C# CvMat.DrawRect方法代码示例

 void DrawROIBox(CvMat _image)
 {
     _image.DrawRect(_rectToTrack, CvColor.Snow);
     Cv.ShowImage("ROI", _image);
 }

    //  Use the CamShift algorithm to track to base histogram throughout the
    // succeeding frames
    void CalculateCamShift(CvMat _image)
    {
        CvMat _backProject = CalculateBackProjection(_image, _histogramToTrack);

        // Create convolution kernel for erosion and dilation
        IplConvKernel elementErode = Cv.CreateStructuringElementEx(10, 10, 5, 5, ElementShape.Rect, null);
        IplConvKernel elementDilate = Cv.CreateStructuringElementEx(4, 4, 2, 2, ElementShape.Rect, null);

        // Try eroding and then dilating the back projection
        // Hopefully this will get rid of the noise in favor of the blob objects.
        Cv.Erode(_backProject, _backProject, elementErode, 1);
        Cv.Dilate(_backProject, _backProject, elementDilate, 1);

        if (backprojWindowFlag)
        {
            Cv.ShowImage("Back Projection", _backProject);
        }

        // Parameters returned by Camshift algorithm
        CvBox2D _outBox;
        CvConnectedComp _connectComp;

        // Set the criteria for the CamShift algorithm
        // Maximum 10 iterations and at least 1 pixel change in centroid
        CvTermCriteria term_criteria = Cv.TermCriteria(CriteriaType.Iteration | CriteriaType.Epsilon, 10, 1);

        // Draw object center based on Kalman filter prediction
        CvMat _kalmanPrediction = _kalman.Predict();

        int predictX = Mathf.FloorToInt((float)_kalmanPrediction.GetReal2D(0, 0));
        int predictY = Mathf.FloorToInt((float)_kalmanPrediction.GetReal2D(1, 0));

        // Run the CamShift algorithm
        if (Cv.CamShift(_backProject, _rectToTrack, term_criteria, out _connectComp, out _outBox) > 0)
        {

            // Use the CamShift estimate of the object center to update the Kalman model
            CvMat _kalmanMeasurement = Cv.CreateMat(2, 1, MatrixType.F32C1);
            // Update Kalman model with raw data from Camshift estimate
            _kalmanMeasurement.Set2D(0, 0, _outBox.Center.X); // Raw X position
            _kalmanMeasurement.Set2D(1, 0, _outBox.Center.Y); // Raw Y position
            //_kalmanMeasurement.Set2D (2, 0, _outBox.Center.X - lastPosition.X);
            //_kalmanMeasurement.Set2D (3, 0, _outBox.Center.Y - lastPosition.Y);

            lastPosition.X = Mathf.FloorToInt(_outBox.Center.X);
            lastPosition.Y = Mathf.FloorToInt(_outBox.Center.Y);

            _kalman.Correct(_kalmanMeasurement); // Correct Kalman model with raw data

            // CamShift function returns two values: _connectComp and _outBox.

            //	_connectComp contains is the newly estimated position and size
            //  of the region of interest. This is passed into the subsequent
            // call to CamShift
            // Update the ROI rectangle with CamShift's new estimate of the ROI
            _rectToTrack = CheckROIBounds(_connectComp.Rect);

            // Draw a rectangle over the tracked ROI
            // This method will draw the rectangle but won't rotate it.
            _image.DrawRect(_rectToTrack, CvColor.Aqua);
            _image.DrawMarker(predictX, predictY, CvColor.Aqua);

            // _outBox contains a rotated rectangle esimating the position, size, and orientation
            // of the object we want to track (specified by the initial region of interest).
            // We then take this estimation and draw a rotated bounding box.
            // This method will draw the rotated rectangle
            rotatedBoxToTrack = _outBox;

            // Draw a rotated rectangle representing Camshift's estimate of the
            // object's position, size, and orientation.
            _image.DrawPolyLine(rectangleBoxPoint(_outBox.BoxPoints()), true, CvColor.Red);

        }
        else
        {

            //Debug.Log ("Object lost by Camshift tracker");

            _image.DrawMarker(predictX, predictY, CvColor.Purple, MarkerStyle.CircleLine);

            _rectToTrack = CheckROIBounds(new CvRect(predictX - Mathf.FloorToInt(_rectToTrack.Width / 2),
                                           predictY - Mathf.FloorToInt(_rectToTrack.Height / 2),
                                        _rectToTrack.Width, _rectToTrack.Height));
            _image.DrawRect(_rectToTrack, CvColor.Purple);

        }

        if (trackWindowFlag)
            Cv.ShowImage("Image", _image);
    }