HOZ/AutoDo/FormAutoDo.cs

//时间：
//作者：
//功能：自动化测试功能
using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
using System.IO;
using OpenCvSharp;

using SmartSEMControl;


namespace AutoDo
{
    public partial class FormAutoDo : Form
    {
        //全局只有一个fatorySEM
        //static FactoryHardware factorySEM = FactoryHardware.Instance;
        //ISEMControl iSEM = factorySEM.ISEM;

        //图像文件夹
        public string  m_strImgPath;

        //显示处理结果
        public Bitmap m_bitmap; 

        public FormAutoDo()
        {
            InitializeComponent();
        }

        //自动对焦过程
        private void button1_Click(object sender, EventArgs e)
        {
            //第一种方法
            var files = Directory.GetFiles(m_strImgPath, "*.tif");

            int i = 0;
            foreach (var file in files)
            {
                LoGEdge(file);
               
            }
        }

        //选择图像文件夹
        private void button2_Click(object sender, EventArgs e)
        {
            System.Windows.Forms.FolderBrowserDialog dialog = new System.Windows.Forms.FolderBrowserDialog();
            dialog.Description = "选择拍图保存的文件夹";
            if (dialog.ShowDialog() == System.Windows.Forms.DialogResult.OK)
            {
                if (string.IsNullOrEmpty(dialog.SelectedPath))
                {
                    MessageBox.Show("图像文件夹不能为空");
                    return;
                }

                m_strImgPath = dialog.SelectedPath;
                tBImgPath.Text = dialog.SelectedPath;

            }
        }

        //LoG算子计算
        private bool LoGEdge(string a_strImgPath)
        {
            //读入Img文件
            if (!File.Exists(a_strImgPath))
            {
                return false;
            }

            Mat src, src_gray;
            int kernel_size = 3;

            src = Cv2.ImRead(a_strImgPath);
            src_gray = new Mat();

            //高斯滤波，噪声消除
            Cv2.GaussianBlur(src, src, new OpenCvSharp.Size(3, 3), 0, 0);
            //转化为灰度图像
            Cv2.CvtColor(src, src_gray, ColorConversionCodes.BayerBG2GRAY);

            Mat dst, abs_dst;
            dst = new Mat();
            abs_dst = new Mat();

            //使用Laplace函数
            Cv2.Laplacian(src_gray, dst, MatType.CV_16S, kernel_size);
            //计算绝对值，并将结果转为8位
            Cv2.ConvertScaleAbs(dst, abs_dst);            

            //进行LoG运算
            return true;
        }
      
    }
}