public List <Rectangle> GetAllRects()
{
var list = new List <Rectangle>();
//定位点
list.Add(this.FixedPoint.LeftTop.Outer);
list.Add(this.FixedPoint.LeftTop.Inner);
list.Add(this.FixedPoint.RightTop.Outer);
list.Add(this.FixedPoint.RightTop.Inner);
list.Add(this.FixedPoint.LeftBottom.Outer);
list.Add(this.FixedPoint.LeftBottom.Inner);
list.Add(this.FixedPoint.RightBottom.Outer);
list.Add(this.FixedPoint.RightBottom.Inner);
//偏移块
this.OffsetAreas.ForEach(a =>
{
list.Add(a.Area);
list.AddRange(CVHelper.MoveRects(a.OffsetList, a.Area.X, a.Area.Y));
});
//选项区域
this.OptionAreaList.ForEach(a =>
{
list.Add(a.Area);
foreach (var item in a.Options.Values)
{
list.AddRange(CVHelper.MoveRects(item, a.Area.X, a.Area.Y));
}
});
return(list);
}
private void Btn_regMult_Click(object sender, EventArgs e)
{
CVHelper commonUse = new CVHelper();
foreach (var filePath in this.multSelectPicPathList)
{
try
{
var bitmap = new Bitmap(filePath);
var rectList = commonUse.GetRectListFromBitmap(bitmap, Convert.ToInt32(this.minNum.Value), Convert.ToInt32(this.maxNum.Value), 0, 0, true, 2);
Mat src = new Image <Bgr, byte>(bitmap).Mat;
foreach (var item in rectList)
{
CvInvoke.Rectangle(src, item, new MCvScalar(0, 0, 255));
}
commonUse.SaveMat(src, Path.GetFileName(filePath), false);
this.successNum++;
}
catch (Exception)
{
this.failNum++;
}
finally
{
this.lbl_regResul.Text = this.failNum == 0?"":$"失败数量：{this.failNum}";
this.lbl_picNumInfo.Text = $"选择张数：{this.successNum}/{this.multSelectPicPathList?.Length}";
}
}
}
private void Btn_paintFormRect_Click(object sender, EventArgs e)
{
//for (int i = 0; i < 6; i++)
//{
// Random r = new Random();
// var index= r.Next(0, Form1.OrginalRectList.Count - 1);
// Form1.OrginalRectList.RemoveAt(index);
//}
Console.WriteLine(Form1.OrginalRectList.Count);
//Form1.OrginalRectList.RemoveAt(0);
//Form1.OrginalRectList.RemoveAt(Form1.OrginalRectList.Count - 1);
CVHelper common = new CVHelper();
var tempList = common.FillFull(Form1.OrginalRectList);
//var tempList = Form1.OrginalRectList;
this.picBox.RegionInfo = new RegionInfo(this.picBox.Image.Width, this.picBox.Image.Height, tempList);
Console.WriteLine(tempList.Count);
this.picBox.CurrentSelectedRect = this.picBox.RegionInfo;
//画出
Mat matOrginal = new Image <Bgr, byte>((Bitmap)this.picBox.Image).Mat;
foreach (var item in this.picBox.CurrentSelectedRect.RectList)
{
CvInvoke.Rectangle(matOrginal, Rectangle.Round(item), new MCvScalar(0, 0, 255));
}
CVHelper commonUse = new CVHelper();
commonUse.SaveMat(matOrginal, "获取裁剪图中的所有轮廓边在原始图中ZoomForm");
}
public OffsetArea NewByOffset(int offsetX, int offsetY)
{
return(new OffsetArea(
CVHelper.MoveRect(this.Area, offsetX, offsetY),
this.OffsetList,
this.OffsetType));
}
private void Btn_regWrap_Click(object sender, EventArgs e)
{
//思路：重新调整大小（根据四个定位点），获取扫描结果的定位点，获取答案结果
//重新获取扫描结果的定位点
var leftTopArea = this.OriginalPaper.FixedPoint.LeftTop.GetEnlargeOuter();
var cutBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, leftTopArea.X, leftTopArea.Y, leftTopArea.Width, leftTopArea.Height);
var leftTopInner = common.GetBigRectFromBitmap(cutBitmap, 2000, 6000, leftTopArea.X, leftTopArea.Y);
CalcOffset(this.OriginalPaper.FixedPoint.LeftTop.Inner, leftTopInner, out int offsetX, out int offsetY);
var scanPaper = this.OriginalPaper.NewPaperByOffset(offsetX, offsetY);
var mat = new Image <Bgr, byte>(this.OriginalBitmap).Mat;
//通过透视调整大小
List <PointF> srcPoints = scanPaper.FixedPoint.GetPointsByClockwise();
List <PointF> desPoints = new List <PointF>()
{
CVHelper.PointToPointF(scanPaper.FixedPoint.LeftTop.Inner.Location)
};
//右上
var rightTopArea = scanPaper.FixedPoint.RightTop.Outer;
var rightTopBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, rightTopArea);
var rightTopInner = common.GetBigRectFromBitmap(rightTopBitmap, 2000, 6000, rightTopArea.X, rightTopArea.Y);
desPoints.Add(CVHelper.PointToPointF(rightTopInner.Location));
//右下
var rightBottomArea = scanPaper.FixedPoint.RightBottom.Outer;
var rightBottomBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, rightBottomArea);
var rightBottomInner = common.GetBigRectFromBitmap(rightBottomBitmap, 2000, 6000, rightBottomArea.X, rightBottomArea.Y);
desPoints.Add(CVHelper.PointToPointF(rightBottomInner.Location));
//左下
var leftBottomArea = scanPaper.FixedPoint.LeftBottom.Outer;
var leftBottomBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, leftBottomArea);
var leftBottomInner = common.GetBigRectFromBitmap(leftBottomBitmap, 2000, 6000, leftBottomArea.X, leftBottomArea.Y);
desPoints.Add(CVHelper.PointToPointF(leftBottomInner.Location));
//计算透视矩阵
Mat data = CvInvoke.GetPerspectiveTransform(desPoints.ToArray(), srcPoints.ToArray());
//进行透视操作
//Mat src_gray = new Mat();
Mat mat_Perspective = new Mat();
CvInvoke.WarpPerspective(mat, mat_Perspective, data, this.OriginalBitmap.Size);
//根据偏移块进行调整
scanPaper = CalPaperByOffsetS(scanPaper, mat_Perspective.Bitmap);
PaperRegResultShowForm.DrawPaperRect(mat_Perspective, scanPaper);
this.picSrc.LoadImage(mat_Perspective.Bitmap);
//保存
string calOffsetStr = this.IsCalOffset.Checked ? "并模块偏移" : "";
common.SaveMat(mat_Perspective, $"试卷结果校正透视后{calOffsetStr}在扫描模板中显示");
}
private void Btn_validate2_Click(object sender, EventArgs e)
{
//思路获取偏移量，
List <PointF> srcPoints = this.OriginalPaper.FixedPoint.GetPointsByClockwise();
List <PointF> desPoints = new List <PointF>();
//重新获取扫描结果的全部定位点-》重新调整大小（根据四个定位点透视）
//左上
var leftTopArea = this.OriginalPaper.FixedPoint.LeftTop.GetEnlargeOuter();
var cutBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, leftTopArea.X, leftTopArea.Y, leftTopArea.Width, leftTopArea.Height);
var leftTopInner = common.GetBigRectFromBitmap(cutBitmap, 500, 6000, leftTopArea.X, leftTopArea.Y);
desPoints.Add(leftTopInner.Location);
//右上
var rightTopArea = this.OriginalPaper.FixedPoint.RightTop.GetEnlargeOuter();
var rightTopBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, rightTopArea);
var rightTopInner = common.GetBigRectFromBitmap(rightTopBitmap, 500, 6000, rightTopArea.X, rightTopArea.Y);
desPoints.Add(CVHelper.PointToPointF(rightTopInner.Location));
//右下
var rightBottomArea = this.OriginalPaper.FixedPoint.RightBottom.GetEnlargeOuter();
var rightBottomBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, rightBottomArea);
var rightBottomInner = common.GetBigRectFromBitmap(rightBottomBitmap, 500, 6000, rightBottomArea.X, rightBottomArea.Y);
desPoints.Add(CVHelper.PointToPointF(rightBottomInner.Location));
//左下
var leftBottomArea = this.OriginalPaper.FixedPoint.LeftBottom.GetEnlargeOuter();
var leftBottomBitmap = PictureBoxReadCard.Cut(this.OriginalBitmap, leftBottomArea);
var leftBottomInner = common.GetBigRectFromBitmap(leftBottomBitmap, 500, 6000, leftBottomArea.X, leftBottomArea.Y);
desPoints.Add(CVHelper.PointToPointF(leftBottomInner.Location));
//计算透视矩阵
Mat data = CvInvoke.GetPerspectiveTransform(desPoints.ToArray(), srcPoints.ToArray());
//进行透视操作
var mat = new Image <Bgr, byte>(this.OriginalBitmap).Mat;
Mat mat_Perspective = new Mat();
CvInvoke.WarpPerspective(mat, mat_Perspective, data, this.OriginalBitmap.Size, Inter.Nearest, Warp.Default, BorderType.Constant, new MCvScalar(255, 255, 255));
//根据偏移块进行调整
var paper = CalPaperByOffsetS(this.OriginalPaper, mat_Perspective.Bitmap);
PaperRegResultShowForm.DrawPaperRect(mat_Perspective, paper);
this.picSrc.LoadImage(mat_Perspective.Bitmap);
//保存
string calOffsetStr = this.IsCalOffset.Checked ? "并模块偏移" : "";
common.SaveMat(mat_Perspective, $"试卷结果直接透视后{calOffsetStr}在扫描模板中显示");
}
private void Btn_percentTest_Click(object sender, EventArgs e)
{
CVHelper common = new CVHelper();
Rectangle r1 = new Rectangle(1, 1, 200, 200);
Rectangle r2 = new Rectangle(2, 2, 190, 190);
var percent = common.DecideOverlap(r2, r1, out Rectangle maxRect);
MessageBox.Show(percent.ToString());
}
private void Btn_regBrokenRect_Click(object sender, EventArgs e)
{
//FastDetector
if (this.ib_middleCut.Image == null)
{
MessageBox.Show("裁剪图片不能为空");
return;
}
CVHelper commonUse = new CVHelper();
var rectList = commonUse.GetRectListFromBitmap(this.ib_middleCut.Image.Bitmap, 40, 600, isAutoFillFull: true, optimizeTimes: 2, isBrokenOption: true);
//排序
var rectListDic = commonUse.OrderRectList(rectList);
Mat src = new Image <Bgr, byte>(ib_middleCut.Image.Bitmap).Mat;
foreach (var item in rectList)
{
CvInvoke.Rectangle(src, item, new MCvScalar(0, 0, 255));
}
commonUse.SaveMat(src, "获取裁剪图中的所有轮廓边界提取");
this.ib_middle.Image = src;
//在原始图片中画出矩形框
var orginalRectList = new List <Rectangle>();
foreach (var item in rectList)
{
var tmpRect = new Rectangle(new Point(this.destRect.X + item.X, this.destRect.Y + item.Y), item.Size);
orginalRectList.Add(tmpRect);
}
Mat matOrginal = new Image <Bgr, byte>(this.ib_original.Image.Bitmap).Mat;
foreach (var item in orginalRectList)
{
CvInvoke.Rectangle(matOrginal, Rectangle.Round(item), new MCvScalar(0, 0, 255));
}
commonUse.SaveMat(matOrginal, "获取裁剪图中的所有轮廓边在原始图中");
this.ib_result.Image = matOrginal;
//在原始的PictureBox中画出框
this.DrawRectInPictureBox(this.ib_original, orginalRectList);
//
OrginalRectList = orginalRectList;
CutedRectList = rectList;
}
/// <summary>
///
/// </summary>
/// <param name="rectList">相对图片0,0</param>
/// <param name="area"></param>
/// <returns></returns>
public static List <Rectangle> GetRectsByAreaAndCol(List <Rectangle> rectList, Rectangle area)
{
var list = new List <Rectangle>();
rectList.ForEach(r =>
{
if (r.Y > area.Y && r.Y < area.Y + area.Height)
{
list.Add(CVHelper.MoveRect(r, -area.X, -area.Y));
}
});
return(list);
}
public static List <Rectangle> GetRectsByAreaAndRow(List <Rectangle> rectList, Rectangle area)
{
var list = new List <Rectangle>();
rectList.ForEach(r =>
{
if (r.X > area.X && r.X < area.X + area.Width)
{
list.Add(CVHelper.MoveRect(r, -area.X, -area.Y));
}
});
return(list);
}
private void Btn_answerReg3_Click(object sender, EventArgs e)
{
CVHelper commonUse = new CVHelper();
var src = new Image <Gray, byte>(ib_middleCut.Image.Bitmap);
var thresholdImage = src.CopyBlank();
int myThreshold = 210;
CvInvoke.Threshold(src, thresholdImage, myThreshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
commonUse.SaveMat(thresholdImage.Mat, "二值化后");
//思路 close -腐蚀-腐蚀-膨胀
//形态学膨胀
Mat mat_dilate = commonUse.MyDilate(thresholdImage.Mat, Emgu.CV.CvEnum.MorphOp.Close);
commonUse.SaveMat(mat_dilate, "形态学膨胀");
//mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Close);
//commonUse.SaveMat(mat_dilate, "形态学膨胀1");
mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Erode);
commonUse.SaveMat(mat_dilate, "形态学膨胀腐蚀1");
mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Erode);
commonUse.SaveMat(mat_dilate, "形态学膨胀腐蚀2");
mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Dilate);
commonUse.SaveMat(mat_dilate, "形态学膨胀2");
var image_dilate = mat_dilate.ToImage <Gray, byte>();
List <Rectangle> validRectList = new List <Rectangle>();
CutedRectList.ForEach(rect =>
{
var newRect = new Rectangle(Math.Max(0, rect.X - 8), Math.Max(0, rect.Y - 8), rect.Width, rect.Height);
var tmpImage = image_dilate.Copy(newRect);
var result = GetWhiteColorPercenter(tmpImage);
if (result > 0.2)
{
validRectList.Add(rect);
}
commonUse.SaveMat(tmpImage.Mat, "形态学后" + result);
});
validRectList.ForEach(r =>
{
CvInvoke.Rectangle(src, r, new MCvScalar(0, 0, 255));
});
new CVHelper().SaveMat(src.Mat, "通过比例计算获取的答案");
this.ib_result.Image = src;
}
private void Btn_offset_Click(object sender, EventArgs e)
{
if (ib_original.Image == null)
{
MessageBox.Show("请先加载图片");
return;
}
var cutedBitmap = this.ib_original.GetFirstRegionRect();
if (cutedBitmap == null)
{
MessageBox.Show("将要识别的图片不能为空");
return;
}
CVHelper commonUse = new CVHelper();
var rectList = commonUse.GetRectListFromBitmap(cutedBitmap, Convert.ToInt32(this.minNum.Value), Convert.ToInt32(this.maxNum.Value), 0, 0, false, 0);
//排序
//var rectListDic = commonUse.OrderRectList(rectList);
Mat src = new Image <Bgr, byte>(cutedBitmap).Mat;
foreach (var item in rectList)
{
CvInvoke.Rectangle(src, item, new MCvScalar(0, 0, 255));
}
commonUse.SaveMat(src, "偏移量测试定位点");
this.ib_result.Image = src.Bitmap;
if (rectList?.Count == 0)
{
return;
}
this.Paper.OffsetAreas.Add(new OffsetArea(this.ib_original.RegionInfo.RectList.FirstOrDefault(), rectList, this.ckb_isRow.Checked? OffsetType.Rows: OffsetType.Column));
}
private static bool ValidateColumn(Rectangle area, List <Rectangle> offsetList)
{
/// 偏移量区域，规范，最高线和最低线距离最近的偏移测量点大于1.5个偏移高度
/// 左右距离需要大于0.6个偏移点宽度
bool isValidate = true;
var averageWidth = offsetList.Average(r => r.Width);
var averageHeight = offsetList.Average(r => r.Height);
var maxRect = CVHelper.GetMaxRect(offsetList);
if (averageWidth * 0.6 > maxRect.X || area.Width - averageWidth * 0.6 < maxRect.X + maxRect.Width ||
averageHeight * 1.5 > maxRect.Y || area.Height < maxRect.Y + maxRect.Height + averageHeight * 1.5)
{
return(false);
}
return(isValidate);
}
private static bool ValidateRow(Rectangle area, List <Rectangle> offsetList)
{
//横向的,上下0.4个宽度，左右大于0.8个高度度即可
bool isValidate = true;
var averageWidth = offsetList.Average(r => r.Width);
var averageHeight = offsetList.Average(r => r.Height);
var maxRect = CVHelper.GetMaxRect(offsetList);
if (maxRect.X < 0.4 * averageWidth || maxRect.X + maxRect.Width + 0.4 * averageWidth > area.Width ||
maxRect.Y < 0.8 * averageHeight || maxRect.Y + maxRect.Height + 0.8 * averageHeight > area.Height)
{
return(false);
}
return(isValidate);
}
private void Btn_reg2All_Click(object sender, EventArgs e)
{
if (this.ib_original.Image == null)
{
MessageBox.Show("原始图片不能为空");
return;
}
CVHelper commonUse = new CVHelper();
var centerList = commonUse.GetCenterPointListFromBitmap(this.ib_original.Image.Bitmap, (int)this.num_threshold.Value);//300分辨率用200,150分辨率用45
Mat tmpMat = new Image <Bgr, byte>(this.ib_original.Image.Bitmap).Mat;
centerList.ForEach(p =>
{
CvInvoke.Circle(tmpMat, p, 6, new MCvScalar(0, 0, 255), 2);
});
this.ib_result.Image = tmpMat;
}
public OptionArea NewByOffsetS(List <OffsetInfo> offsetInfos)
{
var newOptionArea = new OptionArea()
{
Options = this.Options,
WidthInterval = this.WidthInterval,
HeightInterval = this.HeightInterval
};
var offsetCol = OffsetInfo.GetNearestByColumn(offsetInfos, this.Area);
var offsetRow = OffsetInfo.GetNearestByRow(offsetInfos, this.Area);
int xAvgCount = 0, yavgCount = 0;
xAvgCount += offsetCol.offsetX == 0 ? 0 : 1;
xAvgCount += offsetRow.offsetX == 0 ? 0 : 1;
yavgCount += offsetCol.offsetY == 0 ? 0 : 1;
yavgCount += offsetRow.offsetY == 0 ? 0 : 1;
newOptionArea.Area = CVHelper.MoveRect(this.Area, (offsetCol.offsetX + offsetRow.offsetX), (offsetCol.offsetY + offsetRow.offsetY));
return(newOptionArea);
}
/// <summary>
/// 计算占用比
/// </summary>
/// <param name="image">所在区域的图片</param>
public void CalAreaPercent(Image <Gray, byte> image, string saveName = "")
{
//image.Save("ssss.jpg");
int maxX = image.Width, maxY = image.Height;
int width = this.Rectangle.Width, height = this.Rectangle.Height;
int xExtensionDis = width / CVArea.extensionWBase, yExtensionDis = height / CVArea.extensionHBase;
var extensionRect = new Rectangle(Math.Max(0, this.Rectangle.X - xExtensionDis), Math.Max(0, this.Rectangle.Y - yExtensionDis), this.Rectangle.Width + 2 * xExtensionDis, this.Rectangle.Height + 2 * yExtensionDis);
var newRect = new Rectangle(new Point(this.Rectangle.X - extensionRect.X, this.Rectangle.Y - extensionRect.Y), this.Rectangle.Size);
if (extensionRect.Right > maxX)
{
extensionRect.Width -= extensionRect.Right - maxX;
}
if (extensionRect.Bottom > maxY)
{
extensionRect.Height -= extensionRect.Bottom - maxY;
}
using (var extOptionRectImage = image.Copy(extensionRect))
{
var thresholdMat = extOptionRectImage.CopyBlank().Mat;
//CvInvoke.Threshold(CVHelper.Filter( extOptionRectImage.Mat), thresholdMat, this.Threshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
CvInvoke.Threshold(extOptionRectImage, thresholdMat, this.Threshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
Mat mat_dilate = CVHelper.MyDilateS(thresholdMat, Emgu.CV.CvEnum.MorphOp.Open);
mat_dilate = CVHelper.MyDilateS(mat_dilate, Emgu.CV.CvEnum.MorphOp.Dilate);
new CVHelper().SaveMat(extOptionRectImage.Mat, $"原始选项原图行学后-{saveName}");
new CVHelper().SaveMat(mat_dilate, $"异常选项原图行学后-{saveName}");
using (var originalImage = this.Max(mat_dilate.ToImage <Gray, byte>(), newRect))
{
this.AreaPercent = CVHelper.GetWhiteColorPercenterS(originalImage);
Console.WriteLine($"{this.Threshold}下的白色所占比：{this.AreaPercent}");
}
}
}
private void Btn_reg_Click(object sender, EventArgs e)
{
if (this.picSrc.Image == null)
{
MessageBox.Show("请先加载图片");
return;
}
CVHelper commonUse = new CVHelper();
List <Rectangle> posRectList = new List <Rectangle>();
for (int i = 0; i < this.picSrc.RegionInfo.RectList.Count; i++)
{
var tmpRect = this.picSrc.RegionInfo.RectList[i];
var cutedBitmap = PictureBoxReadCard.Cut(this.picSrc.orignalBitmap, tmpRect.X, tmpRect.Y, tmpRect.Width, tmpRect.Height);
if (cutedBitmap == null)
{
MessageBox.Show("将要识别的图片不能为空");
return;
}
var rectList = commonUse.GetRectListFromBitmap(cutedBitmap, 200, 6000, tmpRect.X, tmpRect.Y, false, 0);
posRectList.AddRange(rectList);
}
//获取定位点信息
var dic = commonUse.OrderRectList(posRectList, true, false);
var tempList1 = dic[1].OrderBy(r => r.X).ToList();
var tempList2 = dic[2].OrderBy(r => r.X).ToList();
//四个点
var p1 = tempList1[0];
var p2 = new Point(tempList1[1].X, p1.Y);
lbl1.Text = $"左上角：X：{tempList1[0].X},Y：{tempList1[0].Y},Width:{tempList1[0].Width},Height:{tempList1[0].Height}";
lbl2.Text = $"右上角：X：{tempList1[1].X},Y：{tempList1[1].Y},Width:{tempList1[1].Width},Height:{tempList1[1].Height}";
lbl3.Text = $"左下角：X：{tempList2[0].X},Y：{tempList2[0].Y},Width:{tempList2[0].Width},Height:{tempList2[0].Height}";
lbl4.Text = $"右下角：X：{tempList2[1].X},Y：{tempList2[1].Y},Width:{tempList2[1].Width},Height:{tempList2[1].Height}";
var width = tempList1[1].X - tempList1[0].X;
var height = tempList2[0].Y - tempList1[0].Y;
lbl5.Text = $"W:{width}，H:{height}";
Console.WriteLine($"{lbl1.Text};{lbl5.Text}");
//画出所有定位点
//排序
//var rectListDic = commonUse.OrderRectList(rectList);
using (Mat src = new Image <Bgr, byte>((Bitmap)this.picSrc.orignalBitmap.Clone()).Mat)
{
foreach (var item in posRectList)
{
CvInvoke.Rectangle(src, item, new MCvScalar(0, 0, 255));
}
CvInvoke.Line(src, tempList1[0].Location, tempList1[1].Location, new MCvScalar(0, 0, 255), 2);
CvInvoke.Line(src, tempList2[0].Location, tempList1[0].Location, new MCvScalar(0, 0, 255), 2);
CvInvoke.PutText(src, lbl5.Text, tempList1[0].Location, FontFace.HersheyComplex, 3, new MCvScalar(0, 0, 255), 2);
commonUse.SaveMat(src, "定位点画出后");
}
}
private void BtStart_Click(object sender, EventArgs e)
{
//this.Start();
CVHelper commonUse = new CVHelper();
if (this.ib_middleCut.Image != null)
{
//Mat src1 = new Image<Bgr, byte>(ib_middleCut.Image.Bitmap).Mat;
Mat src = new Image <Bgr, byte>(ib_middleCut.Image.Bitmap).Mat;// new Mat();
//CvInvoke.PyrMeanShiftFiltering(src1, src, 25, 10, 1, new MCvTermCriteria(5, 1));
//commonUse.SaveMat(src, "降噪后");
//commonUse.SaveMat(src1, "降噪后原始");
Mat dst = new Mat();
Mat src_gray = new Mat();
CvInvoke.CvtColor(src, src_gray, Emgu.CV.CvEnum.ColorConversion.Bgr2Gray);
//存储灰度图片
commonUse.SaveMat(src_gray, "灰度");
#region 二值化
//二值化
Mat mat_threshold = new Mat();
int myThreshold = Convert.ToInt32(num_threshold.Value);
CvInvoke.Threshold(src_gray, mat_threshold, myThreshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
commonUse.SaveMat(mat_threshold, "二值化");
//形态学膨胀
Mat mat_dilate = commonUse.MyDilate(mat_threshold, Emgu.CV.CvEnum.MorphOp.Close);
commonUse.SaveMat(mat_dilate, "形态学膨胀");
mat_dilate = commonUse.MyDilate(mat_threshold, Emgu.CV.CvEnum.MorphOp.Open);
commonUse.SaveMat(mat_dilate, "形态学膨胀1");
mat_dilate = commonUse.MyDilate(mat_threshold, Emgu.CV.CvEnum.MorphOp.Erode);
commonUse.SaveMat(mat_dilate, "形态学膨胀");
#endregion
//边缘检测
CvInvoke.Canny(mat_dilate, dst, Convert.ToInt32(this.num_Min.Value), Convert.ToInt32(this.num_Max.Value), Convert.ToInt32(this.num_apertureSize.Value));
commonUse.SaveMat(dst, "边缘检测");
//寻找答题卡矩形边界（所有的矩形）
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint(); //创建VectorOfVectorOfPoint数据类型用于存储轮廓
VectorOfVectorOfPoint validContours = new VectorOfVectorOfPoint(); //有效的，所有的选项的
CvInvoke.FindContours(dst, contours, null, Emgu.CV.CvEnum.RetrType.Ccomp,
Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);//提取轮廓
//CvInvoke.ApproxPolyDP
//画出所有矩形
Mat middleMat = new Image <Bgr, byte>(this.ib_middleCut.Image.Bitmap).Mat;
CvInvoke.DrawContours(middleMat, contours, -1, new MCvScalar(0, 0, 255), 1);
this.ib_result.Image = middleMat;
commonUse.SaveMat(middleMat, "画出所有轮廓的");
//获取矩形边界另一种方法
//var tempRect=CvInvoke.BoundingRectangle(contours);
//CvInvoke.Rectangle(src, tempRect, new MCvScalar(0, 0, 255));
//this.ib_middle.Image = src;
//return;
//打印所以后矩形面积和周长
int size = contours.Size;
//for (int i = 0; i < size; i++)
//{
// var item = contours[i];
// var tempArea = CvInvoke.ContourArea(item);
// var tempArc = CvInvoke.ArcLength(item, true);
// Console.WriteLine($"面积：{tempArea}；周长：{tempArc}"); ;
// if (tempArea > 200 && tempArea<1000)
// {
// validContours.Push(item);
// }
//}
//画出符合要求的所有矩形
//CvInvoke.DrawContours(src, validContours, -1, new MCvScalar(0, 0, 255), 1);
//var rectList = commonUse.GetRectList(validContours);
//foreach (var item in rectList)
//{
// //宽高比例不能>4或者0.24
// if (item.Width * 1.0 / item.Height > 4 || item.Width * 1.0 / item.Height < 0.25)
// {
// continue;
// }
// CvInvoke.Rectangle(src, item, new MCvScalar(0, 0, 255));
//}
//commonUse.SaveMat(src, "带有所有轮廓边界的");
//this.ib_middle.Image = src;
}
else
{
MessageBox.Show("请先加载图片");
}
}
private void Btn_reg_Click(object sender, EventArgs e)
{
if (ib_original.Image == null)
{
MessageBox.Show("请先加载图片");
return;
}
var cutedBitmap = this.ib_original.GetFirstRegionRect();
if (cutedBitmap == null)
{
MessageBox.Show("将要识别的图片不能为空");
return;
}
CVHelper commonUse = new CVHelper();
var rectList = commonUse.GetRectListFromBitmap(cutedBitmap, Convert.ToInt32(this.minNum.Value), Convert.ToInt32(this.maxNum.Value), 0, 0, true, 2);
//排序
//var rectListDic = commonUse.OrderRectList(rectList);
Mat src = new Image <Bgr, byte>(cutedBitmap).Mat;
foreach (var item in rectList)
{
CvInvoke.Rectangle(src, item, new MCvScalar(0, 0, 255));
}
commonUse.SaveMat(src, "获取裁剪图中的所有轮廓边界提取");
this.ib_result.Image = src.Bitmap;
//填充试卷内容
if (rectList?.Count == 0)
{
return;
}
//填充试卷内容
var firstRect = this.ib_original.RegionInfo.RectList.FirstOrDefault();
if (!isFixedPointReg)
{
commonUse.CaculateRectInfo(rectList, out double averageWidth, out double averageHeight, out double intervalWidth, out double intervalHeight);
this.Paper.OptionAreaList.Add(new OptionArea()
{
Area = firstRect, Options = commonUse.OrderRectList(rectList, true, false), WidthInterval = (int)intervalWidth, HeightInterval = (int)intervalHeight
});
}
else
{
var fixedPointDetail = rectList.FirstOrDefault();
fixedPointDetail.X += firstRect.X;
fixedPointDetail.Y += firstRect.Y;
var fixedType = this.GetFixedType(this.ib_original.orignalBitmap.Width, this.ib_original.orignalBitmap.Height, fixedPointDetail);
switch (fixedType)
{
case FixedType.LeftTop:
this.Paper.FixedPoint.LeftTop = new FixedPointDetail()
{
Outer = firstRect, Inner = fixedPointDetail
};
break;
case FixedType.RightTop:
this.Paper.FixedPoint.RightTop = new FixedPointDetail()
{
Outer = firstRect, Inner = fixedPointDetail
};
break;
case FixedType.LeftBottom:
this.Paper.FixedPoint.LeftBottom = new FixedPointDetail()
{
Outer = firstRect, Inner = fixedPointDetail
};
break;
case FixedType.RightBottom:
this.Paper.FixedPoint.RightBottom = new FixedPointDetail()
{
Outer = firstRect, Inner = fixedPointDetail
};
break;
default:
break;
}
}
}
public Paper NewPaperByOffsetS(List <OffsetArea> newOffsetAreaList)
{
var paper = new Paper();
//列偏移模块
var newColOffsetList = new List <Rectangle>(); //相对0,0
var originalColOffsetList = new List <Rectangle>(); //相对0,0
//行偏移模块
var newRowOffsetList = new List <Rectangle>(); //相对0,0
var originalRowOffsetList = new List <Rectangle>(); //相对0,0
newOffsetAreaList.ForEach(a =>
{
if (a.OffsetType == OffsetType.Column)
{
newColOffsetList.AddRange(CVHelper.MoveRects(a.OffsetList, a.Area.X, a.Area.Y));
}
else
{
newRowOffsetList.AddRange(CVHelper.MoveRects(a.OffsetList, a.Area.X, a.Area.Y));
}
});
//tmpColOffsetList = tmpColOffsetList.OrderBy(r => r.Y).ToList();
this.OffsetAreas.ForEach(a =>
{
if (a.OffsetType == OffsetType.Column)
{
originalColOffsetList.AddRange(CVHelper.MoveRects(a.OffsetList, a.Area.X, a.Area.Y));
}
else
{
originalRowOffsetList.AddRange(CVHelper.MoveRects(a.OffsetList, a.Area.X, a.Area.Y));
}
});
//originalColOffsetList = originalColOffsetList.OrderBy(r => r.Y).ToList();
var offsetInfoList = OffsetInfo.NewListByColumn(originalColOffsetList, newColOffsetList);
offsetInfoList.AddRange(OffsetInfo.NewListByRow(originalRowOffsetList, newRowOffsetList));
//定位点 暂不处理
paper.FixedPoint = this.FixedPoint.NewFixedPointByOffset(0, 0);
//选项区域
this.OptionAreaList.ForEach(o =>
{
paper.OptionAreaList.Add(o.NewByOffsetS(offsetInfoList));
});
//偏移量
this.OffsetAreas.ForEach(a =>
{
if (a.OffsetType == OffsetType.Column)
{
var tmpList = OffsetInfo.GetRectsByAreaAndCol(newColOffsetList, a.Area);
paper.OffsetAreas.Add(new OffsetArea(a.Area, tmpList, a.OffsetType));
}
else
{
var tmpList = OffsetInfo.GetRectsByAreaAndRow(newRowOffsetList, a.Area);
paper.OffsetAreas.Add(new OffsetArea(a.Area, tmpList, a.OffsetType));
}
});
return(paper);
}
public void Start()
{
CVHelper commonUse = new CVHelper();
if (ib_original.Image != null)
{
//Mat src = new Image<Bgr, byte>(ib_original.Image.Bitmap).Mat;
Mat src = ib_original.Image.GetInputArray().GetMat();
//1.获取当前图像的最大矩形边界
VectorOfVectorOfPoint max_contour = commonUse.GetBoundaryOfPic(src);
//2.对图像进行矫正
Mat mat_Perspective = commonUse.MyWarpPerspective(src, max_contour);
//规范图像大小
CvInvoke.Resize(mat_Perspective, mat_Perspective, new Size(590, 384), 0, 0, Emgu.CV.CvEnum.Inter.Cubic);
//3.二值化处理（大于阈值取0，小于阈值取255。其中白色为0，黑色为255)
Mat mat_threshold = new Mat();
int myThreshold = Convert.ToInt32(num_threshold.Value);
CvInvoke.Threshold(mat_Perspective, mat_threshold, myThreshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
//ib_middle.Image = mat_threshold;
//形态学膨胀
Mat mat_dilate = commonUse.MyDilate(mat_threshold);
//ib_middle.Image = mat_dilate;
//筛选长宽比大于2的轮廓
VectorOfVectorOfPoint selected_contours = commonUse.GetUsefulContours(mat_dilate, 1);
//画出轮廓
Mat color_mat = commonUse.DrawContours(mat_Perspective, selected_contours);
ib_middle.Image = color_mat;
ib_result.Image = mat_Perspective;
//准考证号，x=230+26*5,y=40+17*10
//tb_log.Text = commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 230, 26, 5, 40, 17, 10, "准考证号：");
////答题区1-5题，x=8+25*5,y=230+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 8, 25, 5, 230, 16, 4, "1-5：");
////答题区6-10题,x=159+25*5,y=230+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 159, 25, 5, 230, 16, 4, "6-10：");
////答题区11-15题,x=310+25*5,y=230+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 310, 25, 5, 230, 16, 4, "11-15：");
////答题区16-20题,x=461+25*5,y=230+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 461, 25, 5, 230, 16, 4, "16-20：");
////答题区21-25题,x=8+25*5,y=312+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 8, 25, 5, 312, 16, 4, "21-25：");
////答题区26-30题,x=159+25*5,y=312+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 159, 25, 5, 312, 16, 4, "26-30：");
////答题区31-35题,x=310+25*5,y=312+16*4
//tb_log.Text += commonUse.GetValueAndDrawGrid(ib_result, selected_contours, 310, 25, 5, 312, 16, 4, "31-35：");
}
else
{
MessageBox.Show("请先加载图片");
}
}
/// <summary>
/// 该区域的图片
/// </summary>
/// <param name="src"></param>
/// <param name="myThreshold"></param>
public void Recognition(Image <Gray, byte> src, int myThreshold = 180)
{
////思路：第一次正常识别--->初步智能筛选---->再次智能筛选---》再次智能(如果未选，继续多次，如果多选)
////var src = new Image<Gray, byte>(bitmap);
var thresholdMat = src.CopyBlank().Mat;
CvInvoke.Threshold(src, thresholdMat, myThreshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
new CVHelper().SaveMat(src.Mat, "原始的");
//思路 open -膨胀
//形态学膨胀
Mat mat_dilate = CVHelper.MyDilateS(thresholdMat, Emgu.CV.CvEnum.MorphOp.Open);
new CVHelper().SaveMat(mat_dilate, "Open行学");
mat_dilate = CVHelper.MyDilateS(mat_dilate, Emgu.CV.CvEnum.MorphOp.Dilate);
new CVHelper().SaveMat(mat_dilate, "Dilate行学");
//补充偏移置换
//src = Max(src);
foreach (var question in this.CVQuestionList)
{
for (int i = 0; i < question.OptionRectList.Count; i++)
{
var cvRect = question.OptionRectList[i];
//计算平均灰度值
//var fileName = $"{this.Name}第";
cvRect.CalVagGrayValueAndHist(src);
//计算面积比
cvRect.CalAreaPercent(src);
if (cvRect.AreaPercent > CVArea.valAreaPercent)
{
question.Results.Add(i);
}
}
}
//打印初步识别的
//new CommonUse().DrawRectCircleAndSave(src.Mat.Clone(), this.GetRectList(), $"{this.Name}-初步识别的", -this.Area.X, -this.Area.Y, points: this.GetResultPointList(false));
this.DrawDetail(src.Clone(), this.Name);
//初步筛选
this.Check();
new CVHelper().DrawRectCircleAndSave(src.Mat.Clone(), this.GetRectList(false), $"{this.Name}-初步筛选结果", points: this.GetResultPointList(false));
//再次智能处理异常的
this.CVQuestionList.ForEach(q =>
{
this.IntelligentChose(src, q);
int total = 11;
for (int i = 2; i <= total; i++)
{
if (q.ResultStatus == QuestionResultStatus.Right)
{
break;
}
else if (q.ResultStatus == QuestionResultStatus.Absence)
{
q.IntelligentChoseByAbsence(src, i);
}
}
});
//再次通过神经网络识别
//this.RecognitionByML();
for (int i = 0; i < this.CVQuestionList.Count; i++)
{
var q = this.CVQuestionList[i];
if (q.ResultStatus != QuestionResultStatus.Absence)
{
continue;
}
//针对只有一个的选框的不适用人工智能网络)
//if (this.GetOptionCount() == 1)
//{
// continue;
//}
for (int j = 0; j < q.OptionRectList.Count; j++)
{
var rect = q.OptionRectList[j];
if (rect.AreaPercent == 0 && rect.AvgGrayValue == 0)
{
continue;
}
//智能识别
var queRect = rect.Rectangle;
using (var copy = src.Copy(queRect))
{
var isAnswer = MLearner.IsAnswer(copy);
if (!q.Results.Contains(j) && isAnswer)
{
q.Results.Add(j);
}
new CVHelper().SaveMat(copy.Mat, "需要智能之别的" + isAnswer, dictory: "MLReg\\");
}
}
}
//脱离原rectangle，再次智能筛选
try {
DoMLAgain(src);
}
catch (Exception ex)
{
Console.WriteLine("再次智能之别是，发生错误");
Console.WriteLine(ex);
}
}
/// <summary>
/// 再次智能识别
/// </summary>
/// <param name="src"></param>
private void DoMLAgain(Image <Gray, byte> src)
{
//正对使用了偏移块还不准的区域再次识别
if (!this.IsAbsence())
{
return;
}
var cvHelper = new CVHelper();
var rectList = cvHelper.GetRectListFromBitmap(src.Bitmap, isAutoFillFull: true);
if (rectList.Count != this.GetOptionCount())// || rectList.Count==1 针对只有一个的选框的不适用
{
return;
}
var rectListDic = cvHelper.OrderRectList(rectList, this.IsOrderByRow());
var anwserDir = new Dictionary <int, List <int> >();
foreach (var key in rectListDic.Keys)
{
var queOptions = rectListDic[key];
var tmpResult = new List <int>();
for (int i = 0; i < queOptions.Count; i++)
{
var queRect = queOptions[i];
using (var copy = src.Copy(queRect))
{
var isAnswer = MLearner.IsAnswer(copy);
if (isAnswer)
{
tmpResult.Add(i);
}
#if DEBUG
new CVHelper().SaveMat(copy.Mat, "再次智能之别的" + isAnswer, dictory: "MLReg2\\");
#endif
}
}
anwserDir.Add(key, tmpResult);
}
//合并答案
foreach (var key in anwserDir.Keys)
{
var result = anwserDir[key];
if (this.CVQuestionList[key - 1].ResultStatus == QuestionResultStatus.Absence)
{
this.CVQuestionList[key - 1].Results = result;
}
}
#if DEBUG
//画出再次智能出来的框和识别出来的中心点
var tmpRectList = new List <Rectangle>();
var tmpPointList = new List <Point>();
foreach (var key in rectListDic.Keys)
{
tmpRectList.AddRange(rectListDic[key]);
anwserDir[key].ForEach(i =>
{
var rect = rectListDic[key][i];
var point = rect.Location;
point.Offset(rect.Width / 2, rect.Height / 2);
tmpPointList.Add(point);
});
}
cvHelper.DrawRectCircleAndSave(src.Mat, tmpRectList, "再次智能后", points: tmpPointList, dictory: "MLReg2\\");
#endif
}
private void Btn_anwserReg_Click(object sender, EventArgs e)
{
if (this.ib_middleCut.Image == null)
{
MessageBox.Show("裁剪图片不能为空");
return;
}
CVHelper commonUse = new CVHelper();
Mat src = new Image <Bgr, byte>(ib_middleCut.Image.Bitmap).Mat;// new Mat();
//CvInvoke.PyrMeanShiftFiltering(src1, src, 25, 10, 1, new MCvTermCriteria(5, 1));
//commonUse.SaveMat(src, "降噪后");
//commonUse.SaveMat(src1, "降噪后原始");
Mat dst = new Mat();
Mat src_gray = new Mat();
CvInvoke.CvtColor(src, src_gray, Emgu.CV.CvEnum.ColorConversion.Bgr2Gray);
//存储灰度图片
commonUse.SaveMat(src_gray, "灰度");
#region 二值化
//二值化
Mat mat_threshold = new Mat();
int myThreshold = Convert.ToInt32(num_threshold.Value);
CvInvoke.Threshold(src_gray, mat_threshold, myThreshold, 255, Emgu.CV.CvEnum.ThresholdType.BinaryInv);
commonUse.SaveMat(mat_threshold, "二值化");
//思路 close -腐蚀-腐蚀-膨胀
//形态学膨胀
Mat mat_dilate = commonUse.MyDilate(mat_threshold, Emgu.CV.CvEnum.MorphOp.Close);
commonUse.SaveMat(mat_dilate, "形态学膨胀");
//mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Close);
//commonUse.SaveMat(mat_dilate, "形态学膨胀1");
mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Erode);
commonUse.SaveMat(mat_dilate, "形态学膨胀腐蚀1");
mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Erode);
commonUse.SaveMat(mat_dilate, "形态学膨胀腐蚀2");
mat_dilate = commonUse.MyDilate(mat_dilate, Emgu.CV.CvEnum.MorphOp.Dilate);
commonUse.SaveMat(mat_dilate, "形态学膨胀2");
#endregion
//边缘检测
CvInvoke.Canny(mat_dilate, dst, Convert.ToInt32(this.num_Min.Value), Convert.ToInt32(this.num_Max.Value), Convert.ToInt32(this.num_apertureSize.Value));
commonUse.SaveMat(dst, "边缘检测");
//寻找答题卡矩形边界（所有的矩形）
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint(); //创建VectorOfVectorOfPoint数据类型用于存储轮廓
VectorOfVectorOfPoint validContours = new VectorOfVectorOfPoint(); //有效的，所有的选项的
CvInvoke.FindContours(dst, contours, null, Emgu.CV.CvEnum.RetrType.Ccomp,
Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple, new Point(8, 8));//提取轮廓
//打印所以后矩形面积和周长
int size = contours.Size;
for (int i = 0; i < size; i++)
{
var item = contours[i];
var tempArea = CvInvoke.ContourArea(item);
var tempArc = CvInvoke.ArcLength(item, true);
Console.WriteLine($"面积：{tempArea}；周长：{tempArc}");;
if (tempArea > 200 && tempArea < 2000)
{
validContours.Push(item);
}
}
//CvInvoke.ApproxPolyDP
//画出所有轮廓
Mat middleMat = new Image <Bgr, byte>(this.ib_middleCut.Image.Bitmap).Mat;
CvInvoke.DrawContours(middleMat, validContours, -1, new MCvScalar(0, 0, 255), 1);
this.ib_result.Image = middleMat;
commonUse.SaveMat(middleMat, "画出所有轮廓的");
//画出所有矩形
Mat tmpMat = new Image <Bgr, byte>(this.ib_middleCut.Image.Bitmap).Mat;
List <Rectangle> rectangles = commonUse.GetRectList(validContours, false);
rectangles.ForEach(rect =>
{
CvInvoke.Rectangle(tmpMat, rect, new MCvScalar(0, 0, 255));
});
commonUse.SaveMat(tmpMat, "画出所有矩形轮廓的");
this.ib_result.Image = tmpMat;
}
private void Btn_answerReg4_Click(object sender, EventArgs e)
{
if (this.ib_middleCut.Image == null)
{
MessageBox.Show("裁剪图片不能为空");
return;
}
CVHelper commonUse = new CVHelper();
var centerList = new List <Point>();
if (!this.ck_IsIntell.Checked && !this.ckb_ANN.Checked)
{
centerList = commonUse.GetCenterPointListFromBitmapByWhiteArea(this.ib_middleCut.Image.Bitmap, CutedRectList);
Mat tmpMat = new Image <Bgr, byte>(this.ib_middleCut.Image.Bitmap).Mat;
centerList.ForEach(p =>
{
CvInvoke.Circle(tmpMat, p, 6, new MCvScalar(0, 0, 255), 2);
});
this.ib_result.Image = tmpMat;
}
else
{
var rectList = new List <Rectangle>();
CutedRectList.ForEach(r =>
{
r.Offset(destRect.Location);
//int offsetX = Math.Min(5, r.X), offsetY = Math.Min(5, r.Y);
//r.Offset(-offsetX, -offsetY);
rectList.Add(r);
});
CVArea area = new CVArea(this.destRect, commonUse.OrderRectList(rectList, IsFillFull: false), name: "测试卷");
if (this.ck_IsIntell.Checked)
{
centerList = commonUse.GetCenterPointListFromBitmapByWhiteArea(this.ib_original.Image.Bitmap, new List <CVArea>()
{
area
});
}
else if (this.ckb_ANN.Checked)
{
centerList = commonUse.GetCenterPointListFromBitmapByWhiteAreaByML(this.ib_original.Image.Bitmap, new List <CVArea>()
{
area
});
}
Mat tmpMat = new Image <Bgr, byte>(this.ib_original.Image.Bitmap).Mat;
centerList.ForEach(p =>
{
CvInvoke.Circle(tmpMat, p, 6, new MCvScalar(0, 0, 255), 2);
});
this.ib_result.Image = tmpMat;
this.CurrentArea = area;
return;
}
}