//更改参数再次分割图片
private void button4_Click(object sender, EventArgs e)
{
if (comboBox1.Text == "grabcut" && value1.Text == "迭代次数：" && value2.Text == "分割算子：")
{
try
{
int iter_count = int.Parse(textBox5.Text);
GrabCutModes grabcutmode = (GrabCutModes)(Enum.Parse(typeof(GrabCutModes), comboBox4.Text));
int x = int.Parse(textBox7.Text);
int y = int.Parse(textBox8.Text);
int w = int.Parse(textBox9.Text);
int h = int.Parse(textBox10.Text);
if (iter_count > 20 || iter_count < 0)
{
MessageBox.Show("迭代次数于0-20次之内较为合适");
}
else
{
System.Drawing.Bitmap bitmap = (System.Drawing.Bitmap)pictureBox1.Image;
Mat image = BitmapConverter.ToMat(bitmap);
double startTime = Cv2.GetTickCount();
Mat res = grabCut(image, iter_count, grabcutmode, x, y, w, h);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("迭代次数：", iter_count.ToString(), "分割算子：", grabcutmode.ToString());
textBox6.Hide();
showRect(x, y, w, h);
}
}
catch (Exception err)
{
if (err.ToString().Contains("totalSampleCount"))
{
MessageBox.Show("您选择的区域无法分割出前景，无法分割，请重新选择区域大小");
}
else if (err.ToString().Contains("mask"))
{
MessageBox.Show("掩模mask为空，无法分割");
}
else if (err.ToString().Contains("Format"))
{
MessageBox.Show("输入的字符串格式不正确，请重新输入");
}
}
}
if (comboBox1.Text == "watershed" && value1.Text == "中值滤波内核：" && value2.Text == "形态学卷积核：")
{
try
{
if (int.Parse(textBox5.Text) % 2 == 0)
{
MessageBox.Show("中值滤波内核应为奇数，请重新输入。");
}
else
{
int meadianblur_ksize = int.Parse(textBox5.Text);
if (meadianblur_ksize > 1000 || meadianblur_ksize < 0)
{
MessageBox.Show("数值不合理，请重新输入适当的数值");
}
else
{
string text = textBox6.Text;
string diff11 = text.Replace("(", string.Empty);
string diff12 = diff11.Replace(")", string.Empty);
string[] str = diff12.Split(',');
Size element_size = new Size(int.Parse(str[0]), int.Parse(str[1]));
System.Drawing.Bitmap bitmap = (System.Drawing.Bitmap)pictureBox1.Image;
Mat image = BitmapConverter.ToMat(bitmap);
double startTime = Cv2.GetTickCount();
Mat result = waterShed(image, meadianblur_ksize, element_size);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(result, duration);
showParameters("中值滤波内核：", meadianblur_ksize.ToString(), "形态学卷积核：", "(" + element_size.Width.ToString() + "," + element_size.Height.ToString() + ")");
}
}
}
catch (Exception err)
{
if (err.ToString().Contains("Format"))
{
MessageBox.Show("输入的字符串格式不正确，请重新输入");
}
else if (err.ToString().Contains("索引超出了数组界限"))
{
MessageBox.Show("形态学卷积内核应用英文括号隔开");
}
else
{
MessageBox.Show(err.ToString());
}
}
}
if (comboBox1.Text == "meanshift" && value1.Text == "颜色域半径：" && value2.Text == "空间域半径：")
{
try
{
int meanshift_sp = int.Parse(textBox5.Text);
int meanshift_sr = int.Parse(textBox6.Text);
if (meanshift_sp < 0 || meanshift_sr < 0 || meanshift_sp > 1000 || meanshift_sr > 1000)
{
MessageBox.Show("参数有误或数值过大，请重新输入数据");
}
else
{
System.Drawing.Bitmap bitmap = (System.Drawing.Bitmap)pictureBox1.Image;
Mat image = BitmapConverter.ToMat(bitmap);
double startTime = Cv2.GetTickCount();
Mat res = meanShift(image, meanshift_sp, meanshift_sr);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("颜色域半径：", meanshift_sp.ToString(), "空间域半径：", meanshift_sr.ToString());
}
}
catch (Exception err)
{
if (err.ToString().Contains("Format"))
{
MessageBox.Show("输入的字符串格式不正确，请重新输入");
}
else
{
MessageBox.Show(err.ToString());
}
}
}
if (comboBox1.Text == "floodfill" && value1.Text == "像素最大下行差异值：" && value2.Text == "像素最大上行差异值：")
{
try
{
string diff1 = textBox5.Text;
string diff11 = diff1.Replace("[", string.Empty);
string diff12 = diff11.Replace("]", string.Empty);
string[] str1 = diff12.Split(',');
Scalar lodiff = new Scalar(int.Parse(str1[0]), int.Parse(str1[1]), int.Parse(str1[2]), int.Parse(str1[3]));
string diff2 = textBox6.Text;
string diff21 = diff2.Replace("[", string.Empty);
string diff22 = diff21.Replace("]", string.Empty);
string[] str2 = diff22.Split(',');
int x = int.Parse(textBox7.Text);
int y = int.Parse(textBox8.Text);
int w = int.Parse(textBox9.Text);
int h = int.Parse(textBox10.Text);
Scalar updiff = new Scalar(int.Parse(str2[0]), int.Parse(str2[1]), int.Parse(str2[2]), int.Parse(str2[3]));
System.Drawing.Bitmap bitmap = (System.Drawing.Bitmap)pictureBox1.Image;
Mat image = BitmapConverter.ToMat(bitmap);
double startTime = Cv2.GetTickCount();
Mat res = floodFill(image, lodiff, updiff, x, y, w, h);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showRect(x, y, w, h);
showParameters("像素最大下行差异值：", lodiff.ToString(), "像素最大上行差异值：", updiff.ToString());
}
catch (Exception err)
{
if (err.ToString().Contains("Format"))
{
MessageBox.Show("输入的字符串格式不正确，请重新输入(应输入英文逗号)");
}
else if (err.ToString().Contains("索引超出了数组界限"))
{
MessageBox.Show("像素最大下(上)行差异值应用英文括号隔开");
}
else
{
MessageBox.Show(err.ToString());
}
}
}
if (comboBox1.Text == "contour" && value1.Text == "高斯核x方向标准差:" && value2.Text == "二值化算子:")
{
try
{
ThresholdTypes contour_type = (ThresholdTypes)(Enum.Parse(typeof(ThresholdTypes), comboBox4.Text));
int sigmax = int.Parse(textBox5.Text);
System.Drawing.Bitmap bitmap = (System.Drawing.Bitmap)pictureBox1.Image;
Mat image = BitmapConverter.ToMat(bitmap);
double startTime = Cv2.GetTickCount();
Mat res = contourSeg(image, contour_type, sigmax);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("高斯核x方向标准差:", sigmax.ToString(), "二值化算子:", contour_type.ToString());
textBox6.Hide();
}
catch (Exception err)
{
if (err.ToString().Contains("Format"))
{
MessageBox.Show("输入的字符串格式不正确，请重新输入");
}
else if (err.ToString().Contains("索引超出了数组界限"))
{
MessageBox.Show("索引超出了数组界限，无法分割");
}
else
{
MessageBox.Show(err.ToString());
}
}
}
}
//图像分割操作
private void button2_Click(object sender, EventArgs e)
{
panel1.Hide();
value1.Hide();
value2.Hide();
textBox5.Hide();
textBox6.Hide();
button4.Hide();
comboBox4.Hide();
textBox1.Text = string.Empty;
textBox2.Text = string.Empty;
textBox3.Text = string.Empty;
textBox4.Text = string.Empty;
if (comboBox1.Text == string.Empty)
{
MessageBox.Show("请先选择您所需要的算法。");
}
else
{
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.Filter = "图片文件|*.bmp;*.ico;*.jpeg;*.jpg;*.png;*.tif;*.tiff";
openFileDialog.ShowDialog();
string fileName1 = openFileDialog.FileName;
if (fileName1 != string.Empty)
{
button4.Show();
pictureBox1.ImageLocation = fileName1;
Mat image = Cv2.ImRead(fileName1);
Mat grayImage = new Mat();
Mat binImage = new Mat();
//自适应阈值分割函数
if (comboBox1.Text == "adaptiveThreshold")
{
if (comboBox2.Text == "THRESH_BINARY")
{
if (comboBox3.Text == "ADAPTIVE_THRESH_MEAN_C")
{
double startTime = Cv2.GetTickCount();
AdaptiveThreshold(image, grayImage, binImage, AdaptiveThresholdTypes.MeanC, ThresholdTypes.Binary);//自适应阈值分割函数
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(binImage, duration);
}
if (comboBox3.Text == "ADAPTIVE_THRESH_GAUSSIAN_C")
{
double startTime = Cv2.GetTickCount();
AdaptiveThreshold(image, grayImage, binImage, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.Binary);//自适应阈值分割函数
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(binImage, duration);
}
}
if (comboBox2.Text == "THRESH_BINARY_INV")
{
if (comboBox3.Text == "ADAPTIVE_THRESH_MEAN_C")
{
double startTime = Cv2.GetTickCount();
AdaptiveThreshold(image, grayImage, binImage, AdaptiveThresholdTypes.MeanC, ThresholdTypes.BinaryInv);//自适应阈值分割函数
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(binImage, duration);
}
if (comboBox3.Text == "ADAPTIVE_THRESH_GAUSSIAN_C")
{
double startTime = Cv2.GetTickCount();
AdaptiveThreshold(image, grayImage, binImage, AdaptiveThresholdTypes.GaussianC, ThresholdTypes.BinaryInv);//自适应阈值分割函数 //算法结束
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(binImage, duration);
}
}
else if (comboBox2.Text == string.Empty || comboBox3.Text == string.Empty)
{
button4.Hide();
MessageBox.Show("请选择参数一和参数二再进行分割");
}
panel1.Hide();
value1.Hide();
value2.Hide();
textBox5.Hide();
textBox6.Hide();
button4.Hide();
}
//grabcut函数迭代五次
else if (comboBox1.Text == "grabcut")
{
comboBox2.Text = string.Empty;
comboBox3.Text = string.Empty;
try
{
double startTime = Cv2.GetTickCount();
Mat res = grabCut(image, ITER_COUNT, GRABCUTMODE, 20, 30, image.Cols - (20 << 1), image.Rows - 30);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("迭代次数：", ITER_COUNT.ToString(), "分割算子：", GRABCUTMODE.ToString());
textBox6.Hide();
comboBox4.Show();
comboBox4.Items.Clear();
comboBox4.Text = GRABCUTMODE.ToString();
comboBox4.Items.Add("InitWithRect");
comboBox4.Items.Add("InitWithMask");
comboBox4.Items.Add("Eval");
}
catch (Exception err)
{
if (err.ToString().Contains("totalSampleCount"))
{
MessageBox.Show("您选择的区域无法分割出前景，无法分割，请重新选择区域大小");
}
else
{
MessageBox.Show(err.ToString());
}
}
}
//分水岭
else if (comboBox1.Text == "watershed")
{
comboBox2.Text = string.Empty;
comboBox3.Text = string.Empty;
try
{
double startTime = Cv2.GetTickCount();
Mat result = waterShed(image, MEADIANBlUR_KSIZE, ELEMENT_SIZE);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(result, duration);
showParameters("中值滤波内核：", MEADIANBlUR_KSIZE.ToString(), "形态学卷积核：", "(" + ELEMENT_SIZE.Width.ToString() + "," + ELEMENT_SIZE.Height.ToString() + ")");
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
}
}
//均值漂移
else if (comboBox1.Text == "meanshift")
{
comboBox2.Text = string.Empty;
comboBox3.Text = string.Empty;
try
{
double startTime = Cv2.GetTickCount();
Mat res = meanShift(image, MEANSHIFT_SP, MEANSHIFT_SR);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("颜色域半径：", MEANSHIFT_SP.ToString(), "空间域半径：", MEANSHIFT_SR.ToString());
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
}
}
//漫水填充分割
else if (comboBox1.Text == "floodfill")
{
comboBox2.Text = string.Empty;
comboBox3.Text = string.Empty;
try
{
double startTime = Cv2.GetTickCount();
Mat res = floodFill(image, LODIFF, UPDIFF, 20, 30, image.Cols - (20 << 1), image.Rows - 30);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("像素最大下行差异值：", LODIFF.ToString(), "像素最大上行差异值：", UPDIFF.ToString());
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
}
}
//通过轮廓分割图像
else if (comboBox1.Text == "contour")
{
comboBox2.Text = string.Empty;
comboBox3.Text = string.Empty;
try
{
double startTime = Cv2.GetTickCount();
Mat res = contourSeg(image, CONTOUR_TYPE, SIGMAX);
double duration = (Cv2.GetTickCount() - startTime) / (Cv2.GetTickFrequency());
showImage(res, duration);
showParameters("高斯核x方向标准差:", SIGMAX.ToString(), "二值化算子:", CONTOUR_TYPE.ToString());
textBox6.Hide();
comboBox4.Show();
comboBox4.Items.Clear();
comboBox4.Text = CONTOUR_TYPE.ToString();
comboBox4.Items.Add("Binary");
comboBox4.Items.Add("BinaryInv");
comboBox4.Items.Add("Trunc");
comboBox4.Items.Add("Tozero");
comboBox4.Items.Add("TozeroInv");
comboBox4.Items.Add("Mask");
comboBox4.Items.Add("Otsu");
comboBox4.Items.Add("Triangle");
}
catch (Exception err)
{
MessageBox.Show(err.ToString());
}
}
//异常处理
else
{
MessageBox.Show("算法选择有误，请重新选择算法和正确的参数");
}
}
}
}
