/// <summary>
/// imageの白部分の面積がminArea以上のものだけ反映した画像を返す
/// </summary>
public static Bitmap GetImageOmitMinimumNoize(Bitmap image, int minArea)
{
var mat = Cv2.Split(image.ToMat())[0];
ConnectedComponents cc = Cv2.ConnectedComponentsEx(mat);
//var maxBlob = cc.GetLargestBlob();
//var filtered = new Mat();
//cc.FilterByBlob(mat, filtered, maxBlob);
//Cv2.ImShow("max", filtered);
List <ConnectedComponents.Blob> blobs = new List <ConnectedComponents.Blob>();
for (int i = 0; i < cc.LabelCount; i++)
{
int area = cc.Blobs[i].Area;
if (area >= minArea)
{
blobs.Add(cc.Blobs[i]);
}
}
var filtered = new Mat();
cc.FilterByBlobs(mat, filtered, blobs);
return(new Bitmap(filtered.ToBitmap()));
}
public ContentUserControlViewModel()
{
FilePath = string.Empty;
BrowseCommand = new DelegateCommand(() =>
{
OpenFileDialog dialog = new OpenFileDialog()
{
Multiselect = false,
CheckPathExists = true,
CheckFileExists = true,
Filter = "画像ファイル|*.bmp;*.jpg;*.png",
};
bool?ret = dialog.ShowDialog();
if (ret.HasValue && ret.Value)
{
FilePath = dialog.FileName;
Mat original = Cv2.ImRead(dialog.FileName);
OriginalImage = ToBitmapSource(BitmapConverter.ToBitmap(original));
Mat grayscale = new Mat();
Cv2.CvtColor(original, grayscale, ColorConversionCodes.BGR2GRAY);
Mat binary = new Mat();
Cv2.Threshold(grayscale, binary, 0.0, 255.0, ThresholdTypes.Binary | ThresholdTypes.Otsu);
Mat labels = new Mat();
ConnectedComponents components = Cv2.ConnectedComponentsEx(binary);
Mat segmented = new Mat();
components.RenderBlobs(segmented);
SegmentedImage = ToBitmapSource(BitmapConverter.ToBitmap(segmented));
}
});
System.Diagnostics.Debug.Print(Cv2.GetVersionString());
}
public static int Labling(this WriteableBitmap src)
{
using (Mat mat = new Mat(src.PixelHeight, src.PixelWidth, MatType.CV_8UC3))
{
src.ToMat(mat);
Mat gray = mat.CvtColor(ColorConversionCodes.BGR2GRAY);
//Cv2.NamedWindow("image", WindowMode.Normal);
//Cv2.ImShow("image", mat);
Mat binary = gray.Threshold(0, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
//Cv2.NamedWindow("image", WindowMode.Normal);
//Cv2.ImShow("image", binary);
//Cv2.WaitKey();
//Cv2.DestroyWindow("image");
ConnectedComponents cc = Cv2.ConnectedComponentsEx(binary);
int c = 0;
foreach (var i in cc.Blobs)
{
c += i.Area > 3 ? 1 : 0;
}
return(c);
}
}
private static void Blob()
{
Mat src = new Mat("data/shapes.png", ImreadModes.Color);
Mat gray = src.CvtColor(ColorConversionCodes.BGR2GRAY);
Mat binary = gray.Threshold(0, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
Mat labelView = new Mat();
Mat rectView = binary.CvtColor(ColorConversionCodes.GRAY2BGR);
ConnectedComponents cc = Cv2.ConnectedComponentsEx(binary);
if (cc.LabelCount <= 1)
{
return;
}
// draw labels
/*
* Scalar[] colors = cc.Blobs.Select(_ => Scalar.RandomColor()).ToArray();
* int height = cc.Labels.GetLength(0);
* int width = cc.Labels.GetLength(1);
* var labelViewIndexer = labelView.GetGenericIndexer<Vec3b>();
* for (int y = 0; y < height; y++)
* {
* for (int x = 0; x < width; x++)
* {
* int labelValue = cc.Labels[y, x];
* labelViewIndexer[y, x] = colors[labelValue].ToVec3b();
* }
* }
*/
cc.RenderBlobs(labelView);
// draw bonding boxes except background
foreach (var blob in cc.Blobs.Skip(1))
{
rectView.Rectangle(blob.Rect, Scalar.Red);
}
// filter maximum blob
ConnectedComponents.Blob maxBlob = cc.GetLargestBlob();
//cc.Blobs.Skip(1).OrderByDescending(b => b.Area).First();
Mat filtered = new Mat();
cc.FilterByBlob(src, filtered, maxBlob);
using (new Window("src", src))
using (new Window("binary", binary))
using (new Window("labels", labelView))
using (new Window("bonding boxes", rectView))
using (new Window("maximum blob", filtered))
{
Cv2.WaitKey();
}
}
public void FilterByLabel()
{
using var src = new Mat(100, 100, MatType.CV_8UC1, Scalar.Black);
Cv2.Rectangle(src, new Rect(10, 20, 10, 20), Scalar.White, -1);
Cv2.Rectangle(src, new Rect(50, 60, 20, 30), Scalar.White, -1); // greater
var cc = Cv2.ConnectedComponentsEx(src, PixelConnectivity.Connectivity8, ConnectedComponentsAlgorithmsTypes.Default);
using var dst = new Mat();
cc.FilterByLabel(src, dst, 1);
using var expected = new Mat(100, 100, MatType.CV_8UC1, Scalar.Black);
Cv2.Rectangle(expected, new Rect(10, 20, 10, 20), Scalar.White, -1);
ShowImagesWhenDebugMode(src, dst, expected);
ImageEquals(dst, expected);
}
public void Run(PixelConnectivity connectivity, ConnectedComponentsAlgorithmsTypes algorithmType)
{
using var src = Image("alphabet.png", ImreadModes.Grayscale);
using var binary = new Mat();
Cv2.Threshold(src, binary, 128, 255, ThresholdTypes.BinaryInv);
ShowImagesWhenDebugMode(src, binary);
var cc = Cv2.ConnectedComponentsEx(binary, connectivity, algorithmType);
Assert.Equal(27, cc.LabelCount);
Assert.NotEmpty(cc.Labels.GetBuffer());
Assert.Equal(src.Rows, cc.Labels.GetLength(0));
Assert.Equal(src.Cols, cc.Labels.GetLength(1));
using var render = new Mat();
cc.RenderBlobs(render);
ShowImagesWhenDebugMode(render);
}
public void Run()
{
Mat src = new Mat(FilePath.Image.Shapes, ImreadModes.Color);
Mat gray = src.CvtColor(ColorConversionCodes.BGR2GRAY);
Mat binary = gray.Threshold(0, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
Mat labelView = src.EmptyClone();
Mat rectView = binary.CvtColor(ColorConversionCodes.GRAY2BGR);
ConnectedComponents cc = Cv2.ConnectedComponentsEx(binary);
if (cc.LabelCount <= 1)
{
return;
}
// draw labels
cc.RenderBlobs(labelView);
// draw bonding boxes except background
foreach (var blob in cc.Blobs.Skip(1))
{
rectView.Rectangle(blob.Rect, Scalar.Red);
}
// filter maximum blob
var maxBlob = cc.GetLargestBlob();
var filtered = new Mat();
cc.FilterByBlob(src, filtered, maxBlob);
//using (new Window("src", src))
//using (new Window("binary", binary))
//using (new Window("labels", labelView))
//using (new Window("bonding boxes", rectView))
//using (new Window("maximum blob", filtered))
//{
// Cv2.WaitKey();
//}
src.SaveImage("src.png");
binary.SaveImage("binary.png");
labelView.SaveImage("labels.png");
rectView.SaveImage("boxes.png");
filtered.SaveImage("maximumblob.png");
}
public void GetLargestBlob()
{
using var src = new Mat(100, 100, MatType.CV_8UC1, Scalar.Black);
Cv2.Rectangle(src, new Rect(10, 20, 10, 20), Scalar.White, -1);
Cv2.Rectangle(src, new Rect(50, 60, 20, 30), Scalar.White, -1); // greater
ShowImagesWhenDebugMode(src);
var cc = Cv2.ConnectedComponentsEx(src, PixelConnectivity.Connectivity8, ConnectedComponentsAlgorithmsTypes.Default);
var largestBlob = cc.GetLargestBlob();
Assert.Equal(50, largestBlob.Left);
Assert.Equal(60, largestBlob.Top);
Assert.Equal(20, largestBlob.Width);
Assert.Equal(30, largestBlob.Height);
Assert.Equal(new Rect(50, 60, 20, 30), largestBlob.Rect);
Assert.Equal(20 * 30, largestBlob.Area);
Assert.Equal(new Point2d(59.5, 74.5), largestBlob.Centroid);
}
public int GetBlobs(Mat img, bool showImage = false)
{
Mat gray = img.CvtColor(ColorConversionCodes.BGR2GRAY);
//Mat binary = gray.Threshold(0, 255, ThresholdTypes.Otsu | ThresholdTypes.Binary);
Mat binary = gray.Threshold(50, 255, ThresholdTypes.Binary);
//2.Define/search ROI area
Mat labelView = img.EmptyClone();
Mat rectView = binary.CvtColor(ColorConversionCodes.GRAY2BGR);
ConnectedComponents cc = Cv2.ConnectedComponentsEx(binary);
if (cc.LabelCount <= 1)
{
throw new Exception("no blob found");
}
//draw lables
cc.RenderBlobs(labelView);
//draw boxes except background
foreach (var blob in cc.Blobs.Skip(1))
{
rectView.Rectangle(blob.Rect, Scalar.Red);
}
if (showImage == true)
{
using (new Window("blob image", rectView))
//using (new Window("labelview image", labelView))
{
//Cv2.WaitKey(1000);
Cv2.WaitKey(0);
Cv2.DestroyWindow("blob image");
//Cv2.DestroyWindow("labelview image");
}
}
return(cc.LabelCount - 1);
}
/// <summary>
/// 処理実行
/// </summary>
public ImageProcessValue Execute(SettingsObj obj)
{
try
{
// webカメラキャプチャ
var camera = new OpenCvSharp.VideoCapture(0)
{
//// 解像度の指定
FrameWidth = 1920,
FrameHeight = 1080
};
using (camera)
{
// カメラ内部パラメータ格納用
Mat mtx = new Mat();
Mat dist = new Mat();
// ymlファイルを読み来み計算パラメータを取得
using (var fs = new FileStorage(obj.CalibratinFilePath, FileStorage.Mode.Read))
{
mtx = fs["mtx"].ReadMat();
dist = fs["dist"].ReadMat();
}
var src = new Mat();
// 撮影画像の読み取り
camera.Read(src);
if (src.Empty())
{
return(null);
}
Mat calib = new Mat();
// 歪み補正
Cv2.Undistort(src, calib, mtx, dist);
// 画像処理
var tmp = new Mat();
// OpenCVのカラーの並びに変換
Cv2.CvtColor(calib, tmp, OpenCvSharp.ColorConversionCodes.RGB2BGR);
// BGR画像をHSV画像に変換
var hsv = new Mat();
Cv2.CvtColor(tmp, hsv, OpenCvSharp.ColorConversionCodes.BGR2HSV);
// inRange関数で範囲指定２値化 -> マスク画像として使う
var msk = new Mat();
Cv2.InRange(hsv, new Scalar(obj.HueMin, obj.SaturationMin, obj.ValueMin), new Scalar(obj.HueMax, obj.SaturationMax, obj.ValueMax), msk);
// bitwise_andで元画像にマスクをかける -> マスクされた部分の色だけ残る
var msk_src = new Mat();
Cv2.BitwiseAnd(hsv, hsv, msk_src, msk);
var show_msk = new Mat();
// 元の色に戻す
Cv2.CvtColor(msk_src, show_msk, ColorConversionCodes.HSV2BGR);
// グレースケール変換
var gray = new Mat();
Cv2.CvtColor(show_msk, gray, ColorConversionCodes.BGR2GRAY);
// 2値化
var th = new Mat();
Cv2.Threshold(gray, th, 130, 255, ThresholdTypes.Otsu);
// ブロブとラベリング
var label = new Mat();
var stats = new Mat();
var centroids = new Mat();
ConnectedComponents cc = Cv2.ConnectedComponentsEx(th);
if (cc.LabelCount <= 1)
{
return(null);
}
// draw labels
//cc.RenderBlobs(show_msk);
// draw bonding boxes except background
foreach (var blob in cc.Blobs.Skip(1))
{
show_msk.Rectangle(blob.Rect, Scalar.Red);
}
// filter maximum blob
var maxBlob = cc.GetLargestBlob();
var filtered = new Mat();
cc.FilterByBlob(show_msk, filtered, maxBlob);
// 矩形探索
// マスク画像から矩形探索
Point[][] contours;
HierarchyIndex[] hierarchy;
Cv2.FindContours(th, out contours, out hierarchy, RetrievalModes.List, ContourApproximationModes.ApproxNone);
// 見つからなかったら何もしない
if (contours.Length == 0)
{
return(null);
}
// 回転を考慮した外接矩形
foreach (var cont in contours)
{
var rect = Cv2.MinAreaRect(cont);
var box = Cv2.BoxPoints(rect).Select(x => (Point)x);
}
Cv2.DrawContours(show_msk, contours, -1, Scalar.Yellow, 3);
//Cv2.ImShow("show_msk", show_msk);
// 画像、画像上の位置発火
var val = new ImageProcessValue();
val.CameraImage = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(show_msk);
val.Blob = maxBlob;
// メモリリーク対策でDispose呼ぶ
mtx.Dispose();
dist.Dispose();
calib.Dispose();
tmp.Dispose();
hsv.Dispose();
msk.Dispose();
msk_src.Dispose();
show_msk.Dispose();
gray.Dispose();
th.Dispose();
label.Dispose();
stats.Dispose();
centroids.Dispose();
filtered.Dispose();
return(val);
}
}
catch (Exception e)
{
throw e;
}
}
