private static void FileStorageTest()
{
const string fileName = "foo.yml";
using (var fs = new FileStorage(fileName, FileStorageMode.Write | FileStorageMode.FormatYaml))
{
fs.Write("int", 123);
fs.Write("double", Math.PI);
using (var tempMat = new Mat("data/lenna.png"))
{
fs.Write("mat", tempMat);
}
}
using (var fs = new FileStorage(fileName, FileStorageMode.Read))
{
Console.WriteLine("int: {0}", fs["int"].ReadInt());
Console.WriteLine("double: {0}", (double)fs["double"]);
using (var window = new Window("mat"))
{
window.ShowImage(fs["mat"].ReadMat());
Cv2.WaitKey();
}
}
}
private static void BForceMatcherSample()
{
var src1 = new Mat("data/match1.png");
var src2 = new Mat("data/match2.png");
var gray1 = new Mat();
var gray2 = new Mat();
Cv2.CvtColor(src1, gray1, ColorConversion.BgrToGray);
Cv2.CvtColor(src2, gray2, ColorConversion.BgrToGray);
var fast = new FastFeatureDetector(10);
var descriptorExtractor = new BriefDescriptorExtractor(32);
var descriptors1 = new Mat();
var descriptors2 = new Mat();
KeyPoint[] keypoints1 = fast.Run(gray1, null);
descriptorExtractor.Compute(gray1, ref keypoints1, descriptors1);
KeyPoint[] keypoints2 = fast.Run(gray2, null);
descriptorExtractor.Compute(gray2, ref keypoints2, descriptors2);
// Match descriptor vectors
var bfMatcher = new BFMatcher(NormType.L2, false);
DMatch[][] bfMatches = bfMatcher.KnnMatch(descriptors1, descriptors2, 3, null, false);
bfMatches.ToString();
var view = new Mat();
Cv2.DrawMatches(src1, keypoints1, src2, keypoints2, bfMatches, view);
Window.ShowImages(view);
}
private static void CaptureTest()
{
var capture = new VideoCapture(@"C:\a.wmv");
if (!capture.IsOpened())
{
throw new Exception("Video can`t be played");
}
int sleepTime = (int)Math.Round(1000 / capture.Fps);
using (var window = new Window("capture"))
{
var trackbar = window.CreateTrackbar2("Position", 0, capture.FrameCount,
(int pos, object userdata) =>
{
capture.PosFrames = pos;
}, null);
// Frame image buffer
Mat image = new Mat();
// When the movie playback reaches end, Mat.data becomes NULL.
while (capture.Read(image))
{
trackbar.Pos = capture.PosFrames;
window.ShowImage(image);
Cv2.WaitKey(sleepTime);
}
}
}
private static void VideoCaptureSample()
{
var cap = new VideoCapture(0);
if (!cap.IsOpened())
{
Console.WriteLine("Can't use camera.");
return;
}
var frame = new Mat();
cap.Read(frame);
Window.ShowImages(frame);
frame.ToString();
}
private static void ChamferMatchingSample()
{
using (var img = new Mat("data/lenna.png", LoadMode.GrayScale))
using (var templ = new Mat("data/lennas_eye.png", LoadMode.GrayScale))
{
Point[][] points;
float[] cost;
using (var imgEdge = img.Canny(50, 200))
using (var templEdge = templ.Canny(50, 200))
{
imgEdge.SaveImage("e1.png");
templEdge.SaveImage("e2.png");
var ret = Cv2.ChamferMatching(imgEdge, templEdge, out points, out cost);
int i = 0;
Console.WriteLine(ret);
Console.WriteLine(points.Count());
using (var img3 = img.CvtColor(ColorConversion.GrayToRgb))
{
foreach (var point in points)
{
foreach (var point1 in point)
{
Vec3b c = new Vec3b(0, 255, 0);
img3.Set <Vec3b>(point1.Y, point1.X, c);
}
Console.WriteLine(cost[i]);
i++;
}
foreach (var point1 in points[0])
{
Vec3b c = new Vec3b(255, 0, 255);
img3.Set <Vec3b>(point1.Y, point1.X, c);
}
Window.ShowImages(img3);
img3.SaveImage("final.png");
}
}
}
}
private static void Stitching(Mat[] images)
{
var stitcher = Stitcher.CreateDefault(false);
Mat pano = new Mat();
Console.Write("Stitching 処理開始...");
var status = stitcher.Stitch(images, pano);
Console.WriteLine(" 完了 {0}", status);
pano.SaveImage(@"C:\temp\pano.png");
Window.ShowImages(pano);
foreach (Mat image in images)
{
image.Dispose();
}
}
private static void Clahe()
{
Mat src = new Mat("data/tsukuba_left.png", LoadMode.GrayScale);
Mat dst20 = new Mat();
Mat dst40 = new Mat();
Mat dst44 = new Mat();
using (CLAHE clahe = Cv2.CreateCLAHE())
{
clahe.ClipLimit = 20;
clahe.Apply(src, dst20);
clahe.ClipLimit = 40;
clahe.Apply(src, dst40);
clahe.TilesGridSize = new Size(4, 4);
clahe.Apply(src, dst44);
}
Window.ShowImages(src, dst20, dst40, dst44);
}
private static void Surf(IplImage img1, IplImage img2)
{
Mat src = new Mat(img1, true);
Mat src2 = new Mat(img2, true);
//Detect the keypoints and generate their descriptors using SURF
SURF surf = new SURF(500, 4, 2, true);
KeyPoint[] keypoints1, keypoints2;
MatOfFloat descriptors1 = new MatOfFloat();
MatOfFloat descriptors2 = new MatOfFloat();
surf.Run(src, null, out keypoints1, descriptors1);
surf.Run(src2, 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);//例外が発生する箇所
Mat view = new Mat();
Cv2.DrawMatches(src, keypoints1, src2, keypoints2, matches, view);
Window.ShowImages(view);
}
