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@@ -0,0 +1,822 @@
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+using System;
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+using System.Collections.Generic;
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+using System.ComponentModel;
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+using System.Data;
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+using System.Drawing;
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+using System.Linq;
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+using System.Text;
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+using System.Threading.Tasks;
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+using System.Windows.Forms;
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+using OpenCvSharp;
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+using OpenCvSharp.Extensions;
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+using System.Threading;
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+
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+namespace 简单图像处理软件
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+{
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+ public partial class Form1 : Form
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+ {
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+ public Form1()
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+ {
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+ InitializeComponent();
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+ }
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+
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+ private void intrudBtn_Load(object sender, EventArgs e)
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+ {
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+
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+ }
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+
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+ public Mat pictureMain;//当前主窗体图像
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+ public Mat form2image;//窗体二图像
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+ public float form2Num1=50f;
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+ public float form2Num2 = 150f;//接受窗体二传入的参数一参数二
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+ string imageName;
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+ private void openBtn_Click(object sender, EventArgs e)
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+ {
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+ OpenFileDialog ofd1 = new OpenFileDialog();//创建打开文件夹窗体
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+ ofd1.Title = "请选择输入的图像";
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+ ofd1.InitialDirectory = @"";//初始化目录
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+ ofd1.Multiselect = false;//不可多选
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+ ofd1.Filter = "图像文件|*.jpg;*.png;*.bmp|全部文件|*.*";
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+ ofd1.ShowDialog();
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+
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+ if (ofd1.FileName!=string.Empty)
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+ {
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+ try
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+ {
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+ pictureShow.Load(ofd1.FileName);
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+ imageName = ofd1.FileName;
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+ textBox1.AppendText("\n\r打开文件：" + imageName);
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+ textBox1.SelectionStart = this.textBox1.TextLength;
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+ textBox1.ScrollToCaret();
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+ pictureMain = new Mat(ofd1.FileName);
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+ }
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+ catch (Exception)
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+ {
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+ MessageBox.Show("打开失败，请检查文件格式是否符合");
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+ }
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+
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+ }
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+
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+ }
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+
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+ private void saveBtn_Click(object sender, EventArgs e)
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+ {
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+
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+ if (pictureShow!=null)
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+ {
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+ SaveFileDialog sfd = new SaveFileDialog();
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+ sfd.Title = "保存文件";
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+ sfd.Filter = "JPGE图像|*.jpg|PNG图像|*.png|BMP图像|*.bmp|所有文件|*.*";
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+ sfd.InitialDirectory = Environment.CurrentDirectory;
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+ sfd.ShowDialog();
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+ if (sfd.FileName != null)
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+ {
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+ try
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+ {
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+ pictureShow.Image.Save(sfd.FileName);
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+ textBox1.AppendText("\r\n图片已保存至：" + sfd.FileName);
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+ textBox1.SelectionStart = textBox1.TextLength;
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+ textBox1.ScrollToCaret();
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+ }
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+ catch (Exception)
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+ {
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+ }
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+ }
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+ }
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+ else
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+ {
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+ MessageBox.Show("无可保存图片");
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+ }
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+
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+ }
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+
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+ private void textBox1_TextChanged(object sender, EventArgs e)
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+ {
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+
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+ }
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+
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+ private void button1_Click(object sender, EventArgs e)
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+ {
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+ // MessageBox.Show("本人第一个以C#和opencvsharp写的小程序，很多bug来不及慢慢优化，但也算包含一番心血，主要是将之前学习的内容再复习深化了解，感叹路漫漫其修远兮，昨日之日不可留，最终走回程序员这条路");
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+ }
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+ private void reflashBtn_Click(object sender, EventArgs e)
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+ {
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+ num = 1;
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+ listBox2.Items.Clear();
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+ textBox1.Text = "以下为通知信息：";
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+ if (imageName != string.Empty)
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+ {
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+ try
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+ {
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+ pictureShow.Load(imageName);
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+ pictureMain = new Mat(imageName);
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ }
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+ catch { }
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+ }
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+
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+ }
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+ int num = 1;//记录处理次数
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+ public enum lb1_list//记录操作方法
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+ {
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+ gray,
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+ reverse,
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+ binary,
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+ gaussianBlur,
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+ blur,
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+ medianBlur,
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+ bilateralFilter,
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+ sobel,
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+ scharr,
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+ canny,
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+ Laplacian,
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+ carve,
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+ rever_lr,
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+ rever_tb,
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+ frost,
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+ sharp,
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+ dilate,
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+ erode,
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+ tophat,
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+ blackhat,
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+ gamma,
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+ log,
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+ hist,
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+ findContours,
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+ template,
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+ drawRect,
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+
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+ }
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+ public int selectIndex;
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+ /// <summary>
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+ /// 实现双击启动处理
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+ /// </summary>
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+ /// <param name="sender"></param>
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+ /// <param name="e"></param>
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+ private void listBox1_DoubleClick(object sender, EventArgs e)
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+ {
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+ selectIndex = listBox1.SelectedIndex;
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+ handle(selectIndex);
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+ }
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+
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+
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+
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+ /// <summary>
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+ /// 二值化Tbar处理函数
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+ /// </summary>
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+ /// <param name="pos"></param>
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+ /// <param name="userdata"></param>
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+ public void binary(int pos, object userdata)
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+ {
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+
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+ Mat a = (Mat)userdata;
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+ Mat b = new Mat();
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+ a.CopyTo(b);
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+ Cv2.Threshold(b, b, pos * 25, 255, ThresholdTypes.Binary);
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+ Cv2.ImShow("二值化处理", b);
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+ b.CopyTo(pictureMain);
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ b.Release();
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+ }
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+
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+ /// <summary>
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+ /// 高斯滤波
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+ /// </summary>
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+ /// <param name="pos"></param>
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+ /// <param name="userdata"></param>
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+ public void gaussianBlur(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+
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+ Cv2.GaussianBlur(a, a, new OpenCvSharp.Size(pos*2+1, pos*2+1), 5);
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+
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+ Cv2.ImShow("高斯滤波", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ }
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+ /// <summary>
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+ /// 均值滤波
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+ /// </summary>
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+ /// <param name="pos"></param>
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+ /// <param name="userdata"></param>
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+ public void blur(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+
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+ Cv2.Blur(a, a, new OpenCvSharp.Size(pos+1, pos+1));
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+
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+ Cv2.ImShow("均值滤波", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ }
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+
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+ public void medianBlur(int pos, object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Cv2.MedianBlur(a, a, pos*2+1);
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+ Cv2.ImShow("中值滤波", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ }
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+ public void bilateralFilter(int pos, object userdata)
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+ {
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+
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ Mat b = new Mat();
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+ src.CopyTo(b);
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+ Cv2.BilateralFilter(b, a, pos*5 + 1, 100, 100);
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+ Cv2.ImShow("双边滤波", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ b.Release();
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+ }
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+ public void canny(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Cv2.Canny(a, a, pos * 25, pos * 25);
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+ Cv2.ImShow("canny边缘检测", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ Thread.Sleep(50);
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+ }
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+ public void laplacian(int pos,object userdata)
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+ {
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+ Mat src=(Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Cv2.Laplacian(a, a, -1, pos*2 + 1);
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+ Cv2.ImShow("Laplacian边缘检测", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ }
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+ public void dilate(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Mat structureElement = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(pos * 2 + 1, pos * 2 + 1));
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+ Cv2.Dilate(a, a, structureElement);
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+ Cv2.ImShow("膨胀处理", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ }
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+ public void erode(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Mat structureElement = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(pos * 2 + 1, pos * 2 + 1));
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+ Cv2.Erode(a, a, structureElement);
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+ Cv2.ImShow("腐蚀处理", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = a.ToBitmap();
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+ a.Release();
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+ }
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+ public void tophat(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Mat stuctureElement = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(pos+1, pos+1), new OpenCvSharp.Point(-1, -1));
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+ Cv2.MorphologyEx(a, a, MorphTypes.TopHat, stuctureElement);
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+ Cv2.ImShow("顶帽处理", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ a.Release();
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+ }
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+ public void blackhat(int pos, object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ src.CopyTo(a);
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+ Mat stuctureElement = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(pos + 1, pos + 1), new OpenCvSharp.Point(-1, -1));
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+ Cv2.MorphologyEx(a, a, MorphTypes.BlackHat, stuctureElement);
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+ Cv2.ImShow("黑帽处理", a);
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+ a.CopyTo(pictureMain);
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ a.Release();
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+ }
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+ public void drawRect(int pos,object userdata)
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+ {
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+ Mat src = (Mat)userdata;
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+ Mat a = new Mat();
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+ Mat gray = new Mat();
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+ src.CopyTo(gray);
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+ if (gray.Channels()==3)
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+ {
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+ Cv2.CvtColor(gray, gray, ColorConversionCodes.BGR2GRAY);
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+ }
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+ gray.CopyTo(a);
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+ Cv2.Threshold(~a, a ,pos *25, 255, ThresholdTypes.Binary);
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+ //Cv2.Canny(a, a, pos*10, 255);
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+ HierarchyIndex[] hierarchy;
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+ OpenCvSharp.Point[][] coutours;
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+ Cv2.FindContours(a, out coutours,out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxNone);
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+ OpenCvSharp.Point[][] contours_ploy = new OpenCvSharp.Point[coutours.Length][];
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+ RotatedRect[] RotatedRect_ploy = new RotatedRect[coutours.Length];
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+ Rect[] rect_poly = new Rect[coutours.Length];
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+ for (int i = 0; i < coutours.Length; i++)
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+ {
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+ contours_ploy[i] = Cv2.ApproxPolyDP(coutours[i], 10, true);//计算凸包
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+ rect_poly[i] = Cv2.BoundingRect(coutours[i]);//最小外接矩形，我们不用，
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+ if (contours_ploy[i].Length>5)//拟合的线条数不少于5
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+ {
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+ RotatedRect temp1 = Cv2.MinAreaRect(contours_ploy[i]);//最小外接矩形，能旋转
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+ RotatedRect_ploy[i] = temp1;//将该矩形放入集合中
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+ }
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+ }
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+ Point2f[] pot = new Point2f[4];
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+ for (int i = 0; i < RotatedRect_ploy.Length; i++)
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+ {
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+ pot = RotatedRect_ploy[i].Points();
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+ double line1 = Math.Sqrt((pot[1].Y - pot[0].Y) * (pot[1].Y - pot[0].Y)+ (pot[1].X - pot[0].X) * (pot[1].X - pot[0].X));
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+ double line2=Math.Sqrt((pot[3].Y - pot[0].Y) * (pot[3].Y - pot[0].Y) + (pot[3].X - pot[0].X) * (pot[3].X - pot[0].X));
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+ if (line1*line2<9000)//太小直接pass
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+ {
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+ continue;
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+ }
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+
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+ for (int j = 0; j < 4; j++)
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+ {
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+ Cv2.Line(pictureMain, (OpenCvSharp.Point)pot[j], (OpenCvSharp.Point)pot[(j + 1) % 4], Scalar.Green,3);
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+ }
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+ }
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+ Cv2.ImShow("最小外包矩形", a);
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ a.Release();
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+ }
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+ public void handle(int selectIndex)
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+ {
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+
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+ switch (selectIndex)
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+ {
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+ case (int)lb1_list.gray:
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+ if (pictureMain.Channels() == 3)
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+ {
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+ Cv2.CvtColor(pictureMain, pictureMain, ColorConversionCodes.BGR2GRAY);
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ display("灰度化");
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+ }
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+ else
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+ {
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+ MessageBox.Show("已是灰度图像，不要重复操作");
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+ }
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+ break;
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+ case (int)lb1_list.reverse:
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+ pictureMain = ~pictureMain;
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+ pictureShow.Image = pictureMain.ToBitmap();
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+ display("反色");
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+ break;
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+ case (int)lb1_list.binary:
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+ Cv2.ImShow("二值化处理", pictureMain);
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+ Mat temp0 = new Mat();
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+ pictureMain.CopyTo(temp0);
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+ CvTrackbarCallback2 ctbc0 = new CvTrackbarCallback2(binary);
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+ CvTrackbar cvtb0 = new CvTrackbar("程度", "二值化处理", 0, 10, ctbc0, temp0);
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+ display("二值化");
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+ break;
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+
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+ case (int)lb1_list.gaussianBlur:
|
|
|
+ Cv2.ImShow("高斯滤波", pictureMain);
|
|
|
+ Mat temp1 = new Mat();
|
|
|
+ pictureMain.CopyTo(temp1);
|
|
|
+
|
|
|
+ CvTrackbarCallback2 ctbc1 = new CvTrackbarCallback2(gaussianBlur);
|
|
|
+ CvTrackbar cvtb1 = new CvTrackbar("程度", "高斯滤波", 0, 10, ctbc1, temp1);
|
|
|
+
|
|
|
+ display("高斯滤波");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.blur:
|
|
|
+ Cv2.ImShow("均值滤波", pictureMain);
|
|
|
+ Mat temp2 = new Mat();
|
|
|
+ pictureMain.CopyTo(temp2);
|
|
|
+
|
|
|
+ CvTrackbarCallback2 ctbc2 = new CvTrackbarCallback2(blur);
|
|
|
+ CvTrackbar cvtb2 = new CvTrackbar("程度", "均值滤波", 0, 10, ctbc2, temp2);
|
|
|
+
|
|
|
+ display("均值滤波");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.medianBlur:
|
|
|
+ Cv2.ImShow("中值滤波", pictureMain);
|
|
|
+ Mat temp3 = new Mat();
|
|
|
+ pictureMain.CopyTo(temp3);
|
|
|
+
|
|
|
+ CvTrackbarCallback2 ctbc3 = new CvTrackbarCallback2(medianBlur);
|
|
|
+ CvTrackbar cvtb3 = new CvTrackbar("程度", "中值滤波", 0, 10, ctbc3, temp3);
|
|
|
+
|
|
|
+ display("中值滤波");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.bilateralFilter:
|
|
|
+ Cv2.ImShow("双边滤波", pictureMain);
|
|
|
+ Mat temp4 = new Mat();
|
|
|
+ pictureMain.CopyTo(temp4);
|
|
|
+
|
|
|
+ CvTrackbarCallback2 crbc4 = new CvTrackbarCallback2(bilateralFilter);
|
|
|
+ CvTrackbar cvtb4 = new CvTrackbar("程度", "双边滤波", 0, 10, crbc4, temp4);
|
|
|
+
|
|
|
+ display("双边滤波");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.sobel://-1 -2 -1
|
|
|
+ Mat sobelx = new Mat();
|
|
|
+ Mat sobely = new Mat();
|
|
|
+ Cv2.Sobel(pictureMain, sobelx, -1, 1, 0);
|
|
|
+ Cv2.Sobel(pictureMain, sobely, -1, 0, 1);
|
|
|
+ Cv2.AddWeighted(sobelx, 0.5, sobely, 0.5, 0, pictureMain);//gamma为加到结果上的值
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("sobel边缘检测");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.scharr://-3 -10 -3
|
|
|
+ Mat scharrx = new Mat();
|
|
|
+ Mat scharry = new Mat();
|
|
|
+ Cv2.Scharr(pictureMain, scharrx, -1, 1, 0);
|
|
|
+ Cv2.Scharr(pictureMain, scharry, -1, 0, 1);
|
|
|
+ Cv2.AddWeighted(scharrx, 0.5, scharry, 0.5, 0, pictureMain);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("scharr边缘检测");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.canny:
|
|
|
+ Cv2.ImShow("canny边缘检测", pictureMain);
|
|
|
+ Mat temp_canny = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_canny);
|
|
|
+ if (temp_canny.Channels() == 3)
|
|
|
+ {
|
|
|
+ Cv2.CvtColor(temp_canny, temp_canny, ColorConversionCodes.BGR2GRAY);
|
|
|
+ }
|
|
|
+ CvTrackbarCallback2 ctbc_canny = new CvTrackbarCallback2(canny);
|
|
|
+ CvTrackbar cvtb_canny = new CvTrackbar("程度", "canny边缘检测", 0, 10, ctbc_canny, temp_canny);
|
|
|
+ display("canny边缘检测");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.Laplacian:
|
|
|
+ Cv2.ImShow("Laplacian边缘检测", pictureMain);
|
|
|
+ Mat temp_Laplacian = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_Laplacian);
|
|
|
+ CvTrackbarCallback2 ctbc_Laplacian = new CvTrackbarCallback2(laplacian);
|
|
|
+ CvTrackbar cvrb_laplacian = new CvTrackbar("程度", "Laplacian边缘检测", 0, 10, ctbc_Laplacian, temp_Laplacian);
|
|
|
+ display("laplacian边缘检测");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.carve:
|
|
|
+ if (pictureMain.Channels() != 1)
|
|
|
+ {
|
|
|
+ Cv2.CvtColor(pictureMain, pictureMain, ColorConversionCodes.BGR2GRAY);
|
|
|
+ }
|
|
|
+
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ int newP = 2 * pictureMain.Get<byte>(i, j) - pictureMain.Get<byte>(i, j + 1) - pictureMain.Get<byte>(i + 1, j)+100 ;
|
|
|
+
|
|
|
+ if (newP > 255)
|
|
|
+ {
|
|
|
+ newP = 255;
|
|
|
+ }
|
|
|
+ else if (newP < 0)
|
|
|
+ {
|
|
|
+ newP = 0;
|
|
|
+ }
|
|
|
+ pictureMain.Set(i, j, (byte)newP);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("浮雕");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.rever_lr:
|
|
|
+ Mat imx_lr = new Mat(pictureMain.Size(), MatType.CV_32FC1);
|
|
|
+ Mat imy_lr = new Mat(pictureMain.Size(), MatType.CV_32FC1);
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ imx_lr.Set(i, j, (float)(pictureMain.Cols - j - 1));
|
|
|
+ imy_lr.Set(i, j, (float)i);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.Remap(pictureMain, pictureMain, imx_lr, imy_lr);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("左右反转");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.rever_tb:
|
|
|
+ Mat imx_tb = new Mat(pictureMain.Size(), MatType.CV_32FC1);
|
|
|
+ Mat imy_tb = new Mat(pictureMain.Size(), MatType.CV_32FC1);
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ imx_tb.Set(i, j, (float)j);
|
|
|
+ imy_tb.Set(i, j, (float)(pictureMain.Rows - i - 1));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.Remap(pictureMain, pictureMain, imx_tb, imy_tb);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("上下反转");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.frost:
|
|
|
+ Mat imx_frost = new Mat(pictureMain.Size(), MatType.CV_32FC1);
|
|
|
+ Mat imy_frost = new Mat(pictureMain.Size(), MatType.CV_32FC1);
|
|
|
+ Random rm = new Random();
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ imx_frost.Set(i, j, (float)(j + rm.Next(-5, 5)));
|
|
|
+ imy_frost.Set(i, j, (float)(i + rm.Next(-5, 5)));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.Remap(pictureMain, pictureMain, imx_frost, imy_frost);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("毛玻璃");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.sharp:
|
|
|
+ Mat mask = new Mat(new OpenCvSharp.Size(3, 3), MatType.CV_32FC1);
|
|
|
+ mask.Set<float>(0, 1, -1); mask.Set<float>(1, 0, -1); mask.Set<float>(1, 1, 5); mask.Set<float>(1, 2, -1); mask.Set<float>(2, 1, -1);
|
|
|
+ Mat temp_sharp = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_sharp);
|
|
|
+ Cv2.Filter2D(pictureMain, temp_sharp, -1, mask);
|
|
|
+ Cv2.WaitKey(500);
|
|
|
+ temp_sharp.CopyTo(pictureMain);
|
|
|
+ pictureShow.Image = temp_sharp.ToBitmap();
|
|
|
+ display("锐化");
|
|
|
+ mask.Release();
|
|
|
+ temp_sharp.Release();
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.dilate:
|
|
|
+ Cv2.ImShow("膨胀处理", pictureMain);
|
|
|
+ Mat temp_dilate = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_dilate);
|
|
|
+ CvTrackbarCallback2 ctbc_dilate = new CvTrackbarCallback2(dilate);
|
|
|
+ CvTrackbar cvtb_dilate = new CvTrackbar("程度", "膨胀处理", 0, 10, ctbc_dilate, temp_dilate);
|
|
|
+ display("膨胀");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.erode:
|
|
|
+ Cv2.ImShow("腐蚀处理", pictureMain);
|
|
|
+ Mat temp_erode = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_erode);
|
|
|
+ CvTrackbarCallback2 ctbc_erode = new CvTrackbarCallback2(erode);
|
|
|
+ CvTrackbar cvtb_erode = new CvTrackbar("程度", "腐蚀处理", 0, 10, ctbc_erode, temp_erode);
|
|
|
+ display("腐蚀");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.gamma:
|
|
|
+ if (pictureMain.Channels() == 1)
|
|
|
+ {
|
|
|
+ Mat temp_gray = new Mat(pictureMain.Size(), MatType.CV_16UC1);
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ temp_gray.Set(i, j, Math.Abs(pictureMain.Get<byte>(i, j) * pictureMain.Get<byte>(i, j)));//因为pictureMain为8UC1，所以这里一定要使用<byte>,不能使用其他类型
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.Normalize(temp_gray, temp_gray, 0, 255, NormTypes.MinMax);
|
|
|
+ Cv2.ConvertScaleAbs(temp_gray, temp_gray);
|
|
|
+ temp_gray.CopyTo(pictureMain);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ temp_gray.Release();
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ Mat temp_gamma = new Mat(pictureMain.Size(), MatType.CV_32FC3);
|
|
|
+ Vec3f channels = new Vec3f();
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ channels.Item0 = Math.Abs(pictureMain.Get<Vec3b>(i, j).Item0 * pictureMain.Get<Vec3b>(i, j).Item0);
|
|
|
+ channels.Item1 = Math.Abs(pictureMain.Get<Vec3b>(i, j).Item1 * pictureMain.Get<Vec3b>(i, j).Item1);
|
|
|
+ channels.Item2 = Math.Abs(pictureMain.Get<Vec3b>(i, j).Item2 * pictureMain.Get<Vec3b>(i, j).Item2);
|
|
|
+ temp_gamma.Set(i, j, channels);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.Normalize(temp_gamma, temp_gamma, 0, 255, NormTypes.MinMax);
|
|
|
+ Cv2.ConvertScaleAbs(temp_gamma, temp_gamma);
|
|
|
+ temp_gamma.CopyTo(pictureMain);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ temp_gamma.Release();
|
|
|
+ }
|
|
|
+ display("gamma调整");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.log:
|
|
|
+ Mat[] temp_log = pictureMain.Split();
|
|
|
+ for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ {
|
|
|
+ for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ {
|
|
|
+ temp_log[0].Set(i, j, Math.Log(temp_log[0].Get<float>(i, j), 1.2));
|
|
|
+ temp_log[1].Set(i, j, Math.Log(temp_log[1].Get<float>(i, j), 1.2));
|
|
|
+ temp_log[2].Set(i, j, Math.Log(temp_log[2].Get<float>(i, j), 1.2));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.Merge(temp_log, pictureMain);
|
|
|
+ Cv2.Normalize(pictureMain, pictureMain, 0, 255, NormTypes.MinMax);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+
|
|
|
+ //Mat temp_log = new Mat(pictureMain.Size(), MatType.CV_8UC3);
|
|
|
+ //pictureMain.CopyTo(temp_log);
|
|
|
+ //if (pictureMain.Channels()==3)
|
|
|
+ //{
|
|
|
+ // Vec3i channels = new Vec3i();
|
|
|
+ // for (int i = 0; i < pictureMain.Rows; i++)
|
|
|
+ // {
|
|
|
+ // for (int j = 0; j < pictureMain.Cols; j++)
|
|
|
+ // {
|
|
|
+ // //float a = pictureMain.Get<Vec3b>(i, j).Item0;
|
|
|
+ // //float b = pictureMain.Get<Vec3b>(i, j).Item1;
|
|
|
+ // //float c = pictureMain.Get<Vec3b>(i, j).Item2;
|
|
|
+ // channels.Item0 = (int)Math.Log(pictureMain.Get<Vec3b>(i, j).Item0,1.2);
|
|
|
+ // channels.Item1 = (int)Math.Log(pictureMain.Get<Vec3b>(i, j).Item1,1.2);
|
|
|
+ // channels.Item2 = (int)Math.Log(pictureMain.Get<Vec3b>(i, j).Item2,1.2);
|
|
|
+ // temp_log.Set<Vec3i>(i, j, channels);
|
|
|
+ // }
|
|
|
+ // }//这个操作有毒，不能归一化，还把GR通道置0,放弃
|
|
|
+ //temp_log.Normalize(255,0, NormTypes.MinMax);
|
|
|
+ //float e1 = temp_log.Get<Vec3b>(0,0).Item0;
|
|
|
+ //float f = temp_log.Get<Vec3b>(0,0).Item1;
|
|
|
+ //float g = temp_log.Get<Vec3b>(0, 0).Item2;
|
|
|
+ //Cv2.Normalize(temp_log, temp_log, 0, 255, NormTypes.MinMax);
|
|
|
+ //Cv2.ConvertScaleAbs(temp_log, temp_log);
|
|
|
+ //temp_log.CopyTo(pictureMain);
|
|
|
+ //pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ //temp_log.Release();
|
|
|
+
|
|
|
+ display("log亮部增强");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.tophat:
|
|
|
+ Mat temp_tophat = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_tophat);
|
|
|
+ Cv2.ImShow("顶帽处理", pictureMain);
|
|
|
+ CvTrackbarCallback2 ctbc_topat = new CvTrackbarCallback2(tophat);
|
|
|
+ CvTrackbar cvtb_tophat = new CvTrackbar("程度", "顶帽处理", 0, 20, ctbc_topat, temp_tophat);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("顶帽");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.blackhat:
|
|
|
+ Mat temp_blackhat = new Mat();
|
|
|
+ pictureMain.CopyTo(temp_blackhat);
|
|
|
+ Cv2.ImShow("黑帽处理", pictureMain);
|
|
|
+ CvTrackbarCallback2 ctbc_blackhat = new CvTrackbarCallback2(blackhat);
|
|
|
+ CvTrackbar cvtb_blackhat = new CvTrackbar("程度", "黑帽处理", 0, 20, ctbc_blackhat, temp_blackhat);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("黑帽");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.hist:
|
|
|
+ if (pictureMain.Channels() == 1)
|
|
|
+ {
|
|
|
+ Mat[] image = { pictureMain };
|
|
|
+ Mat temp_hist = pictureMain;
|
|
|
+ int[] channels = new int[] { 0 };
|
|
|
+ int[] histsize = new int[] { 256 };
|
|
|
+ Mat mask_hist = new Mat();
|
|
|
+ Mat hist = new Mat();
|
|
|
+ Rangef[] range = new Rangef[1];
|
|
|
+ range[0].Start = 0f;
|
|
|
+ range[0].End = 256f;
|
|
|
+ Cv2.CalcHist(image, channels, mask_hist, hist, 1, histsize, range);
|
|
|
+ Mat histImage = new Mat(256, 256, MatType.CV_8UC3);
|
|
|
+ double minValue, maxValue;
|
|
|
+ Cv2.MinMaxLoc(hist, out minValue, out maxValue);
|
|
|
+ for (int i = 0; i < 256; i++)
|
|
|
+ {
|
|
|
+ int len = (int)(hist.Get<float>(i) / maxValue * 256);
|
|
|
+ Cv2.Line(histImage, i, histImage.Rows, i, histImage.Rows - len, Scalar.White, 2);
|
|
|
+ }
|
|
|
+ Cv2.ImShow("灰度图像直方图", histImage);
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ Mat[] images = pictureMain.Split();
|
|
|
+ Mat[] bImage = { images[0] };
|
|
|
+ Mat[] gImage = { images[1] };
|
|
|
+ Mat[] rImage = { images[2] };
|
|
|
+
|
|
|
+ Mat mask_hist = new Mat();
|
|
|
+ Mat[] hists = { new Mat(), new Mat(), new Mat() };
|
|
|
+ int[] channels = { 0 };
|
|
|
+ int[] histSize = { 256 };
|
|
|
+ Rangef[] range = new Rangef[1];
|
|
|
+ range[0].Start = 0f;
|
|
|
+ range[0].End = 256f;
|
|
|
+ Cv2.CalcHist(bImage, channels, mask_hist, hists[0], 1, histSize, range);//dim为需要统计直方图通道的个数
|
|
|
+ Cv2.CalcHist(gImage, channels, mask_hist, hists[1], 1, histSize, range);
|
|
|
+ Cv2.CalcHist(rImage, channels, mask_hist, hists[2], 1, histSize, range);
|
|
|
+
|
|
|
+ Mat[] histImage = { new Mat(256, 256, MatType.CV_8UC3), new Mat(256, 256, MatType.CV_8UC3), new Mat(256, 256, MatType.CV_8UC3) };
|
|
|
+ Scalar[] color = { Scalar.Blue, Scalar.Green, Scalar.Red };
|
|
|
+ for (int i = 0; i < 3; i++)
|
|
|
+ {
|
|
|
+ double minVal = 0f;
|
|
|
+ double maxVal = 0f;
|
|
|
+ Cv2.MinMaxLoc(hists[i], out minVal, out maxVal);
|
|
|
+ for (int j = 0; j < 256; j++)
|
|
|
+ {
|
|
|
+ int len = (int)(hists[i].Get<float>(j) / maxVal * 256);
|
|
|
+ Cv2.Line(histImage[i], j, histImage[0].Rows, j, histImage[0].Rows - len, color[i], 2);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Cv2.ImShow("b", histImage[0]);
|
|
|
+ Cv2.ImShow("g", histImage[1]);
|
|
|
+ Cv2.ImShow("r", histImage[2]);
|
|
|
+ }
|
|
|
+ display("直方图显示");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.findContours:
|
|
|
+ MessageBox.Show("假如卡死了，是计算量太大的缘故，请重新调整canny参数一参数二，默认参数一50，参数二150");
|
|
|
+ Mat temp_find = new Mat();
|
|
|
+ if (pictureMain.Channels() == 3)
|
|
|
+ {
|
|
|
+ Cv2.CvtColor(pictureMain, temp_find, ColorConversionCodes.BGR2GRAY);
|
|
|
+ }
|
|
|
+
|
|
|
+
|
|
|
+ Cv2.Canny(temp_find, temp_find, form2Num1, form2Num2);
|
|
|
+
|
|
|
+ HierarchyIndex[] hierarchy;
|
|
|
+ OpenCvSharp.Point[][] coutours;
|
|
|
+ Cv2.FindContours(temp_find, out coutours, out hierarchy, RetrievalModes.List, ContourApproximationModes.ApproxNone);
|
|
|
+ for (int i = 0; i < coutours.Length; i++)
|
|
|
+ {
|
|
|
+ Cv2.DrawContours(pictureMain, coutours, i, Scalar.RandomColor(), 1);
|
|
|
+ }
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ display("绘制轮廓");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.template:
|
|
|
+ if (form2image != null && pictureMain.Rows > form2image.Rows && pictureMain.Cols > form2image.Cols)
|
|
|
+ {
|
|
|
+ Mat result = new Mat(pictureMain.Cols - form2image.Cols, pictureMain.Rows - form2image.Cols, MatType.CV_32FC1);
|
|
|
+ Cv2.MatchTemplate(pictureMain, form2image, result, TemplateMatchModes.CCoeff);
|
|
|
+ double maxVal, minVal;
|
|
|
+ OpenCvSharp.Point minLoc, maxLoc;
|
|
|
+ Cv2.Normalize(result, result, 0, 1, NormTypes.MinMax);
|
|
|
+ Cv2.MinMaxLoc(result, out minVal, out maxVal, out minLoc, out maxLoc);
|
|
|
+ Cv2.ImShow("匹配的图像", form2image);
|
|
|
+ pictureMain.Rectangle(maxLoc, new OpenCvSharp.Point(maxLoc.X + form2image.Cols, maxLoc.Y + form2image.Rows), Scalar.Red);
|
|
|
+ pictureShow.Image = pictureMain.ToBitmap();
|
|
|
+ textBox1.AppendText("\r\n模板匹配程度为：" + maxVal * 100 + " % ");
|
|
|
+ }
|
|
|
+ else if (form2image == null)
|
|
|
+ {
|
|
|
+ MessageBox.Show("请在窗口二中传入匹配图像");
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ MessageBox.Show("匹配图像需要比原始图像小");
|
|
|
+ }
|
|
|
+ display("模板匹配");
|
|
|
+ break;
|
|
|
+ case (int)lb1_list.drawRect:
|
|
|
+ Cv2.ImShow("最小外包矩形", pictureMain);
|
|
|
+ Mat tempRect = new Mat();
|
|
|
+ pictureMain.CopyTo(tempRect);
|
|
|
+ CvTrackbarCallback2 crbc_rect = new CvTrackbarCallback2(drawRect);
|
|
|
+ CvTrackbar cvtb_rect = new CvTrackbar("程度", "最小外包矩形", 0, 20, crbc_rect, tempRect);
|
|
|
+ MessageBox.Show("这个处理内存占用巨大，不要拖动太多次");
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ /// <summary>
|
|
|
+ /// 图像处理后更新信息
|
|
|
+ /// </summary>
|
|
|
+ /// <param name="name"></param>
|
|
|
+ public void display(string name)
|
|
|
+ {
|
|
|
+ textBox1.AppendText("\r\n图像运行"+ name+ "处理成功");
|
|
|
+ textBox1.SelectionStart = this.textBox1.TextLength;
|
|
|
+ textBox1.ScrollToCaret();
|
|
|
+ listBox2.Items.Add(num + ". "+ name);
|
|
|
+ num++;
|
|
|
+ }
|
|
|
+
|
|
|
+ private void button2_Click(object sender, EventArgs e)
|
|
|
+ {
|
|
|
+ Form2 form2 = new Form2();
|
|
|
+ form2.Show(this);
|
|
|
+ }
|
|
|
+
|
|
|
+ private void initalBtn_Click(object sender, EventArgs e)
|
|
|
+ {
|
|
|
+ pictureMain = null;
|
|
|
+ pictureShow.Image = null;
|
|
|
+ num = 1;
|
|
|
+ listBox2.Items.Clear();
|
|
|
+ textBox1.Text = "以下为通知信息：";
|
|
|
+ }
|
|
|
+ }
|
|
|
+}
|
|
|
+
|
