private void FaceDetect_Click(object sender, EventArgs e)
{
if (!sw.IsRunning)
{
sw.Reset();
sw.Start();
}
Process.Image = Image.FromFile(filepath, true);
if (bvis == false)
{
bvis = true;
}
else
{
bvis = false;
}
GridOn.GridPaint(bvis, (Bitmap)Process.Image);//绘制网格线
label3.Text = "网络线划分";
try {
Bitmap gray_img = Knowledge.ToGray(originalimg); //将原图转化为灰度图
Bitmap BW = Knowledge.Thresholding(gray_img); //利用大津法进行二值化处理
Bitmap detectimg = Knowledge.FaceDetection(BW); //最后利用算法进行检测
AForge.Imaging.BlobCounter blobCounter = new AForge.Imaging.BlobCounter(detectimg);
Rectangle[] rects = blobCounter.GetObjectsRectangles();
Rectangle[] outputrects = new Rectangle[rects.Count()];
////object count
int minx = 100; int tmp = 0;
int rectsCount = rects.Count();
List <decimal> test = new List <decimal>();
for (int c = 0; c < rectsCount; c++)
{
int p = rects[c].Width * rects[c].Height;
decimal bl = (decimal)rects[c].Height / (decimal)rects[c].Width;
int maxx = (gray_img.Width * gray_img.Height) / 2;
if (p > minx && (double)bl < 1.8 && (double)bl > 0.8 && p < maxx)
{
test.Add(bl);
outputrects[tmp++] = rects[c];
}
}
RectanglesMarker marker = new RectanglesMarker(outputrects, Color.Red);
this.Detected.Image = marker.Apply((Bitmap)Image.FromFile(filepath, true));
label4.Text = "检测结果";
ShowMsg("检测结束！");
}
catch (ArgumentException)
{
MessageBox.Show("Invalid usage!");
}
if (sw.IsRunning)
{
sw.Stop();
string str = sw.Elapsed.ToString();
timeElpse.Text = string.Empty;
timeElpse.Text = "运行时间：" + str;
}
}
private void skindetect_Click(object sender, EventArgs e)
{
sw.Reset();
sw.Start();
Bitmap img = (Bitmap)Image.FromFile(filepath, true); //将原图进行导入并进行格式转化
Bitmap normalizedImg = YCbCr.Lightingconpensate(img);
Bitmap skin = YCbCr.SkinDetect1(normalizedImg); //肤色检测
Bitmap BWskin = Knowledge.Thresholding(skin); //图片二值化
Bitmap gray_img = Knowledge.ToGray(img);
AForge.Imaging.SusanCornersDetector scd = new AForge.Imaging.SusanCornersDetector(); //susan检测子
//检测人眼部分
AForge.Imaging.BlobCounter blobCounter = new AForge.Imaging.BlobCounter(BWskin); //对图片进行检测联通区域
Rectangle[] rects = blobCounter.GetObjectsRectangles();
Rectangle[] outputrects = new Rectangle[rects.Count()];
////object count
int minx = 150; int tmp = 0;
int rectsCount = rects.Count();
List <decimal> test = new List <decimal>();
for (int c = 0; c < rectsCount; c++)
{
int p = rects[c].Width * rects[c].Height;
decimal bl = (decimal)rects[c].Height / (decimal)rects[c].Width;
int maxx = (img.Width * img.Height) / 2;
if (p > minx && (double)bl < 1.8 && (double)bl > 0.9 && p < maxx)
{
test.Add(bl);
outputrects[tmp++] = rects[c];
}
}
RectanglesMarker marker = new RectanglesMarker(outputrects, Color.Red);
Process2.Image = img;
Detected.Image = marker.Apply((Bitmap)Image.FromFile(filepath, true));
sw.Stop();
string str = sw.Elapsed.ToString();
timeElpsed.Text = string.Empty;
timeElpsed.Text = "运行时间：" + str;
}
