, 300, Inter.Linear, true);
imgCommit = imgCommit.Resize(300, 300, Inter.Linear, true);
// time elapsed
long timeElapsed = _qz.TQuestion.QStopWatch.ElapsedMilliseconds;
_qz.TQuestion.QStopWatchTimeDiv = timeElapsed - _qz.TQuestion.QStopWatchTime;
_qz.TQuestion.QStopWatchTime = timeElapsed;
// draw 3 parts
int w = imageFrame.Width / 3;
int h = imageFrame.Height;
//imageFrame._EqualizeHist();
var grayFrame = imageFrame.Convert <Gray, byte>();
var faces = FaceDetection.DetectMultiScale(grayFrame, 1.3, 5);
int index = 1;
foreach (var face in faces)
{
// face recognition - detect faces/answer
var result = QuestionFaceRecognition0(grayFrame, face);
// face recognition1 - detect quetion/answer
QuestionFaceRecognition1(imageFrame, w, face, result);
}
// cycle
QuestionCycle(imageFrame, imgCommit, w, h);
}
catch (Exception)
{
}
return(imageFrame);
}
private void Capture_ImageGrabbed(object sender, EventArgs e)
{
Frame = Capture.QueryFrame();
var imageFrame = Frame.ToImage <Bgr, byte>();
if (imageFrame != null)
{
var grayFrame = imageFrame.Convert <Gray, byte>();
var faces = FaceDetection.DetectMultiScale(grayFrame, 1.3, 5);
foreach (var face in faces)
{
CvInvoke.Rectangle(imageFrame, face, new MCvScalar(255, 0, 0, 255), 2);
}
imbWebcam.Image = imageFrame;
}
}
/// <summary>
/// The start method used by Unity.
/// This mostly contains calls to the various initializers for the different components used together to c
/// </summary>
private void Start()
{
webcamController = this.gameObject.GetComponent(typeof(WebcamTextureController)) as WebcamTextureController;
face = this.gameObject.GetComponent(typeof(FaceDetection)) as FaceDetection;
webcamController.Initialize();
this.InitializeMapSizes();
this.InitializeChunkSizes();
this.InitializeNumOfChunks();
this.fullNoiseMap = NoiseGenerator.GenerateNoiseMap(this.mapWidth, this.mapHeight, this.noiseData.seed, this.noiseData.noiseScale, this.noiseData.octaves, this.noiseData.persistance, this.noiseData.lacunarity, this.noiseData.offset, this.noiseData.normalizeMode);
this.textureData.ApplyToMaterial(this.terrainMaterial);
}
private void Timer_Tick(object sender, EventArgs e)
{
Frame = Capture.QueryFrame();
var imageFrame = Frame.ToImage <Gray, byte>();
if (TimerCounter < TimeLimit)
{
TimerCounter++;
if (imageFrame != null)
{
var faces = FaceDetection.DetectMultiScale(imageFrame, 1.3, 5);
if (faces.Length > 0)
{
var processImage = imageFrame.Copy(faces[0]).Resize(ProcessImageWidth, ProcessImageHeight, Inter.Cubic);
Faces.Add(processImage);
Labels.Add(Convert.ToInt32(txtUserId.Text));
ScanCounter++;
rtbOutPut.AppendText($"{ScanCounter} Success Scan Taken... {Environment.NewLine}");
rtbOutPut.ScrollToCaret();
}
}
}
else
{
var trainFaces = ConvertImageToMat(Faces);
foreach (var face in trainFaces)
{
DataStoreAccess.SaveFace(Convert.ToInt32(txtUserId.Text), txtUserName.Text, ConvertImageToBytes(face.Bitmap));
}
EigenFaceRecognizer.Train(trainFaces.ToArray(), Labels.ToArray());
EigenFaceRecognizer.Write(YMLPath);
Timer.Stop();
TimerCounter = 0;
btnPredict.Enabled = true;
rtbOutPut.AppendText($"Training Completed! {Environment.NewLine}");
MessageBox.Show("Training Completed!");
}
}
/// <summary>
/// Constructs a new eyes object.
/// </summary>
/// <param name="visionPreview">A capture element that is placed on a canvas used for capturing what Robbie sees.</param>
/// <param name="previewCanvas">A canvas element used for rendering the image preview showing what Robbie sees.</param>
public Eyes(CaptureElement visionPreview, Canvas previewCanvas)
{
Camera.Instance.Initialize(visionPreview);
this.previewCanvas = previewCanvas;
faceTracking = new FaceTracking();
faceDetection = new FaceDetection();
computerVision = new ComputerVision();
identityInterpolation = new IdentityInterpolation();
visualization = new Vision();
panTilt = new PanTilt();
eyesDisplay = new EyesDisplay();
identityInterpolation.LargestFaceChanged += IdentityInterpolation_LargestFaceChanged;
// fire up the continuous tasks of processing video and controlling the servos
ThreadPoolTimer.CreatePeriodicTimer(ProcessCurrentVideoFrame_Delegate, TimeSpan.FromMilliseconds(125)); // 8 fps
ThreadPoolTimer.CreatePeriodicTimer(UpdatePanTiltPosition_Delegate, TimeSpan.FromMilliseconds(25)); // 40 fps
ThreadPoolTimer.CreatePeriodicTimer(Blink_Delegate, TimeSpan.FromMilliseconds(5000)); // 12 fpm
}
private void Init()
{
_traking = LocatorFactory.GetTrackingLocator(AppId, FtKey) as FaceTracking;
_detection = LocatorFactory.GetDetectionLocator(AppId, FdKey) as FaceDetection;
_recognize = new FaceRecognize(AppId, FrKey);
_processor = new FaceProcessor(_traking, _recognize);
//init cache
if (Directory.Exists(FaceLibraryPath))
{
var files = Directory.GetFiles(FaceLibraryPath);
foreach (var file in files)
{
var info = new FileInfo(file);
_cache.Add(info.Name.Replace(info.Extension, ""), File.ReadAllBytes(file));
}
}
_pImage = Marshal.AllocHGlobal(1920 * 1080 * 3);
_image = new Bitmap(1920, 1080, 1920 * 3, PixelFormat.Format24bppRgb, _pImage);
var ffmpeg = new FFMpegConverter();
outputStream = new MemoryStream();
var setting =
new ConvertSettings
{
CustomOutputArgs = "-an -r 15 -pix_fmt bgr24 -updatefirst 1" //根据业务需求-r参数可以调整，取决于摄像机的FPS
}; //-s 1920x1080 -q:v 2 -b:v 64k
task = ffmpeg.ConvertLiveMedia("rtsp://*****:*****@192.168.1.64:554/h264/ch1/main/av_stream", null,
outputStream, Format.raw_video, setting);
task.OutputDataReceived += DataReceived;
task.Start();
_renderTask = new Task(Render);
_renderTask.Start();
}
private Image <Bgr, byte> TestGroup(Image <Bgr, byte> imageFrame)
{
try
{
if (imageFrame == null)
{
return(null);
}
var grayFrame = imageFrame.Convert <Gray, byte>();
var faces = FaceDetection.DetectMultiScale(grayFrame, 1.2, 5);
foreach (var face in faces)
{
var procImg = grayFrame.Copy(face).Resize(
_qz.TRF_IMAGE_WIDTH,
_qz.TRF_IMAGE_HEIGHT,
Emgu.CV.CvEnum.Inter.Cubic);
var result = _qz.QZGroupArr[_qz.QZTGroup.TGroupNbr].FaceRecoEigen.Predict(procImg);
try
{
imageFrame.Draw(face, new Bgr(Color.BurlyWood), 3);
imageFrame.Draw($"{_qz.QZFaceArr[result.Label].Name}", face.Location, Emgu.CV.CvEnum.FontFace.HersheyTriplex, 1.0, new Bgr(Color.Red));
// if (result.Distance > 1.0)
// imageFrame.Draw($"{_qz.QSet.Faces[result.Label].Name}", face.Location, Emgu.CV.CvEnum.FontFace.HersheyTriplex, 1.0, new Bgr(Color.Red));
}
catch (Exception)
{
}
}
}
catch (Exception)
{
}
return(imageFrame);
}
private void btnPredictFace_Click(object sender, EventArgs e)
{
WebCam.Retrieve(Frame);
var imageFrame = Frame.ToImage <Gray, byte>();
if (imageFrame != null)
{
var faces = FaceDetection.DetectMultiScale(imageFrame, 1.3, 5);
if (faces.Count() != 0)
{
foreach (var fc in faces)
{
var procImg = imageFrame.Copy(fc).Resize(ProcessImageWidth, ProcessImageHeight, Emgu.CV.CvEnum.Inter.Cubic);
var result = FaceRecognition.Predict(procImg);
if (result.Label.ToString() == "1")
{
//tbOutput.AppendText($"FACE {result.Label} {System.Environment.NewLine}");
//tbOutput.ScrollToCaret();
//imageFrame.Draw("CARL", new Point(faces[0].X, faces[0].Y), 2);
//imageFrame.Draw("dd",)
// }
}
}
}
else
{
//tbOutput.AppendText($"????? {System.Environment.NewLine}");
}
}
else
{
//tbOutput.AppendText($"????? {System.Environment.NewLine}");
}
}
private void WebCam_ImageGrabbed(object sender, EventArgs e)
{
WebCam.Retrieve(Frame);
var imageFrame = Frame.ToImage <Bgr, byte>();
if (imageFrame != null)
{
var grayFrame = imageFrame.Convert <Gray, byte>();
var faces = FaceDetection.DetectMultiScale(grayFrame, 1.3, 5);
foreach (var face in faces)
{
imageFrame.Draw(face, new Bgr(Color.BurlyWood), 3);
try
{
var procImg = grayFrame.Copy(face).Resize(ProcessImageWidth, ProcessImageHeight, Emgu.CV.CvEnum.Inter.Cubic);
if (_qz2018.FrmTrain != null)
{
_qz2018.FrmTrain.SetPicture(1, procImg);
}
//imageBox1.Image = procImg;
var result = FaceRecognition.Predict(procImg);
imageFrame.Draw($"<{result.Label}>", face.Location, Emgu.CV.CvEnum.FontFace.HersheyTriplex, 1.0, new Bgr(Color.Red));
}
catch (Exception ex)
{
}
}
//imageWebCam.Image = imageFrame;
}
}
private void Timer_Tick(object sender, EventArgs e)
{
Camera.Retrieve(Frame);
var ImgFrame = Frame.ToImage <Gray, byte>();
if (TimerCounter < TimeLimit)
{
TimerCounter++;
if (ImgFrame != null)
{
var faces = FaceDetection.DetectMultiScale(ImgFrame, 1.3, 5);
if (faces.Count() > 0)
{
var processedImage = ImgFrame.Copy(faces[0]).Resize(ProcessedImageWidth, ProcessedImageHeight, Emgu.CV.CvEnum.Inter.Cubic);
Faces.Add(processedImage);
Ids.Add(Convert.ToInt32(IdBox.Text));
ScanCounter++;
OutputBox.AppendText($"{ScanCounter} Succesful Scans Taken...{Environment.NewLine}");
OutputBox.ScrollToCaret();
}
}
}
else
{
FacialRecognition.Train(Faces.ToArray(), Ids.ToArray());
FacialRecognition.Write(YMLPath);
Timer.Stop();
TimerCounter = 0;
btnTrain.Enabled = !btnTrain.Enabled;
IdBox.Enabled = !IdBox.Enabled;
OutputBox.AppendText($"Training Complete! {Environment.NewLine}");
MessageBox.Show("Training Complete");
}
}
/// <summary>
/// 注册事件触发函数
/// </summary>
/// <param name="sender"></param>
/// <param name="args">变量参数</param>
public static void NewUserRegist(object sender, myEventArgs.RegistArgs args)
{
/****************************
* 保存特征值时才区分性别
* **************************/
//下载图片到本地
String url = String.Format("{0}/{1}_{2}.{3}",
Url_DldImg, args.Regist.Id, args.Regist.Name, args.Regist.Extension);
String pathImg = String.Format("{0}\\{1}_{2}.{3}",
ImgRootPath_Regist, args.Regist.Id, args.Regist.Name, args.Regist.Extension);
HttpUtil.downFile(url, pathImg);
//判断性别（假设性别判断 100% 准确）
try
{
ResultCode result = EngineActivate.ActivateEngine(APPID, APPKEY);
if (result != ResultCode.SDK已激活)
{
Console.WriteLine(result.ToString());
return;
}
IntPtr hengine = EngineFactory.GetEngineInstance(EngineFactory.Image,
DetectionOrientPriority.ASF_OP_0_ONLY, 16); //检测角度指人脸在照片中的角度
Bitmap img1 = new Bitmap(pathImg);
var face = new FaceDetection(hengine, img1);
var r = face.GetGender();
LocalUserMod temp1 = new LocalUserMod();
temp1.Name = args.Regist.Name;
temp1.Num = args.Regist.Id;
//用Base64转码
temp1.Freature = Convert.ToBase64String(face.getFaceFeature(img1));
//销毁图片
img1.Dispose();
//提取特征值保存
switch (r)
{
case "男":
XmlUtil.AddOneData(temp1, "Male");
break;
case "女":
XmlUtil.AddOneData(temp1, "Female");
break;
default:
Console.WriteLine("获取性别失败！用户：{0} , 学号：{1}，注册时间：{2}",
args.Regist.Name, args.Regist.Id, DateTime.Now.ToString());
return;
}
//提示用户注册
Console.WriteLine("User registed: {0} at {1}", args.Regist.Name, DateTime.Now.ToString());
//更新用户信息
//令写一个函数
getAllUserInfo();
}
catch (Exception ex)
{
Console.WriteLine("Regist Error: {0}", ex.Message);
}
finally
{
EngineFactory.DisposeEngine();
}
}
void Awake()
{
instance = this;
Eyes = GameObject.Find("Eye").transform;
Eyes.position = transform.position + Vector3.forward * distanceEye;
}
protected static List <IPrediction> DeserializePredictions(ModelType modelType,
dynamic jsonObject)
{
var propertyValues = (JObject)jsonObject.data;
var data = new List <IPrediction>();
if (propertyValues.Count > 0)
{
string typeName = modelType.Prediction.Name;
switch (typeName)
{
case "Color":
{
foreach (dynamic color in jsonObject.data.colors)
{
data.Add(Color.Deserialize(color));
}
break;
}
case "Concept":
{
foreach (dynamic concept in jsonObject.data.concepts)
{
data.Add(Concept.Deserialize(concept));
}
break;
}
case "Demographics":
{
foreach (dynamic demographics in jsonObject.data.regions)
{
data.Add(Demographics.Deserialize(demographics));
}
break;
}
case "Embedding":
{
foreach (dynamic embedding in jsonObject.data.embeddings)
{
data.Add(Embedding.Deserialize(embedding));
}
break;
}
case "FaceConcepts":
{
foreach (dynamic faceConcepts in
jsonObject.data.regions)
{
data.Add(FaceConcepts.Deserialize(faceConcepts));
}
break;
}
case "FaceDetection":
{
foreach (dynamic faceDetection in jsonObject.data.regions)
{
data.Add(FaceDetection.Deserialize(faceDetection));
}
break;
}
case "FaceEmbedding":
{
foreach (dynamic faceEmbedding in jsonObject.data.regions)
{
data.Add(FaceEmbedding.Deserialize(faceEmbedding));
}
break;
}
case "Focus":
{
foreach (dynamic focus in jsonObject.data.regions)
{
data.Add(Focus.Deserialize(focus,
(decimal)jsonObject.data.focus.value));
}
break;
}
case "Frame":
{
foreach (dynamic frame in jsonObject.data.frames)
{
data.Add(Frame.Deserialize(frame));
}
break;
}
case "Logo":
{
foreach (dynamic logo in jsonObject.data.regions)
{
data.Add(Logo.Deserialize(logo));
}
break;
}
default:
{
throw new ClarifaiException(
string.Format("Unknown output type `{0}`", typeName));
}
}
}
return(data);
}
private async Task <FaceDetection> DetectFacesAsync(MediaFile inputFile)
{
if (!CrossConnectivity.Current.IsConnected)
{
await DisplayAlert("Network error", "Please check your network connection and retry.", "OK");
return(null);
}
// The list of Face attributes to return.
IEnumerable <FaceAttributeType> faceAttributes = new FaceAttributeType[]
{
FaceAttributeType.Gender,
FaceAttributeType.Age,
FaceAttributeType.Smile,
FaceAttributeType.Emotion,
FaceAttributeType.Glasses,
FaceAttributeType.FacialHair,
FaceAttributeType.HeadPose,
};
try
{
// Call the Face API.
Face[] faces = await faceServiceClient.DetectAsync(
inputFile.GetStream(),
returnFaceId : true,
returnFaceLandmarks : false,
returnFaceAttributes : faceAttributes);
if (faces.Length == 0)
{
return(null);
}
// Get highest rated emotion
var emotion = faces[0].FaceAttributes.Emotion.ToRankedList();
FaceDetection theData = new FaceDetection()
{
Age = faces[0].FaceAttributes.Age,
Beard = faces[0].FaceAttributes.FacialHair.Beard,
Emotion = emotion.FirstOrDefault().Key,
Gender = faces[0].FaceAttributes.Gender,
Glasses = faces[0].FaceAttributes.Glasses.ToString(),
Moustache = faces[0].FaceAttributes.FacialHair.Moustache,
Smile = faces[0].FaceAttributes.Smile
};
this.BindingContext = theData;
this.Indicator1.IsRunning = false;
this.Indicator1.IsVisible = false;
return(theData);
}
catch (FaceAPIException f)
{
await DisplayAlert("Network error", f.ErrorMessage, "OK");
return(null);
}
catch (Exception e)
{
await DisplayAlert("Error", e.Message, "OK");
return(null);
}
}
public async Task <MemeberFaceUploadResult> UploadReplacementPhoto()
{
Member _memberRec; string oldFace = "";
string stringMemberId, subPath;
int intMemberId;
FileInfo fileInfo = null;
FaceDetection.FaceDetetctResult faceRes = new FaceDetection.FaceDetetctResult();
try
{
var streamProvider = new CustomMultipartFormDataStreamProvider(ServerUploadFolder);
await Request.Content.ReadAsMultipartAsync(streamProvider);
fileInfo = new FileInfo(streamProvider.FileData.Select(entry => entry.LocalFileName).FirstOrDefault());
if (fileInfo == null)
{
throw (new Exception("Cannot fine uploaded file"));
}
stringMemberId = streamProvider.FormData["MemberId"];
if (string.IsNullOrEmpty(stringMemberId))
{
if (File.Exists(fileInfo.FullName))
{
File.Delete(fileInfo.FullName);
}
return(new MemeberFaceUploadResult
{
IsAddOk = false,
FileNames = string.Empty,
ErrorMsg = "MemberId is missing",
FacesDetected = faceRes.FacesDetected,
IsFaceDetectionOk = faceRes.Outcome
});
}
intMemberId = Convert.ToInt32(stringMemberId);
_memberRec = _memberSvc.FindMember(User.Identity.Name, intMemberId);
if (_memberSvc == null)
{
if (File.Exists(fileInfo.FullName))
{
File.Delete(fileInfo.FullName);
}
return(new MemeberFaceUploadResult
{
IsAddOk = false,
FileNames = string.Empty,
ErrorMsg = "Unauthorized Access",
FacesDetected = faceRes.FacesDetected,
IsFaceDetectionOk = faceRes.Outcome
});
}
// recraete the stream with subpath gotten from member retrieved
subPath = intMemberId.ToString();
File.Move(fileInfo.FullName, ServerUploadFolder + subPath + "\\" + fileInfo.Name);
oldFace = _memberRec.FaceImage;
//---------------------------- open cv routine to do face detection -------------------------------
faceRes = FaceDetection.DetectFaceSave(fileInfo.Name, ServerUploadFolder + subPath, "", ServerBinFolder, fileInfo.Extension);
if (faceRes.Outcome)
{
//-------------------Face detection successful and continue ----------------------------
_memberRec.IsFaceDetected = faceRes.FacesDetected > 0 ? true : false;
_memberRec.IsFaceTagged = true;
_memberRec.FaceImage = faceRes.FacesDetected > 0 ? faceRes.FaceImages.FirstOrDefault() : null;
_memberRec.AbsoultePath = ServerUploadFolder + subPath + "\\";
_memberRec.DetectedFaceImage = faceRes.FacesDetected > 0 ? faceRes.SuperImposedImage : fileInfo.Name;
_memberRec.AllDetectedFaceImages = faceRes.GetAllFaceImageNames();
_memberRec.UnDetectedFaceImage = fileInfo.Name;
_memberRec.DetectedFaceCount = faceRes.FacesDetected;
_memberRec.FolderPath = "/UserContent/Member/" + subPath + "/";
_memberRec.OriginalFaceFileName = streamProvider.GetOriginalFileName;
_memberRec.FaceDetectionRemarks = faceRes.Remarks();
if (_memberRec.FaceImage != null)
{
int count = _memberSvc.UpdateMemberReplaceFace(_memberRec, _memberRec.FaceImage, oldFace);
}
else
{
_memberSvc.Update(_memberRec);
}
}
else
{
_memberRec.IsFaceDetected = false;
_memberRec.IsFaceTagged = false;
_memberRec.DetectedFaceCount = faceRes.FacesDetected;
_memberRec.AbsoultePath = ServerUploadFolder + subPath + "\\";
_memberRec.DetectedFaceImage = fileInfo.Name;
_memberRec.UnDetectedFaceImage = fileInfo.Name;
_memberRec.FolderPath = "/UserContent/Member/" + subPath + "/";
_memberRec.OriginalFaceFileName = streamProvider.GetOriginalFileName;
_memberRec.FaceDetectionRemarks = String.IsNullOrEmpty(faceRes.ErrorMsg) ? "Some Exception" : faceRes.ErrorMsg;
_memberSvc.Update(_memberRec);
}
return(new MemeberFaceUploadResult
{
IsAddOk = true,
FileNames = streamProvider.FileData.Select(entry => entry.LocalFileName).FirstOrDefault(),
ErrorMsg = !faceRes.Outcome ? faceRes.ErrorMsg : faceRes.Remarks(),
UpdatedTimestamp = DateTime.UtcNow,
FacesDetected = faceRes.FacesDetected,
MemberId = _memberRec.Key.ToString(),
IsFaceDetectionOk = faceRes.Outcome
});
}
catch (Exception ex)
{
if (fileInfo != null)
{
if (File.Exists(fileInfo.FullName))
{
File.Delete(fileInfo.FullName);
}
}
return(new MemeberFaceUploadResult
{
IsAddOk = false,
FileNames = string.Empty,
ErrorMsg = ex.Message,
FacesDetected = faceRes.FacesDetected,
IsFaceDetectionOk = faceRes.Outcome,
UpdatedTimestamp = DateTime.UtcNow
});
}
}
/// <summary>
/// Get and save metadata of all files from input folder
/// </summary>
/// <param name="folderPath"></param>
/// <param name="appStartPath"></param>
public void SaveMetadataOfAllImages(string folderPath, string appStartPath)
{
try
{
_blobWrapper = new DataUpload();
_faceDetection = new FaceDetection(appStartPath);
_imgGrabber = new ImageGrabber();
DirectoryInfo directory = new DirectoryInfo(folderPath);
List<DataLayer.EntityModel.Image> imageList = new List<DataLayer.EntityModel.Image>();
String[] files = GetFilesFrom(folderPath, imageFilters,true);
List<string> fileNameList = new List<string>();
fileNameList = GetUniqueImages(files.ToList());
foreach (var fileObj in fileNameList)
{
//Get metadata of file and save it
imageList.Add(GetImageMetadata(fileObj, appStartPath));
//Upload file to file to azure blob
_blobWrapper.UploadFile(fileObj);
}
new DataLayer.ModelClasses.Image().SaveUpdateMetadata(imageList);
}
catch (Exception ex)
{
throw;
}
}
/// <summary>
/// Get and save metadata of file
/// </summary>
/// <param name="filePath"></param>
/// <param name="appStartPath"></param>
public void SaveMetadataOfImage(string filePath, string appStartPath)
{
try
{
_blobWrapper = new DataUpload();
_faceDetection = new FaceDetection(appStartPath);
_imgGrabber = new ImageGrabber();
List<DataLayer.EntityModel.Image> imageList = new List<DataLayer.EntityModel.Image>();
String[] files = new string[1];
files[0] = filePath;
List<string> fileNameList = new List<string>();
fileNameList = GetUniqueImages(files.ToList());
foreach (var fileObj in fileNameList)
{
//Get metadata of file and save it
imageList.Add(GetImageMetadata(fileObj, appStartPath));
//Upload file to file to azure blob
_blobWrapper.UploadFile(fileObj);
}
new DataLayer.ModelClasses.Image().SaveUpdateMetadata(imageList);
}
catch (Exception)
{
throw;
}
}
/// <summary>
/// Reason : TO detect face on selected image, if face(s) detect then mark it in box
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void btnFaceDetect_Click(object sender, EventArgs e)
{
if (!IsMediaFile(txtFilePath.Text.ToString().Trim(), imageExtensions))
{
MessageBox.Show("Please select valid Image file!!");
return;
}
ShowLoader();
_faceDetection = new FaceDetection(appStartPath);
_faceDetection.DetectFace(appStartPath, txtFilePath.Text.ToString(), ref noOfFaces, ref newFrame);
HideLoader();
pbImage.Image = newFrame;
pbImage.SizeMode = PictureBoxSizeMode.StretchImage;
pbImage.BringToFront();
MessageBox.Show("Selected Image contains "+ noOfFaces +" faces.");
}
/// <summary>
/// reason : To show all frames of video in panel
/// </summary>
/// <param name="files"></param>
/// <param name="imageName"></param>
private void ShowAllFramesOnPanel(FileInfo[] files,string imageName)
{
flowLayoutPanel1.BringToFront();
try
{
PictureBox[] pics = new PictureBox[files.Count()];
FlowLayoutPanel[] flws = new FlowLayoutPanel[files.Count()];
Label[] lbl = new Label[files.Count()];
_faceDetection = new FaceDetection(appStartPath);
int brh = 0;
for (int i = 0; i < files.Count(); i++)
{
if (!File.Exists(files[i].FullName))
continue;
noOfFaces = 0;
newFrame = null;
_faceDetection.DetectFace(appStartPath, files[i].FullName, ref noOfFaces, ref newFrame);
flws[i] = new FlowLayoutPanel();
flws[i].Name = "flw" + i;
flws[i].Location = new Point(3, brh);
flws[i].Size = new Size(217, 210);
flws[i].BackColor = Color.DarkCyan;
flws[i].BorderStyle = BorderStyle.Fixed3D;
lbl[i] = new Label();
lbl[i].Name = files[i].Name;
lbl[i].Size = new Size(100, 35);
lbl[i].Text = "Frame " + i + " Contains " + noOfFaces + " Face(s)";
pics[i] = new PictureBox();
pics[i].Name = files[i].FullName;
pics[i].Size = new Size(217, 175);
pics[i].Image = newFrame==null? System.Drawing.Image.FromFile(files[i].FullName): newFrame;
pics[i].SizeMode = PictureBoxSizeMode.StretchImage;
flws[i].Controls.Add(lbl[i]);
flws[i].Controls.Add(pics[i]);
this.Controls.Add(flws[i]);
flowLayoutPanel1.Controls.Add(flws[i]);
}
}
catch(Exception)
{
}
}
/// <summary>
/// 做扫描识别
/// </summary>
/// <param name="path"></param>
private static void doScan(String path)
{
ResultCode result = EngineActivate.ActivateEngine(APPID, APPKEY);
if (result != ResultCode.SDK已激活)
{
Console.WriteLine(result.ToString());
return;
}
IntPtr hengine = EngineFactory.GetEngineInstance(EngineFactory.Image,
DetectionOrientPriority.ASF_OP_0_ONLY, 16);
FaceDetection face = new FaceDetection(hengine);
DirectoryInfo root = new DirectoryInfo(path);
//获取所有下载的图片开始识别
List <FileInfo> Filelist = root.GetFiles("*.jpeg").ToList();
Bitmap img = null;
foreach (FileInfo file in Filelist) //外层是文件
{
try
{
img = new Bitmap(file.FullName);
foreach (LocalUserMod mod in allRegUsers) //内层是用户
{
try
{
//此人已被识别，不做识别
if (resultSend[mod.Name].isScaned) //如果已经查找了这个人
{
continue;
}
byte[] f1 = Convert.FromBase64String(mod.Freature);
byte[] f2 = face.getFaceFeature(img);
float sim = face.Compare(f1, f2);
if (sim >= Similarity)
{
//获取3D角度
FaceDetection.TDAResult tdr = face.GetThreeDAngle(img);
Console.WriteLine("Name: {0}\nThreeDAngle: {1}", mod.Name, tdr.ToString());
//判断角度
//更改状态
if (tdr.Pitch <= -13) //低头角度
{
resultSend[mod.Name].Status = 1; //低头
}
else if (tdr.Yaw <= -26 || tdr.Yaw >= 26)
{
resultSend[mod.Name].Status = 2; //左右
}
else
{
resultSend[mod.Name].Status = 3; //认真
}
//标识已扫描
resultSend[mod.Name].isScaned = true;
//上传文件到前端
HttpUtil.postFile(Url_PostImg, file.FullName);
continue;
}
}
catch (Exception ex)
{
Console.WriteLine("Error in scanning! {0}", ex.Message);
continue;
}
//未识别出
Console.WriteLine("Cannot distinguish : {0}", file.Name);
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
continue;
}
finally
{
//释放图片资源
if (img != null)
{
img.Dispose();
}
}
}
try
{
String datas = JsonConvert.SerializeObject(resultSend);
//post数据到前端
HttpUtil.postData(Url_PostData, datas);
//销毁引擎
EngineFactory.DisposeEngine();
Console.WriteLine("Scan over......");
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
return;
}
}
public async Task <MemeberFaceUploadResult> UploadMemberandFace()
{
Member _memberRec = new Member();
FileInfo fileInfo;
FaceDetection.FaceDetetctResult faceRes = new FaceDetection.FaceDetetctResult();
try
{
//--- insert record in to Member table and create a directory - before reading the file -------------
_memberRec.Name = "Name";
_memberRec.DisplayName = "DisplayName";
_memberRec.DateOfBirth = DateTime.ParseExact("15/08/1947", "dd/MM/yyyy", CultureInfo.InvariantCulture);
_memberRec.Relation = "Relation";
_memberRec.IsActive = true;
_memberRec.IsFaceDetected = false;
_memberRec.IsFaceTagged = false;
_memberRec.Created = DateTime.Now;
_memberRec.UserKey = _userSvc.UserDetails(User.Identity.Name).Key;
_memberSvc.Insert(_memberRec);
string subPath = _memberRec.Key.ToString(); // your code goes here
bool exists = System.IO.Directory.Exists(ServerUploadFolder + subPath);
if (!exists)
{
System.IO.Directory.CreateDirectory(ServerUploadFolder + subPath);
}
//-------------------------------------------------------------------------------------------------------
var streamProvider = new CustomMultipartFormDataStreamProvider(ServerUploadFolder + subPath);
await Request.Content.ReadAsMultipartAsync(streamProvider);
fileInfo = new FileInfo(streamProvider.FileData.Select(entry => entry.LocalFileName).FirstOrDefault());
//---------------------------- open cv routine to do face detection -------------------------------
faceRes = FaceDetection.DetectFaceSave(fileInfo.Name, ServerUploadFolder + subPath, "", ServerBinFolder, fileInfo.Extension);
if (faceRes.Outcome)
{
//-------------------Face detection successful and continue ----------------------------
_memberRec.Name = streamProvider.FormData["Name"];
_memberRec.DisplayName = streamProvider.FormData["DisplayName"];
_memberRec.DateOfBirth = DateTime.ParseExact(streamProvider.FormData["DateOfBirth"], "dd/MM/yyyy", CultureInfo.InvariantCulture);
_memberRec.Relation = streamProvider.FormData["Relation"];
_memberRec.IsFaceDetected = faceRes.FacesDetected > 0 ? true: false;
_memberRec.IsFaceTagged = true;
_memberRec.FaceImage = faceRes.FacesDetected > 0 ? faceRes.FaceImages.FirstOrDefault() : null;
_memberRec.AbsoultePath = ServerUploadFolder + subPath + "\\";
_memberRec.DetectedFaceImage = faceRes.FacesDetected > 0 ? faceRes.SuperImposedImage : fileInfo.Name;
_memberRec.AllDetectedFaceImages = faceRes.GetAllFaceImageNames();
_memberRec.UnDetectedFaceImage = fileInfo.Name;
_memberRec.DetectedFaceCount = faceRes.FacesDetected;
_memberRec.FolderPath = "/UserContent/Member/" + subPath + "/";
_memberRec.OriginalFaceFileName = streamProvider.GetOriginalFileName;
_memberRec.FaceDetectionRemarks = faceRes.Remarks();
if (faceRes.FacesDetected > 0)
{
_memberSvc.UpdateMemberAddFace(_memberRec, faceRes.FaceImages.FirstOrDefault());
}
else
{
_memberSvc.Update(_memberRec);
}
}
else
{
_memberRec.Name = streamProvider.FormData["Name"];
_memberRec.DisplayName = streamProvider.FormData["DisplayName"];
_memberRec.DateOfBirth = DateTime.ParseExact(streamProvider.FormData["DateOfBirth"], "dd/MM/yyyy", CultureInfo.InvariantCulture);
_memberRec.Relation = streamProvider.FormData["Relation"];
_memberRec.IsFaceDetected = false;
_memberRec.IsFaceTagged = false;
_memberRec.DetectedFaceCount = faceRes.FacesDetected;
_memberRec.AbsoultePath = ServerUploadFolder + subPath + "\\";
_memberRec.DetectedFaceImage = fileInfo.Name;
_memberRec.UnDetectedFaceImage = fileInfo.Name;
_memberRec.FolderPath = "/UserContent/Member/" + subPath + "/";
_memberRec.OriginalFaceFileName = streamProvider.GetOriginalFileName;
_memberRec.FaceDetectionRemarks = String.IsNullOrEmpty(faceRes.ErrorMsg) ? "Some Exception" : faceRes.ErrorMsg;
_memberSvc.Update(_memberRec);
}
return(new MemeberFaceUploadResult
{
IsAddOk = true,
FileNames = streamProvider.FileData.Select(entry => entry.LocalFileName).FirstOrDefault(),
ErrorMsg = !faceRes.Outcome ? faceRes.ErrorMsg : faceRes.Remarks(),
UpdatedTimestamp = DateTime.UtcNow,
FacesDetected = faceRes.FacesDetected,
MemberId = _memberRec.Key.ToString(),
IsFaceDetectionOk = faceRes.Outcome
});
}
catch (Exception ex)
{
if (_memberRec.Key > 0)
{
_memberSvc.Delete(_memberRec);
}
return(new MemeberFaceUploadResult
{
IsAddOk = false,
FileNames = string.Empty,
ErrorMsg = ex.Message,
FacesDetected = faceRes.FacesDetected,
IsFaceDetectionOk = faceRes.Outcome
});
}
}
/// <summary>
/// Reason : To get all similar files from folder with percentage of similarity for selected file.
/// compare files from folder which are having length of file +- 100000 of original file.
/// </summary>
/// <param name="inputFilePath">Input file path of image</param>
/// <param name="length">Length of image file that varies to compare with another file</param>
/// <param name="percentageString"> returns percentage of similarities of matched images in string seperated by comma(,)</param>
public void GetAllSimilarImages(string inputFilePath,string appStartPath, double length, ref List<DuplicateImageDetails> duplicateImageList)
{
{
try
{
DuplicateImageDetails imgOriginalFile = new DuplicateImageDetails();
imgOriginalFile.FilePath = inputFilePath;
imgOriginalFile.FileName = inputFilePath.Contains("\\") ? inputFilePath.Split('\\')[inputFilePath.Split('\\').Count() - 1] : inputFilePath;
imgOriginalFile.Percentage = "Original Selected File";
duplicateImageList.Add(imgOriginalFile);
int count = 0;
FileInfo fileInfo = new FileInfo(inputFilePath);
DataLayer.EntityModel.Image metadataInputImgObj = new DataLayer.EntityModel.Image();
//Get metadata of input file
_faceDetection = new FaceDetection(appStartPath);
_imgGrabber = new ImageGrabber();
metadataInputImgObj = GetImageMetadata(inputFilePath, appStartPath);
var bestMatchImageList = new DataLayer.ModelClasses.Image().GetImagesByBestMatch(metadataInputImgObj);
// for Image similarity percentage need to compare both images
foreach (var infoObj in bestMatchImageList)
{
DuplicateImageDetails duplicateImageCheck = new DuplicateImageDetails();
duplicateImageCheck.FilePath = infoObj.ImagePath;
duplicateImageCheck.FileName = infoObj.ImagePath.Contains("\\") ? infoObj.ImagePath.Split('\\')[infoObj.ImagePath.Split('\\').Count() - 1] : infoObj.ImagePath;
duplicateImageCheck.Percentage = "";
duplicateImageList.Add(duplicateImageCheck);
count++;
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
}
