// Use this for initialization
void Start () {
Mat src = new Mat(Application.dataPath + "/lena.png", ImreadModes.GrayScale);
Mat dst = new Mat();
frame = new Mat ();
Cv2.Canny(src, dst, 50, 200);
tex = new Texture2D (dst.Width, dst.Height);
tex.LoadImage (dst.ToBytes (".png", new int[]{0}));
go.GetComponent<Renderer> ().material.mainTexture = tex;
cap = new VideoCapture (1);
}
// Use this for initialization
void Start()
{
rgbMat = new Mat ();
capture = new VideoCapture ();
capture.open (Utils.getFilePath ("768x576_mjpeg.mjpeg"));
if (capture.isOpened ()) {
Debug.Log ("capture.isOpened() true");
} else {
Debug.Log ("capture.isOpened() false");
}
Debug.Log ("CAP_PROP_FORMAT: " + capture.get (Videoio.CAP_PROP_FORMAT));
Debug.Log ("CV_CAP_PROP_PREVIEW_FORMAT: " + capture.get (Videoio.CV_CAP_PROP_PREVIEW_FORMAT));
Debug.Log ("CAP_PROP_POS_MSEC: " + capture.get (Videoio.CAP_PROP_POS_MSEC));
Debug.Log ("CAP_PROP_POS_FRAMES: " + capture.get (Videoio.CAP_PROP_POS_FRAMES));
Debug.Log ("CAP_PROP_POS_AVI_RATIO: " + capture.get (Videoio.CAP_PROP_POS_AVI_RATIO));
Debug.Log ("CAP_PROP_FRAME_COUNT: " + capture.get (Videoio.CAP_PROP_FRAME_COUNT));
Debug.Log ("CAP_PROP_FPS: " + capture.get (Videoio.CAP_PROP_FPS));
Debug.Log ("CAP_PROP_FRAME_WIDTH: " + capture.get (Videoio.CAP_PROP_FRAME_WIDTH));
Debug.Log ("CAP_PROP_FRAME_HEIGHT: " + capture.get (Videoio.CAP_PROP_FRAME_HEIGHT));
texture = new Texture2D ((int)(frameWidth), (int)(frameHeight), TextureFormat.RGBA32, false);
gameObject.transform.localScale = new Vector3 ((float)frameWidth, (float)frameHeight, 1);
float widthScale = (float)Screen.width / (float)frameWidth;
float heightScale = (float)Screen.height / (float)frameHeight;
if (widthScale < heightScale) {
Camera.main.orthographicSize = ((float)frameWidth * (float)Screen.height / (float)Screen.width) / 2;
} else {
Camera.main.orthographicSize = (float)frameHeight / 2;
}
gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
}
private static void VideoCaptureSample()
{
var cap = new VideoCapture(0);
if (!cap.IsOpened())
{
Console.WriteLine("Can't use camera.");
return;
}
var frame = new Mat();
cap.Grab();
NativeMethods.videoio_VideoCapture_operatorRightShift_Mat(cap.CvPtr, frame.CvPtr);
Window.ShowImages(frame);
using (var window = new Window("window"))
{
while (true)
{
cap.Read(frame);
window.ShowImage(frame);
int key = Cv2.WaitKey(50);
if (key == 'b')
break;
}
}
}
void OnApplicationQuit()
{
if ( video !=null ) {
video.Dispose();
video = null;
}
}
public void Run()
{
var capture = new VideoCapture();
capture.Set(CaptureProperty.FrameWidth, 640);
capture.Set(CaptureProperty.FrameHeight, 480);
capture.Open(-1);
if (!capture.IsOpened())
throw new Exception("capture initialization failed");
var fs = FrameSource.CreateCameraSource(-1);
var sr = SuperResolution.CreateBTVL1();
sr.SetInput(fs);
using (var normalWindow = new Window("normal"))
using (var srWindow = new Window("super resolution"))
{
var normalFrame = new Mat();
var srFrame = new Mat();
while (true)
{
capture.Read(normalFrame);
sr.NextFrame(srFrame);
if (normalFrame.Empty() || srFrame.Empty())
break;
normalWindow.ShowImage(normalFrame);
srWindow.ShowImage(srFrame);
Cv2.WaitKey(100);
}
}
}
// Use this for initialization
void Start()
{
// カメラを列挙する
// 使いたいカメラのインデックスをVideoIndexに入れる
// 列挙はUnityで使うのはOpenCVだけど、インデックスは同じらしい
var devices = WebCamTexture.devices;
for ( int i = 0; i < devices.Length; i++ ) {
print( string.Format( "index {0}:{1}", i, devices[i].name) );
}
// ビデオの設定
video = new VideoCapture( VideoIndex );
video.Set( CaptureProperty.FrameWidth, Width );
video.Set( CaptureProperty.FrameHeight, Height );
print( string.Format("{0},{1}", Width, Height) );
// 顔検出器の作成
cascade = new CascadeClassifier( Application.dataPath + @"/haarcascade_frontalface_alt.xml" );
// テクスチャの作成
texture = new Texture2D( Width, Height, TextureFormat.RGB24, false );
renderer.material.mainTexture = texture;
// 変換用のカメラの作成
_Camera = GameObject.Find( Camera.name ).camera;
print( string.Format( "({0},{1})({2},{3})", Screen.width, Screen.height, _Camera.pixelWidth, _Camera.pixelHeight ) );
}
//---------------------------------------------------------
// 関数名 : setDevice
// 機能 : カメラデバイス選択、設定
// 引数 : index/カメラデバイス
// 戻り値 : なし
//---------------------------------------------------------
public void setDevice(int index)
{
// カメラの設定
video = new VideoCapture(index);
video.Set(CaptureProperty.FrameWidth, GlobalVar.CAMERA_WIDTH);
video.Set(CaptureProperty.FrameHeight, GlobalVar.CAMERA_HEIGHT);
video.Set(CaptureProperty.Fps, GlobalVar.CAMERA_FPS);
}
public OpenCVMovie OpenMovie(string fileName) {
try {
VideoCapture load = new VideoCapture(fileName);
OpenCVMovie original = new OpenCVMovie(load);
return original;
} catch {
MessageBox.Show("ошибка при открытии видео");
return null;
}
}
public void Run()
{
const string OutVideoFile = "out.avi";
// Opens MP4 file (ffmpeg is probably needed)
VideoCapture capture = new VideoCapture(FilePath.Bach);
// Read movie frames and write them to VideoWriter
Size dsize = new Size(640, 480);
using (VideoWriter writer = new VideoWriter(OutVideoFile, -1, capture.Fps, dsize))
{
Console.WriteLine("Converting each movie frames...");
Mat frame = new Mat();
while(true)
{
// Read image
capture.Read(frame);
if(frame.Empty())
break;
Console.CursorLeft = 0;
Console.Write("{0} / {1}", capture.PosFrames, capture.FrameCount);
// grayscale -> canny -> resize
Mat gray = new Mat();
Mat canny = new Mat();
Mat dst = new Mat();
Cv2.CvtColor(frame, gray, ColorConversion.BgrToGray);
Cv2.Canny(gray, canny, 100, 180);
Cv2.Resize(canny, dst, dsize, 0, 0, Interpolation.Linear);
// Write mat to VideoWriter
writer.Write(dst);
}
Console.WriteLine();
}
// Watch result movie
using (VideoCapture capture2 = new VideoCapture(OutVideoFile))
using (Window window = new Window("result"))
{
int sleepTime = (int)(1000 / capture.Fps);
Mat frame = new Mat();
while (true)
{
capture2.Read(frame);
if(frame.Empty())
break;
window.ShowImage(frame);
Cv2.WaitKey(sleepTime);
}
}
}
// Use this for initialization
private void Start () {
frame = new Mat ();
cap = new VideoCapture (1);
tex = new Texture2D (cap.FrameWidth, cap.FrameHeight);
cap.Read (frame);
dst = new Mat ();
thresh = new Mat ();
tex.LoadImage (frame.ToBytes (".png", new int[]{0}));
go.GetComponent<Renderer> ().material.mainTexture = tex;
}
public Camera()
{
_capture = Capture();
while (!_capture.IsOpened())
{
Logger.Warn("Не могу подключиться к камере");
Thread.Sleep(1000);
_capture = Capture();
}
Logger.Success(String.Format("Подключился к камере ({0}x{1})",
_capture.FrameWidth, _capture.FrameHeight));
}
private void DeleteCapture()
{
if (null != video)
{
video.Dispose();
video = null;
}
if (null != camera)
{
camera.Dispose();
camera = null;
}
}
private void btnVideo_Click(object sender, EventArgs e)
{
DeleteCapture();
var dialog = new OpenFileDialog()
{
Title = "Open Movie File",
Filter = ".avi, .mpg, .wmv|*.avi;*.mpg;*.wmv|all|*.*"
};
if (dialog.ShowDialog(this) == DialogResult.OK)
{
DeleteCapture();
video = new VideoCapture(dialog.FileName, this.pictureBox1, VideoCapture.VMR.VMR9);
setSize(video.Width, video.Height);
video.Play();
}
}
// Use this for initialization
private void Start () {
if (isVid) {
frame = new Mat ();
//gray = new Mat();
cap = new VideoCapture (1);
tex = new Texture2D (cap.FrameWidth, cap.FrameHeight);
bkrnd_win_size = 20; //cap.FrameWidth / 5;
cap.Read (frame);
} else {
frame = new Mat(Application.dataPath + "/profile_photo.png", ImreadModes.Color);
tex = new Texture2D (frame.Width, frame.Height);
bkrnd_win_size = 20;//frame.Width / 5;
}
frame_backproj = new Mat ();
mask = new Mat ();
tex.LoadImage (frame.ToBytes (".png", new int[]{0}));
go.GetComponent<Renderer> ().material.mainTexture = tex;
//myDetector = new CascadeClassifier ("C:/Users/admin/opencv/build/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml");
bkrnd_rect = new OpenCvSharp.Rect(1,1,bkrnd_win_size,bkrnd_win_size);
}
// Use this for initialization
void Start()
{
// カメラを列挙する
// 使いたいカメラのインデックスをVideoIndexに入れる
// 列挙はUnityで使うのはOpenCVだけど、インデックスは同じらしい
var devices = WebCamTexture.devices;
for ( int i = 0; i < devices.Length; i++ ) {
print( string.Format( "index {0}:{1}", i, devices[i].name ) );
}
// ビデオの設定
video = new VideoCapture( VideoIndex );
video.Set( CaptureProperty.FrameWidth, Width );
video.Set( CaptureProperty.FrameHeight, Height );
print( string.Format( "{0},{1}", Width, Height ) );
// テクスチャの作成
texture = new Texture2D( Width, Height, TextureFormat.RGB24, false );
renderer.material.mainTexture = texture;
}
public void Run()
{
using (var capture = new VideoCapture(FilePath.Bach))
using (var mog = new BackgroundSubtractorMOG())
using (var windowSrc = new Window("src"))
using (var windowDst = new Window("dst"))
{
var frame = new Mat();
var fg = new Mat();
while (true)
{
capture.Read(frame);
if(frame.Empty())
break;
mog.Run(frame, fg, 0.01);
windowSrc.Image = frame;
windowDst.Image = fg;
Cv2.WaitKey(50);
}
}
}
public void Render(IGameContext gameContext, IRenderContext renderContext)
{
if (renderContext.GraphicsDevice == null)
{
return;
}
if (_currentCamera != ActiveCamera)
{
if (_videoCapture != null)
{
_videoCapture.Dispose();
}
_videoCapture = null;
}
_currentCamera = ActiveCamera;
if (_videoCapture == null && _currentCamera != null)
{
_videoCapture = new VideoCapture(
renderContext.GraphicsDevice,
_currentCamera);
}
if (_videoCapture != null)
{
VideoCaptureFrame = _videoCapture.Frame;
VideoCaptureUnlockedRGBA = _videoCapture.UnlockedFrameRGBA;
}
else
{
VideoCaptureFrame = null;
VideoCaptureUnlockedRGBA = null;
}
}
private static void VideoCaptureSample()
{
var cap = new VideoCapture(0);
if (!cap.IsOpened())
{
Console.WriteLine("Can't use camera.");
return;
}
var frame = new Mat();
using (var window = new Window("window"))
{
while (true)
{
cap.Read(frame);
window.ShowImage(frame);
int key = Cv2.WaitKey(50);
if (key == 'b')
break;
}
}
}
public void Run()
{
// Opens MP4 file (ffmpeg is probably needed)
VideoCapture capture = new VideoCapture(FilePath.Movie.Bach);
int sleepTime = (int)Math.Round(1000 / capture.Fps);
using (Window window = new Window("capture"))
{
// Frame image buffer
Mat image = new Mat();
// When the movie playback reaches end, Mat.data becomes NULL.
while (true)
{
capture.Read(image); // same as cvQueryFrame
if(image.Empty())
break;
window.ShowImage(image);
Cv2.WaitKey(sleepTime);
}
}
}
public IEnumerator MakeVideo(TMPro.TMP_Text progressDisplay, TMPro.TMP_Text statusDisplay)
{
// 1. Create video capture
m_vidCapturer = new VideoCapture(m_vidName);
// capture validity check
if (!m_vidCapturer.isOpened())
{
m_vidCapturer.release();
m_vidCapturer = null;
DanbiUtils.LogErr($"Failed to open the selected video at {m_vidName}");
yield break;
}
// 2. init persistant resources
receivedFrameMat = new Mat((int)m_vidCapturer.get(4), (int)m_vidCapturer.get(3), CvType.CV_8UC4); // CV_8UC4 (RGBA).
distortedFrameMat = new Mat((int)m_vidCapturer.get(4), (int)m_vidCapturer.get(3), CvType.CV_8UC4); // CV_8UC4 (RGBA).
texForVideoFrame = new Texture2D((int)m_vidCapturer.get(3), (int)m_vidCapturer.get(4), TextureFormat.RGBA32, false);
// 4. calc video frame counts.
m_currentFrameCount = 0;
m_maxFrameCount = (int)m_vidCapturer?.get(DanbiOpencvVideoCapturePropID.frame_count);
// 5. get a codec for a video writer.
// MJPG -> error!
int codec_fourcc = DanbiOpencvVideoCodec_fourcc.get_fourcc_videoCodec(m_videoCodec);
if (codec_fourcc == -999)
{
DanbiUtils.LogErr($"codec is invalid! codec propID -> {codec_fourcc}");
yield break;
}
// 6. create a video writer
var frameSize = new Size(m_vidCapturer.get(3), m_vidCapturer.get(4)); // width , height
m_vidWriter = new VideoWriter(m_savedVideoPathAndName, codec_fourcc, m_targetFrameRate, frameSize, true);
// while (m_currentFrameCount < m_dbgMaxFrameCount)
while (m_currentFrameCount < m_maxFrameCount - 1)
{
if (m_isSaving)
{
break;
}
// read the new Frame into 'newFrameMat'.
if (!m_vidCapturer.read(receivedFrameMat))
{
DanbiUtils.LogErr($"Failed to read the current video frame! <No next frame>");
break;
}
// testRT = new Mat((int)receivedFrameMat.get(4), (int)receivedFrameMat.get(3), CvType.CV_8UC4);
// OpenCVForUnity.ImgprocModule.Imgproc.cvtColor(receivedFrameMat, testRT, OpenCVForUnity.ImgprocModule.Imgproc.COLOR_RGBA)
if (receivedFrameMat.empty())
{
DanbiUtils.LogErr("Frame failed to receive the captured frame from the video!");
break;
}
Utils.matToTexture2D(receivedFrameMat, texForVideoFrame);
yield return(StartCoroutine(DistortCurrentFrame(texForVideoFrame)));
Utils.texture2DToMat(texForVideoFrame, distortedFrameMat);
if (distortedFrameMat.empty())
{
DanbiUtils.LogErr("Frame failed to receive the distorted result!");
break;
}
// write the newFrameMat into the video writer
m_vidWriter.write(distortedFrameMat);
// TODO: update the text with DanbiStatusDisplayHelper
// progressDisplayText.text = $"Start to warp" +
// "(500 / 25510) " +
// "(1.96001%)";
// TODO: update the text with DanbiStatusDisplayHelper
// statusDisplayText.text = "Image generating succeed!";
++m_currentFrameCount;
}
// dispose resources.
m_vidCapturer.release();
m_vidWriter.release();
receivedFrameMat.release();
distortedFrameMat.release();
texForVideoFrame = null;
// reset flags
DanbiManager.instance.renderFinished = false;
m_isSaving = false;
Application.runInBackground = false;
// wait the saved file
yield return(new WaitUntil(() => new System.IO.FileInfo(m_savedVideoPathAndName).Exists));
System.Diagnostics.Process.Start(@"" + m_savedVideoPath);
}
private async void btStart_Click(object sender, EventArgs e)
{
mmError.Text = string.Empty;
if (rbSTreamTypeFile.Checked)
{
_fileStream = new FileStream(edFilename.Text, FileMode.Open);
_stream = new ManagedIStream(_fileStream);
// specifying settings
MediaPlayer1.Source_Stream = _stream;
MediaPlayer1.Source_Stream_Size = _fileStream.Length;
}
else
{
_memorySource = File.ReadAllBytes(edFilename.Text);
_memoryStream = new MemoryStream(_memorySource);
_stream = new ManagedIStream(_memoryStream);
// specifying settings
MediaPlayer1.Source_Stream = _stream;
MediaPlayer1.Source_Stream_Size = _memoryStream.Length;
}
// video and audio present in file. tune this settings to play audio files or video files without audio
if (rbVideoWithAudio.Checked)
{
MediaPlayer1.Source_Stream_VideoPresent = true;
MediaPlayer1.Source_Stream_AudioPresent = true;
}
else if (rbVideoWithoutAudio.Checked)
{
MediaPlayer1.Source_Stream_VideoPresent = true;
MediaPlayer1.Source_Stream_AudioPresent = false;
}
else
{
MediaPlayer1.Source_Stream_VideoPresent = false;
MediaPlayer1.Source_Stream_AudioPresent = true;
}
MediaPlayer1.Source_Mode = VFMediaPlayerSource.Memory_DS;
MediaPlayer1.Audio_OutputDevice = "Default DirectSound Device";
if (VideoCapture.Filter_Supported_EVR())
{
MediaPlayer1.Video_Renderer.Video_Renderer = VFVideoRenderer.EVR;
}
else if (VideoCapture.Filter_Supported_VMR9())
{
MediaPlayer1.Video_Renderer.Video_Renderer = VFVideoRenderer.VMR9;
}
else
{
MediaPlayer1.Video_Renderer.Video_Renderer = VFVideoRenderer.VideoRenderer;
}
MediaPlayer1.Debug_Mode = cbDebugMode.Checked;
await MediaPlayer1.PlayAsync();
tbTimeline.Maximum = (int)MediaPlayer1.Duration_Time().TotalSeconds;
timer1.Enabled = true;
}
void Start()
{
capture = new VideoCapture(0);
capture.ImageGrabbed += HandleGrab;
classifier = new CascadeClassifier("Assets/Resources/haarcascade_frontalface_default.xml");
}
public bool CheckGetPokemon()
{
Log($"Dialog.CheckGetPokemon()");
return(VideoCapture.Match(410, 970, ImageRes.Get("dialog_getpokemon"), DefaultImageCap, VideoCapture.LineSampler(3)));
}
// Use this for initialization
void Start()
{
face_cascade = new CascadeClassifier ("haarcascade_frontalface_alt.xml");
eye_cascade = new CascadeClassifier ("haarcascade_eye.xml");
int i;
for (i=0; i<10; i++) {
//cap = VideoCapture.FromCamera (i);
cap = new VideoCapture(i);
if (cap!=null)
break;
}
/*
Application.RequestUserAuthorization(UserAuthorization.WebCam);
if (Application.HasUserAuthorization (UserAuthorization.WebCam)) {
WebCamDevice[] devices = WebCamTexture.devices;
string deviceName = devices [0].name;
cameraTexture = new WebCamTexture (deviceName);
}*/
if (cap != null) {
frameSize = new Size (cap.FrameWidth, cap.FrameHeight);
tex = new Texture2D (cap.FrameWidth, cap.FrameHeight);
}
else if (cameraTexture != null) {
frameSize = new Size (cameraTexture.width, cameraTexture.height);
tex = new Texture2D (cameraTexture.width, cameraTexture.height);
}
GameObject.Find ("CamQuad").GetComponent<Renderer> ().material.mainTexture = tex;
GameObject.Find ("CamQuad").GetComponent<Renderer> ().material.SetTextureScale ("_MainTex", new Vector2 (1.0f, -1.0f));
cameraTexture.Play ();
lastx = new float[10];
lasty = new float[10];
}
private void MainWindow_Closed(object sender, EventArgs e)
{
if (this.VideoViewer != null && this.VideoViewer.IsLoaded)
{
this.VideoViewer.Close();
}
if (this.MyVideoCapture != null)
{
this.MyVideoCapture.Dispose();
this.MyVideoCapture = null;
}
}
public Mat RunPlugin(VideoCapture src)
{
capture = src;
return(DetectHandSkin());
}
public override int Run()
{
int device = 0;
var argument = new StringList {
"./"
};
FaceModelParameters det_parameters = new FaceModelParameters(argument);
//vector<string> files, depth_directories, output_video_files, out_dummy;
StringList files = new StringList(), output_video_files = new StringList(), out_dummy = new StringList();
bool u;
string output_codec;
LandmarkDetector.get_video_input_output_params(files, out_dummy, output_video_files, out u, out output_codec, argument);
CLNF clnf_model = new CLNF(det_parameters.model_location);
float fx = 0, fy = 0, cx = 0, cy = 0;
LandmarkDetector.get_camera_params(out device, out fx, out fy, out cx, out cy, argument);
// If cx (optical axis centre) is undefined will use the image size/2 as an estimate
bool cx_undefined = false;
bool fx_undefined = false;
if (cx == 0 || cy == 0)
{
cx_undefined = true;
}
if (fx == 0 || fy == 0)
{
fx_undefined = true;
}
//// Do some grabbing
INFO_STREAM("Attempting to capture from device: " + device);
using (VideoCapture video_capture = new VideoCapture(device))
{
using (Mat dummy = new Mat())
video_capture.Read(dummy);
if (!video_capture.IsOpened())
{
FATAL_STREAM("Failed to open video source");
return(1);
}
else
{
INFO_STREAM("Device or file opened");
}
int frame_count = 0;
Mat captured_image = new Mat();
video_capture.Read(captured_image);
Size = new Size(captured_image.Width / SizeFactor, captured_image.Height / SizeFactor);
using (var resized_image = captured_image.Resize(Size))
{
// If optical centers are not defined just use center of image
if (cx_undefined)
{
cx = resized_image.Cols / 2.0f;
cy = resized_image.Rows / 2.0f;
}
// Use a rough guess-timate of focal length
if (fx_undefined)
{
fx = (float)(500 * (resized_image.Cols / 640.0));
fy = (float)(500 * (resized_image.Rows / 480.0));
fx = (float)((fx + fy) / 2.0);
fy = fx;
}
}
// Use for timestamping if using a webcam
long t_initial = Cv2.GetTickCount();
INFO_STREAM("Starting tracking");
while (video_capture.Read(captured_image))
{
using (var resized_image = captured_image.Resize(Size))
{
// Reading the images
MatOfByte grayscale_image = new MatOfByte();
if (resized_image.Channels() == 3)
{
Cv2.CvtColor(resized_image, grayscale_image, ColorConversionCodes.BGR2GRAY);
}
else
{
grayscale_image = (MatOfByte)resized_image.Clone();
}
// The actual facial landmark detection / tracking
bool detection_success = LandmarkDetector.DetectLandmarksInVideo(new SWIGTYPE_p_cv__Mat_T_uchar_t(grayscale_image.CvPtr), new SWIGTYPE_p_CLNF(CLNF.getCPtr(clnf_model)), new SWIGTYPE_p_FaceModelParameters(FaceModelParameters.getCPtr(det_parameters)));
// Visualising the results
// Drawing the facial landmarks on the face and the bounding box around it if tracking is successful and initialised
double detection_certainty = clnf_model.detection_certainty;
visualise_tracking(resized_image, ref clnf_model, ref det_parameters, frame_count, fx, fy, cx, cy);
// detect key presses
char character_press = (char)Cv2.WaitKey(15);
switch (character_press)
{
case 'r':
clnf_model.Reset();
break;
case 'q':
return(0);
}
// Update the frame count
frame_count++;
grayscale_image.Dispose();
grayscale_image = null;
}
}
}
return(0);
}
static void FindLaneInTheVideo(string path)
{
VideoCapture capture = new VideoCapture(path);
Mat workAreaMask = CreateMask();
using (Window win1 = new Window("test1"))
{
Mat image = new Mat();
// We will save previous results here
List <List <Sensor> > oldResultGroups = null;
int[] countTaked = new int[2] {
0, 0
};
while (true)
{
DateTime dt1 = DateTime.Now;
capture.Read(image);
if (image.Empty())
{
break;
}
if (capture.PosFrames % 2 != 0)
{
continue;
}
// Get the work area
Mat image_s = image.SubMat(Camera.vert_frame[0], Camera.vert_frame[1],
Camera.hor_frame[0], Camera.hor_frame[1]);
Mat workArea = new Mat();
image_s.CopyTo(workArea, workAreaMask);
// Get HSV, grat and canny
Mat hsv_image = workArea.CvtColor(ColorConversionCodes.RGB2HSV);
Mat canny1 = hsv_image.Canny(40, 60);
Mat gray = workArea.CvtColor(ColorConversionCodes.BGR2GRAY);
Mat canny2 = gray.Canny(40, 60);
Mat canny = new Mat();
Cv2.BitwiseAnd(canny1, canny2, canny);
// Get, filter and draw contours
Mat hsv_contoures = new Mat();
hsv_image.CopyTo(hsv_contoures);
var contoures = FindContoures(canny);
hsv_contoures.DrawContours(contoures, -1, Scalar.Red);
// Get indexers
MatOfByte3 hsv_cont_ind = new MatOfByte3(hsv_contoures);
MatOfByte3 hsv_ind = new MatOfByte3(hsv_image);
var hsv_cont_indexer = hsv_cont_ind.GetIndexer();
var hsv_indexer = hsv_ind.GetIndexer();
// Make steps of the algorithm
List <Sensor> sensors = GetSensors(hsv_contoures, hsv_cont_indexer);
List <Sensor> filteredByContours = FilterByContours(sensors, hsv_cont_indexer);
List <Sensor> filteredByColors = FilterByColorAndChangeColor(filteredByContours, hsv_indexer);
List <Sensor> filteredByNearSensors = FilterByNearSensors(filteredByColors);
List <List <Sensor> > groupedByAngle = GroupByAngle(filteredByNearSensors).Where(g => g.Count > 2).ToList();
List <List <Sensor> > groupedByDistance = GroupByDistance(groupedByAngle).Where(g => g.Count > 2).ToList();
List <List <Sensor> > groupedWithoudCovering = DeleteCovering(groupedByDistance);
List <List <Sensor> > unionGroups = UnionGroups(groupedWithoudCovering).Where(g => g.Count > 2).ToList();
List <List <Sensor> > resultGroups = SelectGroups(unionGroups, oldResultGroups, ref countTaked);
image.SaveImage("image.png");
// Draw the result
foreach (var group in resultGroups)
{
if (group != null)
{
foreach (var line in GetLinesForGroup(group))
{
image.Line(line.x1 + Camera.hor_frame[0], line.y1 + Camera.vert_frame[0],
line.x2 + Camera.hor_frame[0], line.y2 + Camera.vert_frame[0], Scalar.Blue, 5);
}
}
}
image.SaveImage("res.png");
Mat imageForDisplay = image.Resize(new Size(0, 0), 0.5, 0.5);
win1.ShowImage(imageForDisplay);
oldResultGroups = resultGroups;
DateTime dt2 = DateTime.Now;
Console.WriteLine("{0}\tms", (dt2 - dt1).TotalMilliseconds);
int key = Cv2.WaitKey(0);
if (key == 27)
{
break; //escape
}
// Free resourses
image_s.Release();
workArea.Release();
hsv_ind.Release();
hsv_cont_ind.Release();
gray.Release();
canny1.Release();
canny2.Release();
canny.Release();
hsv_image.Release();
hsv_contoures.Release();
}
}
}
static void Main(string[] args)
{
//取得した画像とその差分画像を表示する
#region
//Mat src = new Mat(@"C:\Users\tyani\Downloads\lenna.png", ImreadModes.Grayscale);
//// Mat src = Cv2.ImRead("lenna.png", ImreadModes.Grayscale);
//Mat dst = new Mat();
//Cv2.Canny(src, dst, 50, 200);
//using (new Window("src image", src))
//using (new Window("dst image", dst))
//{
// Cv2.WaitKey();
//}
#endregion
//キャプチャーした映像から顔を認識してその位置に丸を付ける
#region
//using (var win = new Window("capture"))
//using (var video = new VideoCapture(0))
//{
// //保存先行列
// var frame = new Mat();
// //分類器
// var haarcascade = new CascadeClassifier(@"C:\Users\tyani\Downloads\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml");
// //グレースケール
// var gray = new Mat();
// while (true)
// {
// video.Read(frame);
// //grayにframeのグレースケール返還画像を代入
// Cv2.CvtColor(frame, gray, ColorConversionCodes.BGR2GRAY);
// //検出
// var faces = haarcascade.DetectMultiScale(gray);
// //検出箇所に円を描画
// foreach (OpenCvSharp.Rect face in faces)
// {
// var center = new Point
// {
// X = (int)(face.X + face.Width * 0.5),
// Y = (int)(face.Y + face.Height * 0.5)
// };
// var axes = new Size
// {
// Width = (int)(face.Width * 0.5),
// Height = (int)(face.Height * 0.5)
// };
// Cv2.Ellipse(frame, center, axes, 0, 0, 360, Scalar.Red, 4);
// Console.WriteLine("Found!");
// }
// win.ShowImage(frame);
// if (Cv2.WaitKey(30) >= 0) { break; }
// }
//}
#endregion
//カメラキャリブレーションを行う
#region
////チェス盤のコーナー座標がを読み込めた数
//int imgInd = 0;
////読み込むチェス盤の定義
//const int BOARD_W = 7;
//const int BOARD_H = 7;
//Size BOARD_SIZE = new Size(BOARD_W, BOARD_H);
//const int SCALE = 26;
////精度の低いコーナーが検出できた座標のリスト
//var imageCorners = new Mat<Point2f>();
////精度の高いコーナー座標の配列
//Point2f[] imageCorners2;
////検出できたframe中のコーナー座標のリスト
//var imagePoints = new List<Mat<Point2f>>();
////毎秒のフレーム画像
//var frame = new Mat();
////フレーム画像のグレースケール
//var gray = new Mat();
////認識したチェス盤画像
//var chessboard = new List<Mat>();
////精度の高いコーナー座標を作る際の終了基準
//var criteria = new TermCriteria(CriteriaType.Count | CriteriaType.Eps, 30, 0.001);
////ウィンドウを生成
//using (var capWindow = new Window("capture"))
//using (var chessWindow = new Window("DrawChessboardCorner"))
////videoにカメラから取得した映像を代入
//using (var video = new VideoCapture(0))
//{
// while (true)
// {
// video.Read(frame);
// var key = Cv2.WaitKey(1);
// if (key == 'c')
// {
// Cv2.CvtColor(frame, gray, ColorConversionCodes.BGR2GRAY);
// //チェス盤のコーナーが検出できたらretにtrueを代入
// var ret = Cv2.FindChessboardCorners(frame, BOARD_SIZE, imageCorners);
// //Console.WriteLine(imageCorners.Get<Point2f>(0));
// if (ret)
// {
// Console.WriteLine("find chess board corners.");
// chessboard.Add(frame);
// //精度を高めたコーナー座標をimageCorners2に代入
// imageCorners2 = Cv2.CornerSubPix(gray, imageCorners, new Size(9, 9), new Size(-1, -1), criteria);
// //Console.WriteLine(imageCorners2[0]);
// Cv2.DrawChessboardCorners(frame, BOARD_SIZE, imageCorners2, ret);
// imageCorners.SetArray<Point2f>(imageCorners2);
// //Console.WriteLine(imageCorners.Get<Point2f>(0));
// //Console.WriteLine(imageCorners.Size());
// imagePoints.Add(imageCorners);
// chessWindow.ShowImage(frame);
// Cv2.WaitKey(500);
// imgInd++;
// }
// }
// else if (key == 'q')
// {
// break;
// }
// else
// {
// Cv2.PutText(frame, "Number of caputure: " + imgInd.ToString(), new Point(30, 20), HersheyFonts.HersheyPlain, 1, new Scalar(0, 255, 0));
// Cv2.PutText(frame, "c: Capture the image", new Point(30, 40), HersheyFonts.HersheyPlain, 1, new Scalar(0, 255, 0));
// Cv2.PutText(frame, "q: Finish capturing and calcurate the camera matrix and distortion", new Point(30, 60), HersheyFonts.HersheyPlain, 1, new Scalar(0, 255, 0));
// capWindow.ShowImage(frame);
// }
// }
// //よくわからない
// var objectPoints = new List<Mat<Point3f>>();
// var objectConrers = new Mat<Point3f>();
// for (int j = 0; j < BOARD_H; j++)
// {
// for (int i = 0; i < BOARD_W; i++)
// {
// objectConrers.PushBack(new Point3f(i * SCALE, j * SCALE, 0f));
// }
// }
// for (int i = 0; i < imgInd; i++)
// objectPoints.Add(objectConrers);
// var cameraMatrix = new Mat();
// var distCoeffs = new Mat();
// Mat[] rvecs;
// Mat[] tvecs;
// var rms = Cv2.CalibrateCamera(objectPoints, imagePoints, frame.Size(), cameraMatrix, distCoeffs, out rvecs, out tvecs);
// Console.WriteLine("Re-projection Error(unit: pixel) : " + rms);
// Console.WriteLine("cameraMatrix(unit: pixel) : " + cameraMatrix);
// Console.WriteLine("distCoeffs : " + distCoeffs);
// var dst = new Mat();
// Cv2.Undistort(chessboard[0], dst, cameraMatrix, distCoeffs);
// using (new Window("補正画像", WindowMode.AutoSize, dst))
// {
// while (true)
// if (Cv2.WaitKey() == 'q')
// break;
// }
//}
#endregion
//SIFTマッチング
#region
//var leftFrame = new Mat();
//var rightFrame = new Mat();
//var view = new Mat();
//var leftGray = new Mat();
//var rightGray = new Mat();
//var sift = SIFT.Create();
//KeyPoint[] keypoints1, keypoints2;
//var descriptors1 = new Mat();
//var descriptors2 = new Mat();
//using (var leftCapWindow = new Window("left capture"))
//using (var rightCapWindow = new Window("right capture"))
//using (var leftVideo = new VideoCapture(0))
//using (var rightVideo = new VideoCapture(1))
//{
// while (true)
// {
// leftVideo.Read(leftFrame);
// rightVideo.Read(rightFrame);
// Cv2.PutText(leftFrame, "d: detect and compute SIFT", new Point(30, 40), HersheyFonts.HersheyPlain, 1, new Scalar(0, 255, 0));
// Cv2.PutText(rightFrame, "d: detect and compute SIFT", new Point(30, 40), HersheyFonts.HersheyPlain, 1, new Scalar(0, 255, 0));
// leftCapWindow.ShowImage(leftFrame);
// rightCapWindow.ShowImage(rightFrame);
// var key = Cv2.WaitKey(1);
// if (key == 'd')
// {
// Cv2.CvtColor(leftFrame, leftGray, ColorConversionCodes.BGR2GRAY);
// Cv2.CvtColor(rightFrame, rightGray, ColorConversionCodes.BGR2GRAY);
// sift.DetectAndCompute(leftGray, null, out keypoints1, descriptors1);
// sift.DetectAndCompute(rightGray, null, out keypoints2, descriptors2);
// BFMatcher matcher = new BFMatcher(NormTypes.L2, false);
// DMatch[] matches = matcher.Match(descriptors1, descriptors2);
// Cv2.DrawMatches(leftGray, keypoints1, rightGray, keypoints2, matches, view);
// using (new Window("SIFT matching", WindowMode.AutoSize, view))
// {
// Cv2.WaitKey();
// }
// }
// }
//}
#endregion
//視差マップ生成
#region
//var leftFrame = new Mat();
//var rightFrame = new Mat();
//var disparity = new Mat();
//var leftGray = new Mat();
//var rightGray = new Mat();
//var sift = SIFT.Create();
//KeyPoint[] keypoints1, keypoints2;
//var descriptors1 = new Mat();
//var descriptors2 = new Mat();
//using (var leftCapWindow = new Window("left capture"))
//using (var rightCapWindow = new Window("right capture"))
//using (var leftVideo = new VideoCapture(1))
//using (var rightVideo = new VideoCapture(0))
//{
// while (true)
// {
// leftVideo.Read(leftFrame);
// rightVideo.Read(rightFrame);
// leftCapWindow.ShowImage(leftFrame);
// rightCapWindow.ShowImage(rightFrame);
// Cv2.CvtColor(leftFrame, leftGray, ColorConversionCodes.BGR2GRAY);
// Cv2.CvtColor(rightFrame, rightGray, ColorConversionCodes.BGR2GRAY);
// var stereo = StereoSGBM.Create(0, 16*10, 11, mode:StereoSGBMMode.HH);
// stereo.Compute(leftGray, rightGray, disparity);
// disparity.Normalize(alpha: 0, beta: 255, normType: NormTypes.MinMax, dtype: MatType.CV_8U);
// using (new Window("disparity map", WindowMode.AutoSize, disparity))
// {
// var key = Cv2.WaitKey(1);
// if (key == 'q')
// break;
// }
// }
//}
#endregion
//もっとも簡単なStereoMatchingのTutorial
#region
//var imgL = new Mat(@"C:\Users\tyani\Downloads\scene1.row3.col1.png", ImreadModes.Grayscale);
//var imgR = new Mat(@"C:\Users\tyani\Downloads\scene1.row3.col3.png", ImreadModes.Grayscale);
//var disparity = new Mat();
//var stereo = StereoBM.Create();
//stereo.Compute(imgL, imgR, disparity);
//using(new Window(disparity))
//{
// Cv2.WaitKey(0);
//}
#endregion
//ARマーカー
#region
using (var video0 = new VideoCapture(0))
using (var video1 = new VideoCapture(1))
using (var window0 = new Window("capture0"))
using (var window1 = new Window("capture1"))
{
var dictionary = CvAruco.GetPredefinedDictionary(PredefinedDictionaryName.Dict6X6_250);
var parameters = DetectorParameters.Create();
var frames = new List <Mat> {
new Mat(), new Mat()
};
var videos = new List <VideoCapture>();
var windows = new List <Window>();
Point2f[][] corners;
int[] ids;
int[] previousIds;
Point2f[][] rejectedImgPoints;
videos.Add(video0);
videos.Add(video1);
windows.Add(window0);
windows.Add(window1);
var wasFoundList = new List <bool> {
false, false
};
var isTouchedList = new List <bool> {
false, false
};
var wasTouched = false;
while (true)
{
for (int i = 0; i < 2; i++)
{
videos[i].Read(frames[i]);
CvAruco.DetectMarkers(frames[i], dictionary, out corners, out ids, parameters, out rejectedImgPoints);
isTouchedList[i] = wasFoundList[i] && !(ids.Length > 0);
if (ids.Length > 0)
{
wasFoundList[i] = true;
CvAruco.DrawDetectedMarkers(frames[i], corners, ids);
}
else
{
wasFoundList[i] = false;
isTouchedList[i] = true;
}
windows[i].ShowImage(frames[i]);
}
if (!isTouchedList.Contains(false))
{
if (!wasTouched)
{
Console.WriteLine("Hello world!");
for (int i = 0; i < isTouchedList.Count; i++)
{
isTouchedList[i] = false;
}
}
wasTouched = true;
}
else
{
wasTouched = false;
}
var key = Cv2.WaitKey(1);
if (key == 'q')
{
break;
}
}
}
#endregion
#region
//var numCamera = 1;
//var dictionary = CvAruco.GetPredefinedDictionary(PredefinedDictionaryName.Dict7X7_50);
//var parameters = DetectorParameters.Create();
//var videoCaps = new List<VideoCapture>(numCamera);
//var windows = new List<Window>(numCamera);
//var capFrames = new List<Mat>(numCamera);
////var markerCornersList = new List<Point2f[][]>(numCamera);
////var markerIdsList = new List<int[]>(numCamera);
////var rejectedImgPointsList = new List<Point2f[][]>(numCamera);
//var isFoundList = new List<bool>(numCamera);
//var isTouchedList = new List<bool>(numCamera);
//try
//{
// for (int i = 0; i < numCamera; i++)
// {
// videoCaps.Add(new VideoCapture(i));
// windows.Add(new Window("VideoCapture" + i.ToString()));
// }
// while (true)
// {
// for (int i = 0; i < numCamera; i++)
// {
// var capFrame = new Mat();
// Point2f[][] markerCorners;
// int[] markerIds;
// Point2f[][] rejectedImgPoints;
// videoCaps[i].Read(capFrame);
// CvAruco.DetectMarkers(capFrame, dictionary, out markerCorners, out markerIds, parameters, out rejectedImgPoints);
// if (!isFoundList[i] && markerIds.Length > 0)
// {
// isFoundList[i] = true;
// }
// if (isFoundList[i] && !(markerIds[i] > 0))
// {
// isTouchedList[i] = true;
// }
// if (markerIds.Length > 0)
// {
// CvAruco.DrawDetectedMarkers(capFrame, markerCorners, markerIds);
// }
// windows[i].ShowImage(capFrame);
// }
// if (!isTouchedList.Contains(false))
// {
// Console.WriteLine("Hello world!");
// }
// var key = Cv2.WaitKey(1);
// if (key == 'q')
// {
// break;
// }
// }
//}
//catch
//{
// Console.WriteLine("例外：カメラが取得できませんでした。");
//}
//finally
//{
// for (int i = 0; i < numCamera; i++)
// {
// if (videoCaps[i] != null)
// videoCaps[i].Dispose();
// if (windows[i] != null)
// {
// windows[i].Dispose();
// }
// }
//}
//test
#endregion
}
public bool EnumerateCameras(List <int> camIdx)
{
camIdx.Clear();
// list of all CAP drivers (see highgui_c.h)
drivers = new List <CapDriver>();
// drivers.Add(new CapDriver { enumValue = CaptureDevice., "CV_CAP_MIL", "MIL proprietary drivers" });
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.VFW, enumName = "VFW", comment = "platform native"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.V4L, enumName = "V4L", comment = "platform native"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Firewire, enumName = "FireWire", comment = "IEEE 1394 drivers"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Fireware, enumName = "Fireware", comment = "IEEE 1394 drivers"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Qt, enumName = "Qt", comment = "Quicktime"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Unicap, enumName = "Unicap", comment = "Unicap drivers"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.DShow, enumName = "DSHOW", comment = "DirectShow (via videoInput)"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.PVAPI, enumName = "PVAPI", comment = "PvAPI, Prosilica GigE SDK"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.OpenNI, enumName = "OpenNI", comment = "OpenNI(for Kinect) "
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.OpenNI_ASUS, enumName = "OpenNI_ASUS", comment = "OpenNI(for Asus Xtion) "
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Android, enumName = "Android", comment = "Android"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.XIAPI, enumName = "XIAPI", comment = "XIMEA Camera API"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.AVFoundation, enumName = "AVFoundation", comment = "AVFoundation framework for iOS (OS X Lion will have the same API)"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Giganetix, enumName = "Giganetix", comment = "Smartek Giganetix GigEVisionSDK"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.MSMF, enumName = "MSMF", comment = "Microsoft Media Foundation (via videoInput)"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.WinRT, enumName = "WinRT", comment = "Microsoft Windows Runtime using Media Foundation"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.IntelPERC, enumName = "IntelPERC", comment = "Intel Perceptual Computing SDK"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.OpenNI2, enumName = "OpenNI2", comment = "OpenNI2 (for Kinect)"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.OpenNI2_ASUS, enumName = "OpenNI2_ASUS", comment = "OpenNI2 (for Asus Xtion and Occipital Structure sensors)"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.GPhoto2, enumName = "GPhoto2", comment = "gPhoto2 connection"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.GStreamer, enumName = "GStreamer", comment = "GStreamer"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.FFMPEG, enumName = "FFMPEG", comment = "Open and record video file or stream using the FFMPEG library"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Images, enumName = "Images", comment = "OpenCV Image Sequence (e.g. img_%02d.jpg)"
});
drivers.Add(new CapDriver {
enumValue = (int)CaptureDevice.Aravis, enumName = "Aravis", comment = "Aravis SDK"
});
string driverName, driverComment;
int driverEnum;
bool found;
Console.WriteLine("Searching for cameras IDs...");
for (int drv = 0; drv < drivers.Count; drv++)
{
driverName = drivers[drv].enumName;
driverEnum = drivers[drv].enumValue;
driverComment = drivers[drv].comment;
Console.WriteLine("Testing driver " + driverName);
found = false;
int maxID = 100; //100 IDs between drivers
if (driverEnum == (int)CaptureDevice.VFW)
{
maxID = 10; //VWF opens same camera after 10 ?!?
}
for (int idx = 0; idx < maxID; idx++)
{
VideoCapture cap = new VideoCapture(driverEnum + idx); // open the camera
cap.Fps = 120;
cap.FrameWidth = 4096;
cap.FrameHeight = 2160;
cap.FourCC = "MJPG";
if (cap.IsOpened()) // check if we succeeded
{
Mat frame = new Mat();
found = true;
camIdx.Add(driverEnum + idx); // vector of all available cameras
cap.Read(frame);
if (frame.Empty())
{
Console.WriteLine(driverName + "+" + idx + "\t opens: OK \t grabs: FAIL");
}
else
{
Console.WriteLine(driverName + "+" + idx + "\t opens: OK \t grabs: OK " + frame.Width + "x" + frame.Height + "@" + cap.Fps);
}
}
cap.Release();
}
if (!found)
{
Console.WriteLine("Nothing !");
}
}
Console.WriteLine(camIdx.Count() + " camera IDs has been found ");
return(camIdx.Count() > 0); // returns success
}
//private Image<Hsv, byte> HsvIm;
//private DenseHistogram histogram = new DenseHistogram(255, new RangeF(0, 255)); //Histogram
//private float[] GrayHist = new float[255]; //Histogram
#endregion
#region Constructor
public DetectorFace(Form1 form)
{
this.form = form;
imageBox1 = new Emgu.CV.UI.ImageBox
{
Location = new Point(12, 12),
Size = new Size(form.Width / 2 - 12, form.Height - 80), //просчитать размеры для оптимального детектирования картинки в зависимости от скалирования каскада
Name = "imageBox1",
TabIndex = 2,
TabStop = false,
FunctionalMode = Emgu.CV.UI.ImageBox.FunctionalModeOption.Minimum,
BorderStyle = System.Windows.Forms.BorderStyle.None,
BackgroundImageLayout = System.Windows.Forms.ImageLayout.Stretch
};
imageBox2 = new Emgu.CV.UI.ImageBox
{
Location = new Point(form.Width / 2 - 12, 12),
Size = new Size(form.Width / 2 - 12, form.Height - 80), //просчитать размеры для оптимального детектирования картинки в зависимости от скалирования каскада
Name = "imageBox2",
TabIndex = 2,
TabStop = false,
FunctionalMode = Emgu.CV.UI.ImageBox.FunctionalModeOption.Minimum,
BorderStyle = System.Windows.Forms.BorderStyle.None,
BackgroundImageLayout = System.Windows.Forms.ImageLayout.Tile
};
/*//trackBar
* trackBar = new TrackBar()
* {
* Location = new Point(),
* Size = new Size(),
* Name = "trackBar",
* TabIndex = 2,
* TabStop = false,
* TickFrequency = 1,
* Maximum = 255,
* Minimum = 0,
* Value = 50
* };*/
/*///HistogramBox
* histogramBox = new Emgu.CV.UI.HistogramBox
* {
* Location = new Point(form.Width / 2 - 12, 12),
* Size = new Size(form.Width / 2 - 12, form.Height - 80), //просчитать размеры для оптимального детектирования картинки в зависимости от скалирования каскада
* Name = "histogramBox",
* TabIndex = 2,
* TabStop = false,
* FunctionalMode = Emgu.CV.UI.ImageBox.FunctionalModeOption.Minimum,
* BorderStyle = System.Windows.Forms.BorderStyle.None,
* BackgroundImageLayout = System.Windows.Forms.ImageLayout.Tile,
* };*/
this.form.Controls.Add(imageBox1);
this.form.Controls.Add(imageBox2);
// this.form.Controls.Add(histogramBox);
capture = new VideoCapture(Config.Config.DefaultCameraIndex, VideoCapture.API.Any);
capture.SetCaptureProperty(CapProp.FrameWidth, imageBox1.Width);
capture.SetCaptureProperty(CapProp.FrameHeight, imageBox1.Height);
pen = new Pen(Color.Red, 3);
// histogramBox.GenerateHistogram("hist1", Color.Red, HsvIm.Mat, 256, HsvIm.Mat. );
// histogramBox.GenerateHistograms(HsvIm, 250);
// HsvIm = capture.QueryFrame().ToImage<Hsv, byte>();
// TrackBar.Scroll += trackBar_Scroll; ///trackBar
im = capture.QueryFrame().ToImage <Hsv, byte>();
capture.ImageGrabbed += Capture_ImageGrabbed;
pen = new Pen(Color.Green, 4);
}
private void videoCaptureDevice1_ImageCaptured(object source, VideoCapture.ImageCapturedEventArgs e)
{
// set the picturebox picture
CubeAnalyser.SourceImage = e.WebCamImage;
saveImageToolStripMenuItem.Enabled = true;
this.picbVideoCapture.Image = (Image)e.WebCamImage.Clone();
this.picbFaceImg.Image = (Image)e.WebCamImage.Clone();
FilterAllImages();
}
public void GetClassHandles(VideoCapture.VideoCapture inVideo, Output.ControllerMax inMax, Output.TitanOne.Write inTo, VideoResolution inVid)
{
Class.VideoCapture = inVideo;
Class.ControllerMax = inMax;
Class.TitanOne = inTo;
Class.VideoResolution = inVid;
}
private static void Main()
{
try
{
var cap = new VideoCapture(0);
//var cap = new VideoCapture("20090124_WeeklyAddress.ogv.360p.webm");
if (!cap.IsOpened())
{
Console.WriteLine("Unable to connect to camera");
return;
}
using (var win = new ImageWindow())
{
// Load face detection and pose estimation models.
using (var detector = Dlib.GetFrontalFaceDetector())
using (var poseModel = ShapePredictor.Deserialize("shape_predictor_68_face_landmarks.dat"))
{
// Grab and process frames until the main window is closed by the user.
while (!win.IsClosed())
{
// Grab a frame
var temp = new Mat();
if (!cap.Read(temp))
{
break;
}
// Turn OpenCV's Mat into something dlib can deal with. Note that this just
// wraps the Mat object, it doesn't copy anything. So cimg is only valid as
// long as temp is valid. Also don't do anything to temp that would cause it
// to reallocate the memory which stores the image as that will make cimg
// contain dangling pointers. This basically means you shouldn't modify temp
// while using cimg.
var array = new byte[temp.Width * temp.Height * temp.ElemSize()];
Marshal.Copy(temp.Data, array, 0, array.Length);
using (var cimg = Dlib.LoadImageData <RgbPixel>(array, (uint)temp.Height, (uint)temp.Width, (uint)(temp.Width * temp.ElemSize())))
{
// Detect faces
var faces = detector.Detect(cimg);
// Find the pose of each face.
var shapes = new List <FullObjectDetection>();
for (var i = 0; i < faces.Length; ++i)
{
var det = poseModel.Detect(cimg, faces[i]);
shapes.Add(det);
}
// Display it all on the screen
win.ClearOverlay();
win.SetImage(cimg);
var lines = Dlib.RenderFaceDetections(shapes);
win.AddOverlay(lines);
foreach (var line in lines)
{
line.Dispose();
}
}
}
}
}
}
//catch (serialization_error&e)
//{
// cout << "You need dlib's default face landmarking model file to run this example." << endl;
// cout << "You can get it from the following URL: " << endl;
// cout << " http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2" << endl;
// cout << endl << e.what() << endl;
//}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
public static List<Mat> PreviewCamera(bool savePictureMode)
{
// Opens a camera device
var capture = new VideoCapture(0);
if (!capture.IsOpened())
return null;
var returnedMat = new List<Mat>();
var frame = new Mat();
var returnedframe = new Mat();
while (true)
{
// Read image
capture.Read(frame);
if (frame.Empty())
return null;
Cv2.ImShow("Camera", frame);
var key = Cv2.WaitKey(30);
if (key == 27) //wait for esc key
{
Cv2.DestroyAllWindows();
return returnedMat;
}
if (key == 115) //wait for s
{
returnedframe = frame.Clone();
returnedMat.Add(returnedframe);
}
}
}
void Recognize(object param)
{
stop = false;
var mode = (RecognizationModes)param;
List <Rect> boundRect = new List <Rect>();
int sleepTime = 0;
int frameCount = 0;
if (mode == RecognizationModes.image)
{
image = new Mat(path);
}
else
{
image = new Mat();
capture = new VideoCapture(0);
double fps = capture.Fps;
if (fps == 0)
{
fps = 60;
}
sleepTime = (int)Math.Round(1000 / fps);
}
using (Mat grayImage = new Mat())
using (Mat sobelImage = new Mat())
using (Mat tresholdImage = new Mat())
{
while (true)
{
if (frameCount % 6 == 0)
{
boundRect.Clear();
}
if (mode == RecognizationModes.camera)
{
capture.Read(image);
}
//make gray image
Cv2.CvtColor(image, grayImage, ColorConversionCodes.BGR2GRAY);
//sobel filter to detect vertical edges
Cv2.Sobel(grayImage, sobelImage, MatType.CV_8U, 1, 0);
Cv2.Threshold(sobelImage, tresholdImage, 0, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
using (Mat element = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(10, 15)))
{
Cv2.MorphologyEx(tresholdImage, tresholdImage, MorphTypes.Close, element);
OpenCvSharp.Point[][] edgesArray = tresholdImage.Clone().FindContoursAsArray(RetrievalModes.External, ContourApproximationModes.ApproxNone);
foreach (OpenCvSharp.Point[] edges in edgesArray)
{
OpenCvSharp.Point[] normalizedEdges = Cv2.ApproxPolyDP(edges, 17, true);
Rect appRect = Cv2.BoundingRect(normalizedEdges);
if (appRect.Height > 10 && appRect.Width > 20 && appRect.Height / (double)appRect.Width < 0.45)
{
boundRect.Add(appRect);
}
}
}
foreach (Rect r in boundRect)
{
Mat cut = new Mat(image, r);
OpenCvSharp.Size size = new OpenCvSharp.Size(25, 25);
Cv2.GaussianBlur(cut, cut, size, 10);
image.CopyTo(cut);
}
frameCount++;
pictureBox1.Image = new Bitmap(OpenCvSharp.Extensions.BitmapConverter.ToBitmap(image));
//Cv2.ImWrite(@"D:\Visual_studio\RegistrationPlateRecognizer\Pictures\hidePlate.jpg", image);
Cv2.WaitKey(sleepTime);
if (mode == RecognizationModes.image)
{
return;
}
if (stop)
{
pictureBox1.Image = null;
return;
}
}
}
}
/// <summary>
/// 关闭窗口
/// </summary>
/// <param name="e"></param>
protected override void OnClosing(CancelEventArgs e)
{
VideoCapture.Close();
base.OnClosing(e);
}
/// <summary>
/// 窗口加载
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void Window_Loaded(object sender, RoutedEventArgs e)
{
VideoCapture.Play();
}
static void Main(string[] args)
{
//var capture = new VideoCapture("rtmp://rtmp.open.ys7.com/openlive/61e96da9f12a4d058f4737d02c42998d");
var capture = new VideoCapture("D:\\视频1\\192.168.1.65_01_20190314114136657_1.mp4");
modelFile = "logs_2\\pb\\frozen_model.pb";
//dir = "tmp";
//List<string> files = Directory.GetFiles("img").ToList();
//ModelFiles(dir);
var graph = new TFGraph();
// 从文件加载序列化的GraphDef
var model = File.ReadAllBytes(modelFile);
//导入GraphDef
graph.Import(model, "");
using (var windowSrc = new Window("src"))
using (var frame = new Mat())
using (var image缩小 = new Mat())
using (var session = new TFSession(graph))
{
string file = "1.jpg";
//var labels = File.ReadAllLines(labelsFile);
Console.WriteLine("TensorFlow图像识别 LineZero");
//var frame = new Mat();
//var inrange = new Mat();
//var fg = new Mat();
while (true)
{
capture.Read(frame);
if (frame.Empty())
{
break;
}
Cv2.Resize(frame, image缩小, new Size(280, 280), 0, 0, InterpolationFlags.Linear);//缩小28*28
Cv2.ImWrite(file, image缩小);
var tensor = CreateTensorFromImageFile(file);
// Run inference on the image files
// For multiple images, session.Run() can be called in a loop (and
// concurrently). Alternatively, images can be batched since the model
// accepts batches of image data as input.
var runner = session.GetRunner();
runner.AddInput(graph["x_input"][0], tensor).Fetch(graph["softmax_linear/softmax_linear"][0]);
var output = runner.Run();
// output[0].Value() is a vector containing probabilities of
// labels for each image in the "batch". The batch size was 1.
// Find the most probably label index.
var result = output[0];
var rshape = result.Shape;
if (result.NumDims != 2 || rshape[0] != 1)
{
var shape = "";
foreach (var d in rshape)
{
shape += $"{d} ";
}
shape = shape.Trim();
Console.WriteLine($"Error: expected to produce a [1 N] shaped tensor where N is the number of labels, instead it produced one with shape [{shape}]");
Environment.Exit(1);
}
// You can get the data in two ways, as a multi-dimensional array, or arrays of arrays,
// code can be nicer to read with one or the other, pick it based on how you want to process
// it
bool jagged = true;
var bestIdx = 0;
float p = 0, best = 0;
if (jagged)
{
var probabilities = ((float[][])result.GetValue(jagged: true))[0];
double[] d = floatTodouble(probabilities);
double[] retResult = Softmax(d);
for (int i = 0; i < retResult.Length; i++)
{
if (probabilities[i] > best)
{
bestIdx = i;
best = probabilities[i];
}
}
}
else
{
var val = (float[, ])result.GetValue(jagged: false);
// Result is [1,N], flatten array
for (int i = 0; i < val.GetLength(1); i++)
{
if (val[0, i] > best)
{
bestIdx = i;
best = val[0, i];
}
}
}
//Console.WriteLine($"{Path.GetFileName(file)} 最佳匹配: [{bestIdx}] {best * 100.0}% 标识为：{labels[bestIdx]}");
string 标识1 = "";
switch (bestIdx)
{
case 0:
标识1 = "kong0";
break;
case 1:
标识1 = "yao1";
break;
case 2:
标识1 = "yao2";
break;
case 3:
标识1 = "yao3";
break;
case 4:
标识1 = "yao4";
break;
case 5:
标识1 = "xian1";
break;
case 6:
标识1 = "xian2";
break;
case 7:
标识1 = "have7";
break;
}
string 标识2 = "--: " + (best).ToString() + "%";
Point textPos = new Point(1, 100);
image缩小.PutText(标识1 + 标识2, textPos, HersheyFonts.HersheySimplex, 0.5, Scalar.White);
windowSrc.ShowImage(image缩小);
Cv2.WaitKey(10);
}
}
Console.ReadKey();
}
private void Form1_Load(object sender, EventArgs e)
{
Text += " (SDK v" + VideoCapture1.SDK_Version + ", " + VideoCapture1.SDK_State + ")";
tmRecording.Elapsed += (senderx, args) =>
{
UpdateRecordingTime();
};
cbOutputFormat.SelectedIndex = 2;
foreach (var device in VideoCapture1.Video_CaptureDevicesInfo)
{
cbVideoInputDevice.Items.Add(device.Name);
}
if (cbVideoInputDevice.Items.Count > 0)
{
cbVideoInputDevice.SelectedIndex = 0;
}
cbVideoInputDevice_SelectedIndexChanged(null, null);
foreach (var device in VideoCapture1.Audio_CaptureDevicesInfo)
{
cbAudioInputDevice.Items.Add(device.Name);
}
if (cbAudioInputDevice.Items.Count > 0)
{
cbAudioInputDevice.SelectedIndex = 0;
cbAudioInputDevice_SelectedIndexChanged(null, null);
}
cbAudioInputLine.Items.Clear();
if (!string.IsNullOrEmpty(cbAudioInputDevice.Text))
{
var deviceItem =
VideoCapture1.Audio_CaptureDevicesInfo.First(device => device.Name == cbAudioInputDevice.Text);
if (deviceItem != null)
{
foreach (string line in deviceItem.Lines)
{
cbAudioInputLine.Items.Add(line);
}
if (cbAudioInputLine.Items.Count > 0)
{
cbAudioInputLine.SelectedIndex = 0;
cbAudioInputLine_SelectedIndexChanged(null, null);
cbAudioInputFormat_SelectedIndexChanged(null, null);
}
}
}
string defaultAudioRenderer = string.Empty;
foreach (string audioOutputDevice in VideoCapture1.Audio_OutputDevices)
{
cbAudioOutputDevice.Items.Add(audioOutputDevice);
if (audioOutputDevice.Contains("Default DirectSound Device"))
{
defaultAudioRenderer = audioOutputDevice;
}
}
if (cbAudioOutputDevice.Items.Count > 0)
{
if (string.IsNullOrEmpty(defaultAudioRenderer))
{
cbAudioOutputDevice.SelectedIndex = 0;
}
else
{
cbAudioOutputDevice.Text = defaultAudioRenderer;
}
}
edOutput.Text = Environment.GetFolderPath(Environment.SpecialFolder.MyDocuments) + "\\VisioForge\\" + "output.mp4";
edNewFilename.Text = Environment.GetFolderPath(Environment.SpecialFolder.MyDocuments) + "\\VisioForge\\" + "output_new.mp4";
if (VideoCapture.Filter_Supported_EVR())
{
VideoCapture1.Video_Renderer.Video_Renderer = VFVideoRenderer.EVR;
}
else if (VideoCapture.Filter_Supported_VMR9())
{
VideoCapture1.Video_Renderer.Video_Renderer = VFVideoRenderer.VMR9;
}
else
{
VideoCapture1.Video_Renderer.Video_Renderer = VFVideoRenderer.VideoRenderer;
}
}
public frmFaceRecognition()
{
InitializeComponent();
WebCam = new VideoCapture(2);
#region camera
pbWebCam.SizeMode = PictureBoxSizeMode.StretchImage;
CaptureDevice = new FilterInfoCollection(FilterCategory.VideoInputDevice);
foreach (FilterInfo Device in CaptureDevice)
{
comboBox1.Items.Add(Device.Name);
}
#endregion camera
#region initialization
FaceDetection = new CascadeClassifier(System.IO.Path.GetFullPath(@"../../Authentification/data/haarcascade_frontalface_default.xml"));
EyeDetection = new CascadeClassifier(System.IO.Path.GetFullPath(@"../../Authentification/data/haarcascade_eye.xml"));
FaceRecognition = new EigenFaceRecognizer();
Frame = new Mat();
Faces = new List <Image <Gray, byte> >();
IDs = new List <int>();
#endregion initialization
#region eigen_list
try
{
//Loading previously added images(negativ results)
string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");
var labels = Labelsinfo.Split('%');
foreach (string label in labels)
{
IDs.Add(Convert.ToInt32(label));
}
IDs.RemoveAt(0);
NumberOfTestImages = Convert.ToInt16(labels[0]);
string faceString = "";
for (int i = 1; i < NumberOfTestImages + 1; i++)
{
faceString = "face" + i + ".bmp";
Faces.Add(new Image <Gray, byte>(Application.StartupPath + "/TrainedFaces/" + faceString));
}
}
catch (Exception e)
{
MessageBox.Show("Error with loading data static data", "Loading error", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
//FaceRecognition = new EigenFaceRecognizer(
// Faces.ToArray(),
// IDs.ToArray(),
// 3000,
// double.PositiveInfinity
// );
var arrayLength = Faces.Count;
//Image<Gray, byte>[] facesArray = Faces.ToArray();
//int[] IDsArray = IDs.ToArray();
Mat[] mats = new Mat[Faces.Count];
int[] newIds = new int[Faces.Count];
for (int i = 0; i < Faces.Count; i++)
{
mats[i] = Faces[i].Mat;
newIds[i] = IDs[i];
}
FaceRecognition.Train(mats, newIds);
var result = FaceRecognition.Predict(mats[0]);
#endregion eigen_list
StartCamera();
}
private List <InputFileModel> GetInputFromStereoCamera(VideoCapture LeftCamera, VideoCapture RightCamera, int countInputFile = 0)
{
LeftCamera.Grab();
RightCamera.Grab();
Mat LeftImage = new Mat();
Mat RightImage = new Mat();
LeftCamera.Retrieve(LeftImage);
RightCamera.Retrieve(RightImage);
LeftImage.Save(Path.Combine($@"{tempLeftStackDirectory}", $"Left_{countInputFile}.JPG"));
RightImage.Save(Path.Combine($@"{tempRightStackDirectory}", $"Right_{countInputFile}.JPG"));
var inputFileLeft = new InputFileModel(Path.Combine($@"{tempLeftStackDirectory}", $"Left_{countInputFile}.JPG"));
var imageList = _winForm.ImageList[(int)EListViewGroup.LeftCameraStack];
var listViewer = _winForm.ListViews[(int)EListViewGroup.LeftCameraStack];
_fileManager.AddInputFileToList(inputFileLeft, _fileManager.listViewerModel.ListOfListInputFolder[(int)EListViewGroup.LeftCameraStack], imageList, listViewer);
var inputFileRight = new InputFileModel(Path.Combine($@"{tempRightStackDirectory}", $"Right_{countInputFile}.JPG"));
imageList = _winForm.ImageList[(int)EListViewGroup.RightCameraStack];
listViewer = _winForm.ListViews[(int)EListViewGroup.RightCameraStack];
_fileManager.AddInputFileToList(inputFileLeft, _fileManager.listViewerModel.ListOfListInputFolder[(int)EListViewGroup.RightCameraStack], imageList, listViewer);
var returnList = new List <InputFileModel>();
returnList.Add(inputFileLeft);
returnList.Add(inputFileRight);
return(returnList);
}
private void InterpretHelper(int index)
{
System.Drawing.Bitmap bitmap = GetBitmap(index);
VideoCapture capture = new VideoCapture(index, bitmap);
CopyPixelsFromDrawingBitmap(bitmap, _currentBuffer);
_currentFrame = Bitmap.FromPixels(bitmap.Width, bitmap.Height, _currentBuffer);
IBoundingBox invalidated = GetDirtyRect(_previousFrame, _currentFrame);
var tags = new Dictionary<string, object>();
tags.Add("videocapture", capture);
tags.Add("invalidated", invalidated);
tags.Add("previous", _previousTree);
Tree root = Tree.FromPixels(_currentFrame, tags);
Tree interpretation = _interpretationLogic.Interpret(root);
if (FrameInterpreted != null)
FrameInterpreted(this, new InterpretedFrame(interpretation));
//Swap the buffers we're writting to
int[] tmp = _currentBuffer;
_currentBuffer = _previousBuffer;
_previousBuffer = tmp;
//Set the previous bitmap and tree
_previousTree = interpretation;
_previousFrame = Bitmap.FromPixels(_currentFrame.Width, _currentFrame.Height, _previousBuffer);
}
/// <summary>
/// Initializes the DeviceClient and sets up the callback to receive
/// messages containing temperature information
/// </summary>
static async Task Init(string connectionString)
{
try
{
LogUtil.Log($"Init: Connection String: {connectionString}", LogLevel.Info);
var mqttSettings = new MqttTransportSettings(TransportType.Mqtt_Tcp_Only);
// During dev you might want to bypass the cert verification. It is highly recommended to verify certs systematically in production
mqttSettings.RemoteCertificateValidationCallback = (sender, certificate, chain, sslPolicyErrors) => true;
ITransportSettings[] settings = { mqttSettings };
// Open a connection to the Edge runtime
_deviceClient = DeviceClient.CreateFromConnectionString(connectionString, settings);
var moduleTwin = await _deviceClient.GetTwinAsync();
moduleId = moduleTwin.ModuleId; // not work yet.
LogUtil.Log($"moduleTwin.moduleId: {moduleId}");
var moduleTwinCollection = moduleTwin.Properties.Desired;
if (moduleTwinCollection["ModuleId"] != null)
{
moduleId = moduleTwinCollection["ModuleId"];
LogUtil.Log($"ModuleId: {moduleId}", LogLevel.Info);
}
if (moduleTwinCollection["RTSP"] != null)
{
string tRTSP = moduleTwinCollection["RTSP"];
LogUtil.Log($"RTSP: {tRTSP}", LogLevel.Info);
lock (captureLocker)
{
if (_cameraCapture != null)
{
_cameraCapture.Dispose();
}
_cameraCapture = new VideoCapture(tRTSP);
RTSP = tRTSP;
}
LogUtil.Log("RTSP Set", LogLevel.Info);
}
if (moduleTwinCollection["StorageConnectString"] != null)
{
STORAGECONNECTSTRING = moduleTwinCollection["StorageConnectString"];
LogUtil.Log($"StorageConnectString: {STORAGECONNECTSTRING}", LogLevel.Info);
}
if (moduleTwinCollection["StorageURI"] != null)
{
STORAGEURI = moduleTwinCollection["StorageURI"];
LogUtil.Log($"StorageURI: {STORAGEURI}", LogLevel.Info);
}
await _deviceClient.OpenAsync();
LogUtil.Log("IoT Hub module client initialized.", LogLevel.Info);
// Register callback to be called when a message is received by the module
await _deviceClient.SetInputMessageHandlerAsync("input1", PipeMessage, _deviceClient);
// Attach callback for Twin desired properties updates
await _deviceClient.SetDesiredPropertyUpdateCallbackAsync(OnDesiredPropertiesUpdate, null);
}
catch (Exception e)
{
LogUtil.LogException(e);
}
}
public void OpenVideo(string fileName)
{
capture = new VideoCapture(fileName);
}
private static async Task GetFrame()
{
Mat frame = null;
Mat newFrame = null;
try
{
frame = _cameraCapture.RetrieveMat();
if (frame != null && (!frame.Empty()))
{
newFrame = frame.Resize(new Size(CAPTUREWIDTH, CAPTUREHEIGHT));
lock (frameLoker)
{
if (latestFrame == newFrame)
{
LogUtil.Log("latest frame the same !!!!!!");
}
if (latestFrame != null)
{
latestFrame.Dispose();
}
latestFrame = newFrame.Clone();
matBuffer.Add(newFrame.Clone());
if (matBuffer.Count >= bufferSize)
{
var firstmat = matBuffer[0];
matBuffer.RemoveAt(0);
firstmat.Dispose();
}
}
}
else
{
if (frame != null)
{
frame.Dispose();
}
failure++;
LogUtil.Log($"failed {failure} times.", LogLevel.Warning);
}
if (failure >= MAXFAILTIMES)
{
LogUtil.Log($"Begin to Reset VideoCapture after failed {MAXFAILTIMES} times.", LogLevel.Warning);
await Task.Delay(5000);
lock (captureLocker)
{
if (_cameraCapture != null)
{
_cameraCapture.Dispose();
}
_cameraCapture = new VideoCapture(RTSP);
}
failure = 0;
LogUtil.Log($"Reset VideoCapture after failed {MAXFAILTIMES} times.", LogLevel.Warning);
}
}
catch (Exception e)
{
LogUtil.LogException(e);
}
finally
{
if (frame != null)
{
frame.Dispose();
}
if (newFrame != null)
{
newFrame.Dispose();
}
}
}
public bool Hatching()
{
Log($"EggHatch.Hatched()");
return(VideoCapture.Match(415, 895, ImageRes.Get("egg_hatched"), DefaultImageCap, VideoCapture.LineSampler(3)));
}
static void Main(string[] args)
{
try
{
LogUtil.Log("start", LogLevel.Info);
// The Edge runtime gives us the connection string we need -- it is injected as an environment variable
string connectionString = Environment.GetEnvironmentVariable("EdgeHubConnectionString");
Init(connectionString).Wait();
LogUtil.Log("device client opend!", LogLevel.Info);
// --for debug only--
// RTSP = "rtsp://*****:*****@10.172.94.234:554/h264/ch1/main/av_stream";
// RTSP = "rtsp://23.102.236.116:5554/test2.mpg";
_cameraCapture = new VideoCapture(RTSP);
_hog = new HOGDescriptor();
_hog.SetSVMDetector(HOGDescriptor.GetDefaultPeopleDetector());
Task.Run(async() =>
{
while (true)
{
var tRtsp = "";
lock (captureLocker)
{
tRtsp = RTSP;
}
if (!String.IsNullOrEmpty(tRtsp) && _cameraCapture != null)
{
break;
}
else
{
await Task.Delay(2000);
LogUtil.Log("Check RTSP", LogLevel.Warning);
}
}
while (true)
{
await GetFrame();
}
});
Task.Run(async() =>
{
while (true)
{
await ProcessFrame();
await Task.Delay(1000);
}
}).Wait();
LogUtil.Log("Main Finshed!");
}
catch (Exception e)
{
LogUtil.LogException(e);
}
}
public VideoProcessing(VideoCapture vc, VideoOverlaySettings settings)
{
videoCapture = vc;
s = settings;
}
public static int Main(string[] args)
{
SerialPort serial;
try
{
IEnumerable <PortInfo> ports = PortInfo.GetPorts();
string port = ports.FirstOrDefault((pi) => pi.Description == serialDevice)?.DeviceID;
if (port != null)
{
serial = new SerialPort(port, baudRate);
}
else
{
throw new IOException("Could not connect to serial port.");
}
}
catch (Exception ex)
{
Console.WriteLine(ex);
return(1);
}
Console.WriteLine();
TcpListener listener = new TcpListener(IPAddress.Any, 5050);
re:
try
{
listener.Start();
Console.WriteLine("Listening " + listener.LocalEndpoint);
using (var client = listener.AcceptTcpClient())
{
listener.Stop();
Console.WriteLine("Connection established " + client.Client.RemoteEndPoint);
using (NetworkStream stream = client.GetStream())
{
int width, height, fps, quality;
using (var reader = new BinaryReader(stream, System.Text.Encoding.ASCII, true))
{
using (var writer = new BinaryWriter(stream, System.Text.Encoding.ASCII, true))
{
width = reader.ReadInt32();
height = reader.ReadInt32();
fps = reader.ReadInt32();
quality = reader.ReadInt32();
Console.WriteLine("Parameters received:");
Console.WriteLine($" Width: {width}");
Console.WriteLine($" Height: {height}");
Console.WriteLine($" Fps: {fps}");
Console.WriteLine($" Quality: {quality}");
var encoderParam = new ImageEncodingParam(ImwriteFlags.JpegQuality, quality);
using (var cap = new VideoCapture(0)
{
FrameWidth = width, FrameHeight = height, Fps = fps
})
{
Console.WriteLine("Started video capturing...");
Mat imgMatrix = new Mat();
Mat mask = new Mat();
Mat tresh = new Mat();
try
{
Scalar lastSeen = default(Scalar);
bool autoPilot = false,
camAuto = false,
moveAuto = false,
none;
while (client.Connected && stream.CanWrite)
{
Command commandTaken = (Command)reader.ReadByte();
autoPilot = commandTaken.HasFlag(Command.AutoPilot);
camAuto = commandTaken.HasFlag(Command.CamAuto);
moveAuto = commandTaken.HasFlag(Command.MoveAuto);
none = commandTaken == Command.None;
if (cap.Read(imgMatrix))
{
Cv2.CvtColor(imgMatrix, mask, ColorConversionCodes.BGR2HSV);
Cv2.InRange(mask, greenLower, greenUpper, tresh);
Cv2.Erode(tresh, tresh, null, iterations: 2);
Cv2.Dilate(tresh, tresh, null, iterations: 2);
Cv2.FindContours(
tresh,
out Point[][] contours,
out HierarchyIndex[] hierarchyIndexes,
RetrievalModes.External,
ContourApproximationModes.ApproxSimple
);
if (contours.Length > 0)
{
contours.OrderBy(element => Cv2.ContourArea(element));
Point[] max = contours[contours.Length - 1];
Cv2.MinEnclosingCircle(max, out Point2f xy, out float radius);
//Moments M = Cv2.Moments(max);
//Point center = new Point((M.M10 / M.M00), (M.M01 / M.M00));
Point center = new Point(xy.X, xy.Y);
if (radius > 10.0f)
{
Cv2.Circle(imgMatrix, center, (int)radius, new Scalar(0, 255, 255), thickness: 2);
Cv2.Circle(imgMatrix, center, 5, new Scalar(0, 0, 255), thickness: -1);
//find the ball which region on the screen horizontally [0-5]
int xRegion = center.X.Map(0, width, 0, 3);
//find the ball which region on the screen vertically [0-5]
int yRegion = center.Y.Map(0, height, 0, 3);
//find the ball is too far from camera or too close
int zRegion = ((int)radius).Map(10, 400, 0, 3);
lastSeen = FindBallCoordinates((int)radius, center, new Point(width / 2, height / 2));
#region Automatic Decisions
Command command = 0;
if (autoPilot)
{
if (xRegion < 1 && yRegion < 1)
{
command |= Command.CamLeft | Command.CamUp;
}
else if (xRegion < 1 && yRegion > 1)
{
command |= Command.CamLeft | Command.CamDown;
}
else if (xRegion > 1 && yRegion < 1)
{
command |= Command.CamRight | Command.CamUp;
}
else if (xRegion > 1 && yRegion > 1)
{
command |= Command.CamRight | Command.CamDown;
}
else if (xRegion < 1)
{
command |= Command.CamLeft;
}
else if (xRegion > 1)
{
command |= Command.CamRight;
}
else if (yRegion < 1)
{
command |= Command.CamUp;
}
else if (yRegion > 1)
{
command |= Command.CamDown;
}
if (zRegion > 1)
{
command |= Command.MoveBackward;
}
else if (zRegion < 1)
{
command |= Command.MoveForward;
}
byte[] message = { (byte)command };
serial.Write(message, 0, 1);
}
else if (camAuto)
{
if (xRegion < 1 && yRegion < 1)
{
command |= Command.CamLeft | Command.CamUp;
}
else if (xRegion < 1 && yRegion > 1)
{
command |= Command.CamLeft | Command.CamDown;
}
else if (xRegion > 1 && yRegion < 1)
{
command |= Command.CamRight | Command.CamUp;
}
else if (xRegion > 1 && yRegion > 1)
{
command |= Command.CamRight | Command.CamDown;
}
else if (xRegion < 1)
{
command |= Command.CamLeft;
}
else if (xRegion > 1)
{
command |= Command.CamRight;
}
else if (yRegion < 1)
{
command |= Command.CamUp;
}
else if (yRegion > 1)
{
command |= Command.CamDown;
}
byte[] message = { (byte)(command | (commandTaken & Command.MoveAuto)) };
serial.Write(message, 0, 1);
}
else if (moveAuto)
{
if (zRegion > 1 && xRegion < 1)
{
command |= Command.MoveForward | Command.MoveLeft;
}
else if (zRegion > 1 && xRegion > 1)
{
command |= Command.MoveForward | Command.MoveRight;
}
else if (zRegion < 1 && xRegion < 1)
{
command |= Command.MoveBackward | Command.MoveRight;
}
else if (zRegion < 1 && xRegion > 1)
{
command |= Command.MoveBackward | Command.MoveLeft;
}
else if (zRegion > 1)
{
command |= Command.MoveBackward;
}
else if (zRegion < 1)
{
command |= Command.MoveForward;
}
else if (xRegion < 1)
{
command |= Command.MoveLeft;
}
else if (xRegion > 1)
{
command |= Command.MoveRight;
}
byte[] message = { (byte)(command | (commandTaken & Command.CamAuto)) };
serial.Write(message, 0, 1);
}
else if (none)
{
byte[] message = { (byte)(commandTaken) };
serial.Write(message, 0, 1);
}
#endregion
}
else
{
Console.WriteLine($"{lastSeen.ToString()}");
}
}
Cv2.ImEncode(".jpg", imgMatrix, out byte[] result, encoderParam);
writer.Write(result.Length);
stream.Write(result, 0, result.Length);
}
private void BtnCaptureStart_Click(object sender, RoutedEventArgs e)
{
this.MyVideoCapture = new VideoCapture();
bool result = this.MyVideoCapture.CreateCapture();
if (!result)
{
MessageBox.Show("キャプチャの作成に失敗しました。");
}
result = this.MyVideoCapture.StartCapture();
if (!result)
{
MessageBox.Show("キャプチャの開始に失敗しました。");
}
this.NotifyPropertyChanged("IsCaptureStartButtonEnabled");
this.NotifyPropertyChanged("IsCaptureEndButtonEnabled");
}
/// <param name="parameters">
/// [0] - Path to image,
/// [1] - Cascade 1,
/// [2] - Cascade 2 ...
/// </param>
private actionResult FindObjects(string[] parameters)
{
var ar = new actionResult();
#region Parameters parsing
switch (parameters.Length)
{
case 0: {
ar.setError("Path to image not specified.");
return(ar);
}
case 1: {
ar.setError("Cascade name not specified.");
return(ar);
}
}
Image <Gray, byte> grayImage;
if (string.IsNullOrEmpty(parameters[0]))
{
using (var capture = new VideoCapture()) {
Thread.Sleep(PluginOptions.CameraDelayMs);
grayImage = capture.QueryFrame().ToImage <Gray, byte>();
}
}
else
{
try {
grayImage = new Image <Gray, byte>(parameters[0]);
}
catch {
ar.setError("Invalid path to image.");
return(ar);
}
}
if (PluginOptions.UseImageCorrection)
{
grayImage._EqualizeHist();
}
#endregion
var resultString = "";
for (var i = 1; i < parameters.Length; i++)
{
if (string.IsNullOrEmpty(parameters[i]))
{
continue;
}
using (var classifier = new CascadeClassifier($"{PluginOptions.CascadesPath}haarcascade_{parameters[i].ToLower().Trim()}.xml")) {
Rectangle[] objects = classifier.DetectMultiScale(grayImage, 1.1, 10);
if (objects.Length != 0)
{
for (var index = 0; index < objects.Length; index++)
{
grayImage.Draw(objects[index], new Gray(0), 2);
}
}
resultString += $"<{parameters[i]}:{objects.Length}>\n";
}
}
SaveImage(grayImage.Bitmap);
grayImage.Dispose();
ar.setSuccess(resultString);
return(ar);
}
// Use this for initialization
void Start()
{
capture = new VideoCapture ();
#if UNITY_WEBGL && !UNITY_EDITOR
StartCoroutine(Utils.getFilePathAsync("768x576_mjpeg.mjpeg", (result) => {
capture.open (result);
Init();
}));
#else
capture.open (Utils.getFilePath ("768x576_mjpeg.mjpeg"));
Init ();
#endif
}
private actionResult TeserractOcr(string[] parameters)
{
var ar = new actionResult();
#region Parameters parsing
switch (parameters.Length)
{
case 0: {
ar.setError("Path to image not specified.");
return(ar);
}
case 1: {
ar.setError("Symbols culture not specified.");
return(ar);
}
}
Image <Gray, byte> grayImage;
if (string.IsNullOrEmpty(parameters[0]))
{
using (var capture = new VideoCapture()) {
Thread.Sleep(PluginOptions.CameraDelayMs);
grayImage = capture.QueryFrame().ToImage <Gray, byte>();
}
}
else
{
try {
grayImage = new Image <Gray, byte>(parameters[0]);
}
catch {
ar.setError("Invalid path to image.");
return(ar);
}
}
if (PluginOptions.UseImageCorrection)
{
grayImage._EqualizeHist();
}
#endregion
using (Tesseract tesseract = parameters.Length == 2
? new Tesseract($"{PluginOptions.PluginPath}TessData\\", parameters[1], OcrEngineMode.TesseractOnly)
: parameters.Length == 3
? new Tesseract(
$"{PluginOptions.PluginPath}TessData\\", parameters[1], OcrEngineMode.TesseractOnly,
parameters[2]
)
: null) {
if (tesseract == null)
{
ar.setError("Failed to initialize recognizer due to invalid number of parameters.");
grayImage.Dispose();
return(ar);
}
string recognizedText;
using (Image <Gray, byte> imgThold = grayImage) {
CvInvoke.Threshold(grayImage, imgThold, 140, 255, ThresholdType.Binary);
tesseract.SetImage(imgThold);
recognizedText = tesseract.GetUTF8Text();
}
if (string.IsNullOrWhiteSpace(recognizedText))
{
ar.setError("No recognized symbols.");
}
else
{
ar.setSuccess(recognizedText);
}
grayImage.Dispose();
}
return(ar);
}
public void GetVideoCapture(VideoCapture.VideoCapture videoCapture)
{
_videoCapture = videoCapture;
}
private actionResult TrainFace(string[] parameters)
{
var ar = new actionResult();
#region Parameters parsing
switch (parameters.Length)
{
case 0: {
ar.setError("Path to image not specified.");
return(ar);
}
case 1: {
ar.setError("Face name not specified.");
return(ar);
}
}
Image <Gray, byte> grayImage;
if (string.IsNullOrEmpty(parameters[0]))
{
using (var capture = new VideoCapture()) {
Thread.Sleep(PluginOptions.CameraDelayMs);
grayImage = capture.QueryFrame().ToImage <Gray, byte>();
}
}
else
{
try {
grayImage = new Image <Gray, byte>(parameters[0]);
}
catch {
ar.setError("Invalid path to image.");
return(ar);
}
}
if (PluginOptions.UseImageCorrection)
{
grayImage._EqualizeHist();
}
#endregion
Rectangle[] faces;
using (var classifier = new CascadeClassifier($"{PluginOptions.CascadesPath}haarcascade_frontalface_default.xml")) {
faces = classifier.DetectMultiScale(grayImage, 1.1, 10);
}
if (faces.Length == 0)
{
ar.setError("No face recognized.");
return(ar);
}
using (Image <Gray, byte> faceImage = grayImage.Copy(faces[0]).Resize(100, 100, Inter.Cubic)) {
MainCtl.TrainedImages.Add(faceImage);
PluginOptions.PeopleFaces.Add(PluginOptions.PeopleFaces.Count + 1, parameters[1]);
faceImage.Save($"{PluginOptions.PluginPath}Faces\\face{MainCtl.TrainedImages.Count}.bmp");
}
PluginOptions.SaveOptionsToXml();
grayImage.Dispose();
using (FaceRecognizer recognizer = new EigenFaceRecognizer()) {
recognizer.Train(MainCtl.TrainedImages.ToArray(), PluginOptions.PeopleFaces.Keys.ToArray());
recognizer.Write($"{PluginOptions.PluginPath}SavedCascade.xml");
}
ar.setInfo($"Added face with name: {parameters[0]}.");
return(ar);
}
public void GetClassHandles(VideoCapture.VideoCapture inVideo, Write inMax, Output.TitanOne.Write inTo, VideoResolution inVid)
{
Class.VideoCapture = inVideo;
Class.CronusPlus = inMax;
Class.TitanOne = inTo;
Class.VideoResolution = inVid;
}
private actionResult RecognizeFace(string[] parameters)
{
var ar = new actionResult();
if (MainCtl.TrainedImages.Count == 0)
{
ar.setError("Database contains no trained faces.");
return(ar);
}
#region Parameters parsing
switch (parameters.Length)
{
case 0: {
ar.setError("Path to image not specified.");
return(ar);
}
case 1: {
ar.setError("Face name not specified.");
return(ar);
}
}
Image <Gray, byte> grayImage;
if (string.IsNullOrEmpty(parameters[0]))
{
using (var capture = new VideoCapture()) {
Thread.Sleep(PluginOptions.CameraDelayMs);
grayImage = capture.QueryFrame().ToImage <Gray, byte>();
}
}
else
{
try {
grayImage = new Image <Gray, byte>(parameters[0]);
}
catch {
ar.setError("Invalid path to image.");
return(ar);
}
}
if (PluginOptions.UseImageCorrection)
{
grayImage._EqualizeHist();
}
#endregion
Rectangle[] faces;
using (var classifier = new CascadeClassifier(PluginOptions.CascadesPath + "haarcascade_frontalface_default.xml")) {
faces = classifier.DetectMultiScale(grayImage, 1.1, 10);
}
if (faces.Length == 0)
{
ar.setError("No trained faces found.");
return(ar);
}
var resultString = "";
foreach (Rectangle face in faces)
{
using (FaceRecognizer recognizer = new EigenFaceRecognizer()) {
recognizer.Read(PluginOptions.PluginPath + "SavedCascade.xml");
FaceRecognizer.PredictionResult recoResult = recognizer.Predict(grayImage.Copy(face).Resize(100, 100, Inter.Cubic));
resultString += $"<{PluginOptions.PeopleFaces.ElementAt(recoResult.Label)}:{recoResult.Distance}>";
}
}
grayImage.Dispose();
ar.setSuccess(resultString);
return(ar);
}
public static void InitCam(int cameraIndex = 0)
{
Camera._cameraCapture = new VideoCapture(cameraIndex);
}
private static void Main()
{
try
{
// 定义图像捕捉方式 从摄像头 ， 注意 Windows下需要选择 VideoCaptureAPIs.DSHOW
var cap = new VideoCapture(0, VideoCaptureAPIs.DSHOW);
// 定义图像捕捉方式 从摄像头 视频文件
//var cap = new VideoCapture("video.webm");
//判断捕捉设备是否打开
if (!cap.IsOpened())
{
Console.WriteLine("Unable to connect to camera");
return;
}
Mat temp = null;
//定义显示窗口
using (var win = new ImageWindow())
{
//读取人脸检测和标注模型
using (var detector = Dlib.GetFrontalFaceDetector())
using (var poseModel = ShapePredictor.Deserialize("shape_predictor_68_face_landmarks.dat"))
{
// 主窗口是否关闭
while (!win.IsClosed())
{
//System.Threading.Thread.Sleep(100);
//获得1帧图片
temp = cap.RetrieveMat();// new Mat();
if (temp == null)
{
break;
}
//将 OPENCV 图像数据 转换为 DILB 图像格式
var array = new byte[temp.Width * temp.Height * temp.ElemSize()];
Marshal.Copy(temp.Data, array, 0, array.Length);
using (var cimg = Dlib.LoadImageData <BgrPixel>(array, (uint)temp.Height, (uint)temp.Width, (uint)(temp.Width * temp.ElemSize())))
{
// 人脸检测
var faces = detector.Operator(cimg);
//标注人脸
var shapes = new List <FullObjectDetection>();
for (var i = 0; i < faces.Length; ++i)
{
var det = poseModel.Detect(cimg, faces[i]);
shapes.Add(det);
}
//显示
win.ClearOverlay();
win.SetImage(cimg);
var lines = Dlib.RenderFaceDetections(shapes);
win.AddOverlay(lines);
foreach (var line in lines)
{
line.Dispose();
}
}
}
}
}
}
//catch (serialization_error&e)
//{
// cout << "需要下载识别模型 http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2" << endl;
// cout << endl << e.what() << endl;
//}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}