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);
}
}
}
private void EnumSources()
{
int sourceId = 0;
this.Properties.CameraSourceIds.Add(-1);
while (true)
{
try
{
using (Mat image = new Mat())
using (OpenCvSharp.VideoCapture videoCapture = new OpenCvSharp.VideoCapture(OpenCvSharp.CaptureDevice.Any, sourceId))
{
if (videoCapture.IsOpened() && videoCapture.Read(image))
{
this.Properties.CameraSourceIds.Add(sourceId++);
}
else
{
break;
}
}
}
catch
{
break;
}
}
}
/// <summary>
/// カメラから画像を取得します
/// </summary>
/// <param name="cameraIndex"></param>
/// <returns></returns>
public static Mat GetCameraImage(int cameraIndex = 0)
{
var frame = new Mat();
using (var capture = new VideoCapture(0))
capture.Read(frame);
return frame;
}
public OpencvSource(string cam_or_url)
{
MAssert.Check(cam_or_url != string.Empty);
// check if cam_or_url is number
bool stream = false;
for (int i = 0; i < cam_or_url.Length; ++i)
{
stream = stream ||
(cam_or_url[i] < '0') ||
(cam_or_url[i] > '9');
}
if (stream)
{
// open stream
Console.WriteLine("opening stream '{0}'", cam_or_url);
capturer = new OpenCvSharp.VideoCapture(cam_or_url);
}
else
{
// convert to integer
int cam_id = Convert.ToInt32(cam_or_url, 10);
MAssert.Check(cam_id >= 0, "wrong webcam id");
// open vebcam
Console.WriteLine("opening webcam {0}", cam_id);
capturer = new OpenCvSharp.VideoCapture(cam_id);
MAssert.Check(capturer.IsOpened(), "webcam not opened");
// set resolution
capturer.Set(OpenCvSharp.CaptureProperty.FrameWidth, 1280);
capturer.Set(OpenCvSharp.CaptureProperty.FrameHeight, 720);
MAssert.Check(capturer.IsOpened(), "webcam not opened");
}
// sometimes first few frames can be empty even if camera is good
// so skip few frames
OpenCvSharp.Mat frame;
for (int i = 0; i < 10; ++i)
{
frame = capturer.RetrieveMat();
}
// check first two frames
OpenCvSharp.Mat image1 = new OpenCvSharp.Mat(), image2 = new OpenCvSharp.Mat();
capturer.Read(image1);
capturer.Read(image2);
Console.WriteLine("image1 size: {0}", image1.Size());
Console.WriteLine("image1 size: {0}", image2.Size());
MAssert.Check(
!image1.Empty() &&
!image2.Empty() &&
image1.Size() == image2.Size() &&
image1.Type() == OpenCvSharp.MatType.CV_8UC3 &&
image2.Type() == OpenCvSharp.MatType.CV_8UC3,
"error opening webcam or stream");
}
private void timer1_Tick(object sender, EventArgs e)
{
if (cap == null || pause)
{
return;
}
if (forwTo)
{
var ofps = cap.Get(5);//5 fps
forwTo = false;
var frm = cap.Get(7);//7 frame count
var secs = (frm / ofps) * 1000;
cap.Set(0, forwPosPercetange * secs);//posmsec 0
}
if (oneFrameStep && oneFrameStepDir == -1)
{
var pf = cap.Get(1);//1 posframes
cap.Set(1, Math.Max(0, pf - 2));
}
if (oneFrameStep)
{
pause = true; oneFrameStep = false;
}
Mat mat = new Mat();
cap.Read(mat);
pictureBox1.Image = BitmapConverter.ToBitmap(mat);
}
// 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;
}
static void Main(string[] args)
{
//size of tag is in meters and camera parameters are obtained from calibration
float tag_size = 0.1F;
float fx = 1200F;
float fy = 1400F;
double px = 817.143;
double py = 387.159;
//array of floats to carry values of image points (x and y * 4 points)
float[] ptsry = new float[8];
//initialize video capture from camera
var capt = new OpenCvSharp.VideoCapture();
capt.Open(0);
//window for displaying video
Window window = new Window("capture");
//main task; display video and find tags
using (Mat frame = new Mat())
{
//looping untill key is pressed
while (true)
{
//read from camera and show it
capt.Read(frame);
window.ShowImage(frame);
//detect tags and find how many and print the number
Apriltag ap = new Apriltag("canny", true, "tag16h5");
var current_tags = ap.detect(frame);
Console.WriteLine("Number of tags = " + current_tags.Count);
Console.WriteLine();
//sleep for 10 msec
System.Threading.Thread.Sleep(10);
//if a key is pressed, close the window and exit
if (Cv2.WaitKey(1) >= 0)
{
capt.Release();
Cv2.DestroyAllWindows();
break;
}
}
}
}
protected override Mat ExecuteImpl(Mat inputImage)
{
lock (m_sync)
{
if (m_videoCapture != null)
{
if (m_videoCapture.Read(m_image) && m_image.Width != 0 && m_image.Height != 0)
{
return(m_image.Clone());
}
}
}
return(null);
}
/// <inheritdoc/>
public async Task StartAsync(int delay = 30)
{
OpenCvSharp.VideoCapture capture;
switch (this.settings.VideoType)
{
case VideoType.Webcam:
capture = new OpenCvSharp.VideoCapture(this.settings.WebcamIndex);
break;
case VideoType.Url:
capture = new OpenCvSharp.VideoCapture(this.settings.Url);
break;
default:
throw new ArgumentException("Invalid settings: video type for grabber not specified or wrong.");
}
using (Mat image = new Mat())
{
while (true)
{
capture.Read(image);
if (image.Empty())
{
break;
}
int analysisWidth = 320;
int analysisHeight = analysisWidth * image.Height / image.Width;
var analysisImage = image.Clone().Resize(new Size(analysisWidth, analysisHeight));
using (var analysisStream = analysisImage.ToMemoryStream(".jpg", new ImageEncodingParam(ImwriteFlags.JpegQuality, 50)))
using (var displayStream = image.ToMemoryStream(".jpg", new ImageEncodingParam(ImwriteFlags.JpegQuality, 100)))
{
this.OnFrameGrabbed?.Invoke(
displayStream,
analysisStream,
"image/jpeg",
analysisImage.Width,
analysisImage.Height);
}
await Task.Delay(delay);
}
}
}
public IActionResult Canny()
{
using (var capture = new OpenCvSharp.VideoCapture(CaptureDevice.Any, index: 0))
{
var fps = GetFps(capture);
capture.Fps = fps;
var interval = (int)(1000 / fps);
using (Mat image = new Mat()) // Frame image buffer
{
// When the movie playback reaches end, Mat.data becomes NULL.
while (true)
{
var frame = capture.Read(image);
if (image.Empty())
{
break;
}
// Load the cascade
var haarCascade = new CascadeClassifier("haarcascade_frontalface_alt2.xml");
// Load target image
var gray = new Mat("faces.png", ImreadModes.GrayScale);
// Detect faces
Rect[] faces = haarCascade.DetectMultiScale(gray, 1.08, 2, HaarDetectionType.ScaleImage, new Size(30, 30));
//byte[] cannyBytes = cannyImage.ToBytes(".png");
//string base64 = Convert.ToBase64String(cannyBytes);
//// ビュー変数に設定
//ViewBag.Base64Image = base64;
//window.ShowImage(image);
//Cv2.WaitKey(sleepTime);
}
}
}
return(View());
}
private void LoadVideoFrames()
{
if (openCvCapture == null)
{
openCvCapture = new OpenCvSharp.VideoCapture(0);
}
OpenCvSharp.Mat frame = new OpenCvSharp.Mat();
bool readingVideo = true;
int cnt = 0;
while (readingVideo)
{
if (openCvCapture.Read(frame))
{
cnt++;
frame.SaveImage(@"d:\junk\testCamImages\image{cnt}.png");
byte[] imagearray = frame.ImEncode(".png");
BitmapImage bmi = new BitmapImage();
using (MemoryStream ms = new MemoryStream(imagearray))
{
ms.Position = 0;
bmi.BeginInit();
bmi.CacheOption = BitmapCacheOption.OnLoad;
bmi.StreamSource = ms;
bmi.EndInit();
}
//this.ImageSource.Dispatcher.BeginInvoke(System.Windows.Threading.DispatcherPriority.Normal,
// new Action(() =>
// {
// ImageSource = bmi;
// }));
//capture.
OpenCvSharp.Cv2.ImShow("video", frame);
int key = OpenCvSharp.Cv2.WaitKey(27);
if (key == 27)
{
readingVideo = false;
}
}
}
}
// 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);
}
public void Run()
{
// Opens MP4 file (ffmpeg is probably needed)
var capture = new VideoCapture(FilePath.Movie.Bach);
int sleepTime = (int)Math.Round(1000 / capture.Fps);
using (var 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);
}
}
}
private void button1_Click(object sender, EventArgs e)
{
if (th != null)
{
button1.Text = "start";
stop = true;
th = null;
return;
}
button1.Text = "stop";
th = new Thread(() =>
{
cap = new OpenCvSharp.VideoCapture(path);
Stopwatch sw = Stopwatch.StartNew();
var session1 = new InferenceSession(netPath);
var inputMeta = session1.InputMetadata;
Mat mat = new Mat();
var nFrames = cap.Get(VideoCaptureProperties.FrameCount);
cap.Read(mat);
var sz = mat.Size();
if (inputDims[2] == -1)
{
sz.Height = mat.Height;
sz.Width = mat.Width;
}
string key = $"{sz.Width}x{sz.Height}";
if (!Processing.allPriorBoxes.ContainsKey(key))
{
var pd = Decoders.PriorBoxes2(sz.Width, sz.Height);;
Processing.allPriorBoxes.Add(key, pd);
}
var prior_data = Processing.allPriorBoxes[key];
var ofps = cap.Get(VideoCaptureProperties.Fps);
VideoWriter vid = null;
if (checkBox1.Checked)
{
vid = new VideoWriter("output.mp4", FourCC.XVID, ofps, mat.Size());
}
while (true)
{
if (stop)
{
break;
}
var pf = cap.Get(VideoCaptureProperties.PosFrames);
int perc = (int)Math.Round((pf / (float)nFrames) * 100);
progressBar1.Invoke(((Action)(() =>
{
label1.Text = $"{pf} / {nFrames} {perc}%";
progressBar1.Value = perc;
})));
if (!cap.Read(mat))
{
break;
}
Mat orig = mat.Clone();
if (inputDims[2] == -1)
{
inputDims[2] = mat.Height;
inputDims[3] = mat.Width;
}
mat.ConvertTo(mat, MatType.CV_32F);
object param = mat;
foreach (var pitem in preps)
{
param = pitem.Process(param);
}
var inputData = param as float[];
var tensor = new DenseTensor <float>(param as float[], inputDims);
var container = new List <NamedOnnxValue>();
container.Add(NamedOnnxValue.CreateFromTensor <float>(inputName, tensor));
float[] confd;
float[] locd;
using (var results = session1.Run(container))
{
var data = results.First().AsTensor <float>();
locd = data.ToArray();
confd = results.Skip(1).First().AsTensor <float>().ToArray();
}
Stopwatch sw2 = Stopwatch.StartNew();
var ret = Processing.boxesDecode(orig.Size(), confd, locd, new System.Drawing.Size(sz.Width, sz.Height), prior_data, visTresh);
if (checkBox1.Checked)
{
var out1 = Processing.drawBoxes(orig, ret.Item1, ret.Item2, visTresh, ret.Item3);
vid.Write(out1);
}
sw2.Stop();
}
vid.Release();
sw.Stop();
});
th.IsBackground = true;
th.Start();
}
static void Main(string[] args)
{
var faceengine = new FaceEngine(ASF_RegisterOrNot.ASF_REGISTER, 2);
//faceengine.OnlineActivation("", "", "");
FaceEngine.OnlineActivationFree("", "");
//faceengine.OfflineActivation();
faceengine.InitEngine(ASF_DetectMode.ASF_DETECT_MODE_IMAGE, ArcSoftFace_OrientPriority.ASF_OP_0_ONLY, 1, ASF_Mask.ASF_FACE_DETECT | ASF_Mask.ASF_FACERECOGNITION | ASF_Mask.ASF_AGE | ASF_Mask.ASF_LIVENESS);
Console.WriteLine(faceengine.Version.BuildDate);
Console.WriteLine(faceengine.Version.CopyRight);
Console.WriteLine(faceengine.Version.Version);
OpenCvSharp.VideoCapture videoCapture = new OpenCvSharp.VideoCapture();
videoCapture.Open(0);
var activeFile = FaceEngine.GetActiveFileInfo();
////Console.WriteLine(FaceEngine.GetActiveDeviceInfo());
Stopwatch stopwatch = new Stopwatch();
stopwatch.Restart();
//faceengine.InitEngine(ASF_DetectMode.ASF_DETECT_MODE_IMAGE, ArcSoftFace_OrientPriority.ASF_OP_ALL_OUT, 9,
// ASF_Mask.ASF_AGE | ASF_Mask.ASF_FACE3DANGLE | ASF_Mask.ASF_FACELANDMARK | ASF_Mask.ASF_FACERECOGNITION | ASF_Mask.ASF_FACESHELTER | ASF_Mask.ASF_FACE_DETECT |
// ASF_Mask.ASF_GENDER | ASF_Mask.ASF_IMAGEQUALITY | ASF_Mask.ASF_IR_LIVENESS | ASF_Mask.ASF_LIVENESS | ASF_Mask.ASF_MASKDETECT | ASF_Mask.ASF_UPDATE_FACEDATA);
//Console.WriteLine($"引擎初始化: {stopwatch.ElapsedMilliseconds}ms");
Mat mat = new Mat();
//Mat mat = new Mat(@"C:\Users\Jch\Desktop\2.jpg");
while (true)
{
stopwatch.Restart();
if (videoCapture.Read(mat))
{
using (var img = mat.ToBitmap())
using (var imgInfo = ImageInfo.ReadBMP(img))
{
Console.WriteLine($"图片处理:{stopwatch.ElapsedMilliseconds}ms");
stopwatch.Restart();
var detectResult = faceengine.DetectFacesEx(imgInfo);
Console.WriteLine($"人脸定位:{stopwatch.ElapsedMilliseconds}ms");
if (detectResult != null)
{
foreach (var item in detectResult.FaceInfos)
{
Console.WriteLine($"Age: {item.Age}");
Console.WriteLine($"FaceID: {item.FaceID}");
Console.WriteLine($"FaceOrient: {item.FaceOrient}");
Console.WriteLine($"FaceShelter: {item.FaceShelter}");
Console.WriteLine($"Gender: {item.Gender}");
Console.WriteLine($"LeftEyeClosed: {item.LeftEyeClosed}");
Console.WriteLine($"Liveness: {item.Liveness}");
Console.WriteLine($"Mask: {item.Mask}");
Console.WriteLine($"RightEyeClosed: {item.RightEyeClosed}");
Console.WriteLine($"WearGlasses: {item.WearGlasses}");
Console.WriteLine($"FaceRect: bottom->{item.FaceRect.bottom} left->{item.FaceRect.left} right->{item.FaceRect.right} top->{item.FaceRect.top}");
Console.WriteLine($"FaceLandmark: x->{item.FaceLandmark.x} y->{item.FaceLandmark.x}");
Console.WriteLine($"Face3DAngle: {item.Face3DAngle.roll} {item.Face3DAngle.yaw} {item.Face3DAngle.pitch} {item.Face3DAngle.status}");
stopwatch.Restart();
var feature = faceengine.FaceFeatureExtractEx(imgInfo, item);
Console.WriteLine($"提取特征值: {stopwatch.ElapsedMilliseconds}ms");
if (feature != null)
{
Console.WriteLine($"feature: {feature.Size}");
}
Console.WriteLine(faceengine.FaceFeatureCompare(feature.ASFFaceFeature, feature.ASFFaceFeature));
var score = faceengine.ImageQualityDetectEx(imgInfo, item);
Console.WriteLine($"人脸质量: {score}");
Console.WriteLine("--------------------------------------------");
}
}
}
}
}
Console.ReadLine();
}
private void Init()
{
new Thread(() =>
{
var eye_casc = new cv.CascadeClassifier("eye.xml");
var left_eye_casc = new cv.CascadeClassifier("left_eye.xml");
var right_eye_casc = new cv.CascadeClassifier("right_eye.xml");
var face_casc = new cv.CascadeClassifier("fface_default.xml");
cap = new cv.VideoCapture(0);
while (true)
{
if (released)
{
break;
}
var img = new cv.Mat();
cap.Read(img);
var gray = img.CvtColor(cv.ColorConversionCodes.BGR2GRAY);
var gaus = gray.AdaptiveThreshold(255, cv.AdaptiveThresholdTypes.GaussianC, cv.ThresholdTypes.Binary, 115, 1);
img = gaus;
var faces = face_casc.DetectMultiScale(gray, 1.3, 5);
RenderTargetBitmap eyes_lay = null;
foreach (var face in faces)
{
var rect = new cv.Rect(face.Location, face.Size);
//img.Rectangle(rect, new cv.Scalar(255, 0, 0));
var sub_ing = gray[rect];
var sub_ing_rgb = img[rect];
//left eye
var eyes = eye_casc.DetectMultiScale(sub_ing, 1.3, 2);
int count = 0;
foreach (var eye in eyes)
{
count++;
if (count > 2)
{
count = 0;
break;
}
var rect_eye = new cv.Rect(eye.Location, eye.Size);
if (eye.X + eye.Width < face.Width / 2)
{
//sub_ing_rgb.Rectangle(rect_eye, new cv.Scalar(0, 255, 0));
Dispatcher.Invoke(() =>
{
eyes_lay = DrawImg(cv.Extensions.BitmapSourceConverter.ToBitmapSource(img), eye.X + face.X, eye.Y + face.Y, eye.Width, eye.Height, eye_l, scale_w, scale_h);
});
}
}
//left eye
count = 0;
foreach (var eye in eyes)
{
count++;
if (count > 2)
{
break;
}
var rect_eye = new cv.Rect(eye.Location, eye.Size);
if (eye.X + eye.Width > face.Width / 2)
{
Dispatcher.Invoke(() =>
{
if (eyes_lay != null)
{
eyes_lay = DrawImg(eyes_lay, eye.X + face.X, eye.Y + face.Y, eye.Width, eye.Height, eye_r, scale_w, scale_h);
}
else
{
eyes_lay = DrawImg(cv.Extensions.BitmapSourceConverter.ToBitmapSource(img), eye.X + face.X, eye.Y + face.Y, eye.Width, eye.Height, eye_r, scale_w, scale_h);
}
});
}
}
}
Dispatcher.Invoke(() =>
{
if (eyes_lay != null)
{
OutImg.Source = eyes_lay;
}
else
{
OutImg.Source = cv.Extensions.BitmapSourceConverter.ToBitmapSource(img);
}
});
//Thread.Sleep(100);
GC.Collect();
}
})
{
IsBackground = true
}.Start();
}
/// <summary>
/// 処理実行
/// </summary>
public ImageProcessValue Execute(SettingsObj obj)
{
try
{
// webカメラキャプチャ
var camera = new OpenCvSharp.VideoCapture(0)
{
//// 解像度の指定
FrameWidth = 1920,
FrameHeight = 1080
};
using (camera)
{
// カメラ内部パラメータ格納用
Mat mtx = new Mat();
Mat dist = new Mat();
// ymlファイルを読み来み計算パラメータを取得
using (var fs = new FileStorage(obj.CalibratinFilePath, FileStorage.Mode.Read))
{
mtx = fs["mtx"].ReadMat();
dist = fs["dist"].ReadMat();
}
var src = new Mat();
// 撮影画像の読み取り
camera.Read(src);
if (src.Empty())
{
return(null);
}
Mat calib = new Mat();
// 歪み補正
Cv2.Undistort(src, calib, mtx, dist);
// 画像処理
var tmp = new Mat();
// OpenCVのカラーの並びに変換
Cv2.CvtColor(calib, tmp, OpenCvSharp.ColorConversionCodes.RGB2BGR);
// BGR画像をHSV画像に変換
var hsv = new Mat();
Cv2.CvtColor(tmp, hsv, OpenCvSharp.ColorConversionCodes.BGR2HSV);
// inRange関数で範囲指定２値化 -> マスク画像として使う
var msk = new Mat();
Cv2.InRange(hsv, new Scalar(obj.HueMin, obj.SaturationMin, obj.ValueMin), new Scalar(obj.HueMax, obj.SaturationMax, obj.ValueMax), msk);
// bitwise_andで元画像にマスクをかける -> マスクされた部分の色だけ残る
var msk_src = new Mat();
Cv2.BitwiseAnd(hsv, hsv, msk_src, msk);
var show_msk = new Mat();
// 元の色に戻す
Cv2.CvtColor(msk_src, show_msk, ColorConversionCodes.HSV2BGR);
// グレースケール変換
var gray = new Mat();
Cv2.CvtColor(show_msk, gray, ColorConversionCodes.BGR2GRAY);
// 2値化
var th = new Mat();
Cv2.Threshold(gray, th, 130, 255, ThresholdTypes.Otsu);
// ブロブとラベリング
var label = new Mat();
var stats = new Mat();
var centroids = new Mat();
ConnectedComponents cc = Cv2.ConnectedComponentsEx(th);
if (cc.LabelCount <= 1)
{
return(null);
}
// draw labels
//cc.RenderBlobs(show_msk);
// draw bonding boxes except background
foreach (var blob in cc.Blobs.Skip(1))
{
show_msk.Rectangle(blob.Rect, Scalar.Red);
}
// filter maximum blob
var maxBlob = cc.GetLargestBlob();
var filtered = new Mat();
cc.FilterByBlob(show_msk, filtered, maxBlob);
// 矩形探索
// マスク画像から矩形探索
Point[][] contours;
HierarchyIndex[] hierarchy;
Cv2.FindContours(th, out contours, out hierarchy, RetrievalModes.List, ContourApproximationModes.ApproxNone);
// 見つからなかったら何もしない
if (contours.Length == 0)
{
return(null);
}
// 回転を考慮した外接矩形
foreach (var cont in contours)
{
var rect = Cv2.MinAreaRect(cont);
var box = Cv2.BoxPoints(rect).Select(x => (Point)x);
}
Cv2.DrawContours(show_msk, contours, -1, Scalar.Yellow, 3);
//Cv2.ImShow("show_msk", show_msk);
// 画像、画像上の位置発火
var val = new ImageProcessValue();
val.CameraImage = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(show_msk);
val.Blob = maxBlob;
// メモリリーク対策でDispose呼ぶ
mtx.Dispose();
dist.Dispose();
calib.Dispose();
tmp.Dispose();
hsv.Dispose();
msk.Dispose();
msk_src.Dispose();
show_msk.Dispose();
gray.Dispose();
th.Dispose();
label.Dispose();
stats.Dispose();
centroids.Dispose();
filtered.Dispose();
return(val);
}
}
catch (Exception e)
{
throw e;
}
}
//var layerName = nets.GetLayerNames()[0];
//prob.MinMaxLoc(out min, out max, out minLoc, out maxLoc);
// Update is called once per frame
void Update()
{
frame_count++;
using (var frames = pipe.WaitForFrames())
using (var depth = frames.DepthFrame)
{
print("The camera is pointing at an object " +
depth.GetDistance(depth.Width / 2, depth.Height / 2) + " meters away\t");
rotate_character3(depth.GetDistance(depth.Width / 2, depth.Height / 2));
}
camera.Read(image);
Cv2.ImShow("image", image);
//var frames = pipe.WaitForFrames();
//Cv2.CvtColor(image, image, ColorConversionCodes.BGR2RGB);
//print("The camera is pointing at an object " +
// depth.GetDistance(depth.Width / 2, depth.Height / 2) + " meters away\t");
//image=Cv2.ImRead("C:/Users/CheNik/Desktop/KakaoTalk_20191128_172510392.jpg");
var image4 = image.Clone();
var image5 = image.Clone();
int frameWidth = image.Width;
int frameHeight = image.Height;
importantImage = OpenCvSharp.Dnn.CvDnn.BlobFromImage(image, 1, new Size(300, 300), new Scalar(104, 117, 123), false, false);
var nets = OpenCvSharp.Dnn.CvDnn.ReadNetFromCaffe("C:/Users/CheNik/Face/Assets/deploy.prototxt", "C:/Users/CheNik/Face/Assets/res10_300x300_ssd_iter_140000.caffemodel");
//var nets = OpenCvSharp.Dnn.CvDnn.ReadNetFromTensorflow("C:/Users/CheNik/Face/Assets/opencv_face_detector_uint8.pb","C:/Users/CheNik/Face/Assets/opencv_face_detector.pbtxt");
nets.SetInput(importantImage, "data");
var prob2 = nets.Forward();
var p = prob2.Reshape(1, prob2.Size(2));
for (int i = 0; i < prob2.Size(2); i++)
{
var confidence = p.At <float>(i, 2);
if (confidence > 0.7)
{
//get value what we need
var idx = (int)p.At <float>(i, 1);
var x1 = (int)(image.Width * p.At <float>(i, 3));
var y1 = (int)(image.Height * p.At <float>(i, 4));
var x2 = (int)(image.Width * p.At <float>(i, 5));
var y2 = (int)(image.Height * p.At <float>(i, 6));
var width = x2 - x1 + 1;
var height = y2 - y1 + 1;
//draw result
OpenCvSharp.Rect facerect = new OpenCvSharp.Rect(x1, y1, width + 1, height + 1);
OpenCvSharp.Point center_point = new OpenCvSharp.Point((int)(x1 + (width / 2)) + 1, (int)(y1 + (height / 2) + 1));
int specified_position = get_position(center_point);
//print("specified_position = " + frame_count +" count = "+ specified_position);
//float depth_center_point = depth.GetDistance(center_point.X, center_point.Y);
rotate_Character(specified_position, center_point);
Mat face = image4.Clone().SubMat(facerect);
var tensorimage = CreateTensorFromImageFileAlt(face);
var tensored_image = int_to_float_and_div(tensorimage);
var runner1 = session1.GetRunner();
var runner2 = session2.GetRunner();
var runner3 = session3.GetRunner();
var input1 = graph1["input_1"][0];
var input2 = graph2["input_1"][0];
var input3 = graph3["input_1"][0];
var pred1 = graph1["pred_pose/mul_24"][0];
var pred2 = graph2["pred_pose/mul_24"][0];
var pred3 = graph3["pred_pose/mul_24"][0];
runner1.AddInput(input1, tensored_image);
runner2.AddInput(input2, tensored_image);
runner3.AddInput(input3, tensored_image);
runner1.Fetch(pred1);
runner2.Fetch(pred2);
runner3.Fetch(pred3);
var output1 = runner1.Run();
var output2 = runner2.Run();
var output3 = runner3.Run();
TFTensor probresult1 = output1[0];
TFTensor probresult2 = output2[0];
TFTensor probresult3 = output3[0];
float[,] result1 = return_value(probresult1);
float[,] result2 = return_value(probresult2);
float[,] result3 = return_value(probresult3);
float[] result = new float[3];
result[0] = result1[0, 0] + result2[0, 0] + result3[0, 0];
result[1] = result1[0, 1] + result2[0, 1] + result3[0, 1];
result[2] = result1[0, 2] + result2[0, 2] + result3[0, 2];
//print("model1 result" + result1[0, 0] +" " +result1[0, 1] +" " +result1[0, 2]);
//print("model2 result" + result2[0, 0] + " " + result2[0, 1] + " " + result2[0, 2]);
//print("model3 result" + result3[0, 0] + " " + result3[0, 1] + " " + result3[0, 2]);
//print(result[0]/3);
//print(result[1]/3);
//print(result[2]/3);
float yaw = result[0] / 3;
float pitch = result[1] / 3;
float roll = result[2] / 3;
image4 = draw_axis(image4, yaw, pitch, roll);
/*if (yaw < -30)
* v3.y =v3.y+ 30;
* if (yaw > 30)
* v3.y = v3.y - 30;
* if(pitch)*/
float yaw2 = yaw;
float pitch2 = pitch - 5;
float roll2 = roll + 2.4f;
//yaw2 = rotate_Charactor(yaw2);
//pitch2 = rotate_Charactor(pitch2);
//roll2 = rotate_Charactor(roll2);
print("yaw = " + yaw2 + " " + "pitch = " + pitch2 + " " + "roll = " + roll2);
rotate_Character2(yaw2, pitch2, roll2, specified_position);
anaglyph_apply(yaw2, pitch2, roll2, center_point);
//pixxy.transform.rotation = Quaternion.Euler(-pitch2, yaw2, roll2);
Cv2.Rectangle(image4, new Point(x1, y1), new Point(x2, y2), new Scalar(255, 0, 0), 3, shift: 8);
}
}
Cv2.ImShow("image4", image4);
}
public void Start(int cameraNumber, int interval = 1000)
{
if (captureWorker.IsBusy)
return;
CameraNumber = cameraNumber;
captureWorker.DoWork += (sender, e) =>
{
var bw = (BackgroundWorker)sender;
using (var capture = new VideoCapture(CameraNumber))
{
capture.FrameHeight = 640;
var image = new Mat();
while (true)
{
if (bw.CancellationPending)
{
e.Cancel = true;
return;
}
capture.Read(image);
if (image == null)
throw new Exception("カメラから画像が読み取れませんでした。");
bw.ReportProgress(0, image);
Thread.Sleep(interval);
}
}
};
captureWorker.RunWorkerAsync();
}
public void Start(string fileName, int interval)
{
if (captureWorker.IsBusy)
throw new InvalidOperationException("すでに Capture スレッドが実行中です。"); //{ Data = { { "GetValue.Arguments.fileName", fileName } } };
FileName = fileName;
captureWorker.DoWork += (sender, e) =>
{
var bw = (BackgroundWorker)sender;
using (var capture = new VideoCapture(FileName))
{
var image = new Mat();
while (true)
{
if (bw.CancellationPending)
{
e.Cancel = true;
return;
}
capture.Read(image);
if (image == null) // 動画終了
return;
bw.ReportProgress(0, image);
Thread.Sleep(interval);
}
e.Cancel = true;
}
};
captureWorker.RunWorkerAsync();
}
public void Start(string fileName)
{
if (captureWorker.IsBusy)
throw new InvalidOperationException("すでに Capture スレッドが実行中です。");
if (string.IsNullOrWhiteSpace(fileName))
throw new ArgumentNullException("fileName");
FileName = fileName;
captureWorker.DoWork += (sender, e) =>
{
var bw = (BackgroundWorker)sender;
using (var capture = new VideoCapture(FileName))
{
int interval = (int)(1000 / capture.Fps);
var image = new Mat();
while (true)
{
if (bw.CancellationPending)
{
e.Cancel = true;
return;
}
capture.Read(image);
if (image == null) // 動画終了
return;
bw.ReportProgress(0, image);
Thread.Sleep(interval);
}
e.Cancel = true;
}
};
captureWorker.RunWorkerAsync();
}
public void Run()
{
using (var capture = new VideoCapture(FilePath.Movie.Bach))
using (var mog = BackgroundSubtractorMOG.Create())
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 Run()
{
const string OutVideoFile = "out.avi";
// Opens MP4 file (ffmpeg is probably needed)
VideoCapture capture = new VideoCapture(FilePath.Movie.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, ColorConversionCodes.BGR2GRAY);
Cv2.Canny(gray, canny, 100, 180);
Cv2.Resize(canny, dst, dsize, 0, 0, InterpolationFlags.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);
}
}
}
