public List <FaceInfo> ScanFaces(Bitmap bitmap)
{
List <FaceInfo> singleFaces = new List <FaceInfo>();
if (bitmap == null)
{
return(null);
}
//从视频帧中获取 多个人脸的矩形框位置
ASF_MultiFaceInfo multiFaceInfo = FaceUtil.DetectFace(pImageEngine, bitmap);
//如果识别出人脸，且当前只有一个人脸
if (multiFaceInfo.faceNum == 1)
{
//将MultiFaceInfo结构体中的数据提取成单人脸数据并放入结构体中
for (int i = 0; i < multiFaceInfo.faceNum; i++)
{
FaceInfo faceInfo = new FaceInfo();
faceInfo.singleFaceInfo.faceRect = MemoryUtil.PtrToStructure <MRECT>(multiFaceInfo.faceRects + MemoryUtil.SizeOf <MRECT>() * i);
faceInfo.singleFaceInfo.faceOrient = MemoryUtil.PtrToStructure <int>(multiFaceInfo.faceOrients + MemoryUtil.SizeOf <int>() * i);
singleFaces.Add(faceInfo);
}
}
else
{
LoggerService.logger.Info($"当前图片中含有多个人脸或没有人脸，请重新选择单人图片，进行特征提取");
if (bitmap != null)
{
bitmap.Dispose();
Console.WriteLine("释放成功");
}
}
return(singleFaces);
}
//对每一帧的图片进行了处理，将该帧画面里检测到所有的人脸进行处理，然后进行显示
public void DetalDisplay(Image <Bgr, byte> nowFrame)
{
//如果有有效的bgr位图像则进行人工智能工作和picturView的显示
if (nowFrame != null)
{
using (Bitmap nowFrameBitmap = nowFrame.ToBitmap())
{
//将每帧图片中的人脸信息位置获取出来给faceInfos集合，视频模式会多一个faceId来唯一标识人脸
List <FaceInfo> faceInfos = faceVideoRecognizer.ScanFaces(nowFrameBitmap);
if (isRGBLock == false)
{
isRGBLock = true;
for (int i = 0; i < faceInfos.Count; i++)
{
//faceInfo 是相机所检测到的人脸信息(带feceId)都会缓存在这个列表中，faceId不变的话，faceInfo可以找到，就把当前的脸的位置替换了，
//但如果faceId变化了，就把新检测到的这张脸添加进列表
int findindex = faceInfo.FindIndex(temp => temp.faceId == faceInfos[i].faceId);
//如果当前摄像设备之前没有侦测过任何人脸，或者在设备人脸缓存中未找到匹配的Faceid
if (faceInfo.Count == 0 || findindex < 0)
{
FaceInfo tempFaceInfo = new FaceInfo();
faceInfos[i].getCopy(tempFaceInfo);
tempFaceInfo.frameNum++;
tempFaceInfo.dateTime = DateTime.Now.ToLocalTime();
faceInfo.Add(tempFaceInfo);
}
//如果在人脸缓存中有该faceid的对象
else
{
faceInfos[i].getCopy(faceInfo[findindex]);
faceInfo[findindex].frameNum++;
faceInfo[findindex].dateTime = DateTime.Now.ToLocalTime();
if (faceInfo[findindex].isFacePass == true)
{
faceInfos[i].studentId = faceInfo[findindex].studentId;
}
else
{
//如果没有比对成功，frameNum超过十次，等400ms再次提取特征值再比对，抽帧
if (faceInfo[findindex].frameNum % 10 == 0)
{
faceInfo[findindex].isGetFeature = false;
if (faceInfo[findindex].faceFeature.feature != IntPtr.Zero)
{
faceInfo[findindex].freeFeature();
}
}
}
}
}
for (int i = 0; i < faceInfo.Count; i++)
{
if ((DateTime.Now - faceInfo[i].dateTime).TotalSeconds > 5)//如果当前人脸未出现在视频中5秒则清除该人脸缓存信息
{
faceInfo[i].Dispose();
faceInfo.RemoveAt(i);
i--;
continue;
}
//camera缓冲里的照片进行遍历，没有提取过特征或者没有比对成功过
if (faceInfo[i].isGetFeature == false || faceInfo[i].isFacePass == false)
{
FaceInfo tempFaceInfo = faceInfo[i];
//提取特征值
faceVideoRecognizer.ScanFaceFeature(nowFrameBitmap, tempFaceInfo);
tempFaceInfo.isGetFeature = true;
//创建一个线程放进这个线程池（资源系统自己维护），因为人脸对比消耗时间较多
//所以将每次需要人脸比对的操作都放进一个线程中
ThreadPool.QueueUserWorkItem(new WaitCallback(delegate
{
if (tempFaceInfo.isGetFeature == true)
{
tempFaceInfo.isFacePass = compareFeature(tempFaceInfo);
//通过Http post方式 发送json数据
if (tempFaceInfo.isFacePass == true)
{
sendCheckIn(tempFaceInfo);
}
}
}));
}
}
for (int i = 0; i < faceInfos.Count; i++)
{
int x = faceInfos[i].singleFaceInfo.faceRect.left;
int width = faceInfos[i].singleFaceInfo.faceRect.right - x;
int y = faceInfos[i].singleFaceInfo.faceRect.top;
int height = faceInfos[i].singleFaceInfo.faceRect.bottom - y;
Rectangle rect = new Rectangle(x, y, width, height);
CvInvoke.Rectangle(nowFrame, rect, new MCvScalar(0, 0, 255), 3);
CvInvoke.PutText(nowFrame, $"FaceId: {faceInfos[i].faceId}, StudentId: {faceInfos[i].studentId}", new Point(x, y - 15), Emgu.CV.CvEnum.FontFace.HersheySimplex, 1, new MCvScalar(0, 0, 255), 3);
}
for (int i = 0; i < faceInfos.Count; i++)
{
faceInfos[i].Dispose();
faceInfos[i] = null;
}
faceInfos.Clear();
isRGBLock = false;
}
}
//显示到屏幕中
if (PictrueBoxId != null)
{
PictrueBoxId.Invoke(new Action(() =>
{
if (PictrueBoxId != null)
{
PictrueBoxId.Image = nowFrame;
}
PictrueBoxId.Refresh();
}));
}
}
}
