private void MatchBySift(Mat src1, Mat src2)
{
var gray1 = new Mat();
var gray2 = new Mat();
Cv2.CvtColor(src1, gray1, ColorConversion.BgrToGray);
Cv2.CvtColor(src2, gray2, ColorConversion.BgrToGray);
var sift = new SIFT();
// Detect the keypoints and generate their descriptors using SIFT
KeyPoint[] keypoints1, keypoints2;
var descriptors1 = new MatOfFloat();
var descriptors2 = new MatOfFloat();
sift.Run(gray1, null, out keypoints1, descriptors1);
sift.Run(gray2, null, out keypoints2, descriptors2);
// Match descriptor vectors
var bfMatcher = new BFMatcher(NormType.L2, false);
var flannMatcher = new FlannBasedMatcher();
DMatch[] bfMatches = bfMatcher.Match(descriptors1, descriptors2);
DMatch[] flannMatches = flannMatcher.Match(descriptors1, descriptors2);
// Draw matches
var bfView = new Mat();
Cv2.DrawMatches(gray1, keypoints1, gray2, keypoints2, bfMatches, bfView);
var flannView = new Mat();
Cv2.DrawMatches(gray1, keypoints1, gray2, keypoints2, flannMatches, flannView);
using (new Window("SIFT matching (by BFMather)", WindowMode.AutoSize, bfView))
using (new Window("SIFT matching (by FlannBasedMatcher)", WindowMode.AutoSize, flannView))
{
Cv2.WaitKey();
}
}
private void MatchBySift(Mat src1, Mat src2)
{
Mat gray1 = new Mat();
Mat gray2 = new Mat();
Cv2.CvtColor(src1, gray1, ColorConversion.BgrToGray);
Cv2.CvtColor(src2, gray2, ColorConversion.BgrToGray);
SIFT sift = new SIFT();
// Detect the keypoints and generate their descriptors using SIFT
KeyPoint[] keypoints1, keypoints2;
MatOfFloat descriptors1 = new MatOfFloat();
MatOfFloat descriptors2 = new MatOfFloat();
sift.Run(gray1, null, out keypoints1, descriptors1);
sift.Run(gray2, null, out keypoints2, descriptors2);
// Matching descriptor vectors with a brute force matcher
BFMatcher matcher = new BFMatcher(NormType.L2, false);
DMatch[] matches = matcher.Match(descriptors1, descriptors2);
// Draw matches
Mat view = new Mat();
Cv2.DrawMatches(gray1, keypoints1, gray2, keypoints2, matches, view);
using (new Window("SIFT matching", WindowMode.AutoSize, view))
{
Cv2.WaitKey();
}
}
public void GetData()
{
var imPath = "D:\\PATHTOIMAGE\\Original.jpg";
var image = Cv2.ImRead(imPath);
var sift = new SIFT(100);
KeyPoint[] keypoints;
MatOfFloat descriptors = new MatOfFloat();
sift.Run(image, null, out keypoints, descriptors);
}
private static void Run()
{
var dm = DescriptorMatcher.Create("BruteForce");
dm.Clear();
string[] algoNames = Algorithm.GetList();
Console.WriteLine(String.Join("\n", algoNames));
SIFT al1 = new SIFT();
string[] ppp = al1.GetParams();
Console.WriteLine(ppp);
var t = al1.ParamType("contrastThreshold");
double d = al1.GetDouble("contrastThreshold");
t.ToString();
d.ToString();
var src = new Mat("data/lenna.png");
var rand = new Random();
var memory = new List<long>(100);
var a1 = new Mat(src, Rect.FromLTRB(0, 0, 30, 40));
var a2 = new Mat(src, Rect.FromLTRB(0, 0, 30, 40));
var a3 = new Mat(src, Rect.FromLTRB(0, 0, 30, 40));
a3.ToString();
for (long i = 0; ; i++)
{
for (int j = 0; j < 200; j++)
{
int c1 = rand.Next(100, 400);
int c2 = rand.Next(100, 400);
Mat temp = src.Row[c1];
src.Row[c1] = src.Row[c2];
src.Row[c2] = temp;
}
memory.Add(MyProcess.WorkingSet64);
if (memory.Count >= 100)
{
double average = memory.Average();
Console.WriteLine("{0:F3}MB", average / 1024.0 / 1024.0);
memory.Clear();
GC.Collect();
}
}
}
