Exemplo n.º 1
0
        private void ProcessFrame(object sender, EventArgs arg)
        {
            Image <Bgr, Byte>  frame         = _capture.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
            Image <Gray, Byte> grayframe     = frame.Convert <Gray, Byte>();
            Image <Gray, Byte> modelImage    = new Image <Gray, byte>("DataPlate/" + 10 + ".jpg");
            Image <Gray, Byte> observedImage = grayframe;
            Stopwatch          watch;
            HomographyMatrix   homography = null;
            SURFDetector       surfCPU    = new SURFDetector(500, false);
            VectorOfKeyPoint   modelKeyPoints;
            VectorOfKeyPoint   observedKeyPoints;
            Matrix <int>       indices;
            Matrix <float>     dist;
            Matrix <byte>      mask;


            if (GpuInvoke.HasCuda)
            {
                GpuSURFDetector surfGPU = new GpuSURFDetector(surfCPU.SURFParams, 0.01f);
                using (GpuImage <Gray, Byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))

                    #region SURF
                    //extract features from the object image
                    using (GpuMat <float> gpuModelKeyPoints = surfGPU.DetectKeyPointsRaw(gpuModelImage, null))
                        using (GpuMat <float> gpuModelDescriptors = surfGPU.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
                            using (GpuBruteForceMatcher matcher = new GpuBruteForceMatcher(GpuBruteForceMatcher.DistanceType.L2))
                            {
                                modelKeyPoints = new VectorOfKeyPoint();
                                surfGPU.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
                                watch = Stopwatch.StartNew();

                                // extract features from the observed image
                                using (GpuImage <Gray, Byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
                                    using (GpuMat <float> gpuObservedKeyPoints = surfGPU.DetectKeyPointsRaw(gpuObservedImage, null))
                                        using (GpuMat <float> gpuObservedDescriptors = surfGPU.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
                                            using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, 2, 1))
                                                using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuMatchIndices.Size, 1))
                                                {
                                                    observedKeyPoints = new VectorOfKeyPoint();
                                                    surfGPU.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);
                                                    matcher.KnnMatch(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, 2, null);
                                                    indices = new Matrix <int>(gpuMatchIndices.Size);
                                                    dist    = new Matrix <float>(indices.Size);
                                                    gpuMatchIndices.Download(indices);
                                                    gpuMatchDist.Download(dist);

                                                    mask = new Matrix <byte>(dist.Rows, 1);

                                                    mask.SetValue(255);

                                                    Features2DTracker.VoteForUniqueness(dist, 0.8, mask);

                                                    int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                                                    if (nonZeroCount >= 4)
                                                    {
                                                        nonZeroCount = Features2DTracker.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                                                        if (nonZeroCount >= 4)
                                                        {
                                                            homography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3);
                                                        }
                                                    }

                                                    watch.Stop();
                                                }
                            }
                #endregion
            }
            else
            {
                //extract features from the object image
                modelKeyPoints = surfCPU.DetectKeyPointsRaw(modelImage, null);
                //MKeyPoint[] kpts = modelKeyPoints.ToArray();
                Matrix <float> modelDescriptors = surfCPU.ComputeDescriptorsRaw(modelImage, null, modelKeyPoints);
                watch = Stopwatch.StartNew();

                // extract features from the observed image
                observedKeyPoints = surfCPU.DetectKeyPointsRaw(observedImage, null);
                Matrix <float>    observedDescriptors = surfCPU.ComputeDescriptorsRaw(observedImage, null, observedKeyPoints);
                BruteForceMatcher matcher             = new BruteForceMatcher(BruteForceMatcher.DistanceType.L2F32);
                matcher.Add(modelDescriptors);
                int k = 2;
                indices = new Matrix <int>(observedDescriptors.Rows, k);

                dist = new Matrix <float>(observedDescriptors.Rows, k);
                matcher.KnnMatch(observedDescriptors, indices, dist, k, null);

                mask = new Matrix <byte>(dist.Rows, 1);

                mask.SetValue(255);

                Features2DTracker.VoteForUniqueness(dist, 0.8, mask);

                int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                if (nonZeroCount >= 20)
                {
                    nonZeroCount = Features2DTracker.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                    if (nonZeroCount >= 20)
                    {
                        homography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3);
                        XMLData();
                    }
                    else
                    {
                        textBox1.Text = string.Empty;
                        textBox2.Text = string.Empty;
                        textBox3.Text = string.Empty;
                        textBox4.Text = string.Empty;
                        textBox5.Text = string.Empty;
                    }
                }
                watch.Stop();
                #region draw the projected region on the image
                if (homography != null)
                {  //draw a rectangle along the projected model
                    Rectangle rect = modelImage.ROI;
                    PointF[]  pts  = new PointF[] {
                        new PointF(rect.Left, rect.Bottom),
                        new PointF(rect.Right, rect.Bottom),
                        new PointF(rect.Right, rect.Top),
                        new PointF(rect.Left, rect.Top)
                    };
                    homography.ProjectPoints(pts);
                    frame.DrawPolyline(Array.ConvertAll <PointF, Point>(pts, Point.Round), true, new Bgr(Color.Red), 2);
                }
                #endregion
                CaptureImageBox.Image = frame;
                DataImageBox.Image    = modelImage;
            }
        }
Exemplo n.º 2
0
        static void Run()
        {
            Image <Gray, Byte> modelImage    = new Image <Gray, byte>("box.png");
            Image <Gray, Byte> observedImage = new Image <Gray, byte>("box_in_scene.png");
            Stopwatch          watch;
            HomographyMatrix   homography = null;

            SURFDetector surfCPU = new SURFDetector(500, false);

            VectorOfKeyPoint modelKeyPoints;
            VectorOfKeyPoint observedKeyPoints;
            Matrix <int>     indices;
            Matrix <float>   dist;
            Matrix <byte>    mask;

            if (GpuInvoke.HasCuda)
            {
                GpuSURFDetector surfGPU = new GpuSURFDetector(surfCPU.SURFParams, 0.01f);
                using (GpuImage <Gray, Byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))
                    //extract features from the object image
                    using (GpuMat <float> gpuModelKeyPoints = surfGPU.DetectKeyPointsRaw(gpuModelImage, null))
                        using (GpuMat <float> gpuModelDescriptors = surfGPU.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
                            using (GpuBruteForceMatcher matcher = new GpuBruteForceMatcher(GpuBruteForceMatcher.DistanceType.L2))
                            {
                                modelKeyPoints = new VectorOfKeyPoint();
                                surfGPU.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
                                watch = Stopwatch.StartNew();

                                // extract features from the observed image
                                using (GpuImage <Gray, Byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
                                    using (GpuMat <float> gpuObservedKeyPoints = surfGPU.DetectKeyPointsRaw(gpuObservedImage, null))
                                        using (GpuMat <float> gpuObservedDescriptors = surfGPU.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
                                            using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, 2, 1))
                                                using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuMatchIndices.Size, 1))
                                                {
                                                    observedKeyPoints = new VectorOfKeyPoint();
                                                    surfGPU.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);

                                                    matcher.KnnMatch(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, 2, null);

                                                    indices = new Matrix <int>(gpuMatchIndices.Size);
                                                    dist    = new Matrix <float>(indices.Size);
                                                    gpuMatchIndices.Download(indices);
                                                    gpuMatchDist.Download(dist);

                                                    mask = new Matrix <byte>(dist.Rows, 1);

                                                    mask.SetValue(255);

                                                    Features2DTracker.VoteForUniqueness(dist, 0.8, mask);

                                                    int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                                                    if (nonZeroCount >= 4)
                                                    {
                                                        nonZeroCount = Features2DTracker.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                                                        if (nonZeroCount >= 4)
                                                        {
                                                            homography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3);
                                                        }
                                                    }

                                                    watch.Stop();
                                                }
                            }
            }
            else
            {
                //extract features from the object image
                modelKeyPoints = surfCPU.DetectKeyPointsRaw(modelImage, null);
                //MKeyPoint[] kpts = modelKeyPoints.ToArray();
                Matrix <float> modelDescriptors = surfCPU.ComputeDescriptorsRaw(modelImage, null, modelKeyPoints);

                watch = Stopwatch.StartNew();

                // extract features from the observed image
                observedKeyPoints = surfCPU.DetectKeyPointsRaw(observedImage, null);
                Matrix <float> observedDescriptors = surfCPU.ComputeDescriptorsRaw(observedImage, null, observedKeyPoints);

                BruteForceMatcher matcher = new BruteForceMatcher(BruteForceMatcher.DistanceType.L2F32);
                matcher.Add(modelDescriptors);
                int k = 2;
                indices = new Matrix <int>(observedDescriptors.Rows, k);
                dist    = new Matrix <float>(observedDescriptors.Rows, k);
                matcher.KnnMatch(observedDescriptors, indices, dist, k, null);

                mask = new Matrix <byte>(dist.Rows, 1);

                mask.SetValue(255);

                Features2DTracker.VoteForUniqueness(dist, 0.8, mask);

                int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                if (nonZeroCount >= 4)
                {
                    nonZeroCount = Features2DTracker.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                    if (nonZeroCount >= 4)
                    {
                        homography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3);
                    }
                }

                watch.Stop();
            }

            //Draw the matched keypoints
            Image <Bgr, Byte> result = Features2DTracker.DrawMatches(modelImage, modelKeyPoints, observedImage, observedKeyPoints,
                                                                     indices, new Bgr(255, 255, 255), new Bgr(255, 255, 255), mask, Features2DTracker.KeypointDrawType.NOT_DRAW_SINGLE_POINTS);

            #region draw the projected region on the image
            if (homography != null)
            { //draw a rectangle along the projected model
                Rectangle rect = modelImage.ROI;
                PointF[]  pts  = new PointF[] {
                    new PointF(rect.Left, rect.Bottom),
                    new PointF(rect.Right, rect.Bottom),
                    new PointF(rect.Right, rect.Top),
                    new PointF(rect.Left, rect.Top)
                };
                homography.ProjectPoints(pts);

                result.DrawPolyline(Array.ConvertAll <PointF, Point>(pts, Point.Round), true, new Bgr(Color.Red), 5);
            }
            #endregion

            ImageViewer.Show(result, String.Format("Matched using {0} in {1} milliseconds", GpuInvoke.HasCuda ? "GPU" : "CPU", watch.ElapsedMilliseconds));
        }