public static List <AnchorBox> GenerateRandomAnchorBoxes()
{
var anchorBoxList = new List <AnchorBox>()
{
new AnchorBox()
{
Height = 1, Width = 1, X = 0, Y = 0
}
};
foreach (int i in Enumerable.Range(0, 1000))
{
anchorBoxList.Add(AnchorBox.GenerateNew());
}
return(anchorBoxList);
}
private static List <System.Drawing.Rectangle> GetDetectionRectangles(INeuralNetwork neuralNetwork, Image <Bgr, Byte> originalImage, Action <double> progressUpdater)
{
List <System.Drawing.Rectangle> DetectedRectangles = new List <System.Drawing.Rectangle>();
var anchorBoxes = AnchorBox.GenerateRandomAnchorBoxes();
int counter = 0;
Parallel.ForEach(anchorBoxes, new ParallelOptions()
{
MaxDegreeOfParallelism = 10
}, (anchorBox) => {
(var croppedImage, var rectangle) = GetAreaUnderAnchorBox(originalImage, anchorBox);
var catDetected = DetectCat(neuralNetwork, croppedImage);
if (catDetected)
{
DetectedRectangles.Add(rectangle);
}
progressUpdater(((double)counter / (double)anchorBoxes.Count()) * 100);
counter++;
});
return(DetectedRectangles);
}
private static System.Drawing.Rectangle GetRectangleFromAnchroBox(Image <Bgr, Byte> originalImage, AnchorBox anchorBox)
{
int areaX = (int)((double)(originalImage.Width) * anchorBox.X);
int areaY = (int)((double)(originalImage.Height) * anchorBox.Y);
int areaWidth = (int)((double)(originalImage.Width) * anchorBox.Width);
int areaHeight = (int)((double)(originalImage.Height) * anchorBox.Height);
return(new System.Drawing.Rectangle(areaX, areaY, areaWidth, areaHeight));
}
private static (Image <Gray, Byte>, System.Drawing.Rectangle) GetAreaUnderAnchorBox(Image <Bgr, Byte> originalImage, AnchorBox anchorBox)
{
var originalImageCopy = originalImage.Copy();
var rectangle = GetRectangleFromAnchroBox(originalImageCopy, anchorBox);
originalImageCopy.ROI = rectangle;
var croppedImage = LocalImage.ConvertOriginalImageToGrayScaleAndProcess(originalImageCopy.Copy());
originalImageCopy.ROI = System.Drawing.Rectangle.Empty;
return(croppedImage, rectangle);
}