public void UseRansacAlgorithm(int iterationsCount = 1000, float r = 5, float R = 700, bool secondError = true)
{
var min = GetMinSide();
r = min * 0.05f;
R = min * 0.3f;
RansacTriangle = Ransac.RansacAlgorithm(ConsistencyNeighbourPairs, iterationsCount, r, R, secondError);
RansacFilterNeighbourPairs = Ransac.RansacFilterKeyPoint(ConsistencyNeighbourPairs, RansacTriangle, R);
}
static void Main(string[] args)
{
RansacSettings = new Ransac[40];
int IterateAmount = 700;
//iterate through all settings
for (int i = 0; i < RansacSettings.Length; i++)
{
int k;
if (i < 20)
{
k = 500;
}
else
{
k = 1000;
}
int x, y;
if ((i % 20) < 5)
{
x = 600; y = 600;
}
else if ((i % 20) < 10)
{
x = 900; y = 400;
}
else if ((i % 20) < 15)
{
x = 1200; y = 300;
}
else
{
x = 1500; y = 240;
}
int b = i % 5;
Console.WriteLine(System.DateTime.Now + " - Setting " + i + ", k=" + k + ", b=" + b + ", x=" + x + ", y=" + y);
RansacSettings[i] = new Ransac(k, b, x, y, IterateAmount);
RansacSettings[i].WriteToFile("output" + i + ".txt");
Console.WriteLine(System.DateTime.Now + " - Setting " + i + ", " + RansacSettings[i].ToString());
}
Console.WriteLine(System.DateTime.Now + " - Mission Accompished.");
Console.ReadLine();
}
private void FindPairs()
{
ChangeButtonState();
Pairs = new List <Pair>();
foreach (var p in Pic1Points)
{
var pair = KeyPointService.FindPair(p, Pic2Points);
if (p.Equals(KeyPointService.FindPair(pair, Pic1Points)))
{
Pairs.Add(new Pair()
{
A = p,
B = pair,
});
}
}
if (Pairs.Count < Neighbors)
{
Neighbors = Pairs.Count;
}
Application.Current.Dispatcher.Invoke((Action) delegate { PairsTextBox.Text = Pairs.Count.ToString(); });
Ransac.FindBestModel(Pairs, Iterations, MaxError, Type);
Pairs = Pairs.OrderByDescending(x => x.TransformationScore).ToList();
int counter = 0;
foreach (var p in Pairs)
{
counter++;
KeyPointService.UpdatePairProperties(p, Pairs, Neighbors);
DrawLine(p);
UpdateProgressBar(counter, Pairs.Count);
}
ChangeButtonState();
}
private void button2_Click(object sender, EventArgs e)
{
int maxPoints = Convert.ToInt32(txb_Filter.Text);
string name = PathToWriteImage + "resultPicture.jpg";
Bitmap bmp1 = new Bitmap(PathToReadImage + "bridge1.jpg");
Bitmap bmp2 = new Bitmap(PathToReadImage + "bridge2.jpg");
var descriptorsABlobs = BlobsFinder.FindBlobs(IOHelper.ImageToMat(bmp1), maxPoints);
var descriptorsBBlobs = BlobsFinder.FindBlobs(IOHelper.ImageToMat(bmp2), maxPoints);
var match = DescriptorMatcher.Nndr(descriptorsABlobs, descriptorsBBlobs);
lbl_findPoints1.Text = "Найдено интересных точек(1): " + descriptorsABlobs.Count;
lbl_findPoints2.Text = "Найдено интересных точек(2): " + descriptorsBBlobs.Count;
lbl_PairCount.Text = "Найдено пар точек: " + match.Count;
var(matrixA, matrixB) = Ransac.CalculateTransform(match);
var result = Transformer.Transform(bmp1, bmp2, matrixA, matrixB);
result.Save(name, ImageFormat.Jpeg);
pictureBox1.Image = result;
}
public void Approximate(int topIndention, double sampleShare, double outlierShare, int iterations)
{
Ransac linear = new Ransac(sampleShare, outlierShare, iterations);
List <IntPoint> leftPoints = new List <IntPoint>();
LeftContour.Points.ForEach(point =>
{
if (point.Y >= topIndention)
{
leftPoints.Add(point);
}
});
List <IntPoint> rightPoints = new List <IntPoint>();
RightContour.Points.ForEach(point =>
{
if (point.Y >= topIndention)
{
rightPoints.Add(point);
}
});
_leftApproximation = linear.Approximate(leftPoints, leftPoints.Count, out _rSquareLeft, out _relativeEstimationLeft);
_rightApproximation = linear.Approximate(rightPoints, rightPoints.Count, out _rSquareRight, out _relativeEstimationRight);
}
static void Main(string[] args)
{
Stopwatch st = new Stopwatch();
#region Develop
ImageUtils imgUtils = new ImageUtils();
KeyPointExtractor myExtrac = new KeyPointExtractor();
ExtractionManager exManager = new ExtractionManager();
myExtrac.ExtractKeyPoints(Const.imagesFolderDirectory + Const.imgName01 + ".png");
myExtrac.ExtractKeyPoints(Const.imagesFolderDirectory + Const.imgName02 + ".png");
PictureKeyPoints pkp01 = new PictureKeyPoints(Const.imgName01);
PictureKeyPoints pkp02 = new PictureKeyPoints(Const.imgName02);
LetDraw ld = new LetDraw();
pkp01.KeyPoints = exManager.ExtractKeyPointsFromImages(pkp01.GetImagePath());
pkp02.KeyPoints = exManager.ExtractKeyPointsFromImages(pkp02.GetImagePath());
KeyPointPairsFinder kppf = new KeyPointPairsFinder(pkp01, pkp02);
//foreach (KeyPoint kp in pkp01.KeyPoints)
//{
// Console.WriteLine("Picture One key points: \n");
// Console.WriteLine(kp);
//}
Console.WriteLine("Start searching neighbours");
st.Start();
//Dictionary<KeyPoint, KeyPoint> neighbors = exManager.FindNeighbers(pkp01.KeyPoints, pkp02.KeyPoints); //WHY DICTIONARY NOT WORK ?
List <KeyValuePair <KeyPoint, KeyPoint> > neighbors = kppf.FindKeyPointsPairs();
st.Stop();
Console.WriteLine("Neighbors Count: " + neighbors.Count + "\nin time: " + st.ElapsedMilliseconds.ToString());
//ld.MergeImagesAndDrawLines(neighbors);
/*
* st.Reset();
* st.Start();
* NeighbourhoodCoherenceFilter neighbourhoodCoherenceFilter = new NeighbourhoodCoherenceFilter(neighbors, Const.neighborsToCheck, Const.neighborsCondition);
* List<KeyValuePair<KeyPoint, KeyPoint>> filteredPairs = neighbourhoodCoherenceFilter.GetFilteredPairs();
* st.Stop();
* Console.WriteLine("AFTER FILTER");
* Console.WriteLine("pairs Count: " + filteredPairs.Count + "\nin time: " + st.ElapsedMilliseconds.ToString());
* //ld.MergeImagesAndDrawLines(filteredPairs);
*/
Console.WriteLine("RANSAC IN PROGRESS");
st.Reset();
st.Start();
//ITransform transform = new AffineTransform();
ITransform transform = new PerspectiveTransform();
Ransac ransac = new Ransac(Const.iterationNumber, transform, Const.maxError);
TransformFilter transformFilter = new TransformFilter(ransac);
List <KeyValuePair <KeyPoint, KeyPoint> > ransacPairs = transformFilter.Filter(neighbors);
st.Stop();
Console.WriteLine("AFTER RANSCAC");
Console.WriteLine("pairs Count: " + ransacPairs.Count + "\nin time: " + st.ElapsedMilliseconds.ToString());
ld.MergeImagesAndDrawLines(ransacPairs);
Console.ReadKey();
#endregion
//ConsoleInterface cI = new ConsoleInterface();
}
/// <summary>
/// Find laser-plane through RANSAC
/// </summary>
/// <param name="context">Context</param>
/// <param name="plane">Found plane</param>
/// <returns>Success</returns>
public bool FindLaserPlane(Bundle bundle) {
BundleBookmarks b = new BundleBookmarks(bundle);
List<System.Drawing.PointF> laser_pixels = b.LaserPixel;
List<Ray> eye_rays = b.EyeRays;
System.Drawing.Rectangle roi = b.ROI;
List<Ray> rays;
if (_only_out_of_roi) {
rays = new List<Ray>();
for (int i = 0; i < laser_pixels.Count; ++i) {
if (!roi.Contains(laser_pixels[i])) {
rays.Add(eye_rays[i]);
}
}
} else {
rays = eye_rays;
}
if (rays.Count == 0) {
return false;
}
Vector[] isect;
double[] ts;
int[] plane_ids;
IList<Plane> reference_planes = b.ReferencePlanes;
Core.Intersection.FindEyeRayPlaneIntersections(
rays.ToArray(),
reference_planes.ToArray(),
out ts, out isect, out plane_ids);
Ransac<PlaneModel> ransac = new Ransac<PlaneModel>(isect);
int min_consensus = (int)Math.Max(rays.Count * _min_consensus_precent, b.Image.Width * 0.05);
_constraint.Bundle = bundle;
Ransac<PlaneModel>.Hypothesis h = ransac.Run(_max_iterations, _plane_accurracy, min_consensus, _constraint);
if (h != null) {
b.LaserPlane = h.Model.Plane;
return true;
} else {
return false;
}
}
