Exemplo n.º 1
0
        private Mat detectFace(Mat image)
        {
            long             detectionTime;
            List <Rectangle> faces      = new List <Rectangle>();
            bool             tryUseCuda = true;

            DetectFace.Detect(image, "haarcascade_frontalface_default.xml", faces, tryUseCuda, out detectionTime);

            foreach (Rectangle face in faces)
            {
                CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
            }
            return(image);
        }
Exemplo n.º 2
0
        private void ProcessFrame(object sender, EventArgs e)
        {
            Mat image = new Mat();

            _capture.Retrieve(image);
            if (_forgroundDetector == null)
            {
                _forgroundDetector = new BackgroundSubtractorMOG2();
            }

            _forgroundDetector.Apply(image, _forgroundMask);

            //update the motion history
            _motionHistory.Update(_forgroundMask);

            #region get a copy of the motion mask and enhance its color
            double[] minValues, maxValues;
            Point[]  minLoc, maxLoc;
            _motionHistory.Mask.MinMax(out minValues, out maxValues, out minLoc, out maxLoc);
            Mat motionMask = new Mat();
            using (ScalarArray sa = new ScalarArray(255.0 / maxValues[0]))
                CvInvoke.Multiply(_motionHistory.Mask, sa, motionMask, 1, DepthType.Cv8U);
            //Image<Gray, Byte> motionMask = _motionHistory.Mask.Mul(255.0 / maxValues[0]);
            #endregion

            //DetectFace.Detect(image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml", faces, eyes, tryUseCuda, out detectionTime);
            //create the motion image
            Mat motionImage = new Mat(motionMask.Size.Height, motionMask.Size.Width, DepthType.Cv8U, 3);
            //display the motion pixels in blue (first channel)
            //motionImage[0] = motionMask;
            CvInvoke.InsertChannel(motionMask, motionImage, 0);

            //Threshold to define a motion area, reduce the value to detect smaller motion
            double minArea = 100;

            //storage.Clear(); //clear the storage
            Rectangle[] rects;
            using (VectorOfRect boundingRect = new VectorOfRect())
            {
                _motionHistory.GetMotionComponents(_segMask, boundingRect);
                rects = boundingRect.ToArray();
            }
            List <Rectangle> Availablerects = new List <Rectangle>();
            foreach (Rectangle comp in rects)
            {
                int area = comp.Width * comp.Height;
                //reject the components that have small area;
                if (area < minArea)
                {
                    continue;
                }
                double angle, motionPixelCount;
                _motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);
                //reject the area that contains too few motion
                if (motionPixelCount < area * size)
                {
                    continue;
                }
                else
                {
                    Availablerects.Add(comp);
                }
            }

            //iterate through each of the motion component
            List <Rectangle> faces = new List <Rectangle>();
            List <Rectangle> eyes  = new List <Rectangle>();
            Task             task2 = new Task(() =>
            {
                Mat Detectmat = new Mat();
                Detectmat     = image;
                DetectFace.Detect(Detectmat, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml", faces, eyes, tryUseCuda, out detectionTime);
                if (faces.Count > 0)
                {
                    label1.Text = "detectionTime:" + detectionTime.ToString();
                    for (int i = 0; i < faces.Count; i++)
                    {
                        Bitmap bt2 = DetectFace.Cutbitmap(Detectmat.Bitmap, faces[i].X, faces[i].Y, faces[i].Width, faces[i].Height);
                        Emgu.CV.Image <Bgr, Byte> currentFrame1 = new Emgu.CV.Image <Bgr, Byte>(bt2); //只能这么转
                        Mat invert1 = new Mat();
                        CvInvoke.BitwiseAnd(currentFrame1, currentFrame1, invert1);                   //这是官网上的方法,变通用。没看到提供其它方法直接转换的。
                        faceimage.Image = invert1;
                        string filePath = "G:\\motion1\\" + DateTime.Now.ToString("人脸-yyyy年MM月dd日HH点mm分ss秒") + i.ToString() + "-" + faces.Count.ToString() + ".jpg";
                        bt2.Save(filePath);
                        System.Media.SystemSounds.Beep.Play();
                    }
                    Bitmap bt1       = Detectmat.Bitmap;
                    string filePath2 = "G:\\motion1\\" + DateTime.Now.ToString("原图-yyyy年MM月dd日HH点mm分ss秒") + ".jpg";
                    //System.Diagnostics.Debug.WriteLine("准备保存原图" + detectionTime.ToString());
                    bt1.Save(filePath2);
                }
            });
            task2.Start();

            foreach (Rectangle comp in Availablerects)
            {
                int area = comp.Width * comp.Height;
                //reject the components that have small area;
                if (area < minArea)
                {
                    continue;
                }



                // find the angle and motion pixel count of the specific area
                double angle, motionPixelCount;
                _motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);

                //reject the area that contains too few motion
                if (motionPixelCount < area * size)
                {
                    continue;
                }

                //Draw each individual motion in red

                //=================转换mat格式为bitmap并裁切===========================
                Task task = new Task(() =>
                {
                    Bitmap bt = DetectFace.Cutbitmap(image.Bitmap, comp.X, comp.Y, comp.Width, comp.Height);
                    Emgu.CV.Image <Bgr, Byte> currentFrame = new Emgu.CV.Image <Bgr, Byte>(bt); //只能这么转
                    Mat invert = new Mat();
                    CvInvoke.BitwiseAnd(currentFrame, currentFrame, invert);                    //这是官网上的方法,变通用。没看到提供其它方法直接转换的。
                    moveimage.Image = invert;
                });
                task.Start();
                try
                {
                    DrawMotion(motionImage, comp, angle, new Bgr(Color.Red));
                    DrawMotion(capturedImageBox.Image, comp, angle, new Bgr(Color.Red));
                }
                catch (Exception a)
                {
                }

                #region//area

                /*
                 * bool time = false;
                 * if ((comp.X > 1770 && comp.X < 1830) && (comp.Y > 2 && comp.Y < 40))
                 * {
                 *  time = true;
                 * }
                 * if (youxiaorects.Count < 50&&!time)
                 * {
                 *  if (capturedImageBox.Image != null)
                 *  {
                 *      Random rd = new Random();
                 *      Bitmap bt = new Bitmap(capturedImageBox.Image.Bitmap);
                 *   //   string filePath = "G:\\motion\\" + DateTime.Now.ToString("yyyy年MM月dd日HH点mm分ss秒") + ".jpg";
                 *   //   image.Save(filePath);
                 *
                 *  }
                 * }
                 */
                #endregion
            }

            #region//垃圾堆
            //=================当检测到图像更变,获取更变区域坐标与大小时,尝试将更变区域保存 传入人脸识别函数分析=====================
            //===============根据更变区域个数来动态创建线程,增加效率======================

            /*   Thread[] downloadThread;
             * Thread face=new Thread(confirmface);
             * face.Start();*/
            /*  int areacount = Availablerects.Count;
             * //声名下载线程,这是C#的优势,即数组初始化时,不需要指定其长度,可以在使用时才指定。
             *
             * //这个声名应为类级,这样也就为其它方法控件它们提供了可能
             *
             * ThreadStart startDownload = new ThreadStart(confirmface);
             * //线程起始设置:即每个线程都执行DownLoad()
             * downloadThread = new Thread[areacount];//为线程申请资源,确定线程总数
             * for (int k = 0; k < areacount; k++)//开启指定数量的线程数
             * {
             *    downloadThread[k] = new Thread(startDownload);//指定线程起始设置
             *    downloadThread[k].Start();//逐个开启线程
             * }*/
            #endregion

            #region//_forgroundMask

            /*
             * // find and draw the overall motion angle
             * double overallAngle, overallMotionPixelCount;
             *
             * _motionHistory.MotionInfo(_forgroundMask, new Rectangle(Point.Empty, motionMask.Size), out overallAngle, out overallMotionPixelCount);
             * // DrawMotion(motionImage, new Rectangle(Point.Empty, motionMask.Size), overallAngle, new Bgr(Color.Green));
             * // DrawMotion(image, new Rectangle(Point.Empty, image.Size), overallAngle, new Bgr(Color.Green));
             * if (this.Disposing || this.IsDisposed)
             *   return;
             */
            /*  foreach (Rectangle face in faces)
             *    CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
             * foreach (Rectangle eye in eyes)
             *    CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);*/
            capturedImageBox.Image = image;
            // forgroundImageBox.Image = _forgroundMask;

            //Display the amount of motions found on the current image
            //UpdateText(String.Format("Total Motions found: {0}; Motion Pixel count: {1} detectionTime:{2} ", rects.Length, overallMotionPixelCount, detectionTime));

            //Display the image of the motion
            //  motionImageBox.Image = motionImage;


            #endregion
        }