public void SetData(cv.Mat input)
{
//if (xSize != -1 || zSize != -1)
//{
// surfaceMeshRenderableSeries.DataSeries.Clear();
//}
zMap = new cv.Mat(new cv.Size(input.Width, input.Height), cv.MatType.CV_32FC1);
input.ConvertTo(zMap, cv.MatType.CV_32FC1);
//Init(zMap.Rows, zMap.Cols);
Init(zMap.Rows, zMap.Cols);
Parallel.For(0, xSize, x =>
{
for (int z = 0; z < zSize; ++z)
{
MeshDataSeries[z, x] = zMap.At <float>(x, z);
if (yMax < zMap.Get <float>(x, z))
{
yMax = zMap.Get <float>(x, z);
}
}
});
double min = 0.0f, max = 0.0f;
zMap.MinMaxLoc(out min, out max);
surfaceMeshRenderableSeries.Maximum = max;
surfaceMeshRenderableSeries.Minimum = min;
//backgroundSurfaceMesh.IsVisible = false;
}
public void ApplyMinMaxCalc(cv.Mat input)
{
double zMax = double.MinValue;
double zMin = double.MaxValue;
for (int x = 0; x < xSize; ++x)
{
for (int z = 0; z < zSize; ++z)
{
if (zMax < input.At <double>(x, z))
{
zMax = input.At <double>(x, z);
}
if (zMin > input.At <double>(x, z))
{
zMin = input.At <double>(x, z);
}
}
}
for (int x = 0; x < xSize; ++x)
{
for (int z = 0; z < zSize; ++z)
{
input.Set <float>(x, z, input.At <float>(x, z) - (float)zMin);
input.Set <float>(x, z, input.At <float>(x, z) * 1000.0f / (float)(zMax - zMin));
MeshDataSeries[z, x] = input.Get <float>(x, z);
}
}
}
public void Run()
{
Console.WriteLine("===== FlannTest =====");
// creates data set
using (var features = new Mat(10000, 2, MatType.CV_32FC1))
{
var rand = new Random();
for (int i = 0; i < features.Rows; i++)
{
features.Set<float>(i, 0, rand.Next(10000));
features.Set<float>(i, 1, rand.Next(10000));
}
// query
var queryPoint = new Point2f(7777, 7777);
var queries = new Mat(1, 2, MatType.CV_32FC1);
queries.Set<float>(0, 0, queryPoint.X);
queries.Set<float>(0, 1, queryPoint.Y);
Console.WriteLine("query:({0}, {1})", queryPoint.X, queryPoint.Y);
Console.WriteLine("-----");
// knnSearch
using (var nnIndex = new Index(features, new KDTreeIndexParams(4)))
{
const int Knn = 1;
int[] indices;
float[] dists;
nnIndex.KnnSearch(queries, out indices, out dists, Knn, new SearchParams(32));
for (int i = 0; i < Knn; i++)
{
int index = indices[i];
float dist = dists[i];
var pt = new Point2f(features.Get<float>(index, 0), features.Get<float>(index, 1));
Console.Write("No.{0}\t", i);
Console.Write("index:{0}", index);
Console.Write(" distance:{0}", dist);
Console.Write(" data:({0}, {1})", pt.X, pt.Y);
Console.WriteLine();
}
}
}
Console.Read();
}
public void Start(cv.Mat color, cv.Mat result1, int filterSize, int levels)
{
int[] intensityBin = new int[levels];
int filterOffset = (filterSize - 1) / 2;
int currentIntensity = 0, maxIntensity = 0, maxIndex = 0;
for (int offsetY = filterOffset; offsetY < color.Height - filterOffset; offsetY++)
{
for (int offsetX = filterOffset; offsetX < color.Width - filterOffset; offsetX++)
{
maxIntensity = maxIndex = 0;
intensityBin = new int[levels];
cv.Vec3i[] bins = new cv.Vec3i[levels];
for (int y = offsetY - filterOffset; y < offsetY + filterOffset; y++)
{
for (int x = offsetX - filterOffset; x < offsetX + filterOffset; x++)
{
cv.Vec3b rgb = color.Get <cv.Vec3b>(y, x);
currentIntensity = (int)(Math.Round((Double)(rgb.Item0 + rgb.Item1 + rgb.Item2) / 3.0 * (levels - 1)) / 255.0);
intensityBin[currentIntensity] += 1;
bins[currentIntensity].Item0 += rgb.Item0;
bins[currentIntensity].Item1 += rgb.Item1;
bins[currentIntensity].Item2 += rgb.Item2;
if (intensityBin[currentIntensity] > maxIntensity)
{
maxIntensity = intensityBin[currentIntensity];
maxIndex = currentIntensity;
}
}
}
if (maxIntensity == 0)
{
maxIntensity = 1;
}
double blue = bins[maxIndex].Item0 / maxIntensity;
double green = bins[maxIndex].Item1 / maxIntensity;
double red = bins[maxIndex].Item2 / maxIntensity;
result1.Set <cv.Vec3b>(offsetY, offsetX, new cv.Vec3b(ClipByte(blue), ClipByte(green), ClipByte(red)));
}
}
}
public void Run()
{
Mat src = Cv2.ImRead(FilePath.Image.Lenna, ImreadModes.GrayScale);
// Histogram view
const int Width = 260, Height = 200;
Mat render = new Mat(new Size(Width, Height), MatType.CV_8UC3, Scalar.All(255));
// Calculate histogram
Mat hist = new Mat();
int[] hdims = {256}; // Histogram size for each dimension
Rangef[] ranges = { new Rangef(0,256), }; // min/max
Cv2.CalcHist(
new Mat[]{src},
new int[]{0},
null,
hist,
1,
hdims,
ranges);
// Get the max value of histogram
double minVal, maxVal;
Cv2.MinMaxLoc(hist, out minVal, out maxVal);
Scalar color = Scalar.All(100);
// Scales and draws histogram
hist = hist * (maxVal != 0 ? Height / maxVal : 0.0);
for (int j = 0; j < hdims[0]; ++j)
{
int binW = (int)((double)Width / hdims[0]);
render.Rectangle(
new Point(j * binW, render.Rows),
new Point((j + 1) * binW, render.Rows - (int)(hist.Get<float>(j))),
color,
-1);
}
using (new Window("Image", WindowMode.AutoSize | WindowMode.FreeRatio, src))
using (new Window("Histogram", WindowMode.AutoSize | WindowMode.FreeRatio, render))
{
Cv2.WaitKey();
}
}
IEnumerator CalculateHomography()
//void CalculateHomography()
{
//Debug.Log("CalculateHomography1");
//myCam.Pause();
yield return(new WaitForEndOfFrame());
//yield return new WaitForSeconds((float)0.5);
//程式開始後至少要等0.3秒才會出現影像畫面，不然算sift一開始就會記憶體爆掉
//input camera image
/*Texture2D sourceTex = ScreenCapture.CaptureScreenshotAsTexture();
* Color[] pix = sourceTex.GetPixels((int)rectBotLeft.x, (int)rectBotLeft.y, width, height);
* Texture2D tex = new Texture2D(width, height);
* tex.SetPixels(pix);
* tex.Apply();*/
//Debug.Log("CalculateHomography2");
//rawimage position at (0,0)，start from bottom left
int xStart = (int)(Screen.width - rawImageRT.rect.width) / 2;
int yStart = (int)(Screen.height - rawImageRT.rect.height) / 2;
/*Debug.Log("xStart: "+xStart);
* Debug.Log("yStart: "+yStart);
* Debug.Log("Screen.width: "+Screen.width);
* Debug.Log("Screen.height: "+Screen.height);
* Debug.Log("rawImageRT.rect.width: "+rawImageRT.rect.width);
* Debug.Log("rawImageRT.rect.height: "+rawImageRT.rect.height);*/
//get sign image with text
Texture2D sourceTex = ScreenCapture.CaptureScreenshotAsTexture();
//rawImageRI.texture = sourceTex;
//Color[] pix = sourceTex.GetPixels((int)rectBotLeft.x, (int)rectBotLeft.y, width, height);
Color[] pix = sourceTex.GetPixels(xStart, yStart, (int)rawImageRT.rect.width, (int)rawImageRT.rect.height);
tex = new Texture2D((int)rawImageRT.rect.width, (int)rawImageRT.rect.height);
tex.SetPixels(pix);
tex.Apply();
//Debug.Log("tex.width: "+tex.width);
//Debug.Log("tex.height: "+tex.height);
//input fixed image
/*Texture2D tex = new Texture2D(2,2);
* string imgPath = "../signboard-rectangle/test-199-fast-628.jpg";
* byte [] binaryImageData = File.ReadAllBytes(imgPath);
* tex.LoadImage(binaryImageData);*/
//scale texture to make it smaller
TextureScale.Bilinear(tex, tex.width / 2, tex.height / 2);
//必要 防止記憶體爆炸
tex = TextureGray.ToGray(tex);
//rawImageRI.texture = tex;
mat = Unity.TextureToMat(tex);
Destroy(sourceTex);
Destroy(tex);
//Cv2.ImShow("img", mat); ok
//OpenCvSharp.Mat mat = Cv2.ImRead(imgPath, ImreadModes.Unchanged);
//Debug.Log("mat: "+mat.ToString());
//string imgPath = "../signboard-rectangle/test-199-fast-628.jpg";
//OpenCvSharp.Mat mat = Cv2.ImRead(imgPath);
InputArray imgCam = InputArray.Create(mat);
desCam = OutputArray.Create(mat);
//Cv2.ImShow("img", mat); ok
//OpenCvSharp.Mat mat2 = mat;
//sift = SIFT.Create();
//System.Diagnostics.Stopwatch time = new System.Diagnostics.Stopwatch();
//time.Start ();
//卡卡
OpenCvSharp.KeyPoint[] kpCam = sift.Detect(mat);
//OpenCvSharp.KeyPoint[] kpCam = surf.Detect(mat);
//OpenCvSharp.KeyPoint[] kpCam = orb.Detect(mat);
//OpenCvSharp.KeyPoint[] kpCam = brief.Detect(mat);
//time.Stop();
//Debug.Log("執行 " + time.Elapsed.TotalSeconds + " 秒");
//myCam.Pause();
//rawImageRI.texture = tex;
//Cv2.ImShow("img", mat); ok
//Cv2.ImShow("img", mat2); ok
sift.Compute(imgCam, ref kpCam, desCam);
//surf.Compute(img2, ref kpCam, desCam);
//orb.Compute(img2, ref kpCam, desCam);
//brief.Compute(img2, ref kpCam, desCam);
//Cv2.ImShow("img", mat);
//Cv2.ImShow("img", mat2); 爆炸
OpenCvSharp.Mat desCammat = desCam.GetMat();
//Debug.Log("desCammat: "+desCammat);
//if (!M) 如果還沒計算出homography M {
//desFirstCatch = desCam;
//OutputArray descriptors_object = des1;
OpenCvSharp.Mat des1mat = des1.GetMat();
OpenCvSharp.Mat des2mat = des2.GetMat();
//OpenCvSharp.Mat des3mat = des3.GetMat();
//Debug.Log("des1mat: "+des1mat);
OpenCvSharp.DMatch[] dmatch1 = descriptorMatcher.Match(des1mat, desCammat);
OpenCvSharp.DMatch[] dmatch2 = descriptorMatcher.Match(des2mat, desCammat);
//OpenCvSharp.DMatch[] dmatch3 = descriptorMatcher.Match(des3mat, desCammat);
//Debug.Log("damtch1[0]: "+dmatch1[0].ToString());
//}
//else {
//OpenCvSharp.Mat desFirstCatchmat = desFirstCatch.GetMat();
// OpenCvSharp.DMatch[] dmatch = descriptorMatcher.Match(desFirstCatchmat, desCammat);
// OutputArray descriptors_object = desFirstCatch;
//}
double max_dist1 = 0;
double min_dist1 = 100;
double max_dist2 = 0;
double min_dist2 = 100;
//double max_dist3 = 0;
//double min_dist3 = 100;
//Cv2.ImShow("img", mat); 爆炸
//Quick calculation of max and min distances between keypoints
foreach (OpenCvSharp.DMatch d in dmatch1)
{
double dist = d.Distance;
if (dist < min_dist1)
{
min_dist1 = dist;
}
if (dist > max_dist1)
{
max_dist1 = dist;
}
}
foreach (OpenCvSharp.DMatch d in dmatch2)
{
double dist = d.Distance;
if (dist < min_dist2)
{
min_dist2 = dist;
}
if (dist > max_dist2)
{
max_dist2 = dist;
}
}
/*foreach (OpenCvSharp.DMatch d in dmatch3){
* double dist = d.Distance;
* if( dist < min_dist3 ) min_dist3 = dist;
* if( dist > max_dist3 ) max_dist3 = dist;
* }*/
//Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
List <OpenCvSharp.DMatch> goodMatch1 = new List <OpenCvSharp.DMatch>();
foreach (OpenCvSharp.DMatch d in dmatch1)
{
if (d.Distance < 3 * min_dist1)
{
goodMatch1.Add(d);
}
}
List <OpenCvSharp.DMatch> goodMatch2 = new List <OpenCvSharp.DMatch>();
foreach (OpenCvSharp.DMatch d in dmatch2)
{
if (d.Distance < 3 * min_dist2)
{
goodMatch2.Add(d);
}
}
/*List<OpenCvSharp.DMatch> goodMatch3 = new List<OpenCvSharp.DMatch>();
* foreach (OpenCvSharp.DMatch d in dmatch3){
* if( d.Distance < 3*min_dist3 )
* goodMatch3.Add(d);
* }*/
List <OpenCvSharp.Point2f> srcPts1 = new List <OpenCvSharp.Point2f>();
List <OpenCvSharp.Point2f> dstPts1 = new List <OpenCvSharp.Point2f>();
foreach (OpenCvSharp.DMatch d in goodMatch1)
{
//-- Get the keypoints from the good matches
srcPts1.Add(kp1[d.QueryIdx].Pt);
dstPts1.Add(kpCam[d.TrainIdx].Pt);
//Debug.Log("kp1[d.QueryIdx].Pt: "+kp1[d.QueryIdx].Pt);
}
List <OpenCvSharp.Point2f> srcPts2 = new List <OpenCvSharp.Point2f>();
List <OpenCvSharp.Point2f> dstPts2 = new List <OpenCvSharp.Point2f>();
foreach (OpenCvSharp.DMatch d in goodMatch2)
{
//-- Get the keypoints from the good matches
srcPts2.Add(kp2[d.QueryIdx].Pt);
dstPts2.Add(kpCam[d.TrainIdx].Pt);
//Debug.Log("kp1[d.QueryIdx].Pt: "+kp1[d.QueryIdx].Pt);
}
/*List<OpenCvSharp.Point2f> srcPts3 = new List<OpenCvSharp.Point2f>();
* List<OpenCvSharp.Point2f> dstPts3 = new List<OpenCvSharp.Point2f>();
* foreach (OpenCvSharp.DMatch d in goodMatch3){
* //-- Get the keypoints from the good matches
* srcPts3.Add(kp3[d.QueryIdx].Pt);
* dstPts3.Add(kpCam[d.TrainIdx].Pt);
* //Debug.Log("kp1[d.QueryIdx].Pt: "+kp1[d.QueryIdx].Pt);
* }*/
//jump to next iteration if less than certain number of keypoints matched
if (srcPts1.Count < 200 && srcPts2.Count < 200)
{
yield break;
}
if (srcPts1.Count >= srcPts2.Count)
{
srcPts = new List <OpenCvSharp.Point2f>(srcPts1);
dstPts = new List <OpenCvSharp.Point2f>(dstPts1);
text1.enabled = true;
text2.enabled = false;
num1++;
//text3.enabled = false;
}
/*else if(srcPts2.Count >= srcPts1.Count && srcPts2.Count >= srcPts3.Count){
* srcPts = new List<OpenCvSharp.Point2f>(srcPts2);
* dstPts = new List<OpenCvSharp.Point2f>(dstPts2);
* text2.enabled = true;
* text1.enabled = false;
* text3.enabled = false;
* }*/
else
{
srcPts = new List <OpenCvSharp.Point2f>(srcPts2);
dstPts = new List <OpenCvSharp.Point2f>(dstPts2);
text2.enabled = true;
text1.enabled = false;
num2++;
//text2.enabled = false;
}
if (num1 > num2 + 10)
{
text1.enabled = true;
text2.enabled = false;
}
if (num2 > num1 + 10)
{
text2.enabled = true;
text1.enabled = false;
}
if (num1 > 60 || num2 > 60)
{
num1 = 0;
num2 = 0;
}
//OpenCvSharp.Mat mat2 = mat;
//Cv2.DrawKeypoints(mat, kpCam, mat2);
//Cv2.ImShow("img", mat); 亂碼圖
//Texture2D tex2 = new Texture2D(8, 8);
//tex2 = Unity.MatToTexture(mat);
//rawImageRI.texture = tex2;
//myCam.Pause();
//Cv2.ImShow("img", mat2); 亂碼圖
Texture2D emptyTex = new Texture2D(8, 8);
OpenCvSharp.Mat outputImg = Unity.TextureToMat(emptyTex);
//Debug.Log("outputImg: "+outputImg.ToString());
InputArray srcArr = InputArray.Create <OpenCvSharp.Point2f>(srcPts);
InputArray dstArr = InputArray.Create <OpenCvSharp.Point2f>(dstPts);
OutputArray mask = OutputArray.Create(outputImg);
OpenCvSharp.Mat M = Cv2.FindHomography(srcArr, dstArr, HomographyMethods.Ransac, 5, mask);
OpenCVForUnity.Mat transMat = new OpenCVForUnity.Mat(3, 3, CvType.CV_32FC1);
transMat.put(0, 0, M.Get <double>(0, 0), M.Get <double>(0, 1), M.Get <double>(0, 2),
M.Get <double>(1, 0), M.Get <double>(1, 1), M.Get <double>(1, 2),
M.Get <double>(2, 0), M.Get <double>(2, 1), M.Get <double>(2, 2));
//Debug.Log("transMat: "+transMat.dump());
//Debug.Log("mask: "+mask);
//OpenCvSharp.Mat maskMat = mask.GetMat();
//Debug.Log("maskMat: "+maskMat.ToString());
//maskMoB = new OpenCvSharp.MatOfByte(maskMat);
//-- Get the corners from the image_1 ( the object to be "detected" )
/*OpenCvSharp.Point2f[] obj_corners = new OpenCvSharp.Point2f[4];
* obj_corners[0] = new OpenCvSharp.Point2f(0, 0);
* obj_corners[1] = new OpenCvSharp.Point2f(inputTex.width, 0);
* obj_corners[2] = new OpenCvSharp.Point2f(inputTex.width, inputTex.height);
* obj_corners[3] = new OpenCvSharp.Point2f(0, inputTex.height);
*
* //OpenCvSharp.Point2f[] scene_corners = new OpenCvSharp.Point2f[4];
* //scene_corners = Cv2.PerspectiveTransform(obj_corners, M);
*
* //if (!M) 如果還沒計算出homography M {
* //Cv2.DrawMatches(inputImg, kp1, mat, kpCam, goodMatch, outputImg, OpenCvSharp.Scalar.All(-1),
* //OpenCvSharp.Scalar.All(-1), maskMoB.ToArray(), DrawMatchesFlags.NotDrawSinglePoints);
* //else {
*
* //Texture2D outputTex = Unity.MatToTexture(outputImg);
* //rawImageRI.texture = outputTex;
*
* //-- Draw lines between the corners (the mapped object in the scene - image_2 )
* //Cv2.Line(outputImg, scene_corners[0] + obj_corners[1], scene_corners[1] + obj_corners[1], OpenCvSharp.Scalar.LightBlue, 4);
* //Cv2.Line(outputImg, scene_corners[1] + obj_corners[1], scene_corners[2] + obj_corners[1], OpenCvSharp.Scalar.LightBlue, 4);
* //Cv2.Line(outputImg, scene_corners[2] + obj_corners[1], scene_corners[3] + obj_corners[1], OpenCvSharp.Scalar.LightBlue, 4);
* //Cv2.Line(outputImg, scene_corners[3] + obj_corners[1], scene_corners[0] + obj_corners[1], OpenCvSharp.Scalar.LightBlue, 4);
*
* //OpenCvSharp.Mat outimg = Unity.TextureToMat(emptyTex);
* //inputImg = Unity.TextureToMat(emptyTex);
* //Cv2.DrawKeypoints(mat, kpCam, outimg, OpenCvSharp.Scalar.LightBlue);
*
* //show image with text after homography
* /*string imgPath2 = "../signboard-rectangle/test-IMG_0204-text.PNG";
* textTex = new Texture2D(2,2);
* byte [] binaryImageData2 = File.ReadAllBytes(imgPath2);
* textTex.LoadImage(binaryImageData2);
* rawImageRI.texture = textTex;*/
/*OpenCVForUnity.Mat inputTextImg = new OpenCVForUnity.Mat(new OpenCVForUnity.Size(textTex.width, textTex.height), CvType.CV_8UC4);
* Utils.texture2DToMat(textTex, inputTextImg);
* OpenCVForUnity.Mat outputTextImg = new OpenCVForUnity.Mat(new OpenCVForUnity.Size(textTex.width, textTex.height), CvType.CV_8UC4);
*
* Imgproc.warpPerspective(inputTextImg, outputTextImg, transMat, new OpenCVForUnity.Size(textTex.width, textTex.height));
*
* Texture2D outputTex = new Texture2D((int)textTex.width, (int)textTex.height, TextureFormat.RGB24, false);
* Utils.matToTexture2D(outputTextImg, outputTex);*/
//TextureScale.Bilinear(outputTex, outputTex.width/5, outputTex.height/5);
//rawImageRI.texture = outputTex;
//text.enabled = true;
/*Vector3 scale;
* scale.x = new Vector4((float)M.Get<double>(0,0), (float)M.Get<double>(1,0), (float)M.Get<double>(2,0), 0).magnitude;
* scale.y = new Vector4((float)M.Get<double>(0,1), (float)M.Get<double>(1,1), (float)M.Get<double>(2,1), 0).magnitude;
* scale.z = new Vector4((float)M.Get<double>(0,2), (float)M.Get<double>(1,2), (float)M.Get<double>(2,2), 0).magnitude;
*
* Vector3 forward;
* forward.x = (float)M.Get<double>(0,2);
* forward.y = (float)M.Get<double>(1,2);
* forward.z = (float)M.Get<double>(2,2);
*
* Vector3 upwards;
* upwards.x = (float)M.Get<double>(0,1);
* upwards.y = (float)M.Get<double>(1,1);
* upwards.z = (float)M.Get<double>(2,1);
*
* //textRT.localScale = scale;
* //textRT.rotation = Quaternion.LookRotation(forward, upwards);*/
Matrix4x4 matrix = new Matrix4x4();
/*matrix.SetRow(0, new Vector4((float)M.Get<double>(0,0), (float)M.Get<double>(0,1), (float)M.Get<double>(0,2),0));
* matrix.SetRow(1, new Vector4((float)M.Get<double>(1,0), (float)M.Get<double>(1,1), (float)M.Get<double>(1,2),0));
* matrix.SetRow(2, new Vector4(0,0,1,0));
* matrix.SetRow(3, new Vector4(0,0,0,1));*/
//inverse效果還行
matrix.SetRow(0, new Vector4((float)M.Get <double>(0, 0), (float)M.Get <double>(0, 1), 0, (float)M.Get <double>(0, 2)));
matrix.SetRow(1, new Vector4((float)M.Get <double>(1, 0), (float)M.Get <double>(1, 1), 0, (float)M.Get <double>(1, 2)));
matrix.SetRow(2, new Vector4(0, 0, 1, 0));
matrix.SetRow(3, new Vector4(0, 0, 0, 1));
Matrix4x4 inverse = matrix.inverse;
//textRT.localScale = matrix.lossyScale;
//textRT.rotation = matrix.rotation; //rotation跟eulerangles效果一樣
textRT1.rotation = inverse.rotation;
textRT2.rotation = inverse.rotation;
//textRT3.rotation = inverse.rotation;
Destroy(emptyTex);
//calculate euler angle
/*double angleX = Math.Asin(-M.Get<double>(2,1));
* double angleY = Math.Atan2(M.Get<double>(2,0), M.Get<double>(2,2));
* double angleZ = Math.Atan2(M.Get<double>(0,1), M.Get<double>(1,1));
* //textRT.eulerAngles = new Vector3((float)angleX, (float)angleY, (float)angleZ);
* //Debug.Log("textRT.eulerAngles: "+textRT.eulerAngles.ToString());
*
* //calculate quaternion
* double w = Math.Sqrt(1 + M.Get<double>(0,0) + M.Get<double>(1,1) + M.Get<double>(2,2))/2;
* double w4 = w*4;
* double qx = (M.Get<double>(2,1) - M.Get<double>(1,2))/w4 ;
* double qy = (M.Get<double>(0,2) - M.Get<double>(2,0))/w4 ;
* double qz = (M.Get<double>(1,0) - M.Get<double>(0,1))/w4 ;
* //textRT.rotation = new Quaternion((float)qx, (float)qy, (float)qz, 1);
*
* double tr = M.Get<double>(0,0) + M.Get<double>(1,1) + M.Get<double>(2,2);
* Debug.Log("tr: "+tr);*/
//Cv2.ImShow("img", mat);
//myCam.Pause();
}
/// <summary>
/// Classical Multidimensional Scaling
/// </summary>
public void Run()
{
// creates distance matrix
int size = CityDistance.GetLength(0);
Mat t = new Mat(size, size, MatType.CV_64FC1, CityDistance);
// adds Torgerson's additive constant to t
double torgarson = Torgerson(t);
t += torgarson;
// squares all elements of t
t = t.Mul(t);
// centering matrix G
Mat g = CenteringMatrix(size);
// calculates inner product matrix B
Mat b = g * t * g.T() * -0.5;
// calculates eigenvalues and eigenvectors of B
Mat values = new Mat();
Mat vectors = new Mat();
Cv2.Eigen(b, values, vectors);
for (int r = 0; r < values.Rows; r++)
{
if (values.Get<double>(r) < 0)
values.Set<double>(r, 0);
}
//Console.WriteLine(values.Dump());
// multiplies sqrt(eigenvalue) by eigenvector
Mat result = vectors.RowRange(0, 2);
{
var at = result.GetGenericIndexer<double>();
for (int r = 0; r < result.Rows; r++)
{
for (int c = 0; c < result.Cols; c++)
{
at[r, c] *= Math.Sqrt(values.Get<double>(r));
}
}
}
// scaling
Cv2.Normalize(result, result, 0, 800, NormTypes.MinMax);
// opens a window
using (Mat img = Mat.Zeros(600, 800, MatType.CV_8UC3))
using (Window window = new Window("City Location Estimation"))
{
var at = result.GetGenericIndexer<double>();
for (int c = 0; c < size; c++)
{
double x = at[0, c];
double y = at[1, c];
x = x * 0.7 + img.Width * 0.1;
y = y * 0.7 + img.Height * 0.1;
img.Circle((int)x, (int)y, 5, Scalar.Red, -1);
Point textPos = new Point(x + 5, y + 10);
img.PutText(CityNames[c], textPos, HersheyFonts.HersheySimplex, 0.5, Scalar.White);
}
window.Image = img;
Cv2.WaitKey();
}
}
