Accord.Vision.Detection.HaarObjectDetector.ProcessFrame C# (CSharp) Метод

        public Rectangle[] ProcessFrame(UnmanagedImage image)
        {
            int colorChannel =
              image.PixelFormat == PixelFormat.Format8bppIndexed ? 0 : channel;

            // Creates an integral image representation of the frame
            IntegralImage2 integralImage = IntegralImage2.FromBitmap(
                image, colorChannel, classifier.Cascade.HasTiltedFeatures);

            // Creates a new list of detected objects.
            this.detectedObjects.Clear();

            int width = integralImage.Width;
            int height = integralImage.Height;

            // Update parameters only if different size
            if (steps == null || width != lastWidth || height != lastHeight)
                update(width, height);


            Rectangle window = Rectangle.Empty;

            // For each scaling step
            for (int i = 0; i < steps.Length; i++)
            {
                float scaling = steps[i];

                // Set the classifier window scale
                classifier.Scale = scaling;

                // Get the scaled window size
                window.Width = (int)(baseWidth * scaling);
                window.Height = (int)(baseHeight * scaling);

                // Check if the window is lesser than the minimum size
                if (window.Width < minSize.Width || window.Height < minSize.Height)
                {
                    // If we are searching in greater to smaller mode,
                    if (scalingMode == ObjectDetectorScalingMode.GreaterToSmaller)
                    {
                        goto EXIT; // it won't get bigger, so we should stop.
                    }
                    else continue; // continue until it gets greater.
                }

                // Check if the window is greater than the maximum size
                else if (window.Width > maxSize.Width || window.Height > maxSize.Height)
                {
                    // If we are searching in greater to smaller mode,
                    if (scalingMode == ObjectDetectorScalingMode.GreaterToSmaller)
                    {
                        continue; // continue until it gets smaller.
                    }
                    else goto EXIT; // it won't get smaller, so we should stop.                    }
                }

                // Grab some scan loop parameters
                int xStep = window.Width >> 3;
                int yStep = window.Height >> 3;

                int xEnd = width - window.Width;
                int yEnd = height - window.Height;


                if (!parallel)  // Check if we should run in parallel
                {
                    // Sequential mode. Scan the integral image searching
                    // for objects in the window without parallelization.

                    // For every pixel in the window column
                    for (int y = 0; y < yEnd; y += yStep)
                    {
                        window.Y = y;

                        // For every pixel in the window row
                        for (int x = 0; x < xEnd; x += xStep)
                        {
                            window.X = x;

                            if (searchMode == ObjectDetectorSearchMode.NoOverlap && overlaps(window))
                                continue; // We have already detected something here, moving along.

                            // Try to detect an object inside the window
                            if (classifier.Compute(integralImage, window))
                            {
                                // object has been detected
                                detectedObjects.Add(window);

                                if (searchMode == ObjectDetectorSearchMode.Single)
                                    goto EXIT; // stop on first object found
                            }
                        }
                    }
                }

#if !NET35
                else // use parallel processing
                {
                    // Parallel mode. Scan the integral image searching
                    // for objects in the window with parallelization.
                    var bag = new System.Collections.Concurrent.ConcurrentBag<Rectangle>();

                    int numSteps = (int)Math.Ceiling((double)yEnd / yStep);

                    // For each pixel in the window column
                    Parallel.For(0, numSteps, (j, options) =>
                    {
                        int y = j * yStep;

                        // Create a local window reference
                        Rectangle localWindow = window;

                        localWindow.Y = y;

                        // For each pixel in the window row
                        for (int x = 0; x < xEnd; x += xStep)
                        {
                            if (options.ShouldExitCurrentIteration) return;

                            localWindow.X = x;

                            // Try to detect and object inside the window
                            if (classifier.Compute(integralImage, localWindow))
                            {
                                // an object has been detected
                                bag.Add(localWindow);

                                if (searchMode == ObjectDetectorSearchMode.Single)
                                    options.Stop();
                            }
                        }
                    });

                    // If required, avoid adding overlapping objects at
                    // the expense of extra computation. Otherwise, only
                    // add objects to the detected objects collection.
                    if (searchMode == ObjectDetectorSearchMode.NoOverlap)
                    {
                        foreach (Rectangle obj in bag)
                            if (!overlaps(obj)) detectedObjects.Add(obj);
                    }
                    else if (searchMode == ObjectDetectorSearchMode.Single)
                    {
                        if (bag.TryPeek(out window))
                        {
                            detectedObjects.Add(window);
                            goto EXIT;
                        }
                    }
                    else
                    {
                        foreach (Rectangle obj in bag)
                            detectedObjects.Add(obj);
                    }
                }
#endif
            }


        EXIT:

            Rectangle[] objects = detectedObjects.ToArray();

            if (searchMode == ObjectDetectorSearchMode.Average)
                objects = match.Group(objects);

            checkSteadiness(objects);
            lastObjects = objects;

            return objects; // Returns the array of detected objects.
        }

        public void MaxSizeTest()
        {
            HaarCascade cascade = new FaceHaarCascade();
            HaarObjectDetector target = new HaarObjectDetector(cascade,
                50, ObjectDetectorSearchMode.Default);

            Bitmap bmp = Properties.Resources.lena_color;
            Rectangle[] result;

            target.MaxSize = new Size(10, 60);
            result = target.ProcessFrame(bmp);
            Assert.AreEqual(0, result.Length);

            target.MaxSize = new Size(60, 60);
            result = target.ProcessFrame(bmp);
            Assert.AreEqual(1, result.Length);
            foreach (var r in result)
            {
                Assert.IsTrue(r.Width <= target.MaxSize.Width);
                Assert.IsTrue(r.Height <= target.MaxSize.Height);
            }

            target.MaxSize = new Size(80, 80);
            result = target.ProcessFrame(bmp);
            Assert.AreEqual(2, result.Length);
            foreach (var r in result)
            {
                Assert.IsTrue(r.Width <= target.MaxSize.Width);
                Assert.IsTrue(r.Height <= target.MaxSize.Height);
            }
        }