/// <summary>
/// Niblackの手法による二値化処理を行う。
/// </summary>
/// <param name="imgSrc">入力画像</param>
/// <param name="imgDst">出力画像</param>
/// <param name="kernelSize">局所領域のサイズ</param>
/// <param name="k">係数</param>
#else
/// <summary>
/// Binarizes by Niblack's method
/// </summary>
/// <param name="src">Input image</param>
/// <param name="dst">Output image</param>
/// <param name="kernelSize">Window size</param>
/// <param name="k">Adequate coefficient</param>
#endif
public static void Niblack(Mat src, Mat dst, int kernelSize, double k)
{
if (src == null)
throw new ArgumentNullException("src");
if (dst == null)
throw new ArgumentNullException("dst");
// グレースケールのみ
if (src.Type() != MatType.CV_8UC1)
throw new ArgumentException("src must be gray scale image");
if (dst.Type() != MatType.CV_8UC1)
throw new ArgumentException("dst must be gray scale image");
// サイズのチェック
if (kernelSize < 3)
throw new ArgumentOutOfRangeException("kernelSize", "size must be 3 and above");
if (kernelSize % 2 == 0)
throw new ArgumentOutOfRangeException("kernelSize", "size must be odd number");
int width = src.Width;
int height = src.Height;
dst.Create(src.Size(), src.Type());
using (var tSrcMat = new MatOfByte(src))
using (var tDstMat = new MatOfByte(dst))
{
var tSrc = tSrcMat.GetIndexer();
var tDst = tDstMat.GetIndexer();
//for (int y = 0; y < gray.Height; y++)
MyParallel.For(0, height, delegate(int y)
{
for (int x = 0; x < width; x++)
{
double m, s;
MeanStddev(src, x, y, kernelSize, out m, out s);
double threshold = m + k * s;
if (tSrc[y, x] < threshold)
tDst[y, x] = 0;
else
tDst[y, x] = 255;
}
}
);
}
}
/// <summary>
/// Raises the web cam texture to mat helper inited event.
/// </summary>
public void OnWebCamTextureToMatHelperInited()
{
Debug.Log ("OnWebCamTextureToMatHelperInited");
Mat webCamTextureMat = webCamTextureToMatHelper.GetMat ();
colors = new Color32[webCamTextureMat.cols () * webCamTextureMat.rows ()];
texture = new Texture2D (webCamTextureMat.cols (), webCamTextureMat.rows (), TextureFormat.RGBA32, false);
matOpFlowThis = new Mat ();
matOpFlowPrev = new Mat ();
MOPcorners = new MatOfPoint ();
mMOP2fptsThis = new MatOfPoint2f ();
mMOP2fptsPrev = new MatOfPoint2f ();
mMOP2fptsSafe = new MatOfPoint2f ();
mMOBStatus = new MatOfByte ();
mMOFerr = new MatOfFloat ();
gameObject.transform.localScale = new Vector3 (webCamTextureMat.cols (), webCamTextureMat.rows (), 1);
Debug.Log ("Screen.width " + Screen.width + " Screen.height " + Screen.height + " Screen.orientation " + Screen.orientation);
float width = 0;
float height = 0;
width = gameObject.transform.localScale.x;
height = gameObject.transform.localScale.y;
float widthScale = (float)Screen.width / width;
float heightScale = (float)Screen.height / height;
if (widthScale < heightScale) {
Camera.main.orthographicSize = (width * (float)Screen.height / (float)Screen.width) / 2;
} else {
Camera.main.orthographicSize = height / 2;
}
gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
// webCamTextureToMatHelper.Play ();
}
/// <summary>
/// Niblackの手法による二値化処理を行う（高速だが、メモリを多く消費するバージョン）。
/// </summary>
/// <param name="imgSrc">入力画像</param>
/// <param name="imgDst">出力画像</param>
/// <param name="kernelSize">局所領域のサイズ</param>
/// <param name="k">係数</param>
#else
/// <summary>
/// Binarizes by Niblack's method (This is faster but memory-hogging)
/// </summary>
/// <param name="src">Input image</param>
/// <param name="dst">Output image</param>
/// <param name="kernelSize">Window size</param>
/// <param name="k">Adequate coefficient</param>
#endif
public static void NiblackFast(Mat src, Mat dst, int kernelSize, double k)
{
if (src == null)
throw new ArgumentNullException("src");
if (dst == null)
throw new ArgumentNullException("dst");
// グレースケールのみ
if (src.Type() != MatType.CV_8UC1)
throw new ArgumentException("src must be gray scale image");
if (dst.Type() != MatType.CV_8UC1)
throw new ArgumentException("dst must be gray scale image");
// サイズのチェック
if (kernelSize < 3)
throw new ArgumentOutOfRangeException("kernelSize", "size must be 3 and above");
if (kernelSize % 2 == 0)
throw new ArgumentOutOfRangeException("kernelSize", "size must be odd number");
int borderSize = kernelSize / 2;
int width = src.Width;
int height = src.Height;
dst.Create(src.Size(), src.Type());
using (var tempMat = new Mat(height + (borderSize * 2), width + (borderSize * 2), src.Type()))
using (var sumMat = new Mat(tempMat.Height + 1, tempMat.Width + 1, MatType.CV_64FC1, 1))
using (var sqSumMat = new Mat(tempMat.Height + 1, tempMat.Width + 1, MatType.CV_64FC1, 1))
{
Cv2.CopyMakeBorder(src, tempMat, borderSize, borderSize, borderSize, borderSize, BorderTypes.Replicate, Scalar.All(0));
Cv2.Integral(tempMat, sumMat, sqSumMat);
using (var tSrcMat = new MatOfByte(src))
using (var tDstMat = new MatOfByte(dst))
using (var tSumMat = new MatOfDouble(sumMat))
using (var tSqSumMat = new MatOfDouble(sqSumMat))
{
var tSrc = tSrcMat.GetIndexer();
var tDst = tDstMat.GetIndexer();
var tSum = tSumMat.GetIndexer();
var tSqSum = tSqSumMat.GetIndexer();
int ylim = height + borderSize;
int xlim = width + borderSize;
int kernelPixels = kernelSize * kernelSize;
for (int y = borderSize; y < ylim; y++)
{
for (int x = borderSize; x < xlim; x++)
{
int x1 = x - borderSize;
int y1 = y - borderSize;
int x2 = x + borderSize + 1;
int y2 = y + borderSize + 1;
double sum = tSum[y2, x2] - tSum[y2, x1] - tSum[y1, x2] + tSum[y1, x1];
double sqsum = tSqSum[y2, x2] - tSqSum[y2, x1] - tSqSum[y1, x2] + tSqSum[y1, x1];
double mean = sum / kernelPixels;
double var = (sqsum / kernelPixels) - (mean * mean);
if (var < 0.0) var = 0.0;
double stddev = Math.Sqrt(var);
double threshold = mean + k * stddev;
if (tSrc[y - borderSize, x - borderSize] < threshold)
tDst[y - borderSize, x - borderSize] = 0;
else
tDst[y - borderSize, x - borderSize] = 255;
}
}
}
}
}
/// <summary>
/// 注目画素の周辺画素の最大値と最小値を求める
/// </summary>
/// <param name="img">画像の画素データ</param>
/// <param name="x">x座標</param>
/// <param name="y">y座標</param>
/// <param name="size">周辺画素の探索サイズ。奇数でなければならない</param>
/// <param name="min">出力される最小値</param>
/// <param name="max">出力される最大値</param>
private static void MinMax(Mat img, int x, int y, int size, out byte min, out byte max)
{
int size2 = size / 2;
min = byte.MaxValue;
max = byte.MinValue;
int xs = Math.Max(x - size2, 0);
int xe = Math.Min(x + size2, img.Width);
int ys = Math.Max(y - size2, 0);
int ye = Math.Min(y + size2, img.Height);
using (var tImg = new MatOfByte(img))
{
var indexer = tImg.GetIndexer();
for (int xx = xs; xx < xe; xx++)
{
for (int yy = ys; yy < ye; yy++)
{
byte v = indexer[yy, xx];
if (max < v)
max = v;
else if (min > v)
min = v;
}
}
}
}
public static float[] GetArray(this Mat self, float[] buffer = null, bool bgr2rgb = true)
{
int width = self.Width;
int height = self.Height;
float[] f;
if (buffer == null)
{
f = new float[width * height * self.Channel];
}
else
{
if (buffer.Length < width * height * self.Channel)
{
throw new ArgumentOutOfRangeException(nameof(buffer));
}
f = buffer;
}
if (self.Channel == 3)
{
using (MatOfByte3 matByte = new MatOfByte3())
{
self.CopyTo(matByte);
var indexer = matByte.GetIndexer();
int i = 0;
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
Vec3b color = indexer[y, x];
if (bgr2rgb)
{
f[i] = color.Item2;
i++;
f[i] = color.Item1;
i++;
f[i] = color.Item0;
i++;
}
else
{
f[i] = color.Item0;
i++;
f[i] = color.Item1;
i++;
f[i] = color.Item2;
i++;
}
}
}
}
}
else if (self.Channel == 1)
{
using (var matByte = new MatOfByte())
{
self.CopyTo(matByte);
var w = self.Width;
var h = self.Height;
var indexer = matByte.GetIndexer();
int i = 0;
for (int y = 0; y < h; y++)
{
for (int x = 0; x < w; x++)
{
var pixel = indexer[y, x];
f[i] = pixel;
i++;
}
}
}
}
else
{
throw new Exception("not supported channel");
}
return(f);
}
/// <summary>
/// Niblackの手法による二値化処理を行う（高速だが、メモリを多く消費するバージョン）。
/// </summary>
/// <param name="imgSrc">入力画像</param>
/// <param name="imgDst">出力画像</param>
/// <param name="kernelSize">局所領域のサイズ</param>
/// <param name="k">係数</param>
#else
/// <summary>
/// Binarizes by Niblack's method (This is faster but memory-hogging)
/// </summary>
/// <param name="src">Input image</param>
/// <param name="dst">Output image</param>
/// <param name="kernelSize">Window size</param>
/// <param name="k">Adequate coefficient</param>
#endif
public static void NiblackFast(Mat src, Mat dst, int kernelSize, double k)
{
if (src == null)
{
throw new ArgumentNullException("src");
}
if (dst == null)
{
throw new ArgumentNullException("dst");
}
// グレースケールのみ
if (src.Type() != MatType.CV_8UC1)
{
throw new ArgumentException("src must be gray scale image");
}
if (dst.Type() != MatType.CV_8UC1)
{
throw new ArgumentException("dst must be gray scale image");
}
// サイズのチェック
if (kernelSize < 3)
{
throw new ArgumentOutOfRangeException("kernelSize", "size must be 3 and above");
}
if (kernelSize % 2 == 0)
{
throw new ArgumentOutOfRangeException("kernelSize", "size must be odd number");
}
int borderSize = kernelSize / 2;
int width = src.Width;
int height = src.Height;
dst.Create(src.Size(), src.Type());
using (var tempMat = new Mat(height + (borderSize * 2), width + (borderSize * 2), src.Type()))
using (var sumMat = new Mat(tempMat.Height + 1, tempMat.Width + 1, MatType.CV_64FC1, 1))
using (var sqSumMat = new Mat(tempMat.Height + 1, tempMat.Width + 1, MatType.CV_64FC1, 1))
{
Cv2.CopyMakeBorder(src, tempMat, borderSize, borderSize, borderSize, borderSize, BorderTypes.Replicate, Scalar.All(0));
Cv2.Integral(tempMat, sumMat, sqSumMat);
using (var tSrcMat = new MatOfByte(src))
using (var tDstMat = new MatOfByte(dst))
using (var tSumMat = new MatOfDouble(sumMat))
using (var tSqSumMat = new MatOfDouble(sqSumMat))
{
var tSrc = tSrcMat.GetIndexer();
var tDst = tDstMat.GetIndexer();
var tSum = tSumMat.GetIndexer();
var tSqSum = tSqSumMat.GetIndexer();
int ylim = height + borderSize;
int xlim = width + borderSize;
int kernelPixels = kernelSize * kernelSize;
for (int y = borderSize; y < ylim; y++)
{
for (int x = borderSize; x < xlim; x++)
{
int x1 = x - borderSize;
int y1 = y - borderSize;
int x2 = x + borderSize + 1;
int y2 = y + borderSize + 1;
double sum = tSum[y2, x2] - tSum[y2, x1] - tSum[y1, x2] + tSum[y1, x1];
double sqsum = tSqSum[y2, x2] - tSqSum[y2, x1] - tSqSum[y1, x2] + tSqSum[y1, x1];
double mean = sum / kernelPixels;
double var = (sqsum / kernelPixels) - (mean * mean);
if (var < 0.0)
{
var = 0.0;
}
double stddev = Math.Sqrt(var);
double threshold = mean + k * stddev;
if (tSrc[y - borderSize, x - borderSize] < threshold)
{
tDst[y - borderSize, x - borderSize] = 0;
}
else
{
tDst[y - borderSize, x - borderSize] = 255;
}
}
}
}
}
}
/// <summary>
/// Bernsenの手法による二値化処理を行う。
/// </summary>
/// <param name="imgSrc">入力画像</param>
/// <param name="imgDst">出力画像</param>
/// <param name="kernelSize">局所領域のサイズ</param>
/// <param name="constrastMin">この数値以下のコントラストの領域は背景領域とみなす</param>
/// <param name="bgThreshold">背景領域と見なされた領域に適用する閾値（背景領域以外では、適応的に閾値を求める）</param>
#else
/// <summary>
/// Binarizes by Bernsen's method
/// </summary>
/// <param name="src">Input image</param>
/// <param name="dst">Output image</param>
/// <param name="kernelSize">Window size</param>
/// <param name="constrastMin">Adequate coefficient</param>
/// <param name="bgThreshold">Adequate coefficient</param>
#endif
public static void Bernsen(Mat src, Mat dst, int kernelSize, byte constrastMin, byte bgThreshold)
{
if (src == null)
{
throw new ArgumentNullException(nameof(src));
}
if (dst == null)
{
throw new ArgumentNullException(nameof(dst));
}
// グレースケールのみ
if (src.Type() != MatType.CV_8UC1)
{
throw new ArgumentException("src must be gray scale image");
}
// サイズのチェック
if (kernelSize < 3)
{
throw new ArgumentOutOfRangeException(nameof(kernelSize), "size must be 3 and above");
}
if (kernelSize % 2 == 0)
{
throw new ArgumentOutOfRangeException(nameof(kernelSize), "size must be odd number");
}
int width = src.Width;
int height = src.Height;
dst.Create(src.Size(), src.Type());
using (var tSrcMat = new MatOfByte(src))
using (var tDstMat = new MatOfByte(dst))
{
var tSrc = tSrcMat.GetIndexer();
var tDst = tDstMat.GetIndexer();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
byte min, max;
MinMax(src, x, y, kernelSize, out min, out max);
int contrast = max - min;
byte threshold;
if (contrast < constrastMin)
{
threshold = bgThreshold;
}
else
{
threshold = (byte)((max + min) / 2);
}
if (tSrc[y, x] <= threshold)
{
tDst[y, x] = 0;
}
else
{
tDst[y, x] = 255;
}
}
}
}
}
/// <summary>
/// Refines the matches with homography.
/// </summary>
/// <returns><c>true</c>, if matches with homography was refined, <c>false</c> otherwise.</returns>
/// <param name="queryKeypoints">Query keypoints.</param>
/// <param name="trainKeypoints">Train keypoints.</param>
/// <param name="reprojectionThreshold">Reprojection threshold.</param>
/// <param name="matches">Matches.</param>
/// <param name="homography">Homography.</param>
static bool refineMatchesWithHomography
(
MatOfKeyPoint queryKeypoints,
MatOfKeyPoint trainKeypoints,
float reprojectionThreshold,
MatOfDMatch matches,
Mat homography
)
{
// Debug.Log ("matches " + matches.ToString ());
int minNumberMatchesAllowed = 8;
List <KeyPoint> queryKeypointsList = queryKeypoints.toList();
List <KeyPoint> trainKeypointsList = trainKeypoints.toList();
List <DMatch> matchesList = matches.toList();
if (matchesList.Count < minNumberMatchesAllowed)
{
return(false);
}
// Prepare data for cv::findHomography
List <Point> srcPointsList = new List <Point> (matchesList.Count);
List <Point> dstPointsList = new List <Point> (matchesList.Count);
for (int i = 0; i < matchesList.Count; i++)
{
srcPointsList.Add(trainKeypointsList [matchesList [i].trainIdx].pt);
dstPointsList.Add(queryKeypointsList [matchesList [i].queryIdx].pt);
}
// Find homography matrix and get inliers mask
using (MatOfPoint2f srcPoints = new MatOfPoint2f())
using (MatOfPoint2f dstPoints = new MatOfPoint2f())
using (MatOfByte inliersMask = new MatOfByte(new byte[srcPointsList.Count])) {
srcPoints.fromList(srcPointsList);
dstPoints.fromList(dstPointsList);
// Debug.Log ("srcPoints " + srcPoints.ToString ());
// Debug.Log ("dstPoints " + dstPoints.ToString ());
Calib3d.findHomography(srcPoints,
dstPoints,
Calib3d.FM_RANSAC,
reprojectionThreshold,
inliersMask, 2000, 0.955).copyTo(homography);
if (homography.rows() != 3 || homography.cols() != 3)
{
return(false);
}
//Debug.Log ("homography " + homography.ToString ());
//Debug.Log ("inliersMask " + inliersMask.dump ());
List <byte> inliersMaskList = inliersMask.toList();
List <DMatch> inliers = new List <DMatch> ();
for (int i = 0; i < inliersMaskList.Count; i++)
{
if (inliersMaskList [i] == 1)
{
inliers.Add(matchesList [i]);
}
}
matches.fromList(inliers);
//Debug.Log ("matches " + matches.ToString ());
}
return(matchesList.Count > minNumberMatchesAllowed);
}
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);
}
private void BeamDetection(string outputfilename, bool isup)
{// beam Detection
int BinarizeThreshold = 60;
int BrightnessThreshold = 4;
int nop = 7;
double dz = 0;
if (isup == true)
{
dz = -0.003;
}
else
{
dz = 0.003;
}
Camera camera = Camera.GetInstance();
MotorControler mc = MotorControler.GetInstance(parameterManager);
Vector3 InitPoint = mc.GetPoint();
Vector3 p = new Vector3();
TracksManager tm = parameterManager.TracksManager;
int mod = parameterManager.ModuleNo;
int pl = parameterManager.PlateNo;
Track myTrack = tm.GetTrack(tm.TrackingIndex);
string[] sp = myTrack.IdString.Split('-');
//string datfileName = string.Format("{0}.dat", System.DateTime.Now.ToString("yyyyMMdd_HHmmss"));
string datfileName = string.Format(@"c:\test\bpm\{0}\{1}-{2}-{3}-{4}-{5}.dat", mod, mod, pl, sp[0], sp[1], System.DateTime.Now.ToString("ddHHmmss"));
BinaryWriter writer = new BinaryWriter(File.Open(datfileName, FileMode.Create));
byte[] bb = new byte[440 * 512 * nop];
string fileName = string.Format("{0}", outputfilename);
StreamWriter twriter = File.CreateText(fileName);
string stlog = "";
List <ImageTaking> LiIT = TakeSequentialImage(0.0, 0.0, dz, nop);
Mat sum = Mat.Zeros(440, 512, MatType.CV_8UC1);
for (int i = 0; i < LiIT.Count; i++)
{
Mat bin = (Mat)DogContrastBinalize(LiIT[i].img, 31, BinarizeThreshold);
Cv2.Add(sum, bin, sum);
//byte[] b = LiIT[i].img.ToBytes();//format is .png
MatOfByte mob = new MatOfByte(LiIT[i].img);
byte[] b = mob.ToArray();
b.CopyTo(bb, 440 * 512 * i);
}
mc.MovePointZ(InitPoint.Z);
mc.Join();
Cv2.Threshold(sum, sum, BrightnessThreshold, 1, ThresholdType.Binary);
//Cv2.FindContoursをつかうとAccessViolationExceptionになる(Release/Debug両方)ので、C-API風に書く
using (CvMemStorage storage = new CvMemStorage())
{
using (CvContourScanner scanner = new CvContourScanner(sum.ToIplImage(), storage, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple))
{
//string fileName = string.Format(@"c:\img\{0}.txt",
// System.DateTime.Now.ToString("yyyyMMdd_HHmmss_fff"));
foreach (CvSeq <CvPoint> c in scanner)
{
CvMoments mom = new CvMoments(c, false);
if (c.ElemSize < 2)
{
continue;
}
if (mom.M00 == 0.0)
{
continue;
}
double mx = mom.M10 / mom.M00;
double my = mom.M01 / mom.M00;
stlog += string.Format("{0:F} {1:F}\n", mx, my);
}
}
}
twriter.Write(stlog);
twriter.Close();
writer.Write(bb);
writer.Flush();
writer.Close();
sum *= 255;
sum.ImWrite(String.Format(@"c:\img\{0}_{1}_{2}.bmp",
System.DateTime.Now.ToString("yyyyMMdd_HHmmss"),
(int)(p.X * 1000),
(int)(p.Y * 1000)));
}//BeamDetection
/**
* Draws the found matches of keypoints from two images.
*
* param img1 First source image.
* param keypoints1 Keypoints from the first source image.
* param img2 Second source image.
* param keypoints2 Keypoints from the second source image.
* param matches1to2 Matches from the first image to the second one, which means that keypoints1[i]
* has a corresponding point in keypoints2[matches[i]] .
* param outImg Output image. Its content depends on the flags value defining what is drawn in the
* output image. See possible flags bit values below.
* param matchColor Color of matches (lines and connected keypoints). If matchColor==Scalar::all(-1)
* , the color is generated randomly.
* param singlePointColor Color of single keypoints (circles), which means that keypoints do not
* have the matches. If singlePointColor==Scalar::all(-1) , the color is generated randomly.
* param matchesMask Mask determining which matches are drawn. If the mask is empty, all matches are
* drawn.
* DrawMatchesFlags.
*
* This function draws matches of keypoints from two images in the output image. Match is a line
* connecting two keypoints (circles). See cv::DrawMatchesFlags.
*/
public static void drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask)
{
if (img1 != null)
{
img1.ThrowIfDisposed();
}
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (img2 != null)
{
img2.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (outImg != null)
{
outImg.ThrowIfDisposed();
}
if (matchesMask != null)
{
matchesMask.ThrowIfDisposed();
}
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
Mat matchesMask_mat = matchesMask;
features2d_Features2d_drawMatches_11(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj, matchColor.val[0], matchColor.val[1], matchColor.val[2], matchColor.val[3], singlePointColor.val[0], singlePointColor.val[1], singlePointColor.val[2], singlePointColor.val[3], matchesMask_mat.nativeObj);
}
//
// C++: void cv::drawMatches(Mat img1, vector_KeyPoint keypoints1, Mat img2, vector_KeyPoint keypoints2, vector_DMatch matches1to2, Mat& outImg, Scalar matchColor = Scalar::all(-1), Scalar singlePointColor = Scalar::all(-1), vector_char matchesMask = std::vector<char>(), DrawMatchesFlags flags = DrawMatchesFlags::DEFAULT)
//
//javadoc: drawMatches(img1, keypoints1, img2, keypoints2, matches1to2, outImg, matchColor, singlePointColor, matchesMask)
public static void drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask)
{
if (img1 != null)
{
img1.ThrowIfDisposed();
}
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (img2 != null)
{
img2.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (outImg != null)
{
outImg.ThrowIfDisposed();
}
if (matchesMask != null)
{
matchesMask.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
Mat matchesMask_mat = matchesMask;
features2d_Features2d_drawMatches_10(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj, matchColor.val[0], matchColor.val[1], matchColor.val[2], matchColor.val[3], singlePointColor.val[0], singlePointColor.val[1], singlePointColor.val[2], singlePointColor.val[3], matchesMask_mat.nativeObj);
return;
#else
return;
#endif
}
public Dictionary <string, BitmapSource> GenerateQRCore(string inputMessage, QRCodeProperties qrCodeProps, QRColorMode colorMode)
{
outputImages = new Dictionary <string, BitmapSource>();
outputMats = new Dictionary <string, Mat>();
matSearchPixels = new List <Point>();
this.inputMessage = inputMessage;
CalculateSearchPoint(qrCodeProps);
if (colorMode == QRColorMode.Grayscale)
{
// Generate empty mat and set all pixels to white
qrMatMono = Mat.Zeros(new Size(qrCodeProps.ImgSize.Width, qrCodeProps.ImgSize.Height), MatType.CV_8UC1);
//qrMat.SetTo(Scalar.White);
// Get mat indexer
MatOfByte mob1 = new MatOfByte(qrMatMono);
MatIndexer <byte> indexerByte = mob1.GetIndexer();
int stringIndex = -1;
for (int y = 0; y < qrCodeProps.CellsPerDim * qrCodeProps.CellSize; y += qrCodeProps.CellSize)
{
for (int x = 0; x < qrCodeProps.CellsPerDim * qrCodeProps.CellSize; x += qrCodeProps.CellSize)
{
// If message is done reading
if (++stringIndex + 1 > inputMessage.Length)
{
break;
}
// If bit is 0, skip this cell
if (inputMessage[stringIndex].Equals('0'))
{
continue;
}
// If bit is 1, color the cell
else if (inputMessage[stringIndex].Equals('1'))
{
for (int i = y; i < y + qrCodeProps.CellSize; i++)
{
for (int j = x; j < x + qrCodeProps.CellSize; j++)
{
indexerByte[i, j] = LUM_INTENSITY_MAX;
}
}
}
}
}
// Add image and mat to output lists
outputImages.Add(QR_TYPE_MONOCHROME, Utils.MatToImage(qrMatMono));
outputMats.Add(QR_TYPE_MONOCHROME, qrMatMono);
// Return images to UI
return(outputImages);
}
else if (colorMode == QRColorMode.Color)
{
// Generate empty mats and fill with white
Mat qrRedMat = Mat.Zeros(new Size(qrCodeProps.ImgSize.Width, qrCodeProps.ImgSize.Height), MatType.CV_8UC3);
Mat qrGreenMat = Mat.Zeros(new Size(qrCodeProps.ImgSize.Width, qrCodeProps.ImgSize.Height), MatType.CV_8UC3);
Mat qrBlueMat = Mat.Zeros(new Size(qrCodeProps.ImgSize.Width, qrCodeProps.ImgSize.Height), MatType.CV_8UC3);
//qrCyanMat.SetTo(Scalar.White);
//qrMagentaMat.SetTo(Scalar.White);
//qrYellowMat.SetTo(Scalar.White);
// Get mat indexers
MatOfByte3 mobRed = new MatOfByte3(qrRedMat);
MatOfByte3 mobGreen = new MatOfByte3(qrGreenMat);
MatOfByte3 mobBlue = new MatOfByte3(qrBlueMat);
MatIndexer <Vec3b> indexerMobRed = mobRed.GetIndexer();
MatIndexer <Vec3b> indexerMobGreen = mobGreen.GetIndexer();
MatIndexer <Vec3b> indexerMobBlue = mobBlue.GetIndexer();
// Split message thrice
int bitsPerChar = 7;
int messageChars = inputMessage.Length / bitsPerChar;
string messageForRed = string.Empty;
string messageForGreen = string.Empty;
string messageForBlue = string.Empty;
for (int i = 0; i < messageChars; i++)
{
if (i % 3 == 0)
{
for (int j = 0; j < bitsPerChar; j++)
{
messageForRed += inputMessage[(i * bitsPerChar) + j];
}
}
else if (i % 3 == 1)
{
for (int j = 0; j < bitsPerChar; j++)
{
messageForGreen += inputMessage[(i * bitsPerChar) + j];
}
}
else if (i % 3 == 2)
{
for (int j = 0; j < bitsPerChar; j++)
{
messageForBlue += inputMessage[(i * bitsPerChar) + j];
}
}
}
indexerMobRed = WriteColorComponent(messageForRed, qrCodeProps, indexerMobRed, COLOR_RED);
indexerMobGreen = WriteColorComponent(messageForGreen, qrCodeProps, indexerMobGreen, COLOR_GREEN);
indexerMobBlue = WriteColorComponent(messageForBlue, qrCodeProps, indexerMobBlue, COLOR_BLUE);
Mat combinedMat = qrRedMat + qrGreenMat + qrBlueMat;
// Add image and mats to output lists
outputImages.Add(QR_TYPE_COMBINED, Utils.MatToImage(combinedMat));
outputImages.Add(QR_TYPE_RED, Utils.MatToImage(qrRedMat));
outputImages.Add(QR_TYPE_GREEN, Utils.MatToImage(qrGreenMat));
outputImages.Add(QR_TYPE_BLUE, Utils.MatToImage(qrBlueMat));
outputMats.Add(QR_TYPE_COMBINED, combinedMat);
outputMats.Add(QR_TYPE_RED, qrRedMat);
outputMats.Add(QR_TYPE_GREEN, qrGreenMat);
outputMats.Add(QR_TYPE_BLUE, qrBlueMat);
return(outputImages);
}
return(null);
}
public Dictionary <string, string> DecodeQRCode(QRCodeProperties qrCodeProps, QRColorMode colorMode)
{
outputMessages = new Dictionary <string, string>();
if (colorMode == QRColorMode.Grayscale)
{
string decodedBinary = string.Empty;
outputMats.TryGetValue(QR_TYPE_MONOCHROME, out Mat qrMatMono);
// Get mat indexer
MatOfByte mob1 = new MatOfByte(qrMatMono);
MatIndexer <byte> indexerByte = mob1.GetIndexer();
// Read decoded strings
int bitsPerChar = 7;
int messageLength = inputMessage.Length;
decimal messageChars = messageLength / bitsPerChar;
// Read decoded binary
for (int i = 0; i < messageChars; i++)
{
decodedBinary += ReadMonochromePixels(indexerByte, i, bitsPerChar);
}
// Add decoded messag to output list
outputMessages.Add(QR_TYPE_MONOCHROME, decodedBinary);
return(outputMessages);
}
else if (colorMode == QRColorMode.Color)
{
string decodedBinaryRed = string.Empty;
string decodedBinaryGreen = string.Empty;
string decodedBinaryBlue = string.Empty;
string decodedBinaryCombined = string.Empty;
outputMats.TryGetValue(QR_TYPE_COMBINED, out Mat qrMatCombined);
// Get mat indexer
MatOfByte3 mobComb = new MatOfByte3(qrMatCombined);
MatIndexer <Vec3b> indexerMobComb = mobComb.GetIndexer();
// Read decoded strings
int bitsPerChar = 7;
int messageLength = inputMessage.Length;
decimal messageChars = messageLength / bitsPerChar;
int coloredMessageLength = (int)Math.Ceiling(messageChars / 3);
for (int i = 0; i < coloredMessageLength; i++)
{
string tempRed = ReadColorPixels(indexerMobComb, QR_TYPE_RED, i, bitsPerChar);
string tempGreen = ReadColorPixels(indexerMobComb, QR_TYPE_GREEN, i, bitsPerChar);
string tempBlue = ReadColorPixels(indexerMobComb, QR_TYPE_BLUE, i, bitsPerChar);
decodedBinaryRed += tempRed;
decodedBinaryGreen += tempGreen;
decodedBinaryBlue += tempBlue;
decodedBinaryCombined += tempRed;
decodedBinaryCombined += tempGreen;
decodedBinaryCombined += tempBlue;
}
// Add output messages
outputMessages.Add(QR_TYPE_RED, decodedBinaryRed);
outputMessages.Add(QR_TYPE_GREEN, decodedBinaryGreen);
outputMessages.Add(QR_TYPE_BLUE, decodedBinaryBlue);
outputMessages.Add(QR_TYPE_COMBINED, decodedBinaryCombined);
return(outputMessages);
}
return(null);
}
//javadoc: calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts, status, err, winSize, maxLevel, criteria)
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria)
{
if (prevImg != null)
{
prevImg.ThrowIfDisposed();
}
if (nextImg != null)
{
nextImg.ThrowIfDisposed();
}
if (prevPts != null)
{
prevPts.ThrowIfDisposed();
}
if (nextPts != null)
{
nextPts.ThrowIfDisposed();
}
if (status != null)
{
status.ThrowIfDisposed();
}
if (err != null)
{
err.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat prevPts_mat = prevPts;
Mat nextPts_mat = nextPts;
Mat status_mat = status;
Mat err_mat = err;
video_Video_calcOpticalFlowPyrLK_12(prevImg.nativeObj, nextImg.nativeObj, prevPts_mat.nativeObj, nextPts_mat.nativeObj, status_mat.nativeObj, err_mat.nativeObj, winSize.width, winSize.height, maxLevel, criteria.type, criteria.maxCount, criteria.epsilon);
return;
#else
return;
#endif
}
//javadoc: calcOpticalFlowPyrLK(prevImg, nextImg, prevPts, nextPts, status, err)
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err)
{
if (prevImg != null)
{
prevImg.ThrowIfDisposed();
}
if (nextImg != null)
{
nextImg.ThrowIfDisposed();
}
if (prevPts != null)
{
prevPts.ThrowIfDisposed();
}
if (nextPts != null)
{
nextPts.ThrowIfDisposed();
}
if (status != null)
{
status.ThrowIfDisposed();
}
if (err != null)
{
err.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat prevPts_mat = prevPts;
Mat nextPts_mat = nextPts;
Mat status_mat = status;
Mat err_mat = err;
video_Video_calcOpticalFlowPyrLK_15(prevImg.nativeObj, nextImg.nativeObj, prevPts_mat.nativeObj, nextPts_mat.nativeObj, status_mat.nativeObj, err_mat.nativeObj);
return;
#else
return;
#endif
}
private IEnumerator init()
{
if (webCamTexture != null)
{
webCamTexture.Stop();
initDone = false;
rgbaMat.Dispose();
matOpFlowThis.Dispose();
matOpFlowPrev.Dispose();
MOPcorners.Dispose();
mMOP2fptsThis.Dispose();
mMOP2fptsPrev.Dispose();
mMOP2fptsSafe.Dispose();
mMOBStatus.Dispose();
mMOFerr.Dispose();
}
// Checks how many and which cameras are available on the device
for (int cameraIndex = 0; cameraIndex < WebCamTexture.devices.Length; cameraIndex++)
{
if (WebCamTexture.devices [cameraIndex].isFrontFacing == shouldUseFrontFacing)
{
Debug.Log(cameraIndex + " name " + WebCamTexture.devices [cameraIndex].name + " isFrontFacing " + WebCamTexture.devices [cameraIndex].isFrontFacing);
webCamDevice = WebCamTexture.devices [cameraIndex];
webCamTexture = new WebCamTexture(webCamDevice.name, width, height);
break;
}
}
if (webCamTexture == null)
{
webCamDevice = WebCamTexture.devices [0];
webCamTexture = new WebCamTexture(webCamDevice.name, width, height);
}
Debug.Log("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
// Starts the camera
webCamTexture.Play();
while (true)
{
//If you want to use webcamTexture.width and webcamTexture.height on iOS, you have to wait until webcamTexture.didUpdateThisFrame == 1, otherwise these two values will be equal to 16. (http://forum.unity3d.com/threads/webcamtexture-and-error-0x0502.123922/)
#if UNITY_IOS && !UNITY_EDITOR && (UNITY_4_6_3 || UNITY_4_6_4 || UNITY_5_0_0 || UNITY_5_0_1)
if (webCamTexture.width > 16 && webCamTexture.height > 16)
{
#else
if (webCamTexture.didUpdateThisFrame)
{
#endif
Debug.Log("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
Debug.Log("videoRotationAngle " + webCamTexture.videoRotationAngle + " videoVerticallyMirrored " + webCamTexture.videoVerticallyMirrored + " isFrongFacing " + webCamDevice.isFrontFacing);
colors = new Color32[webCamTexture.width * webCamTexture.height];
rgbaMat = new Mat(webCamTexture.height, webCamTexture.width, CvType.CV_8UC4);
matOpFlowThis = new Mat();
matOpFlowPrev = new Mat();
MOPcorners = new MatOfPoint();
mMOP2fptsThis = new MatOfPoint2f();
mMOP2fptsPrev = new MatOfPoint2f();
mMOP2fptsSafe = new MatOfPoint2f();
mMOBStatus = new MatOfByte();
mMOFerr = new MatOfFloat();
texture = new Texture2D(webCamTexture.width, webCamTexture.height, TextureFormat.RGBA32, false);
gameObject.GetComponent <Renderer> ().material.mainTexture = texture;
updateLayout();
screenOrientation = Screen.orientation;
initDone = true;
break;
}
else
{
yield return(0);
}
}
}
public static SWIGTYPE_p_cv__Mat_T_uchar_t ToSwig(this MatOfByte obj)
{
return(new SWIGTYPE_p_cv__Mat_T_uchar_t(obj.CvPtr));
}
/// <summary>
/// Bernsenの手法による二値化処理を行う。
/// </summary>
/// <param name="imgSrc">入力画像</param>
/// <param name="imgDst">出力画像</param>
/// <param name="kernelSize">局所領域のサイズ</param>
/// <param name="constrastMin">この数値以下のコントラストの領域は背景領域とみなす</param>
/// <param name="bgThreshold">背景領域と見なされた領域に適用する閾値（背景領域以外では、適応的に閾値を求める）</param>
#else
/// <summary>
/// Binarizes by Bernsen's method
/// </summary>
/// <param name="src">Input image</param>
/// <param name="dst">Output image</param>
/// <param name="kernelSize">Window size</param>
/// <param name="constrastMin">Adequate coefficient</param>
/// <param name="bgThreshold">Adequate coefficient</param>
#endif
public static void Bernsen(Mat src, Mat dst, int kernelSize, byte constrastMin, byte bgThreshold)
{
if (src == null)
throw new ArgumentNullException("src");
if (dst == null)
throw new ArgumentNullException("dst");
// グレースケールのみ
if (src.Type() != MatType.CV_8UC1)
throw new ArgumentException("src must be gray scale image");
if (dst.Type() != MatType.CV_8UC1)
throw new ArgumentException("dst must be gray scale image");
// サイズのチェック
if (kernelSize < 3)
throw new ArgumentOutOfRangeException("kernelSize", "size must be 3 and above");
if (kernelSize % 2 == 0)
throw new ArgumentOutOfRangeException("kernelSize", "size must be odd number");
int width = src.Width;
int height = src.Height;
dst.Create(src.Size(), src.Type());
using (var tSrcMat = new MatOfByte(src))
using (var tDstMat = new MatOfByte(dst))
{
var tSrc = tSrcMat.GetIndexer();
var tDst = tDstMat.GetIndexer();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
byte min, max;
MinMax(src, x, y, kernelSize, out min, out max);
int contrast = max - min;
byte threshold;
if (contrast < constrastMin)
threshold = bgThreshold;
else
threshold = (byte)((max + min) / 2);
if (tSrc[y, x] <= threshold)
tDst[y, x] = 0;
else
tDst[y, x] = 255;
}
}
}
}
private IEnumerator init()
{
if (webCamTexture != null) {
webCamTexture.Stop ();
initDone = false;
rgbaMat.Dispose ();
matOpFlowThis.Dispose ();
matOpFlowPrev.Dispose ();
MOPcorners.Dispose ();
mMOP2fptsThis.Dispose ();
mMOP2fptsPrev.Dispose ();
mMOP2fptsSafe.Dispose ();
mMOBStatus.Dispose ();
mMOFerr.Dispose ();
}
// Checks how many and which cameras are available on the device
for (int cameraIndex = 0; cameraIndex < WebCamTexture.devices.Length; cameraIndex++) {
if (WebCamTexture.devices [cameraIndex].isFrontFacing == shouldUseFrontFacing) {
Debug.Log (cameraIndex + " name " + WebCamTexture.devices [cameraIndex].name + " isFrontFacing " + WebCamTexture.devices [cameraIndex].isFrontFacing);
webCamDevice = WebCamTexture.devices [cameraIndex];
webCamTexture = new WebCamTexture (webCamDevice.name, width, height);
break;
}
}
if (webCamTexture == null) {
webCamDevice = WebCamTexture.devices [0];
webCamTexture = new WebCamTexture (webCamDevice.name, width, height);
}
Debug.Log ("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
// Starts the camera
webCamTexture.Play ();
while (true) {
//If you want to use webcamTexture.width and webcamTexture.height on iOS, you have to wait until webcamTexture.didUpdateThisFrame == 1, otherwise these two values will be equal to 16. (http://forum.unity3d.com/threads/webcamtexture-and-error-0x0502.123922/)
#if UNITY_IOS && !UNITY_EDITOR && (UNITY_4_6_3 || UNITY_4_6_4 || UNITY_5_0_0 || UNITY_5_0_1)
if (webCamTexture.width > 16 && webCamTexture.height > 16) {
#else
if (webCamTexture.didUpdateThisFrame) {
#if UNITY_IOS && !UNITY_EDITOR && UNITY_5_2
while (webCamTexture.width <= 16) {
webCamTexture.GetPixels32 ();
yield return new WaitForEndOfFrame ();
}
#endif
#endif
Debug.Log ("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
Debug.Log ("videoRotationAngle " + webCamTexture.videoRotationAngle + " videoVerticallyMirrored " + webCamTexture.videoVerticallyMirrored + " isFrongFacing " + webCamDevice.isFrontFacing);
colors = new Color32[webCamTexture.width * webCamTexture.height];
rgbaMat = new Mat (webCamTexture.height, webCamTexture.width, CvType.CV_8UC4);
matOpFlowThis = new Mat ();
matOpFlowPrev = new Mat ();
MOPcorners = new MatOfPoint ();
mMOP2fptsThis = new MatOfPoint2f ();
mMOP2fptsPrev = new MatOfPoint2f ();
mMOP2fptsSafe = new MatOfPoint2f ();
mMOBStatus = new MatOfByte ();
mMOFerr = new MatOfFloat ();
texture = new Texture2D (webCamTexture.width, webCamTexture.height, TextureFormat.RGBA32, false);
gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
updateLayout ();
screenOrientation = Screen.orientation;
initDone = true;
break;
} else {
yield return 0;
}
}
}
/// <summary>
/// 注目画素の周辺画素の平均値と標準偏差を求める
/// </summary>
/// <param name="img">画像の画素データ</param>
/// <param name="x">x座標</param>
/// <param name="y">y座標</param>
/// <param name="size">周辺画素の探索サイズ。奇数でなければならない</param>
/// <param name="mean">出力される平均</param>
/// <param name="stddev">出力される標準偏差</param>
private static void MeanStddev(Mat img, int x, int y, int size, out double mean, out double stddev)
{
int count = 0;
int sum = 0;
int sqsum = 0;
int size2 = size / 2;
int xs = Math.Max(x - size2, 0);
int xe = Math.Min(x + size2, img.Width);
int ys = Math.Max(y - size2, 0);
int ye = Math.Min(y + size2, img.Height);
byte v;
using (var tImg = new MatOfByte(img))
{
var indexer = tImg.GetIndexer();
for (int xx = xs; xx < xe; xx++)
{
for (int yy = ys; yy < ye; yy++)
{
v = indexer[yy, xx];
sum += v;
sqsum += v*v;
count++;
}
}
}
mean = (double)sum / count;
double var = ((double)sqsum / count) - (mean * mean);
if (var < 0.0) var = 0.0;
stddev = Math.Sqrt(var);
}
private IEnumerator init()
{
if (webCamTexture != null) {
webCamTexture.Stop ();
initDone = false;
rgbaMat.Dispose ();
matOpFlowThis.Dispose ();
matOpFlowPrev.Dispose ();
MOPcorners.Dispose ();
mMOP2fptsThis.Dispose ();
mMOP2fptsPrev.Dispose ();
mMOP2fptsSafe.Dispose ();
mMOBStatus.Dispose ();
mMOFerr.Dispose ();
}
// Checks how many and which cameras are available on the device
for (int cameraIndex = 0; cameraIndex < WebCamTexture.devices.Length; cameraIndex++) {
if (WebCamTexture.devices [cameraIndex].isFrontFacing == isFrontFacing) {
Debug.Log (cameraIndex + " name " + WebCamTexture.devices [cameraIndex].name + " isFrontFacing " + WebCamTexture.devices [cameraIndex].isFrontFacing);
webCamDevice = WebCamTexture.devices [cameraIndex];
webCamTexture = new WebCamTexture (webCamDevice.name, width, height);
break;
}
}
if (webCamTexture == null) {
webCamDevice = WebCamTexture.devices [0];
webCamTexture = new WebCamTexture (webCamDevice.name, width, height);
}
Debug.Log ("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
// Starts the camera
webCamTexture.Play ();
while (true) {
//If you want to use webcamTexture.width and webcamTexture.height on iOS, you have to wait until webcamTexture.didUpdateThisFrame == 1, otherwise these two values will be equal to 16. (http://forum.unity3d.com/threads/webcamtexture-and-error-0x0502.123922/)
#if UNITY_IOS && !UNITY_EDITOR && (UNITY_4_6_3 || UNITY_4_6_4 || UNITY_5_0_0 || UNITY_5_0_1)
if (webCamTexture.width > 16 && webCamTexture.height > 16) {
#else
if (webCamTexture.didUpdateThisFrame) {
#endif
Debug.Log ("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
Debug.Log ("videoRotationAngle " + webCamTexture.videoRotationAngle + " videoVerticallyMirrored " + webCamTexture.videoVerticallyMirrored + " isFrongFacing " + webCamDevice.isFrontFacing);
colors = new Color32[webCamTexture.width * webCamTexture.height];
rgbaMat = new Mat (webCamTexture.height, webCamTexture.width, CvType.CV_8UC4);
matOpFlowThis = new Mat ();
matOpFlowPrev = new Mat ();
MOPcorners = new MatOfPoint ();
mMOP2fptsThis = new MatOfPoint2f ();
mMOP2fptsPrev = new MatOfPoint2f ();
mMOP2fptsSafe = new MatOfPoint2f ();
mMOBStatus = new MatOfByte ();
mMOFerr = new MatOfFloat ();
texture = new Texture2D (webCamTexture.width, webCamTexture.height, TextureFormat.RGBA32, false);
gameObject.transform.eulerAngles = new Vector3 (0, 0, 0);
#if (UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR
gameObject.transform.eulerAngles = new Vector3 (0, 0, -90);
#endif
// gameObject.transform.rotation = gameObject.transform.rotation * Quaternion.AngleAxis (webCamTexture.videoRotationAngle, Vector3.back);
gameObject.transform.localScale = new Vector3 (webCamTexture.width, webCamTexture.height, 1);
// bool videoVerticallyMirrored = webCamTexture.videoVerticallyMirrored;
// float scaleX = 1;
// float scaleY = videoVerticallyMirrored ? -1.0f : 1.0f;
// if (webCamTexture.videoRotationAngle == 270)
// scaleY = -1.0f;
// gameObject.transform.localScale = new Vector3 (scaleX * gameObject.transform.localScale.x, scaleY * gameObject.transform.localScale.y, 1);
gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
#if (UNITY_ANDROID || UNITY_IOS) && !UNITY_EDITOR
Camera.main.orthographicSize = webCamTexture.width / 2;
#else
Camera.main.orthographicSize = webCamTexture.height / 2;
#endif
initDone = true;
break;
} else {
yield return 0;
}
}
}
// Update is called once per frame
void Update ()
{
if (!initDone)
return;
#if UNITY_IOS && !UNITY_EDITOR && (UNITY_4_6_3 || UNITY_4_6_4 || UNITY_5_0_0 || UNITY_5_0_1)
if (webCamTexture.width > 16 && webCamTexture.height > 16) {
#else
if (webCamTexture.didUpdateThisFrame) {
#endif
Utils.webCamTextureToMat (webCamTexture, rgbaMat, colors);
if (webCamTexture.videoVerticallyMirrored) {
if (webCamDevice.isFrontFacing) {
if (webCamTexture.videoRotationAngle == 0) {
Core.flip (rgbaMat, rgbaMat, 1);
} else if (webCamTexture.videoRotationAngle == 90) {
Core.flip (rgbaMat, rgbaMat, 0);
} else if (webCamTexture.videoRotationAngle == 270) {
Core.flip (rgbaMat, rgbaMat, 1);
}
} else {
if (webCamTexture.videoRotationAngle == 90) {
} else if (webCamTexture.videoRotationAngle == 270) {
Core.flip (rgbaMat, rgbaMat, -1);
}
}
} else {
if (webCamDevice.isFrontFacing) {
if (webCamTexture.videoRotationAngle == 0) {
Core.flip (rgbaMat, rgbaMat, 1);
} else if (webCamTexture.videoRotationAngle == 90) {
Core.flip (rgbaMat, rgbaMat, 0);
} else if (webCamTexture.videoRotationAngle == 270) {
Core.flip (rgbaMat, rgbaMat, 1);
}
} else {
if (webCamTexture.videoRotationAngle == 90) {
} else if (webCamTexture.videoRotationAngle == 270) {
Core.flip (rgbaMat, rgbaMat, -1);
}
}
}
if (mMOP2fptsPrev.rows () == 0) {
// first time through the loop so we need prev and this mats
// plus prev points
// get this mat
Imgproc.cvtColor (rgbaMat, matOpFlowThis, Imgproc.COLOR_RGBA2GRAY);
// copy that to prev mat
matOpFlowThis.copyTo (matOpFlowPrev);
// get prev corners
Imgproc.goodFeaturesToTrack (matOpFlowPrev, MOPcorners, iGFFTMax, 0.05, 20);
mMOP2fptsPrev.fromArray (MOPcorners.toArray ());
// get safe copy of this corners
mMOP2fptsPrev.copyTo (mMOP2fptsSafe);
} else {
// we've been through before so
// this mat is valid. Copy it to prev mat
matOpFlowThis.copyTo (matOpFlowPrev);
// get this mat
Imgproc.cvtColor (rgbaMat, matOpFlowThis, Imgproc.COLOR_RGBA2GRAY);
// get the corners for this mat
Imgproc.goodFeaturesToTrack (matOpFlowThis, MOPcorners, iGFFTMax, 0.05, 20);
mMOP2fptsThis.fromArray (MOPcorners.toArray ());
// retrieve the corners from the prev mat
// (saves calculating them again)
mMOP2fptsSafe.copyTo (mMOP2fptsPrev);
// and save this corners for next time through
mMOP2fptsThis.copyTo (mMOP2fptsSafe);
}
/*
Parameters:
prevImg first 8-bit input image
nextImg second input image
prevPts vector of 2D points for which the flow needs to be found; point coordinates must be single-precision floating-point numbers.
nextPts output vector of 2D points (with single-precision floating-point coordinates) containing the calculated new positions of input features in the second image; when OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.
status output status vector (of unsigned chars); each element of the vector is set to 1 if the flow for the corresponding features has been found, otherwise, it is set to 0.
err output vector of errors; each element of the vector is set to an error for the corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't found then the error is not defined (use the status parameter to find such cases).
*/
Video.calcOpticalFlowPyrLK (matOpFlowPrev, matOpFlowThis, mMOP2fptsPrev, mMOP2fptsThis, mMOBStatus, mMOFerr);
if (!mMOBStatus.empty ()) {
List<Point> cornersPrev = mMOP2fptsPrev.toList ();
List<Point> cornersThis = mMOP2fptsThis.toList ();
List<byte> byteStatus = mMOBStatus.toList ();
int x = 0;
int y = byteStatus.Count - 1;
for (x = 0; x < y; x++) {
if (byteStatus [x] == 1) {
Point pt = cornersThis [x];
Point pt2 = cornersPrev [x];
Core.circle (rgbaMat, pt, 5, colorRed, iLineThickness - 1);
Core.line (rgbaMat, pt, pt2, colorRed, iLineThickness);
}
}
}
Utils.matToTexture2D (rgbaMat, texture, colors);
gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
}
}
void OnDisable ()
{
webCamTexture.Stop ();
}
void OnGUI ()
{
float screenScale = Screen.width / 240.0f;
Matrix4x4 scaledMatrix = Matrix4x4.Scale (new Vector3 (screenScale, screenScale, screenScale));
GUI.matrix = scaledMatrix;
GUILayout.BeginVertical ();
if (GUILayout.Button ("back")) {
Application.LoadLevel ("OpenCVForUnitySample");
}
if (GUILayout.Button ("change camera")) {
isFrontFacing = !isFrontFacing;
StartCoroutine (init ());
}
GUILayout.EndVertical ();
}
}
}
public static FormExtractionResult ProcessImage(string filename, FormExtractionOptions options = null)
{
if (options == null)
{
// Assume recommanded parameters.
options = new FormExtractionOptions();
}
var orig = new Mat(filename);
var image = new Mat(filename, ImreadModes.GrayScale);
Cv2.AdaptiveThreshold(image, image, 255, AdaptiveThresholdTypes.MeanC, ThresholdTypes.Binary, 9, 4);
// Resize image if too large.
if (image.Width > options.ResizeWidth)
{
var height = options.ResizeWidth * image.Height / image.Width;
Cv2.Resize(image, image, new Size(options.ResizeWidth, height));
}
Cv2.BitwiseNot(image, image);
Cv2.Dilate(image, image, Cv2.GetStructuringElement(MorphShapes.Cross, new Size(2, 2)));
MatOfByte mat = new MatOfByte(image);
MatIndexer <byte> indexer = mat.GetIndexer();
var row = image.Height;
var col = image.Width;
Mat newImage = new Mat(row, col, MatType.CV_8UC3);
newImage.SetTo(Scalar.Black);
// We must determine if it "may" be an interesting blob.
Stopwatch watch = new Stopwatch();
watch.Start();
int[] imgData = new int[row * col];
for (int y = 0; y < row; y++)
{
for (int x = 0; x < col; x++)
{
imgData[y + x * row] = indexer[y, x];
}
}
var result = HasBoxes(imgData, row, col, options);
watch.Stop();
result.Duration = watch.Elapsed;
// Preview
if (result.Boxes.Any() && image.Width != 0 && options.ShowDebugImage)
{
var img = CreateImage(result.DebugImg, hasColor: true);
Cv2.BitwiseOr(newImage, img, newImage);
Cv2.BitwiseNot(image, image);
int width = 400;
var height = width * image.Height / image.Width;
Cv2.Resize(orig, orig, new Size(width, height));
Cv2.Resize(image, image, new Size(width, height));
Cv2.Resize(newImage, newImage, new Size(width, height));
using (new Window("orig", orig))
using (new Window("pre", image))
using (new Window("post", newImage))
{
Cv2.WaitKey();
Cv2.DestroyAllWindows();
}
}
// Dispose.
orig.Dispose();
image.Dispose();
newImage.Dispose();
mat.Dispose();
return(result);
}
