public AnnotationsFetcher(FaceProcessor faceProcessor, string servicePrefix, string instance)
{
faceProcessor_ = faceProcessor;
serviceInstance_ = instance;
serviceNamespace = new Namespace(new Name(servicePrefix));
serviceNamespace.setFace(faceProcessor.getFace());
}
/// <summary>
/// Enables the input of the webcam
/// </summary>
public static bool EnableWebcam(string cameraUrl = null)
{
IVideoSource capture;
try
{
if (cameraUrl == null)
{
capture = new VideoCaptureDevice(
new FilterInfoCollection(FilterCategory.VideoInputDevice)[0].MonikerString);
}
else //assumes that it's a MJPEG stream, it's forms so whatever
{
capture = new MJPEGStream(cameraUrl);
}
source = new ProcessableVideoSource(capture);
}
catch (Exception e)
{
Console.WriteLine(e);
MessageBox.Show(Messages.cameraNotFound);
return(false);
}
processor = new FaceProcessor(source);
processor.Start();
source.NewFrame += GetFrame;
source.Start();
return(true);
}
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));
}
}
CvInvoke.UseOpenCL = false;
_capture = GetWebCamera();
_capture.Start();
//Application.Idle += VideoCaptured; //可以采用此方式捕获视频，则无需单独开线程
//_capture.ImageGrabbed += VideoCaptured; //不要采用此方式
_run = new Task(VideoCaptured);
_run.Start();
}
public async Task <ActionResult> CheckImage()
{
if (System.Web.HttpContext.Current.Request.Files.AllKeys.Any())
{
var pic = System.Web.HttpContext.Current.Request.Files["Image"];
Image image = Image.FromStream(pic.InputStream);
using (var uploadedImage = HelperMethods.ProcessImage(new Bitmap(image)))
{
FrameAnalysisJSON result = await FaceProcessor.ProcessFrame(new Bitmap(uploadedImage));
if (result == null || result.Faces.Count == 0)
{
return(Json(new { result = new List <CroppedFace>() }
, JsonRequestBehavior.AllowGet));
}
List <CroppedFace> croppedFaces = new List <CroppedFace>();
foreach (var face in result.CroppedFaces(uploadedImage, 25))
{
croppedFaces.Add(face);
}
return(Json(new { result = croppedFaces }
, JsonRequestBehavior.AllowGet));
}
}
return(null);
}
private void Init()
{
_age = new FaceAge(AppId, AgeKey);
_gender = new FaceGender(AppId, GenderKey);
_traking = LocatorFactory.GetTrackingLocator(AppId, FtKey, _age, _gender) 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));
}
}
stride = width * pixelSize;
bufferSize = stride * height;
_pImage = Marshal.AllocHGlobal(bufferSize);
_image = new Bitmap(width, height, stride, PixelFormat.Format24bppRgb, _pImage);
var ffmpeg = new FFMpegConverter();
outputStream = new MemoryStream();
var setting =
new ConvertSettings
{
CustomOutputArgs = "-s 1920x1080", //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
//-an -r 15 -pix_fmt bgr24 -updatefirst 1
//task = ffmpeg.ConvertLiveMedia("rtsp://*****:*****@192.168.1.64:554/h264/ch1/main/av_stream", null,
// outputStream, Format.raw_video, setting);
/*
* USB摄像头捕获
* 通过ffmpeg可以捕获USB摄像，如下代码所示。
* 首先通过：ffmpeg -list_devices true -f dshow -i dummy命令，可以列出系统中存在的USB摄像设备（或通过控制面板的设备管理工具查看设备名称），例如在我电脑中叫USB2.0 PC CAMERA。
* 然后根据捕获的分辨率，修改视频图形信息，包括width和height，一般像素大小不用修改，如果要参考设备支持的分辨率，可以使用：
* ffmpeg -list_options true -f dshow -i video="USB2.0 PC CAMERA"命令
*/
task = ffmpeg.ConvertLiveMedia("video=Logitech HD Webcam C270", "dshow",
outputStream, Format.raw_video, setting);
task.OutputDataReceived += DataReceived;
task.Start();
_renderTask = new Task(Render);
_renderTask.Start();
}
//this should probably return action result, otherwise nothing will happen in the frontend IIRC
public async Task <ActionResult> CaptureSnapshot(string imgBase64, string latitude, string longitude)
{
FaceApiCalls apiCalls = new FaceApiCalls(new HttpClientWrapper());
// Prepare base64 string
imgBase64 = imgBase64.Substring(imgBase64.IndexOf("base64,", StringComparison.Ordinal) + 7);
imgBase64 = imgBase64.Substring(0, imgBase64.LastIndexOf("\"", StringComparison.Ordinal));
imgBase64 = imgBase64.Replace(" ", "+");
// Create a bitmap
byte[] bitmapData = Convert.FromBase64String(FixBase64ForImage(imgBase64));
System.IO.MemoryStream streamBitmap = new System.IO.MemoryStream(bitmapData);
Bitmap bitmap = new Bitmap((Bitmap)Image.FromStream(streamBitmap));
bitmap = HelperMethods.ProcessImage(bitmap);
// Analyze bitmap
FrameAnalysisJSON analysisResult = await FaceProcessor.ProcessFrame(bitmap);
if (analysisResult == null)
{
//error must've occured, should alert user.
return(null);
}
if (analysisResult.Faces.Count == 0)
{
return(Json(new { result = "No faces have been found in the provided picture" }, JsonRequestBehavior.AllowGet));
}
var biggestConfidence = LikelinessConfidence.LowProbability;
foreach (var face in analysisResult.Faces)
{
var searchResult = await apiCalls.SearchFaceInFaceset(face.Face_token);
if (searchResult != null)
{
foreach (var likelinessResult in searchResult.LikelinessConfidences()) //might want to set the camera properties to some value.
{
biggestConfidence = (likelinessResult.Confidence > biggestConfidence)
? likelinessResult.Confidence
: biggestConfidence;
await SearchResultHandler.HandleOneResult(result : likelinessResult,
minimumConfidence : LikelinessConfidence.VeryHighProbability,
cameraProperties : new CameraProperties(Convert.ToDouble(latitude), Convert.ToDouble(longitude)));
}
}
}
return
(Json(new
{ result =
string.Format("There's a {0} probability that the person/people from your picture are currently missing. Thank you for the submission, appropriate actions will be taken.",
biggestConfidence.ToPrettyString()) }, JsonRequestBehavior.AllowGet));
}
void Start()
{
TextureReaderComponent.OnImageAvailableCallback += OnImageAvailable;
//timestamp = gameObject.GetComponent<TangoARScreen> ().m_screenUpdateTime;
frameMgr = GameObject.FindObjectOfType <FramePoolManager>();
frameNumber = 0;
//frameObjects = new Dictionary<long, FrameObjectData> ();
boxMgr = GameObject.FindObjectOfType <BoundingBoxPoolManager>();
timestamp = 0;
frameBuffer = new ConcurrentQueue <Dictionary <int, FrameObjectData> > ();
boundingBoxBufferToCalc = new ConcurrentQueue <BoxData> ();
boundingBoxBufferToUpdate = new ConcurrentQueue <CreateBoxData> ();
boxData = new List <CreateBoxData> ();
// frameObjectBuffer = new RingBuffer<FrameObjectData> (100000);
// boxBufferToCalc = new RingBuffer<BoxData> (100000);
// boxBufferToUpdate = new RingBuffer<CreateBoxData> (100000);
camForCalcThread = GameObject.Find("Camera").GetComponent("Camera") as Camera;
calc = new Thread(calculationsForBoundingBox);
calc.Start();
labelColors = new Dictionary <string, Color> ();
kalman = new Dictionary <string, IKalmanWrapper> ();
colors = new List <Color> {
new Color(255f / 255, 109f / 255, 124f / 255),
new Color(119f / 255, 231f / 255, 255f / 255),
new Color(82f / 255, 255f / 255, 127f / 255),
new Color(252f / 255, 187f / 255, 255f / 255),
new Color(255f / 255, 193f / 255, 130f / 255)
};
// @Therese - these need to be moved somewhere to a higher-level entity as
// configuration parameters (may be changed frequently during testing)
string rootPrefix = "/icear/user";
string userId = "peter"; // "mobile-terminal0";
string serviceType = "object_recognizer";
string serviceInstance = "yolo"; // "yolo";
string serviceInstance2 = "openface"; // "yolo";
NdnRtc.Initialize(rootPrefix, userId);
faceProcessor_ = new FaceProcessor();
faceProcessor_.start();
assetFetcher_ = new AssetBundleFetcher(faceProcessor_);
string servicePrefix = rootPrefix + "/" + userId + "/" + serviceType;
// AnnotationsFetcher instance might also be a singleton class
// and initialized/created somewhere else. here just as an example
aFetcher_ = new AnnotationsFetcher(faceProcessor_, servicePrefix, serviceInstance);
openFaceFetcher_ = new AnnotationsFetcher(faceProcessor_, servicePrefix, serviceInstance2);
// setup CNL logging
ILOG.J2CsMapping.Util.Logging.Logger.getLogger("").setLevel(ILOG.J2CsMapping.Util.Logging.Level.FINE);
ILOG.J2CsMapping.Util.Logging.Logger.Write = delegate(string message) { Debug.Log(System.DateTime.Now + ": " + message); };
}
/// <summary>
/// Uploads the picture
/// Author: Tomas Drasutis
/// </summary>
private async void uploadButton_Click(object sender, EventArgs e)
{
int chosenImageIndex = 0;
Bitmap uploadedImage = ImageUpload.UploadImage();
if (uploadedImage == null)
{
return;
}
else
{
uploadedImage = HelperMethods.ProcessImage(uploadedImage);
}
FrameAnalysisJSON result = await FaceProcessor.ProcessFrame((Bitmap)uploadedImage.Clone());
missingPersonPictureBox.Image?.Dispose();
missingPersonPictureBox.Image = null;
if (result == null)
{
MessageBox.Show(Messages.errorWhileAnalysingImage);
validImage = false;
return;
}
switch (result.Faces.Count)
{
case 0:
MessageBox.Show(Messages.noFacesInImage);
validImage = false;
uploadedImage.Dispose();
return;
case 1:
break;
default:
var chooseFaceForm = new ChooseFaceFormcs(result.Faces, uploadedImage);
chooseFaceForm.ShowDialog();
if (chooseFaceForm.DialogResult == DialogResult.OK)
{
chosenImageIndex = chooseFaceForm.SelectedFace;
chooseFaceForm.Dispose();
}
else
{
return;
}
break;
}
validImage = true;
missingPersonPictureBox.Image = HelperMethods.CropImage(uploadedImage, result.Faces[chosenImageIndex].Face_rectangle, 25);
faceToken = result.Faces[chosenImageIndex].Face_token;
}
public FaceDetectionService()
{
_age = new FaceAge(AppConfigurations.AppId, AppConfigurations.AgeKey); // 年龄识别
_gender = new FaceGender(AppConfigurations.AppId, AppConfigurations.GenderKey); // 性别识别
//// 图片检测人脸
_detection = LocatorFactory.GetDetectionLocator(AppConfigurations.AppId, AppConfigurations.FdKey, _age, _gender) as FaceDetection;
_traking = LocatorFactory.GetTrackingLocator(AppConfigurations.AppId, AppConfigurations.FtKey, _age, _gender) as FaceTracking;
_recognize = new FaceRecognize(AppConfigurations.AppId, AppConfigurations.FrKey);
_processor = new FaceProcessor(_detection, _recognize);
_personFaceRepository = new PersonFaceRepository();
}
private static void TestMatching()
{
using (var proccesor = new FaceProcessor("appId",
"ftKey", "frKey", true))
{
var image1 = Image.FromFile("test2.jpg");
var image2 = Image.FromFile("test.jpg");
var result1 = proccesor.LocateExtract(new Bitmap(image1));
var result2 = proccesor.LocateExtract(new Bitmap(image2));
if ((result1 != null) & (result2 != null))
{
Console.WriteLine(proccesor.Match(result1[0].FeatureData, result2[0].FeatureData, true));
}
}
}
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();
}
public AssetBundleFetcher(FaceProcessor faceProcessor)
{
faceProcessor_ = faceProcessor;
}
/**
* 增加处理回调，在人脸检测前会被回调。
*
* @param processor 图片帧处理回调
*/
public void addPreProcessor(FaceProcessor processor)
{
preProcessors.Add(processor);
}
public FaceProcessingService(IHubContext <FaceDetectedAlertHub> hubContext)
{
this.hubContext = hubContext;
Processor = new FaceProcessor();
Processor.FacesDetected += HandleFacesDetectedEvent;
}
void Start()
{
Debug.Message("initializing OnCameraFrame...");
try
{
renderBoundingBoxes = true;
timestamp_ = 0;
Debug.Log("adding callback for capturing camera frames");
TextureReaderComponent.OnImageAvailableCallback += OnImageAvailable;
frameMgr_ = GameObject.FindObjectOfType <FramePoolManager>();
boxMgr_ = GameObject.FindObjectOfType <BoundingBoxPoolManager>();
Debug.Log("creating structures for frames and bounding boxes processing");
frameBuffer_ = new ConcurrentQueue <Dictionary <int, FrameObjectData> >();
boundingBoxBufferToCalc_ = new ConcurrentQueue <BoxData>();
boundingBoxBufferToUpdate_ = new ConcurrentQueue <CreateBoxData>();
boxData_ = new List <CreateBoxData>();
camForCalcThread_ = GameObject.Find("Camera").GetComponent("Camera") as Camera;
//calc_ = new Thread(calculationsForBoundingBox);
//calc_.Start();
labelColors_ = new Dictionary <string, Color>();
kalman_ = new Dictionary <string, IKalmanWrapper>();
colors_ = new List <Color> {
new Color(255f / 255, 109f / 255, 124f / 255),
new Color(119f / 255, 231f / 255, 255f / 255),
new Color(82f / 255, 255f / 255, 127f / 255),
new Color(252f / 255, 187f / 255, 255f / 255),
new Color(255f / 255, 193f / 255, 130f / 255)
};
Debug.Log("initializing semantic db controller");
lastDbQuery_ = System.DateTime.Now;
lastKeyFrame_ = System.DateTime.Now;
dbQueryRate_ = 0.5f; // once every 2 seconds
dbController_ = new SemanticDbController("http://131.179.142.7:8888/query");
Debug.Log("initializing NDN modules");
// @Therese - these need to be moved somewhere to a higher-level entity as
// configuration parameters (may be changed frequently during testing)
string rootPrefix = "/icear/user";
string userId = "peter"; // "mobile-terminal0";
string serviceType = "object_recognizer";
string [] edgeServices = { "yolo", "openface" }; // these must be unique!
NdnRtc.Initialize(rootPrefix, userId);
faceProcessor_ = new FaceProcessor();
faceProcessor_.start();
assetFetcher_ = new AssetBundleFetcher(faceProcessor_);
string servicePrefix = rootPrefix + "/" + userId + "/" + serviceType;
annotationFetchers_ = new List <AnnotationsFetcher>();
foreach (var service in edgeServices)
{
Debug.LogFormat("initializing annotations fetcher for {0}...", service);
annotationFetchers_.Add(new AnnotationsFetcher(faceProcessor_, servicePrefix, service));
}
// setup CNL logging
//ILOG.J2CsMapping.Util.Logging.Logger.getLogger("").setLevel(ILOG.J2CsMapping.Util.Logging.Level.FINE);
//ILOG.J2CsMapping.Util.Logging.Logger.Write = delegate (string message) { Debug.Log(System.DateTime.Now + ": " + message); };
}
catch (System.Exception e)
{
Debug.LogExceptionFormat(e, "while initializing");
}
}
